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haematologica Journal of the European Hematology Association Published by the Ferrata Storti Foundation

Editor-in-Chief Jan Cools (Leuven)

Deputy Editor Luca Malcovati (Pavia)

Managing Director Antonio Majocchi (Pavia)

Associate Editors Hélène Cavé (Paris), Ross Levine (New York), Claire Harrison (London), Pavan Reddy (Ann Arbor), Andreas Rosenwald (Wuerzburg), Juerg Schwaller (Basel), Monika Engelhardt (Freiburg), Wyndham Wilson (Bethesda), Paul Kyrle (Vienna), Paolo Ghia (Milan), Swee Lay Thein (Bethesda), Pieter Sonneveld (Rotterdam)

Assistant Editors Anne Freckleton (English Editor), Cristiana Pascutto (Statistical Consultant), Rachel Stenner (English Editor), Kate O’Donohoe (English Editor), Ziggy Kennell (English Editor)

Editorial Board Omar I. Abdel-Wahab (New York); Jeremy Abramson (Boston); Paolo Arosio (Brescia); Raphael Bejar (San Diego); Erik Berntorp (Malmö); Dominique Bonnet (London); Jean-Pierre Bourquin (Zurich); Suzanne Cannegieter (Leiden); Francisco Cervantes (Barcelona); Nicholas Chiorazzi (Manhasset); Oliver Cornely (Köln); Michel Delforge (Leuven); Ruud Delwel (Rotterdam); Meletios A. Dimopoulos (Athens); Inderjeet Dokal (London); Hervé Dombret (Paris); Peter Dreger (Hamburg); Martin Dreyling (München); Kieron Dunleavy (Bethesda); Dimitar Efremov (Rome); Sabine Eichinger (Vienna); Jean Feuillard (Limoges); Carlo Gambacorti-Passerini (Monza); Guillermo Garcia Manero (Houston); Christian Geisler (Copenhagen); Piero Giordano (Leiden); Christian Gisselbrecht (Paris); Andreas Greinacher (Greifswals); Hildegard Greinix (Vienna); Paolo Gresele (Perugia); Thomas M. Habermann (Rochester); Claudia Haferlach (München); Oliver Hantschel (Lausanne); Christine Harrison (Southampton); Brian Huntly (Cambridge); Ulrich Jaeger (Vienna); Elaine Jaffe (Bethesda); Arnon Kater (Amsterdam); Gregory Kato (Pittsburg); Christoph Klein (Munich); Steven Knapper (Cardiff); Seiji Kojima (Nagoya); John Koreth (Boston); Robert Kralovics (Vienna); Ralf Küppers (Essen); Ola Landgren (New York); Peter Lenting (Le Kremlin-Bicetre); Per Ljungman (Stockholm); Francesco Lo Coco (Rome); Henk M. Lokhorst (Utrecht); John Mascarenhas (New York); Maria-Victoria Mateos (Salamanca); Simon Mendez-Ferrer (Madrid); Giampaolo Merlini (Pavia); Anna Rita Migliaccio (New York); Mohamad Mohty (Nantes); Martina Muckenthaler (Heidelberg); Ann Mullally (Boston); Stephen Mulligan (Sydney); German Ott (Stuttgart); Jakob Passweg (Basel); Melanie Percy (Ireland); Rob Pieters (Utrecht); Stefano Pileri (Milan); Miguel Piris (Madrid); Andreas Reiter (Mannheim); Jose-Maria Ribera (Barcelona); Stefano Rivella (New York); Francesco Rodeghiero (Vicenza); Richard Rosenquist (Uppsala); Simon Rule (Plymouth); Claudia Scholl (Heidelberg); Martin Schrappe (Kiel); Radek C. Skoda (Basel); Gérard Socié (Paris); Kostas Stamatopoulos (Thessaloniki); David P. Steensma (Rochester); Martin H. Steinberg (Boston); Ali Taher (Beirut); Evangelos Terpos (Athens); Takanori Teshima (Sapporo); Pieter Van Vlierberghe (Gent); Alessandro M. Vannucchi (Firenze); George Vassiliou (Cambridge); Edo Vellenga (Groningen); Umberto Vitolo (Torino); Guenter Weiss (Innsbruck).

Editorial Office Simona Giri (Production & Marketing Manager), Lorella Ripari (Peer Review Manager), Paola Cariati (Senior Graphic Designer), Igor Ebuli Poletti (Senior Graphic Designer), Marta Fossati (Peer Review), Diana Serena Ravera (Peer Review)

Affiliated Scientific Societies SIE (Italian Society of Hematology, www.siematologia.it) SIES (Italian Society of Experimental Hematology, www.siesonline.it)


haematologica Journal of the European Hematology Association Published by the Ferrata Storti Foundation

Information for readers, authors and subscribers Haematologica (print edition, pISSN 0390-6078, eISSN 1592-8721) publishes peer-reviewed papers on all areas of experimental and clinical hematology. The journal is owned by a non-profit organization, the Ferrata Storti Foundation, and serves the scientific community following the recommendations of the World Association of Medical Editors (www.wame.org) and the International Committee of Medical Journal Editors (www.icmje.org). Haematologica publishes editorials, research articles, review articles, guideline articles and letters. Manuscripts should be prepared according to our guidelines (www.haematologica.org/information-for-authors), and the Uniform Requirements for Manuscripts Submitted to Biomedical Journals, prepared by the International Committee of Medical Journal Editors (www.icmje.org). Manuscripts should be submitted online at http://www.haematologica.org/. Conflict of interests. According to the International Committee of Medical Journal Editors (http://www.icmje.org/#conflicts), “Public trust in the peer review process and the credibility of published articles depend in part on how well conflict of interest is handled during writing, peer review, and editorial decision making”. The ad hoc journal’s policy is reported in detail online (www.haematologica.org/content/policies). Transfer of Copyright and Permission to Reproduce Parts of Published Papers. Authors will grant copyright of their articles to the Ferrata Storti Foundation. No formal permission will be required to reproduce parts (tables or illustrations) of published papers, provided the source is quoted appropriately and reproduction has no commercial intent. Reproductions with commercial intent will require written permission and payment of royalties. Detailed information about subscriptions is available online at www.haematologica.org. Haematologica is an open access journal. Access to the online journal is free. Use of the Haematologica App (available on the App Store and on Google Play) is free. For subscriptions to the printed issue of the journal, please contact: Haematologica Office, via Giuseppe Belli 4, 27100 Pavia, Italy (phone +39.0382.27129, fax +39.0382.394705, E-mail: info@haematologica.org). Rates of the International edition for the year 2017 are as following: Print edition

Institutional Euro 500

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Advertisements. Contact the Advertising Manager, Haematologica Office, via Giuseppe Belli 4, 27100 Pavia, Italy (phone +39.0382.27129, fax +39.0382.394705, e-mail: marketing@haematologica.org). Disclaimer. Whilst every effort is made by the publishers and the editorial board to see that no inaccurate or misleading data, opinion or statement appears in this journal, they wish to make it clear that the data and opinions appearing in the articles or advertisements herein are the responsibility of the contributor or advisor concerned. Accordingly, the publisher, the editorial board and their respective employees, officers and agents accept no liability whatsoever for the consequences of any inaccurate or misleading data, opinion or statement. Whilst all due care is taken to ensure that drug doses and other quantities are presented accurately, readers are advised that new methods and techniques involving drug usage, and described within this journal, should only be followed in conjunction with the drug manufacturer’s own published literature. Direttore responsabile: Prof. Edoardo Ascari; Autorizzazione del Tribunale di Pavia n. 63 del 5 marzo 1955. Printing: Tipografia PI-ME, via Vigentina 136, Pavia, Italy. Printed in December 2016.


haematologica calendar of events

Journal of the European Hematology Association Published by the Ferrata Storti Foundation

EHA Scientific Meeting on Anemias Diagnosis and Treatment in the Omics Era Chair: A Iolascon February 2-4, 2017 Barcelona, Spain

EuroClonality Workshop: “Clonality assessment in Pathology” European Scientific foundation for Laboratory Hemato Oncology (ESLHO) Chairs: P Groenen, J van Krieken, A Langerak February 13-15, 2016 Nijmegen, The Netherlands

EHA Hematology Tutorial on Lymphoid malignancies, Multiple myeloma and Bone Marrow Failure Chairs: R Foà , K Wickramaratne February 23-24, 2017 Colombo, Sri Lanka

EHA Hematology Tutorial on Lymphoid Malignancies Chairs: R Foà, I Hus, T Robak March 17-18, 2017 Warsaw, Poland

EHA Scientific Meeting on Advances in Biology and Treatment of B Cell Malignancies with a Focus on Rare Lymphoma Subtypes Chairs: M Kersten and M Dreyling March 10-12, 2017 Barcelona, Spain

EHA Scientific Meeting on Aging and Hematology Chair: D Bron May 4-6, 2017 Location: TBC

22nd Congress of the European Hematology Association European Hematology Association June 22 - 25, 2017 Madrid, Spain

EHA Scientific Meeting on Challenges in the Diagnosis and Management of Myeloproliferative Neoplasms Chairs: J Kiladjian and C Harrison October 12-14, 2017 Location: TBC

EHA Scientific Meeting on Shaping the Future of Mesenchymal Stromal Cells Therapy Chair: W Fibbe November 23-25, 2017 Location: TBC

Calendar of Events updated on December 5, 2016


haematologica Journal of the European Hematology Association Published by the Ferrata Storti Foundation

Table of Contents Volume 102, Issue 1: January 2017 Cover Figure JAK2 and CALR mutant proteins in myeloproliferative neoplasms - image accompanying the review article on page 7 (Image created by www.somersault1824.com)

Editorials 1

Circulating microRNAs: promising biomarkers in aplastic anemia Jonathan B. Bell et al.

2

Risk stratification in myelofibrosis: the quest for simplification Laura C. Michaelis

4

How “precise” is precision medicine in hematology? Carlo Gambacorti-Passerini and Rocco Piazza

Review Articles 7

Leaders in Hematology - Mechanisms in Hematology Molecular determinants of pathogenesis and clinical phenotype in myeloproliferative neoplasms Jacob Grinfeld, Jyoti Nangalia and Anthony R. Green et al.

18

Leaders in Hematology - Management in Hematology From leeches to personalized medicine: evolving concepts in the management of polycythemia vera Alessandro M. Vannucchi

30

The emerging role of immune checkpoint inhibition in malignant lymphoma Ida Hude et al.

Guideline Article 43

Guideline for the diagnosis, treatment and response criteria for Bing-Neel syndrome Monique C. Minnema et al.

Articles Blood Transfusion

52

Treatments for hematologic malignancies in contrast to those for solid cancers are associated with reduced red cell alloimmunization Dorothea Evers et al.

Iron Metabolism & Its Disorders

60

Erythroferrone contributes to hepcidin repression in a mouse model of malarial anemia Chloé Latour et al.

Haematologica 2017; vol. 102 no. 1 - January 2017 http://www.haematologica.org/


haematologica Journal of the European Hematology Association Published by the Ferrata Storti Foundation Bone Marrow Failure

69

A plasma microRNA signature as a biomarker for acquired aplastic anemia Kohei Hosokawa et al.

Myeloproliferative Disorders

79

An accurate, simple prognostic model consisting of age, JAK2, CALR, and MPL mutation status for patients with primary myelofibrosis Uri Rozovski et al.

85

Associations between gender, disease features and symptom burden in patients with myeloproliferative neoplasms: an analysis by the MPN QOL International Working Group Holly L. Geyer et al.

94

A phase 1/2, open-label study evaluating twice-daily administration of momelotinib in myelofibrosis Vikas Gupta et al.

103

Risk of thrombosis according to need of phlebotomies in patients with polycythemia vera treated with hydroxyurea Alberto Alvarez-Larrán et al.

Acute Myeloid Leukemia

110

Pre-transplantation minimal residual disease with cytogenetic and molecular diagnostic features improves risk stratification in acute myeloid leukemia Betül Oran et al.

Acute Lymphoblastic Leukemia

118

ZNF384-related fusion genes consist of a subgroup with a characteristic immunophenotype in childhood B-cell precursor acute lymphoblastic leukemia Shinsuke Hirabayashi et al.

130

Adults with Philadelphia chromosome–like acute lymphoblastic leukemia frequently have IGH-CRLF2 and JAK2 mutations, persistence of minimal residual disease and poor prognosis Tobias Herold et al.

139

Improving results of allogeneic hematopoietic cell transplantation for adults with acute lymphoblastic leukemia in first complete remission: an analysis from the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation Sebastian Giebel et al.

Non-Hodgkin Lymphoma

150

Mediastinal gray zone lymphoma: clinico-pathological characteristics and outcomes of 99 patients from the Lymphoma Study Association Clémentine Sarkozy et al.

Pasma Cell Disorders

160

High-dose therapy and autologous stem cell transplantation in patients with POEMS syndrome: a retrospective study of the Plasma Cell Disorder sub-committee of the Chronic Malignancy Working Party of the European Society for Blood & Marrow Transplantation Gordon Cook et al.

168

Synergistic DNA-damaging effect in multiple myeloma with the combination of zalypsis, bortezomib and dexamethasone Ana-Alicia López-Iglesias et al.

Cell Therapy & Immunotherapy

176

The increase of the global donor inventory is of limited benefit to patients of non-Northwestern European descent Suzanna M. van Walraven et al.

184

Sequential regimen of clofarabine, cytosine arabinoside and reduced-intensity conditioned transplantation for primary refractory acute myeloid leukemia Mohamad Mohty et al.

Haematologica 2017; vol. 102 no. 1 - January 2017 http://www.haematologica.org/


haematologica Journal of the European Hematology Association Published by the Ferrata Storti Foundation

Immunodeficiency

176

The immunophenotypic fingerprint of patients with primary antibody deficiencies is partially present in their asymptomatic first-degree relatives Delfien J.A. Bogaert et al.

Letters to the Editor Letters are available online only at www.haematologica.org/content/102/1.toc

e1

APOL1, a-thalassemia, and BCL11A variants as a genetic risk profile for progression of chronic kidney disease in sickle cell anemia Santosh L. Saraf et al. http://www.haematologica.org/content/102/1/e1

e7

Myelodysplastic syndrome can propagate from the multipotent progenitor compartment Kevin Rouault-Pierre et al. http://www.haematologica.org/content/102/1/e7

e11

Genomic analysis of myeloproliferative neoplasms in chronic and acute phases Frédéric Courtier et al. http://www.haematologica.org/content/102/1/e11

e15

Absence of CALR mutations in JAK2-negative polycythemia Aurélie Chauveau et al. http://www.haematologica.org/content/102/1/e15

e17

CK2 inhibitor CX-4945 destabilizes NOTCH1 and synergizes with JQ1 against human T-acute lymphoblastic leukemic cells Haiwei Lian et al. http://www.haematologica.org/content/102/1/e17

e22

Renal insufficiency is an independent prognostic factor in patients with chronic lymphocytic leukemia Paolo Strati et al. http://www.haematologica.org/content/102/1/e22

e26

Impaired pulmonary endothelial barrier function in sickle cell mice Nagavedi S. Umapathy et al. http://www.haematologica.org/content/102/1/e26

Comments Comments are available online only at www.haematologica.org/content/102/1.toc

e30

Gene panel sequencing in idiopathic erythrocytosis François Girodon and Veronika Némethová http://www.haematologica.org/content/102/1/e30

e31

Gene expression patterns as predictive biomarkers in hematology-oncology: principal hurdles on the road to the clinic Filip Rázga and Veronika Némethová http://www.haematologica.org/content/102/1/e31

Haematologica 2017; vol. 102 no. 1 - January 2017 http://www.haematologica.org/


EDITORIALS Circulating microRNAs: promising biomarkers in aplastic anemia Jonathan B. Bell,1 Sameem Abedin1 and Leonidas C. Platanias1,2 1

Robert H. Lurie Comprehensive Cancer Center and Division of Hematology/Oncology, Feinberg School of Medicine, Northwestern University, IL and 2Department of Medicine, Jesse Brown VA Medical Center, Chicago, IL, USA. E-mail: l-platanias@northwestern.edu doi:10.3324/haematol.2016.156117

M

icroRNAs (miRNAs) are short non-coding RNAs that play key regulatory roles in gene expression through complementary binding to the 3’-untranslated regions (3’-UTRs) of target mRNAs, leading to subsequent translational repression.1 Since miRNAs were first identified in 1993, there has been continuous growing interest in better understanding the roles of these molecules in the regulation of both normal cell function as well as numerous disease processes.2 Furthermore, miRNAs released into the circulation after cell death, or in extracellular vesicles, have been identified in a number of different diseases.3,4 These circulating miRNAs can be measured in the blood, and represent promising new biomarkers for both the diagnosis of disease and the assessment of treatment responses. Acquired aplastic anemia represents a significant clinical problem and it is of unclear etiology in the majority of cases. There has been extensive evidence for T cell-mediated bone marrow destruction, leading to a characteristic clinical presentation with hypocellular bone marrow and pancytopenia on blood work.5 In line with this, upfront immunosuppressive therapy (IST) consisting of horse antithymocyte globulin (ATG) and cyclosporine (CsA) has significant activity and is the standard of care. Bone marrow transplantation represents an additional approach and has specific indications for some groups of aplastic anemia patients, however, even with a HLA-matched sibling donor (MSD), transplant related mortality, including the risk of graft-versus-host disease, exists.6 Further, in individuals lacking a MSD, unrelated donor transplantation carries an even greater risk of graft-versus-host disease; alternatively, haploidentical donor transplantation remains experimental for this condition.7 While upfront treatment with IST is the standard of care for aplastic anemia, predicting responses to immunosuppression is difficult. Response rates for IST are estimated at about 70%, with refractory aplastic anemia patients requiring additional rounds of IST or consideration for bone marrow transplantation.8,9 As such, biomarkers to monitor responses to IST throughout treatment have the potential to change clinical decision making and improve outcomes in aplastic anemia. Although several biomarkers to monitor responses in aplastic anemia have been proposed, these biomarkers are largely non-specific (e.g., age, blood counts), and molecular biomarkers represent a more sophisticated approach for follow-up in these patients.10 In the current issue of the journal, Hosokawa and colleagues build upon their previous research to establish circulating miRNAs as potential biomarkers in aplastic anemia.11 The authors used an unbiased PCR-based panel to identify miRNAs differentially regulated in patients with severe aplastic anemia as compared to patients with myelodysplastic syndrome or healthy volunteer controls. Of note, none of these patients had received IST prior to sample collection. After identifying 19 dysregulated miRNAs in a discovery set of 179 miRNAs, the authors further validated their findings in 108 haematologica | 2017; 102(1)

patients, and identified three miRNAs dysregulated with at least a 1.5-fold change. Interestingly, the two miRNAs upregulated in the aplastic anemia group (miR-150-5p and miR146b-5p) have previously described roles in T cell development and regulation of innate immunity, while the role of the one miRNA downregulated in the aplastic anemia group (miR-1) may play a part in autoimmunity.12-14 Perhaps the most interesting finding of Hosokawa and colleagues is the identification of miR-150-5p as a marker for treatment responses to immunosuppression in aplastic anemia. The authors analyzed 40 aplastic anemia patients before and after 6 months of IST, and identified statistically significant decreases in miR-150-5p and miR-146b-5p, and a statistically significant increase in miR-1. These findings mirror the authors’ other findings comparing the levels of these miRNAs in aplastic anemia patients and healthy controls. When the authors specifically compared the effect of IST on these miRNAs in responders and non-responders, miR-150-5p demonstrated a significant decrease only in responders. Surprisingly, miR-1 demonstrated a significant increase after IST regardless of whether or not the patients responded to the treatment. These findings suggest that some miRNAs differentially expressed in aplastic anemia can be used to monitor treatment response, while others cannot. The results of the work of Hosokawa and colleagues are interesting and potentially important. Prospective studies will be required to further validate whether miR-150-5p monitoring can identify responders from non-responders to IST. Future efforts should also focus on determining the earliest time point when meaningful changes can be observed. Clinically, early identification of potential IST non-responders could conceivably trigger an earlier consideration for bone marrow transplantation. Conversely, identifying potential IST responders prior to hematologic recovery may serve a purpose in selecting so-called “late responders”, for whom hematologic recovery can take up to 6 months to observe. Beyond having important clinical implications, this report also advances our understanding of the mechanisms of immune-mediated failure. The role of miRNAs in the pathophysiology of aplastic anemia and other bone marrow failure syndromes has been generally unclear. By providing evidence that miRNAs can be used to distinguish aplastic anemia from healthy patient controls, the work of the authors suggests the involvement of miR-150-5p in the immune-mediated failure. However, further research into the relevant targets of this, and other miRNAs, is needed. The authors provide some insight into this through pathway analysis, which identifies potential immune-related targets of these miRNAs. These targets will need to be validated in future studies using molecular biology techniques classically used to study miRNA biology. In summary, Hosokawa and colleagues suggest a promising new approach to monitor response to immunosuppression in aplastic anemia, an autoimmune regulated disease that lacks 1


Editorials

useful biomarkers. Future studies will need to uncover the underlying mechanisms driving the observed changes in circulating relevant miRNAs in the disease, and how immunosuppression modulates such levels.

7.

References

9.

1. Yates LA, Norbury CJ, Gilbert RJ. The long and short of microRNA. Cell. 2013;153(3):516-519. 2. Lee RC, Feinbaum RL, Ambros V. The C. elegans heterochronic gene lin4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843-854. 3. Wagschal A, Najafi-Shoushtari SH, Wang L, et al. Genome-wide identification of microRNAs regulating cholesterol and triglyceride homeostasis. Nat Med. 2015;21(11):1290-1297. 4. Seyhan AA, Nunez Lopez YO, Xie H, et al. Pancreas-enriched miRNAs are altered in the circulation of subjects with diabetes: a pilot cross-sectional study. Sci Rep. 2016;6:31479. 5. Young NS, Calado RT, Scheinberg P. Current concepts in the pathophysiology and treatment of aplastic anemia. Blood. 2006;108(8):2509-2519. 6. Bacigalupo A, Giammarco S, Sica S. Bone marrow transplantation versus

8.

10. 11. 12. 13. 14.

immunosuppressive therapy in patients with acquired severe aplastic anemia. Int J Haematol. 2016;104(2):168-174. Bacigalupo A, Socie G, Hamladji RM, et al. Current outcome of HLA identical sibling versus unrelated donor transplants in severe aplastic anemia: an EBMT analysis. Haematologica. 2015;100(5):696-702. Killick SB, Bown N, Cavenagh J, et al. Guidelines for the diagnosis and management of adult aplastic anaemia. Brit J Haematol. 2016;172(2):187207. Marsh JC, Kulasekararaj AG. Management of the refractory aplastic anemia patient: what are the options? Blood. 2013;122(22):3561-3567 Narita A, Kojima S. Biomarkers for predicting clinical response to immunosuppressive therapy in aplastic anemia. Int J Haematol. 2016;104(2):153-158. Hosokawa K, Kajigaya S, Feng X, et al. A plasma microRNA signature as a biomarker for acquired aplastic anemia. Haematologica. 2017;102 (1):69-78. Kroesen BJ, Teteloshvili N, Smigielska-Czepiel K, et al. Immuno-miRs: critical regulators of T-cell development, function and ageing. Immunology. 2015;144(1):1-10. Takyar S, Vasavada H, Zhang JG, et al. VEGF controls lung Th2 inflammation via the miR-1-Mpl (myeloproliferative leukemia virus oncogene)P-selectin axis. J Exp Med. 2013;210(10):1993-2010. O'Neill LA, Sheedy FJ, McCoy CE. MicroRNAs: the fine-tuners of Tolllike receptor signalling. Nat Rev Immunol. 2011;11(3):163-175.

Risk stratification in myelofibrosis: the quest for simplification Laura C. Michaelis Department of Medicine, Division of Hematology/Oncology, Medical College of Wisconsin, Froedtert Medical Center, 9200 W Wisconsin Ave, Milwaukee, WI, USA E-mail: lmichaelis@mcw.edu

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doi:10.3324/haematol.2016.158865

isk-stratification systems in hematologic malignancies can serve a myriad of clinical and research purposes. They facilitate rational bedside discussion regarding the likely trajectory of a disease, provide an objective screen to ensure clinical trial enrollment reproducibility, and help guide decision-making with regard to risky interventions. The ideal prognostic model would be that derived from the experience of patients very similar to those who are seen in your clinic; thus, generalizable. It would utilize data that you have at hand, or at least can easily and accurately obtain, and it would reliably predict the future clinical course of your patient’s health condition, providing greater precision when discussing sometimes highly heterogeneous diseases. Myeloproliferative neoplasms (MPNs) are a group of malignant conditions known for such heterogeneity. For essential thrombocythemia and polycythemia vera, two of the lower-risk subtypes of MPNs, risk-stratification models have always been remarkably simple – perhaps due to the limited number of therapeutic interventions employed. A thorough patient history, complete blood count, and, in the case of essential thrombocythemia, knowledge of the JAK2V617F mutation status, allow the physician to sort patients into standard and high-risk categories, and assign therapy accordingly. However, in primary myelofibrosis (PMF), a disease where survival can range from months to over a decade, there has been continuous re-evaluation of the prognostic models used. Initially, those utilized in myelodysplastic syndrome, such as the International Prognostic Scoring 2

System (IPSS), were opted for. In the last few years, two PMF-specific models have become the standard of care: dynamic IPSS (DIPSS), and DIPSS-plus. Each of these works with relatively easy to obtain inputs including age, blood count, symptoms, peripheral blood blast percentage, transfusion history, and karyotype. Typically, clinicians use the system that best fits the situation at hand – for example, if one were discussing transplantation with a younger than average patient, one might calculate the DIPSS score since the retrospective results published by Nicolaus Kröger et al., comparing transplant to non-transplant outcomes, were stratified using that same score.1 For a patient under consideration for Ruxolitinib therapy, one might use the IPSS score since it was the model chosen for eligibility in the pivotal registration studies for this agent.2,3 Since 2005, when a mutation in the JAKV617F gene was first identified as a seminal pathologic event in polycythemia vera, an increasing number of somatic mutations have been described in association with PMF. In general, JAK2, CALR and MPL are considered driver mutations, though there are elegant studies examining how acquisition order dictates phenotypic destiny.4 Additional somatic mutations found in the disease include LNK, CBL, TET2, ASXL1, IDH1/2, IKZF1, EZH2, DNMT3A, TP53, SF3B1, SRSF2, and U2AF1, a list that is likely not exhaustive. While we await additional research on the mechanistic consequences of these aberrations, retrospective studies are already looking into the prognostic importance of mutations, or groups of mutations, in patients. How these molecular mutations should be integrated into pre-existing scores, such as the DIPSS, remains a significant conundrum haematologica | 2017; 102(1)


Editorials

for both the practitioner and their patients. Two stratification systems, the Mutation-Enhanced International Prognostic Scoring System (MIPSS)5 and the GeneticsBased Prognostic Scoring System (GPSS),6 have been presented; however, they are not yet the standard of care. In this issue of Haematologica, a group of researchers from the MD Anderson Cancer Center put forth a model for prognosis in primary myelofibrosis that attempts to cut through some of the noise.7 They have provided a simple model, based on a large number of patients, which uses relatively easy to obtain, objective and reproducible data. It incorporates quantitation of the JAK2 allele burden, but does not require patients to undergo next generation sequencing – a test which has highly variable reimbursement patterns and is financially out of reach for many patients. Indeed, the only features needed to classify patients are age, JAK2 allele burden (dichotomized at 50%), and CALR and MPL status. Their model is based on 13 years’ worth of patient data; 344 individuals were included in the analysis, ranging in age from 26-86 years. The researchers were able to establish two patient profiles: one with high-risk mutation status, the other with low-risk mutation status. Notably, this was possible by testing the presence or absence of MPL and CALR, but they needed to quantify the allele burden of the JAKV617F mutation. Whilst the presence of higher V617F allele burden describes a more dangerous phenotype in polycythemia vera, the opposite is true in myelofibrosis, where a low allele burden has been associated with reduced survival.8 In addition, in myelofibrosis, patients with a higher JAK2617F allele burden are more likely to achieve clinical benefit when treated with Ruxolitinib therapy.9 Therefore, combining age, presence of MPL or CALR, and JAK2V617F allele burden, researchers established a highly discriminant scale that could separate patients into four categories of median overall survival – ranging from 35 to 126 months. Will we adopt this new system for clinical use? Perhaps eventually. Firstly, however, it needs to be validated in a large, independent patient population. Secondly, clinicians and third-party payers need to acknowledge that baseline calculation of the JAK2V617F allele burden is of significant clinical relevance to patients with this devastating disease – data such as that presented here makes a compelling argument. Should the above happen, the prognostic scale proposed by Dr. Rozovski et al. has great clinical potential; most notably in that it is highly objective. One of the downfalls of the DIPSS is the categorization of “constitutional symptoms,” which can be subjective, depending on the evalua-

haematologica | 2017; 102(1)

tor. With this system, the clinician can avoid having to sort out whether fatigue or some other “not quite severe enough symptom” merits a point on the DIPSS scale. Secondly, it is transportable; a patient seen at one institution will have the same risk features when referred to a tertiary care center for a transplant consultation. Finally, this analysis most likely includes patients who were treated with Ruxolitinib. As such, this data becomes more generalizable to the contemporary patient, where Ruxolitinib or an investigational equivalent is administered. Of course, there is still much to learn: Does risk, with this scale, change over time? How might somatic mutations like TP53 or ASXL1 be integrated? Can we use this data to assess timing of allogeneic stem-cell transplantation? How do we weigh findings like ascites, splenomegaly or a progressive failure to thrive – findings that portend, in clinical judgement and experience, worse outcomes? Such findings are poorly captured in charts, and are therefore difficult to integrate into scales that are derived from retrospective data, such as this one. As our clinical community struggles to advance the field, prognostic scales like the one proposed here can provide uniformity, reproducibility and clinical precision for our patient encounters and future research. They represent an important tool for patient care and management. Kudos for reaching toward the ideal.

References 1. Kroger N, Giorgino T, Scott BL, et al. Impact of allogeneic stem cell transplantation on survival of patients less than 65 years of age with primary myelofibrosis. Blood. 2015;125(21):3347-3350; quiz 64. 2. Verstovsek S, Mesa RA, Gotlib J, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. 2012;366(9):799-807. 3. Harrison C, Kiladjian JJ, Al-Ali HK, et al. JAK inhibition with ruxolitinib versus best available therapy for myelofibrosis. N Engl J Med. 2012;366(9):787-798. 4. Ortmann CA, Kent DG, Nangalia J, et al. Effect of mutation order on myeloproliferative neoplasms. N Engl J Med. 2015;372(7):601-612. 5. Vannucchi AM, Guglielmelli P, Rotunno G, et al. Mutation-enhanced international prognostic scoring system (MIPSS) for primary myelofibrosis: An AGIMM & IWG-MRT Project. Blood. 2014;124(21):405. 6. Tefferi A, Guglielmelli P, Finke C, et al. Integration of mutations and karyotype towards a genetics-based prognostic scoring system (GPSS) for primary myelofibrosis. Blood. 2014;124(21):406. 7. Rozovski U, Verstovsek S, Manshouri T, et al. An accurate, simple prognostic model consisting of age, JAK2, CALR, and MPL mutation status for patients with primary myelofibrosis. Haematologica. 2017;102(1):7984. 8. Vannucchi AM, Pieri L, Guglielmelli P. JAK2 Allele burden in the myeloproliferative neoplasms: effects on phenotype, prognosis and change with treatment. Ther Adv Hematol. 2011;2(1):21-32. 9. Barosi G, Klersy C, Villani L, et al. JAK2(V617F) allele burden 50% is associated with response to ruxolitinib in persons with MPN-associated myelofibrosis and splenomegaly requiring therapy. Leukemia. 2016;30(8):1772-1775.

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Editorials

How “precise” is precision medicine in hematology? Carlo Gambacorti-Passerini and Rocco Piazza Hematology,School of Medicine and Surgery, University of Milano Bicocca, via Cadore 48, Monza, Italy E-mail: carlo.gambacorti@unimib.it or rocco.piazza@unimib.it

M

assive parallel sequencing, the foundation of next generation sequencing (NGS), allows us to sequence the entire exome (the coding sequences of the genome) of leukemia or lymphoma cells, and can be combined with RNA-Seq to evaluate the transcriptome. Using these techniques, one can search for mutations, indels, gene fusions, copy number alterations, alternative splicing, and gene expression profiles from a blood sample from a person with leukemia. Importantly, these analyses can be performed in just a few days and at modest cost. Given these advances, we might expect data from NGS to be quickly integrated into therapy decisions to effect so-called precision or personalized medicine.1,2 In fact, cancer treatment was envisioned as one of the most promising applications of PM. In particular, haematological neoplasias, and especially leukemias, were seen as the most direct candidates, given the accessibility of neoplastic cells. Interestingly, and surprisingly, this is not yet widely used, although it continues to generate interest and debates.3 In contrast, our current situation is similar to having many or most pieces of a puzzle, but limited ability to put them in the right place to complete the picture. Several important limitations and challenges associated with using these data to precisely treat persons with leukemia or lymphoma have emerged and are summarized below along with possible solutions. We do not deal here with germline mutations; only with those somatic.

Distinguishing the wheat from the chaff Many mutations identified by NGS are present before a cell is transformed and are unrelated to leukemia development. These mutations are termed passenger mutations. Passenger mutations are distinguished from driver mutations which cause leukemia transformation. Passenger mutations increase over time and are more frequent in older persons.4,5 They are also present in persons without leukemia or any blood disorder.6 One way to distinguish passenger from driver mutations is to consider drivers as only those recurrently identified in a substantial proportion of persons with leukemia or clonal hematopoiesis,7,8 and not age-adjusted normals. However, this approach risks ignoring infrequent mutations (black holes), which may be important in a specific person’s leukemia. In an attempt to identify mutations which may be drivers, we developed OncoScore (revised version submitted for publication in Scientific Reports; available as Bioconductor software at: https://bioconductor.org/packages/release/bioc/html/OncoScore.ht ml and as a web tool at: http://www.galseq.com/oncoscore.html). OncoScore is dynamic software which tracks medical literature in real time, and suggests a numerical score of the probability a mutation is a driver mutation. We tested the possible clinical value of OncoScore in a cohort of 23 persons with Chronic Myeloid Leukemia at diagnosis and found it was better correlated with sustained response to 4

doi:10.3324/haematol.2016.155267

tyrosine kinase-inhibitors than the total number of mutations or Sokal score.9 Further work and analysis will be needed to ascertain the real value of this software. If the impact of a specific mutation on transformation is unknown, it is also possible to try to predict its impact on the encoded protein function with software such as PolyPhen, DAVID or PROVEAN.10-13 These software tools help to indicate whether the observed mutation is likely to cause perturbation in the protein function. Alternatively, animal models could be used to characterize the functional significance of a particular mutation; however, these models require a substantial amount of time, and thus are frequently incompatible with the dynamics and time frames allowed in clinical medicine. All these tools are imperfect and require improvement and complementation with additional decision making instruments. However, they represent a first step in the direction of differentiating driver and passenger mutations.

Determining mutation hierarchy Once mutations in a persons’ leukemia cells are identified, we must then add a further dimension: the temporal order in which mutations are acquired. Data from diseases such as MPN-associated myelofibrosis indicated different sequences of mutation acquisition results in different phenotypes despite a similar genotype.14 Reconstruction of the order of acquiring mutations is also important in other settings. Some leukemias first acquire important driver mutations (e.g., BCR/ABL1, NPM/ALK, PML/RARalpha) with substantial tranforming ability such that additional mutations are dispensable. In other diseases, such as myelodysplastic syndrome (MDS), the first mutations are only weakly transforming, and additional genetic alterations are needed for the fully transformed phenotype. Targeting the earliest driver mutation(s) holds the greatest therapeutic promise when they carry a relevant transforming potential.15,16 In this setting (CML, APL, ALK+ lymphomas), PM can change disease prognosis.17 Alternatively, therapies targeting several different driver mutations are a potential therapeutic strategy when the transforming potential of the initial mutation is low. Here, the available evidence for a benefit to patients is more limited, although some promising data are emerging.18 Knowing the mutation hierarchy could also reveal why the same type of mutation, such as ALK containing fusion genes, have different therapeutic implications in different cancers; in lymphoma versus lung cancer, for example, the same drug (crizotinib) obtains quite different therapeutic responses. Hierarchical variant reconstruction is possible but requires sequencing many individual leukemia colonies or sequential studies. In addition, this is presently feasible for myeloid neoplasms, but less so for other cancers. Alternative strategies such as single cell exome/RNASeq analysis are being developed to facilitate reconstruction of clonal hierarchy and to eliminate the need to haematologica | 2017; 102(1)


Editorials

sequence colonies arising from single cells. Statistical methods to infer the order of acquisition of multiple mutations in a cancer were recently suggested by Papaemmanuil et al.19 and Caravagna et al.20 These methods are important as they show that cancer progression follows a defined trajectory, not a random pattern. However they are valid for groups of patients, but cannot assess the order of development of mutations inside a single leukemia.14 All these considerations are valid when the therapeutic strategy is “functional” targeting, e.g., blocking the enzymatic activity of the product of a mutated gene such as a tyrosine kinase. Paradoxically, passenger mutations could represent ideal targets for immune therapy since they are present in all cancer cells, before the driver mutation.21

is probably clinically the most feasible one, and will allow physicians to familiarize themselves with the complexities of NGS without being overwhelmed by a mass of omics data. However, in the near future, complete unbiased NGS will, in our opinion, predominate. This evolution may result from improvements in sequencing technology and reduced cost, thus solving, for example, the black holes problem. New, user-friendly bioinformatics tools are likely to be developed, and physicians and researchers will become more familiar with them; new communication skills will also be needed to convey this complex information to patients and their families. Importantly, new clinical trial designs are needed to test the clinical relevance of data from NGS (see below).

A new type of clinical trial is needed Signal transduction pathways An ideal initial driver mutation is one which carries most of the leukemogenic activity and which can be directly targeted. BCR/ABL1 in CML is an example. However, most leukemias and lymphomas are more complex, with a median of >10 mutations/cases and several sub-clones at the time of diagnosis.22 Several software packages, for example DAVID,12 are designed to address this complexity using inputs such as lists of mutated genes or Differentially Expressed Genes (DEG) derived from RNASeq analyses. The output can identify the pathway(s) used by the leukemia or lymphoma which could be targeted. Clearly, therapeutic specificity is reduced with this approach as targeting is focused on a pathway used by many normal functions, not solely by the driver mutation. Nonetheless, this approach holds promise when direct targeting is not yet available or feasible.

Which NGS strategy is best? Whole genome or exome NGS is attractive, but targeted sequencing is gaining favor.19 The strategy is to sequence specific genes (or mutations) identified as recurrent in a specific tumor type and which are actionable, i.e., can be directly targeted with current drugs. Advantages of this approach are: (1) lower cost; (2) higher coverage (mean number of times each nucleotide of the target region is sequenced), which decreases the risk that some targeted loci are insufficiently covered for reliable variant-calling (despite improvements in NGS, it is still common to find parts of targeted genes insufficiently covered); and (3) less complex bioinformatics. Using this approach, one can interrogate <1,000 instead of >13,000 genes. The obvious potential drawback is missing non-conventional mutations (black holes). However, the use of panel-based sequencing is, in some regards, contrary to the original goal of NGSbased PM, namely, characterizing the universe of genetic abnormalities in an individual cancer. Panel-based sequencing is, instead, a standardized approach to PM, which can be unable to reconstruct mutation hierarchy in a person with leukemia or cancer.23 It is difficult to foresee which strategy, comprehensive or panel-based, will be most useful in the future.

Proving clinical benefit from any therapy intervention requires rigorous methodology, best exemplified by randomized clinical trials. NGS, however, makes it increasingly difficult to identify homogeneous cohorts of persons for study using this trial design. Consequently, new types of clinical trials are needed which preserve the value and rigorous approach of the controlled study, but also take into consideration the NGS-based molecular profile of the tumor.18,24-26 A possible solution could reside in trials in which the strategy of using PM data or not to inform treatment decisions is evaluated in a controlled way, rather than the single therapeutic intervention.

Conclusions NGS has increased our understanding of leukemia/lymphoma development, and must be translated into better therapy. Consequently, NGS will likely change the way physicians treat lymphomas and leukemias.27 In this scenario, panel-based sequencing will be a bridging-technology to whole-exome or even whole-genome sequencing and RNA-Seq. We are entering an exciting era of PM in general, and leukemia therapy specifically. However, we must also solve the important logistical problems that the use of NGS will inevitably cause. We must find new ways to evaluate therapy strategies, and off-label use of approved drugs must be streamlined and simplified. Finally, we must develop new types of clinical studies and new ways to render the complexity of PM information understandable and useful to patients. Acknowledgements This work was supported by Associazione Italiana Ricerca sul Cancro 2013 (IG-14249 to C.G.P.), Associazione Italiana Ricerca sul Cancro 2015 (IG-17727 to R.P.) and by European Union’s Horizon 2020 Marie Skłodowska-Curie Innovative Training Networks (ITN-ETN) under grant agreement No.: 675712CGP, CGP is a member of the European Research Initiative for ALK-Related Malignancies (www.erialcl.net). The authors regret to be unable to cite many appropriate references, given the limitations allowed by the journal.

References In medio stat virtus Virtue, as is often the case, likely lies between these alternative strategies. Presently, use of pre-defined panels haematologica | 2017; 102(1)

1. Mardis ER, Ding L, Dooling DJ, et al. Recurring mutations found by sequencing an acute myeloid leukemia genome. The New England journal of medicine. 2009;361(11):1058-1066.

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Editorials 2. Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793-795. 3. Hunter DJ. Uncertainty in the Era of Precision Medicine. N Engl J Med. 2016;375(8):711-713. 4. Milholland B, Auton A, Suh Y, Vijg J. Age-related somatic mutations in the cancer genome. Oncotarget. 2015;6(28):24627-24635. 5. Jiang L, Gu ZH, Yan ZX, et al. Exome sequencing identifies somatic mutations of DDX3X in natural killer/T-cell lymphoma. Nat Genet. 2015;47(9):1061-1066. 6. Martin GM, Ogburn CE, Colgin LM, Gown AM, Edland SD, Monnat RJ, Jr. Somatic mutations are frequent and increase with age in human kidney epithelial cells. Hum Mol Genet. 1996;5(2):215-221. 7. Genovese G, Kahler AK, Handsaker RE, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med. 2014;371(26):2477-2487. 8. Jaiswal S, Fontanillas P, Flannick J, et al. Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med. 2014;371(26):24882498. 9. Piazza R, Mologni L, Ramazzotti D, et al. Oncoscore, a Novel, InternetBased Tool to Assess the Oncogenic Potential of Genes Can Differentiate Between CP-CML and BC-CML Associated Genes, and Between CPCML Patients with Good and Bad Prognosis ASH 2016,#3075, 58th Annual Meeting and Exposition (December 3-6, 2016) in San Diego, CA, USA. 10. Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248-249. 11. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the functional effect of amino acid substitutions and indels. PloS One. 2012;7(10):e46688. 12. Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44-57. 13. Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1-13. 14. Ortmann CA, Kent DG, Nangalia J, et al. Effect of mutation order on

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myeloproliferative neoplasms. N Engl J Med. 2015;372(7):601-612. 15. Kantarjian H, Sawyers C, Hochhaus A, et al. Hematologic and cytogenetic responses to imatinib mesylate in chronic myelogenous leukemia. N Engl J Med. 2002;346(9):645-652. 16. Gambacorti-Passerini C, Messa C, Pogliani EM. Crizotinib in anaplastic large-cell lymphoma. N Engl J Med. 2011;364(8):775-776. 17. Gambacorti-Passerini C, Piazza R. Imatinib--A New Tyrosine Kinase Inhibitor for First-Line Treatment of Chronic Myeloid Leukemia in 2015. JAMA Oncol . 2015;1(2):143-144. 18. Mody RJ, Wu YM, Lonigro RJ, et al. Integrative Clinical Sequencing in the Management of Refractory or Relapsed Cancer in Youth. JAMA. 2015;314(9):913-925. 19. Papaemmanuil E, Gerstung M, Bullinger L, et al. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N Engl J Med. 2016;374(23):2209-2221. 20. Caravagna G, Graudenzi A, Ramazzotti D, et al. Algorithmic methods to infer the evolutionary trajectories in cancer progression. Proc Natl Acad Sci U S A. 2016;113(28):E4025-4034. 21. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189-2199. 22. Walter MJ, Shen D, Ding L, et al. Clonal architecture of secondary acute myeloid leukemia. N Engl J Med. 2012;366(12):1090-1098. 23. Xu X, Hou Y, Yin X, et al. Single-cell exome sequencing reveals singlenucleotide mutation characteristics of a kidney tumor. Cell. 2012;148(5):886-895. 24. Willyard C. 'Basket studies' will hold intricate data for cancer drug approvals. Nat Med. 2013;19(6):655. 25. Patterson SE, Liu R, Statz CM, Durkin D, Lakshminarayana A, Mockus SM. The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies. Hum Genomics. 2016;10:4. 26. Schwaederle M, Zhao M, Lee J, et al. Impact of precision medicine in refractory malignancies: A meta-analysis of 13,203 patients in phase I clinical trials. J Clin Oncol 2016;34((suppl; abstr 11520)): 27. Jameson JL, Longo DL. Precision medicine--personalized, problematic, and promising. N Engl J Med. 2015;372(23):2229-2234.

haematologica | 2017; 102(1)


Leaders in Hematology - Mechanisms in Hematology

Molecular determinants of pathogenesis and clinical phenotype in myeloproliferative neoplasms

REVIEW ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Jacob Grinfeld,1,2 Jyoti Nangalia1,2 and Anthony R. Green1,2

Department of Haematology, Cambridge Institute for Medical Research and Wellcome Trust/MRC Stem Cell Institute, University of Cambridge and 2Department of Haematology, Addenbrooke’s Hospital, Cambridge, UK 1

ABSTRACT

Haematologica 2017 Volume 102(1):7-17

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he myeloproliferative neoplasms are a heterogeneous group of clonal disorders characterized by the overproduction of mature cells in the peripheral blood, together with an increased risk of thrombosis and progression to acute myeloid leukemia. The majority of patients with Philadelphia-chromosome negative myeloproliferative neoplasms harbor somatic mutations in Janus kinase 2, leading to constitutive activation. Acquired mutations in calreticulin or myeloproliferative leukemia virus oncogene are found in a significant number of patients with essential thrombocythemia or myelofibrosis, and mutations in numerous epigenetic regulators and spliceosome components are also seen. Although the cellular and molecular consequences of many of these mutations remain unclear, it seems likely that they interact with germline and microenvironmental factors to influence disease pathogenesis. This review will focus on the determinants of specific myeloproliferative neoplasm phenotypes as well as on how an improved understanding of molecular mechanisms can inform our understanding of the disease entities themselves.

Correspondence: arg1000@cam.ac.uk

Introduction The classical Philadelphia-negative myeloproliferative neoplasms (MPNs) are characterized by clonal expansion at a hematopoietic progenitor level with the overproduction of mature myeloid and erythroid progeny. Clinically, they share the features of bone marrow hypercellularity, increased incidence of thrombosis or hemorrhage, and an increased rate of transformation to acute myeloid leukemia, which is usually fatal. Since these are chronic conditions that normally manifest well in advance of leukemic transformation, they offer an invaluable model for studying the earliest steps of leukemogenesis, including the ways in which somatic mutations perturb stem and progenitor cell function. Current diagnostic criteria separate Philadelphia-negative MPNs into three distinct disease entities: polycythemia vera (PV) – primarily characterized by a raised red cell mass; essential thrombocytosis (ET) – characterized by an isolated increase in platelet numbers; and idiopathic/primary myelofibrosis (MF) – in which the hematopoietic compartment is gradually replaced with collagen fibers, leading to bone marrow failure and extramedullary hematopoiesis, and which is often associated with constitutional symptoms.

Mutations affecting cytokine receptor signaling pathways Mutations in Janus Kinase 2 (JAK2) In 1951 William Dameshek hypothesized that rather than these being “pure” proliferations, the myeloproliferative conditions PV, ET and MF may represent differing manifestations of a single underlying process.1 This hypothesis was borne out by the discovery of a valine to phenylalanine substitution at codon 617 (V617F, due to a G>T substitution), of the JAK2 gene in over 95% of patients with PV and haematologica | 2017; 102(1)

Received: July 4, 2016. Accepted: September 27, 2016. Pre-published: December 1, 2016. doi:10.3324/haematol.2014.113845

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/7

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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50-60% of those with ET or MF.2-5 JAK2 is a cytoplasmic tyrosine kinase, required for signal transduction from type I cytokine receptors which include those for thrombopoietin, erythropoietin and granulocyte colony stimulating factor (G-CSF), and therefore plays a vital role in myelopoiesis.

Molecular consequences of JAK2 mutations The V617F mutation occurs in the JH2 (or â&#x20AC;&#x153;pseudokinaseâ&#x20AC;?) domain (see Figure 1A) and results in constitutive activation of the JH1 kinase domain. The mechanism by which this occurs is increasingly becoming clear.6 In short, there is evidence that the mutation may reduce the autoinhibitory function of the JH2 domain via changes in JH1JH2 conformation7 and adenosine triphosphate (ATP) binding.8 The expression of JAK2V617F has been shown to allow for JAK2 signaling in the absence of cytokine receptor ligation,3,4 but the expression of type I cytokine receptors9 and a functional FERM domain (required for receptor binding)10 are still required for JAK2 signaling and cytokine-independent growth. Furthermore, the V617F mutation may allow for the escape from negative regulation by the suppressor of cytokine signaling 3 (SOCS3).11 The increased JAK2 signaling recapitulates that seen in the physiological response to cytokine binding, namely the increased activation of signal transducer and activator of transcription (STAT) 1, 3 and 5, mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K) pathways.3,5,12 STAT5 in particular is thought to have a crit-

ical role in the pathogenesis of PV.13,14 Mutations in exon 12, located between F533 and F547, within the linker region between the SH2 and JH2 domains (Figure 1A), are found in 1-2% of patients with PV.15,16 These mutations also induce constitutive activation, but to a greater degree than JAK2V617F, with greater JAK2 phosphorylation and MAPK pathway activation,15 and also result in cytokine-independent growth. The mechanism by which these mutations act is less well understood, but given their location, it is likely that they also disrupt JH1-JH2 domain interactions. Moreover, a number of non-canonical roles have also been described for JAK2, which may be perturbed by pathogenic mutations. JAK2 has been found to localize to the nucleus, where it can phosphorylate tyrosine 41 on histone H3.17 This has been associated with the increased expression of LMO2, which has been implicated in leukemogenesis. JAK2V617F expression has also been associated, in vitro, with an increase in homologous recombination, the activation of DNA-repair mechanisms, aneuploidy and the acquisition of a mutator phenotype.18 Furthermore, there is evidence that JAK2V617F can increase the production of reactive oxygen species and reduce the apoptotic response to DNA damage by inhibiting the Bcl-xl deamidation pathway.14,19

Cellular consequences of JAK2 mutations Mutations in JAK2 have been shown to occur in cells near the top of the hematopoietic hierarchy and can be

Figure 1: Panel A shows a schematic representation of the structure of the JAK2 gene, indicating the sites of common JAK2 mutations. Panel B shows a schematic representation of the structure of the CALR gene and the consequences of the common mutations seen in myeloproliferative neoplasms (MPNs). JH: janus homology; FERM; 4.1 protein, ezrin, radixin and moesin; bp: base pair; KDEL: lysine, aspartic acid, glutamic acid, leucine; SH2: Src homology 2.

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Determinants of phenotypes in MPNs

found in the hematopoietic stem cell (HSC) compartment.20,21 These observations are consistent with the long-term persistence of JAK2-mutated MPNs, and the fact that the mutation can be found in cells of the lymphoid as well as myeloid lineages in some cases.22 Several lines of evidence indicate that JAK2V617F does not confer an advantage at the HSC level. Xenografts of JAK2-mutant patient cells into immunodeficient animals suggest that JAK2 mutations do not result in a strong self-renewal advantage;21 a finding that is recapitulated in several knock-in mouse models.23,24 Instead, JAK2 mutant HSCs are skewed towards symmetrical differentiation with a subsequent expansion of the progenitor pool, rather than self-renewal, and do not demonstrate an advantage in competitive transplantation experiments.25 These observations have led to the suggestion that JAK2V617F alone is insufficient to initiate disease and that additional mutations are required. This is consistent with the detection of the JAK2V617F mutation on its own in patients without overt myeloid malignancy.26-29 An alternative explanation for these findings is that the expansion of the progenitor (rather than the stem cell) pool is sufficient to mediate disease development, an idea that is reinforced by recent studies which demonstrate that a pool of long-term multipotent progenitors are the main drivers of adult hematopoiesis.30 Finally, it is likely that there is functional heterogeneity within the JAK2-mutated HSC pool and across disease subtypes. For instance, there is evidence that the ability to self-renew, and therefore stably engraft, may decrease with increasing levels of JAK2 expression,31 similar to the differences in stem cell behavior seen at different expression levels of STAT532 and oncogenic NRAS.33

CALR is not known to have a direct role in cytokine signaling, hematopoiesis or cell fate decisions, and therefore the mechanism(s) by which CALR mutations result in megakaryocytic proliferation and an ET/MF phenotype were not initially apparent. CALR is known to be involved in the regulation of calcium uptake and release in the endoplasmic reticulum,42 and acts as a chaperone, together with calnexin and ERp57, to form part of the regulatory machinery involved in the folding and quality control of newly synthesized glycoproteins.43 Differences in cytosolic calcium mobilization have been reported with the 52 base pair deletion,44 suggesting that this may be one mechanism by which mutant CALR exerts its effect, and expression of the mutant protein does appear to be particularly restricted to megakaryocytes on immunohistochemical evaluation of bone marrow specimens.45 More recently, it has been shown that CALR mutations can impart TPO-independence in both cell lines46,47 and retroviral mouse models,48,49 in a MPL- and JAK2-dependent manner, mimicking the effect of activating MPL mutations. This has been shown to be mediated by direct binding of MPL by the N domain of CALR, a phenomenon that uniquely occurs in the presence of the mutated C-terminus,48,49 leading to autocrine activation of MPL, JAK2 dimerization and downstream STAT5 and ERK phosphorylation.46,49 It is therefore clear that the inappropriate activation of JAK2 signaling is common to the three main phenotypic driver mutations (i.e., those in CALR, MPL and JAK2 itself) and plays an important role in disease pathogenesis in each case, in keeping with the clinical efficacy of JAK2 inhibition irrespective of the presence of the mutations in JAK2.50

Mutations in MPL and CALR

Other mutations in signaling pathways â&#x20AC;&#x201C; LNK, CBL and RAS

A number of hotspot missense mutations in exon 10 of myeloproliferative leukemia (MPL), the human homologue of the murine myeloproliferative leukemia virus oncogene (v-MPL), the cell surface receptor for thrombopoietin, such as M515L and M515K (and less commonly S505N), have been reported in patients with ET and MF (Figure 2A). MPL mutations are associated with increased STAT3, STAT5, ERK and AKT signaling and cytokine autonomous growth.34,35 More recently, the S204P and Y591N mutations were described in a cohort of patients with ET or MF, otherwise found to be lacking established phenotypic driver mutations. These mutations were found to have a weak gain-of-function effect, either with a degree of thrombopoietin-independent growth or signaling, or thrombopoietin hypersensitivity.36,37 Mutations in calreticulin (CALR) are also found in approximately 25-35% of patients with ET and 35-40% of those with MF (Figure 2A). These are exclusively insertions/deletions (most commonly a 52 base pair deletion or 5 base pair insertion) in the final exon (Figure 1B), and in all cases these result in a 1 base pair shift in the reading frame.38,39 This points strongly to a specific gain of function involving the C-terminus of the protein. The mutual exclusivity of JAK2, MPL and CALR mutations point to a similar mechanism of action, as do the similarities in clinical phenotype between CALR and MPL. Furthermore, there is evidence that CALR mutations are also associated with increased JAK-STAT signaling,38,40 although some studies have suggested that other pathways may be of more importance.41 haematologica | 2017; 102(1)

Other than the aforementioned mutations in JAK2, MPL and CALR, a number of genes are also mutated in patients with MPNs (Figure 2B). As might be expected from the role of receptor signaling pathways in the pathogenesis of MPNs, loss-of-function mutations in negative regulators of receptor tyrosine kinases are seen, as well as mutations in members of downstream pathways. LNK (lymphocyte specific adaptor protein, or SH2B3) binds both MPL and JAK2 to act as a negative regulator of JAK-STAT signaling. LNK deficient mice display an MPNlike phenotype with megakaryocytic hyperplasia, cytokine hypersensitivity and splenomegaly.51 LNK exon 2 mutations are found in a small number of MPN patients. They are more often seen in advanced phase disease, but can also be found in patients with an erythrocytosis lacking a JAK2 mutation, suggesting that these mutations may be sufficient to initiate disease.52-54 Casitas B-lineage lymphoma proto-oncogene (CBL) is an E3 ubiquitin ligase, which is specifically involved in the ubiquitination (and resultant degradation) of a number of receptor tyrosine kinases, as well as having a role in intracellular signal transduction. Its targets include PDGFR, c-KIT, FLT3 and MPL.55 Mutations in the RING domain, responsible for CBLâ&#x20AC;&#x2122;s ligase activity, have been described in MPNs.56,57 Mutations in SOCS proteins, another class of regulators of JAK2 signaling, however, are only reported in a handful of patients,58 but there is evidence that their expression may be suppressed in a subset of patients due to hypermethylation of SOCS pro9


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moter regions.59 Mutations increasing RAS pathway signaling are also observed in a small number of patients, but, as with CBL and LNK mutations, tend to be seen more in myelofibrosis, advanced phase/transformed disease or myeloproliferative neoplasm/myelodysplastic syndrome (MPN/MDS) overlap conditions.60 NRAS mutations tend to occur in a hotspot location at codon 12. These mutations appear to result in a gain-of-function, resulting in myeloid differentiation and increased HSC self-renewal, and can induce a chronic myelomonocytic leukemia (CMML)-like disease in a mouse model.61 Similarly, negative regulators of RAS, such as NF162 and PTPN11,63 have also been found to be mutated in some MPN or MPN/MDS-overlap cases.

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Mutations affecting other cellular processes Mutations in epigenetic regulators Other genes commonly mutated in MPNs are not specific to these conditions and are mutated across myeloid malignancies in general, including acute myeloid leukemia (AML) and MDS, as well as in some elderly patients without an overt myeloid malignancy.26-29 These include genes involved in epigenetic regulation and messenger RNA (mRNA) splicing (summarized in Figure 2B and Figure 3), but their role in the pathogenesis of MPNs is less well understood. The most commonly mutated of these is a member of the TET family, ten-eleven translocation 2 (TET2); loss-of-function mutations which are found in approximately 10% of MPNs.64,65 TET2 converts 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC), a process which is thought to be particularly important for gene regulation in stem cells and embryonic development. A reduction in 5-hmc is observed in TET2 mutated patients, and is associated with increased selfrenewal capacity and myeloid bias.66,67 The HOXA cluster, which is implicated in lineage commitment, is known to be regulated by TET2, suggesting one possible mechanism by which TET2 mutations may result in a differentiation block.68 Hotspot mutations in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are described in <5% of cases.62,69 These enzymes catalyze the conversion of isocitrate to a-ketoglutarate, but these mutations result in the production of 2hydroxyglutarate, which inhibits Jumonji-C domain histone demethylases. This leads to histone hypermethylation and also inhibits TET2 activity, which in turn results in a differentiation block.70,71 TET2 mutations do not appear to be associated with particular MPN subtypes, but have been found, in one study, to correlate with poorer overall survival and increased progression to AML,72 while IDH mutations are more commonly found in MF or transformed disease.69 Loss-of-function mutations (including dominant negative missense mutations at codon 882) in DNA methyltransferase 3A (DNMT3A), a protein responsible for de novo methylation of CpG dinucleotides, are found across MPN subtypes.73 As with TET2 mutations, their exact role in MPN pathogenesis is not yet fully understood, but it is thought that the resultant epigenetic deregulation results in the upregulation of “HSC fingerprint” genes such as GATA3 and RUNX1 and the downregulation of differentiation factors such as Ikaros, together resulting in a differentiation block and HSC expansion.74 Mutations of genes involved in histone methylation are 10

Figure 2. Panel A shows the relative frequencies of the mutually exclusive phenotypic driver mutations in JAK2, CALR and MPL, together with the proportions of those without mutations in these genes (triple negative – TN).38,39,72 Panel B shows the prevalence of additional mutations and their relative proportions across ET, PV and MF.39,62,72 ET: essential thrombosis; PV: polycythemia vera; MF: myelofibrosis.

overrepresented in myelofibrosis/transformed disease. EZH2 ( PcG Enhancer of Zeste Homolog 2) is the catalytic component of the polycomb repressive complex 2 (PRC2) and, together with EED and SUZ12 acts to trimethylate histone H3 lysine 27 causing transcriptional repression. In contrast to EZH2 mutations seen in lymphoma, those in MPNs tend to be loss-of-function mutations75 that result in the derepression of a set of genes that includes a number of putative oncogenes (e.g., LMO1 and HOXA9), and are associated with increased HSC self-renewal.76,77 Mutations of additional sex combs like 1 (ASXL1) are also relatively common in MF.78 ASXL1, a component of PRC1, is also known to regulate PRC2 and to have a role in the regulation of HOX genes. Accordingly, ASXL1 mutations are associated with HOXA upregulation and the reduction in H3K27 methylation, both of which have been linked to impaired recruitment of EZH2.79 In summary therefore, a number of the mutations found in MPNs affect the regulation of DNA/histone methylation in the HSC compartment and are linked to increased self-renewal and a block in differentiation; features that play a role in disease progression.

Mutations in mRNA processing machinery Mutations in components of the spliceosome, including splicing factor 3B subunit 1 (SF3B1), serine/arginine-rich splicing factor 2 (SRSF2), U2 small nuclear RNA auxiliary haematologica | 2017; 102(1)


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factor 1 (U2AF1) and zinc finger RNA binding motif and serine/arginine rich 2 (ZRSR2), are well described in MDS and also seen in MPNs,80 particularly in MF or MPN/MDS overlap syndromes. The role of these mutations in disease pathogenesis is still not fully understood, but the effects of hotspot mutations of codon 95 of SRSF2, and codon 34 of U2AF1 are perhaps the best explored, as knock-in mouse models have been made for each. SRSF2 mutations appear to result specifically in skewed mRNA motif recognition (rather than loss of function), which is associated with alterations in exon usage in a number of genes. These include EZH2 (leading to reduced expression), and bcl-6 corepressor (BCOR),81 which is also known to be mutated in myeloid malignancies. U2AF1 mutations alter its 3' splice acceptor preferences leading to mis-splicing of a set of genes that includes BCOR and SRSF2.82 EZH2 expression was found to be reduced in 63% of U2AF1- or SRSF2mutated patient specimens, and this was associated with decreased H3K27 trimethylation.77 Thus, while mutations in spliceosome components result in mis-splicing of multiple genes, there is evidence that they may also act via the dysregulation of PRC2 function.

Other determinants of MPN pathogenesis and phenotype Germline variation There are several reports of familial clustering of MPNs (where two or more family members are affected by MPNs), and there is a tendency for family members to present with the same MPN phenotypes. In fact, the relative risk of acquiring ET has been estimated to be approximately 12 times higher in first-degree relatives of MPN patients.83 This strongly points to the existence of germline susceptibility factors. Causes of familial MPNs include germline mutations of RBBP6,84 and a high penetrance duplication of 14q32.2, which has been associated with overexpression of ATG2B, a mediator of autophagy, and GSKIP, a regulator of the WNT/β-catenin pathway.85 It appears that these changes operate via independent pathways: RBBP6 mutations affect the p53 pathway and thereby influence the response to apoptotic stimuli and the risk of developing further mutations, while ATG2B and GSKIP overexpression promote megakaryopoiesis via increased thrombopoietin sensitivity. A number of more common, but lower penetrance germline variants have been associated with MPN development, including single nucleotide polymorphisms (SNPs) present in, or close to, telomerase reverse transcriptase (TERT)86 and “MDS1 and EVI1 complex locus” (MECOM).87 Two JAK2 haplotypes (46 and 1) are found to be in linkage disequilibrium (with the exception of one SNP). Whilst the combined haplotype (termed 46/1, or GGCC in reference to the defining alleles) is found in 24% of the population, it is found in up to 56% of patients with MPNs, with an odds ratio of 3 to 4.88,89 Together with TERT and MECOM-associated SNPs, the 46/1 haplotype is estimated to account for 55% of the population attributable risk of developing an MPN.87 Furthermore, the JAK2V617F mutation preferentially occurs on the 46/1 allele. One possibility for this association is that the 46/1 haplotype is more prone to mutation haematologica | 2017; 102(1)

and therefore more likely to give rise to JAK2V617F and exon 12 mutations. However, perhaps a more likely possibility is that the occurrence of mutant JAK2 in the context of the JAK2 46/1 haplotype confers an additional clonal or phenotypic advantage – the ‘fertile ground’ hypothesis. Further support for a clonal advantage for JAK2 46/1 is the fact that it is also seen more frequently in patients with MPL mutations.90 One final SNP, in the intergenic region between HBS1L and MYB (rs9376092) has been found to be enriched in MPL- and CALR-mutated MPNs, and more frequently in JAK2-mutated ET patients.87 With the exception of the 14q32.2 duplication mentioned above, which was found to be predominantly associated with an ET phenotype, the HBS1L-MYB SNP appears to one of the few germline variants that is associated with a particular MPN phenotype.

Role of the microenvironment in MPN pathogenesis and the development of fibrosis The importance of cell extrinsic factors, and in particular the bone marrow microenvironment, in the pathogenesis of MPNs is exemplified by the fact that the deletion of Mib1 (causing dysregulated Notch signaling)91 or of retinoic acid receptor γ,92 in non-hematopoietic cells alone was sufficient to induce a myeloproliferative phenotype in mouse models. One possible mechanism by which the microenvironment could support the development of MPNs may be through the secretion of soluble factors, such as tumor necrosis factor a (TNFa), interleukin-6 (IL-6), fibroblast growth factor (FGF) or interferon-γ-inducible protein 10 (IP-10). Such cytokines are produced by the bone marrow stroma and have been shown to promote the growth of MPN clones, while, in some cases inhibiting the growth of wild-type clones.93,94 Overexpression of NF-I, which has been described in patients with uniparental disomy (UPD) of chromosome 9, has also been suggested to result in resistance to transforming growth factor-β (TGF-β), which has been demonstrated to have inhibitory effects on the hematopoiesis and on myeloid cell lines.95,96 The secretion of proteases which disrupt the stromal cell derived factor-1/chemokine receptor 4 (CXCR4) axis, as well as the downregulation of CXCR4 itself by tumor cells, have both been associated with greater mobilization of HSCs, and these mechanisms may contribute to extramedullary hematopoiesis and potentially mediate the loss of HSC quiescence.97 Whilst there are numerous mechanisms by which the microenvironment can affect MPN clones, neoplastic cells can also subvert their niche. Clonal megakaryocytes and monocytes themselves secrete a number of cytokines, which include FGF, interleukin-8, TGF-β and vascular endothelial growth factor, that stimulate angiogenesis and drive fibroblast differentiation and recruitment, leading to bone marrow fibrosis.98,99 The secretion of other cytokines by the clone, such as TNFa, may create an autocrine/paracrine loop, promoting the growth of the tumor clone while inhibiting normal hematopoiesis. The overexpression of these pro-inflammatory cytokines is particularly well described in MF; however, there is a considerable overlap between the cytokine profile seen in MF and those seen in PV and ET, suggesting the possibility of a biological spectrum.100,101 In mouse models, JAK2-mutated clones have also been found to secrete lipocalin-2, which has been shown to suppress normal hematopoiesis via paracrine oxidative DNA damage, and may also drive 11


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the development of additional mutations in the tumor clone.102 In addition, there is also evidence that, through direct cell-cell interactions and the secretion of soluble mediators, such as TPO, CC chemokine ligand 3 (CCL3) and interleukin-1β, the mutant clone can remodel the bone marrow niche to create an environment more permissive for its expansion, via the depletion of sympathetic nerve fibers and nestin-positive mesenchymal cells103 and the expansion of osteoblast lineage cells.104

Determinants of MPN phenotype – towards an integrated model? The MPNs represent a heterogeneous group of diseases with phenotypes that include isolated thrombocytosis, the expansion of all three myeloid lineages, and pancytopenia. In the majority of cases, abnormalities in cytokine signaling pathways are a common factor, and most commonly lead to increased JAK-STAT signaling. It is increasingly clear that the traditional division into three MPN subtypes does not necessarily reflect the underlying biological complexity of these conditions, and that the resultant clinical phenotype is a function of genetic factors intrinsic to the neoplastic clone, the overall clonal architecture, host factors (including genetic background), and factors relating to crosstalk between the neoplastic clone and its microenvironment.

Cell intrinsic factors – somatic mutations, transcription profiles and gene dosage At the cell intrinsic level, mutations in phenotypic driver mutations (JAK2, CALR and MPL) subvert physiological EpoR and TpoR signaling, leading to erythrocytosis and megakaryopoiesis, respectively. It is clear that this is a major factor in determining phenotype. Most strikingly, mutations in MPL are never found in cases with PV (Figure 2A), and this is also the case for CALR mutations, which, as discussed above, are likely to act via interaction with MPL. How the same mutation in JAK2 can occur in three different MPN phenotypes is a central question within the MPN field. One possible mechanism may relate to the level of gene ‘dosage’, as several lines of evidence suggest that increased JAK2 signaling leads to more of a polycythemic phenotype. Firstly, JAK2 exon 12 mutations are found exclusively in PV, and have been shown to result in greater STAT5 phosphorylation than V617F mutations.15 Secondly, UPD of chromosome 9, leading to JAK2V617F homozygosity, has been associated with greater erythropoietin independence in hematopoietic progenitors105,106 and is found in approximately one-third of patients with PV, but was not initially reported in ET.96 The hypothesis that increasing JAK2V617F dosage may skew towards erythrocytosis is supported by the correlation between the size of homozygous clones and hemoglobin concentrations in patients,107 as well as by knock-in mouse models, where the ratio of mutant to wild-type JAK2 correlates with the degree of erythrocytosis,24,108 and by an induced pluripotent stem cell model.109 Furthermore, even within the context of ET, greater JAK2V617F allele burdens are associated with a higher degree of erythrocytosis and leukocytosis.110 However, some PV patients do not carry a homozygous JAK2V617F subclone,111 and JAK2V617F-homozygous subclones have been detected in patients with ET107,110-112 (although these were generally small (<10%), in contrast 12

to those in PV where they tended to represent the dominant MPN clone). Together, these findings demonstrate that JAK2V617F homozygosity is neither necessary nor sufficient for PV. It is possible that mutations in other, as yet unidentified, genes may play a similar role to homozygosity in these JAK2V617F-heterozygous PV patients. There is also reason to believe that UPD of 9p may have effects beyond inducing loss of heterozygosity of JAK2V617F, as evidenced in patients where it occurs prior to the acquisition of a JAK2 mutation.113 This suggests that 9p UPD itself may independently carry a competitive advantage (whether due to selection of a particular JAK2 haplotype or alterations in other genes on 9p, such as NFIB97) that is unrelated to JAK2V617F dosage. Finally, JAK2V617F-heterozygous cells from patients with ET are characterized by greater STAT3114 and STAT112 phosphorylation as well as upregulation of interferon-γ regulated genes, when compared to those from patients with PV. This again demonstrates that mechanisms beyond JAK2V61F dosage alone contribute to the determination of the PV or ET phenotype. Differences in phenotypic driver mutations may additionally account for some of the clinical heterogeneity seen within the individual MPN subtypes. As mentioned above, the presence of JAK2 homozygosity is associated with higher hemoglobin levels in JAK2-mutated ET and PV as well as with a greater incidence of aquagenic pruritus and splenomegaly.107,110 JAK2 homozygosity was also associated with a greater risk of progression to MF and of thrombosis in patients with ET.110 CALR-mutated patients with ET tend to have higher platelet counts, but lower leukocyte counts and hemoglobin levels and lower rates of thrombosis than those with JAK2 mutations.38,39,115,116 CALR mutations are also associated with higher platelet and lower leukocyte counts, and are independent predictors for improved overall survival in patients with MF.117,118 There is some evidence that the type of CALR mutation itself may also result in differential phenotypes.44,119 TET2 and DNMT3A mutations are commonly seen across all three MPN phenotypes and are not specifically associated with MF or MDS/MPN overlap syndromes, in contrast to mutations in other epigenetic regulators. Their role in disease biology and phenotype is therefore not entirely clear. Recent evidence suggests that the context in which these mutations are acquired can influence the proliferative potential of a given clone in a cell-intrinsic manner.120 Namely, the acquisition of a JAK2 mutation on a wild-type background resulted in a proliferative advantage, but this was not the case on the background of an earlier TET2 mutation. Furthermore, TET2 and JAK2mutated (double mutant) HSCs/progenitors from JAK2first patients were able to generate more progenitors than those from TET2-first patients. Some additional mutations seen in MPNs, however, do appear to be enriched in certain subtypes, as indicated in Figure 2B, and may additionally have an impact on the survival or risk of leukemic transformation. Mutations in components of the spliceosome (including SRSF2, U2AF1 and SF3B1) are strongly correlated with an MF (or MPN/MDS overlap) phenotype, as are mutations in ASXL1 and EZH2, which are prevalent in MDS and de novo AML and associated with leukemic transformation and a worse overall survival in MPNs.39,62,75,121 This may be related to the deregulation of PRC2 and derepression of stem cell signature genes, causing increased stem cell self renewal, haematologica | 2017; 102(1)


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Figure 3. Summary of epigenetic regulatory pathways affected by known mutations. In addition to the “phenotypic driver” mutations in JAK2, CALR and MPL, a number of other mutations are described, affecting epigenetic regulation and the spliceosome. These pathways are interlinked in a number of ways, and in common, appear to lead to the dysregulation in genes involved in stem cell fate decision choices. These in turn may be associated with expansion of the hematopoietic stem cell (HSC) compartment with differentiation block, dysplasia and accelerated disease. CpG: cytosine-phosphate-guanine dinucleotide.

as discussed above77,79,81 (Figure 3). Finally, mutations in NRAS and CBL are also more frequently seen in patients with MF, atypical chronic myeloid leukemia and chronic myelomonocytic leukemia, and are associated with poorer overall survival.57

Heterogeneity in clonal architecture and the significance of order of mutation acquisition Another important source of phenotypic diversity across MPNs, even amongst those that share phenotypic driver mutations, is heterogeneity in clonal architecture.122 Given that JAK2 mutations themselves may not promote a clonal advantage, and may even result in an impairment of HSC self-renewal, as discussed previously, there may be selective pressure on the JAK2 clone leading to the selection of particular subclones (e.g., those carrying concurrent mutations in epigenetic modifier genes). This may be further enhanced by differential sensitivities to, and production of, secreted soluble mediators, such as TNFa and TGFβ. The overall disease phenotype is likely to be a function of the relative proportions of all the subclones, as they will differ in terms of their functional properties, for example in terms of differentiation or self-renewal potential and soluble mediator secretion profiles. Furthermore, subclones may be present which, while not directly contributing to the disease phenotype, exert an effect via constraints on the growth of other clones. One factor that may play a role in determining clonal architecture is the order in which somatic mutations are acquired. The importance of the order of mutation acquisition has been demonstrated in JAK2-mutated MPNs haematologica | 2017; 102(1)

harboring concurrent TET2 or DNMT3A mutations, where mutation order has been shown to have an impact on disease phenotype,120,123 thrombotic risk, age at presentation and response to treatment.120 Patients in whom the JAK2 mutation occurred first have larger “double mutant” subclones (harboring both JAK2 and either TET2 or DNMT3A mutations) as well as larger JAK2-mutated homozygous clones. In the case of TET2 mutations, these patients show expansion of erythroid progenitors, present at a younger age, and are at a greater risk of thrombosis.120 In contrast, TET2-first or DNMT3A-first patients are characterized by a dominant “single mutant” subclone (i.e., harboring the TET2/DNMT3A mutation only), in keeping with the greater self-renewal capacity seen with TET2/DNMT3A mutations compared to those in JAK2. These patients were more likely to have ET, which may in part be related to constraints on the expansion of the JAK2-mutated clone and on the development of homozygosity. Therefore, as well as the cell-intrinsic effect of mutation order on clonogenic potential discussed in the previous section, it is likely that the order in which mutations occur will influence the composition of the stem cell niche in which later subclones will arise and reside, potentially introducing constraints on their potential to expand. As well as competition between clones causing constraints on relative clone sizes, it is also feasible that separate clones may act cooperatively. This has been shown in solid tumors such as glioblastoma, where cytokine secretion by a relatively minor subclone can drive the expansion of a more dominant tumor clone.124 13


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Role of non-tumor factors Germline variants have also been shown to influence MPN phenotype. One example previously discussed is that of rs9376092, an intronic SNP which affects the expression of MYB, and is found more frequently in JAK2mutated ET than PV patients. This is in keeping with a knockdown mouse model where low MYB levels were sufficient to induce an ET-like phenotype.125 In addition, germline copy number variations on chromosome 14, which are associated predominantly with an ET phenotype, appear to result in increased sensitivity to TPO and cytokine-independent growth, even in the absence of a phenotypic driver mutation.85 Other non-genetic host factors may also influence MPN phenotype. For example, iron deficiency may constrain erythropoiesis and promote thrombocytosis, skewing towards an ET phenotype. The greater incidence of ET in pre-menopausal women is consistent with such an effect, and may also suggest an additional role for estrogens in skewing towards megakaryopoiesis rather than erythropoiesis. Finally, given the role of pro-inflammatory cytokines, and other microenvironmental changes, in promoting the growth of MPN clones and the fibrotic process as discussed previously, it is conceivable that concurrent inflammatory conditions, age or sex-related changes in the bone marrow microenvironment, or even the hostâ&#x20AC;&#x2122;s microbiome may influence the resultant MPN phenotype.126 Overall, it is clear that the evolution of a MPN is a dynamic process involving complex interactions between subclones and the bone marrow microenvironment, which in turn drive changes in the tumor itself (such as the acquisition of new mutations, genetic copy number or epigenetic changes, or mobilization of cells into a separate niche) as well as changes in the bone marrow environment (such as sympathetic neuropathy, osteoclast expansion, fibroblast recruitment/differentiation and differential soluble mediator secretion).

Final remarks and questions A number of common threads run through this discussion of MPN pathogenesis. First, it is clear that MPNs are diseases of cytokine signaling pathways. This is evident from the prevalence of mutations in cytokine signaling pathways, not only in JAK2 and MPL, but also in loss-offunction mutations of negative regulators of JAK-STAT signaling. There is increasing evidence that CALR mutations also act on these pathways. Furthermore, cytokine secretion by the bone marrow stroma and by the tumor clone itself appears to play a role in disease persistence and progression. Secondly, additional mutations, such as those in epigenetic modifiers (specifically ASXL1 and EZH2) and spliceosomal components, are likely to modulate the disease phenotype via the derepression of genes regulating stem cell quiescence and self-renewal. This in turn may contribute to the development of accelerated phase disease, bone marrow fibrosis and leukemic transformation, and be associated with worse overall survival. Thirdly, it is clear that not only is the presence of somatic mutations important in disease pathogenesis, but also that the genetic background upon which they occur has functional and clinical relevance. This applies to both the 14

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Figure 4. An integrated model of determinants of MPN phenotype. Different germline, acquired or microenvironmental factors (vectors represented in 4C) can influence differentiation/self-renewal fate choices, polarization of differentiation towards erythropoiesis or megakaryopoiesis or stimulate fibrosis (the main processes determining MPN phenotype, represented in 4A). Some may operate on more than one process, for example ASXL1 mutations may promote both self-renewal and fibrosis. These then result in a continuum of different phenotypes and account for the heterogeneity seen within the MPNs, despite the small number of phenotypic driver mutations. A representation of where different myeloid disorders sit within this framework is provided in Figure 4B. MF: myelofibrosis; PV: polycythemia vera; ET: essential thrombocytosis; MPN: myeloproliferative neoplasms; MDS: myelodysplastic syndrome; AML: acute myeloid leukemia; PRC2: polycomb repressive complex 2; SNPs: single nucleotide polymorphisms; lL-8: interleukin-8; TGF-β: transforming growth factor-β.

germline background (for example, the HBS1L-MYB SNP and 46/1 haplotype) and to that of other somatically acquired mutations, such as those affecting TET2 and DNMT3A. Finally, the fact that changes in clonal architecture, mutation profile and microenvironment can occur in a given patient over time with a resultant change in clinical phenotype (e.g., transformation of ET to PV, or chronic phase disease to accelerated phase or acute leukemia), further supports the idea that ET, PV and MF are not distinct biological entities but rather sit in a biological continuum where clinical phenotype is determined by three main factors: (1) the relative degrees of erythropoiesis compared to megakaryopoiesis, (2) the degree of differentiation versus stem cell/progenitor expansion, and (3) the degree of fibrosis. haematologica | 2017; 102(1)


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A simplified representation of this is shown in Figure 4. Under this schema, for example, JAK2-mutated ET may be an intermediate on the spectrum between CALR/MPLmutated ET and JAK2-mutated PV, as is reflected in clinical parameters such as hemoglobin concentration, platelet counts and the risk of venous thrombosis.115,116,127,128 This model is also consistent with the concept that “primary” MF reflects progression from a preceding (but previously undiagnosed) MPN. Similarly, it has been suggested that prefibrotic MF may represent a transitional point between ET and MF.129 Our understanding of the biological complexity under-

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17


REVIEW ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Leaders in Hematology - Management in Hematology

From leeches to personalized medicine: evolving concepts in the management of polycythemia vera Alessandro M. Vannucchi

Haematologica 2017 Volume 102(1)18-29

CRIMM, Centro di Ricerca e Innovazione per le Malattie Mieloproliferative, Azienda Ospedaliera Universitaria Careggi, Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi, Firenze, DENOTHE Excellence Center, Italy

ABSTRACT

P

Correspondence: amvannucchi@unifi.it

Received: July 18, 2016. Accepted: September 22, 2016. Pre-published: November 24, 2016.

olycythemia vera is a clonal disorder of hematopoietic stem/progenitor cells. It manifests as an expansion of red cell mass. It is the most common chronic myeloproliferative neoplasm. In virtually all cases, it is characterized by a V617F point mutation in JAK2 exon 14 or less common mutations in exon 12. The landmark discovery of the autonomously activated JAK/STAT signaling pathway paved the way for the clinical development of the first target drug, the JAK1 and JAK2 inhibitor ruxolitinib. This is now approved for patients with resistance or intolerance to hydroxyurea. Phlebotomies and hydroxyurea are still the cornerstone of treatment, and aim to prevent the first appearance or recurrence of cardiovascular events that, together with progression to post-polycythemia vera myelofibrosis and leukemia, represent the main causes of death. Interferon-a is an alternative drug and has been shown to induce molecular remissions. It is currently undergoing phase III trials that might eventually lead to its approval for clinical use. The last few years have witnessed important advances towards an accurate early diagnosis of polycythemia vera, greater understanding of its pathogenesis, and improved patient management. This review will focus on the most recent achievements and will aim to unify the different concepts involved in a personalized approach to the patient with polycythemia vera. In spite of many recent advances in the understanding of its pathogenesis and improved disease management, polycythemia vera remains a lifethreatening myeloproliferative neoplasm for which there is no cure. This review will present a critical overview of evolving concepts in diagnosis and treatment of this disease.

doi:10.3324/haematol.2015.129155

Introduction Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/18

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

18

If I ask my daughter to give me three key dates in the history of Rome, I expect her to say: 753 BC (the foundation of the city), 44 BC (the murder of Julius Cesar) and 476 AD (the fall of the Roman Empire). If I am asked to provide three key dates for polycythemia vera (PV), I will say: 1892, the date of the first description by Louis Henri Vaquez which was then reinforced by William Osler's report in 1903,1 1951, when William Dameshek grouped together PV, myelofibrosis (MF) and essential thrombocythemia (ET) under the term “myeloproliferative disorders”,2 and 2005, when William Vainchenker,3 Tony Green,4 Ross Levine5 and Robert Kralovics6 independently described the JAK2V617F mutation. It is fascinating that the original speculation by Vaquez that PV was due to hematopoietic hyperactivity, and the illuminating hypothesis of Dameshek that all myeloproliferative disorders [now known as myeloproliferative neoplasms (MPN)]7 variably reflected increased proliferative activity of bone marrow (BM) cells “due to a hitherto undiscovered stimulus”,2 were both reconciled by the demonstration of abnormal activation of JAK/STAT signaling as the unifying pathogenetic mechanism. However, beyond these groundbreaking discoveries, the history of PV is punctuated by achievements that have contributed to various degrees to improve our understandhaematologica | 2017; 102(1)


Management of polycythemia vera

ing to the level of knowledge we have now. Table 1 lists some of these landmark studies; due to space constraints, I will not be able to address all of them in detail.

Evolving concepts in diagnosis Making a diagnosis of polycythemia vera The World Health Organization (WHO) recently released a revised classification of MPN in which important changes to the 2008 version were introduced (Table 2).8 In the 2008 version, the most compelling innovation had been the introduction of JAK2V617F and “similar” mutations (involving JAK2 exon 12 in 3%-4% of patients) as major diagnostic criteria.3-6 Although JAK2V617F mutation is associated with PV in more than 95% of cases, it does not represent a clear diagnosis since it is found also in 50%-60% of ET and PMF. However, the use of JAK2V617F as a marker of clonal myeloproliferation greatly facilitates the distinction of PV from reactive or congenital erythrocytosis. Considering that isotope-based assays for measuring red cell mass (RCM) and plasma volume are not routinely available even in most tertiary centers, the 2008 WHO classification listed a hemoglobin level more than 185 g/L and 165 g/L in men and women, respectively, as a strong surrogate marker of absolute increase of RCM. Since some PV patients do not fulfill such high levels, other criteria were added to facilitate diagnosis, including: 1) hemoglobin or hematocrit level that is more than 99th percentile of reference range for age, sex, or altitude of residence; 2) an RCM that is more than 25% above mean normal predicted value;

3) a hemoglobin level more than 170 g/L and 150 g/L in men and women, associated with a sustained increase of 20 g/L from baseline not attributable to correction of iron deficiency. According to the pragmatic British standards, hematocrit more than 52% in males and more than 48% in females, or an RCM more than 25% above predicted value, are sufficient to establish a diagnosis of PV if JAK2 mutation is present.9 However, a reassessment of how far the WHO criteria can be applied in a real-life setting raised the issue of JAK2V617F mutated patients with only a borderline increase in hemoglobin. It was shown that BM morphology, according to WHO guidelines, accurately reflected a condition of increased RCM, since all patients with increased RCM also had a BM morphology consistent with PV.10 In 140 such patients, Barbui et al. delineated a category operationally defined as “masked” PV11 that includes a majority of early cases, in which thrombocytosis is the initial disease manifestation, mimicking ET. Additional features that distinguish masked from overt PV include male predominance, higher incidence of arterial thrombosis and progression to post-PV myelofibrosis (PPV-MF) and acute leukemia (AL), resulting in inferior survival. Therefore, masked PV is a heterogeneous condition including early forms of PV as well as a distinct phenotype with a more aggressive course. The identification of masked PV might also reconcile differences in reported incidence of transformation of JAK2V617F mutated ET to PV.12-14 The best cut off for hemoglobin/hematocrit to discriminate JAK2V617F mutated ET from PV was set at 165 g/L/49% in males and 160 g/L/48% in females.15 These findings constituted the backbone for the 2016

Table 1. Landmark studies in understanding polycythemia vera and its diagnosis and management.

Domain

Field of investigation/Study

Findings / Comments

• • • •

• • • •

Natural history Description Classification Natural history Natural history

First description by L. Vaquez, first review by W. Osler1 W. Dameshek theorizes the concept of “myeloproliferative disorders”2 A cohort study on the natural history of PV by the Gruppo Italiano Studio Policitemia111 An international study on natural history of contemporary PV patients23

Pathophysiology • Clonality • • • •

EEC Molecular basis Molecular basis Molecular basis

• Involvement of a hematopoietic stem/progenitor cell established by analysis of G6PDH isoenzymes112 • Cytokine independent growth of erythroid progenitor cells16 • Description of the JAK2V617F mutation3-6 • Description of mutations in JAK2 exon 12113 • Occurrence of non-driver somatic mutations114

Diagnosis • PVSG criteria • WHO 2008 • WHO 2016

• Development of formal diagnostic criteria40 • Introduces JAK2 mutations as major diagnostic criteria7 • Introduces BM biopsy as major diagnostic criterion and adopts the concept of “masked” PV8

• • • • • • • •

• • • • • • • •

Management Thrombosis and hematocrit PVSG-01 trial PVSG-08 trial ECLAP trial CytoPV trial FPSG long-term trial Interferon study RESPONSE trial

Points to hematocrit >45% as main risk factor for thrombosis77 Use of phlebotomy; leukemogenic risk of 32P and chlorambucil39 Efficacy of hydroxyurea115 Low-dose aspirin for prevention of CV events55 Evidence-based setting of the optimal hematocrit level at <45%79 Leukemogenic risk with pipobroman41 First sound evidence of an impact of interferon on molecular remission86 Ruxolitinib for patients with resistance/intollerance to hydroxyurea73

G6PDH: glucose-6-phosphate dehydrogenase, an X-linked locus; EEC: endogenous erythroid colonies; CV: cardiovascular; PVSG: Polycythemia Vera Study Group; Cyto-PV: Cytoreductive Therapy in PV trial; ECLAP: European Collaboration on Low-dose Aspirin in PV trial; RESPONSE: Randomized Study of Efficacy and Safety in Polycythemia Vera with JAK Inhibitor INCB018424 versus Best Supportive Care; FPSG: French Polycythemia Study Group.

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revision of WHO criteria, where main changes regarded the threshold level of hemoglobin/hematocrit, the upgrade of BM biopsy to major criterion, and the abandonment of endogenous erythroid colony assay16 as minor criterion8 (Table 2). Subnormal erythropoietin levels remain the only accessory criterion, although in more than 20% of cases the levels fall within normal range. It has been argued that these novel criteria might promote an increased usage of BM biopsy in the diagnostic path of erythrocytosis. However, in JAK2 mutated cases that present hemoglobin levels fulfilling the 2008 criteria, biopsy is not required for diagnosis, although it may be recommended, especially in younger subjects, to assess initial fibrosis that predicts an accelerated progression to PPV-MF.17 Conversely, biopsy is mandatory when hemoglobin/hematocrit are at the lower threshold level set by the 2016 criteria, and early PV must be distinguished from JAK2V617F mutated ET. Misdiagnosis with ET would mean that many patients would only receive suboptimal control of hematocrit.18

Diagnosis of transformation to post-polycythemia vera myelofibrosis Post-polycythemia vera myelofibrosis (PPV-MF) represents a natural evolution of PV. Diagnostic criteria have been outlined by the International Working GroupMyeloproliferative neoplasms Research and Treatment (IWG-MRT) expert consensus (Table 3).19 The major criterion is the development of BM fibrosis grade 2 or higher (in the European scale;20 ≥grade 3 in the conventional scale21) in the context of a previous diagnosis of PV. It is worthy of note that the 2016 WHO revision enlists criteria for semiquantitative grading of BM fibrosis on a scale from 0 to 3. Additional variables, two of which are required to establish diagnosis, are: 1) anemia or sustained loss of need for phlebotomy and/or cytoreductive therapy; 2) leukoerythroblastic peripheral blood; 3) the new appearance, or progression, of splenomegaly; 4) development of constitutional symptom(s). Based on several small historical series (reviewed by Cerquozzi and Tefferi22) and a recent large study with

mature survival data,23 the median time to myelofibrosis transformation ranges from 8.5 to 20 years and the cumulating risk increases from 6% to 14% to 26% at 10, 15 and 20 years, after the initial diagnosis, respectively. Older age, leukocytosis, high JAK2V617F allele burden (that usually increases further along with transformation),24,25 splenomegaly and thrombocytosis have all been associated with increased risk of PPV-MF.23-26 More recently, the independent value of BM fibrosis at diagnosis of PV17 and the clinical phenotype of masked PV were recognized. Of 526 PV patients, 14% showed grade 1 fibrosis; this group was characterized by a higher prevalence of palpable splenomegaly and greater risk of progression to overt myelofibrosis [incidence rate (IR) 2.2 per 100 patient-years vs. 0.8 for those without fibrosis].17 Furthermore, the combined rate of transformation to PPV-MF and AL was significantly higher among patients with masked PV compared with overt PV (1.60 vs. 0.97 per 100 patient-years, respectively). Preliminary evidence suggests that chromosome 12 abnormalities are associated with a greater likelihood to progress to PPV-MF.27 Occurrence of PPV-MF signifies a dramatic shortening of PV survival to a median of approximately six years with an adjusted hazard ratio (HR) of 2.17.26 A longer (>10 years) duration of the chronic PV phase is also associated with shortened survival after transformation to PPV-MF (HR 2.26).28 According to a dynamic prognostic model, presence of any of 3 independent variables (anemia, thrombocytopenia and leukocytosis) resulted in a 4.2-fold increase in the risk of death; in particular, occurrence of anemia at PPV-MF was associated with shortened survival (1.9 vs. 6.6 years for non-anemic patients).26 However, in clinical practice, and in clinical trials,29,30 prognostication assessment of PPV-MF patients is usually performed with the International Prognostic Scoring System (IPSS) and the dynamic International Prognostic Scoring System (DIPSS), originally developed for PMF.31,32 In fact, these scores have not been

Table 3. The IWG-MRT recommended diagnostic criteria for post-polycythemia vera myelofibrosis.19 Table 2. The 2016 WHO revised diagnostic criteria for polycythemia vera.8 Major criteria: 1. Hemoglobin > 165 g/L or, Hematocrit > 49% in men Hemoglobin > 160 g/L or, Hematocrit > 48% in women or, increased red cell mass* 2. BM biopsy showing hypercellularity for age with trilineage growth (panmyelosis) including prominent erythroid, granulocytic and megakaryocytic proliferation with pleomorphic, mature megakaryocytes (differences in size)** 3. Presence of JAK2V617F or JAK2 exon 12 mutation Minor criterion: Subnormal serum erythropoietin level Diagnosis of PV requires meeting either all three major criteria, or the first two major criteria and the minor criterion** WHO: World Health Organization; BM: bone marrow; PV: polycythemia vera. *More than 25% above mean normal predicted value. **Criterion number 2 (BM biopsy) may not be required in cases with sustained absolute erythrocytosis: hemoglobin levels more than 185 g/L in men (hematocrit 55.5%) or more than 165 g/L in women (hematocrit 49.5%) if major criterion 3 and the minor criterion are present. However, initial myelofibrosis (present in up to 20% of patients) can only be detected by performing a BM biopsy; this finding may predict a more rapid progression to overt myelofibrosis (post-PV MF).

20

Required criteria: 1. Documentation of a previous diagnosis of PV as defined by the WHO criteria 2. BM fibrosis grade 2–3 (on 0–3 scale) or grade 3–4 (on 0–4 scale)* Additional criteria (two are required): 1. Anemia** or sustained loss of requirement for either phlebotomy (in the absence of cytoreductive therapy) or cytoreductive treatment for erythrocytosis 2. A leukoerythroblastic peripheral blood picture 3. Increasing splenomegaly, defined as either an increase in palpable splenomegaly of ≥ 5 cm (distance of tip of the spleen from LCM) or the appearance of a newly palpable splenomegaly 4. Development of ≥ 1 of 3 constitutional symptoms: > 10% weight loss in 6 months, night sweats, and unexplained fever (> 37.5°C) IWG-MRT: International Working Group for Myeloproliferative neoplasms Research and Treatment; PV: polycythemia vera; WHO: World Health Organization; BM: bone marrow; LCM: left costal margin. Diagnosis is made with the 2 required criteria plus 2 additional criteria. *Grade 2–3 according to the European classification20: diffuse, often coarse fiber network with no evidence of collagenization (negative trichrome stain) or diffuse, coarse fiber network with areas of collagenization (positive trichrome stain). Grade 3–4 according to the standard classification21: diffuse and dense increase in reticulin with extensive intersections, occasionally with only focal bundles of collagen and/or focal osteosclerosis or diffuse and dense increase in reticulin with extensive intersections with coarse bundles of collagen, often associated with significant osteosclerosis. **Below the reference range for appropriate age, sex, and altitude considerations.

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validated in PPV-MF and they may not perform adequately in distinguishing different risk categories.28,33 Finally, although the mutation landscape of PPV-MF has similarities with PMF,34 in contrast with PMF, little impact of mutations on prognosis was demonstrated.28

Diagnosis of transformation to blast phase A consensus has been achieved as to the definition of accelerated and blast phase disease in PV (and other MPN) as being characterized by peripheral or BM blast percentages of 11%-19% and more than 20%, respectively.35 Rate of transformation to AL is estimated at 2%, 5%, and more than 10% at 10, 15 and 20 years.23,36 Risk factors for leukemic transformation include advanced age, leukocytosis, splenomegaly and abnormal karyotype.22,23 There is no specific molecular marker that is predictive of blast transformation; interestingly, leukemic blasts may result JAK2 wild type, suggesting the emergence of an unrelated leukemic clone.37 The promoting role of cytotoxic therapy in the events leading to blast transformation of PV remains a subject of major debate.38 The leukemogenic potential of 32P and alkylating agents (chlorambucil and pipobroman) was demon-

strated by the PVSG39,40 and the French Polycythemia Study Group.41 The randomized PVSG-01 study reported an excess of late-appearing AL in patients treated either with chlorambucil or 32P (13.2% and 9.6%, respectively) compared with phlebotomy (1.5%).39 The latest update after a median follow up of 16 years of a French study that randomized PV patients under 65 years of age to receive pipobroman or hydroxyurea as first-line therapy reported significantly shorter survival in the pipobroman group (15.4 years vs. 20.3 years for patients treated with hydroxyurea) and significantly higher cumulative incidence of leukemia (13%, 34% and 52% vs. 6.6%, 16.5%, 24% for hydroxyurea, at 10, 15 and 20 years), although transformation to PPV-MF was lower in the pipobroman group (21% vs. 32% at 20 years).41 Similar findings were reported in a retrospective cohort of more than 1500 patients with PV;23 in this study, the use of hydroxyurea or busulphan alone was not burdened with increased leukemia rate, similar to findings of the prospective ECLAP cohort.42 However, the use of 2 or more cytotoxic agents, including hydroxyurea, was associated with a 2.9 increased odds of leukemia.43 Although it is not possible to verify whether such an increased rate of transformation in patients receiving multiple lines of thera-

Figure 1. The burden of disease in a patient with polycythemia vera. Shown is the famous drawing Uomo Vitruviano of Leonardo da Vinci (1490), named after the ancient roman architect Vitruvius. Here the ideal man is represented as perfectly inscribed in both a square and a circle. In the figure, this concept is used to signify the appropriateness of a modern approach to the patient with PV that ideally takes into account the multiplicity of aspects associated with the disease.

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py is directly caused by drugs or rather reflects a more aggressive disease, the decision to shift to second-line therapy in patients previously treated with hydroxyurea must consider the risk associated with the use of multiple cytotoxic agents. In this regard, there is no evidence of a leukemogenic effect of interferon.44 Furthermore, in a nested-case control study of 162 MPN patients, of which the majority (68%) were PV, 25% of those who transformed to AL had never been exposed to cytotoxic therapy, thereby reinforcing the contention that individual genetic characteristics are themselves causative of the inherent propensity of PV to transform to AL or myelodysplastic syndrome (MDS).43

Evolving concepts in understanding predisposition to polycythemia vera Polycythemia vera, as all MPN, shows a familial aggregation whereby it has been calculated that first-degree relatives have a 5-7-fold higher risk of developing an MPN in comparison to the general population.45,46 Clinical presentation, rate of thrombosis and survival of familial cases are similar to sporadic MPN.46,47 The JAK2V617F mutation is acquired somatically in familial cases of PV as in sporadic patients. The genetic basis of familial aggregation of MPN have not yet been clarified, although it is likely that patients inherit some predisposition to acquire one of the driver mutations.46 In sporadic cases, the JAK2 46/1 haplotype has been associated with the acquisition of JAK2V617F mutation.48,49 A high incidence of PV among Ashkenazi Jewish descent has been described,50 but there are no clues as to genetic background. No association between an excess risk of PV and blood donation or donation frequency has been observed in a study involving 1.4 million donors,51 refuting previous reports in smaller series.52

Evolving concepts in patient management Risk stratification Polycythemia vera is associated with reduced life expectancy, primarily because of hematologic progression and cardiovascular events.23,36,53 Analysis of the most mature survival data clearly shows the shorter life expectancy. Among 337 patients followed at the Mayo Clinic, of whom 44% died, median survival was 14.1 years; significantly shorter than the control population.23 Risk factors for overall survival independent of the cause included advanced age, leukocytosis, venous thrombosis, and abnormal karyotype.

Median survival was 10.9 and 27.8 years in high- and lowrisk patients, respectively23 (Table 4). However, this score is not used for decision making in clinical practice. Approximately 15% of patients with PV may experience a thrombotic event during the disease course. Major thrombotic events are transient ischemic attacks, stroke, myocardial infarction, deep venous thrombosis or pulmonary embolism, peripheral arterial and venous thrombosis. Microvascular symptoms, such as hearing or visual impairments, paresthesia, or headache, are common. Venous thrombosis in unusual sites, particularly the splanchnic veins (SVT; portal, mesenteric, splenic), Budd-Chiari syndrome, thrombosis of the cerebral venous sinuses and central retinal vein are more frequent than in the general population. History of thrombosis is the main risk factor for recurrent cardiovascular events that occurred in the same vessel district as the first event in 75% and 61% of arterial and venous thrombosis, respectively;54 history of hypertension predicts for arterial thrombosis and advanced age predicts for venous thrombosis. The frequency of arterial (16%) and venous (7.4%) thrombosis in 1818 patients diagnosed in the last decade was lower than in previous historical cohorts, including the ECLAP study (27% and 11%, respectively),55,56 but was similar to the contemporary CytoPV study (arterial 17%, venous 12%) and the Swedish registry.57 However, it is remarkable that while a reduction of thromboses from 4.01 to 2.93 per 100 patient-years was seen in the “high-risk” category, the rate of vascular events was unchanged in the “low-risk” category (2.03 vs. 2.24), thereby suggesting some under-treatment of these conventionally-defined low-risk subjects.58 This is supported by the unexpected higher rate of thrombosis in young patients (age < 40 years) with masked PV compared with overt PV (3.01 vs. 1.99 per 100 patient-years, respectively). In multivariate analysis, the only factor accounting for such a difference was the less frequent use of phlebotomies and cytoreduction in younger patients with masked PV.18 The current risk stratification, informing therapeutic decisions, is designed to estimate the likelihood of developing thrombotic complications, and not necessarily the overall survival (Table 4). Age of 60 years or over and history of previous thrombosis are used to classify patients into a low(neither present) or high- (either present) risk category. An important element for risk stratifıcation is the comprehensive assessment of additional risk factors for thromboembolism, including smoking,59 hypertension, diabetes, abnormal lipid levels, and obesity. The individual should be made aware of the value of a healthy life style in minimizing thrombotic risk, and encouraged to adopt appropriate

Table 4. Criteria used for risk stratification in polycythemia vera.

Criteria Thrombotic risk56 Shortened survival risk23

Thrombosis

22

Variables

Risk categories

Used for riskadopted therapy

• Age > 60 • Previous thrombosis • Age (57-66 years = 2 points) (≥ 67 years = 5 points) • Leukocytes > 15x109/L (= 1 point) • Venous thrombosis (= 1 point) • Leukocytosis59 • JAK2V617F allele burden60 • Generic cardiovascular risk factors59

• Low (neither present) • High (either present) • Low (0 points) • Intermediate (1-2 points) • High (> 3 points)

Yes No

Not yet formally included in risk scores

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measures to correct bad habits. However, generic cardiovascular risk factors, as well as leukocytosis59 and higher JAK2V617F allele burden,60 that have all been associated with higher risk of thrombosis, are not formally integrated into current scores.

Recognizing the burden associated with disease Although symptoms typically associated with PV have been well known since initial descriptions, it is only recently that a full appreciation of their complexity, extent and impact has been acknowledged.61 Components of the disease-associated burden include symptomatic manifestations (especially, but not limited to, fatigue, pruritus, symptoms due to splenomegaly, constitutional symptoms), reduced quality of life, the emotional impact, the financial impact of increased healthcare utilization and impaired incomes. Pruritus, typically acquagenic, is the most frequent and disabling complaint of patients with PV, and is reported in up to 70% of cases.62 In extreme situations (approx. 15%)63 it causes severe disruption of the individual's lifestyle, inducing sleep disturbances, depression, and impaired working capabilities and social relationships. In a recent landmark study into MPN in the United States that interviewed 380 PV patients undergoing treatment, fatigue and itching were identified by 33% and 9% of the respondents as the symptom they most urgently wanted to resolve.64 The pathogenetic link between symptoms and clonal myeloproliferation is likely sustained by an abnormal release and signaling of inflammatory cytokines through the deranged JAK/STAT pathway,65 a concept that is reinforced by the unique and rapid symptomatic efficacy of the JAK1 and JAK2 inhibitor ruxolitinib.66 To add to the burden associated with PV, one must consider the side effects of treatment, including worsening of fatigue and other signs of iron deficiency in heavily phlebotomized patients, varying manifestations of intolerance

to hydroxyurea, the known toxicities of interferon, the increased Herpes Zoster reactivation with ruxolitinib, to name but a few. Presence of splenomegaly, use of hydroxyurea, and phlebotomy requirement are all independently associated with a substantial symptom burden.67 Interestingly, a high symptomatic burden may occur independently of conventional risk categories; therefore, some low-risk patients might remain under-managed according to current recommendations.67 Another component of the PV-associated burden is the high incidence of co-existing hematologic or solid cancers. In a study including 353 PV patients, a 3.44-fold increased risk of lymphoproliferative neoplasms, especially chronic lymphocytic leukemia, compared with the general population, was reported.68 Among 2000 MPN patients from cancer registries, the prevalence of all types of cancer was higher than in the general population; in PV patients there was a significantly higher risk of malignant skin melanoma.69 It is remarkable that recognition of disease-associated burden, and the development of standardized approaches for its quantification,70-72 such as the Myeloproliferative Neoplasm Symptomatic Assessment Form (MPN-SAF),70 have been fostered by the development of JAK2 inhibitors that proved unforeseen efficacy to ameliorate symptomatic manifestations of MPN.29,30,66 It is worthy of note that such scores have been integrated into the pivotal study leading to approval of the use of ruxolitinib in PV.73

Defining end points for treatment According to the European Leukemia Net (ELN) consensus criteria, the goals of therapy in patients with PV are to reduce the risk of first and/or recurrent thrombosis, prevent bleeding events, minimize the risk of evolution to PPV-MF and AML, and ameliorate the symptom burden.74 Revised response criteria were released recently by the ELN and IWG-MRT75 (Table 5). Three levels of responses are enlist-

Table 5. Response criteria for polycythemia vera according to the ELN and IWG-MRT consensus.75 Complete remission A Durable* resolution of disease-related signs including palpable hepatosplenomegaly, large symptoms improvement† AND B Durable* peripheral blood count remission, defined as Ht lower than 45% without phlebotomies; platelet count < 400x109/L, WBC count < 10x109/L, AND C Without progressive disease, and absence of any hemorrhagic or thrombotic event, AND D Bone marrow histological remission defined as the presence of age-adjusted normocellularity and disappearance of trilinear hyperplasia, and absence of > grade 1 reticulin fibrosis Partial remission A Durable* resolution of disease-related signs including palpable hepatosplenomegaly, large symptoms improvement† AND B Durable* peripheral blood count remission, defined as Ht lower than 45% without phlebotomies; platelet count < 400x109/L, WBC count < 10x109/L, AND C Without progressive disease, and absence of any hemorrhagic or thrombotic event, AND D Without bone marrow histological remission defined as persistence of trilinear hyperplasia. No response Any response that does not satisfy partial remission Progressive disease Transformation into post-PV myelofibrosis, myelodysplastic syndrome or acute leukemia ELN: European LeukemiaNet; IWG-MRT: International Working Group-Myeloproliferative neoplasms Research and Treatment; Ht: hematocrit; WBC: white blood cell count; PV: polycythemia vera.*Lasting at least 12 weeks. †Large improvement in symptom(s) (≥10-point decrease) in MPN-SAF TSS.10 Molecular response is not required for assignment as complete response or partial response. Molecular response evaluation requires analysis in peripheral blood granulocytes. Complete response is defined as eradication of a pre-existing abnormality. Partial response applies only to patients with at least 20% mutant allele burden at baseline. Partial response is defined as 50% or more decrease in allele burden.

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ed: complete response, partial response and no response. The variables included regard the categories of clinicohematologic response (CHR, including normalization of blood counts and spleen volume, and resolution of diseaserelated symptoms), molecular response, and BM histology response. The rationale to maintain separate categories of response was the fact that there was no evidence that available therapies alter the natural course of disease. Therefore, while in clinical studies of new therapeutics it might be worthwhile to address the achievement of a molecular or histological response, these are not relevant in patients receiving standard treatments. In fact, the ELN criteria were developed mainly to allow for a reproducible design and interpretation of clinical trials rather than for routine practice. Most patients with PV receiving conventional treatment at best fulfill the criteria of partial response,76 although most of those treated with interferon-a may achieve a CHR (but not necessarily resolution of splenomegaly and/or symptoms) and some also achieve a molecular response. In a retrospective study of PV patients managed with hydroxyurea and followed for four years, no association was seen between achievement of an ELN response and survival or vascular complications.76 These findings, although biased by the retrospective characteristics and the small size of the study population, raise concerns about the real-life impact of the ELN response criteria, and identify the need for their prospective evaluation, as well as a search for more powerful surrogate markers of clinical benefit. Interestingly, in the above cited MPN landmark study, the most important treatment goals reported by patients were slowing/delaying disease progression (25%), prevention of thrombosis (24%), normalization of normal blood counts (18%), better quality of life (12%), symptomatic improvement (9%) and maintaining a hematocrit level less than 45% (6%).64

Evolving concepts in the treatment of patients with PV The basic concept: risk-adopted cytoreductive therapy The current treatment recommendations for patients with PV rely on a few randomized studies and several consensus/clinical practice indications. The first objective of treatment is to reduce the hematocrit and associated blood viscosity to minimize the risk of thrombosis. In a seminal observational study, Pearson reported that the incidence of thrombosis directly increased with hematocrit above a level of 45%.77 This study claimed this level of hematocrit

to be the optimal target for management, but a survey of the practice patterns of American Society of Hematology members revealed that, in practice, such a hematocrit threshold was used by only a minority of physicians while 16% preferred to adopt a target of 50%.78 It took almost 40 years to make the transition from an observation/recommendation to an evidence-based guideline. The CytoPV study randomly assigned 365 PV patients, irrespective of risk category (approx. one-third were low-risk) and treatment (phlebotomy, hydroxyurea, or both), to a target level of less than 45% or 45%-50%.79 Results indicated that patients in the higher hematocrit level had a 4-times increased rate of death from cardiovascular events in comparison to those maintained at less than 45%.79 A lower hematocrit level (ideally <42%) may be indicated (but not formally proven) in women80 and/or in cases of SVT, where RBC volume expansion is masked by hemodilution. How to maintain the target hematocrit level depends on the risk category. For low-risk patients, phlebotomy is still the cornerstone of treatment. For patients at high risk, cytoreduction with hydroxyurea or interferon-a is recommended. Cytoreduction is also indicated in low-risk patients to control progressive leukocytosis (no threshold formally identified) and thrombocytosis (usually above 11.5 million/mm3), symptomatic splenomegaly and/or disabling symptoms. In the non-randomized PVSG-08 study81 that included 51 treatment-naĂŻve patients, use of hydroxyurea was associated with a significantly lower rate of thrombosis compared with the phlebotomy arm of the PVSG-01 study (6.6% vs. 14% at 2 years).40 There is growing interest in the use of interferon-a as first-line agent. The mechanisms by which interferon-a induces responses in PV have not yet been clarified. Interferon has pleiotropic activities, including effects on immune modulatory cells, inhibition of apoptosis, induced expression of pro-apoptotic genes, a direct antiproliferative effect on hematopoietic progenitor and possibly stem cells (reviewed by Kiladjian et al.82). The efficacy of interferon-a in inducing hematologic remission in PV was first reported in 199883 (up-dated by Silver84) and confirmed in several small studies.82 Two larger independent studies85,86 and one sponsored87 phase II study with different preparations of pegylated interferon-a were reported. These studies confirmed drug efficacy in inducing prompt and sustained hematologic responses, eventually associated with improvement of symptoms and splenomegaly. Furthermore, in most patients, a substantial decrease of JAK2 mutant burden, usually after the first year of treat-

Table 6. Definition of resistance/intolerance to hydroxyurea in polycythemia vera according to the ELN consensus.92 1. Need of phlebotomy to keep ht <45% after 3 months of at least 2 g/day of hydroxyurea, OR 2. Uncontrolled myeloproliferation, i.e. platelet count >400x109/L AND WBC >10x109/L after 3 months of at least 2 g/day of hydroxyurea, OR 3. Failure to reduce massive* splenomegaly by more than 50% as measured by palpation, OR failure to completely relieve symptoms related to splenomegaly after 3 months of at least 2 g/day of hydroxyurea, OR 4. Absolute neutrophil <1x109/L OR platelet count <100x109/L OR hemoglobin <100 g/L at the lowest dose of hydroxyurea required to achieve a complete or partial clinico-hematologic response#, OR 5. Presence of leg ulcers or other unacceptable hydroxyurea-related non-hematologic toxicities, such as mucocutaneous manifestations, gastrointestinal symptoms, pneumonitis or fever at any dose of hydroxyurea ELN: European LeukemiaNet; Ht: hematocrit; WBC: white blood cell count.*Organ extending by more than 10 cm from the costal margin. #Complete response was defined as: hematocrit less than 45% without phlebotomy, platelet count â&#x2030;¤400x109/L, WBCâ&#x2030;¤10x109/L or under, and no disease-related symptoms. Partial response was defined as: hematocrit less than 45% without phlebotomy, or response in three or more of the other criteria.

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ment and including also complete responses, was documented, although this was not found in other studies.88,89 Toxicity is lower with pegylated over conventional preparations of interferon, and a mono-pegylated interferon that requires less frequent administrations might improve tolerability.87 However, approximately 20% of the patients stop interferon in the first year due to toxicity. Interestingly, interferon-a is not approved for the treatment of PV. Two randomized studies are ongoing, one with interferon-a 2a (sponsored by the Myeloproliferative Disorders-Research Consortium; registered at clinicaltrials.gov identifier: 01259856), the other with pegylated interferon-a 2b (the company sponsored PROUD-PV study; registered at clinicaltrials.gov identifier: 1949805), both compared with hydroxyurea. Results of these studies might eventually provide the missing evidence to support an evidence-based use of interferon as first-line agent; hopefully this will lead to its approval for clinical use.

Second-line therapy: JAK2 inhibition Most patients do pretty well with hydroxyurea for the entire duration of their disease; however, 15%-20% develop some intolerance or become resistant to the drug over time.90,91 A set of consensus criteria are commonly used to identify resistant or intolerant patients.92 The development of cytopenias at the lowest dose of hydroxyurea needed to achieve a response was retrospectively associated with an increased risk of death and transformation to PPV-MF and AL.90 Patients who are not adequately controlled with therapy or who develop an intolerance do not have many options. In the case of intolerance, one common practice approach is to reduce the daily dose to the best tolerated one and make more generous use of phlebotomies to maintain the target hematocrit. However, too many phlebotomies are not well tolerated and may cause symptomatic iron deficiency. One may switch from hydroxyurea to interferon, although this is not supported by formal studies; vice versa hydroxyurea can be used if interferon is not tolerated or effective. The use of an alternative cytotoxic agent must be evaluated carefully, particularly in younger subjects, due to the increased risk of leukemia associated with alkylating agents after hydroxyurea.42,43 Recently, the JAK1 and JAK2 inhibitor ruxolitinib has been approved for the treatment of patients with PV who are refractory to, or intolerant of, hydroxyurea based on the results of the phase III RESPONSE trial that enrolled PV patients with baseline splenomegaly and phlebotomy dependence.73 The study demonstrated superiority of ruxolitinib versus best-available therapy (BAT) in controlling hematocrit without phlebotomy and reduction of enlarged spleen volume (the composite primary end point of the study, reached by 22.7% vs. 0.9% of the patients); hematocrit and spleen volume responses were maintained in 89% and 98% of patients, respectively, at a median of 111 weeks of exposure.93 Less phlebotomies were required in the ruxolitinib arm to maintain hematocrit less than 45%, and the number of cardiovascular events was lower (1.8 vs. 8.2 in BAT per 100 patient-years); however, this end point was not statistically controlled, and interpretation of the findings remains problematic. These results were largely in line with those of the phase II study66 and have been further confirmed in the phase III RESPONSE II study that enrolled patients with similar characteristics but without palpable splenomegaly.94 Patients receiving ruxolitinib had significant improvement of the MPN-SAF total symptom score that concerned all indihaematologica | 2017; 102(1)

vidual symptoms related to splenomegaly, inflammatory cytokines and microvascular abnormalities, unlike patients receiving BAT who experienced no change or even a worsening of symptoms. Treatment was usually well tolerated with 82.7% of patients initially randomized to ruxolitinib still on therapy at the 80-week update.93 However, patients receiving ruxolitinib experienced more frequent reactivation of Herpes Zoster infections (6.4% vs. 0 in BAT, mostly grade 1-2) and more non-melanoma skin cancers (4.4 vs. 2.0 in BAT per 100-patient years; however, most cases developed in patients with prior history of skin cancers), indicating that active surveillance is required in daily practice and in longterm follow-up analysis.

The unmet needs and perspectives for the future Diagnostic criteria: too relaxed, too selective? Early diagnosis of PV is of the utmost importance to minimize the risk of thrombosis through the prompt adoption of measures to control hematocrit, institution of antiplatelet therapy, and correction of cardiovascular risk factors. Thanks to the availability of genetic tests for JAK2 mutation, and the revised WHO 2016 criteria, early diagnosis is possible. Although the use of the lower threshold levels of hemoglobin set by the 2016 criteria might result in some inappropriate investigations in subjects with modest, yet sustained, increased hemoglobin without obvious reason, â&#x20AC;&#x153;Paris is worth a massâ&#x20AC;?, and potentially preventing thrombosis with prompt institution of therapy justifies the additional costs.

How to manage the risk of disease progression Due to a greater knowledge of disease pathophysiology, earlier diagnosis and improved management, it might be assumed that the median survival of patients with PV will continue to improve mainly because of a reduction of lifethreatening thrombosis.36,56 Conversely, disappointingly, the rate of progression to PPV-MF or AML/MDS has remained unchanged over the years. Although some clinical and molecular (p53,95,96 IDH1 and 2 mutations97,98) variables have been associated with increased risk of PPV-MF and AML/MDS, none is specific enough to be clinically useful. Furthermore, it has been argued that, because of the intrinsically low pace of progression, development of PPV-MF may occur well before the worsening of fibrosis to the grade 2 or more required by IWG-MRT criteria.99 There is, therefore, the possibility that appropriate treatment, including JAK inhibitors or stem cell transplantation, is delayed in some patients. Given this, diagnosis of PPV-MF should not be restrained by the degree of fibrosis, and novel diagnostic criteria, ideally supported by hitherto unknown biomarkers, are needed. The genetic profile of AL after PV differs from de novo leukemia for the notable absence of typical abnormalities, including FLT3 and NPM-1. Survival from post-PV AL is dismal, with a median of 3-5 months from diagnosis,100,101 and no medical therapy, including induction chemotherapy and ruxolitinib, provided evidence of efficacy,102,103 although stem cell transplantation is a curative option in a few patients. Therefore, understanding the molecular basis of transformation that will help identify surrogate markers and develop effective therapeutic strategies represent urgent unmet needs. Notably, very few clinical studies have been conducted, or indeed planned, in this clinical setting. 25


A.M. Vannucchi

The trouble with inheritance in a somatic disease An extensive family history should be obtained during the diagnostic workup in any PV patient. The knowledge that PV, like other MPNs, may cluster in the family is a cause of great concern for parents of PV patients. Increased knowledge of the genetic basis of MPN and screening of family members might in the future allow early disease phases to be identified. However, at present, parents should be discouraged from performing unnecessary tests in otherwise healthy offspring, including driver mutations or germline variants such as the 46/1 allele.

Who is the “patient in need of treatment”? The risk-adopted criteria in use for therapy do not formally account for additional variables that impact on thrombosis rate, beyond history and age, as well as for the residual approximate 2-fold risk over controls in conventionally low-risk patients. Quantitative assessment of the symptomatic burden might allow patients to be better categorized and has been widely used in clinical trials. However, how to implement these tools in practice and how to use such information for therapeutic decision making remain challenging issues. Therefore, it is urgent to develop a definition of patients with “inadequately controlled disease” who need to be shifted to second-line treatment, including ruxolitinib, a highly effective, but costly, therapy.104 Patients who continue to have symptoms that are difficult to manage, or who manifest progressive symptomatic splenomegaly or progressive leukocytosis/thrombocytosis, or develop unacceptable toxicities with their current therapy, may obviously belong to that category of patients for whom alternative treatment is required. However, the most important indicator of an inadequately controlled PV in terms of thrombosis and survival is the hematocrit level.79 Unfortunately, there is as yet no consensus on what is the “acceptable” rate of phlebotomies required, either alone (in low-risk patients) or combined with cytoreduction (in highrisk patients) to maintain the target level of hematocrit. Furthermore, it was shown that patients with phlebotomy requirements present a substantial symptomatic burden.67 Just based on the ELN criteria, need of (any) phlebotomy after three months on an optimal dose of hydroxyurea would per se be evidence of resistance to treatment, and therefore of an inadequately controlled disease.92 However, there is no hard evidence that this concept might be translated into the clinical practice. Timely action from the scientific community to develop consensus criteria of what constitutes an “inadequately controlled PV” is needed.

Antithrombotic prophylaxis: low-dose aspirin, anticoagulation, or both? Evidence from the ECLAP trial55 led to the recommendation of low-dose aspirin in all PV patients (unless contraindicated) and this has certainly contributed to the improvement in outcome that has been observed since. However, the rate of recurrent thrombosis, and the residual risk in low-risk patients, remain unsatisfactorily high, and should prompt studies of novel approaches for both primary and secondary prophylaxis. From studies in non-PV patients, it might be assumed that twice daily aspirin is more efficacious against arterial, and possibly venous, thrombosis, than once daily, but this still has to be proved, as does the added value of combination therapy with oral anticoagulants in patients with a history of venous events. The duration of anticoagulant prophylaxis in certain conditions, such 26

as SVT or pulmonary embolism, the added value of statins, and the role of new direct oral anticoagulant are all questions that need to be addressed in prospective studies.105

Do we want or need molecular remission? The BCR-ABL negativization produced by imatinib and other TKIs in chronic myelogenous leukemia represents the holy grail for PV, too. However, it must be emphasized that reduction/elimination of the JAK2V617F allele might not necessarily be indicative of cure, since other mutated clones preceding JAK2V617F acquisition, and also hematologic abnormalities, may persist even in patients with complete molecular remissions induced by interferon106 and ruxolitinib.107 Therefore, while elimination of JAK2V617F mutated cells certainly constitutes a goal for novel therapies, the impact of molecular responses on the natural history of disease remains uncertain and further studies are required.

What’s available? Ruxolitinib is the first and only JAK2 inhibitor approved for second-line treatment in PV; a phase II study with another JAK2 inhibitor, momelotinib, is ongoing (clinicaltrials.gov identifier: 019898828). An alternative class of potentially active drugs is made up by the histone deacethylase inhibitors. Vorinostat was poorly tolerated, with 44% of patients discontinuing treatment early.108 Givinostat proved promising in a phase II study for control of hematocrit and symptoms,109 and was also tested in combination with hydroxyurea in patients who were refractory to this drug, producing responses in approximately half.110 A phase Ib/II study to assess the safety and tolerability, and preliminary efficacy, in PV patients (clinicaltrials.gov identifier: 01901432) is ongoing. Overall, not much is available and the shelf is quite empty. Novel molecular insights are urgently needed to boost pharmacological research.

Personalized medicine for PV: “what’s in a word?” After the discovery of aberrantly activated JAK/STAT signaling as the basic pathogenetic defect, PV has potentially entered the arena of personalized medicine. However, it remains uncertain how to transfer this new information into the daily management of the individual patient. Current therapeutic decisions are dictated by the needs of the individual patient and/or are based on predictive clinical variables, such as age and history of thrombosis that are not ‘druggable’, rather than by the disease itself. There is some evidence of a ‘cure’, but we still do not know how big an impact it might have on long term-outcome, as compared to optimized disease management, or how expensive it would be (in terms of side effects and money) to get it. Since new drugs may be more effective than conventional ones, but are not without toxicity and are costly, predictive biomarkers need to be identified. In the meanwhile, fostering basic research, producing evidence-based data and developing evidence-based recommendations seem to be the most productive approach to move towards personalized management of patients with PV. Acknowledgments This work was supported by a grant from the Associazione Italiana per la Ricerca sul Cancro (AIRC; Milan, Italy), Special Program Molecular Clinical Oncology 5x1000 to AIRC-Gruppo Italiano Malattie Mieloproliferative (AGIMM) project #1005. I apologize to the many colleagues whose work could not be cited due to space constraints. haematologica | 2017; 102(1)


Management of polycythemia vera

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neoplasms (MPN) acute myeloid leukemia (AML). Blood. 2012;119(20):4614-4618. 104. Reiter A, Harrison C. How We Identify and Manage Patients with Inadequately Controlled Polycythemia Vera. Curr Hematol Malig Rep. 2016 Feb 19 [Epub ahead of print]. 105. Kreher S, Ochsenreither S, Trappe R, et al. Prophylaxis and management of venous thromboembolism in patients with myeloproliferative neoplasms: consensus statement of the Haemostasis Working Party of the German Society of Hematology and Oncology (DGHO), the Austrian Society of Hematology and Oncology (Ă&#x2013;GHO) and Society of Thrombosis and Haemostasis Research (GTH e.V.). Ann Hematol. 2014;93(12):1953-1963. 106. Kiladjian JJ, Masse A, Cassinat B, et al. Clonal analysis of erythroid progenitors suggests that pegylated interferon [alpha]-2a treatment targets JAK2V617F clones without affecting TET2 mutant cells. Leukemia. 2010;24(8):1519-1523. 107. Pieri L, Pancrazzi A, Pacilli A, et al. JAK2V617F complete molecular remission in polycythemia vera/essential thrombocythemia patients treated with ruxolitinib. Blood. 2015;125(21):3352-3353. 108. Andersen CL, McMullin MF, Ejerblad E, et al. A phase II study of vorinostat (MK-0683) in patients with polycythaemia vera and essential thrombocythaemia. Br J Haematol. 2013;162(4):498-508.

109. Rambaldi A, Dellacasa CM, Finazzi G, et al. A pilot study of the Histone-Deacetylase inhibitor Givinostat in patients with JAK2V617F positive chronic myeloproliferative neoplasms. Br J Haematol. 2010;150 (4):446-455. 110. Finazzi G, Vannucchi AM, Martinelli V, et al. A phase II study of Givinostat in combination with hydroxycarbamide in patients with polycythaemia vera unresponsive to hydroxycarbamide monotherapy. Br J Haematol. 2013;161(5):688-694. 111. Policitemia GIS. Polycythemia vera: the natural history of 1213 patients followed for 20 years. Gruppo Italiano Studio Policitemia. Ann Intern Med. 1995;123(9):656-664. 112. Adamson JW, Fialkow PJ, Murphy S, Prchal JF, Steinmann L. Polycythemia vera: stem-cell and probable clonal origin of the disease. N Engl J Med. 1976;295(17):913-916. 113. Scott LM, Tong W, Levine RL, et al. JAK2 exon 12 mutations in polycythemia vera and idiopathic erythrocytosis. N Engl J Med. 2007;356(5):459-468. 114. Vainchenker W, Delhommeau F, Constantinescu SN, Bernard OA. New mutations and pathogenesis of myeloproliferative neoplasms. Blood. 2011;118(7): 1723-1735. 115. Fruchtman SM, Mack K, Kaplan ME, Peterson P, Berk PD, Wasserman LR. From efficacy to safety: a Polycythemia Vera Study group report on hydroxyurea in patients with polycythemia vera. Semin Hematol. 1997;34(1):17-23.

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REVIEW ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

The emerging role of immune checkpoint inhibition in malignant lymphoma

Ida Hude,1 Stephanie Sasse,2 Andreas Engert2 and Paul J. BrĂśckelmann2

Department of Internal Medicine, Division of Hematology, University Hospital Center Zagreb, Croatia and 2Department I of Internal Medicine and German Hodgkin Study Group (GHSG), University Hospital of Cologne, Germany

1

Haematologica 2017 Volume 102(1):30-42

ABSTRACT

T

Correspondence: paul.broeckelmann@uk-koeln.de

Received: July 15, 2016. Accepted: August 19, 2016. Pre-published: November 24, 2016. doi:10.3324/haematol.2016.150656

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/30

Š2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

30

o evade elimination by the host immune system, tumor cells commonly exploit physiological immune checkpoint pathways, restraining efficient anti-tumor immune cell function. Growing understanding of the complex dialog between tumor cells and their microenvironment contributed to the development of immune checkpoint inhibitors. This innovative strategy has demonstrated paradigmshifting clinical activity in various malignancies. Antibodies targeting programmed death 1 and cytotoxic T-lymphocyte-associated protein-4 are also being investigated in lymphoid malignancies with varying levels of activity and a favorable toxicity profile. To date, evaluated only in the setting of relapsed or refractory disease, anti-programmed death 1 antibodies such as nivolumab and pembrolizumab show encouraging response rates particularly in classical Hodgkin lymphoma but also in follicular lymphoma and diffuse-large B-cell lymphoma. As the first immune checkpoint inhibitor in lymphoma, nivolumab was approved for the treatment of relapsed or refractory classical Hodgkin lymphoma by the Food and Drug Administration in May 2016. In this review, we assess the role of the pathways involved and potential rationale of checkpoint inhibition in various lymphoid malignancies. In addition to data from current clinical trials, immune-related side effects, potential limitations and future perspectives including promising combinatory approaches with immune checkpoint inhibition are discussed.

Introduction Even though malignant lymphomas are still considered rare diseases, their incidence has increased over time, so that there are now more than 250.000 new cases per year worldwide, accounting for about 3% of all cancer-related deaths.1 Lymphoma represents a diverse group of malignancies with distinct clinical, histopathological, and molecular features, as well as heterogeneous outcomes after standard therapy. About 90% of adult lymphomas derive from mature B cells, with the rest being derived from T and natural killer cells.2 Up until the end of the 20th century, treatment for malignant lymphoma relied mainly on combination cytotoxic chemotherapies, with or without additional radiotherapy. Treatment outcomes were often not satisfactory and associated with significant short- and long-term morbidity and mortality. The introduction of targeted therapy changed the therapeutic landscape of malignant lymphoma with the advent of monoclonal antibodies targeting surface antigens on malignant cells. In particular, the anti-CD20 antibody rituximab, targeting CD20 in B-cell non-Hodgkin lymphoma (NHL), but also the anti-CD30 antibody-drug-conjugate brentuximab-vedotin (BV) in classical Hodgkin lymphoma (cHL) and T-cell lymphoma, led to higher response rates and prolonged survival in first-line or relapsed/refractory (r/r) disease, while showing acceptable safety profiles.3-6 Nevertheless, a significant number of patients still undergo multiple lines of treatment, including high-dose chemotherapy and stem cell transplantation (SCT) haematologica | 2017; 102(1)


Checkpoint inhibition in lymphoma

with limited outcome due to r/r disease or therapy-associated toxicities. On the other hand, growing insights into the molecular biology of lymphoma have contributed to the development of innovative therapies in recent years: drugs such as kinase inhibitors blocking the aberrant B-cell receptor pathways, or immunomodulators such as lenalidomide obtained regulatory approval for treatment of certain NHL entities after promising activity had been shown in pivotal clinical trials.7 More recently, an improved understanding of the interplay between malignant cells and the tumor microenvironment, as well as evasion of the host immune response, has led to identification of new targets in cancer therapy. The idea of harnessing the host immune system to combat cancer effectively has led to the development of agents that target immune checkpoint signaling pathways, enhance T-cell cytotoxic activity and subsequently induce tumor cell lysis. This groundbreaking immunotherapeutic approach has produced exciting results in different malignancies and many clinical trials are currently ongoing or underway to explore immune checkpoint inhibition (ICI) further. The aim of this review is to elaborate on the biology of clinically relevant immune checkpoints, discuss early clinical results with ICI in different lymphoma subtypes, as well as to address potential limitations, current challenges and the future role of ICI in clinical practice.

Immune checkpoints The biology of immune checkpoints has been thoroughly reviewed elsewhere.8,9 In brief, naïve T cells become

activated after recognizing a unique peptide presented by antigen-presenting cells, via interaction of major histocompatibility complex molecules on antigen-presenting cells with the T-cell receptor, and a co-stimulatory signal. Activating signals are finely modulated by a complex network of inhibitory receptors, referred to as checkpoint molecules.10 The main function of these molecules is to prevent destructive immune responses, particularly in the presence of chronic infections and inflammation, as well as to maintain peripheral self-tolerance. Tumor cells are capable of evading immunosurveillance by over-expressing the ligands of checkpoint receptors, bringing T cells to a state of non-responsiveness or exhaustion.11,12 Therapeutic manipulation of these pathways by ICI reverses T-cell anergy, facilitating an effective T-cell-mediated antitumor response. Recently, the cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) and programmed death-1 (PD-1) pathways have been the major focus, with several other pathways also described.10 CTLA-4 is expressed on activated T cells and plays a crucial role in the priming phase of an immune response thereby representing a prototype for ICI. As depicted in Figure 1, inhibition of this pathway allows co-stimulatory signaling and generates antitumor T-cell responses by inhibiting the interaction between CTLA-4 and B7 (the CTLA-4 ligand on, for example, antigen-presenting cells).8 One such inhibitor is ipilimumab (Bristol-Myers Squibb), a fully human monoclonal IgG1κ antibody. Its efficacy and the resulting survival benefit led to international approval for its use as first-line treatment of advanced

Figure 1. Inhibition of the immune checkpoints PD-1 and CTLA4 to restore T-cell activation. Antigen-presenting cells (APC) present an antigen (e.g., tumor-associated antigen – TAA) to naïve T cells via interaction of T-cell receptor (TCR) and major histocompatibility 1 (MHC-I) molecule, followed by a co-stimulatory signal by CD28/B7-2 interaction, which leads to Tcell activation. The activation is followed by expression of inhibitory checkpoint molecules such as PD-1 and CTLA-4 on T cells. In an immunosuppressive lymph node microenvironment, APC express corresponding inhibitory ligands, bringing T cells to an inactivated or anergic state (via the CTLA4/B7-1 and/or PD-1/PD-L1/L2 interaction). If co-stimulatory signals overpower the co-inhibitory ones, activated effector T cells are released into the blood stream, where they encounter TAA presented on MHC-I molecules on tumor cells. Coexpression of PD-L1 on tumor cells induces inactivation of tumor-specific effector T cells, disabling adequate T-cellmediated immune responses. Treatment with immune checkpoint inhibitors (ICI) affects both the priming phase of T-cell activation in lymph nodes and the effector phase in the tumor microenvironment (TME), by blocking the inhibitory checkpoint interaction between activated T cells and APC and/or tumor cells, restoring Tcell activity and leading to T-cell-mediated tumor cell lysis. TCR: T-cell receptor; MHCI: major histocompatibility complex; PD-1: programmed cell death protein 1; PD-L1: programmed death-ligand 1; PD-L2: programmed death-ligand 2; CTLA-4: cytotoxic T-lymphocyte-associated protein 4.

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I. Hude et al.

melanoma.13,14 Clinical results of ipilimumab in other malignancies,15 as well as results of a second anti-CTLA-4 antibody (tremelimumab; Medimmune/Astra Zeneca) have so far been modest and these drugs are undergoing further clinical investigation. PD-1 is another inhibitory receptor expressed on activated T cells. It plays a central role in regulating the effector phase of the immune response via its interaction with two ligands, PD-L1 and PD-L2. PD-L1 is expressed on many malignant cells as well as hematopoietic cells and peripheral tissues, while the expression of PD-L2 is mostly restricted to hematopoietic cells as shown in Figure 1.16 Currently, various antibodies against PD1 and PD-L1 are under clinical evaluation in different malignancies. The anti-PD-1 antibodies nivolumab (a human IgG4 antibody; Bristol-Meyers Squibb/Ono) and pembrolizumab (a humanized IgG4 antibody; Merck) obtained approval from the Food and Drug Administration (and partially from the European Medicines Agency) for use in advanced melanoma, non-small-cell lung carcinoma, and renal-cell cancer. In addition, nivolumab has recently also been approved in the USA for r/r cHL.17,18 Novel checkpoint tar-

gets such as OX-40, LAG-3 and KIR (a natural killer-cell inhibitory receptor) are also currently under investigation (Figure 2). Inhibition of the PD1/PD1-L and the CTLA-4/B7 pathways in malignant lymphoma has been evaluated in early phase clinical trials. Hereafter, the preclinical rationale and results of recent trials (Table 1) are discussed by lymphoma type.

Hodgkin lymphoma Hodgkin lymphoma (HL), consisting of a small number of Hodgkin and Reed-Sternberg (HRS) tumor cells surrounded by an abundant, yet ineffective inflammatory immune-cell infiltrate, is considered a typical example of an ineffective anti-tumor immune response.2,19 Preclinical data indicate that the PD-1/PD-L pathway contributes significantly to the immunosuppressive microenvironment of cHL. PD-1 is expressed on tumor-infiltrating and peripheral T cells in patients with cHL,20,21 whereas PD-ligands are frequently expressed by HRS cells22,23 and tumorinfiltrating macrophages.24 PD-L genes have been shown to be key targets of structural amplification of chromo-

Figure 2. Potential targets of ICI on lymphocytes and tumor cells. (A) Activated T cells (and natural killer cells to a certain extent) express multiple co-stimulatory and co-inhibitory checkpoint molecules on their surface, all of which are potential targets for immunomodulation by checkpoint agonists (co-stimulatory molecules) or inhibitors (co-inhibitory molecules). (B) Tumor cells evade the host immune system by expressing ligands for co-inhibitory checkpoint molecules on T cells, hence targeting these ligands leads to inactivation of inhibitory pathways and reactivation of tumor-specific T cells. TCR: T-cell receptor; MHC-I: major histocompatibility complex I; TAA: tumor-associated antigen; LAG-3: lymphocyte-activation gene 3; CTLA-4: cytotoxic T-lymphocyte-associated protein 4; PD-1: programmed cell death protein 1; TIM-3: T-cell immunoglobulin and mucin-domain containing-3; TIGIT: T-cell immunoreceptor with Ig and ITIM domains; BTLA: B- and Tlymphocyte attenuator; VISTA: V-domain immunoglobulin suppressor of T-cell activation; KIR: killer cell immunoglobulin-like receptor; ICOS: inducible T-cell co-stimulator; GITR: glucocorticoid-induced TNFR-related protein; HVEM: Herpesvirus entry mediator, PD-L1: programmed death-ligand 1; PD-L2: programmed death-ligand 2.

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Checkpoint inhibition in lymphoma

Table 1. Early phase clinical trial data for ICI according to lymphoma type.

Lymphoma

Agent

Ref.

ipilimumab

(30)

ipilimumab + BV (31)

Phase Disease setting I

r/r HL after allogeneic SCT

I/II

r/r HL

nivolumab

(18, 32)

I

r/r HL

nivolumab

(33)

II

r/r HL

pembrolizumab

(36)

Ib

r/r HL (failing BV)

pembrolizumab

(37)

II

r/r HL

ipilimumab

(46)

I

r/r B-NHL

nivolumab

(47)

I

r/r lymphoid malignancies

pembrolizumab

(48)

Ib

PMBCL

nivolumab

(47)

I

r/r lymphoid malignancies

pembrolizumab

(67)

II

r/r CLL (including RS)

HL

DLBCL + PMBCL

FL

CLL

No of Pts

Treatment plan

Outcome

Safety

Most common AE

14

dose esc. trial: 0.1 mg/kg ORR: 14% no Gr 3/4 GvHD fatigue 0.33 mg/kg - 0.66 mg/kg CR: 14% 1 pt Gr 4 pneumonitis chills/ fever 1.0 mg/kg - 3.0 mg/kg no TRD abdominal pain 23 dose esc. trial: IPI 1 mg/kg - ORR: 72% 100% any AE neuropathy 3 mg/kg Q21d x 4 doses CR: 50% 1 pt Gr 4 AE (thrombocytopenia) nausea/ BV: 1.8 mg/kg Q21d x median PFS: 1.02y no TRD vomiting 16 doses fatigue pruritus/rash 23 3 mg/kg NIVO at week 1 ORR: 87% 1 pt Gr 3 pneumonitis rash/pruritus and 4, Q2w thereafter until 2y CR: 22% 1 pt Gr 3 colitis hypothyroidism median OS and PFS diarrhea not reached after 101m FU 1.5y OS 83% 801 3 mg/kg Q2w ORR: 66% 90% any AE hypothyroidism/ CR: 8,8% 1 TRD thyreoiditis PR: 57,5% 25% Gr 3/4 AE rash ORR (no BV hypersensitivity response)*: 72% 31 10 mg/kg Q2w/2y ORR: 65% no Gr 4 AE hypothyroidism CR: 16% 5 pt Gr 3 AE diarrhea PR: 48% nausea/vomiting 24w PFS 69% pneumonitis 902 200 mg Q3w cohort 1: ORR 73%, 4% Gr 4 AE pyrexia CR 27%, PR 47% no TRD diarrhea cohort 2: ORR 83%, 7 pt Gr AE CR 30%, PR 53% cohort 3: ORR 73%, CR 30%, PR 43% 3 DLBCL dose level 1: 1 CR 5 pt Gr 3 AE (diarrhea) fatigue 3 mg/kg once DOR > 31 months no Gr 4 or TRD diarrhea + 1 mg/kg Q1m x3 abdominal pain dose level 2: 3 mg/kg thrombocytopenia Q1m x4 11 DLBCL + dose level 1: DLBCL: CR 18%, PR all AE 71%3 fatigue 2 PMBCL 1 mg/kg at w 1 and 4, 18%, SD 27%, Gr 3-5 AE: pneumonitis, pneumonitis thereafter Q2w/2y Median PFS 7w ARDS, dermatitis, pruritus/rash dose level 2: 3 mg/kg at PMBCL: SD 100% diplopia, enteritis, w 1 and 4, thereafter Q2w/2y eosinophilia, mucosal inflammation, pyrexia, vomiting 16 10 mg/kg Q2W ORR: 37,5% 62% TR AE decreased apetite, or 200 mg Q3W/2y CR: 6,25% 1 pt Gr 3 AE (neutropenia) nausea PR: 31,25% no Gr 4 AE, no TRD fatigue diarrhea hypothyroidism 3 10 FL dose level 1: ORR: 40% any AE 72% of pt fatigue 1 mg/kg Q2w/2y CR: 10% Gr 3-5 AE: pneumonitis, ARDS, pneumonitis dose level 2: 3 mg/kg Q2w/2y PR: 30% dermatitis, diplopia, enteritis, pruritus/rash Median PFS eosinophilia, mucosal not reached inflammation, pyrexia, vomiting 16, 200 mg Q3w ORR: 57% 2 pt Gr 3 AE dyspnea 7 evaluable CR: 14% no Gr 4, no TRD anemia PR: 14% 2 responses before PD

Gr: grade; ARDS: acute respiratory distress syndrome; IP: ipilimumab; NIVO: nivolumabBV; brentuximab-vedotin; R: rituximab; r/r: relapsed/refractory; autoSCT: autologous stem cell transplantation; RS: Richter syndrome; PMBCL: primary mediastinal B-cell lymphoma; esc.: escalation; pt: patient(s); TR: treatment-related; TRD: treatment-related death; AE: adverse event; ORR: overall response rate; CR: complete remission; PR: partial remission; PD: progressive disease; m: month(s); w: week(s); DOR: duration of response; PFS: progression-free survival; OS: overall survival; QXd: every X days; QXw: every X weeks; QXm: every X months. 1Results from cohort B: r/r cHL pts who received BV after failing prior autoSCT; 230 pts in cohort 1 (r/r cHL after autologous SCT and subsequent BV therapy), 30 in cohort 2 (r/r cHL ineligible for autologous SCT due to chemo-resistance, no response to salvage chemotherapy and prior BV therapy) and 30 in cohort 3 (r/r cHL after autologous SCT without subsequent BV therapy). 3Adverse events reported for all B-NHL patients enrolled (31 pts).

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some 9p24.1, a recurrent genetic abnormality in cHL. Extended amplification of the 9p24.1 region also induces expression of the Janus kinase 2 (JAK2) protein whose activity further induces PDL expression via JAK2/STAT signaling.22 In addition, Epstein-Barr virus infection has been demonstrated as an alternative, mutually exclusive, mechanism of PD-L1 induction,23 consistent with the ability of the virus to usurp the PD-1 pathway.16 A recent retrospective analysis in first-line cHL biopsies suggests a correlation between advanced stage disease and a negative prognostic impact of 9p24.1 amplification.25 In another immunohistochemical study, PD-1 expression on tumorinfiltrating lymphocytes was suggested as a stage-independent negative prognostic factor for overall survival (OS) in cHL,26 while others found only rare PD-1-positive tumor-infiltrating lymphocytes.27 According to two phase I trials investigating the safety and activity of anti-PD1 antibodies in r/r HL, over 90% of the examined patientsâ&#x20AC;&#x2122; samples showed strong expression of PD-L1 on HRS cells, with rather low PD-1 expression on tumor-infiltrating lymphocytes.18,28 Taking these discrepant data into account, relevant predictive factors for treatment outcome with anti-PD1 antibodies are still unknown. Other potential immune escape mechanisms including the CTLA-4 pathway have been described in cHL29 and it is thought that these mechanisms contribute to the rather low graftversus-lymphoma effect in cHL after allogeneic SCT. The first checkpoint inhibitor tested in HL was ipilimumab administered as a single dose in a phase I trial to 14 r/r HL patients after allogeneic SCT. The drug was well tolerated, with no cases of relevant graft-versus-host disease (GvHD) and two patients achieved a complete remission (CR).30 Preliminary results of a NCI-sponsored phase I/II trial testing 3 mg/kg ipilimumab in combination with 1.8 mg/kg BV in r/r cHL showed an overall response rate (ORR) of 72% with a 50% CR rate in 18 evaluable patients.31 More recently, two early phase trials with anti-PD1 antibodies in r/r HL patients reported encouraging results: the dose-escalation phase I trial of nivolumab included 23 intensively pretreated r/r cHL patients and the ORR was 87%.18 In the updated report with a median follow-up of 101 weeks, the median progression-free survival (PFS) was not reached with a 1.5-year overall survival rate of 83%.32 CR was observed in 22% of the patients, but partial remissions (PR) seem to be durable with 13 patients remaining in stable remission without further treatment. Treatment-related adverse events were observed in 78% of patients, with 22% having grade 3 or 4 events. Preliminary results of a phase II trial in r/r cHL patients who had relapsed after autologous SCT and BV, presented at EHA and ASCO 2016, depicted an ORR of 66% based on central review and of 72% based on investigator evaluation after a median follow-up of 8.9 months, with 51 out of 80 patients still receiving treatment at the time of the data cut-off.33 Interestingly, a high ORR of 72% was observed among 43 patients without prior response to BV. Drug-related adverse events occurred in 90% of patients, with 25% grade 3â&#x20AC;&#x201C;4 adverse events and one non-treatment-related grade 5 multi-organ failure. Of note, correlative questionnaires suggested substantial improvement in quality of life after initiation of treatment. As far as allogeneic SCT is concerned, preclinical data suggested that anti-PD-1 antibodies might contribute to significant GvHD.34 Severe GvHD was documented in 34

patients undergoing allogeneic SCT after treatment with nivolumab in the phase I trial. In contrast, recent results of a cohort receiving nivolumab for r/r cHL after allogeneic SCT suggested a more acceptable safety profile: acute GvHD was recorded in three patients, all of whom already had a history of acute GvHD after allogeneic SCT.35 Among 14 patients evaluated at the time of reporting, the ORR was 92.7% with six patients achieving a CR. Pembrolizumab is being evaluated in an ongoing phase Ib trial in patients with different r/r hematologic malignancies who had failed prior treatment, were refractory to or refused autologous SCT. The ORR among the 31 r/r cHL patients in whom prior BV treatment had failed was 65% and included five patients who achieved a CR (16%). The 24- and 52-week PFS rates were 69% and 46%, respectively. Similarly to nivolumab, treatment was well tolerated, with grade 3 drug-related adverse events reported in five patients and no grade 4 adverse events or treatment-related deaths.36 Preliminary results of a multicohort phase II trial in r/r HL patients were presented at EHA and ASCO 2016. The results showed promising activity: in cohort 1 (r/r HL after autologous SCT and BV), cohort 2 (ineligible for autologous SCT after BV) and cohort 3 (r/r HL after autologous SCT without BV) investigator-based ORR of 73%, 83% and 73%, respectively, were reported.37

Large B-cell lymphoma Unlike on HRS cells, PD-L1 overexpression is not commonly seen on B NHL cells. PD-L1 overexpression has been described in the more aggressive, non-germinal center Bcell-like type of diffuse large B-cell lymphoma (DLBCL),38 in which it was recently also found to be a predictor of poor OS.39 The ratio of CD4*CD8 to (CD163:CD68 [M2])*PD-L1 in histopathological samples of DLBCL patients treated with R-CHOP also indicated differences in OS.40 Interestingly, soluble plasma PD-L1 (sPD-L1), measured prior to treatment in newly diagnosed DLBCL patients, has also been found to correlate with poorer 3-year OS in multivariate analysis.41 Of note, serum-levels of sPD-L1 decreased significantly in patients achieving a CR and were attributed to an immunological effect of treatment, suggesting that sPD-L1 levels mirror the host anti-immune response, rather than the specific presence of malignant cells. This hypothesis is supported by a poor correlation of sPD-L1 and tumor PD-L1 expression in this cohort of patients. The aforementioned 9p24.1 alterations responsible for PD-L1/L2 upregulation in cHL have also been observed in specific subsets of large B-cell lymphoma such as primary mediastinal but also primary testicular lymphoma and primary central nervous system DLBCL.42-44 Furthermore, the PD-L1/PD-L2 locus was identified as a recurrent translocation partner for immunoglobulin heavy chain locus, a hallmark of DLBCL, by whole genome sequencing analysis. Interestingly, these cytogenetic alterations were more frequently observed in the non-germinal center B-cell-like type of DLBCL.45 Even though the role of the CTLA-4 pathway in DLBCL remains unclear, ipilimumab was the first checkpoint inhibitor investigated in this malignancy. The dose-escalation phase I trial of ipilimumab in 18 patients with r/r B-cell NHL included three cases with DLBCL. Two out of the 18 patients had clinical responses and one with DLBCL achieved a durable CR lasting more than 31 months. Analysis of post-treatment samples showed T-cell proliferhaematologica | 2017; 102(1)


Checkpoint inhibition in lymphoma

ation in response to recall antigens after ipilimumab treatment in five of the 16 evaluated cases (31%).46 A phase I trial of nivolumab monotherapy recruited patients with heavily pretreated r/r lymphoid malignancies including 11 patients with DLBCL.47 Four patients (36%) responded (2 CR and 2 PR) and three (27%) had stable disease (SD) with a median PFS of 7 weeks. A comparable ORR of 37.5% with a tolerable safety profile was recently reported in heavily pretreated patients with r/r primary mediastinal large B-cell lymphoma receiving pembrolizumab.48

Mantle cell lymphoma Preclinical data suggest that mantle cell lymphoma (MCL) cells evade the host immune response by inducing several microenvironmental changes. In a study investigating BNHL biopsy tissues including two MCL cases, intratumoral T regulatory cells were shown to inhibit proliferation and cytokine production of CD4+CD25â&#x20AC;&#x201C; T cells by the PD-1/PDL1 interaction.49 PD-L1 expressed by MCL cell lines results in impaired T-cell proliferation after tumor exposure, impaired T-cell-mediated tumor cytotoxicity and inhibited specific anti-tumor T-cell responses.50 So far, data available on ICI in MCL are limited: in the aforementioned ipilimumab phase I study,46 the only MCL patient included did not respond to treatment. In contrast, a PR was observed in a single MCL patient treated with ipilimumab for relapse after allogeneic SCT.30 Four MCL patients treated with nivolumab did not respond.47 Results of currently ongoing combination trials with nivolumab and ipilimumab or anti-KIR therapy are pending (Table 2). In addition to the clinical efficacy of single-agent brutonkinase inhibition in MCL,50,51 combinations of ibrutinib and ICI look appealing, in light of the immunomodulatory effect targeting interleukin-2-inducible T-cell kinase.52

Follicular lymphoma Preclinical studies described an immunosuppressive microenvironment as the key component of disease sustainability and progression in follicular lymphoma (FL).49,53 Moreover, the gene expression signature of non-malignant stromal cells is prognostically more relevant than the neoplastic B cells themselves. While a tumor-infiltrating lymphocyte gene expression signature seems to be associated with a favorable outcome, a signature enriched for genes expressed by macrophages and dendritic cells implies poor survival, suggesting that the complex dialog within the tumor microenvironment also plays a crucial role in FL.54 Despite several attempts at translating these findings into immunohistochemical studies and clinical practice, results are still inconclusive.55,56 Similarily, attempts to distinguish the prognostic impact of PD-1 expression in the FL tumor microenvironement on survival have resulted in controversial findings, possibly due to technical issues and different prior treatment regimens including different rituximab utilization within the tested cohorts.57-59 Ten FL patients were included in a phase I study of nivolumab in a variety of r/r hematologic malignancies;47 the ORR was 40% and three responses were ongoing after a median follow-up of 91.4 weeks, which encouraged further clinical trials.

Chronic lymphocytic leukemia Immune dysfunction is common among patients with chronic lymphocytic leukemia (CLL), who may have profound defects in the function of T cells, which eventually haematologica | 2017; 102(1)

develop an exhausted phenotype, resulting in both failure of anti-tumor effectiveness and increased susceptibility to infections. T cells isolated from CLL patients have higher expression of checkpoint molecules such as CTLA-4 and PD-1.60,61 The cellsâ&#x20AC;&#x2122; cytotoxic and proliferating capacities are reduced, but they maintain the ability to produce cytokines.62 Unlike the situation in most hematologic malignancies, PD-1 is expressed on both T and CLL cells, while PD-L1 is also highly expressed in the different compartments of the tumor microenvironment, including CLL cells.61,63 Preclinical data on anti-PD-1 effects in CLL demonstrated restored CD8 T-cell cytotoxicity, immune synapse formation and prevention of CLL development in TCL-1 mouse models.64,65 These observations and other preclinical data suggesting the importance of additional immune checkpoint pathways66 provide a strong rationale for investigating immunomodulating therapies in CLL. A phase I trial of ipilimumab did not show that the drug had efficacy as monotherapy in CLL patients.30 On the other hand, preliminary results of an ongoing phase II trial of pembrolizumab in r/r CLL patients, including those with Richter syndrome, showed an ORR of 21% in 20 evaluable patients. Responses, including one CR, were documented in three patients with Richter syndrome and also in patients in whom prior ibrutinib therapy had failed. Treatment seemed to be well tolerated, with two patients developing grade 3 adverse events. Correlative studies indicate that sPD-L1 might be a biomarker for response to treatment.67 After the combination of ibrutinib and an anti-PD-L1 antibody showed synergistic effects in a mouse model resistant to either agent given alone,52 several combination clinical trials in CLL are underway.

Other lymphoma There are limited data on the efficacy of ICI in other Bcell malignancies. Due to the rapid clinical course of disease, it is questionable whether monotherapy with ICI is adequate in more aggressive lymphoma subtypes such as Burkitt lymphoma. However, preclinical evidence indicates that some patients with virus-associated aggressive lymphomas might benefit from such treatment: retroviral infection is known to upregulate immune checkpoint pathways68 and recent evidence shows that PD-1 blockade might be efficient in controlling human immunodeficiency virus infection.69 This renders anti-PD-1 antibodies interesting agents in human immunodeficiency virus-associated lymphomas, e.g. as part of combinatory therapies to induce host immune restitution, anti-retroviral and antitumor effects. Other virus-related lymphomas (i.e. Epstein-Barr virus- or hepatitis C virus-related)24,70 might be susceptible to a similar approach. As far as T-cell lymphomas (TCL) are concerned, a phase I trial with nivolumab included five patients with peripheral TCL and 18 with other TCL and obtained an ORR of 17% (2 patients with peripheral TCL and 2 with mycosis fungoides achieved a PR).47 Encouraged by these results and preclinical data confirming PD-1 and PD-L1 expression in peripheral TCL,71,72 further studies are currently underway. It is feasible to anticipate that these patients, like those with MCL and indolent lymphoma, might benefit more from combination treatments with other agents. Table 2 provides an overview of the numerous currently ongoing phase I and phase II trials investigating ICI as monotherapy or in combinatory approaches in lymphoid malignancies. 35


I. Hude et al. Table 2. Selection of currently ongoing clinical trials with ICI in lymphoma (clinicaltrials.gov as of 1st of June, 2016).

Trial N. (Name)

Malignancies

NCT02254772 NCT01729806 NCT00586391 NCT01919619 NCT02581631 (CheckMate 436) NCT02681631 (CPIT001) NCT02518958 (PRIMETIME) NCT01896999

r/r low grade NHL r/r B-NHL r/r B-NHL, CLL, ALL leukemia and lymphoma, after SCT r/r NHL, CD30 positive high risk and or r/r lymphoma/myeloma solid tumors + lymphoma r/r HL

NCT02631746 NCT02758717 NCT02038946 (Checkmate 140) NCT02572167 NCT02038933 (CheckMate 139) NCT02181738 (CheckMate 205) NCT02253992 NCT01592370

NCT01822509 NCT02327078 NCT02329847 NCT02362997 NCT02446457 NCT02541565 NCT02332980

NCT02677155 (Lyuvac-2)

NCT01953692 (Keynote 13) NCT02576990 (Keynote 170) NCT02501473 NCT02650990 NCT02684292 (Keynote 204) NCT02453594 (Keynote 87) NCT0266560 NCT02779101 NCT02595866 NCT02362035 (Keynote 145) NCT02178722 (Keynote 155) NCT02684617 (Keynote 155) NCT02243578 NCT02220842 NCT02779896 NCT02631577

Agent/Procedure

ipilimumab + SD-101 + RTx ipilimumab + R ipilimumab + CD19-CAR-T-cells ipilimumab + lenalidomide nivolumab + BV ipilimumab + nivolumab nivolumab + RRX-001 ipilimumab + nivolumab + BV ipilimumab + BV nivolumab + BV adult HTLV-assoc. T-cell lymphoma/leukemia nivolumab HL (first line) nivolumab + BV r/r FL nivolumab r/r HL (second line) nivolumab + BV r/r DLBCL nivolumab cHL (r/r cohorts A,B,C, first line cohort D) nivolumab nivolumab + AVD solid tumors + r/r B-NHL nivolumab + urelumab NHL, HL, multiple myeloma nivolumab nivolumab + ipilimumab nivolumab + lirilumab relapsed hematologic malignancies ipilimumab or nivolumab after allogeneic SCT multiple nivolumab + epacadostat CLL, FL, DLBCL nivolumab + ibrutinib r/r HL, r/r DLBCL pembrolizumab (consolidation after autoSCT) relapsed FL pembrolizumab + R DLBCL (first line) pembrolizumab + R-CHOP r/r CLL or low-grade NHL pembrolizumab pembrolizumab + ibrutinib pembrolizumab + idelalisib FL (first line or relapse) pembrolizumab + R + Rtx + dendritic-cell autotransplantation (intra-tumoral) + GM-CSF multiple hematologic malignancies pembrolizumab pembrolizumab + lenalidomide (DLBCL) r/r PMBCL pembrolizumab low grade NHL pembrolizumab + G100 r/r DLBCL, MCL pembrolizumab (after antiCD19 failure) r/r HL pembrolizumab vs. BV r/r HL pembrolizumab r/r HL pembrolizumab + AFM13 recurrent /progressive PCNSL pembrolizumab r/r or disseminated HIV-related malignancies pembrolizumab multiple hematologic malignancies pembrolizumab + ACP-196 DLBCL, solid tumors pembrolizumab, epacadostat r/r CLL, DLBCL, multiple myeloma pembrolizumab + dinaciclib r/r mycosis fungoides and Sezary syndrome pembrolizumab r/r FL and DLBCL atezolizumab + obinutuzumab r/r FL and DLBCL atezolizumab + obinutuzumab + polatuzumab-vedotin r/r FL atezolizumab + obinutuzumab + lenalidomide

Immunological Target

Phase

CTLA-4, TLR9a CTLA-4, CD20 CTLA-4, CAR-T-cells CTLA-4 PD-1, CD30 CTLA-4, PD-1 PD-1 CTLA-4, PD1, CD30

I/II I I/II I I/II I/II I I

PD-1 PD-1, CD30 PD-1 PD-1, CD30 PD-1 PD-1

II II II I/II I II

PD-1, CD 137 PD-1, CTLA-4, KIR

I/II I

CTLA-4, PD-1

I

PD-1, IDO PD-1 PD-1 PD-1, CD20 PD-1, CD20 PD-1

I/II I/II II II II II

PD-1, CD20

II

PD-1, CD20

I

PD-1 PD-1, TLR-4 PD-1

II I/II I/II

PD-1, CD30 PD-1 PD-1, CD30/CD16A PD-1 PD-1 PD-1 PD-1, IDO PD-1 PD-1 PD-L1, CD20 PD-L1, CD20, CD79

III II I II I I/II I/II I II I/II I/II

PD-L1, CD20

I/II continued on the next page

36

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Checkpoint inhibition in lymphoma continued from the previous page

NCT02596971

FL and DLBCL - first line or r/r

NCT02603419 NCT02643303

r/r HL advanced, biopsy accessible tumors (including cutaneus T-cell NHL)

NCT02733042 (Fusion NHL)

r/r B-NHL or high-risk CLL

NCT02549651

r/r DLBCL

NCT02706405

r/r B-NHL

NCT02401048 NCT02205333

r/r FL, DLBCL advanced solid tumors, DLBCL

NCT02061761

r/r CLL, HL, NHL

NCT01775631 NCT01471210 NCT02481297 NCT02271945

r/r B-NHL r/r B-NHL, advanced solid tumors r/r or high-risk CLL r/r agressive B-NHL

atezolizumab + obinutuzumab + bendamustine atezolizumab + obinutuzumab + CHOP maintenance: atezolizumab maintenance: atezolizumab + obinutuzumab avelumab durvalumab(i.v.) tremelimumab (i.v. or intra-tumoral) poly ICLC (intra-tumoral/i.m.) durvalumab monotherapy, durvalumab + Ibrutinib durvalumab + R + lenalidomide durvalumab + R + bendamustine durvalumab durvalumab + tremelimumab durvalumab + AZD9150 durvalumab + JCAR014 cyclophosphamide + fludarabine durvalumab + ibrutinib MEDI6469 MEDI6469 + tremelimumab MEDI6469 + R anti-LAG-3 anti-LAG-3 + nivolumab urelumab + R urelumab lirilumab + R AMP-514 + MEDI-551

PD-L1, CD20

Ib

PD-L1 Ib PD-L1, CTLA-4, TME modulator I/II

PD-L1, CD20

I/II

PD-L1, CTLA-4

I

PD-L1, CAR-T-cells

Ib

PD-L1 OX40, CTLA4, CD20

I/II Ib/II

LAG-3, PD-1

I/II

CD137, CD20 CD137 KIR, CD20 PD-1, CD19

I I II Ib/II

PMBCL: primary mediastinal large B-cell lymphoma; PCNSL: primary central nervous system lymphoma; RTx: radiotherapy; R: rituximab; CAR: chimeric antigen receptor; AVD: doxorubicin, vinblastine, dacarbazine; GM-CSF: granulocyte-macrophage colony-stimulating factor.

Toxicity of immune checkpoint inhibition Engaging the host immune system by ICI is associated with specific immune-related adverse events that had not been typical for traditional anti-cancer therapy so far. As a result of generalized immune activation, immune-related adverse events affecting practically every tissue have been described.73 These side effects commonly involve the skin (vitiligo, rash, pruritus), gastrointestinal tract (diarrhea, colitis), liver (hepatitis) and endocrine glands (hypophysitis, thyroiditis, adrenal insufficiency). Reports from several phase III trials evaluating antiCTLA-4 antibodies in different malignancies demonstrated a 61-90% incidence of immune-related adverse events, with 15-43% being grade 3 or higher. Skin toxicities, especially vitiligo and diffuse rash, are most common and develop 3-4 weeks after the initiation of treatment. Most adverse events are manageable with topical corticosteroids and oral antipruritic agents, but sporadic lifethreatening cases of Steven-Johnson syndrome and toxic epidermal necrolysis have been reported.74 Gastrointestinal toxicities such as diarrhea and colitis develop after 6-7 weeks and are of major clinical concern with anti-CTLA-4 therapy. They share features with Crohn disease, seem to be dose-related, and have been reported as causes of treatment-related deaths.13,75,76 Endocrinopathies mostly occur about 9 weeks after starting treatment and their reported incidence is up to 18%. Hypophysitis has been quite frequently associated with haematologica | 2017; 102(1)

ipilimumab.77 Thyroid dysfunction has also been commonly reported, with hypothyroidism occurring more often than hyperthyroidism77 and consequent hormonal deficiencies often require long-term hormone supplementation. Usually asymptomatic, pancreatic and hepatic enzyme elevations have been described, in rare cases manifesting as hepatitis with fever, malaise and abdominal pain. Rarer toxicities of anti-CTLA-4 treatment include neurological, renal and pulmonary side effects.74 Comparing monotherapy with anti-PD-1 or anti-CTLA4 antibodies, anti-PD-1 treatment seems to cause fewer high-grade events. A meta-analysis of immune-related adverse events presented at ASCO 2016 found significantly higher toxicity rates among patients receiving antiCTLA-4 than among those receiving anti-PD-1 or anti-PDL1 antibodies (P<0.0001). Furthermore, the rates of highgrade (3-5) adverse events was significantly higher with anti-CTLA-4 therapy than with other ICI.78 The spectrum of reported toxicities is rather similar. Even though maculopapular rash is a common dermatologic adverse effect of inhibiting both pathways, vitiligo seems to occur more frequently with anti-PD-1 treatment.79 On the other hand, diarrhea, colitis and hepatic toxicities, as well as severe endocrinopathies are less frequently reported.73 Immunerelated pneumonitis occurs in <5% of patients with antiPD-1 monotherapy, but severe clinical presentations and cases of treatment-related death make this complication an utmost concern of many clinicians.80 Combinations of 37


I. Hude et al.

anti-CTLA-4 and anti-PD-1 antibodies are associated with higher rates of treatment-related toxicities, as well as increased rates of high-grade toxicities, including pneumonitis.81 In respect to checkpoint inhibition in lymphoma, severe immune-related adverse events have so far been rare. Diarrhea has been reported frequently (56%) among patients receiving ipilimumab,46 with 28% of these patients developing grade 3-4 adverse events. Among patients with relapsed NHL receiving nivolumab within a phase Ib trial, 4% developed grade 3-5 pneumonitis47 and newly developed myelodysplastic syndrome was noted in one heavily-pretreated r/r cHL patient.32 The occurrence of low-grade pancytopenia has been substantial in several studies,32,46 with rare or no grade 3-4 events. Another adverse event is fatigue, which has been reported to occur in 13-56% of patients, mostly at grade 1-2.32,46 Another immune-related adverse event of particular interest is the development or worsening of GvHD after allogeneic SCT in a subset of patients. After favorable results from preclinical studies,82 the idea of applying ICI to enhance graft-versus-tumor effects after allogeneic SCT led to ICI usage in trials and practice. A single dose of ipilimumab in patients who relapsed after allogeneic SCT appeared to be safe with no case of severe GvHD reported among 29 patients.30 A French study of nivolumab in r/r cHL after allogeneic SCT reported limited toxicity and no cases of significant GvHD,35 which is in contrast to preliminary results of an ongoing trial of ipilimumab in relapsed malignancies after allogeneic SCT reported at ASH 2015.83 This trial included 28 patients, five of whom had drugrelated toxicities leading to treatment discontinuation, including three cases of grade 3 chronic liver GvHD and one case of acute intestinal GvHD. Additionally, the application of a consolidating allogeneic SCT after re-induction treatment with nivolumab is still a matter of discussion since the occurrence of severe GvHD in r/r cHL patients was observed in the nivolumab phase I trial.32 Although severe immune-related adverse events are relatively rare, early recognition and timely management are crucial to prevent irreversibility. Treatment mostly relies on temporary dose delay and immunosuppression by topical, oral or intravenous corticosteroids, with addition of mycophenolate mofetil and other immunosuppressants for refractory cases. Whether and how immunosuppression, including prophylactic measures for infusion-related reactions, affects treatment efficacy is currently unknown. A recent case-presentation showed the feasibility of rituximab therapy for B-cell mediated autoimmune thrombocytopenia during nivolumab treatment, with no added toxicity and the possibility of continuing effective antiPD-1 treatment.84

Future perspectives Despite the promising responses with ICI in hematologic malignancies, the limited amount of data still calls for some caution. On the other hand, impressive response rates among selected heavily pretreated patients and acceptable treatment tolerability make ICI a valuable therapeutic option. Regarding treatment response evaluation in lymphoma, it is important to keep in mind that all former and current trials used response assessment criteria which were developed on principles of standard antineo38

plastic treatment85 and are mainly based on the findings of positron emission tomography (PET) and computed tomography. Response kinetics with ICI are different, with some patients even achieving responses after disease progression by conventional imaging studies.86 Also, due to anti-tumor immune responses, ICI might result in metabolic activity at previous tumor sites reflected by potentially (false-)positive PET signals. Furthermore, at least in the r/r setting, a revised definition of favorable response is required: despite a rather low complete response rate, a substantial proportion of patients with otherwise desperate prognosis achieve durable disease control, without further treatment necessity and improved quality of life. Similar observations have already led to the development of novel immune-related response criteria proposed in solid tumors.86 Two major preconditions are required for effective ICI: a capacitated host immune system to act against the tumor and effective tumor antigen presentation and recognition, enabling a specific immune response. Bearing in mind that all currently available ICI trials in lymphoma only included r/r patients after multiple lines of chemotherapy, it is possible that modest response rates were conditioned by a weakened host immune system. Implementation of ICI earlier in the course of disease, with a potentially more competent immune system, is under investigation. On the other hand, mutational load and mismatch-repair deficiency have been identified as possible biomarkers for ICI response and so r/r disease might be associated with a more obvious benefit from treatment. The optimal treatment duration is unknown; although the majority of responses are being observed within the first 6 months, some responses occur rather late when compared to those following conventional therapy. Most trials investigated ICI until disease progression or intolerable toxicity; other trials allowed treatment for up to 2 years or longer. Some studies were amended to allow cessation of therapy in case of a prolonged PET-negative CR. Treatment duration should ideally be based on biomarkers and minimal residual disease diagnostics in future studies, taking into account both clinical and economic factors. Evaluation of PD-L1 expression on tumor-cells as a predictive marker has been inconclusive so far, both in solid tumors and hematologic malignancies. This might be due to complex dynamics of expression depending on the tumor microenvironment and the lack of standardized immunohistochemistry.87 Mutational load, leading to higher neo-antigen presentation, might be a potential biomarker in solid tumors,88 but frequent mutations of MHC molecules in lymphomas suggest that neo-antigen presentation might still be inefficient, leading to a gradual loss of ICI efficacy.89 Recently, emerging data that gut microbiota might interact with and have some impact on ICI response90,91 suggest that probiotics or microbial transplantation could theoretically enhance the efficacy of ICI. A more detailed understanding of the principle of action of PD-1/PD-L pathway blockade is indispensable in order to apply ICI efficiently and to develop combination treatments. One modality to improve ICI would be to combine this new approach with other immunological agents or conventional therapeutics. Studies combining anti-CTLA4 and anti-PD-1 antibodies in melanoma and multiple myeloma showed promising results81,92 and similar trials in lymphoma are underway. It has long been recognized that haematologica | 2017; 102(1)


Checkpoint inhibition in lymphoma

chemotherapy has an immunomodulatory effect, e.g. by enhancing antigen availability and presentation by antigen-presenting cells.93 Many agents efficient in lymphoma treatment such as cyclophosphamide or anthracyclines have known immunomodulatory effects and might be promising partners for ICI. In addition, combination strategies with other, non-cytotoxic targeted immunomodulatory agents could work synergistically and are currently under investigation. Most of these combination strategies to date include ibrutinib or idelalisib and have a strong translational rationale. On the other hand, clinical observation may also identify promising combinations: in a small study of eight r/r cHL patients, the high CR rate of 87.5% with nivolumab might in part have been due to prior exposure to azacitidine.94 Exposure to hypomethylating agents seems to prime ICI, complement-

ing preclinical data on its immunogenicity.95 Pidilizumab, a humanized IgG1 antibody thought to target PD-1, showed interesting results in DLBCL and FL.96,97 However, it has become clear that its mechanism of action is not checkpoint inhibition, but innate immune system activation, which needs further elucidation. A phase II clinical trial testing the efficacy of pidilizumab as consolidation treatment in stage III-IV DLBCL in first CR is underway, and it will be interesting to see â&#x20AC;&#x201C; once its mechanism of action is clarified â&#x20AC;&#x201C; whether this antibody represents another platform for possible combinations with ICI. Immunogenic effects of radiotherapy, one of the most effective monotherapies in lymphoma treatment, are also well recognized.98 Local effects of direct DNA damage and cellular stress can translate into a systemic boost of effica-

Figure 3. Schematic depiction of synergistic effects of ICI and radiotherapy or chemotherapy. Tumors are able to model the tumor microenvironment (TME) as well as the systemic immune system by production of immunosuppressive factors, thus evading the host immune response and assuring their survival. Chemotherapy and ionizing radiation induce immunogenic tumor-cell death by multiple mechanisms. Expression of major histocompatibility complex I (MHC-I) molecules, presenting tumorassociated antigens (TAA), is up-regulated in tumor cells. The release of TAA and danger-associated molecular patterns (DAMP) in TME stimulates dendritic cell (DC) activation. At the same time, DC activation is additionally enhanced by a newly established pro-inflammatory milieu in TME caused by direct effects of chemotherapy and/or radiotherapy. Activated and mature DC provide co-stimulatory signals to naĂŻve T cells in draining lymph nodes, enabling priming of tumor-specific T cells. Addition of immune checkpoint inhibitors synergistically facilitates activation of T cells and T-cell-mediated anti-tumor cytotoxicity, overcoming inhibitory effects caused by tumorderived immunosuppressive factors.

haematologica | 2017; 102(1)

39


I. Hude et al.

cy. The response to immune-activating chemokines and cytokines caused by radiation initiates further innate and adoptive immune responses. This systemic immune response even induces regression of non-radiated lesions, a phenomenon which is often termed the “abscopal effect”, presenting a potential platform for combination with ICI. Radiation dose, fractioning and timing as well as safety and efficacy of such combinations are yet to be determined in future clinical trials. In addition to these effects, low-dose total-body irradiation causes transient lymphopenia, with subsequent lymphoid reconstitution and stimulation of tumor-reactive effector T cells99 – another possible setting in which to exploit T-cell activity enhancement by ICI. The schematic mechanism of how addition of chemotherapy or radiotherapy to ICI may bypass tumor-induced immunosuppression is depicted in Figure 3. Ongoing preclinical and translational research including correlative analyses of ICI-based therapies will likely create the rationale for evaluation of further combination strategies potentially including adoptive T-cell therapy, oncolytic viruses, metabolic checkpoint blockade or BET inhibitors as well as foster more individualized treatment approaches e.g. with personalized vaccines. Carefully investigating potentially synergistic combinations by evaluating optimal timing, dosage and sequencing is crucial in order to achieve optimal effects and to avoid unprecedented increased toxicity.

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Summary ICI has shown promising activity in r/r cHL, DLBCL and FL, and to some extent also in other lymphoid malignancies. Evidence from preclinical data and clinical trials investigating ICI is emerging, but major issues such as timing and sequencing, treatment duration and synergistic combinatory approaches remain to be resolved. Furthermore, long-term efficacy outcomes and potential development of late toxicities in lymphoma patients are still poorly defined. With its recent approval from the Food and Drug Administration for use in r/r cHL, nivolumab, a first antibody directed against PD-1 has already made its way into standard treatment. Other promising antibodies and ICI-based combination strategies are under investigation to develop efficient and well-tolerated treatments in various disease settings. This new treatment modality is set to reduce late effects of conventional chemotherapy and radiotherapy, potentially leading to less early and late toxicities and an improved quality of life. The emerging role of immunotherapy in lymphoma requires an “out of the box” way of thinking about antineoplastic therapy, redefining treatment outcomes and response assessment, but also raises financial issues regarding prolonged therapies. Results of ongoing trials and collaborative translational research in the field of lymphoma are, therefore, eagerly awaited.

cell receptor signaling inhibitors and lenalidomide. Expert Rev Hematol. 2015;8(6):765-783. Intlekofer AM, Thompson CB. At the bench: preclinical rationale for CTLA-4 and PD-1 blockade as cancer immunotherapy. J Leukoc Biol. 2013;94(1):25-39. Parry RV, Chemnitz JM, Frauwirth KA, Lanfranco AR, Braunstein I, Kobayashi SV, et al. CTLA-4 and PD-1 receptors inhibit Tcell activation by distinct mechanisms. Mol Cell Biol. 2005;25(21):9543-9553. Chen L, Flies DB. Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat Rev Immunol. 2013;13(4):227-242. Dong H, Strome SE, Salomao DR, et al. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat Med. 2002;8(8):793800. Wherry EJ, Kurachi M. Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol. 2015;15(8):486-99. Hodi FS, O'Day SJ, McDermott DF, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363(8):711-723. Robert C, Thomas L, Bondarenko I, et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N Engl J Med. 2011;364(26):2517-2526. Barbee MS, Ogunniyi A, Horvat TZ, Dang T-O. Current status and future directions of the immune checkpoint inhibitors ipilimumab, pembrolizumab, and nivolumab in oncology. Ann Pharmacother. 2015;49(8): 907-937. Keir ME, Butte MJ, Freeman GJ, Sharpe AH. PD-1 and its ligands in tolerance and immunity. Annu Rev Immunol. 2008;26:677-704.

17. Kourie HR, Awada G, Awada AH. Learning from the “tsunami” of immune checkpoint inhibitors in 2015. Crit Rev Oncol Hematol. 2016;101:213-220. 18. Ansell SM, Lesokhin AM, Borrello I, et al. PD-1 blockade with nivolumab in relapsed or refractory Hodgkin's lymphoma. N Engl J Med. 2015;372(4):311-319. 19. Bröckelmann PJ, Borchmann P, Engert A. Current and future immunotherapeutic approaches in Hodgkin lymphoma. Leuk Lymphoma. 2016;57(9):2014-2024. 20. Chemnitz JM, Eggle D, Driesen J, et al. RNA fingerprints provide direct evidence for the inhibitory role of TGFbeta and PD-1 on CD4+ T cells in Hodgkin lymphoma. Blood. 2007;110(9):3226-3233. 21. Yamamoto R, Nishikori M, Kitawaki T, et al. PD-1-PD-1 ligand interaction contributes to immunosuppressive microenvironment of Hodgkin lymphoma. Blood. 2008;111(6):3220-3224. 22. Green MR, Monti S, Rodig SJ, et al. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma. Blood. 2010;116(17):3268-3277. 23. Green MR, Rodig S, Juszczynski P, et al. Constitutive AP-1 activity and EBV infection induce PD-L1 in Hodgkin lymphomas and posttransplant lymphoproliferative disorders: implications for targeted therapy. Clin Cancer Res. 2012;18(6):1611-1618. 24. Chen BJ, Chapuy B, Ouyang J, et al. PD-L1 expression is characteristic of a subset of aggressive B-cell lymphomas and virus-associated malignancies. Clin Cancer Res. 2013;19(13):3462-3473.

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55. Fend F, Quintanilla-Martínez L. Assessing the prognostic impact of immune cell infiltrates in follicular lymphoma. Haematologica. 2014;99(4):599-602. 56. Yang ZZ, Grote DM, Ziesmer SC, Xiu B, Novak AJ, Ansell SM. PD-1 expression defines two distinct T-cell sub-populations in follicular lymphoma that differentially impact patient survival. Blood Cancer J. 2015;5:e281. 57. Carreras J, Lopez-Guillermo A, Roncador G, et al. High numbers of tumor-infiltrating programmed cell death 1-positive regulatory lymphocytes are associated with improved overall survival in follicular lymphoma. J Clin Oncol. 2009;27(9):1470-1476. 58. Muenst S, Hoeller S, Willi N, Dirnhofera S, Tzankov A. Diagnostic and prognostic utility of PD-1 in B cell lymphomas. Dis Markers. 2010;29(1):47-53. 59. Richendollar BG, Pohlman B, Elson P, Hsi ED. Follicular programmed death 1-positive lymphocytes in the tumor microenvironment are an independent prognostic factor in follicular lymphoma. Hum Pathol. 2011;42(4):552-557. 60. Kosmaczewska A, Ciszak L, Suwalska K, Wolowiec D, Frydecka I. CTLA-4 overexpression in CD19+/CD5+ cells correlates with the level of cell cycle regulators and disease progression in B-CLL patients. Leukemia. 2005;19(2):301-304. 61. Grzywnowicz M, Karczmarczyk A, Skorka K, et al. Expression of programmed death 1 ligand in different compartments of chronic lymphocytic leukemia. Acta Haematol. 2015;134(4):255-262. 62. Riches JC, Davies JK, McClanahan F, et al. T cells from CLL patients exhibit features of Tcell exhaustion but retain capacity for cytokine production. Blood. 2013;121(9): 1612-1621. 63. Brusa D, Serra S, Coscia M, et al. The PD1/PD-L1 axis contributes to T-cell dysfunction in chronic lymphocytic leukemia. Haematologica. 2013;98(6):953-963. 64. McClanahan F, Hanna B, Miller S, et al. PDL1 checkpoint blockade prevents immune dysfunction and leukemia development in a mouse model of chronic lymphocytic leukemia. Blood. 2015;126(2):203-211. 65. McClanahan F, Riches JC, Miller S, et al. Mechanisms of PD-L1/PD-1–mediated CD8 T-cell dysfunction in the context of agingrelated immune defects in the Eµ-TCL1 CLL mouse model. Blood. 2015;126(2):212-221. 66. Jitschin R, Braun M, Büttner M, et al. CLLcells induce IDOhi CD14+HLA-DRlo myeloid-derived suppressor cells that inhibit T-cell responses and promote TRegs. Blood. 2014;124(5):750-760. 67. Ding W, Dong H, Call TG, et al. PD-1 blockade with pembrolizumab (MK-3475) in relapsed/refractory CLL including richter transformation: an early efficacy report from a phase 2 trial (MC1485) ASH 57th Annual Meeting and Exibition. Orlando, Florida, USA, 2015. 68. Trautmann L, Janbazian L, Chomont N, et al. Upregulation of PD-1 expression on HIVspecific CD8+ T cells leads to reversible immune dysfunction. Nat Med. 2006;12(10):1198-1202. 69. Velu V, Shetty RD, Larsson M, Shankar EM. Role of PD-1 co-inhibitory pathway in HIV infection and potential therapeutic options. Retrovirology. 2015;12:14. 70. Ni L, Ma CJ, Zhang Y, et al. PD-1 modulates regulatory T cells and suppresses T cell responses in HCV-associated lymphoma. Immunol Cell Biol. 2011;89(4):535-539. 71. Mahadevan D, Vick E, Huber B, et al. Aurora

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GUIDELINE ARTICLE

Guideline for the diagnosis, treatment and response criteria for Bing-Neel syndrome

Monique C. Minnema,1 Eva Kimby,2 Shirley D’Sa,3 Luc-Matthieu Fornecker,4 Stéphanie Poulain,5 Tom J. Snijders,6 Efstathios Kastritis,7 Stéphane Kremer,8 Aikaterini Fitsiori,8 Laurence Simon,4 Frédéric Davi,9 Michael Lunn,10 Jorge J. Castillo,11 Christopher J. Patterson,11 Magali Le Garff-Tavernier,9 Myrto Costopoulos,9 Véronique Leblond,12 Marie-José Kersten,13 Meletios A. Dimopoulos7 and Steven P. Treon11

1 Department of Hematology, UMC Utrecht Cancer Center, the Netherlands; 2Hematology Center, Department of Medicine, Karolinska Institutet, Stockholm, Sweden; 3Cancer Division, University College London Hospitals NHS Foundation Trust, UK; 4Department of Oncology and Hematology, Hôpital Universitaires de Strasbourg and Université de Strasbourg, France; 5Service d’Hématologie-Immunologie-Cytogénétique, Centre Hospitalier de Valenciennes/ Laboratoire d’Hématologie, Centre de Biologie et Pathologie, CHRU de Lille/ INSERM, France; 6Department of Neurology & Neurosurgery, Brain Center Rudolf Magnus, UMC Utrecht, The Netherlands; 7Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Greece; 8Pôle d’Imagerie – Neuroradiologie, Hôpital de Hautepierre/CHU Strasbourg, France; 9Laboratory of Hematology, Hôpital Pitié Salpêtrière, Paris, France; 10Centre for Neuromuscular Disease, National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; 11 Bing Center for Waldenstrom’s Macroglobulinemia, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA, USA; 12AP-HP Hôpital Pitié Salpêtrière, UPMC univ Paris, France and 13Department of Hematology, Academic Medical Center, Amsterdam, the Netherlands

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):43-51

ABSTRACT

B

ing Neel syndrome is a rare disease manifestation of Waldenström’s macroglobulinemia that results from infiltration of the central nervous system by malignant lymphoplasmacytic cells. In this guideline we describe the clinical symptoms, as well as the appropriate laboratory and radiological studies, that can aid in the diagnosis. The presentation of Bing Neel syndrome may be very diverse, and includes headaches, cognitive deficits, paresis, and psychiatric symptoms. The syndrome can present in patients with known Waldenström’s macroglobulinemia, even in the absence of systemic progression, but also in previously undiagnosed patients. Diagnostic work-up should include cerebral spinal fluid analysis with multiparameter flow cytometry to establish B-cell clonality, protein electrophoresis and immunofixation for the detection and classification of a monoclonal protein as well as molecular diagnostic testing for immunoglobulin gene rearrangement and mutated MYD88. MRI of the brain and spinal cord is also essential. The second challenge is to expand our knowledge of prognosis and treatment outcome. Prospective clinical trials on Bing Neel syndrome patients that employ uniform treatment along with appropriate laboratory cerebral spinal fluid assessments and standardized MRI protocols will be invaluable, constituting a significant step forward in delineating treatment outcome for this intriguing disease manifestation.

Introduction Bing Neel syndrome (BNS) is a rare disease manifestation of Waldenström’s macroglobulinemia (WM) that usually presents as a feature of relapsing disease, though it may also occur at first diagnosis of WM.1 In BNS, malignant lymphoplasmacytic cells (LPC) invade the central nervous system (CNS). LPC may be detected in the cerebrospinal fluid (CSF), the meninges, and/or the cerebral parenchyma. The syndrome is named after Jens Bing and Axel Valdemar von Neel; two physihaematologica | 2017; 102(1)

Correspondence: m.c.minnema@umcutrecht.nl

Received: April 11, 2016. Accepted: October 6, 2016. Pre-published: October 6, 2016. doi:10.3324/haematol.2016.147728

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/43

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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cians who described the first two patients with hyperglobulinemia and neurological symptoms in 1936.2 The clinical symptoms of BNS may be very diverse, and include headaches, cognitive deficits, paresis, cranial nerve involvement, gait disorders, and psychiatric symptoms.1 Since the first case report by Bing and Neel, additional case reports of BNS have been published identifying at least 50 patients with this diagnosis. Two recent retrospective surveys added 44 and 34 patients, respectively, to this total.3,4 A diagnostic work-up and a classification system for BNS were proposed by Hochberg and colleagues in 2009 and 2011.5,6 However, 80 years following the first publication, no comprehensive guidelines exist for the diagnostic and therapeutic approach or response assessment of BNS. Therefore, during the 8th International Workshop on WM, a task force on BNS was established comprising hematologists, neurologists, immunologists and radiologists, with the aim of producing a practical guideline for the diagnosis and management of BNS. A comprehensive search was performed using the bibliographic database of PubMed up to February 2016. Both free text terms and MeSH terms were used as search terms. The terms used were; “Bing Neel” and “Waldenström’s macroglobulinemia and central nervous system”, and only English peer-reviewed publications were selected. In addition, all references of selected articles were searched for additional references. The draft of the manuscript was written by the first author and, in subsequent teleconferences, all items were discussed with a multidisciplinary team of international experts in WM.

Clinical picture The clinical symptoms of BNS are diverse and reflect involvement of the CNS and, rarely, the peripheral nervous system (PNS). Importantly, there is no clinical picture or specific symptom(s) that can prove or exclude BNS. The symptoms are gradually progressive in nature, usually developing over the course of weeks or months. Of the symptoms described in literature, headache, nausea and vomiting, visual disturbances, hearing loss and cranial neuropathies, mostly of the facial or oculomotor nerves, usually accompany meningeal involvement. Seizures, cognitive decline, aphasia, psychiatric symptoms, cerebellar dysfunction, impairment of consciousness including coma, and paresis typically represent involvement of brain parenchyma or the spinal cord. Sensory symptoms including paresthesias, pins and needles sensations, and pain - may represent involvement of brain parenchyma, spinal cord, cauda equine, and/or spinal nerve roots, depending on their anatomical distribution. The differential diagnosis of BNS includes hyperviscosity syndrome (HVS) with neurological symptoms such as new-onset headaches, visual impairment, and spontaneous nosebleeds. Confirmation of HVS with appropriately increased IgM or serum viscosity measurements can aid in differentiating HVS related CNS symptoms from BNS.7 Sensory symptoms of the legs due to nerve root/cauda equina involvement may be mistaken for neuropathy related to anti-myelin associated glycoprotein (MAG) antibodies produced in WM and IgM related disorders.8 These patients mostly present with a sensory ataxia with impaired gait and mild to moderate distal muscle weakness which slowly develops over years.9 44

Anti-MAG antibodies can be measured in the serum of these patients. Other types of lymphoma-like diffuse large B-cell lymphoma, marginal zone lymphoma, chronic lymphocytic leukemia (CLL), Hodgkin Lymphoma, and NK/T-cell lymphomas, may also invade the CNS, and are sometimes difficult to differentiate from BNS without correct histology.10

Epidemiology Due to the diversity of symptoms, and the rarity of BNS, there is often a considerable delay between the initial symptoms and the diagnosis. In a recent retrospective analysis, the median time between first symptoms and diagnosis of BNS was 4 months; but more than one year in 20% of patients.3 It is possible that some patients succumb to BNS even before a correct diagnosis is made. The incidence of BNS is unknown, but in a retrospective cohort study of 1,523 WM patients, only 13 patients (0.8%) were diagnosed with BNS, suggesting a very low prevalence.11 No risk factors were identified for BNS, other than the concurrent presence or history of WM. Most patients diagnosed with BNS were previously diagnosed with WM. It is important to recognize that BNS can occur despite WM being in remission with an M-protein level remaining stable or undetectable.3 In approximately 15% to 36% of patients, BNS was the presenting symptom with no previous history of WM.3,4 These patients may have a better prognosis compared to patients with BNS and a previous history of WM.4 The clinical suspicion of BNS in these patients with neurological symptoms was raised because of the presence of an IgM M-protein in the serum or the detection of a clonal Bcell population by multiparameter flow cytometry (MFC) in the cerebral spinal fluid (CSF). Solitary BNS without concurrent or past WM has also been reported.12 Asymptomatic BNS may exist (personal observation), but the incidence is unknown since CSF examination is not routinely carried out in WM.

Diagnostic criteria and work up of BNS Histology The golden standard for the diagnosis of BNS is a histological biopsy of the cerebrum or meninges demonstrating a lymphoplasmacytic lymphoma, comprised of small lymphocytes in which there is morphological evidence of plasma cell differentiation. Immunochemistry is essential and, as in WM, the malignant cells are defined as monotypic B cells which express the pan B-cell antigens CD19, CD20, CD79a and CD79b and, in most cases, also the memory Bcell marker CD27 as well as CD52. CD5 and CD23 are expressed in a minority of cases only. Monotypic plasma cells may also be present, expressing CD138 and IgM.13 Molecular testing is strongly advised and described in a separate section. Besides primary central nervous system lymphoma (PCNSL), also other systemic (indolent) lymphomas can be present in the CNS as well as transformation to high grade lymphoma and, therefore, biopsy remains an important diagnostic procedure.10,14 Biopsy should be attempted prior to steroid administration, if possible, and the risks associated with this procedure should be carefully considered for each patient. haematologica | 2017; 102(1)


Guideline for Bing Neel syndrome

Table 1. Treatment regimens and response activity reported in BNS.

Therapy Intrathecal or -ventricular (monotherapy) Systemic conventional

Name of Drug

Outcome

Reference

methotrexate and/or (liposomal) cytarabine (7 patients) fluda/2-CDA ± rituximab (15 patients)

3 CR 3 PR 1 PD 8 CR 4 PR 3 PD 2 CR 5 PR 2 SD 5 CR (one with ASCT) 1 SD 8 PD 1 PR

3, 17, 43, 62, 63

bendamustine+ rituximab (9 pts)

Systemic High Dose

DT-PACE /CVP/CD/ chlorambucil ± rituximab (14 patients) BCNU based (1 patient) HD-MTX based ± rituximab ± ASCT (48 patients) HD-ARA-C based ± ASCT (12 patients)

Novel

ibrutinib (5 patients)

15 CR 16 PR 9 SD 8 PD 8 CR 3 PR 1 SD 2 CR 3 PR

1, 3, 4, 46, 52, 64 3, 4, 53 3, 37, 58

65 1, 3, 4, 18, 36, 43, 44, 66-68

3, 4, 18, 21, 26, 48, 69

4, 48, 55

Published treatment regiments and their outcome in BNS patients based upon response criteria provided in the publications. CR: Complete Response; PR: Partial Response; SD: Stable Disease; PD: Progressive Disease. Fluda, Fludarabine; 2-CDA, Cladribine; BCNU, Carmustine; DT PACE, Dexamethasone, Thalidomide, Cisplatin, Doxoruucin, Cyclophosphamide, Etoposide. CVP: Cyclophosphamide, Vincristine, Prednisone; CD: Cyclophosphamide, Dexamethasone; HD-MTX: High Dose Methotrexate; HD- ARA-C: High Dose Cytarabine; ASCT: Autologous Stem Cell Transplantation.

Fintelmann et al. have proposed the terms type A and type B BNS.5 Up to 75% of the patients were classified as type A, defined as patients in whom LPC could be demonstrated in the parenchyma, meninges, dura or CSF. Type B patients had very low (less than 5 cells/mm3) counts of LPC in the CSF, and it was suggested that symptoms were caused by IgM deposits rather than by cellular infiltration of the CNS. However, the demonstration of M-protein deposition as a cause of BNS remains to be demonstrated.

Analysis of the CSF When there is leptomeningeal involvement, the CSF may contain malignant LPC; it is therefore recommended to perform repeated CSF analysis and, if possible, to do so before MRI is performed to exclude non-specific meningeal enhancement that occurs after CSF sampling. The analysis of the CSF should include leukocyte cell count and differentiation, biochemistry, morphological analysis, MFC, and molecular testing to increase the sensitivity for the detection of malignant B cells. Also, replication of CSF analysis increases the diagnostic yield. CSF findings may include an elevated opening pressure, lymphocytosis, elevated total protein, and normal or decreased glucose.1 It is important to recognize that other lymphomatous or infectious and inflammatory processes may present with CSF lymphocytosis, and should therefore be considered in the differential diagnosis and appropriately investigated. Morphology is the golden standard but may be difficult to interpret due to the cytospin technique; it also has a low diagnostic yield, as has also been demonstrated in PCNSL (Figure 1).15,16 MFC analysis demonstrating B-cell or plasma-cell markers with light chain restriction is essential for establishing tumor clonalhaematologica | 2017; 102(1)

ity.17,18 MFC should be performed as soon as possible because of the potential for rapid decay of viable cells in native CSF. A cell-stabilizing agent, such as TransFix, may enhance the detection of B-cell clones in the CSF by preventing cellular decay.19 Clonal B cells in the CSF should have the same immunophenotypic features as those in bone marrow (BM). Since MFC is a sensitive method, caution should be taken to avoid blood contamination of the CSF. Protein electrophoresis (PEP) and immunofixation (IF) for the detection and classification of an M-protein in the CSF can be used.18,20,21 If there is no blood-brain barrier disruption, the presence of an IgM M-protein in the CSF with the same light chain restriction as the LPC in the BM and correlation with the serum M-protein may be indicative of the presence of LPC in the leptomeninges.22 However, in the case of increased permeability of the blood-brain barrier, IgM proteins may diffuse from the blood into the CSF and do not reflect the presence of LPC in the CNS.23 As before, caution should be taken to avoid blood contamination for laboratory studies aimed at identifying a monoclonal protein in the CSF.

Molecular testing in CNS biopsy and CSF Immunoglobulin gene rearrangement analysis Because of the complex process of VDJ rearrangement resulting in a unique B-cell receptor in each B lymphocyte, analysis of the immunoglobulin (Ig) gene rearrangement is an essential tool for establishing the clonal character of a lymphoid B-cell population.24,25 In addition, Ig rearrangement testing can help establish the clonal relationship 45


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Figure 1. Morphology of CSF. Left panel; Giemsa stain of the CSF of a patient with BNS relapse after previous diagnosis of WM. Right panel; kappa immunohistochemistry positivity of the LPL cells which was concordant with LPL in bone marrow biopsy. MYD88L265P mutation tested positive in the CSF. (Courtesy of Mrs van Lom and Leguit).

between samples. Therefore, identifying the same clonal Ig heavy and/or light chain gene rearrangements in the LPC from a CNS biopsy or the CSF and BM can provide strong evidence in support of the diagnosis of BNS.17,26 Due to the low rate of infiltration of cells in the CSF, it may be difficult to detect a clonal B-cell population in the CSF given the low sensitivity of this technique. Moreover, the possibility to perform several genetic tests may be limited with few malignant cells in the CSF.

MYD88L265P mutation Whole genome sequencing has shown mutations in MYD88 to be highly prevalent in WM.27 In the vast majority of patients, a point mutation at amino acid position 265 is found, resulting in a leucine to proline change (MYD88L265P).28 Using more sensitive diagnostic techniques, such as allele-specific PCR assay (AS-PCR), MYD88L265P mutations are found in 93-97% of WM patients, whereas it is found only in a minority of other indolent lymphomas. Using a highly sensitive real time quantitative PCR (qPCR) technique, it has been demonstrated that MYD88L265P can be detected in the CSF of BNS patients, and the mutation was also present in the CNS biopsy in one patient.4,18,26 Moreover, disappearance of the MYD88L265P by AS-PCR correlated with clinical and MRI response. Since the qPCR is a very sensitive technique, caution must be taken to avoid blood contamination of the CSF since MYD88L265P can also be detected in peripheral blood.29 It is therefore advised to use the last diagnostic tube of CSF for this test to decrease the likelihood of blood contamination and false detection of MYD88L265P. The detection of the MYD88L265P mutation in a CNS biopsy or CSF sample is not specific for BNS. In a recent study, MYD88L265P was detected in brain biopsy material from 17/18 patients with PCNSL.30 Other groups have also detected the MYD88L265P mutation in high prevalence in PCNSL patients, and similarly in lymphomas presenting in other immune-privileged sites such as the testes.31,32 In WM patients, whole genome sequencing has also identified mutations in CXCR4, a cell surface receptor that binds to CXCL12 (SDF-1a) and promotes migration of LPC to the BM stroma.33,34 Approximately 30-40% of WM patients harbor CXCR4 mutations.35 Sanger sequencing of 46

cells obtained from CSF and BM of 3 BNS patients did not identify CXCR4 mutations, though detection of these mutations by Sanger may have been outside the limits of detection.18 Further studies, including the use of the more sensitive AS-PCR to detect nonsense mutations or high depth targeted re-sequencing may help identify CXCR4 mutations in LPC from CSF in WM patients with BNS.

Radiology Magnetic resonance imaging (MRI) of the brain and spinal cord is essential for the diagnosis of CNS lymphomas, and this is also advised in cases of suspected BNS.6,36 MRI abnormalities can be found in the majority of patients.3,4 The goal of neuroimaging is not only to find supportive evidence for BNS, but also for the exclusion of differential diagnoses (infectious and others), and to select a possible site for biopsy. MRI should be performed prior to lumbar puncture to exclude focal mass effects and/or obstructive hydrocephalus as well as to avoid non-specific meningeal enhancement that occurs after CSF sampling. The MRI protocol must include fluid-attenuated inversion recovery and T1-weighted sequences before and after non-iodine gadolinium contrast injection. Due to the rarity of BNS, optimal imaging protocols have yet to be established. Two categories of CNS involvement in BNS can be distinguished by MRI imaging: the diffuse form, and the tumoral form.37 The diffuse form corresponds to lymphoid cell infiltration in the leptomeningeal sheaths and the perivascular spaces, and usually presents with contrast enhancement and/or thickening of meningeal sheaths; best evaluated in T1 WI after gadolinium administration (Figure 2A&B). In contrast, the tumoral form can be unifocal or multifocal, and is usually located in the deep subcortical hemispheric regions, well-demonstrated in T1 WI and FLAIR sequences as well as in T1 WI after gadolinium administration (figure 2A&B).38 Other characteristic findings of leptomeningeal lymphoma can include abnormal contrast enhancement of cranial and spinal nerves as well as thickening and enhancement of the cauda equina (Figure 2C). Increased parenchymal signal intensity can be identified in T2 and in FLAIR images corresponding either to the tumoral form of the disease or to vasogeneic edema (figure haematologica | 2017; 102(1)


Guideline for Bing Neel syndrome

A

C

D

E

B

Figure 2. MRI abnormalities in BNS. A. Parenchymal involvement of the brain, increased signal abnormalities in both pre-central regions in axial FLAIR sequence. B. Brain parenchymal involvement, multiple nodular contrast enhancement in both pre-central regions in axial T1 sequence after contrast media administration. C. Cauda equina thickening T2 sagittal sequence D. Positive diffusion showing high signal in both pre-central regions. E. ADC map reconstruction showing high signal in both pre-central regions.

2A).39,40 In diffusion weight imaging (DWI) images, increased signal intensity with elevated or normal (isointense) apparent diffusion coefficient (ADC) values , suggestive of vasogenic edema, can be caused by a malignant cell infiltration in the perivascular spaces damaging this blood-brain barrier (figure 2D&E).38,39 In contrast, a restriction of diffusion due to vascular infarcts may be related to HVS and, therefore, DWI can help in the differential diagnosis of BNS. Although MRI is a very sensitive technique for the detection of malignant infiltration of the CNS, it cannot differentiate between the different histological entities of CNS lymphoma, nor does it obviate the need for CSF or tissue sampling. Absence of MRI findings should not be considered a basis to exclude the diagnosis of BNS.21

Blood analysis Because BNS is mainly diagnosed concurrently with or following a prior diagnosis of WM, the blood work-up should include at least a full blood count, serum viscosity, serum PEP, serum IF, and quantification of serum IgM, IgG and IgA levels, β2 microglobulin, and cryoglobulins. When systemic WM is present, the IPSSWM score at diagnosis may help with risk assessment for systemic disease, though it is not a prognostic marker for BNS.41,42

Ocular assessment Involvement of the eye is rarely described in WM, besides the changes in the retina in HVS, but may occur in BNS.43,44 It is advised to consult an ophthalmologist for extended eye examination in patients with new complaints of the eyes and/or sight where no abnormality is evident from direct ophthalmoscopy. haematologica | 2017; 102(1)

Recommendations The task force recommends that definitive histological evidence should be sought to establish the diagnosis of BNS. Weighing the risks versus benefits of this procedure may be accomplished as follows: I) A direct biopsy of the affected CNS tissue demonstrating lymphoplasmacytic lymphoma. or II) CSF analysis demonstrating cytological detail supportive of lymphoplasmacytic lymphoma without evidence of clinical transformed disease, and the presence of monoclonal B cells evidenced by MFC or molecular technique such as Ig rearrangement analysis or MYD88L265P mutation. Abnormal brain and/or spinal MRI imaging demonstrating leptomeningeal or parenchymal disease is supportive but not sufficient for the diagnosis of BNS. Absence of abnormal MRI findings does not exclude the diagnosis of BNS. In all other circumstances, BNS may be suspected without definitive evidence for diagnosis, and further diagnostic testing is advised.

Prognosis WM is an indolent lymphoma with an estimated median survival of 7-12 years.45 Treatment for WM is initiated when symptomatic disease is present, and current prognostic criteria are not useful in either determining start of treatment nor in choosing which treatment type to use. For BNS, there are no established prognostic factors, and in most case reports only a short follow-up is available. However, long-term survival for more than 10 years after successful treatment has been described.46 Simon et al. 47


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Figure 3. Consensus Recommendations for Treatment Approach of BNS. Suggested treatment regimens. Order of regimens is alphabetical and does not imply preference. HD-MTX, High Dose Methotrexate; HD- ARA-C, High Dose Cytarabine; ASCT, Autologous Stem Cell Transplantation.

described a survival rate of 71% at 5 years and 59% at 10 years in a retrospective cohort of 44 patients with BNS.3 In a cohort of 34 patients, Castillo et al. estimated the 3 years overall survival rate to be 59% and identified, in univariate analysis, age above 65 years, previous treatment for WM, and platelet count <100 x 109/L as adverse prognostic factors.4

Treatment Goals Treatment should be offered to symptomatic patients in whom a definitive diagnosis of BNS has been established. The aim of treatment of BNS is to reverse the clinical symptoms and induce long progression-free survival (PFS). As in WM, which is an indolent, non-curative disease, the current goal of treatment does not necessitate the complete eradication of all malignant cells, but the improvement of outcome for patients. Some patients may continue to have CSF detectable disease, for example with sensitive MYD88L265P AS-PCR testing, following treatment despite becoming asymptomatic.4 Currently, there is not enough information to support continuous treatment in these patients. Moreover, radiological findings may lag behind clinical improvement or resolution of symptoms. Also, while gadolinium-enhancing lesions are expected to regress with successful therapy, residual lesions on T2 or FLAIR images may persist, representing gliosis or demyelination rather than residual LPC; these T2/FLAIR lesions alone do not necessarily constitute persisting disease. As such, treatment should be guided by clearance of the patientâ&#x20AC;&#x2122;s symptoms. On the other hand, it is also important to realize that some clinical symptoms or signs may not be reversible due to the lower regenerative capacity of the CNS and PNS. These sequelae should therefore not be interpreted as treatment failure, and treatment may be stopped when the best clinical result is accomplished. Since the used treatment regimens can also induce brain damage, the possibility of clinical decline induced by the brain penetrating treatment regimens should be excluded as much as possible when considering progression of relapse.47 48

Response Criteria Besides the clinical response, ongoing response, as well as progression or relapse, can be monitored by way of serial MRI imaging and/or examination of the CSF. The CSF response can be monitored during and after treatment, and normalization of the CSF may indicate an adequate anti-tumor strategy. Serial quantitative measurement of the CSF cellular compartment for MYD88L265P mutation by qPCR has not been examined, but may represent a promising technology given its ability to detect changes in systemic WM disease.18,48 The task force therefore proposes the following response criteria: Complete Remission (CR); resolution of all reversible clinical symptoms with normalization of cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) findings. MRI findings may show minimal residual abnormalities on T2 or FLAIR. The absence of new clinical signs, symptoms, and new contrast enhancing MRI findings are required for CR attainment. Partial response (PR); improvement but no complete resolution of all reversible clinical symptoms, or complete resolution of all reversible clinical symptoms but with maintained radiological abnormalities, excluding minimal residual abnormalities on T2 or FLAIR. The CSF findings should be negative. Non-response; persistence or progression of neurological symptoms, radiological or CSF findings. Relapse; Reappearance of new signs and symptoms attributed to BNS; or detection by cytological, and/or MFC, and/or molecular techniques of BNS disease; or progression or new findings attributed to BNS by MRI examination of the brain and/or spine. Evaluation of response should be considered once during treatment, and then at the end of treatment. With continuous treatment, testing can be done after 3-4 months and then yearly, but only in those patients in which a neurological improvement is seen. Evaluation should be performed earlier if there is a lack of clinical response, and also at the moment of progressive neurological disease. The above criteria for BNS assessment should be haematologica | 2017; 102(1)


Guideline for Bing Neel syndrome

applied independently of the evaluation of systemic WM disease.

monotherapy with intrathecal drugs rarely induces longlasting responses.17

Anti-CD20 therapy Treatment Strategy General In the recent retrospective surveys with response data of 44 and 34 BNS patients, respectively, the overall response rate was 70% to first line therapy, and no differences according to type of treatment could be made.3,4 Therefore, the choice for the type of systemic treatment should be made on an individual basis, considering the patient condition, medical history, preference and experience of the physician. BNS can exist with or without concurrent WM. It is not known if the occurrence of both disease presentations influence one another. Furthermore, there are no data to suggest that effective treatment of the systemic WM component may beneficially influence the outcome of the BNS treatment. On the other hand, many of the treatments used for BNS, such as fludarabine, cladribine, bendamustine, and ibrutinib, clearly have systemic effects and therefore a positive effect of adequate systemic treatment cannot be ruled out. However, the indication for treatment for the systemic WM component should be made on its own merits according to the published guidelines for definition of symptomatic WM.13

Steroid therapy Evidence from PCNSL cases indicates sensitivity to steroid therapy, with prompt clinical improvement and radiological resolution within 48 hours.49 However, this response is short-lived, with disease recurrence occurring soon after steroid cessation. Steroid treatment should therefore not be thought of as long-lasting effective therapy in BNS, and should, if possible, be avoided before tissue biopsy and CSF investigation to assure optimal histopathological assessment.

Chemotherapy Several treatment options can be considered. These options include intrathecal, intraventricular, and systemic chemotherapy with known or probable penetration of the blood-brain barrier. Most series that have reported on the outcome of treatment for BNS are retrospective, with only one small series reported on the treatment of four serial consecutive patients.46 Chemotherapy regimens commonly used for the treatment for BNS are mainly adapted from treatment schedules used in the treatment of PCNSL. These treatments include high dose methotrexate (MTX) and high dose cytarabine (Ara-C) for several cycles.50 This may be an appropriate treatment for patients considered fit for intensive therapy. However, with standard dosed fludarabine, cladribine, and bendamustine, responses have been achieved, and these drugs can also be used in the front-line setting.3,4,5153 Ibrutinib, a Brutonâ&#x20AC;&#x2122;s tyrosine kinase (BTK) inhibitor, has recently been improved for the treatment of WM, dosed 420 mg once daily. Recent reports suggest that both this dose, as well as the 560 dosing as used in Mantle cell lymphoma, is effective and capable of passing the blood-brain barrier.48,54,55 Intrathecal treatment may be combined with systemic treatment to treat meningeal involvement of BNS since haematologica | 2017; 102(1)

Rituximab is mostly given systemically and combined with chemotherapy. Monotherapy is not advised due to uncertainty of blood-brain barrier passage. In PCNSL, intrathecally administered rituximab therapy has been described as efficacious, but serious side effects have also been reported with this type of administration and is, therefore, not advised as first-line treatment.56, 57

Treatment of Relapsed BNS Relapse treatment is feasible in BNS patients. In a retrospective analysis, 53% of the initial 34 patients were retreated, and 48% responded to this treatment.4 In this setting, factors to be considered are the depth of response and duration of response to previous treatment. The role of autologous stem cell transplantation (ASCT) is unclear but can be considered in young patients with aggressive disease behavior.3,4,58 The optimum conditioning therapy has not been clarified, but in patients with PCNSL, BCNU/thiotepa conditioning is recommended over BEAM (BCNU, etoposide, cytarabine and melphalan) by the European Association for Neuro-Oncology.50 The toxicity of standard chemotherapy treatment is well known to oncologists and hematologists but it must be realized that applying blood-brain barrier penetrating chemotherapy may induce more unknown central nervous system toxicity like dizziness, confusion and changes in mental status. These side effects must be distinguished from disease progression.47 In Table 1, all chemotherapy regimens published in English peer reviewed journals are listed with information on treatment outcome.

Radiation Therapy BNS is sensitive to radiotherapy (RT). The effective use of RT has been described in many case reports, both as first-line and as rescue therapy.12,59,60 Localized RT to affected lesions at a dose of 30 to 40 Gy may be preferable to whole brain radiation to limit toxicity; this may fail to address widespread deposits that are not apparent on imaging. In general, cerebral RT, even when localized (stereotactic techniques), is associated with enhanced neurotoxicity, especially the occurrence of late neurocognitive effects in elderly patients which can affect up to 80% of patients.61 Therefore, first-line use of RT is not recommended and should be reserved for patients failing other treatment options. However, RT may be considered in BNS patients with localized spinal involvement in whom toxicity can be limited.

Treatment Algorithm Although limited data are available, a treatment algorithm is proposed for the treatment of de novo BNS patients (Figure 3). Since anecdotal information confirms that patients can be asymptomatic and that clinical improvement is the most important treatment goal, asymptomatic patients may be observed without initial treatment. When patients have BNS with a tumoral presentation localized in deep regions of the brain (periventricular regions, basal ganglia, brainstem, and/or cerebellum), systemic therapy is advised; in some patients with only meningeal involvement, use of monotherapy with intrathecal treatment may be an option. However, most of 49


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the responses with only intrathecal chemotherapy are not long-lasting. Other factors to be considered are prior therapy for WM with persisting or possible long-term side effects. For example, repeated use of purine analogues may compromise stem cell collection in the future and may increase the risk of disease transformation. Intensive chemotherapy with high dose chemotherapy increases the occurrence of side effects in patients. In the relapse setting, factors to be considered are the response and duration of response to previous treatment. The use of bloodbrain barrier passing chemotherapy in patients that were previously treated with RT is not advised due to the increased neurotoxicity if used in this order.

Proposed Clinical Trials The task force recognizes that there is a need for prospective clinical trials that will incorporate a uniformly diagnosed patient group with BNS, treated with a standardized treatment protocol. Moreover, incorporating the novel diagnostic CSF techniques both for diagnosis and follow up will aid in the understanding of this rare disease manifestation. Since BNS patients are often elderly, these treatments should be as toxicity-sparing as possible. Both fludarabine and BTK inhibitors may be particularly attractive candidates for a prospective study given their CNS drug penetrance and efficacy in BNS.

Conclusions BNS is a rare disease manifestation of WM. The first challenge is to increase physician awareness of the existence of

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this syndrome and of the performance of the appropriate tests in the right clinical setting to establish the diagnosis. In this guideline, we describe the clinical symptoms as well as the appropriate laboratory and radiological studies that can aid in the diagnosis of BNS. It is important to realize that BNS can present in patients with known WM even in the absence of systemic progression. In a substantial portion of WM patients, BNS can also be the presenting symptom in previously undiagnosed WM. Like other CNS lymphomas, it is important to perform a brain biopsy whenever possible and to expand CSF analysis to include MFC testing; if possible M protein screening as well as molecular diagnostic testing for immunoglobulin gene rearrangement and MYD88. MRI of the brain and spinal cord is essential. The second challenge is to expand our knowledge of the prognosis and treatment outcome of BNS. It should be possible to improve the prognosis for these patients if better treatment strategies are employed and backed up by a commonality of aims and the use of uniform diagnostic and response criteria. Prospective clinical trials in BNS patients that employ uniform treatment along with appropriate laboratory CSF assessments and standardized MRI protocols will be invaluable, and will constitute a significant step forward in delineating treatment outcome for this intriguing disease manifestation. Acknowledgments The authors would like to thank the staff of the Bing Center for WaldenstrĂśmâ&#x20AC;&#x2122;s Macroglobulinemia for their help in organizing the BNS consensus effort and preparation of this manuscript.

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Guideline for Bing Neel syndrome 23. Dalakas MC, Papadopoulos NM. Paraproteins in the spinal fluid of patients with paraproteinemic polyneuropathies. Ann Neurol. 1984;15(6):590-593. 24. van Krieken JH, Langerak AW, Macintyre EA, et al. Improved reliability of lymphoma diagnostics via PCR-based clonality testing: report of the BIOMED-2 Concerted Action BHM4-CT98-3936. Leukemia. 2007;21(2): 201-206. 25. Liu L, Cao F, Wang S, Zhou J, Yang G, Wang C. Detection of malignant B lymphocytes by PCR clonality assay using direct lysis of cerebrospinal fluid and low volume specimens. Int J Lab Hematol. 2015;37(2):165173. 26. Frustaci AM, Rusconi C, Picardi P, et al. Bing Neel Syndrome in a Previously Untreated Patient With Waldenstrom's Macroglobulinemia: Contribution of MYD88 L265P Mutation on Cerebrospinal Fluid. Clin Lymphoma Myeloma Leuk. 2016;16(1):e7-e9. 27. Treon SP, Xu L, Yang G, et al. MYD88 L265P somatic mutation in Waldenstrom's macroglobulinemia. N Engl J Med. 2012;367(9):826-833. 28. Treon SP, Xu L, Hunter Z. MYD88 Mutations and Response to Ibrutinib in Waldenstrom's Macroglobulinemia. N Engl J Med. 2015;373(6):584-586. 29. Xu L, Hunter ZR, Yang G, et al. Detection of MYD88 L265P in peripheral blood of patients with Waldenstrom's Macroglobulinemia and IgM monoclonal gammopathy of undetermined significance. Leukemia. 2014;28(8):1698-1704. 30. Yamada S, Ishida Y, Matsuno A, Yamazaki K. Primary diffuse large B-cell lymphomas of central nervous system exhibit remarkably high prevalence of oncogenic MYD88 and CD79B mutations. Leuk Lymphoma. 2015;56(7):2141-2145. 31. Poulain S, Boyle EM, Tricot S, et al. Absence of CXCR4 mutations but high incidence of double mutant in CD79A/B and MYD88 in primary central nervous system lymphoma. Br J Haematol. 2015;170(2):285-287. 32. Kraan W, Horlings HM, van KM, et al. High prevalence of oncogenic MYD88 and CD79B mutations in diffuse large B-cell lymphomas presenting at immune-privileged sites. Blood Cancer J. 2013;3:e139. 33. Hunter ZR, Xu L, Yang G, et al. The genomic landscape of Waldenstrom macroglobulinemia is characterized by highly recurring MYD88 and WHIM-like CXCR4 mutations, and small somatic deletions associated with B-cell lymphomagenesis. Blood. 2014;123(11):1637-1646. 34. Ngo HT, Leleu X, Lee J, et al. SDF1/CXCR4 and VLA-4 interaction regulates homing in Waldenstrom macroglobulinemia. Blood. 2008;112(1):150-158. 35. Treon SP, Cao Y, Xu L, Yang G, Liu X, Hunter ZR. Somatic mutations in MYD88 and CXCR4 are determinants of clinical presentation and overall survival in Waldenstrom macroglobulinemia. Blood. 2014;123(18):2791-2796. 36. Rigamonti A, Lauria G, Melzi P, et al. A case of Bing-Neel syndrome presenting as spinal cord compression. J Neurol Sci. 2014; 346(1-2):345-347. 37. Logothetis J, Silvestein P, Coe J. Neurologic aspects of Waldenstrom's macroglobulinemia; report of a case. Arch Neurol. 1960; 3:564-573.

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38. Kim HJ, Suh SI, Kim JH, Kim BJ. Brain magnetic resolution imaging to diagnose bingneel syndrome. J Korean Neurosurg Soc. 2009;46(6):588-591. 39. Drappatz J, Akar S, Fisher DC, Samuels MA, Kesari S. Imaging of Bing-Neel syndrome. Neurology 2008;70(16):1364. 40. Rigual D, Qiu J, Fenstermaker RA, Fabiano AJ. Tumoral Bing-Neel Syndrome presenting as a cerebellar mass. Clin Neurol Neurosurg. 2013;115(6):823-826. 41. Morel P, Duhamel A, Gobbi P, et al. International prognostic scoring system for Waldenstrom macroglobulinemia. Blood. 2009;113(18):4163-4170. 42. Kastritis E, Kyrtsonis MC, Hadjiharissi E, et al. Validation of the International Prognostic Scoring System (IPSS) for Waldenstrom's macroglobulinemia (WM) and the importance of serum lactate dehydrogenase (LDH). Leuk Res. 2010;34(10): 1340-1343. 43. Hughes MS, Atkins EJ, Cestari DM, Stacy RC, Hochberg F. Isolated optic nerve, chiasm, and tract involvement in Bing-Neel Syndrome. J Neuroophthalmol. 2014;34(4): 340-345. 44. Stacy RC, Jakobiec FA, Hochberg FH, Hochberg EP, Cestari DM. Orbital involvement in Bing-Neel syndrome. J Neuroophthalmol. 2010;30(3):255-259. 45. Kristinsson SY, Bjorkholm M, Landgren O. Survival in monoclonal gammopathy of undetermined significance and Waldenstrom macroglobulinemia. Clin Lymphoma Myeloma Leuk. 2013;13(2): 187-190. 46. Vos JM, Kersten MJ, Kraan W, et al. Effective treatment of Bing-Neel Syndrome with oral fludarabine: a case series of four consecutive patients. Br J Haematol. 2016;172(3):461-464. 47. Pentsova E, Rosenblum M, Holodny A, Palomba ML, Omuro A. Chemotherapyrelated magnetic resonance imaging abnormalities mimicking disease progression following intraventricular liposomal cytarabine and high dose methotrexate for neurolymphomatosis. Leuk Lymphoma. 2012; 53(8):1620-1622. 48. Cabannes-Hamy A, Lemal R, Goldwirt L, et al. Efficacy of ibrutinib in the treatment of Bing-Neel syndrome. Am J Hematol. 2016;91(3):E17-E19. 49. Weller M. Glucocorticoid treatment of primary CNS lymphoma. J Neurooncol. 1999; 43(3):237-239. 50. Hoang-Xuan K, Bessell E, Bromberg J, et al. Diagnosis and treatment of primary CNS lymphoma in immunocompetent patients: guidelines from the European Association for Neuro-Oncology. Lancet Oncol. 2015; 16(7):e322-e332. 51. Arumugam M, Raes J, Pelletier E, et al. Enterotypes of the human gut microbiome. Nature. 2011;473(7346):174-180. 52. Richards AI. Response of meningeal Waldenstrom's macroglobulinemia to 2chlorodeoxyadenosine. J Clin Oncol. 1995; 13(9):2476. 53. Varettoni M, Marchioni E, Bonfichi M, et al. Successful treatment with Rituximab and Bendamustine in a patient with newly diagnosed Waldenstrom's Macroglobulinemia complicated by BingNeel syndrome. Am J Hematol. 2015; 90(8):E152-E153. 54. Bernard S, Goldwirt L, Amorim S, et al. Activity of ibrutinib in mantle cell lym-

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phoma patients with central nervous system relapse. Blood. 2015;126(14):16951698. Mason C, Savona S, Xu L, Treon SP, Allen SL. Ibrutinib penetrates the blood brain barrier and shows efficacy in the therapy of Bing Neel syndrome. Blood. 2016 Jul 13. [Epub ahead of print] Rubenstein JL, Fridlyand J, Abrey L, et al. Phase I study of intraventricular administration of rituximab in patients with recurrent CNS and intraocular lymphoma. J Clin Oncol. 2007;25(11):1350-1356. Bromberg JE, Doorduijn JK, Baars JW, van Imhoff GW, Enting R, van den Bent MJ. Acute painful lumbosacral paresthesia after intrathecal rituximab. J Neurol. 2012;259 (3):559-561. Abdallah AO, Atrash S, Muzaffar J, et al. Successful treatment of Bing-Neel syndrome using intrathecal chemotherapy and systemic combination chemotherapy followed by BEAM auto-transplant: a case report and review of literature. Clin Lymphoma Myeloma Leuk. 2013;13(4): 502-506. Shimizu K, Fujisawa K, Yamamoto H, Mizoguchi Y, Hara K. Importance of central nervous system involvement by neoplastic cells in a patient with Waldenstrom's macroglobulinemia developing neurologic abnormalities. Acta Haematol. 1993;90(4): 206-208. Imai F, Fujisawa K, Kiya N, et al. Intracerebral infiltration by monoclonal plasmacytoid cells in Waldenstrom's macroglobulinemia--case report. Neurol Med Chir (Tokyo). 1995;35(8):575-579. Saad S, Wang TJ. Neurocognitive Deficits After Radiation Therapy for Brain Malignancies. Am J Clin Oncol. 2015; 38(6):634-640. Bhatti MT, Yuan C, Winter W, McSwain AS, Okun MS. Bilateral sixth nerve paresis in the Bing-Neel syndrome. Neurology. 2005;64(3):576-577. Sanchez-Guerrero S, Castillo JJ. Bing-Neel syndrome: a rare complication of Waldenstrom macroglobulinemia. Blood. 2015;126(11):1390. Delgado J, Canales MA, Garcia B, AlvarezFerreira J, Garcia-Grande A, HernandezNavarro F. Radiation therapy and combination of cladribine, cyclophosphamide, and prednisone as treatment of Bing-Neel syndrome: Case report and review of the literature. Am J Hematol. 2002;69(2):127-131. Torrey JJ, Katakkar SB. Treatable meningeal involvement in Waldenstrom's macroglobulinemia. Ann Intern Med. 1984;101(3): 345-347. Doshi RR, Silkiss RZ, Imes RK. Orbital involvement in Bing-Neel syndrome. J Neuroophthalmol. 2011;31(1):94-95. Ritzenthaler T, Leray V, Bourdin G, et al. Ventriculitis revealing Bing-Neel syndrome in a patient without Waldenstrom's macroglobulinemia. Clin Neurol Neurosurg. 2013;115(1):82-84. Morita K, Yoshimi A, Masuda A, Ichikawa M, Yatomi Y, Kurokawa M. Unique association of Waldenstrom macroglobulinemia with optic neuritis and monoclonal T cell expansion. Int J Hematol. 2013;98(2):247249. Jennane S, Doghmi K, Mahtat EM, Messaoudi N, Varet B, Mikdame M. Bing and neel syndrome. Case Rep Hematol. 2012;2012:845091.

51


ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Blood Tranfusion

Ferrata Storti Foundation

Treatments for hematologic malignancies in contrast to those for solid cancers are associated with reduced red cell alloimmunization Dorothea Evers,1,2 Jaap Jan Zwaginga,*1,2 Janneke Tijmensen,1,2 Rutger A. Middelburg,1,3 Masja de Haas,1,2,4 Karen M.K. de Vooght,5 Daan van de Kerkhof,6 Otto Visser,7 Nathalie C.V. Péquériaux,8 Francisca Hudig9 and Johanna G. van der Bom*1,3

Center for Clinical Transfusion Research, Sanquin Research, Leiden; 2Department of Immuno-hematology and Blood Transfusion, Leiden University Medical Center; 3 Department of Clinical Epidemiology, Leiden University Medical Center; 4Department of Immunohematology Diagnostics, Sanquin, Amsterdam; 5Department of Clinical Chemistry and Hematology, University Medical Center, Utrecht; 6Department of Clinical Chemistry and Hematology, Catharina Hospital, Eindhoven; 7Department of Hematology, VU Medical Center, Amsterdam; 8Department of Clinical Chemistry and Hematology, Jeroen Bosch Hospital, ‘s-Hertogenbosch and 9LabWest, Haga Teaching Hospital, The Hague, the Netherlands

1

Haematologica 2017 Volume 102(1):52-59

*JJZ and JGB contributed equally to this work.

ABSTRACT

Correspondence: j.g.vanderbom@lumc.nl

Received: July 4, 2016. Accepted: September 9, 2016. Pre-published: September 15, 2016. doi:10.3324/haematol.2016.152074

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/52

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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R

ed cell alloimmunization may induce severe hemolytic side effects. Identification of risk-modifying conditions will help tailor preventative strategies. This study aims to quantify the associations of hematologic malignancies and solid cancers with red cell alloimmunization in patients receiving red cell transfusions. We performed a nested multicenter case-control study in a source population of 24,063 patients receiving their first and subsequent red cell transfusions during an 8-year follow-up period. Cases (n=505), defined as patients developing a first transfusion-induced red cell alloantibody, were each compared with 2 non-alloimmunized controls (n=1010) who received a similar number of red cell units. Using multivariate logistic regression analyses, we evaluated the association of various malignancies and treatment regimens with alloimmunization during a delineated 5-week risk period. The incidence of alloimmunization among patients with acute (myeloid or lymphoid) leukemia and mature (B- or T-cell) lymphoma was significantly reduced compared to patients without these malignancies: adjusted relative risks (RR) with 95% confidence interval (CI) 0.36 (range 0.19-0.68) and 0.30 (range 0.12-0.81). Associations were primarily explained by immunosuppressive treatments [RR for (any type of) chemotherapy combined with immunotherapy 0.27 (95%CI: 0.090.83)]. Alloimmunization risks were similarly diminished in allogeneic or autologous stem cell transplanted patients (RR 0.34, 95%CI: 0.160.74), at least during the six months post transplant. Alloimmunization risks of patients with other hematologic diseases or solid cancers, and their associated treatment regimens were similar to risks in the general transfused population. Our findings suggest that, in contrast to malignancies in general, hemato-oncological patients treated with dose-intensive regimens have strongly diminished risk of red cell alloimmunization.

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Malignancies and red cell alloimmunization

Introduction Transfusion of red cells exposes recipients to non-self antigens and, consequently, may induce alloantibody formation. Although prior alloimmunization requires the exclusive administration of donor blood that is negative for the cognate antigen, accidental re-exposure may induce severe hemolytic transfusion reactions.1,2 Prevention of alloimmunization and its consequences is promoted by transfusion of ABO/RhD compatible units to all red cell recipients. In addition, matching beyond those antigens is recommended for certain patients considered to be at high risk of alloimmunization due to repeated exposure, since the number of transfusions is strongly associated with the likelihood of alloimmunization.3-5 As such, in several high-income countries, patients with hemoglobinopathies and with myelodysplastic syndrome (MDS), who often face regular transfusions over long periods of time, receive red cell units matched for the most immunogenic and clinically relevant antigens C, c, E, e, and K.3,4 The ability of the recipient’s immune system to evoke a humoral alloimmune response upon red cell alloantigen exposure is likely modulated by his or her clinical condition.6-8 In this regard, while oncological patients were suggested to have a similar alloimmunization risk to the general transfused population,9-11 some studies reported high incidences of alloimmunization among MDS patients.12,13 Importantly, apart from the study by Sanz et al.,13 these reports did not take into account the cumulative red cell exposure, which in the oncological patient population is often considerable and a main determinant of alloimmunization.5 Therefore, the possible influence of diseasespecific features remains to be clarified. In addition, cancer types differ from one another in their intrinsic immunobiological characteristics as well as in the immunosuppressive nature of their treatments. Therefore, alloimmunization rates observed in a heterogeneous oncological patient population cannot be extrapolated to specific diseases. Here we report the results of a nested case-control study quantifying the associations of various hematologic malignancies and solid cancers with the risk of red cell alloimmunization in a cohort of red cell transfusion recipients.

Methods

‘Nth’ transfusion) to have been likely to elicit alloimmunization and defined this as the implicated transfusion. If, due to incomplete donor typing, this last mismatched transfusion could not be identified, the last non-tested unit preceding the first positive screen was considered as the implicated transfusion. For each case, we then randomly sampled 2 non-alloimmunized controls on the pre-condition that these patients received at least N or more transfusions at the same hospital, hereby following an ‘incidence-density sampling strategy’.16 After marking the Nth transfusion in the 2 matched controls, we subsequently constructed a so-called ‘alloimmunization risk period’ in both the case and the 2 controls, which stretches from 30 days before to seven days after this Nth (implicated) transfusion (Figure 1).15 Next, hospital electronic laboratory information systems and patient medical charts were consulted to record the presence of various clinical conditions during this period. The study protocol was approved by the Ethical Review Board in Leiden and by the board of each participating center.

Malignancies and their treatments We used internationally approved response criteria to define the remission state of various hematologic malignancies.17-21 Malignancies in complete remission during the alloimmunization risk period were considered as absent. The presence of minimal residual disease was not taken into account. All medication under subcategory L01 in the World Health Organization’s Anatomic Therapeutic Chemical (ATC) classification index22 was defined as chemotherapy, with the exception of agents in the pharmacological subgroup L01XC, as these involve monoclonal antibodies. Within subgroups L01XC and L04AA, we defined rituximab, alemtuzumab, and rabbit- or horse-derived anti-thymocyte globulin (ATG) as anti-lymphocyte immunotherapy.

Statistical analysis Multiple imputation was used to account for missing data. Potential confounders were identified on the basis of their association with the assessed determinant among the source population (i.e. the non-alloimmunized controls). Using multivariate logistic regression analyses conditioning on the matched variables and on the identified potential confounders, we evaluated the associations of various hematologic malignancies and solid cancers, treatment modalities, and degree of leukopenia with the development of red cell alloimmunization. As we used an incidence-density sampling procedure to select controls,16 all odds ratios are presented as relative risks (RRs).23,24 Further details on the statistical analytical methods adopted are provided in the Online Supplementary Appendix.

Study design and setting We performed a nested case-control study within a mainly Caucasian source population of patients receiving their first and subsequent red cell transfusion between 2005 and 2013 at one of six Dutch hospitals. All six hospitals treat patients diagnosed with oncological pathologies; treatment includes standard remissioninduction chemotherapy for acute leukemia patients. Allogeneic hematopoietic stem cell transplantation (HSCT) is performed at three and autologous HSCT at four of these centers. Details of the source population, including eligibility criteria, study period per hospital, and the methods adopted have been published previously5,14,15 (see the Online Supplementary Appendix for details). Briefly, cases were all patients who developed a first transfusion-induced alloantibody against c, C, e, E, K, Cw, Fya, Fyb, Jka, Jkb, Lua, Lub, M, N, S, or s. For all cases, we assumed the last antigen mismatched transfusion preceding the first positive screen (the haematologica | 2017; 102(1)

Results Among 54,347 newly-transfused patients, 24,063 met all study criteria. The majority of excluded patients were ineligible due to the absence of an antibody screen following a single transfusion episode (n=25,037). First-formed red cell alloantibodies were identified in 505 patients (2.1%) (Online Supplementary Table S1). Thirty-seven of those patients (7.3%), including 21 of 32 (65.6%) who formed anti-Lua, only received units for which testing of the cognate antigen had not been performed; we assumed the last non-tested unit preceding the first positive screen to have elicited alloimmunization. General and clinical characteristics of the 505 alloimmunized patients and their 1010 matched control subjects are presented in Online Supplementary Tables S1 and S2. 53


D. Evers et al.

Malignancies present during the alloimmunization risk period A total of 606 patients (40.0%) had at least one type of malignancy (270 had a hematologic malignancy and 338 a solid tumor; 2 patients presented with both types of malignancies). Online Supplementary Table S3 presents types and subtypes of malignancies. The presence of a malignancy could not be confirmed for 12 patients: 4 patients with a clinical condition suspected for a malignancy that was not further evaluated, 4 patients with a suspected malignancy in whom a malignancy was later confirmed, and 4 patients receiving treatment for a solid tumor for whom the remission status at the time of the risk period was unclear. These 12 patients were not included in the corresponding analyses. Online Supplementary Tables S4 and S5 show identified confounders for each type of malignancy. Control patients with acute leukemia and lymphoma, as compared to control patients without these diseases, were younger and had less comorbidity (including renal insufficiency and presence of other malignancies). They more frequently received chemotherapy and immunosuppressant medication and more frequently had decreased leukocyte counts. Maximum frequency of missing data per identified confounder was 2.7% (Online Supplementary Table S6).

The association between types of malignancies and red cell alloimmunization Table 2 presents the number of cases and controls according to various types of malignancies. Acute leukemia was present in 14 cases (2.8%) compared to 74 (7.3%) controls. There was a reduced incidence of red cell alloimmunization in patients with acute (myeloid or lymphoblastic) leukemia and in patients with mature (B- or Tcell) lymphoma [adjusted RR 0.36 (95%CI: 0.19-0.68) and 0.30 (95%CI: 0.12-0.81), respectively]. Conversely, patients with chronic lymphocytic leukemia (CLL) showed a modest, albeit statistically non-significant, increased risk [adjusted RR 1.20 (95%CI: 0.36-3.93)]. No association between the other types of malignancies and red cell alloimmunization was observed, including MDS

and solid malignancies. Similarly, subtypes of solid tumors were not associated to red cell alloimmunization, although some RRs presented with wide 95% CIs (Online Supplementary Table S7). As extensive matching recommendations have only been introduced in the Netherlands since 2011,3 only one of 64 patients (1.6%) with MDS received CcEe- and K-matched units. Effects were similar in all six hospitals (data not shown).

The association between treatment modalities and red cell alloimmunization A total of 290 patients received chemo- and/or (antilymphocyte) immunotherapy during the implicated risk period. Use of any type of chemotherapy without immunotherapy was not associated with red cell alloimmunization. However, when regimens included lymphocyte-targeted monoclonal antibodies the adjusted RR was 0.27 (95%CI: 0.09-0.83) (Table 3). Twenty-five of the 49 patients (51%) treated with monoclonal antibodies received ATG (with or without alemtuzumab) for in vivo depletion of T cells in the context of an allogeneic HSCT (n=21), aplastic anemia (n=3), or combined pancreas-kidney organ transplant (n=1).

Table 1. Patients' characteristics during the alloimmunization risk period.

Characteristics Men Age in years (median, IQR) Cumulative number of red cell units received (median, IQR) Over lifetime* During risk period Days transfused during risk period (median, IQR)

Cases (N=505)

Controls (N=1010)

237 (46.9) 67.0 (55.0-75.9)

568 (56.2) 65.3 (51.6-75.1)

4 (2-8) 3 (2-6) 1 (1-3)

4 (2-8) 4 (2-8) 2 (1-3)

Values are number (N) (%), unless otherwise stated. IQR: interquartile range. *Up until the first positive screen for cases and up until the last available (negative) screen for controls.

Table 2. Association between various malignancies and red cell alloimmunization.

Hematologic malignancies Acute leukemia Myeloid Lymphoblastic‡ Myelodysplastic syndrome§ Multiple myeloma Myeloproliferative neoplasm|| Chronic lymphocytic leukemia Lymphoma¶ All (Mature) B-cell lymphoma T-cell lymphoma Non-hematologic malignancies Carcinoma Other

Cases (N=505)

Controls (N=1010)

RR (CI)*

Adjusted RR (CI)†

Excluded from analysis

14 (2.8) 14 (2.8) 0 (0) 18 (3.6) 10 (2.0) 9 (1.8) 5 (1.0)

74 (7.3) 62 (6.1) 12 (1.2) 46 (4.6) 26 (2.6) 29 (2.9) 7 (0.7)

0.31 (0.17-0.58) 0.38 (0.20-0.71) 0.00 (NC) 0.76 (0.43-1.36) 0.77 (0.36-1.62) 0.62 (0.29-1.33) 1.45 (0.45-4.67)

0.36 (0.19-0.68) 0.41 (0.22-0.79) 0.00 (NC) 0.75 (0.41-1.36) 0.79 (0.36-1.71) 0.64 (0.29-1.41) 1.20 (0.36-3.93)

1 0 1 2 0 0 0

5 (1.0) 4 (0.8) 1 (0.2)

35 (3.5) 28 (2.8) 6 (0.6)

0.27 (0.10-0.69) 0.27 (0.09-0.77) 0.33 (0.04-2.75)

0.30 (0.12-0.81) 0.30 (0.10-0.89) 0.37 (0.04-3.15)

2 2 2

112 (22.3) 12 (2.4)

183 (18.2) 31 (3.1)

1.30 (0.99-1.70) 0.77 (0.39-1.53)

1.01 (0.75-1.37) 0.83 (0.41-1.68)

7 1

Values are expressed as number (N) (%). *Adjusted for the matched variables: number of transfused red cell units and hospital. †Additionally adjusted for other potential confounders (for details, see Online Supplementary Table S5). ‡Acute lymphoblastic leukemia and acute lymphoblastic lymphoma. §Six patients were diagnosed with a myelodysplastic syndrome in combination with another hemato-oncological disorder. ||Including polycythemia vera, essential thrombocytosis, primary myelofibrosis, juvenile and chronic myelomonocytic leukemia. ¶One patient was diagnosed with an undifferentiated mature lymphoma. RR: relative risk; NC: not computable.

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Malignancies and red cell alloimmunization

Patients receiving chemotherapeutic agents for acute leukemia or lymphoma during the implicated risk period had substantially reduced alloimmunization incidences [RR 0.29 (95%CI: 0.14-0.60) and 0.08 (95%CI: 0.01-0.57), respectively]. This reduction in risk did not seem to be further influenced to any great extent by the time interval between the initial diagnosis and the period of risk (data not shown). In contrast, non-treated patients with these disorders demonstrated risks comparable to the remainder of the patient population (Table 4). Sixty-two of the 74 treated patients (84%) with acute leukemia received induction therapy during the alloimmunization risk period. Analogous to acute leukemia and mature lymphoma, the 22 patients who received treatment for MDS (including 13 patients receiving induction therapy and 7 receiving hypomethylating agents), demonstrated a trend towards reduced alloimmunization incidences [RR 0.31 (95%CI: 0.09-1.06)] (Table 4). Chemotherapy did not have any impact on risks in patients with other types of hematologic malignancies or carcinoma (Table 4 and Online Supplementary Table S8). A total of 54 patients received radiotherapy (of any dose and frequency), including 10 patients who received total body irradiation in the setting of an allogeneic HSCT. Radiotherapy was not associated with red cell alloimmunization (Table 3). Respectively 51, 13, and 10 patients underwent an allogeneic HSCT, an autologous HSCT, or both before or during the risk period. In 51 patients, a reduced-intensity allogeneic HSCT conditioning regimen was followed (including 8 patients who received a double cord transplant), while 10 patients received a myeloablative conditioning regimen. Alloimmunization incidences were substantially decreased in these allogeneic or autologous stem cell transplant recipients [RR 0.34, (95%CI: 0.16-0.74)], at least during the first six months after transplant (Table 3). There was no difference in alloimmunization risk between recipients of an autologous or allogeneic HSCT (data not shown).

Finally, the degree of leukopenia was strongly associated with diminished red cell alloimmunization (Table 5). Here, patients with leukocyte counts of less than 1.0x109/L demonstrated an adjusted RR of 0.33 (95%CI: 0.20-0.55). Similar results were obtained when we restricted these analyses to leukocyte counts determined within the week following the implicated transfusion (Table 5). The degree of leukopenia was associated with the type of malignancy and whether or not the patient received chemotherapy. In this regard, minimum leukocyte counts of less than 1.0x109/L were observed respectively in 66.2%, 75.9%, and 13.8% of patients with acute leukemia, lymphoma, and carcinoma receiving chemotherapy during the risk period (P<0.0001 for carcinoma vs. acute leukemia and for carcinoma vs. lymphoma).

Discussion In this nested case-control study, we evaluated whether patients diagnosed with hematologic malignancies and solid cancers differed from the general transfused patient population with regards to the risk of forming red cell alloantibodies. Patients treated for acute leukemia (of either myeloid or lymphoblastic origin) and patients with mature (B- or T-cell) lymphomas demonstrated a 3-fold decrease in the incidence of clinically relevant alloantibodies against red cell alloantigens. In contrast, the alloimmunization incidence among patients treated for other hematologic malignancies or solid tumors was similar to those among the non-malignant patient population. Although earlier reports only observed similar or even increased red cell alloimmunization frequencies in the oncological patient population,9-11 these prevalence-based studies did not adjust for the substantial number of transfusions these patients usually receive. However, it is well known that the cumulative transfusion dose is an important determinant of alloimmunization.5 Consequently, the

Figure 1. Illustration of the alloimmunization risk period. For each case, the last antigen mismatched transfusion preceding the first serological detection of an alloantibody was defined as the â&#x20AC;&#x2DC;implicated (Nth) transfusionâ&#x20AC;&#x2122; since this transfusion most likely triggered alloimmunization. Alloimmunizations within seven days of the first antigen mismatched transfusion were not taken into consideration as these most likely represented boosting rather than primary alloimmunizations. An alloimmunization risk period was then constructed starting 30 days before and finishing seven days after the defined implicated transfusion. Subsequently, for each case, 2 controls who received at least the same number of red cell units were randomly selected and a similar alloimmunization risk period was constructed around the Nth transfusion. In this example, as the fourth red cell unit most likely elicited red cell alloimmunization, the alloimmunization risk period in both the case and control was constructed around the fourth transfusion. Figure adapted from: Evers et al.15

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D. Evers et al. Table 3. Treatment modalities and red cell alloimmunization risks.

Cases (N=505) Chemo- and/or immunotherapy Type None 437 (86.9) (Only) chemotherapy‡ 61 (12.1) (Only) immunotherapy§ 1 (0.2) Chemo- and immunotherapy 4 (0.8) HSCT Type Autologous or allogeneic || 10 (2.0) Timing (months before implicated transfusion) None 495 (98.0) 0-1 4 (0.8) >1-6 3 (0.6) >6 3 (0.6) Radiotherapy 15 (3.0)

Controls (N=1010)

RR (CI)*

Adjusted RR (CI)†

Excluded from analysis 6

782 (77.7) 180 (17.9) 4 (0.4) 40 (4.0)

ref 0.57 (0.41-0.79) 0.57 (0.06-5.67) 0.17 (0.06-0.48)

ref 0.86 (0.54-1.36) 0.62 (0.07-5.18) 0.27 (0.09-0.83) 0

64 (6.3)

0.29 (0.14-0.58)

0.34 (0.16-0.74)

946 (93.7) 27 (2.7) 24 (2.4) 13 (1.3) 39 (3.9)

ref 0.28 (0.09-0.81) 0.22 (0.06-0.75) 0.46 (0.13-1.70) 0.78 (0.42-1.44)

ref 0.34 (0.11-1.07) 0.24 (0.07-0.86) 0.55 (0.14-2.09) 0.75 (0.39-1.44)

0

Values are expressed as number (N) (%). *Adjusted for the matched variables: number of transfused red cell units and hospital. †Additionally adjusted for other potential confounders (for details, see Online Supplementary Table S5). ‡All medication under subcategory L01 within the Anatomical Therapeutic Chemical (ATC) classification index with the exception of monoclonal antibodies. §Monoclonal antibodies directed against B- and/or T-lymphocyte markers received by 49 patients (rituximab n=20, alemtuzumab n=5, and anti-thymocyte globulin n=25). ||10 patients received an allogeneic stem cell transplant after an earlier autologous HSCT; RR: relative risk; CI: confidence interval; HSCT: hematopoietic stem cell transplant (either autologous or allogeneic) received before or during the alloimmunization risk period.

observed positive associations might have been due to the quite intensive red cell transfusion support that is generally needed in the treatment of certain malignancies rather than to disease-specific characteristics. So far, no studies have compared specific oncological diseases for alloimmunization risks. Our findings suggest that especially the dose-intensive immunosuppressive therapy influences alloimmunization. This seems biologically plausible. Several classical cytotoxic agents frequently used in the treatment of acute leukemia and lymphoma, including cyclophosphamide, purine nucleoside analogs, and anthracyclines, are known to induce prolonged (mainly naïve) CD4+ T-cell and B-cell depletion.25-28 Moreover, chemotherapeutic regimens often include corticosteroids, a class of immunosuppressants which we earlier reported to protect against red cell alloimmunization.8 Significantly reduced incidence of red cell alloimmunization was also found in patients receiving anti-lymphocyte targeted agents (i.e. ATG, alemtuzumab, and rituximab). ATG is well known for its strong and prolonged T-cell depleting effects.29,30 In addition, ATG preparations contain antibodies against several B- and even plasma cell-specific markers.30,31 In agreement with this, eradication of B cells by rituximab has been shown to coincide with impaired primary as well as re-call vaccine responses.32-35 Finally, we observed profoundly lower alloimmunization rates in the setting of HSCT, either autologous or allogeneic, which appeared to be sustained at least during the first six months after transplant. Even though we cannot fully exclude the possibility that the 8 cases of alloimmunization following an allogeneic HSCT could have been elicited by donor-recipient red cell antigen mismatches (in addition to exposure via transfusion), these findings are consistent with previous studies reporting anti-D formation to be rare in RhD-negative HSCT recipients exposed to RhD.36-38 Reconstitution of adaptive immune cells generally takes up to 6-12 months following HSCT,39-44 depending on age-associated thymic functioning, type of stem cell harvest, and intensity of T-cell deple56

tion strategies, while humoral immunity may continue to be deficient even after several years.45,46 Although treatment-induced immunosuppression seems to be the principle explanation for our observations, other non-measured factors associated with receiving treatment (e.g. co-morbidities and disease stage) might have interacted with disease-specific effects on the immune response. Therefore, we cannot exclude the possibility that part of the observed effects could be directly related to the diseases themselves, i.e. induction of an immunosuppressive but tumor tolerant state via host immune evasion mechanisms of malignant cells.47-50 Furthermore, as patients received a wide range of different chemotherapeutic regimens at varying times before the alloimmunization risk period, it is not possible to come to any firm conclusions as to whether or to what extent patients in complete remission of their treated malignancy should be considered to be significantly immunosuppressed. As such, our RRs might underestimate true effects and our results do not preclude the possibility that these patients have a diminished red cell alloimmunization risk. In contrast to some other studies,12,13 our incidencebased analysis did not demonstrate an enhanced alloimmunization susceptibility with a diagnosis of MDS. However, and similar to intensively treated patients with acute leukemia and mature lymphoma, patients who received treatment for their MDS tended to show incidence of reduced alloimmunization. Consequently, the decision to transfuse extended donor-matched products to this patient population should not be based on the MDS diagnosis itself, but on other factors associated to an increased alloimmune response, e.g. a high transfusion burden. Finally, the alloimmunization RR in patients with chronic lymphocytic leukemia (CLL) independent of their treatment seemed to be increased compared to lymphoma patients, although we acknowledge that the number of CLL patients in the current study is not sufficient to conhaematologica | 2017; 102(1)


Malignancies and red cell alloimmunization

Table 4. Chemotherapy and red cell alloimmunization risks.

Type of malignancy

Chemotherapy

Cases (N=505)

Controls (N=1010)

RR (CI)*

Adjusted RR (CI)†

+

489 4 10

931 10 64

ref 0.77 (0.22-2.66) 0.25 (0.12-0.51)

ref 0.88 (0.25-3.09) 0.29 (0.14-0.60)

+

484 15 3

959 28 18

ref 1.06 (0.54-2.07) 0.32 (0.09-1.12)

ref 1.04 (0.52-2.06) 0.31 (0.09-1.06)

+

498 4 1

969 7 28

ref 1.08 (0.31-3.76) 0.07 (0.01-0.49)

ref 1.26 (0.35-4.51) 0.08 (0.01-0.57)

+

390 85 26

821 141 39

ref 1.28 (0.95-1.73) 1.40 (0.84-2.35)

ref 0.99 (0.71-1.38) 1.14 (0.67-1.94)

Acute leukemia + + Myelodysplastic syndrome + + Lymphoma + + Carcinoma + +

+ = present; - = absent. Only numbers of patients for whom the presence or absence of a given malignancy and the use of chemotherapy during the alloimmunization risk period could be determined are presented. *Adjusted for the matched variables: number of transfused red cell units and hospital. †Additionally adjusted for other potential confounders (for details, see Online Supplementary Table S5). N: number; RR: relative risk; CI: confidence interval.

Table 5. Leukopenia and red cell alloimmunization risks.

Minimum leukocyte counts (x109/L) during: Alloimmunization risk period‡ 4-10 2-<4 1-<2 <1 ≤1 week following implicated transfusion 4-10 2-<4 1-<2 <1

Cases (N=505)

Controls (N=1010)

RR (CI)*

Adjusted RR (CI)†

307 61 14 26

524 128 43 142

ref 0.82 (0.58-1.15) 0.52 (0.27-0.99) 0.27 (0.17-0.44)

ref 0.87 (0.61-1.24) 0.59 (0.31-1.13) 0.33 (0.20-0.55)

273 44 15 19

485 107 41 119

ref 0.72 (0.47-1.10) 0.60 (0.30-1.23) 0.24 (0.13-0.44)

ref 0.80 (0.52-1.23) 0.75 (0.36-1.58) 0.34 (0.17-0.66)

Minimum leukocyte counts as measured during the alloimmunization risk period and as measured during the week following the implicated transfusion.Values are expressed as number (N) (%). Cumulative numbers of presented cases and controls do not necessarily equal the total number of cases and controls, as patients with leukocytosis are not presented. * Adjusted for the matched variables: number of transfused red cell units and hospital. †Additionally adjusted for other potential confounders (for details, see Online Supplementary Table S5). ‡P=0.02 for trend analysis. RR: relative risk; CI: confidence interval.

firm such a hypothesis. However, CLL is characterized by profound immune disturbances including non-clonal formation of IgG auto-antibodies directed against blood cell antigens.51-53 Observations seem to suggest that the disease disturbs normal regulatory potential. Seemingly in contrast with these findings, antimicrobial vaccination responses are often compromised in CLL patients.54 Some final comments regarding our methods are appropriate. First, the use of an incidence-density sampling strategy guaranteed that controls were exposed to at least the same number of red cell units as their matched cases.16,55 Given this adjustment for cumulative number of red cell exposures, our RRs reflect relative risks independent of exposures. Our alloimmunization risk period was defined specifically to provide a comprehensive study of the influential effect of conditions present around the time of red cell exposure. As the immunosuppressive effects of various treatment regimens are slow to wear off, we preferred to use a relatively long period of risk to precede the implicated transfusion. Second, our strategies do not fully guarantee the excluhaematologica | 2017; 102(1)

sion of all boosting events. Actual ‘lag periods’, i.e. the time needed before antibody levels become detectable after primary antigen encounter, are currently unknown and may even differ according to the antigen used. Regarding our chosen lag period of seven days, we cannot, therefore, fully exclude the possibility that our study included patients whose antibody titers became undetectable over time and who quickly demonstrated re-call responses upon re-exposure to the alloantigen. However, we had thought that a substantial amount of boosting reactions as primary alloimmunization events would have biased our RRs towards the null-effect. However, a sensitivity analysis, in which we excluded the 53 patients in whom alloantibodies were discovered during the second week after their first antigen-incompatible transfusion, showed no change in RRs (data not shown). We are confident, therefore, that any possible bias deriving from our choice of lag period is small. Third, we observed no associations with red cell alloimmunization other than the above mentioned hematologic malignancies and specific types of solid malignancies, 57


D. Evers et al.

although the low numbers of some of these subgroups and the consequent wide CIs per RR prevent any firm conclusions to be made. A much larger study or a meta-analysis of similar studies is needed to assess whether these malignancies are indeed not associated to red cell alloimmunization. Also, due to the fact that remission evaluations available during the alloimmunization risk period were not always complete, we were unable to assess whether the disease stage itself is associated to cell alloimmunization. Finally, since patients treated with chemotherapy received a wide range of chemotherapeutic agents and combinations, as well as varying dose intensities, we were not able to quantify risks according to each single agent. In conclusion, risks associated with red cell alloimmunization are significantly reduced in patients treated for acute leukemia and mature lymphomas, as well as in recipients of an autologous or allogeneic HSCT. These diminished immune responses most likely reflect the intensity of treatment-associated immunosuppression. In

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Malignancies and red cell alloimmunization

33. Cha Z, Li C, Zang Y, et al. Adaptive B cell responses in rituximab-treated diffuse large B cell lymphoma patients during complete remission. Tumour Biol. 2015;37(1):829-835. 34. van der Kolk LE, Baars JW, Prins MH, van Oers MH. Rituximab treatment results in impaired secondary humoral immune responsiveness. Blood. 2002;100(6):22572259. 35. Yri OE, Torfoss D, Hungnes O, et al. Rituximab blocks protective serologic response to influenza A (H1N1) 2009 vaccination in lymphoma patients during or within 6 months after treatment. Blood. 2011;118(26):6769-6771. 36. Asfour M, Narvios A, Lichtiger B. Transfusion of RhD-incompatible blood components in RhD-negative blood marrow transplant recipients. MedGenMed. 2004; 6(3):22. 37. Cid J, Lozano M, Fernandez-Aviles F, et al. Anti-D alloimmunization after D-mismatched allogeneic hematopoietic stem cell transplantation in patients with hematologic diseases. Transfusion. 2006;46(2):169-173. 38. Mijovic A. Alloimmunization to RhD antigen in RhD-incompatible haemopoietic cell transplants with non-myeloablative conditioning. Vox Sang. 2002;83(4):358-362. 39. Booth C, Lawson S, Veys P. The current role of T cell depletion in paediatric stem cell transplantation. Br J Haematol. 2013; 162(2):177-190. 40. Mackall CL, Fleisher TA, Brown MR, et al. Age, thymopoiesis, and CD4+ T-lymphocyte regeneration after intensive chemother-

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59


ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Iron Metabolism & Its Disorders

Ferrata Storti Foundation

Erythroferrone contributes to hepcidin repression in a mouse model of malarial anemia

Chloé Latour,1 Myriam F. Wlodarczyk,2 Grace Jung,3 Aurélie Gineste,1 Nicolas Blanchard,2 Tomas Ganz, 3,4 Marie-Paule Roth,1 Hélène Coppin1 and Léon Kautz 1

Haematologica 2017 Volume 102(1):60-68

IRSD, Université de Toulouse, INSERM U1220, INRA U1416, ENVT, UPS, Toulouse, France; 2CPTP, Université de Toulouse, CNRS U5282, Inserm U1043, UPS, Toulouse, France and Departments of 3Pathology and 4Medicine, David Geffen School of Medicine, University of California, Los Angeles, USA

1

ABSTRACT

M

Correspondence: leon.kautz@inserm.fr or helene.coppin@inserm.fr

Received: May 29, 2016. Accepted: September 14, 2016. Pre-published: September 22, 2016. doi:10.3324/haematol.2016.150227

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/60

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is required for any other use.

60

alaria, a major global health challenge worldwide, is accompanied by a severe anemia secondary to hemolysis and increased erythrophagocytosis. Iron is an essential functional component of erythrocyte hemoglobin and its availability is controlled by the liverderived hormone hepcidin. We examined the regulation of hepcidin during malarial infection in mice using the rodent parasite Plasmodium berghei K173. Mice infected with Plasmodium berghei K173 develop a severe anemia and die after 18 to 22 days without cerebral malaria. During the early phase of blood-stage infection (days 1 to 5), a strong inflammatory signature was associated with an increased production of hepcidin. Between days 7 and 18, while infection progressed, red blood cell count, hemoglobin and hematocrit dramatically decreased. In the late phase of malarial infection, hepcidin production was reduced concomitantly to an increase in the messenger RNA expression of the hepcidin suppressor erythroferrone in the bone marrow and the spleen. Compared with wild-type mice, Erfe–/– mice failed to adequately suppress hepcidin expression after infection with Plasmodium berghei K173. Importantly, the sustained production of hepcidin allowed by erythroferrone ablation was associated with decreased parasitemia, providing further evidence that transient iron restriction could be beneficial in the treatment of malaria. Introduction Malaria remains a major health burden in intertropical countries. According to the annual World Malaria Report by the World Health Organization, an estimated 214 million people were clinically affected by malaria in 2015 and approximately 438 000 of these patients died due to severe complications.1 Infection initiates when Plasmodium sporozoites are injected together with anti-coagulant saliva during a blood meal of an infected Anopheles mosquito. Sporozoites migrate to the liver in search of a favorable niche in the hepatocyte where they replicate extensively. Thousands of merozoites are then produced and released into the circulation to invade red blood cells (RBCs),2 in which parasites further replicate during the symptomatic blood stage of the asexual developmental cycle.3 Nearly all forms of life, including plants and pathogens, utilize iron for fundamental processes such as DNA synthesis, oxygen transport and generation of ATP. Plasmodium species are no exception, as the replication of the parasite in the liver and in erythrocytes is highly dependent on iron.4 Indeed, iron chelators can inhibit Plasmodium growth in vitro,5 in murine models of malaria infection,6,7 and in malaria-infected monkeys.8 In humans, iron deficiency appears to protect against severe malaria,9-11 while iron supplementation increases the risks of infection and disease.1215 Iron deficiency also provides protection against infection with Plasmodium berghei in mice.16,17 haematologica | 2017; 102(1)


ERFE suppresses hepcidin in malarial anemia

The host systemic iron availability is controlled by the iron regulatory hormone hepcidin,18-20 which could therefore influence the susceptibility to malaria. Iron is absorbed from the diet by intestinal enterocytes and recycled from senescent or damaged RBCs by macrophages.21 The export of iron across the basolateral membrane of enterocytes and from iron-recycling macrophages is ensured by the sole known iron exporter, ferroportin. Hepcidin binds to ferroportin and causes its internalization and degradation.19,20 The loss of ferroportin from the cell surface prevents iron efflux from intestinal enterocytes and from macrophages, leading to iron retention in these cells and subsequent hypoferremia. Multiple studies have shown that hepcidin is upregulated during malarial infection in humans22-24 and in murine models.25,26 The underlying mechanisms may involve parasite-induced inflammatory pathways, but they are still unclear. Under the influence of high hepcidin concentration, as iron is redistributed to macrophages, the flow of iron into plasma is decreased, which routes iron away from the parasite and thereby prevents its multiplication. As a consequence, combined with RBC destruction by the parasite, this may worsen the host anemia because of restricted iron availability for erythropoiesis. Although the majority of studies on hepcidin and malaria have demonstrated an increased production of hepcidin during malarial infection, three recent studies have shown that in certain circumstances, hepcidin suppression may also occur. One study reported that among all children presenting with malaria, those with severe anemia had the lowest hepcidin levels.27 Another study demonstrated that children with uncomplicated malaria had higher hepcidin levels than those who could be classified as either presenting with severe anemia or cerebral malaria.28 Finally, a group of children with severe malarial anemia exhibited very low serum hepcidin levels.29 Taken together, these studies clearly indicate that during severe malarial anemia, the signaling pathway that suppresses hepcidin can override the activation pathway associated with parasiteinduced inflammation. The mechanisms of hepcidin suppression in severe malaria syndromes are not well defined. In the two human studies that monitored erythropoietin (EPO) levels and serum hepcidin in malaria infection, EPO and hepcidin were negatively correlated.27,29 One animal study has also demonstrated a significant negative correlation between serum EPO and hepcidin in mice infected with Plasmodium berghei.24 We recently showed that high levels of EPO cause hepcidin suppression indirectly by inducing the production of the erythroid regulator erythroferrone (ERFE) by erythroid progenitors in the bone marrow and the spleen.30 ERFE is secreted in the circulation and acts on the liver to suppress hepcidin expression and increase dietary iron absorption and iron release from macrophages.30 To assess the role of ERFE in hepcidin suppression observed in severe malaria, we first checked whether Erfe expression was upregulated in a murine model of malaria induced by Plasmodium berghei K173 (PbK), a strain that causes severe malarial anemia. Mice injected with PbK-parasitized RBCs develop high parasitemia and severe anemia and die without cerebral symptoms 18-22 days post-infection.31 We then infected Erfedeficient mice and examined the impact of Erfe deletion on hepcidin expression, parasitemia and RBC indices. By highlighting the contribution of ERFE in hepcidin regulahaematologica | 2017; 102(1)

tion in malaria, this study may suggest new therapeutic strategies to combat malaria.

Methods Mice and infection Since iron parameters and hepcidin levels differ significantly between male and female mice,32,33 only male mice were used in this study. 9 week-old C57BL/6 wild-type (WT) mice (5 to 10 per time-point) were infected intraperitoneally with 106 PbK-infected RBCs, and given free access to tap water and standard laboratory mouse chow diet (250 mg iron/kg; SAFE, Augy, France) during the 18 days post-infection. All animals were kept in pathogen-free animal facilities in Toulouse, and analyzed at days 0, 1, 2, 3, 4, 5, 7, 9, 11, 13, 16 and 18 post-infection. PbK was serially passaged in vivo in C57BL/6 mice. Infected blood was harvested at day 5-7 postinfection and stored as frozen stabilates in Alsever's solution containing 10% glycerol. Erfe–/– mice on a C57BL/6 background were maintained at UCLA on a standard chow (200 ppm iron; Labdiet, MO, USA). Control WT C57BL/6J males were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). 8 week-old WT and Erfe–/– mice were infected intraperitoneally with 106 PbK-infected RBCs (6 mice per genotype). 50 ml of blood was sampled on days 0, 7, 10 and 13 to determine complete blood count and hepcidin levels, and mice were sacrificed on day 16. To monitor the effect of repetitive blood collection, control WT and Erfe–/– mice were injected intraperitoneally with normal saline and manipulated similarly to the infected mice (4 mice per genotype).

Ethic statement Experimental protocols were approved by the Midi-Pyrénées Animal Ethics Committee, France (n° MP/07/59/10/11). Experiments including Erfe–/– mice were conducted in accordance with guidelines by the National Research Council and were approved by the University of California, Los Angeles, USA (protocol #2011-114-13C).

Measurement of hematologic parameters and parasitemia Complete blood counts were obtained with a CELL-DYN Emerald Hematology System (Abbott Diagnostics, France) or with a HemaVet blood analyzer (Drew Scientific) for the experiment performed at UCLA. Serum iron concentration was determined using the IRON Direct Method kit (BIOLABO, Maizy, France). Parasitemia (i.e., the percentage of infected RBCs) was assessed at each time point by microscopic counts of thin blood smears stained with Giemsa solution (Diff-Quik, Medion Diagnostics, Switzerland).

Quantitation of messenger RNA (mRNA) levels Total RNA from mouse liver, spleen, kidney or bone marrow was extracted using TRIzol (Invitrogen). Complementary DNA (cDNA) was synthesized using M-MLV RT (Promega). Quantitative polymerase chain reaction (qPCR) reactions were prepared with LightCycler® 480 DNA SYBR Green I Master reaction mix (Roche Diagnostics) and run in duplicate on a LightCycler® 480 System (Roche Diagnostics). For experiments in which WT and Erfe–/– mice were compared, cDNA was synthesized using iScript (Bio-rad). Quantitative PCR reactions were prepared with SsoAdvanced Universal Sybr Green supermix (BioRad) and run in duplicate on a CFX Connect Instrument (Bio-Rad). Primer sequences are indicated in the Online Supplementary Table S1. Tnf, Ifn-γ, Hamp, Erfe, Gypa, Gdf15 and Twsg1 mRNA transcript 61


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abundance was normalized to the reference gene Rpl4. Epo mRNA expression was normalized to the reference gene Hprt. Results are expressed as -ΔCt ± standard error of the mean (i.e., the cycle threshold differences between reference and target genes within each group of mice).

Serum hepcidin enzyme-linked immunosorbent assays Serum hepcidin and serum IL-6 levels were quantified using the Intrinsic LifeSciences (La Jolla, CA, USA) Hepcidin-Murine Compete competitive ELISA and the R&D Systems Mouse IL-6 Quantikine ELISA Kit, respectively, according to the manufacturer's instructions.

Statistical analysis The statistical significance of differences between groups was evaluated by one-way ANOVA followed by Dunnett’s multiple comparisons test using GraphPad Prism version 6.00 (GraphPad Software, La Jolla, CA, USA). The Student's t-test was used to compare WT and Erfe–/– mice. A P value <0.05 in a two-tailed test was considered as statistically significant.

Results Plasmodium berghei K173 infection causes inflammation and leads to severe anemia We first assessed parasitemia and the hematological parameters 1 to 18 days after infection of mice with PbK. The parasites became detectable in the bloodstream 3 days after injection and multiplied exponentially to nearly 70% of parasitized RBCs 18 days after infection (Figure 1A). White blood cells count increased concomitantly with the parasitemia from day 7 to day 18 (Figure 1B). We

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Hepcidin expression in Plasmodium berghei K173-infected mice is first induced by parasite-induced inflammation and, in a second phase, suppressed while anemia worsens Increased production of the liver-produced hormone hepcidin has proven beneficial to prevent superinfections.25 However, hepcidin expression is stimulated by inflammation during infections, but also repressed by increased erythropoietic activity during anemia. We therefore measured circulating levels of hepcidin and liver hepcidin mRNA expression in PbK-infected mice. Consistent with the inflammatory status, serum hepcidin concentration and liver hepcidin mRNA expression were increased by approximately 2-fold 3 to 5 days after infection with PbK compared to control mice (Figure 3A,B). Since hepcidin expression is regulated by iron and inflammation, we next assessed the iron parameters and the production of

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next examined the expression of inflammatory cytokines during PbK infection. Tnf mRNA expression was induced 8-fold at day 1 and more than 30-fold at day 18 in the liver of PbK-infected mice compared to control mice (Figure 1C). Similarly, interferon-γ (Ifn-γ) expression was slightly increased at day 2 and maximally increased by 30- to 60fold between day 5 and day 18 after infection with PbK compared to controls (Figure 1D). On the contrary, RBC, hemoglobin concentration, and hematocrit dramatically decreased between day 7 and day 18 after infection (Figure 2A-C), whereas mean corpuscular volume (MCV) increased between days 13 and 18 (Figure 2D). Collectively, these results indicate that infection with PbK leads to a severe malarial anemia with subsequent death after 18 days.

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Figure 1. Plasmodium berghei K173 infection is accompanied by a strong inflammatory response. Parasitemia (A) and WBC count (B) progressively increased from day 7 to day 18. Hepatic Tnf mRNA expression (C) increased from day 1 to day 18 in the liver of mice infected with PbK. Similarly, Interferon-γ (Ifn-γ) expression (D) significantly increased by day 2 and reached a plateau at day 5 after infection with PbK. Data shown are mean ± sem and were compared for each time point to values for control mice at t=0 (n=5 to 10 mice per group except at day 18 where only 3 mice had survived) by one-way ANOVA. ***P<0.001, **P<0.01, *P<0.05. WBC: white blood cell; PbK: Plasmodium berghei K173.

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IL-6 and activin B, two activators of hepcidin expression during inflammation. Serum iron concentration was only marginally increased 3 to 5 days after infection while liver Bmp6 mRNA expression decreased 4 to 5 days after infection (Figure 4A,B), suggesting that changes in circulating iron and liver iron content do not contribute to hepcidin upregulation during malarial infection. Changes in serum iron concentration are concomitant with the increase in parasitemia 3 days after infection. Erythrocytic forms of Plasmodium degrade approximately 60% to 80% of the total RBC hemoglobin content, which generates free heme and reactive oxygen species.34 We therefore surmise that the slight increase in serum iron observed at days 3 to 5 may be attributable to the release of free iron after hemoglobin degradation, or to positive interference of contaminating heme with the colorimetric procedure during the measurement.35 Compared to mice injected with lipopolysaccharide (LPS), serum IL-6 concentration and liver activin B (Inhbb) mRNA expression (Figure 4C,D) were only modestly increased after infection with PbK, and hepatocytes STAT3 phosphorylation was not detectable (Online Supplementary Figure S1). These results suggest that these molecules are not major contributors to the stimulation of hepcidin production during malaria. While anemia progressed, serum hepcidin concentration decreased below baseline levels 13 to 18 days after infection (Figure 3A). Hepcidin mRNA expression was also repressed by approximately 8- to 32-fold between 13 and 18 days after infection with PbK compared to control mice (Figure 3B).

Hepcidin suppression coincides with increased erythropoietic activity and erythroferrone production In parallel, Epo mRNA expression in the kidney was upregulated between days 7 and 18 in mice infected with

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PbK compared to control mice (Figure 5A). Similarly, spleen index (spleen weight relative to body weight) increased from day 4 to day 18 after infection with PbK (Figure 5B) and glycophorin A (Gypa) mRNA expression, a marker of erythropoiesis, was elevated by approximately 5- to 64-fold in the spleen between days 7 and 18 (Figure 5C). Collectively, these results show a progressive increase in erythropoietic activity that is proportional to the degree of anemia in PbK-infected mice and accompanied by extramedullary erythropoiesis. Interestingly, Gypa mRNA expression was reduced 2 to 5 days after infection in the bone marrow and 3 days after infection in the spleen, presumably because of an inhibition of erythropoiesis by inflammatory cytokines36 during Plasmodium berghei infection. To decipher the mechanism involved in hepcidin suppression, we studied the expression of the known negative regulators of hepcidin: Erfe,30 Gdf15,37 and Twsg1.38 We found that Erfe mRNA expression mirrored circulating levels of EPO, and was induced in the bone marrow (~128-fold) and in the spleen (~2000-fold) of PbK-infected mice compared to control mice at day 18 (Figure 5D). The increase in Erfe mRNA expression in the spleen is mostly attributable to the expansion of the splenic erythroid compartment, as shown by Gypa mRNA expression (Figure 5C). On the contrary, Gdf15 and Twsg1 mRNA expression did not correlate with hepcidin suppression during malarial infection. Indeed, Gdf15 mRNA expression was only slightly increased between day 1 and day 9 in the bone marrow and the spleen of infected mice, and returned to normal before hepcidin suppression (Online Supplementary Figure S2). Similarly, Twsg1 mRNA expression showed only minor fluctuations in the spleen, and was significantly decreased in the bone marrow 11 and 13 days after infection compared to control mice (Online Supplementary Figure S2).

Figure 2. Mice infected with Plasmodium berghei K173 develop a severe anemia. RBC count (A), hemoglobin concentration (B) and hematocrit (C) decreased dramatically from day 7 to day 18. Conversely, MCV was increased 13 to 18 days after infection with PbK. Data shown are mean Âą sem and were compared for each time point to values for control mice at t=0 (n=5 to 10 mice per group except at day 18 where only 3 mice had survived) by one-way ANOVA. ***P<0.001, **P<0.01, *P<0.05. RBC: red blood cell; PbK: Plasmodium berghei K173; MCV: mean corpuscular volume.

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Figure 3. Biphasic regulation of hepcidin production during Plasmodium berghei K173 infection. Consistent with the inflammatory stimulation, serum hepcidin concentration (A) and hepcidin (Hamp) mRNA expression in the liver (B) were increased between day 3 and day 5 but progressively returned to normal between day 5 and 11 and were significantly reduced between day 13 and day 18. Data shown are mean ± sem and were compared for each time point to values for control mice at t=0 (n=5 to 10 mice per group except at day 18 where only 3 mice had survived) by one-way ANOVA. ***P<0.001, **P<0.01, *P<0.05. PbK: Plasmodium berghei K173.

Erythroferrone contributes to hepcidin suppression during malarial anemia, and its absence in Erfe–/– mice has a significant impact on parasitemia To determine whether ERFE contributes to hepcidin suppression during malarial infection, we compared WT and Erfe–/– mice after infection with PbK. Six mice per genotype were infected with PbK, and blood was repetitively sampled on days 0, 7, 10 and 13 before the mice were analyzed on day 16. The repetitive blood collection did not influence serum hepcidin concentration (Figure 6A). We found that serum hepcidin concentration was similarly elevated in WT and Erfe-deficient mice 7 and 10 days after infection compared to baseline at day 0 (Figure 6B). However, whereas serum hepcidin concentration was reduced below baseline in WT mice 13 and 16 days after infection, hepcidin suppression was totally blunted in Erfe-deficient mice. In the same line, hepatic hepcidin mRNA expression was 6-fold higher in Erfe–/– mice compared to WT mice 16 days after infection with PbK (Figure 6C). As a consequence of higher circulating levels of hepcidin, Erfe–/– mice had higher spleen iron content compared to WT mice 16 days after infection (Figure 6D), which is consistent with hepcidin-induced degradation of the iron exporter ferroportin at the cell surface of macrophages. These results clearly demonstrate that ERFE contributes to hepcidin suppression and the mobilization of iron from the stores during malarial infection. Interestingly, determination of parasitemia revealed lower parasite count in Erfedeficient mice compared to WT mice 13 days after infection (Figure 7A), suggesting that iron retention in the reticuloendothelial system temporarily impeded the multiplication of the parasite. Despite higher hemoglobin concentration and RBC in Erfe–/– compared to WT mice at day 10, the drop in hemoglobin (Figure 7B) and RBC (Online Supplementary Figure S3) was more prominent in Erfe–/– mice than in WT mice between day 10 and day 13 after infection with PbK (Figure 7B). Indeed, Erfe–/– mice had significantly lower hemoglobin at day 13 compared to WT mice. Similarly, MCV and mean corpuscular hemoglobin (MCH) were also lower in Erfe-deficient mice compared to 64

WT mice at day 13 (Figure 7C,D), indicating a mild iron restriction in Erfe–/– mice. This shows that, by preventing the complete suppression of hepcidin, the absence of ERFE leads to transient iron restriction during Plasmodium berghei infection and has a significant impact on parasitemia.

Discussion Malaria is currently one of the most geographically widespread and deadly diseases resulting in around half a million deaths every year.1 Iron, and its regulatory hormone hepcidin, play a crucial role in determining the multiplicity of malaria infections within the host. In accordance with previous studies on other murine models of malaria infection,25,26 we observed that the injection of PbK-infected RBCs into C57BL/6 mice led to a rapid upregulation of hepcidin production. The circulating levels of hepcidin more than doubled 3 to 5 days after infection, but the mechanisms involved in this upregulation remain unclear. Although IL-6 has been shown to be correlated with hepcidin in some studies,27-29 in another study serum IL-6 and urinary hepcidin were not significantly associated.23 Furthermore, in one ex vivo study, human peripheral blood mononuclear cells co-incubated with Plasmodiuminfected RBCs exhibited a significant upregulation of hepcidin mRNA without a concomitant IL-6 mRNA increase.39 Finally, a study investigating the mechanisms by which blood-stage malaria infection can prevent the establishment of a liver-stage infection, which is thought to be modulated by hepcidin, found that liver-stage inhibition was preserved in mice treated with anti-IL-6 antibodies.25 Thus, the role of IL-6 in hepcidin induction in malaria remains controversial. Notably, in comparison to mice injected with LPS,40 we did not observe any physiologically relevant increase in serum IL-6 concentration 4 to 5 days after infection with PbK, and phosphorylated STAT3 was not detected in hepatocytes (Figure 4 and Online Supplementary Figure S1). Activin B is a ligand of the TGF-β superfamily that is upregulated by inflammatory haematologica | 2017; 102(1)


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B Serum iron concentration (mM)

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stimuli such as LPS, and was shown to increase hepcidin expression through SMAD1/5/8 signaling in hepatoma cell lines.40 Similarly to IL-6, we detected only a mild induction of activin B mRNA expression compared to mice challenged with LPS (Figure 4). It is therefore unlikely that IL-6 and activin B stimulate hepcidin expression during Plasmodium berghei infection. Dissecting the pathways leading to early hepcidin upregulation in response to parasite exposure represents a major goal for future studies. Although the mechanism stimulating hepcidin in malaria is unclear, increased hepcidin production appears to have several advantages for the host. First, as seen in this study, sustained hepcidin production leads to iron relocalization in macrophages, which is reflected by the increased splenic iron content in Erfe-deficient mice compared to WT mice. Although hepcidin upregulation also blocks iron absorption from the diet, which together with iron retention in macrophages probably contributes to the malarial anemia, it routes iron away from pathogens that could potentially exploit circulating iron, limiting Plasmodium growth and proliferation. Interestingly, the increased hepcidin caused by blood-stage infections was shown to significantly reduce the development of liverstage Plasmodium infection by limiting the access of proliferating parasites to iron in hepatocytes.25 Clearance of an ongoing blood-stage infection with chloroquine returned hepcidin mRNA to normal levels and allowed the development of a secondary liver infection. Thus, the redistribution of iron caused by hepcidin is a key factor that can determine the outcome of liver Plasmodium infection, and may protect children living in endemic areas of malaria from superinfections.41 haematologica | 2017; 102(1)

Figure 4. Serum iron and IL-6 concentration and liver Bmp6 and Inhbb mRNA expression during Plasmodium berghei K173 infection. Serum iron concentration (A) was slightly increased at days 4, 13 and 16 whereas Bmp6 mRNA expression (B) was decreased 5 days after infection with PbK. Serum IL-6 concentration (C) and liver activin B (Inhbb) mRNA expression (D) were marginally increased 4-5 days after infection with PbK compared to mice challenged with LPS.40 Data shown are mean Âą sem and were compared for each time point to values for control mice at t=0 (n=5 to 10 mice per group except at day 18 where only 3 mice had survived) by one-way ANOVA. ***P<0.001, **P<0.01, *P<0.05. PbK: Plasmodium berghei K173; LPS: lipopolysaccharide; lL-6: interleukin 6.

Iron sequestered in macrophages is not available for an efficient bone marrow response to increased erythrophagocytosis of both parasitized and non-parasitized RBCs.42 As a consequence, starting at day 7, mice infected with PbK present with a progressive decrease in the number of RBCs, hemoglobin, and hematocrit. A few days later, massive erythrocyte lysis due to elevated parasitemia and the negative effects of inflammatory cytokines, including TNF-a and IFN-Îł, on reticulocyte production, leads to severe anemia in this experimental model. Stimulation of erythropoietic activity translates into a dramatic increase of EPO expression and extramedullary erythropoiesis. These manifestations are reminiscent of severe anemia observed in some children living in endemic areas of malaria,27,29 and is accompanied by a strong repression of hepcidin expression, both at the mRNA and the protein level. There is, therefore, a turning point post-infection where the signaling pathway that suppresses hepcidin overrides the activation pathway associated with blood-stage parasitemia. Consistent with previous studies,27,29 we observed that the suppression of hepcidin starting at day 7 was negatively correlated with the increase in EPO. More interestingly, we show herein that this suppression is also negatively correlated with the expression of the recently described erythroid factor ERFE in the bone marrow and in the spleen. Given that ERFE suppresses hepcidin during increased erythropoietic activity, we used Erfe-deficient mice to demonstrate that ERFE was indeed involved in the suppression of hepcidin in mice infected with PbK. We showed that, in contrast to WT mice, Erfe-deficient mice failed to repress their hepcidin below the level of non65


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Figure 5. Erfe mRNA expression is highly increased during infection with Plasmodium berghei K173. Epo mRNA expression was highly induced in the kidney of infected mice (A). Increased EPO production was accompanied by a massive increase in spleen index (B), Gypa (C) and Erfe mRNA expression (D) in the bone marrow and the spleen. Gypa mRNA expression (C) decreased between day 0 and day 3 in the bone marrow and the spleen and increased in the spleen between day 15 and 18. Data shown are mean ± sem and were compared for each time point to values for control mice at t=0 (n=5 to 10 mice per group except at day 18 where only 3 mice had survived) by one-way ANOVA. (A, B) ***P<0.001, **P<0.01 and (C, D) ***P<0.001, *P<.05 for the marrow and ###P<0.001, ##P<0.01, #P<0.05 for the spleen. Spleen index = spleen weight in mg/body weight in g. PbK: Plasmodium berghei K173; A.U: arbitrary units.

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Figure 6. Ablation of Erfe leads to impaired regulation of hepcidin and iron retention in the stores during infection with Plasmodium berghei K173. Repetitive blood collection did not influence serum hepcidin concentration in saline controls (A). Serum hepcidin levels (B) were significantly decreased below baseline at days 13 and 16 after infection in WT mice (solid line, dotted symbols) but not in Erfe-deficient mice (dashed line, triangle symbols). At day 16 after infection with PbK, Hamp mRNA expression (C) was suppressed in WT but not in Erfe–/– mice. As a result, Erfe–/– mice had higher spleen iron content than WT mice (D). (A, B) The same mice were monitored between day 0 and 16 (n=6 mice per genotype for PbKtreated mice and 4 mice per genotype for saline controls). Data shown are mean ± sem and were compared for each mice at each time point to values at t=0 (***P<0.001, **P<0.01) and between WT and Erfe–/– mice (###P<0.001, ##P<0.01, #P<0.05) by two-tailed Student's ttest (n=6 mice per group). (C-D) Data shown are mean ± sem and were compared for each genotype between mice injected with saline and PbK (***P<0.001, **P<0.01) and between WT and –/– Erfe mice (##P<0.01, #P<0.05) at day 16 by two-tailed Student's ttest. WT: wild-type; PbK: Plasmodium berghei K173.

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infected mice. As a consequence, they retain more iron in the cells of the reticuloendothelial system than WT mice, which translates into higher splenic iron content and lower RBC indices. Most interestingly, parasitemia is significantly lower at day 13 post-infection in Erfe-deficient mice compared with WT mice. These data indicate the potential benefit of maintaining even a moderate hepcidin production during the course of severe malaria. We also observed a decrease in hepcidin production in Erfe-deficient mice between days 7 and 10 after infection, which may be attributable to the resolution of the inflammatory pathway stimulating hepcidin, or to potential additional regulators. Similar results were observed in mice treated with heat-killed Brucella abortus particles.43 However, hepcidin levels only returned toward baseline and we did not observe any suppression of hepcidin in Erfe–/– mice, indicating that ERFE represses hepcidin during malarial anemia. Further investigation will be necessary to identify the mechanism leading to hepcidin upregulation during malarial infection. Surprisingly, Erfe–/– mice had higher RBC and hemoglobin levels compared to WT mice 7 to 10 days after infection, despite comparable parasitemia and hepcidin levels. We speculate that ERFE deficiency is somewhat protective against the ability of the parasite to invade or to replicate in RBCs during the early stage of infection. Given the hepcidin suppressive effect of ERFE,30,43,44 and the clear advantage of Erfe-deficient mice during malaria infection, ERFE inhibitors would be expected to maintain hepcidin levels high enough to impede Plasmodium growth and proliferation and promise to be useful adjuvants in the treatment of malaria. However, the inhibition of ERFE during malarial infection may also worsen the anemia.30,43 haematologica | 2017; 102(1)

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Figure 7. Parasitemia, hemoglobin, MCV and MCH in WT and Erfe–/– mice during infection with Plasmodium berghei K173. WT and Erfe–/– mice exhibited similar parasitemia at days 7 and 10 post-infection, but Erfe–/– had lower parasite count at day 13 (A). Hemoglobin (B) dramatically decreased during infection, whereas MCV (C) and MCH (D) increased between day 10 and 16. Compared to WT mice, the drop in hemoglobin between day 10 and 13 was more prominent in Erfe–/– mice, despite lower parasitemia. MCV and MCH were lower in Erfe–/– mice than in WT mice at day 13, suggesting iron restriction. The same mice were monitored between day 0 and 16 (n=6 mice per genotype for PbK-treated mice and 4 mice per genotype for saline controls). Data shown are mean ± sem and were compared for each mice at each time point to values at t=0 (***<0.001, **P<0.01, *P<0.05) by one-way ANOVA and between WT and Erfe–/– mice (##P<0.01, #P<0.05) by two-tailed Student's t-test. WT: wild-type; PbK: Plasmodium berghei K173; MCV: mean corpuscular volume; MCH: mean corpuscular hemoglobin.

Thus, after clearance of the parasite from the bloodstream, ERFE or related agonists could, in a second step, accelerate the recovery from malarial anemia by increasing intestinal iron absorption and mobilization of iron from the stores. Importantly, our study focused on the blood-stage infection as the liver-stage was completely bypassed by the direct injection of infected RBCs into mice. However, the malaria parasite also requires iron during the exoerythrocytic phase of replication in the liver. Indeed, hepcidin peptide injection or hepcidin overexpression by transgene or viral vector can reduce parasite survival in the liver.25 It remains to be determined whether ERFE contributes to the asymptomatic liver-stage and the release of merozoites into the bloodstream. Acknowledgments The authors thank Elizabeta Nemeth (Los Angeles, CA, USA) for helpful discussions, Florence Capilla (Experimental Histopathology Platform, Toulouse Purpan, France), Antoine Berry (Toulouse, France) for the P. berghei K173 strain, and the members of the Inserm US006 facility (Toulouse, France) and Victoria Gabayan (Los Angeles, CA, USA) for their technical assistance and help in mouse breeding. Funding This research was supported by the French National Research Agency (ANR-13-BSV3-0015-01), the Fondation pour la Recherche Médicale (FRM DEQ2000326528) to MPR, the NIH grant R01 DK 065029 to TG, the ASH scholar award and ANR-16-ACHN-0002-01 to LK, the PIA Parafrap Consortium (ANR-11-LABX0024) to NB and the Fondation pour l’Aide à la Recherche sur la Sclérose en Plaque (ARSEP) to MW and NB. 67


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diseases and bone marrow iron deficiency. PLoS One. 2013;8(12):e78964. Kautz L, Jung G, Valore EV, Rivella S, Nemeth E, Ganz T. Identification of erythroferrone as an erythroid regulator of iron metabolism. Nat Genet. 2014; 46(7):678684. Mitchell AJ, Hansen AM, Hee L, et al. Early cytokine production is associated with protection from murine cerebral malaria. Infect Immun. 2005;73(9):5645-5653. Courselaud B, Troadec MB, Fruchon S, et al. Strain and gender modulate hepatic hepcidin 1 and 2 mRNA expression in mice. Blood Cells Mol Dis. 2004;32(2):283289. Latour C, Kautz L, Besson-Fournier C, et al. Testosterone perturbs systemic iron balance through activation of epidermal growth factor receptor signaling in the liver and repression of hepcidin. Hepatology. 2014;59(2): 683-694. Francis SE, Sullivan DJ, Jr., Goldberg DE. Hemoglobin metabolism in the malaria parasite Plasmodium falciparum. Annu Rev Microbiol. 1997;51:97-123. Young DS. Effect of drugs on Clinical laboratory tests, 4th Ed. 1995;3-361 to 363-364. Weiss G, Goodnough LT. Anemia of chronic disease. N Engl J Med. 2005; 352(10):10111023. Tanno T, Bhanu NV, Oneal PA, et al. High levels of GDF15 in thalassemia suppress expression of the iron regulatory protein hepcidin. Nat Med. 2007;13(9):1096-1101. Tanno T, Porayette P, Sripichai O, et al. Identification of TWSG1 as a second novel erythroid regulator of hepcidin expression in murine and human cells. Blood. 2009; 114(1):181-186. Armitage AE, Pinches R, Eddowes LA, Newbold CI, Drakesmith H. Plasmodium falciparum infected erythrocytes induce hepcidin (HAMP) mRNA synthesis by peripheral blood mononuclear cells. Br J Haematol. 2009;147(5):769-771. Besson-Fournier C, Latour C, Kautz L, et al. Induction of activin B by inflammatory stimuliupregulates expression of the iron-regulatory peptide hepcidin through Smad1/5/8 signaling. Blood. 2012; 120(2): 431-439 Portugal S, Drakesmith H, Mota MM. Superinfection in malaria: Plasmodium shows its iron will. EMBO Rep. 2011; 12(12):1233-1242. Lamikanra AA, Brown D, Potocnik A, Casals-Pascual C, Langhorne J, Roberts DJ. Malarial anemia: of mice and men. Blood. 2007;110(1):18-28. Kautz L, Jung G, Nemeth E, Ganz T. Erythroferrone contributes to recovery from anemia of inflammation. Blood. 2014;124 (16):2569-2574. Kautz L, Jung G, Du X, et al. Erythroferrone contributes to hepcidin suppression and iron overload in a mouse model of beta-thalassemia. Blood. 2015;126(17):2031-2037.

haematologica | 2017; 102(1)


ARTICLE

Bone Marrow Failure

A plasma microRNA signature as a biomarker for acquired aplastic anemia Kohei Hosokawa, Sachiko Kajigaya, Xingmin Feng, Marie J. Desierto, Maria del Pilar Fernandez Ibanez, Olga Rios, Barbara Weinstein, Phillip Scheinberg, Danielle M. Townsley and Neal S. Young

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Hematology Branch, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MA, USA

ABSTRACT

Haematologica 2017 Volume 102(1):69-78

A

plastic anemia is an acquired bone marrow failure characterized by marrow hypoplasia, a paucity of hematopoietic stem and progenitor cells, and pancytopenia of the peripheral blood, due to immune attack on the bone marrow. In aplastic anemia, a major challenge is to develop immune biomarkers to monitor the disease. We measured circulating microRNAs in plasma samples of aplastic anemia patients in order to identify disease-specific microRNAs. A total of 179 microRNAs were analyzed in 35 plasma samples from 13 aplastic anemia patients, 11 myelodysplastic syndrome patients, and 11 healthy controls using the Serum/Plasma Focus microRNA Polymerase Chain Reaction Panel. Subsequently, 19 microRNAs from the discovery set were investigated in the 108 plasma samples from 41 aplastic anemia patients, 24 myelodysplastic syndrome patients, and 43 healthy controls for validation, confirming that 3 microRNAs could be validated as dysregulated (>1.5-fold change) in aplastic anemia, compared to healthy controls. MiR-150-5p (induction of T-cell differentiation) and miR-146b5p (involvement in the feedback regulation of innate immune response) were elevated in aplastic anemia plasma, whereas miR-1 was decreased in aplastic anemia. By receiver operating characteristic curve analysis, we developed a logistic model with these 3 microRNAs that enabled us to predict the probability of a diagnosis of aplastic anemia with an area under the curve of 0.86. Dysregulated expression levels of the microRNAs became normal after immunosuppressive therapy at 6 months. Specifically, miR-150-5p expression was significantly reduced after successful immunosuppressive therapy, but did not change in nonresponders. We propose 3 novel plasma biomarkers in aplastic anemia, in which miR-150-5p, miR-146b-5p, and miR-1 can serve for diagnosis and miR-150-5p for disease monitoring. Clinicaltrials.gov identifiers:00260689, 00217594, 00961064.

Introduction The disease, aplastic anemia (AA) is caused in most patients by immune-mediated destruction of hematopoietic stem and progenitor cells (HSPCs), resulting in trilineage marrow hypoplasia and pancytopenia of the peripheral blood. The responsiveness of a significant proportion of AA patients to immunosuppressive therapies (IST) is the best evidence of an underlying immune pathophysiology: the majority of patients show hematologic improvement after only transient T-cell depletion by antithymocyte globulins (ATGs).1,2 Although the immune pathophysiology of AA is well characterized,3-5 there are no biomarkers that would allow a better understanding of the immunological status of an individual AA patient, including disease severity and response to therapy.6 Reliable biomarkers that correlated with disease severity or response would be useful for individual treatment decisions and in clinical trials. haematologica | 2017; 102(1)

Correspondence: kohei.hosokawa@nih.gov

Received: June 17, 2016. Accepted: September 15, 2016. Pre-published: September 22, 2016. doi:10.3324/haematol.2016.151076

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/69

Š2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is required for any other use.

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MicroRNAs (miRNAs) are a group of small, conserved, non-coding RNA molecules that primarily modulate gene expression, post-transcriptionally by hybridization to complementary sequences in the 3′ untranslated region of corresponding messenger RNAs (mRNAs).7 MiRNAs contribute to the pathophysiology of important human diseases.8,9 Emerging evidence supports the fact that miRNAs have important roles in controlling and modulating immunity.10 Dysregulation of miRNAs can lead to autoimmune diseases, such as rheumatoid arthritis (RA) and multiple sclerosis (MS).11,12 Although miRNA regulation of each target results in small changes in gene expression, the network activity of miRNAs affecting hundreds of genes simultaneously can produce dramatic changes in cell behavior.13 We have recently reported that downregulation of miR-126-3p and miR-145-5p promotes CD4+ and CD8+ T-cell activation by increasing MYC and PIK3R2 expression levels in AA patients.14 MiRNAs can also be detected outside the cell. Extracellular miRNAs are cell-free circulating molecules residing in microvesicles, exosomes, and microparticles.15 These circulating miRNAs can be detected and quantified in biofluids, such as serum, plasma, urine, and saliva.16 Circulating miRNAs mirror physiological and pathophysiological conditions and have high stability in stored patient samples, allowing them to serve as biomarkers for various diseases.17 In particular, the detection of miRNA levels in blood plasma and serum has the potential for early cancer diagnosis and to predict prognosis and response to therapy.18,19 Recent studies have also identified circulating miRNAs as biomarkers to monitor the disease state in T cell-mediated autoimmune diseases, such as MS and myasthenia gravis (MG).20,21 However, miRNAs have yet to be explored in the serum or plasma of AA. The purpose of our study was to analyze the circulating miRNA profile in the plasma of AA patients and to assess whether specific miRNAs could serve as new biomarkers for AA.

patients, 24 MDS patients, and 43 HC. Demographics of the discovery and validation sets are shown in the Online Supplementary Table S1. To assess the effect of IST, 40 out of 41 AA patients with plasma samples available both before and after 6 months of IST were analyzed further.

RNA isolation and cDNA synthesis Blood samples collected in EDTA tubes were centrifuged and stored at -80°C until use. RNA isolation from 200 ml EDTA plasma was performed using the miRCURY RNA Isolation Kit - Biofluids (Exiqon, Vedbaek, Denmark), according to the manufacturer’s instructions. RNA isolation efficiency was monitored with three synthetic RNA spike-ins at different concentrations (UniSp2, UniSp4, and UniSp5). Isolated RNA samples were employed for cDNA synthesis with the Universal cDNA Synthesis Kit II (Exiqon). Two synthetic RNA spike-ins in different concentrations (UniSp6 and cel-miR-39-3p) were used to check for reverse transcription reactions and polymerase chain reaction (PCR) inhibitors. Prepared cDNAs were stored at -20°C until use.

MiRNA profiling Initial miRNA detection screening with the discovery set (n=35) was performed using the Serum/Plasma Focus microRNA PCR Panel, 384 well (V4.M) and the ExiLENT SYBR Green Master Mix (Exiqon). This panel allows for the analysis of 179 human miRNAs and was used to profile the discovery set of 13 AA, 11 MDS, and 11 HC (Online Supplementary Table S2). The information for validation of the miRNA profiling by a custom PCR panel is shown in the Online Supplementary Table S3 and Online Supplementary Experimental Methods.

Statistics Statistical analysis was performed using the GenEx6 software (Exiqon) and SPSS 23.0 software, and graphs were generated using GraphPad PRISM version 6.0 (GraphPad Software, Inc., La Jolla, CA, USA). More detailed information is provided in the Online Supplementary Experimental Methods.

Methods Results Patients and treatment The study population was 183 human subjects who were enrolled on clinical protocols between 2006 and 2015 at the NIH's National Heart, Lung, and Blood Institute (NHLBI) (Bethesda, MD, USA). Samples were collected after informed consent was obtained in accordance with the Declaration of Helsinki. All human subjects were enrolled on clinical protocols approved by the NHLBI Institutional Review Board. Ethylenediaminetetraacetic acid (EDTA) anticoagulated plasma samples were obtained from patients and age-matched healthy blood donors. Standard criteria were used for the diagnosis of AA and the assessment of disease severity.22 All AA patients were diagnosed as severe AA and none had received IST at the time of sampling. All AA patients received IST [horse-ATG + cyclosporine (CsA) or rabbit-ATG + CsA] on a clinical research protocol (clinicaltrials.gov identifier:00260689).2,23 EDTA plasma samples from myelodysplastic syndrome (MDS) were used for comparison (clinicaltrials.gov identifier:00217594 or clinicaltrials.gov identifier:00961064).24 Healthy controls (HC) were recruited from donors of the National Institutes of Health Clinical Center Department of Transfusion Medicine. A discovery set (n=35) included 13 AA patients without IST at the time of sampling, 11 MDS patients, and 11 blood donors as HC. A validation set (n=108) consisted of 41 treatment-naïve AA 70

A distinct circulating miRNA profile in AA, compared to MDS and HC To examine whether there were unique AA-associated miRNAs, we first analyzed 35 discovery set plasma samples (13 untreated AA, 11 MDS, and 11 HC) without hemolysis (ΔCT<7) using the Serum/Plasma Focus microRNA PCR Panel (179 miRNAs). Of 179 miRNAs, 178 miRNAs showed amplification in more than 60% of the samples. When compared between AA and HC, 14 miRNAs displayed more than a 1.5-fold change (FC) (P<0.05 by t-test; Figure 1A and Table 1): 7 miRNAs were significantly upregulated (miR-501-3p, miR-146b-5p, miR150-5p, let-7b-5p, miR-200a-3p, miR-1260a, and miR-4245p) and 7 miRNAs were significantly downregulated (miR-1, miR-29b-3p, miR-30e-5p, miR-143-3p, let-7e-5p, let-7c-5p, and let-7f-5p) in AA, compared to HC. Hierarchical clustering showed that the plasma miRNA signature distinguished AA from HC (Figure 1B). The comparison of different groups by one-way ANOVA revealed multiple differentially expressed circulating miRNAs (P<0.05): 12, 47, and 36 miRNAs distinguished AA from HC, MDS from HC, and AA from MDS, respectively (Online Supplementary Table S4). haematologica | 2017; 102(1)


Circulating microRNA profile in aplastic anemia

A

C

B

AA vs. HC

AA vs. HC

D

MDS vs. HC

E

AA vs. HC

Figure 1. Distinct circulating microRNA (miRNA) expression profiles of AA patients compared to MDS and HC in the discovery set. (A) A volcano plot of 178 miRNA expression levels in the plasma of AA patients (n=13) and HC (n=11) in the discovery set. The x-axis displays the estimated expression difference measured in log2. Vertical lines refer to a 1.5-fold expression difference between two groups, showing that miRNAs highly expressed in AA or HC are on the right or the left, respectively, in which 6 miRNAs with higher fold changes are depicted. The y-axis shows the significance of the expression difference measured in â&#x2C6;&#x2019;log10 of the P-value. The horizontal red line represents our cut-off for the significance at P<0.05. (B) A heatmap analysis visualizes hierarchical clustering of 14 miRNAs in the plasma from 13 AA patients and 11 HC. A red-blue color scale indicates normalized miRNA expression levels (red: high, blue: low). (C) Principal component analysis (PCA) plots of significantly (P<0.05) and differentially expressed miRNAs from the discovery set. Blue circles = AA, red circles = MDS, and green circles = HC. AA: aplastic anemia; HC: healthy control; MDS: myelodysplastic syndrome.

To further address differences of plasma miRNA levels between individual groups, a principal component analysis (PCA) of differentially expressed miRNAs was performed, resulting in distinct profiles between AA and MDS vs. HC, and between AA vs. MDS (Figure 1C-E). The PCA plots clearly visualized potential distinct grouping of the compared disease populations and controls, providing a basis to validate results of the discovery set in a separate cohort. The Online Supplementary Figure S1 summarizes all the analysis steps for the candidate miRNAs.

Validation of miRNA expression profiles To validate findings in the discovery set, 19 miRNAs, including 17 candidate miRNAs from the discovery set (Online Supplementary Table S4), were selected to investigate in a separate cohort of AA, MDS, and HC (n=108; Online Supplementary Table S1) using the custom PCR array plate (Online Supplementary Table S3): 12 miRNAs (let-7f5p, miR-1, miR-1260a, miR-143-3p, miR-146b-5p, miR150-5p, miR-20a-5p, miR-21-5p, miR-26b-5p, miR-29b3p, miR-30e-5p, and miR-501-3p) differentially expressed between AA and HC (P<0.05 by one-way ANOVA); 5 miRNAs (let-7g-5p, miR-181a-5p, miR-22-3p, miR-29c-3p, and miR-424-5p) significantly different by 3 group comparison (AA vs. MDS vs. HC); and additional 2 miRNAs haematologica | 2017; 102(1)

Table 1. Differentially expressed miRNAs (>1.5 FC) in the aplastic anemia (AA) discovery set.

miRNA miR-501-3p miR-146b-5p miR-150-5p let-7b-5p miR-200a-3p miR-1260a miR-424-5p miR-1 miR-29b-3p miR-30e-5p miR-143-3p let-7e-5p let-7c-5p let-7f-5p

P 0.002 <0.001 0.009 0.014 0.021 0.017 0.033 0.018 <0.001 <0.001 0.014 0.048 0.006 0.010

FC Elevated

Decreased

2.0 1.9 1.9 1.7 1.7 1.6 1.6 2.4 2.0 1.6 1.6 1.6 1.5 1.5

miRNA: microRNA; FC: fold change.

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AA vs. HC

B

MDS vs. HC

C

AA vs. MDS

D

Figure 2. Validation of the circulating microRNA (miRNA) expression profiles in the validation set. (A-B) Volcano plots of 19 miRNA expression levels in the plasma of AA (n=41), MDS (n=24), and HC (n=43) in the validation set. The x-axis is the estimated difference in expression measured in log2; vertical lines refer to a 1.5fold difference in expression between the two groups. MiRNAs highly expressed in AA (MDS) or HC are on the right or the left, respectively. The y-axis is the significance of the difference measured in −log10 of the P-value; the horizontal red line represents our cut-off for significance at P<0.05. (C) Volcano plots of 19 miRNA expression levels in the plasma of AA (n=41) and MDS patients (n=24) in the validation set. MiRNAs highly expressed in AA or MDS are on the right or the left, respectively. (D) miR-150-5p, miR-146b-5p, miR-1, miR-22-3p, and miR-424-5p expression in the plasma of AA (n=41), MDS (n=24), and HC (n=43). *P<0.05 (one-way ANOVA). AA: aplastic anemia; HC: healthy control; MDS: myelodysplastic syndrome.

(let-7a-5p and miR-144-5p) that have been reported to distinguish MDS from HC in previous reports.19,25 Box plots of 19 miRNA expression levels in the discovery set are shown in the Online Supplementary Figure S2. As a hemolysis marker (miR-23a-3p-miR-451a) was >7 in 3 HC and 3 patient plasma samples (1 AA and 2 MDS); these 6 samples were excluded from further analysis. All of the selected 19 miRNAs were amplified by quantitative real time PCR (qRT-PCR) in >60% of the samples, then subjected to further analysis. Of the 5 reference genes, miR-106a-5p and miR-320a were selected to calculate ΔCT and relative expression, as these 2 miRNAs displayed stable amplification in all of the individual samples with good expression (CT≤30, Online Supplementary Figure S3). Group comparison revealed distinct expression profiles at statistical significance (>1.5-FC, P<0.05): upregulated miR-150-5p and miR-146b-5p and downregulated miR-1 in AA, compared to HC (Figure 2A,D); upregulated miR-146b-5p and miR22-3p in MDS, compared to HC (Figure 2B,D); and downregulated miR-1, miR-22-3p, and miR-424-5p in AA, com72

pared to MDS (Figure 2C,D). Summary data (AA and MDS vs. HC, and AA vs. MDS) obtained from the validation set are shown in Table 2. When AA was compared to HC, 6 miRNAs showed significant association with AA: miR-1 (P=0.004), let-7g-5p (P=0.04), miR-146b-5p (P=0.0001), miR-26b-5p (P=0.049), miR-150-5p (P=0.015), and miR-181a-5p (P=0.029). Additionally, these 6 miRNAs were subjected to multivariate analysis to determine which miRNA associated with AA: miR-1 [odds ratio (OR)=0.34, adjusted P=0.005], miR-146b-5p (OR=3.82, adjusted P=0.03), and miR-150-5p (OR=2.19, adjusted P=0.04), that were differentially expressed in AA patients in the discovery set (Online Supplementary Table S4), significantly and independently associated with the AA diagnosis (Table 3). The comparison between MDS and HC revealed 5 miRNAs that exhibited significant association with MDS: let-7g-5p (P=0.005), miR-146b-5p (P=0.0003), miR-26b-5p (P=0.028), miR-21-5p (P=0.014), and miR-22-3p (P=0.003). Subsequent multivariate analysis of these 5 miRNAs haematologica | 2017; 102(1)


Circulating microRNA profile in aplastic anemia

A AA vs. HC

B MDS vs. HC

C AA vs. MDS

Figure 3. Receiver operating characteristic (ROC) curves of dysregulated miRNAs in the validation set. ROC curves for individual miRNAs in AA vs. HC (A), MDS vs. HC (B), and AA vs. MDS (C). Logistic regression demonstrated a linear combination of values of miRNAs for the compared groups: miR-150-5p, miR-146b-5p, and miR-1 produced the model for AA diagnosis (the equation of the Combined miRNA panel = 4.728 + 0.446 × miR-150-5p + 1.725 × miR-146b-5p – 1.022 × miR1); miR-146b-5p and miR-22-3p produced the model for MDS diagnosis (the equation of Combined miRNA panel = 9.547 + 1.416 × miR-146b-5p + 1.089 × miR22-3p), and miR-22-3p, miR-424-5p, and miR-1 produced the model for AA diagnosis compared to MDS (the equation of Combined miRNA panel = -13.117 – 2.046 × miR-22-3p – 1.384 × miR-424-5p – 1.221 × miR-1). The ROC curve of the miRNA panel was generated based on the predicted probability for each patient. Predicted probability = Exponential function (Exp) (Combined miRNA panel) / [1+ Exp (Combined miRNA panel)]. AA: aplastic anemia; HC: healthy control; MDS: myelodysplastic syndrome; AUC: area under the curve; miRNA: microRNA.

showed that only miR-22-3p, which was differentially expressed in the discovery set (Online Supplementary Table S4), significantly associated with MDS (OR=4.09, adjusted P=0.03; Table 3); 4 other miRNAs were not significantly associated with MDS, in part due to the high correlations of the 4 miRNAs with each other. When AA was compared to MDS, 4 miRNAs displayed significant association with AA: miR-1 (P=0.024), miR-22-3p (P=0.005), miR-29c3p (P=0.049), and miR-424-5p (P=0.004). In multivariate analysis of these miRNAs, significant, independent association with AA was observed only for miR-1 (OR=0.22, adjusted P=0.01) and miR-22-3p (OR=0.03, adjusted P=0.02; Table 3).

Development of a diagnostic panel for AA composed of three plasma miRNAs Next, the sensitivity and specificity of the miRNAs for haematologica | 2017; 102(1)

the diagnosis of AA were evaluated by receiver operating characteristic (ROC) curve analysis using the validation set: there was strong association of miR-146b-5p [95% confidence interval (CI), 0.65-0.86, P=0.0001], miR-150-5p (95% CI, 0.63-0.85, P=0.0002), and miR-1 (95% CI, 0.620.85, P=0.0004) with AA [area under the curve (AUCs) of 0.76, 0.74, and 0.73, respectively; Figure 3A]. Logistic regression was employed to determine the best combination of miRNAs to diagnose AA, demonstrating that a linear combination of expression levels of miR-150-5p, miR146b-5p, and miR-1 produced the best model. A miRNA biomarker panel composed of miR-150-5p, miR-146b-5p, and miR-1 provided significantly increased AUC of 0.86 (95% CI, 0.78-0.94, P<0.00001; Figure 3A), compared with the use of each miRNA alone. Cut-off values of the diagnostic performances of the model were determined based on the maximum of Youden's Index of the ROC curve 73


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(cut-off value >0.44 for AA vs. HC). In the 3 miRNA-combined panel, a sensitivity of 82% and a specificity of 80% were obtained for the diagnosis of AA, compared with HC. By comparing MDS to HC in the validation set, a strong association was observed between miR-146b-5p and MDS, with AUC of 0.80 (95% CI, 0.68-0.91, P=0.0001), and miR-22-3p, with AUC of 0.74 (95% CI, 0.61-0.86) (Figure 3B). In the 2 miRNA-combined panel (miR-146b5p and miR-22-3p), AUC was increased to 0.85 (95% CI, 0.76-0.95, P<0.00001; Figure 3B). The comparison

between AA and MDS revealed strong association of miR22-3p with AA, having an AUC of 0.81 (95% CI, 0.700.92, P<0.0001; Figure 3C), miR-424-5p, with AUC of 0.77 (95% CI, 0.65-0.90), and miR-1 with AUC of 0.71 (95% CI, 0.57-0.85) (Figure 3C). Increased AUC (0.88) was achieved by using a panel composed of these 3 miRNAs (95% CI, 0.79-0.96, P<0.00001; Figure 3C).

Correlations of miRNAs with clinical parameters in AA In addition to group comparisons, correlation analysis between differentially expressed miRNAs and clinical

Table 2. Association between miRNAs and groups in validation set.

AA vs. HC miRNA miR-1 let-7g-5p miR-146b-5p miR-26b-5p miR-150-5p miR-181a-5p miR-21-5p miR-22-3p miR-29c-3p miR-424-5p

FC -1.76 1.23 1.80 1.34 1.72 1.48 1.08 1.02 -1.12 -1.18

P 0.004 0.040 <0.001 0.049 0.015 0.029 0.552 0.982 0.680 0.429

MDS vs. HC AUC 0.73 0.64 0.76 0.63 0.74 0.64 0.55 0.53 0.55 0.59

FC -1.02 1.38 2.12 1.46 1.17 1.08 1.29 1.60 1.31 1.41

P 0.995 0.005 <0.001 0.028 0.770 0.902 0.014 0.003 0.215 0.075

AA vs. MDS AUC 0.51 0.71 0.80 0.66 0.54 0.53 0.72 0.74 0.62 0.65

FC -1.72 -1.12 -1.18 -1.09 1.48 1.37 -1.19 -1.56 -1.47 -1.67

P 0.024 0.502 0.575 0.830 0.208 0.189 0.122 0.005 0.049 0.004

AUC 0.71 0.59 0.55 0.58 0.63 0.71 0.68 0.81 0.67 0.77

Bold text represents values that were significant, controlling for a false discovery rate at 0.05. miRNA: microRNA; AA: aplastic anemia; HC: healthy control; MDS: myelodysplastic syndrome; FC: fold change; AUC: area under the curve.

A

B

C

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Figure 4. MicroRNA (miRNA) expression changes after IST. (A) MiR-150-5p, miR146b-5p, and miR-1 expression in the plasma of AA patients at onset (n=40) and after IST at 6 months (n=40). (B) MiR-150-5p, miR-146-5p, and miR-1 expression in the plasma of AA patients (responders) at onset (n=23) and after IST at 6 months (n=23). (C) MiR-150-5p, miR-146-5p, and miR-1 expression in the plasma of AA patients (non-responders) at onset (n=17) and after IST at 6 months (n=17). *P<0.05 (paired two-tailed t-test). AA: aplastic anemia; IST: immunosuppressive therapy; N.S: not significant.

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Circulating microRNA profile in aplastic anemia

parameters [complete blood count (CBCs) (absolute neutrophil count (ANC), absolute reticulocyte count (ARC), and platelet count) and age] was performed using the validation set to assess their correlation with disease severity. At the onset of AA, miR-150-5p and miR-146b-5p showed modest but significant negative correlations with platelet counts (r=-0.33, P=0.025) and ARC (r=-0.34, P=0.020), respectively (Online Supplementary Table S5 and Online Supplementary Figure S4). MiR-1 positively correlated with ANC (r=0.30, P=0.038; Online Supplementary Table S5 and Online Supplementary Figure S4). Thus, expression levels of the 3 miRNAs (elevated miR-150-5p and miR-146b-5p and reduced miR-1) were correlated to clinical parameters in AA. There was no correlation between age and the differentially expressed miRNAs (data not shown).

Effects of IST on miRNA expression in AA patients To address whether IST affected the circulating miRNA profile of AA, 40 AA patients with plasma samples before commencing IST and 6 months after IST (Online Supplementary Table S6) were analyzed. Statistically significant changes after IST were detected in all 3 miRNA (miR-150-5p, miR-146b-5p, and miR-1) levels, suggesting the restoration of dysregulated miRNA expressions after therapy (P=0.0001 for miR-150-5p, P=0.0263 for miR146b-5p, and P=0.0003 for miR-1; Figure 4A and Table 4). In particular, a sharp miR-150-5p decline was seen after IST (48%, 95% CI: 34â&#x20AC;&#x201C;68%), compared to before IST (Figure 4A). The use of horse-ATG (n=23) or rabbit-ATG (n=17) did not significantly affect the miRNA expression changes after IST: statistically significant changes after IST were detected for all 3 miRNA levels in both groups. Of 40 AA patients, 23 patients (58%) achieved partial responses (PR) or complete responses (CR) while the remaining 17 patients (42%) were non-responders 6 months after IST. When we analyzed the effects of IST in responders (either PR or CR) and non-responders, a reduced miR-150-5p level was observed in responders (P=0.0005; Figure 4B), but there were no statistically significant changes of miR-150-5p expression in non-responders (Figure 4C), indicating that the restoration of miR150-5p levels after IST was associated with successful treatment. Restoration of miR-1 levels was also observed both in responders and non-responders after IST (Figure 4B,C). Further, miRNA expression levels were compared between responders and non-responders before IST to assess whether miRNA signatures were useful for predicting response to IST. When expression levels of 19 miRNAs at onset were compared between responders (n=23) and

non-responders (n=17), none of them was significantly different (Online Supplementary Figure S5).

Discussion In recent publications, circulating miRNAs have been described as noninvasive biomarkers for many different diseases.17-21 Challenges in the analysis of circulating miRNAs include pre-analytical decisions (such as sample storage and processing) and post-analytical assessments (data normalization).17 Detailed analyses of miRNA spectra in serum and plasma recommend plasma over serum to reduce sample-to-sample variations induced by serum coagulation,26 and we used EDTA anticoagulated plasma in this study to avoid such variations. To characterize miRNA signatures in the plasma of AA, the Serum/Plasma Focus microRNA PCR Panel was used, as it is considered optimal in terms of reproducibility, sensitivity, accuracy, and specificity.27 We found that circulating miRNAs were differentially expressed in AA and MDS vs. HC and in AA vs. MDS, which was validated in a larger separate cohort using a different normalization method. By multivariate analysis, we identified the 5 miRNAs (miR-150-5p, miR146-5p, miR-1, miR-22-3p, and miR-424-5p) that were significantly associated with AA or MDS, and these miRNA expression patterns were similar between the 2 cohorts. Our study showed the possible utility of â&#x20AC;&#x153;liquid biopsy" to distinguish AA and MDS. Starting with a total of 179 miRNAs, 19 from the discovery set were investigated and 3 miRNAs were validated as dysregulated in AA. Two miRNAs (miR-150-5p and miR146b-5p) and miR-1 were significantly elevated and decreased in the plasma of AA patients, respectively. Pathway analysis revealed that these 3 miRNAs targeted important immune-related functions (Figure 5). One of miR-150-5p targets is NOTCH3: the regulation of the Notch pathway through miR-150-5p may impact T-cell development.28 Another target of miR-150-5p is the transcription factor C-MYB which plays an essential role in Tcell differentiation.29 MiR-150-5p is an immuno-miRNA considered to be a crucial regulator of T-cell processes.30 Since AA is a T cell mediated disease, it is interesting that miR-150-5p is selectively expressed in immature resting T cells and then strongly upregulated with their maturation and differentiation of the T-cell progresses.28 MiR150-5p is a circulating biomarker in female MG patients without immunosuppressive drug treatment, as the miR150-5p level is reduced with clinical improvement after

Table 3. Multivariate logistic regression model in the validation set.

AA vs. HC miRNA

OR

adjusted P

miRNA

miR-1 let-7g-5p miR-146b-5p miR-26b-5p miR-150-5p miR-181a-5p

0.34 1.22 3.82 1.62 2.19 1.31

0.005 0.845 0.029 0.477 0.041 0.620

let-7g-5p miR-146b-5p miR-26b-5p miR-21-5p miR-22-3p

MDS vs. HC OR adjusted P 4.54 2.44 1.02 1.52 4.09

0.126 0.125 0.972 0.604 0.029

miRNA

AA vs. MDS OR

adjusted P

miR-1 miR-22-3p miR-29c-3p miR-424-5p

0.22 0.03 1.33 0.37

0.013 0.021 0.698 0.259

All analyses were adjusted for age and sex. OR >1 for AA vs. HC and AA vs. MDS comparisons demonstrates that increased expression levels were associated with increased odds of being AA. For the comparisons of MDS vs. HC, OR >1 represents that increased expression levels were associated with increased odds of being MDS. Bold text indicates values that were significant, controlling a false discovery rate at 0.05. miRNA: microRNA; AA: aplastic anemia; HC: healthy control; OR: odds ratio; MDS: myelodysplastic syndrome.

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Figure 5. Ingenuity Pathway Analysis (IPA) to identify immune targets of the selected three microRNAs (miRNAs). Shown are network genes of the dysregulated 3 miRNAs (miR-1, miR-146b-5p, and miR-150-5p) in aplastic anemia (AA) plasma, compared to healthy control (HC). Color intensity indicates upregulation (red) and downregulation (green). Solid and dotted lines represent direct and indirect relationships between genes.

Table 4. Changes in miRNA expression after immumosuppresive therapies (IST).

miRNA

Ratio

Lower 95% CI

Upper 95% CI

P

miR-1 miR-146b-5p miR-150-5p

2.61 0.74 0.48

1.60 0.56 0.34

4.30 0.96 0.68

<0.001 0.026 <0.001

CI: confidence interval; miRNA: microRNA.

thymectomy.21 Why miRNA expression changes is unknown. MiRNAs are released into the circulation as a result of apoptotic and necrotic cell death.31 Active secretion is also a potential source of cell-free miRNAs,32 and miR-150-5p is transferred to plasma with CD8+ T cellderived exosomes.33 We detected increased expression of miR-150-5p in plasma, which might be due to the secretion from active T cells in AA. Of interest, we also observed a negative correlation between miR-150-5p levels and platelet counts. MiR-150-5p is preferentially expressed in megakaryocytic lineage cells and it drives megakaryocyte-erythrocyte progenitor (MEP) differentiation toward megakaryocytes.34 A mechanistic link between thrombopoietin (TPO)-induced miR-150-5p upregulation and megakaryopoiesis has been described.35 Circulating TPO levels are very high in AA.36 Therefore, considering our data demonstrating high miR-150-5p expression in AA plasma, and previous reports,34-36 it is plausible that miR-150-5p promotes megakaryopoiesis in 76

AA. The miR-146b-5p plasma level was able to differentiate both AA and MDS from HC. In addition, pathway analysis identified innate immune pathways related to Toll-like receptors that might be important both in AA and MDS (Figure 5).5,37 MiR-146b-5p decreases TNFa expression in THP-1 monocytes by targeted repression of IRAK1 and TRAF6,38 and miR-146b-5p is involved in feedback regulation of the innate immune response.39 Previous studies have also described alterations of miR-146a-5p and/or miR-146b-5p levels to be associated with inflammatory diseases.11 In a recent study, the regulatory roles of miR146b-5p in erythropoiesis and megakaryopoiesis have been reported.40 MiR-1 has BCL2 as its target,41 and circulating miR-1 is a potential novel biomarker in acute myocardial infarction.42 MiR-1 exhibits anti-inflammatory roles in asthma mouse models and in inflammatory myopathies.43,44 Decreased levels of miR-1 might reflect an active inflammatory status in AA patients. The recovery of miR-1 levels after IST might be mediated by the immunological effects of ATG + CsA. Collectively, our data suggest that the miRNA signature in AA plasma samples may reflect the aberrant immune response and dysregulated hematopoiesis in AA. We included MDS patients in our study to compare AA to another bone marrow failure syndrome. Others have described an association of miRNA expression with MDS subtypes and disease outcome.45 For example, reduced expression levels of 5 miRNAs (miR-378a-3p, miR-143-3p, miR-143-5p, miR-145-5p, and miR-146a-5p) have been reported in MDS with del(5q),46,47 but these reports focused haematologica | 2017; 102(1)


Circulating microRNA profile in aplastic anemia

on miRNA expression in HSPCs. Circulating let-7a and miR-16 from MDS predicted progression-free survival and overall survival,19 and a 7-miRNA signature (let-7a-5p, miR144-5p, miR-16-5p, miR-25-3p, miR-451a, miR-651, and miR-655) was an independent predictor of survival in MDS.25 Based on the literature, we included 2 miRNAs (let7a-5p and miR-144-5p) into the custom PCR panel for validation, but we did not observe association of let-7a-5p and miR-144-5p with MDS, probably due to the heterogeneity of the disease, or variations between the sample processing and detection protocols, or our particular MDS patient cohort. In our study, MDS patients were relatively young, compared to the median age of >70 years for typical MDS. Patients enrolled on our research protocols might be more likely to have an immune-mediated pathology compared to typical MDS, with a higher response rate to alemtuzumab.24 Thus, patient selection might lead to the underestimation of our results when comparing AA and MDS. Distinguishing between AA and MDS is often difficult.48 We found that the miR-146b-5p expression level was significantly elevated both in AA and MDS, and miR-1 and miR-22-3p could distinguish AA and MDS, perhaps reflecting commonalities and differences between both AA and MDS. MiR-22-3p, which could distinguish MDS with AA and MDS with HC in our cohort, is an oncogenic miRNA and is upregulated in MDS.49 Regarding autoimmune cytopenias, 7 plasma miRNAs (miR-302c-3p, miR-483-5p, miR-410, miR-544a, miR-302a-3p, miR-223-3p, and miR-597) are differentially expressed in immune thrombocytopenia (ITP).50 These results also suggest the miRNA signatures in AA are disease-related and not simply a reflection of blood counts. The analysis of serial plasma samples in 40 AA patients suggest potential utility of 3 dysregulated miRNAs (miR150-5p, miR-146b-5p, and miR-1) as disease biomarkers for diagnosis, as their expression levels were significantly different from those of healthy donors, and levels tended to normalize after IST. Specifically, miR-150-5p may represent a response marker in AA, as its plasma concentration expression was significantly decreased in responders but not in non-responders after IST. Similarly, in cancer patients, not all dysregulated miRNAs at diagnosis have clinical relevance for monitoring, and only some miRNAs normalize after successful treatment.18 Our study showed rather modest miRNA expression changes in AA plasma, but miRNAs may affect biologic

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functions even with subtle alterations in expression levels.51 ROC curve analysis revealed the potential clinical utility of combined miRNA panels for future applications. Our current study had other limitations, such as the relatively small number of patients. Nonetheless, our data strongly suggest that aberrant miRNA expression was disease-related, especially as the restoration of miRNA levels was observed after IST. In our recent work, we identified concurrent downregulation of 4 miRNAs (miR-126-3p, miR145-5p, miR-199a-5p, and miR-223-3p) in both CD4+ and CD8+ T cells from AA patients,14 but dysregulation of the 4 miRNAs was not observed in AA plasma samples in the study herein. Previous reports in autoimmune diseases12,20,5259 and cancers,60-63 have also demonstrated discrepancies of expression profiles between cellular and circulating miRNAs. Systemic lupus erythematosus (SLE) patients exhibit distinct miRNA expression profiles in T cells52-55 and plasma,56 and miRNA profiles in T cells12,57,58 and plasma20,59 are inconsistent in MS. Although circulating miRNAs originate from cells, not all cellular miRNAs can be identified as circulating miRNAs in biofluids. Indeed, miRNA expression profiles are cell-type specific. Of note, regardless of discrepancies between cellular and circulating miRNA profiles, we could observe some common miRNA signatures in both AA and MG, such as decreased miR-145-5p in T cells14,64 and increased miR-150-5p in plasma specimens.21 In conclusion, we demonstrate that expression levels of 3 dysregulated miRNAs in AA plasma associate with clinical parameters and normalize after IST, suggesting their use as potential biomarkers in AA. Importantly, we developed a diagnostic logistic model using combined miRNA panels for diagnosis. Additional studies in larger patient cohorts are required to validate miRNAs as disease biomarkers for diagnostic and therapeutic purposes in bone marrow failure. Acknowledgments The authors would like to thank Kinneret Broder for assistance in obtaining healthy volunteer samples and Camilo Canel and Barbara R. Gould for designing the custom plate. Funding This research was supported by the Intramural Research Program of the NIH, National Heart, Lung, and Blood Institute, USA.

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haematologica | 2017; 102(1)


ARTICLE

Myeloproliferative Disorders

An accurate, simple prognostic model consisting of age, JAK2, CALR, and MPL mutation status for patients with primary myelofibrosis

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Uri Rozovski,1,2,3 Srdan Verstovsek,1 Taghi Manshouri,1 Vilma Dembitz,1,4 Ksenija Bozinovic,1 Kate Newberry,1 Ying Zhang,1 Joseph E. Bove IV,1 Sherry Pierce,1 Hagop Kantarjian1 and Zeev Estrov1

Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 2Davidoff Medical Center, Beilinson Hospital, Petah Tikva, Israel; 3 Tel Aviv University, Sackler School of Medicine, Israel and 4University of Zagreb School of Medicine, Croatian Institute for Brain Research, Croatia

1

Haematologica 2017 Volume 102(1):79-84

ABSTRACT

I

n most patients with primary myelofibrosis, one of three mutually exclusive somatic mutations is detected. In approximately 60% of patients, the Janus kinase 2 gene is mutated, in 20%, the calreticulin gene is mutated, and in 5%, the myeloproliferative leukemia virus gene is mutated. Although patients with mutated calreticulin or myeloproliferative leukemia genes have a favorable outcome, and those with none of these mutations have an unfavorable outcome, prognostication based on mutation status is challenging due to the heterogeneous survival of patients with mutated Janus kinase 2. To develop a prognostic model based on mutation status, we screened primary myelofibrosis patients seen at the MD Anderson Cancer Center, Houston, USA, between 2000 and 2013 for the presence of Janus kinase 2, calreticulin, and myeloproliferative leukemia mutations. Of 344 primary myelofibrosis patients, Janus kinase 2 V617F was detected in 226 (66%), calreticulin mutation in 43 (12%), and myeloproliferative leukemia mutation in 16 (5%); 59 patients (17%) were triple-negatives. A 50% cut-off dichotomized Janus kinase 2-mutated patients into those with high Janus kinase 2 V617F allele burden and favorable survival and those with low Janus kinase 2 V617F allele burden and unfavorable survival. Patients with a favorable mutation status (high Janus kinase 2 V617F allele burden/myeloproliferative leukemia/calreticulin mutation) and aged 65 years or under had a median survival of 126 months. Patients with one risk factor (low Janus kinase 2 V617F allele burden/triple-negative or age >65 years) had an intermediate survival duration, and patients aged over 65 years with an adverse mutation status (low Janus kinase 2 V617F allele burden or triplenegative) had a median survival of only 35 months. Our simple and easily applied age- and mutation status-based scoring system accurately predicted the survival of patients with primary myelofibrosis.

Correspondence: zestrov@mdanderson.org

Received: May 23, 2016. Accepted: September 14, 2016. Pre-published: September 29, 2016. doi:10.3324/haematol.2016.149765

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/79

Introduction Primary myelofibrosis (PMF) is a myeloproliferative neoplasm characterized by bone marrow fibrosis and extramedullary hematopoiesis, resulting in variable degrees of splenomegaly, leukocytosis, anemia, thrombocytopenia, and impaired quality of life.1 The median survival of patients with PMF is five years from diagnosis,2,3 but the clinical course is variable. Some patients succumb to the disease within one year, whereas others survive for more than ten years.2-4 Several prognostic scoring systems have been developed for PMF that are based on clinical characteristics and blood counts.2,5 The international prognostic scoring haematologica | 2017; 102(1)

Š2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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system (IPSS) stratifies patients into 4 risk groups (low, intermediate-1, intermediate-2, and high) based on age (>65 years), the presence of constitutional symptoms, hemoglobin less than 10 g/dL, white blood cell (WBC) count of more than 25x109/L, and circulating blast cells of 1% or more at time of diagnosis.5 Based on the IPSS, a dynamic IPSS (DIPSS) was developed, which accounts for acquisition of risk factors over time.6 A refinement of the DIPPS that incorporates adverse karyotype, transfusion dependency, and thrombocytopenia has been suggested by the Mayo Clinic.7 In most patients with PMF, one of three mutually exclusive hematopoietic cell somatic mutations is commonly identified.8-10 In approximately 60% of PMF patients, an activating substitution mutation at position 617 of the pseudo kinase domain of Janus kinase 2 (JAK2V617F) is detected.11-13 In 20%-25% of patients, frameshift mutations caused either by deletions or insertions in the last exon of the calreticulin (CALR) gene are detected. CALR encodes a Ca++ binding protein that is primarily localized to the endoplasmic reticulum (ER). When CALR is mutated, the ER C-terminal ER retention signal (KDEL) is lost and, as a result, the protein is no longer localized to the ER.8,9 In 5% of patients, an activating mutation in the myeloproliferative leukemia virus (MPL) (thrombopoietin receptor) gene is found.14 Patients with a mutated JAK2 present a more aggressive disease than patients with mutated CALR. However, the overall survival (OS) of patients with high JAK2V617F allele burden is better than that of patients with a low JAK2V617F allele burden.15,16 In this study, we developed an easy-to-use scoring system that integrates age and mutation status, and accurately predicts the survival of patients with newly diagnosed PMF.

Methods Included in our study were patients with PMF who were referred to MD Anderson Cancer Center, Houston, USA, between June 2000 and July 2013; the diagnosis was established in accordance with World Health Organization (WHO) criteria.17 Demographic and clinical information at the time of presentation was obtained from patients’ medical records by using a retrospective chart review protocol that was approved by the MD Anderson Institutional Review Board. The IPSS5 and DIPSS scores were assigned to each patient, as previously described.6 After obtaining patients' informed consent, we analyzed residual blood and/or bone marrow cells which had been obtained from the patients for diagnostic purposes and stored, in accordance with a research protocol that was approved by the MD Anderson Institutional Review Board. Before freezing, all samples were fractionated with use of the Ficoll Hypaque 1077 (SigmaAldrich, St. Louis, MO, USA). Low-density cells were recovered from the Ficoll interface and collected by centrifugation. Genomic DNA was extracted by using Puregene DNA purification reagents (Gentra, Minneapolis, MN, USA). To detect JAK2V617F mutation and measure the JAK2V617F allele burden, we extracted 50 ng of total genomic DNA and performed quantitative allele-specific suppressive polymerase chain reaction (PCR) with the use of the 7900HT FAST platform sequence detection system (Applied Biosystems, Foster City, CA, USA), as previously described.18 Detection of frame shift mutations in exon 9 of CALR was per80

formed as previously described8 by using the following primer pairs: Forward: 5’ -FAM-GGCAAGGCCCTGAGGTGT; reverse: GGCCTCAGTCCAGCCCTG. This reaction captures the two frameshift type 1 (52 bp deletion) and type 2 (5-bp deletions) mutations. To detect mutations in exon 10 of MPL, we amplified genomic DNA by using the following primer set: MPL13474-F; GTGACCGCTCTGCATCTAGTG, MPL13726-R; GTGGGCGTGTTAGAG TGT. The resulting 250-bp PCR product was purified with use of a Qiagen PCR purification kit (Qiagen, Valencia, CA, USA) and was subjected to Sanger sequencing by using the above primers on a 3300 Genetic Analyzer (Applied Biosystems). The DNA sequencing fragments were analyzed with the use of Lasergene 11 (DNASTAR, Madison, WI, USA).

Statistical analysis Patients' characteristics were summarized by using frequencies (percentages) for categorical variables and median and range for continuous variables. To compare patients on the basis of categorical variables, we used the χ2 test. To compare medians, we used the Mann-Whitney test. To determine the optimal survival cut-off point that dichotomized patients according to their JAK2V617F allele burden, we used the X-Tile statistical software (http://www.tissuearray.org/rimmlab). The cut-off point used corresponds to the maximum χ2 value of the Mantel-Cox test for OS between groups above and below the cut-off point threshold.19 The probability of OS was estimated by the Kaplan-Meier method. The log-rank test was used to compare patients’ survival. Univariable and multivariable Cox proportional hazard regression models were fit to assess the association between mutation status and OS. The Wald test was used to assess the significance of covariates in Cox models. To compare competing models, we used the log-likelihood ratio. The replicability of the prognostic scoring system was tested by bootstrap resampling. One thousand samples, the same size as the original series, were built through random extraction with reposition. To predict the risk of transformation based on mutation status, we applied a logistic regression model and used the Exp (β) to estimate the odds ratio and the 95% confidence interval (CI) around it. Statistical analyses were performed with SPSS software (version 21, SPSS Inc., Chicago, IL, USA) and Graph Pad Prism (version 6.0, San Diego, CA, USA).

Results JAK2V617F, CALR, and MPL mutation frequency A total of 344 PMF patients, aged 26 to 86 years (median: 65 years; 64% males) were included. Patients’ characteristics are shown in Table 1. Of the 344 patients, 226 (66%) had a JAK2V617F mutation, 43 (12%) had a CALR mutation (40 patients had 50-52-bp deletions and 3 patients had 5-10 bp insertion), and 16 (5%) had an MPL mutation. Fifty-nine patients (17%) had none of these mutations and were designated 'triple-negative'.

JAK2V617 allele burden and survival When used as a continuous variable, JAK2V617F allele burden (ranging from 0% to 98%) had only marginal power to predict OS [Hazard Ratio (HR): 0.997, 95% Confidence Interval (CI): 0.990-1.00]. However, a 50% cut off of the JAK2V617F allele burden dichotomized patients into two groups with different survival outcomes. Patients with a JAK2V617F allele burden of 50% or over had a median OS of 80 months (95%CI: 51-109 months), whereas patients with a JAK2V617F allele burden of less than 50% had a median OS of 50 months (95%CI: 40-60 months) (P=0.01) haematologica | 2017; 102(1)


Mutation status and age predict survival in PMF

Table 1. Baseline characteristics of the 344 patients with primary myelofibrosis.

Table 2. Clinical characteristics of 226 primary myelofibrosis patients with a high (≥50%) and low (<50%) JAK2V617F allele burden.

Characteristics

Characteristics

Sex, n. (%) Male Female Age, median (range) (years) Performance status n. (%) 0 1 2 Splenomegaly n. (%) Yes No Splenectomy White cell count, median (range) (×109/L) Platelet count, median (range) (×109/L) Hemoglobin, median (range) (×109/L) Cytogenetics n. (%) Normal karyotype Abnormal Missing data n. (%)

N. (%) of patients 221 (64) 123 (36) 65 (26-86) 55 (16) 267 (78) 22 (6) 206 (60) 113 (33) 25 (7) 9.7 (1-361) 200 (10-971) 10.5 (5-19) 207 (60) 111 (32) 26 (8)

N., n:number.

(Figure 1A). Remarkably, patients with a high (≥50%) JAK2V617F allele burden had a larger spleen, a higher hemoglobin level, and a higher WBC count than did patients with a low (<50%) JAK2V617F allele burden (Table 2).

Mutation status and survival outcome The longest OS was observed in patients with mutated MPL (median survival 221 months, 95%CI: 40-401 months), followed by patients with mutated CALR (median survival 131 months, 95%CI: 100-160 months), high JAK2V617F burden (median survival 80 months, 95%CI: 51-109 months), triple-negatives (median survival 56 months, 95%CI: 35-77 months), and low JAK2V617F burden (median survival 50 months, 95%CI: 38-62 months) (Figure 1B).The incorporation of high- and low-JAK2V617F mutation status divides PMF patients into two groups: patients with either high JAK2V617F allele burden, mutated CALR, or mutated MPL had a median survival of 104 months (95%CI: 86-122 months), whereas patients with low JAK2V617F allele burden or triple-negative mutation status had a median survival of 48 months (95%CI: 39-57 months) (Figure 1C).

Development of an age- and mutation status-based prognostic model for survival When mutation status and DIPSS variables were included as covariates in a multivariable analysis, only unfavorable mutation status, older age, and a high percentage of peripheral blood blasts predicted a shorter survival (Table 3). Age dichotomized patients into two groups with different survival outcomes. Patients aged 65 years or under had a median OS of 97 months (95%CI: 67-127 months; n=175), whereas patients older than 65 had a median OS of 47 months (95% CI: 39-55 months; n=169) (P<0.0001) (Figure 1D). However, a model that included 2 parameter estimates (age and mutation status) was superior in fitting the data, as had the largest log-likelihood ratio, and dividhaematologica | 2017; 102(1)

Sex, n. (%) Male Female Age, median (range) (years) Performance status, n. (%) 0 1 2 Splenomegaly, n. (%) Yes No Splenectomy Hemoglobin, median (range) (×109/L) WBC count, median (range) (×109/L) Platelet count, median (range) (×109/L) Circulating blasts, median (range) (×109/L) Cytogenetic abnormalities, n. (%) Normal karyotype Abnormal karyotype Missing data DIPSS risk group, n. (%) Low Intermediate-1 Intermediate-2 High Transformation to acute myeloid leukemia, n. (%)

P

Low allele burden N=115

High allele burden N=111

77 (67) 38 (33) 65 (38-83)

74 (67) 37 (33) 66 (39-84)

22 (18) 89 (77) 5 (4)

13 (12) 86 (78) 12 (11)

61 (53) 48 (42) 6 (5) 10.3 (5-16)

89 (80) 15 (14) 7 (6) 11.3 (6-19)

<0.001

7.5 (1-159)

16.1 (2-189)

<0.0001

187 (18-858)

201 (15-642)

0.3

0 (0-6)

0 (0-7)

0.9

0.9 0.8 0.08

<0.0001

0.6 69 (60) 35 (30) 11 (10)

66 (59) 40 (36) 5 (5)

9 (8) 34 (30) 57 (56) 14 (12) 7 (6)

7 (6) 45 (41) 45 (44) 13 (12) 11 (10)

0.4

0.3

DIPSS: dynamic international prognostic system; WBC: white blood count.

ed the cohort into 4 groups of almost equal size. Bootstrapping resampling procedure confirmed the stability of the model. Patients with a favorable mutation status (high JAK2V617F allele burden, CALR, or MPL mutations) and aged 65 years or under had a median OS of 126 months (95%CI: 91-161 months; n=82). Patients with one risk factor, either age over 65 years (n=88) or adverse mutation status (n=87) had an intermediate OS of 72 months, whereas patients with two risk factors, e.g. age over 65 years and an adverse mutation status (low JAK2V617F allele burden or triple-negative; n=87) had a median OS of 35 months (95%CI: 31-113 months) (Table 4 and Figure 1E). In comparison, the DIPSS uses 5 risk factors to classify patients into one of 4 groups. In our cohort, most patients (n=228, 78%) were classified as either intermediate-1 or -2 (Table 5) and had similar survival outcome.

Mutation status and the risk of transformation Thirty-two patients (9%) transformed to acute myeloid leukemia. Median time to transformation was 33 months (range 1-271 months). None of the mutations predicted transformation to acute myeloid leukemia. 81


U. Rozovski et al. B Overall survival (probability)

Overall survival (probability)

A

P=0.0012

P=0.0064

C

P=0.0001

E

P<0.0001

Overall survival (probability)

Overall survival (probability)

D

P<0.0001

Figure 1. Survival of 344 patients with primary myelofibrosis (PMF). (A) Overall survival of PMF patients with high (≥50%) and low (<50%) JAK2V617F allele burden. (B) Overall survival (OS) of PMF patients according to mutation status. (C) Overall survival of PMF patients with favorable and adverse mutation status. Patients with either high JAK2V617F allele burden, mutated CALR, or mutated MPL had a better OS than patients with low JAK2V617F allele burden or triple-negative mutation status. (D) Overall survival according to patients’ age (over or under 65 years of age). (E) OS of patients with PMF based on risk stratification according to age and mutation status.

Discussion The clinical outcome of patients with PMF is partially dictated by mutually exclusive driver mutations in the genes JAK2, CALR, or MPL.20 Here we show that patients’ mutation status can be integrated into a prognostic model. Although the survival of patients with a JAK2V617F mutation is heterogeneous, dividing these patients into subgroups of high and low JAK2V617F allele burden enabled the development of a prognostic model that integrates genetic information. Patients with low JAK2V617F allele burden or a triple-negative mutation status had a shorter OS than patients in the other groups. Because we found that patients’ age is of prognostic significance, similar to other investigators’ findings, we integrated the patients’ mutation status and age, and analyzed 4 equally-sized cohorts. Patients with no risk factors (aged 65 years or under with a favorable mutation status) had the longest survival (median OS 126 months); patients with a single risk factor (over 65 years of age or an adverse mutation status) had an intermediate survival duration (median OS 72 months); 82

and patients with two risk factors (over 65 years of age and an adverse mutation such as JAK2V617F allele burden or triple-negative mutation status) had the worst prognosis (median OS 35 months). Although the percentage of circulating blasts emerged as a prognostic indicator, it did not contribute to the overall variance and was not included in the final model. Given that our hospital is a tertiary care cancer center, our PMF patient cohort has a high proportion of high-risk patients; this PMF patient population is particularly suitable for this analysis. Notably, only 7% of our patients were low-risk patients according to the DIPSS, compared with 44% in the IPSS. Hence, while our prognostic scale divides our patient cohort into 4 groups of equal size, it is possible that lower-risk patients were under-represented. Nevertheless, because prognostic scales for patients with PMF are routinely used to identify high-risk patients who are suitable for allogeneic transplantation, this scale might prove to be very useful. The identification of mutually exclusive mutations in most patients with PMF8-10 suggests that at least three distinct pathways play a role in disease acquisition. In our cohort, 13% of PMF patients had triple-negative haematologica | 2017; 102(1)


Mutation status and age predict survival in PMF

Table 3. Cox regression model of mortality including age and mutation status and DIPSS variables as covariates.

Covariate

Wald test

Hazard ratio

95% CI

P

22.6 15.6 10.8 0.002 0.7 1.0

2.2 1.9 1.7 1.0 0.8 0.8

(1.6-3.1) (1.6-3.1) (1.2-2.3) (0.7-1.4) (0.6-1.3) (0.6-1.2)

<0.0001 <0.0001 0.001 0.96 0.40 0.30

Mutation status Peripheral blood blasts >1% Age >65 years Hemoglobin <10 g/dL WBC count >25,000 (x109/L) Constitutional symptoms

Table 4. Cox regression model to assess the age and mutation status model of mortality in patients with PMF.

Covariate

Age ≤65 years, favorable mutation status Age >65 years, favorable mutation status Age ≤65 years, unfavorable mutation status Age >65 years, unfavorable mutation status

Wald test

Hazards ratio

95% CI

P

8.5 6.9 25.1

1 1.9 1.8 3.3

(1.2-3.1) (1.2-2.9) (2.1-5.3)

0.004 0.009 <0.0001

PMF: primary myelofibrosis; CI: confidence interval.

Table 5. Comparison of the DIPSS and genetic-based Cox proportions models for prediction of survival in patients with PMF. Covariates

Cohort distribution of risk, n. (%) patients

Model statistics P value for the deviance**

DIPSS

Age and mutation status model

Age Hemoglobin White blood cell counts Peripheral blood cell counts Constitutional symptoms Low: 25 (7) Intermediate-1: 114 (33) Intermediate-2: 154 (45) High 49: (14) P=0.03

Mutation status Age

Low: 87 (25) Intermediate: 175 (51) High: 82 (24) P <0.0001

DIPSS: dynamic international prognostic system; PMF: primary myelofibrosis. **Deviance equals the 2 distribution of the -2 (LL1-LL0) where LL1 is the log likelihood of the model and LL0 is the log likelihood of the null model.

mutation status. It is possible that these patients carry mutations in yet unidentified genes or that triple-negative status may represent a late event in clonal evolution that gives proliferation and/or survival advantage to a dominant neoplastic clone that is no longer dependent on the initial 'driver' mutagenic event. The survival of patients with a high (≥50%) JAK2V617F allele burden was significantly better than that of patients with a low JAK2V617F allele burden. It has been reported that PMF patients with a homozygous JAK2 mutation have distinct clinical features such as splenomegaly.21 Here we show that the clinical features on presentation of patients with a high JAK2V617F allele burden were reminiscent of patients with polycythemia vera (PV); they had discernible splenomegaly, leukocytosis, and higher hemoglobin levels compared with the group with low JAK2V617F allele burden. Therefore, it is possible that this group consists, at least in part, of patients with post-PV myelofibrosis that evolved from an undiagnosed PV. Interestingly, in a study of 68 patients with post-PV myelofibrosis, all patients carried a high JAK2V617F allele burden, and 78% had an allele burden of more than 50%.6,22 CALR mutations have been divided into two types. In PMF the type haematologica | 2017; 102(1)

1/type 1-like mutations are the most common ones.23-25 In our patient cohort only 3 patients had type 2 mutations. Therefore, our study was not powered to determine the prognostic value of CALR mutation subtypes. Since the initial publication of the IPSS prognostic score,5 several refinements have been proposed, most of which attempt to incorporate recurrent gene mutations that have been identified in patients with PMF.26 Some mutations, such as those in DNTM327 or TET2,28 have not been shown to correlate with survival outcome. Conversely, mutations in ASXL1, SRSF2, and EZH2 predicted short survival in a large cohort of patients, and only the ASXL1 mutation remained statistically significant when added to the IPSS prognostic score.29 A report by Tefferi et al.10 points to the CALR–/ASXL1+ profile as the most detrimental mutation profile in PMF. The applicability of our prognostic scale depends on screening for mutations in CALR and MPL and quantification of the JAK2V617F allele burden. Recently, the WHO added CALR and MPL mutations to the PMF diagnostic criteria30 and, as a result, most diagnostic laboratories perform these tests. Moreover, most diagnostic laboratories assess the presence of JAK2 mutations by using quantita83


U. Rozovski et al.

tive PCR. Although the JAK2V617F allele burden is readily available, it is not routinely reported, although various assays yield similar quantification results.31 Here we present a prognostic model that is based on a relatively large cohort. The internal validation of this model was confirmed by bootstrap resampling. By using only 2 variables, we developed a simple, easily applied model with excellent discrimination power for survival outcome of patients with newly diagnosed PMF. Although this prognostic model needs to be validated

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haematologica | 2017; 102(1)


ARTICLE

Myeloproliferative Disorders

Associations between gender, disease features and symptom burden in patients with myeloproliferative neoplasms: an analysis by the MPN QOL International Working Group Holly L. Geyer,1 Heidi Kosiorek,2 Amylou C. Dueck,2 Robyn Scherber,3 Stefanie Slot,4 Sonja Zweegman,4 Peter AW te Boekhorst,5 Zhenya Senyak,6 Harry C. Schouten,7 Federico Sackmann,8 Ana Kerguelen Fuentes,9 Dolores HernándezMaraver,9 Heike L. Pahl,10 Martin Griesshammer,11 Frank Stegelmann,12 Konstanze Döhner,12 Thomas Lehmann,13 Karin Bonatz,14 Andreas Reiter,14 Francoise Boyer,15 Gabriel Etienne,16 Jean-Christophe Ianotto,17 Dana Ranta,18 Lydia Roy,19 Jean-Yves Cahn,20 Claire N. Harrison,21 Deepti Radia,21 Pablo Muxi,22 Norman Maldonado,23 Carlos Besses,24 Francisco Cervantes,25 Peter L. Johansson,26 Tiziano Barbui,27 Giovanni Barosi,28 Alessandro M. Vannucchi,29 Chiara Paoli,29 Francesco Passamonti,30 Bjorn Andreasson,26 Maria L Ferrari,31 Alessandro Rambaldi,27 Jan Samuelsson,32 Keith Cannon,1 Gunnar Birgegard,33 Zhijian Xiao,34 Zefeng Xu,34 Yue Zhang,34 Xiujuan Sun,34 Junqing Xu,34 JeanJacques Kiladjian,35 Peihong Zhang,36 Robert Peter Gale37 and Ruben A. Mesa38

1 Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ, USA; 2Section of Biostatistics, Mayo Clinic, Scottsdale, AZ, USA; 3Oregon Health Sciences University, Portland, OR, USA; 4Department of Hematology, VU University Medical Center, Amsterdam, the Netherlands; 5Department of Hematology, Erasmus MC, Rotterdam, the Netherlands; 6MPN Forum, Ashville, NC, USA; 7Department of Hematology, MUMC, Maastricht, the Netherlands; 8Fundaleu, Buenos Aires, Argentina; 9Department of Haematology, University Hospital La Paz, Madrid, Spain; 10Department of Molecular Hematology, University Hospital Freiburg, Germany; 11Johannes Wesling Klinikum, Minden, Germany; 12Department of Internal Medicine III, University Hospital of Ulm, Germany; 13Hematology Department, University Hospital, Basel, Switzerland; 14 Medizinische Klinik, Universitätsmedizin, Mannheim, Germany; 15Centre Hospitalier Universitaire, Angers, France; 16Institut Bergonie, Bordeaux, France; 17Centre Hospitalier Universitaire, Brest, France; 18Hospitalier Universitaire, Nancy, France; 19Centre Hospitalier Universitaire, Poitiers, France; 20Centre Hospitalier Universitaire, Grenoble, France; 21Department of Haematology, Guy's and St. Thomas NHS Foundation Trust, London, UK; 22Unidadde Hematología, Hospital Británico, Montevideo, Uruguay; 23 University of Puerto Rico School of Medicine, San Juan, Puerto Rico; 24Hematology Department, Hospital del Mar, Barcelona, Spain; 25Hematology Department, Hospital Clínic, IDIBAPS, University of Barcelona, Spain; 26Internal Medicine, NU Hospital Organization, Uddevalla, Sweden; 27Research Foundation (FROM), Hospital Papa Giovanni XXIII, Bergamo, Italy; 28Laboratory of Clinical Epidemiology, IRCCS Policlinico S. Matteo Foundation, Pavia, Italy; 29Center for Research and Innovation of Myeloproliferative Neoplasms, University of Florence, Italy; 30Ematologia, Dipartimento di Medicina Clinica e Sperimentale, University of Insubria, Varese, Italy; 31Biol. Sci., Ospedali Riuniti di Bergamo, Italy; 32Department of Internal Medicine, Stockholm South Hospital, Sweden; 33Department of Hematology, University Hospital, Uppsala, Sweden; 34MDS and MPN Center, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China; 35Clinical Investigation Center, Hospital Saint-Louis, Paris, France; 36Department of Pathology, Institute of Hematology and Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China; 37Imperial College, London, UK and 38Department of Hematology and Oncology, Mayo Clinic, Scottsdale, AZ, USA

ABSTRACT

T

he myeloproliferative neoplasms, including polycythemia vera, essential thrombocythemia and myelofibrosis, are distinguished by their debilitating symptom profiles, life-threatening complications and profound impact on quality of life. The role gender plays in the symptomatology of myeloproliferative neoplasms remains underinvestigated. In this study we evaluated how gender relates to patients’ characteristics, disease complications and overall symptom expression. A total of 2,006 patients (polycythemia vera=711, essential thrombocythemia=830, myelofibrosis=460, unknown=5) were prospectively evaluated, with patients completing the Myeloproliferative NeoplasmSymptom Assessment Form and Brief Fatigue Inventory Patient haematologica | 2017; 102(1)

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):85-93

Correspondence: mesa.ruben@mayo.edu or geyer.holly@mayo.edu

Received: May 19, 2016. Accepted: August 12, 2016. Pre-published: August 18, 2016. doi:10.3324/haematol.2016.149559

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/85

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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Reported Outcome tools. Information on the individual patients’ characteristics, disease complications and laboratory data was collected. Consistent with known literature, most female patients were more likely to have essential thrombocythemia (48.6% versus 33.0%; P<0.001) and most male patients were more likely to have polycythemia vera (41.8% versus 30.3%; P<0.001). The rate of thrombocytopenia was higher among males than females (13.9% versus 8.2%; P<0.001) and males also had greater redblood cell transfusion requirements (7.3% versus 4.9%; P=0.02) with shorter mean disease duration (6.4 versus 7.2 years, P=0.03). Despite there being no statistical differences in risk scores, receipt of most therapies or prior complications (hemorrhage, thrombosis), females had more severe and more frequent symptoms for most individual symptoms, along with overall total symptom score (22.8 versus 20.3; P<0.001). Females had particularly high scores for abdominal-related symptoms (abdominal pain/discomfort) and microvascular symptoms (headache, fatigue, insomnia, concentration difficulties, dizziness; all P<0.01). Despite complaining of more severe symptom burden, females had similar quality of life scores to those of males. The results of this study suggest that gender contributes to the heterogeneity of myeloproliferative neoplasms by influencing phenotypic profiles and symptom expression.

Introduction

Methods

The myeloproliferative neoplasms (MPN) have a reputation for molecular complexity, clinical heterogeneity and profound impact on duration and quality of life. Polycythemia vera (PV), essential thrombocythemia (ET) and myelofibrosis (MF) are debilitating MPN associated with arterial and venous thrombosis, cytopenias, marked splenomegaly, persistent constitutional symptoms and a predilection for transformation into acute myelogenous leukemia or MF (in ET and PV). There is emerging interest in understanding how gender affects the development of MPN as well as the manifestations and progression of the disease. As exemplified by the higher prevalence of females with ET and males with PV, it has long been recognized that males and females may be affected differently. However, recent literature supports the potential for gender to influence genotypic expression and, potentially, clonal expansion. For example, an investigation of gene expression in circulating CD34+ cells from 19 JAK2V617F-positive PV patients found that fewer genes were differentially expressed in females (235 genes) than in males (571 genes), but that more than three times as many molecular pathways were activated in females.1 Females also have dramatically lower JAK2V617F allele burdens.2,3 Furthermore, it has been shown that there are female-dominant MPN clusters (both PV and ET) typified by a high prevalence of laboratory abnormalities and sexuality-related complaints.4 Despite these new insights, little is known about how gender relates to symptom profiles. The timely development of MPN-specific Patient Reported Outcome (PRO) tools has allowed us to objectively quantify MPN symptom burden and evaluate the impact of this disease on quality of life. The Myelofibrosis Symptom Assessment Form (MF-SAF), Myeloproliferative Neoplasm Symptom Assessment Form (MPN-SAF) and MPN-10 have been applied in both clinical and trial settings, yielding significant insights into how observed clinical and symptomatic heterogeneity may, in fact, follow predictable patterns and/or harbor otherwise unrecognized associations. In this study, we examine associations between gender and patients’ symptomatology, along with disease features, laboratory abnormalities and overall quality of life.

Survey development and collection

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This study was approved by the Mayo Clinic Institutional Review Board. Data were collected from an international cohort of patients with MPN including ET, PV and MF. All patients were recruited using the methods described previously during the validation of the MPNSAF.5 The development and validation of the MPN-SAF PRO are described in the Online Supplementary Appendix. The language translation process is also detailed in the Online Supplementary Appendix and was based on standard PRO translation methods.6 In addition to the MPNSAF, subjects also completed the Brief Fatigue Inventory (BFI).7 Data were collected in various languages: English, Dutch, Italian, French, German, Chinese, Swedish and Spanish. Gender was recorded based on patients’ selfreporting under the question of ‘sex’ with respondent options of ‘male’ or ‘female’. Evaluation of cultural/regional variations in symptom expression involved comparisons of Chinese patients with ‘Western’ patients, who were predominantly Caucasian individuals from western Europe and the USA.

Symptom evaluation Symptoms listed in the MPN-SAF included the patient’s perceptions of common MPN-related symptoms and overall quality of life on a scale from 0 (absent) to 10 (worst imaginable). The symptoms assessed included items related to sadness, quality of life, inactivity, concentration problems, abdominal pain/discomfort, dizziness, insomnia, night sweats, worst fatigue, early satiety, bone pain, numbness, cough, itching, headache, fever and weight loss. Total symptom score was computed based on ten symptom items. For individuals completing at least six of the ten MPN-SAF total symptom score items, the survey was scored by multiplying the average score across items by ten to obtain a scaled score from 0 to 100.

Prognostic scoring A prognostic score for ET was calculated using the International Prognostic Scoring for Essential Thrombocythemia (IPSET) system.8 This scoring system, which includes the variables of leukocyte count haematologica | 2017; 102(1)


Gender differences in MPN ≥11x109/L (1 point), age ≥60 years (2 points), and history of thrombosis (1 point), was used to stratify patients into different risk groups: low risk (0 points), intermediate risk (1-2 points) and high risk (3-4 points). The prognostic score for survival of patients with PV was calculated using the Leukemia 2013 prognostic scoring model.9 This scoring system includes the variables of age ≥67 years(5 points), age 57-66 years (2 points), prior thrombosis (1 point) and leukocyte count ≥15x109/L (1 point) to stratify patients into low-risk (0 points), intermediate risk (1-2 points) and high-risk (≥3 points) groups. The prognostic score for survival in patients with MF was calculated using the Dynamic International Prognostic Scoring System (DIPSS).10 This scoring model includes the variables of hemoglobin <10 g/dL (2 points), age ≥65 years (1 point), white blood cell count ≥25x109/L (1 point), the presence of constitutional symptoms (1 point) and ≥1% blasts (1 point) to stratify patients into low-risk (0 points), intermediate-1-risk (1-2 points), intermediate-2-risk (3-4 points) and high-risk (>4 points) groups.

Statistical analysis All comparisons of patients’ symptoms were adjusted for type of MPN and age. Continuous variables were compared using analysis of variance and dichotomous data were compared using the chi-square test. Statistical significance was set at P<0.05. SAS version 9.3 (Cary, NC, USA) was used for the analyses.

Results Patients’ demographics A total of 2,006 patients (917 males, 1,089 females) with MPN completed the MPN-SAF and BFI (Table 1). MPN subtypes included PV (n=711), ET (n=830) and MF [n=460; primary MF (68.3%); post-ET MF (18%); postPV MF (13.7%)]. Patients were of the expected age (mean 59.9 years; range, 15-94) for their disorders and consisted primarily of Chinese (27.1%) and French (23.0%) speakers. When separated by DIPSS risk categories, most MF patients were stratified as intermediate-1 risk (54.5%), followed by intermediate-2 risk (24.3%), low risk (18.3%) and high risk (3%). Most ET patients were stratified as intermediate risk (46.7%), followed by low risk (36.0%) and high risk (17.3%). For PV, most patients were in the high-risk category (49.5%), followed by intermediate-risk (29.7%) and low-risk (20.7%) categories. The mean hemoglobin concentration (13.4 g/dL, SD 3.17), white blood cell count (8.9x109/L, SD 7.15), and platelet count (429.5x109/L, SD 269.72) were evaluated, along with laboratory abnormalities including anemia (present in 8.5%), thrombocytopenia (present in 10.7%) and leukopenia (present in 10.0%). Prior thrombosis (21.2%) and prior hemorrhage (5.4%) were relatively uncommon and most patients (94.0%) did not require red blood cell transfusions.

Clinical factors When comparing clinical factors between genders, female patients were found to be slightly younger (59.3 versus 60.7 years, P=0.02) with more patients under the age of 60 at the time of data collection (48.9% versus 43.4%, P=0.01; Table 1). The prevalence of MPN subhaematologica | 2017; 102(1)

types also differed by gender (P=0.01) with more females having a diagnosis of ET (48.6%) than of PV (30.3%) and MF (21.2%) and more male patients having a history of PV (41.8%) than of ET (33.0%) and MF (25.2%). Gender distribution also differed by MPN subtype with primary

Table 1. MPN patients’ demographics by gender.

Females (n=1089)

Males (n=917)

Mean age (range), years 59.3 (14.36) 60.7 (12.64) Age <60 years 532 (48.9%) 397 (43.4%) MPN subtype (n, %) ET 528 (48.6%) 302 (33.0%) PV 329 (30.3%) 382 (41.8%) MF 230 (21.2%) 230 (25.2%) MF (n, %) Primary MF 142 (61.7%) 172 (74.8%) ET-MF 50 (21.7%) 33 (14.3%) PV-MF 38 (16.5%) 25 (10.9%) Mean MPN duration 7.2 (7.0) 6.4 (6.5) (years, SD) Language (n, %) Chinese 292 (26.8%) 252 (27.5%) Dutch 118 (10.8%) 118 (12.9%) English 75 (6.9%) 82 (8.9%) French 257 (23.6%) 205 (22.4%) German 72 (6.6%) 41 (4.5%) Italian 103 (9.5%) 83 (9.1%) Spanish 112 (10.3%) 82 (8.9%) Swedish 60 (5.5%) 54 (5.9%) MF DIPSS risk (n, %) Low 24 (20.7%) 19 (16.0%) Intermediate-1 64 (55.2%) 64 (53.8%) Intermediate-2 24 (20.7%) 33 (27.7%) High 4 (3.4%) 3 (2.5%) ET IPSET risk (n, %) Low 176 (37.8%) 86 (32.7%) Intermediate 218 (46.9%) 122 (46.4%) High 71 (15.3%) 55 (20.9%) PV risk (n, %) Low 49 (19.1%) 66 (22.1%) Intermediate 71 (27.7%) 94 (31.4%) High 136 (53.1%) 139 (46.5%) Anemia 78 (8.4%) 66 (8.7%) (Hb<10 g/dL) (n, %) Leukopenia 91 (9.9%) 77 (8.7%) (WBC<10x109/L) (n, %) Thrombocytopenia 76 (8.2%) 105 (13.9%) (platelets <150x109/L) (n, %) Mean hemoglobin (SD) 13.0 (3.36) 13.8 (2.86) Mean WBC count (SD) 8.5 (6.09) 9.5 (8.24) Mean platelet 454.1 (269.42) 399.5 (267.21) count (SD) Laboratory abnormalities (n, %) 206 (22.2%) 200 (26.3%) Prior thrombosis (n, %) 217 (20.4%) 200 (22.2%) Prior hemorrhage 55 (5.1%) 52 (5.7%) RBC transfusion 53 (4.9%) 67 (7.3%) requirements

Total (n=2006) 59.9 (13.61) 929 (46.4%)

P-value 0.02 0.01 <0.001

830 (41.5%) 711 (35.5%) 460 (23.0%) 0.01 314 (68.3%) 83 (18%) 63 (13.7%) 6.8 (6.9)

0.03 0.19

544 (27.1%) 236 (11.8%) 157 (7.8%) 462 (23%) 113 (5.6%) 186 (9.3%) 194 (9.7%) 114 (5.7%) 0.55 43 (18.3%) 128 (54.5%) 57 (24.3%) 7 (3%) 0.11 262 (36%) 340 (46.7%) 126 (17.3%) 0.30 115 (20.7%) 165 (29.7%) 275 (49.5%) 144 (8.5%)

0.84

168 (10.0%)

0.83

181 (10.7%)

<0.001

13.4 (3.17) 8.9 (7.15) 429.5 (269.72)

<0.001 0.004 <0.001

406 (24%) 417 (21.2%) 107 (5.4%) 120 (6.0%)

0.049 0.34 0.53 0.02

WBC: white blood cell; RBC: red blood cell.

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MF being more prevalent in males (74.8% versus 61.7%; P=0.01) and post-ET MF being more common in females (21.7% versus 14.3%; P=0.01). Mean hemoglobin concentration (13.8 versus 13.0 g/dL, P<0.001) and white blood cell count (9.5 versus 8.5x109/L, P=0.004) were higher in males whereas females had a higher mean platelet count (454.1 versus 399.5x109/L, P<0.001). Thrombocytopenia was more common in males (13.9% versus 8.2%, P<0.001) whereas no differences were noted in the prevalence of anemia or leukopenia (P>0.05). Males were also more likely to have a history of red blood cell transfusion requirements (7.3% versus 4.9%, P=0.02). Risk scores, language prevalence, history of prior thrombosis or hemorrhage did not differ by gender (all P>0.05). Prior thrombosis was further stratified by gender and MPN type: no differences were noted in ET (males 23.5% versus females 19.3%, P=0.156), PV (males 26.7% versus females 29.8%, P=0.339) or MF (males 12.8% versus females 9.7%, P=0.298). Few differences were noted

between genders when comparing prior therapies, with the exception of higher rates of phlebotomy/venesection and givinostat/vorinostat use in males (both P<0.05; Figure 1).

Symptoms of myeloproliferative neoplasms analyzed by gender After adjusting for MPN subtype and age, the overall total symptom score was higher for females than males [22.8 (SD=17.0) versus 20.3 (SD=16.3), P<0.001; Figure 2]. Females also had higher scores for all individual MPN symptoms that met statistical significance (Figure 3). These included fatigue (4.5 versus 4.0, P<0.001), early satiety (2.6 versus 2.3, P=0.02), abdominal pain (1.6 versus 1.2, P=0.001), abdominal discomfort (2.1 versus 1.6, P<0.001), headache (2.2 versus 1.6, P<0.001), concentration difficulties (2.7 versus 2.3, P=0.01), dizziness (2.5 versus 2.0, P<0.001), numbness (2.6 versus 2.2, P=0.001), insomnia (3.4 versus 2.4, P<0.001), sadness (2.6 versus 2.3,

Figure 1. Percentage of MPN patients who have received prior therapies (x axis) compared by gender.

Figure 2. Distribution of MPN-SAF scores according to age in females (top) and males (bottom) Evaluation of total number of patients in each gender (y axis) when compared by total MPNSAF TSS value (x axis).

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P=0.01), night sweats (2.4 versus 2.0, P=0.002) and bone pain (2.3 versus 1.6, P<0.001). Items that did not show gender differences included inactivity, sexuality concerns, cough, pruritus, fever, weight loss and overall quality of life. Fatigue was the most severe symptom in both genders. The prevalence of symptoms differed between genders for many of the individual MPN items (Figure 4). With the exception of weight loss (males 37.4% versus females 31.7%, P=0.008), the prevalence of all symptoms that were statistically different between females and males were higher in the former. These symptoms included abdominal pain (46.0% versus 40.8%, P=0.02), abdominal discomfort (55.2% versus 50.7%, P=0.046), headache (58.1% versus 49.1%, P<0.001), dizziness (61.0% versus 56.6%, P=0.046), numbness (64.1% versus 58.1%, P=0.007), insomnia (70.5% versus 59.9%, P<0.001), night sweats (55.6% versus 49.8%, P=0.01) and bone pain (53.2% versus 43.4%, P<0.001).

Symptoms of myeloproliferative neoplasms analyzed by region/culture The influence of region/culture was also explored among male and female patients by comparing the Chinese cohort (n=544) with the Western cohort consisting of patients from Europe and the USA (n=1,462). Overall, female Chinese patients expressed more severe symptoms related to headaches (2.5 versus 2.0, P=0.01), dizziness (3.1 versus 2.2, P<0.0001), problems with sexuality (4.6 versus 2.9, P<0.0001), fever (0.6 versus 0.4, P=0.005) and weight loss (1.6 versus 1.1, P=0.001) with a higher total symptom score (22.2 versus 19.5, P=0.023) and worse overall quality of life (3.1 versus 2.8, P=0.048; Figure 5). Chinese females had higher scores for sexuality-related complaints (4.6/10) and insomnia (3.3/10). In contrast, Western females described worse fatigue (4.7 versus 4.0, P=0.0003) and abdominal pain (1.7 versus 1.1, P=0.0004). The highest scores for Western females were for fatigue (4.7/10) and insomnia (3.4/10).

Figure 3. Comparison of scores for the individual items of the MPN-SAF between males and females.

Figure 4. Comparison of the prevalence of MPN-SAF symptoms between males and females.

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Like Chinese females, Chinese males also expressed more severe symptoms related to headaches (1.9 versus 1.4, P=0.001), dizziness (2.6 versus 1.8, P<0.0001), sexuality problems (4.5 versus 3.4, P=0.0001), fever (0.7 versus 0.4, P=0.0002) and weight loss (2.2 versus 1.1, P<0.0001) (Figure 6) than their Western counterparts. The highest scores for Chinese males were for sexuality concerns (4.5/10) and fatigue (3.9/10). The same pattern was seen for Western males, with the highest scores being for fatigue (4.1/10) and sexuality concerns (3.4/10).

Discussion The diversity of the various types of MPN has made full characterization of their symptom profiles challenging. PV, ET and MF may concurrently shorten survival and impair quality of life. For decades, gender differences in MPN have been observed and documented but remained of low investigational priority given the pauci-

ty of exploratory tools. Objective examination of symptom heterogeneity has now emerged as a possibility following the development of MPN-specific PRO tools (MFSAF, MPN-SAF and MPN-10), enhanced precision of risk scoring algorithms and advances in genomic sequencing.5,11,12 Applying many of these novel instruments, this study represents the first large-scale investigation into the correlates between gender, clinical features and patientsâ&#x20AC;&#x2122; symptoms. This investigation yielded a number of important findings. The first is the observation that female patients were more likely to have ET (48.6%) whereas males were more likely to have PV (30.3%). This is consistent with previous findings, with published data historically supporting a prevalence of females among ET patients and a prevalence of males among patients with PV.13-17 Gender discrepancies within hematologic malignancies are not unique to MPN. Similar discordances in gender prevalence have been demonstrated in other disorders such as acute lymphoblastic leukemia, chronic lympho-

Figure 5. Comparison of scores for individual MPN-SAF items between Chinese and Western females.

Figure 6. Comparison of scores for individual MPN-SAF items between Chinese and Western males.

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cytic leukemia and multiple myeloma.18,19 Although the etiological cause of this discordance remains unclear, sex chromosome complement/aberrations/aneuploidy, an influence of sex hormones, immune-competence, and gene expression may all be potential contributors.20-23 Investigation of these factors was beyond the scope of this study but they would be worth exploring in future studies. This study also found that males and females have similar rates of thrombosis. Previous investigations showed that thrombotic risk typically differs by sex among the MPN subtypes.2,24-26 Within the ECLAP study, female PV patients were more likely than males to suffer thrombotic complications (11% versus 8%), particularly within the splanchnic system.27 Similarly, multivariable analysis of data from a recent international collaborative study of 891 ET patients identified that only male gender was predictive of venous thrombosis.28 Gender also appears to influence the location of vascular events. A recent investigation identified that women were more likely to experience macrothrombosis within the abdominal venous system (hepatic, portal, mesenteric or splenic veins) whereas males were more likely to experience events in the deep venous system, including limb thrombosis and pulmonary emboli.16 Although the influence of gender on the pathogenesis of thrombosis remains unclear, mounting evidence suggests that both the type and ratio of circulating sex hormones plays an important role in the thrombotic cascade. In an investigation involving exogenous sex-steroid administration, ET patients exposed to hormone replacement therapy (estrogen only) had similar rates of arterial and venous thrombosis when compared to ET patients not on therapy.29 Importantly, this finding conflicts with studies of healthy populations in which females taking hormone replacement therapy have been observed to be at greater thrombotic risk. However, ET patients utilizing oral contraceptive therapy (estrogen and progesterone combined) had increased rates of venous thrombosis, and specifically, a 5-fold increased risk of splanchnic venous thrombosis (15% versus 3%). From a hormonal standpoint, it remains unclear why male ET patients seem to face a higher risk of thrombosis than females, but this serves to show that the pathogenesis is likely multifactorial. We have no explanation for why males and females in our specific study population had similar rates of thrombosis, independently of MPN subtype. It should be noted that neither the location nor the type of thrombosis (arterial versus venous) was recorded in this study, and we suspect this information might have shed some light on our discrepant finding. We found it interesting that despite not differing by total number of thrombotic events, our female population still described more abdominal pain. Given that this study utilized reported events only (and did not prospectively investigate for thrombosis), it is possible that some female patients had unrecognized macrothrombosis in the abdominal cavity, accounting for this symptom. Alternatively, the discrepancy may be related to differences in spleen size, which were not investigated in this study, or to differences in symptom expression, which are discussed below. The observation that males and females reported different symptom burdens remains a major finding. Overwhelmingly, females described symptoms with haematologica | 2017; 102(1)

greater frequency and severity than males. In particular, abdominal complaints (abdominal pain, discomfort) and microvascular symptoms (headache, fatigue, insomnia, concentration difficulties, dizziness) dominated the female symptom burden. Factors that might have accounted for higher symptom scores (such as anemia, high-risk disease status or increased counts of hemorrhagic/thrombotic complications) were not observed to occur at higher rates in females. In fact, males were more likely to have increased transfusion requirements (despite describing less fatigue) and thrombocytopenia. The underlying cause of our observations is, therefore, uncertain. It is well recognized that the prevalence of abdominal pain is higher among females.30 Irritable bowel syndrome, a chronic constellation of abdominal symptoms including pain, discomfort and alterations in bowel habits, has been reported to occur in a female-tomale ratio of 3:1 and remains a common source of abdominal complaints in younger populations.31 However, the prevalence of irritable bowel syndrome declines in individuals over 60 years old and given the average age of MPN females, this syndrome is unlikely to serve as a primary symptom driver. It is plausible that in addition to having a higher risk of macrovascular events, females also incur more microvascular events. Microthrombosis contributes to microvascular symptoms (lightheadedness, dizziness, vertigo, concentration problems, numbness/tingling and sexual dysfunction) by compromising endothelial function and inducing local hypoxia.32 In this study, females clearly described more frequent and more severe microvascular symptoms than did males. Mechanisms that may account for different risks of microvascular dysfunction are worthy of further exploration and may parallel those driving macrothrombosis. Underreporting of microvascular symptoms by males is also a potential explanation of our observations and is discussed further below. Congruent with previous investigations, males and females described similar degrees of sexual dysfunction and fatigue remained the most symptomatic facet of the disease burden. Patientsâ&#x20AC;&#x2122; ethnicity and culture also appear to contribute to symptom burden. Variations in symptom expression were noted when Western and Eastern patients were compared. Independent of gender, Chinese patients described more microvascular symptoms (headaches, dizziness) and more concerns related to sexuality. In contrast, fatigue was the most prominent symptom among Western male and female patients. Variations between MPN in Eastern and Western patients have been highlighted by the presence of fundamental biological and clinical differences, which are being increasingly discussed in the literature.33,34 For example, Eastern patients with MF are more likely to be younger and less likely to struggle with constitutional symptoms or splenomegaly. Survival differences between the two cohorts has also been observed, with median survival being slightly longer in patients of Chinese ethnicity. Given the subjectivity inherent to symptom reporting, it remains unclear whether the differences in MPN-SAF scores between races are related to norms of cultural expression (especially willingness to verbalize problems related to sexuality) or the natural outworking of true genotypic and phenotypic differences between races. The possibility that our observations are related to reporting discrepancies is also an important matter of 91


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discussion. Published data show that females tend to describe more numerous and more intense symptoms than males, independent of location or organ system involved. In a study of 13,538 non-patient community residents, participants evaluated the lifetime prevalence of non-menstrual complaints and 20 of the 22 most common symptoms were reported more frequently by females.35 Similarly, experimental studies involving induction of pain have shown that females have a lower threshold of pain tolerance and report more symptoms than males.36 These findings may be driven by biological differences in somatic and visceral sensation, sex-influenced descriptiveness in symptom labeling and reporting, social acceptance of symptom revelation, sex-related differences in the prevalence of depression and anxiety and gender biases inherent to the research process. Some studies have suggested that females engender greater bodily vigilance, potentially as an innate mechanism to optimize fertility.37,38 Other studies advocate that social cues have impressed upon males the importance of limiting expression of discomfort/illness, maintaining a stoic appearance and underemphasizing complaints.39 Independently of the foregoing, we find it intriguing that female MPN patients had the same quality of life scores as males, despite having more frequent and severe symptomatology. The literature supports health-related quality of life as being typically rated lower among females. This has traditionally been attributed to the higher prevalence of disability and chronic conditions in this population.40 However, in this study MPN-related comorbidities were similar between the two sexes. It is plausible that MPN females have socially adapted to compensate for their intensified symptom burden. Alternatively, female patients may simply be more disposed to voice their complaints. We also note that females described greater symptom burdens but their risk scores were similar to those of the males. This information corroborates the previous finding of the MPN Symptom Burden study that MPN symptoms are not surrogates for disease severity.4 It is important to recognize that there are a number of limitations to this exploratory investigation. The first is that the term ‘gender’ is being used synonymously with genotypically-defined ‘sex’. As stated, the surveys allowed patients to self-report their sex as either ‘male’ or ‘female’. Although it may be assumed that the recorded choice referred to genotypic makeup, it is possible that some

References 1. Spivak JL, Considine M, Williams DM, et al. Two clinical phenotypes in polycythemia vera. N Engl J Med. 2014;371(9):808-817. 2. Stein BL, Williams DM, Wang NY, et al. Sex differences in the JAK2 V617F allele burden in chronic myeloproliferative disorders. Haematologica. 2010;95(7):1090-1097. 3. Passamonti F, Randi ML, Rumi E, et al. Increased risk of pregnancy complications in patients with essential thrombocythemia carrying the JAK2 (617V>F) mutation. Blood. 2007;110(2):485-489. 4. Geyer HL, Scherber RM, Dueck AC, et al. Distinct clustering of symptomatic burden

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patients recorded their ‘gender identity’ instead, which may not be synonymous with chromosomal makeup. Should this have occurred, we believe that the number of cases would have been small and likely consistent with the prevalence of discordant associations in the community. We also lack information on the exact location of events (peripheral versus central) and note that males had greater transfusion requirements than females despite similar rates of anemia. We suspect that this is related to the averaging of pre- and post-transfusion hemoglobin controls in males, resulting in falsely high hemoglobin levels. It is worth noting that the majority of patients within this population of MPN patients were classified as low to intermediate risk, which potentially skews symptom burden towards lower values. Although an evaluation of differences in symptom burden between genders separated by risk category was beyond the scope of this study, future investigations could further explore this issue to determine whether symptom progression differs between the sexes. It is important to note that there are inherent flaws in using a ‘self-reporting’ format. However, we believe that the use of validated MPN-specific PRO tools greatly improves the cogency of the results. In addition, members of the clinical team were primarily responsible for all data collection not related to symptom expression, conceivably limiting errors in the recording process. It is regrettable that underlying mutations could not be analyzed, as doing so could have offered yielded interesting information. The concomitant development of innovative technologies and novel symptom assessment tools has revolutionized the treatment landscape for MPN. Few fields of study can boast of a faster or more cooperative manner via which pioneering research has translated into improved outcomes for patients. In this study, we have determined that gender integrally relates to disease features and symptom burden. These results further underscore the importance of considering each gender individually as treatment regimens are designed. Understanding that males may be less likely to voice their MPN symptoms should influence clinicians to explore potentially under-expressed complaints. Similarly, acknowledging that females may have greater symptom burdens should motivate healthcare providers to consider novel therapies and explore trial options. This exploratory study indicates the importance of including gender as a contributor to heterogeneity and as an object of investigation in future studies.

among myeloproliferative neoplasm patients: retrospective assessment in 1470 patients. Blood. 2014;123(24):3803-3810. 5. Scherber R, Dueck AC, Johansson P, et al. The Myeloproliferative Neoplasm Symptom Assessment Form (MPN-SAF): international prospective validation and reliability trial in 402 patients. Blood. 2011;118 (2):401-408. 6. Wild D, Grove A, Martin M, et al. Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: report of the ISPOR Task Force for Translation and Cultural Adaptation. Value Health. 2005;8 (2):94-104. 7. Mendoza TR, Wang XS, Cleeland CS, et al.

The rapid assessment of fatigue severity in cancer patients: use of the Brief Fatigue Inventory. Cancer. 1999;85(5):1186-1196. 8. Passamonti F, Thiele J, Girodon F, et al. A prognostic model to predict survival in 867 World Health Organization-defined essential thrombocythemia at diagnosis: a study by the International Working Group on Myelofibrosis Research and Treatment. Blood. 2012;120(6):1197-1201. 9. Tefferi A, Rumi E, Finazzi G, et al. Survival and prognosis among 1545 patients with contemporary polycythemia vera: an international study. Leukemia. 2013;27(9):18741881. 10. Passamonti F, Cervantes F, Vannucchi AM, et al. A dynamic prognostic model to predict

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11.

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survival in primary myelofibrosis: a study by the IWG-MRT (International Working Group for Myeloproliferative Neoplasms Research and Treatment). Blood. 2010;115(9):1703-1708. Mesa RA, Schwager S, Radia D, et al. The Myelofibrosis Symptom Assessment Form (MFSAF): an evidence-based brief inventory to measure quality of life and symptomatic response to treatment in myelofibrosis. Leuk Res. 2009;33(9):1199-1203. Emanuel RM, Dueck AC, Geyer HL, et al. Myeloproliferative neoplasm (MPN) symptom assessment form total symptom score: prospective international assessment of an abbreviated symptom burden scoring system among patients with MPNs. J Clin Oncol. 2012;30(33):4098-4103. Passamonti F, Rumi E, Pungolino E, et al. Life expectancy and prognostic factors for survival in patients with polycythemia vera and essential thrombocythemia. Am J Med. 2004;117(10):755-761. Bellucci S, Janvier M, Tobelem G, et al. Essential thrombocythemias. Clinical evolutionary and biological data. Cancer. 1986;58(11):2440-2447. Fenaux P, Simon M, Caulier MT, Lai JL, Goudemand J, Bauters F. Clinical course of essential thrombocythemia in 147 cases. Cancer. 1990;66(3):549-556. Stein BL, Rademaker A, Spivak JL, Moliterno AR. Gender and vascular complications in the JAK2 V617F-positive myeloproliferative neoplasms. Thrombosis. 2011;2011:874146. Ania BJ, Suman VJ, Sobell JL, Codd MB, Silverstein MN, Melton LJ 3rd. Trends in the incidence of polycythemia vera among Olmsted County, Minnesota residents, 1935-1989. Am J Hematol. 1994;47(2):89-93. Ward E, DeSantis C, Robbins A, Kohler B, Jemal A. Childhood and adolescent cancer statistics, 2014. CA Cancer J Clin. 2014;64(2):83-103.

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19. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):730. 20. Ellegren H, Parsch J. The evolution of sexbiased genes and sex-biased gene expression. Nat Rev Genet. 2007;8(9):689-698. 21. Rinn JL, Snyder M. Sexual dimorphism in mammalian gene expression. Trends Genet. 2005;21(5):298-305. 22. Ober C, Loisel DA, Gilad Y. Sex-specific genetic architecture of human disease. Nat Rev Genet. 2008;9(12):911-922. 23. Bouman A, Heineman MJ, Faas MM. Sex hormones and the immune response in humans. Hum Reprod Update. 2005;11(4): 411-423. 24. Kittur J, Knudson RA, Lasho TL, et al. Clinical correlates of JAK2V617F allele burden in essential thrombocythemia. Cancer. 2007;109(11):2279-2284. 25. Larsen TS, Pallisgaard N, Moller MB, Hasselbalch HC. The JAK2 V617F allele burden in essential thrombocythemia, polycythemia vera and primary myelofibrosis-impact on disease phenotype. Eur J Haematol. 2007;79(6):508-515. 26. Girodon F, Schaeffer C, Cleyrat C, et al. Frequent reduction or absence of detection of the JAK2-mutated clone in JAK2V617Fpositive patients within the first years of hydroxyurea therapy. Haematologica. 2008;93(11):1723-1727. 27. Landolfi R, Marchioli R. European Collaboration on Low-dose Aspirin in Polycythemia Vera (ECLAP): a randomized trial. Semin Thromb Hemost. 1997;23(5): 473-478. 28. Carobbio A, Thiele J, Passamonti F, et al. Risk factors for arterial and venous thrombosis in WHO-defined essential thrombocythemia: an international study of 891 patients. Blood. 2011;117(22):5857-5859. 29. Gangat N, Wolanskyj AP, Schwager SM, Mesa RA, Tefferi A. Estrogen-based hor-

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ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Myeloproliferative DIsorders

Ferrata Storti Foundation

A phase 1/2, open-label study evaluating twice-daily administration of momelotinib in myelofibrosis

Vikas Gupta,1 Ruben A. Mesa,2 Michael W.N. Deininger,3 Candido E. Rivera,4 Shireen Sirhan,5 Carrie Baker Brachmann,6 Helen Collins,6 Jun Kawashima,6 Yan Xin6 and Srdan Verstovsek7

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Princess Margaret Cancer Centre, University of Toronto, ON, Canada; 2Division of Hematology and Medical Oncology, Mayo Clinic Cancer Center, Phoenix, AZ, USA; 3 Division of Hematology and Hematologic Malignancies, University of Utah Huntsman Cancer Institute, Salt Lake City, UT, USA; 4Division of Hematology/Oncology, Mayo Clinic Jacksonville, FL, USA; 5Division of Hematology, Jewish General Hospital, Montreal, QC, Canada; 6Gilead Sciences, Inc., Foster City, CA, USA and 7University of Texas MD Anderson Cancer Center, Houston, TX, USA

1

ABSTRACT

M

Correspondence: vikas.gupta@uhn.on.ca

Received: May 27, 2016. Accepted: September 14, 2016. Pre-published: September 15, 2016. doi:10.3324/haematol.2016.148924

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/94

omelotinib, a small-molecule inhibitor of Janus kinase 1 and Janus kinase 2, has demonstrated efficacy in myelofibrosis patients with 300 mg, once-daily dosing. This open-label, nonrandomized, phase 1/2 study evaluated the safety and therapeutic benefit of momelotinib with twice-daily dosing. A total of 61 subjects with primary myelofibrosis or post–polycythemia vera/post–essential thrombocythemia myelofibrosis with intermediate- or high-risk disease received momelotinib. A phase 1 dose escalation identified 200 mg twice daily as the optimal dose to be expanded in phase 2. The most frequent adverse events were diarrhea (45.9%), peripheral neuropathy (44.3%), thrombocytopenia (39.3%), and dizziness (36.1%), the latter primarily due to a first-dose effect. The response assessment according to the 2006 International Working Group criteria (≥8 weeks duration at any time point) demonstrated spleen response by palpation of 72% (36/50) and anemia response of 45% (18/40). Spleen response by magnetic resonance imaging obtained at 24 weeks was 45.8% (27/59) for all subjects and 54.0% (27/50) for those with palpable splenomegaly at baseline. The symptoms of myelofibrosis were improved in most subjects. Cytokine analysis showed a rapid decline in interleukin-6 with momelotinib treatment, and a slower reduction in other inflammatory cytokines. In the subgroup of subjects with the JAK2V617F mutation at baseline (n=41), momelotinib significantly reduced the allele burden by 21.1% (median) at 24 weeks. These results provide evidence of tolerability and a potential therapeutic activity of momelotinib for subjects that support further evaluation in ongoing, phase 3 randomized trials. (clinicaltrials. gov identifier:01423058).

Introduction ©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

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Primary myelofibrosis (PMF) is a chronic myeloproliferative neoplasm that originates at the level of the hematopoietic stem cell and is characterized by cytopenias, extramedullary hematopoiesis, megakaryocytic hyperplasia, marrow fibrosis, and systemic symptoms resulting from elevated levels of inflammatory and proangiogenic cytokines. A form of myelofibrosis, indistinguishable from PMF, can occur as part of the natural history of polycythemia vera (PV) and essential thrombocythemia (ET), referred to as post–PV myelofibrosis and post–ET myelofibrosis, respectively. The discovery of the JAK2V617F mutation contributed to the understanding of the role of the dysregulated Janus kinase-signal transducer and activator haematologica | 2017; 102(1)


Momelotinib in twice-daily dosing for myelofibrosis

of transcription (JAK-STAT) pathway in myeloproliferative neoplasm, and paved the way for the development of small-molecule inhibitors of JAK1/2. The first-in-class JAK1/2 inhibitor ruxolitinib has been approved for myelofibrosis and is effective in the reduction of splenomegaly as well as the myelofibrosis-related symptom burden; however, anemia and thrombocytopenia are significant hematologic toxicities.1,2 Momelotinib (formerly known as CYT387) is a smallmolecule, adenosine triphosphate-competitive inhibitor of JAK1 and JAK2. Kinase profiling of momelotinib indicated that this molecule has good selectivity over other JAK family kinases (JAK3, tyrosine kinase 2) and excellent selectivity over other tyrosine and serine/threonine kinases.3 Momelotinib has previously been evaluated in a phase 1/2 study in myelofibrosis patients (study CCL09101; clinicaltrials. gov identifier:00935987), in which the dose was escalated from a 100-mg once-daily (QD) capsule to a maximum of 400 mg QD.4 In that study, the maximum tolerated dose (MTD) was determined to be 300 mg QD, and the 400-mg QD dose met the definition of dose-limiting toxicity (DLT). Both the 150-mg QD and 300-mg QD doses demonstrated clinical responses and were expanded where both doses showed similar spleen responses.4 A dose expansion at 150 mg twice daily (BID) demonstrated similar efficacy and safety to the 150 mg QD dose and the MTD of 300 mg QD.5 This study was undertaken to investigate the possibility that additional therapeutic benefit may be achieved with a BID regimen with higher doses; therefore, further dose escalation was carried out in the current study. The use of a BID regimen was supported by the half-life of momelotinib, which ranged from 4 to 6 hours in the previous study.6 The primary objectives of this study were to determine the safety, tolerability, and pharmacokinetics (PK) of momelotinib for the BID dosing regimen, as well as to obtain information on the effectiveness of this dosing schema. The intention was to review the results from this study and those from the previous phase 1/2 study in order to select the appropriate dose for phase 3 trials.

Methods Patient eligibility criteria

Subjects ≥18 years of age with PMF or post–ET/PV myelofibrosis diagnosis according to the revised World Health Organization criteria7 were eligible for enrollment if they had high-risk, intermediate-2 risk, or intermediate-1 risk myelofibrosis (defined by the International Prognostic Scoring System [IPSS]8) associated with symptomatic splenomegaly/hepatomegaly and/or were unresponsive to available therapy. Other eligibility criteria included life expectancy ≥12 weeks, Eastern Cooperative Oncology Group performance status ≤2, absolute neutrophil count ≥0.5×109/L, platelet count ≥50×109/L, and acceptable organ function within 7 days of initiating momelotinib. A washout period of 14 days was required for any previous systemic therapy. Key exclusion criteria were grade ≥2 peripheral neuropathy, acute active infection, or intercurrent illness that would jeopardize safety or compliance.

Study design This multicenter, open-label phase 1/2 study (clinicaltrials. gov identifier:01423058) consisted of a dose-escalation phase (Part 1) to identify DLTs and/or MTD of momelotinib BID, and a dose-confirmation phase (Part 2), which was a cohort expansion at or haematologica | 2017; 102(1)

below the MTD. In Part 1, the first cohort received 200 mg BID (doses approximately 12 hours apart) for a 28-day cycle. Higher dosing cohorts were initiated if ≤2 DLTs were experienced per 6 subjects in cycle 1 and following a review of the toxicity and efficacy of the lower dose. In Part 2, subjects were to receive the MTD or a lower dose shown to have significant clinical activity. Subjects in both phases were evaluated for 6 cycles. The study was approved by the institutional research and ethics boards of all of the participating institutions and was conducted in accordance with the principles of the Declaration of Helsinki.

Assessments The primary safety endpoint was to determine the safety profile and MTD of momelotinib. Safety assessments included the characterization of DLTs, treatment-emergent adverse events (TEAEs), and adverse events (AEs) incidence and severity. The primary efficacy endpoint was the therapeutic response rate as defined by the number of subjects achieving complete remission, partial remission, or clinical improvement according to the 2006 International Working Group for Myeloproliferative Neoplasms Research and Treatment criteria (IWG-MRT).9 Spleen response by palpation: ≥50% decrease from baseline in palpable spleen length for baseline splenomegaly ≥10 cm that lasted ≥8 weeks, or resolution of palpable splenomegaly for baseline splenomegaly >5 cm and <10 cm that lasted ≥8 weeks. Spleen response by magnetic resonance imaging (MRI): ≥35% reduction in spleen volume from baseline and, for the subgroup who had palpable splenomegaly, >5 cm below the left costal margin at baseline. Anemia response: no red blood cell (RBC) transfusions for ≥8 weeks for transfusion-dependent subjects, or ≥2 g/dL increase in hemoglobin lasting ≥8 weeks for transfusion-independent subjects who had hemoglobin <10 g/dL at baseline. RBC transfusiondependence was defined as ≥2 RBC units in the 30 days prior to the first dose of momelotinib. Two post hoc analyses were performed using a 12-week endpoint: one with the same transfusiondependence definition as the 8-week analysis, and the other using a stricter definition for transfusion-dependence at baseline (i.e., 6 RBC units within the 12 weeks prior to the first dose with ≥1 unit administered in the 28 days prior to the first dose). Myelofibrosis symptoms response: ≥50% reduction in total symptom score (TSS) using the Myelofibrosis Symptom Assessment Form lasting ≥12 weeks. TSS was defined as the sum of the scores for constitutional symptoms. See the Online Supplementary Methodology Information for the list. For details of pharmacology and JAK2V617F allele burden analyses, see the Online Supplementary Methodology Information.

Results A total of 61 subjects were enrolled between September 21, 2011, and July 30, 2012, and received at least one dose of momelotinib. Subject disposition and baseline characteristics are shown in Figure 1 and Table 1, respectively. The safety analysis and modified intention-to-treat analysis comprised of 61 and 60 subjects, respectively. Overall, 45 subjects (73.8%) completed at least six 28-day cycles of momelotinib BID treatment; 22 subjects continued until study closure in June 2014, at which time they were enrolled in an open-label maintenance study (clinicaltrials. gov identifier:02124746). Overall, 39 subjects discontinued, and the median duration of exposure to the study drug was 382 days (range 2–995 days) for the total safety cohort. The most common reason for study discontinua95


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tion was AEs, which occurred in 16 subjects (26.2%), followed by progressive disease (9 subjects [14.6%]) and subject withdrawal (8 subjects [13.1%] (Figure 1). Seven subjects (11.5%) died during the course of the study. None of the deaths were considered related to the study drug.

Cytokine release syndrome or withdrawal effect Among the 39 subjects (64%) who discontinued the study drug prior to the end of the study, there were no reported cases of cytokine release syndrome or withdrawal effect.

Hematologic toxicities Safety analysis Dose-escalation phase In Part 1 of the study, 6 subjects were enrolled at the 200 mg BID dose level and 7 subjects were enrolled at the next dose level of 250 mg BID. Although no protocoldefined DLTs were identified, all but 1 of the 7 subjects at the 250 mg BID dose level required treatment interruptions, resulting in dose reductions in 5 subjects (4 due to thrombocytopenia and 1 due to elevated lipase) and 1 discontinuation (due to dysesthesia and skin rash). Therefore, the safety review committee designated 200 mg BID as the dose level for expansion, and an additional 48 subjects were enrolled at this dose level.

Toxicities All 61 subjects experienced at least one AE, with 58 subjects (95.1%) having events related to the study drug as determined by the investigator. A total of 33 subjects (54.1%) experienced at least one serious AE (SAE), with 14 subjects (23.0%) reporting a treatment-related SAE.

Nonhematologic toxicities The most frequently reported nonhematologic TEAEs, regardless of drug attribution, were diarrhea (28 subjects, 45.9%), peripheral neuropathy (27 subjects, 44.3%), dizziness (22 subjects, 36.1%), and hypotension (15 subjects, 24.6%). These TEAEs are summarized in Figure 2A and Online Supplementary Table S1.

First-dose hypotension/dizziness A total of 27 subjects (44.3%) reported 1 or more AE(s) after the first dose—primarily hypotension, dizziness, and/or lightheadedness (14 subjects each, 23.0%; all grade 1). The majority of these AEs lasted ≤1 hour, with 86.3% resolving prior to the subject leaving the clinic. There was a mean decline of systolic blood pressure of 13 mm Hg and 15 mm Hg at 1 and 2 hours post-dose, respectively. Systolic blood pressure returned to baseline within 12 to 24 hours without intervention. None of these events led to hospital admissions or discontinuation of the drug.

Peripheral neuropathy Peripheral neuropathy was observed in 27 subjects (44.3%) and was mainly reported as sensory in nature. Neuropathy events were classified as grade 1 (n=10), grade 2 (n=15), and grade 3 (n=2). The median time to neuropathy onset was 227 days (range: 6–785 days). For the two grade 3 neuropathy events, 1 subject discontinued treatment on day 221; the other subject had a drug interruption on day 702 (due to a grade 3 hand neuropathy that resolved without sequelae) and resumed treatment on day 785. Overall, 5 subjects discontinued from the study because of symptoms of peripheral neuropathy. As the study generally captured only the highest reported grade of neuropathy and did not follow subjects beyond a day 30 safety visit, the reversibility of neuropathy could not be determined. 96

Thrombocytopenia was observed in 24 study subjects (39.3%) (Figure 2B and Online Supplementary Table S2), with 18 (29.5%) experiencing grade ≥3 toxicity. Thrombocytopenia was more common in subjects receiving the 250 mg BID dose (5/7 subjects; 71.4%) than the Table 1. Baseline demographics and characteristics.

Characteristic

200 mg BID 250 mg BID N=54 N=7

Age, median (range), years 72 (48-86) 60 (50-75) Sex, male, n (%) 33 (61.1) 5 (71.4) Diagnosis, n (%) Primary MF 37 (68.5) 6 (85.7) Post–PV MF 7 (13.0) 1 (14.3) Post–ET MF 10 (18.5) 0 Baseline Eastern Cooperative Oncology Group status, n (%) 0 9 (16.7) 1 (14.3) 1 41 (75.9) 6 (85.7) 2 4 (7.4) 0 IPSS Low-risk* 2 (3.7) 1 (14.3) Intermediate—I 5 (9.3) 0 Intermediate—II 21 (38.9) 3 (42.9) High-risk 26 (48.1) 3 (42.9) Cytogenetics at screening, n (%) Normal 21 (38.9) 5 (71.4) Abnormal 26 (48.1) 1 (14.3) Not available 7 (13.0) 1 (14.3) Prior therapy, n (%)† 41 (75.9) 4 (57.1) Hydroxycarbamide 20 (37.0) 2 (28.6) Prednisone 10 (18.5) 1 (14.3) Investigational drug‡ 9 (16.7) 2 (28.6) Erythropoietin 8 (14.8) 1 (14.3) Pomalidomide 7 (13.0) 1 (14.3) Thalidomide 6 (11.1) 2 (28.6) Lenalidomide 6 (11.1) 1 (14.3) Spleen size by palpation, 12.0 16.0 median cm Spleen volume by MRI, 2056.45 2444.00 median cm3 Transfusion-dependent, n (%)§ 25 (46.3) 4 (57.1) Hb <10 g/dL, n (%) 36 (66.7) 5 (71.4) Hb, median g/dL 9.1 9.7 Platelet count, ×109/L, median 177 201 Absolute neutrophil count, 5.69 8.45 × 109/L, median Hb for transfusion-independent 10.1 13.3 subjects, median g/dL

Total N=61 71 (48-86) 38 (62.3) 43 (70.5) 8 (13.1) 10 (16.4) 10 (16.4) 47 (77.0) 4 (6.6) 3 (4.9) 5 (8.2) 24 (39.3) 29 (47.5) 26 (42.6) 27 (44.3) 8 (13.1) 45 (73.8) 22 (36.1) 11 (18.0) 11 (18.0) 9 (14.8) 8 (13.1) 8 (13.1) 7 (11.5) 12.5 2069.90 29 (47.5) 41 (67.2) 9.3 179 5.73 10.3

*IPSS electronic case report form stated to enter the IPSS at diagnosis; IPSS at the time of enrollment was intermediate or higher. †Therapies listed were used in >10% subjects. Other prior therapies included ruxolitinib (n=5), anagrelide, danazol, darbepoetin alfa, histone deacetylase, fluoxymesterone, imatinib mesylate, interferon, panobinostat, peginterferon alfa-2a, peginterferon alfa-2b, sodium phosphate (32P), and tipifarnib. ‡Investigational therapies included non-ruxolitinib Janus kinase (JAK) inhibitors (n=8), anti–lysyl oxidase-like 2 antibody, hedgehog pathway inhibitor, and gemifloxacin. §Baseline transfusion-dependent subjects were defined as subjects who had at least 2 units of red blood cell (RBC) transfusions within 30 days prior to cycle 1, day 1. BID: twice daily; ET: essential thrombocythemia; Hb: hemoglobin; IPSS: International Prognostic Scoring System; MF: myelofibrosis; MRI: magnetic resonance imaging; PV: polycythemia vera.

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Figure 1. Subject disposition. *2 subjects with loss of response, 1 proceeded to bone marrow transplant, 1 lack of efficacy. BID: twice daily; mITT: modified intention-to-treat.

200 mg BID dose (19/53 subjects; 35.2%). Although no subject discontinued the study due to thrombocytopenia, there were 3 SAEs of grade 4 thrombocytopenia reported as related to momelotinib, all of which were resolved with drug interruption. Two bleeding events were associated with platelet counts of <50×109/L; one was a fatal intracranial bleed in a subject who had a baseline platelet count of 50×109/L, which declined to 37×109/L.

Efficacy evaluation IWG-MRT response Overall, 35 subjects (58.4%) showed a therapeutic response (clinical improvement: 34/60, 56.7%; partial remission 1/60, 1.7%) by investigator assessment during the study as per the 2006 IWG-MRT criteria. No subjects achieved a complete remission. Stable disease was seen in 21 subjects (35%).

Pharmacokinetics PK profiles were evaluated for 24 subjects from the 200 mg BID group and 7 subjects from the 250 mg BID group. Momelotinib concentrations peaked at around 2 hours post-dose for both the 200 mg and 250 mg BID cohorts. Momelotinib exposures were higher at the 250 mg BID dose than at the 200 mg BID dose (14% to 25% increase in maximum plasma concentration and 33% to 36% increase in the area under the curve; Table 2).

Spleen response Clinical improvement in splenomegaly was demonstrated using both palpation and MRI methods of measuring spleens (Figure 3). Only subjects who had an enlarged spleen at baseline demonstrated a spleen response by MRI. Of the 59 subjects with spleens who underwent a baseline MRI, 38 (64.4%) underwent repeat MRIs at 24 weeks, and 27 (45.8%) demonstrated a ≥35% reduction in

Table 2. Pharmacokinetic parameters of momelotinib following single and multiple doses.

Mean (%CV) Single-dose PK parameter Cmax (ng/mL) AUC0-last (ng·h/mL) Tmax (h)* Multiple-dose PK parameter† Cmax (ng/mL) AUCtau (ng·h/mL) Tmax (h)*

200 mg BID N=24

250 mg BID N=7

342.9 (37.9) 1360.1 (30.1) 2.00 (1.59, 2.14) N=13-21‡ 505.0 (61.3) 3095.6 (56.3) 2.00 (1.00, 2.08)

391.5 (66.7) 1815.3 (65.5) 2.00 (1.00, 2.08) N=3-4‡ 629.9 (37.0) 4217.8 (40.5) 2.00 (1.50, 2.07)

AUC0-last: area under the concentration versus time curve to the last quantifiable concentration; AUCtau: area under the plasma concentration versus time curve over the dosing interval; BID: twice daily; %CV: percent coefficient of variation; Cmax: maximum observed plasma concentration; PK: pharmacokinetics; Tmax: time at maximum concentration. *Median (range). †Multiple-dose parameters were measured after 28 days of momelotinib administration. ‡Number of subjects differed for different pharmacokinetic parameters.

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spleen volume. Of the 50 subjects with baseline palpable splenomegaly >5 cm who underwent a baseline MRI, 27 (54.0%) demonstrated a ≥35% reduction in spleen volume (Table 3). Subjects who missed the 24-week MRI for any reason were classified as treatment failures. Spleen volume by MRI correlated with palpable spleen at the MRI designated time points, with the correlation coefficient ranging from 0.56 to 0.80. Anemia response. Subjects demonstrating an 8-week anemia response had either a transfusion-independent response (subjects who were transfusion-dependent at baseline) or a hemoglobin response (subjects who were transfusion-independent with hemoglobin <10 g/dL at baseline). Of the 29 subjects (48.3%) classified as transfusion-dependent at baseline, 15 (51.7%) achieved 8-week transfusion independence. Of the 11 baseline transfusionindependent subjects with a baseline hemoglobin <10 g/dL, 3 subjects (27.3%) had a rise in hemoglobin ≥2 g/dL lasting ≥8 weeks, for an overall anemia response seen in 18/40 subjects (45%; Table 3). A careful review of medications received prior to trial entry was done by the study authors (VG, SV, and CER) to ensure that these responses were not attributable to the discontinuation of myelosuppressive medications received prior to trial entry. Due to intervening changes in the accepted definitions of anemia response after the study had completed enrollment, a first post hoc evaluation of anemia response was performed using a 12-week rolling endpoint. The 12-week rolling anemia response was 25% (10/40), composed of a 31% (9/29) 12-week, transfusion-independent response com-

bined with a 9% (1/11) hemoglobin response. A second post hoc anemia response evaluation defined transfusiondependent subjects at baseline more stringently, as subjects who required at least 6 units of blood in the 12 weeks prior to the first dose and at least 1 of those units in the 28 days prior to study day 1. Using this stricter definition of transfusion dependence at baseline, the number of transfusion-dependent subjects decreased to 19, and the 12week transfusion response in this heavily transfusiondependent group was 21.1% (4/19 subjects; Table 3). While the 12-week response rates were lower than the 8week response rates, the 12-week responses were more durable (Table 3).

Secondary efficacy endpoints Overall, treatment with momelotinib resulted in a reduction of hepatomegaly and an improvement in almost all constitutional symptoms experienced by subjects at baseline (Table 3). Approximately one-third of subjects reported either a complete response (absence of symptoms [score=0]) or marked response (≥50% reduction in score from baseline) of their TSS at the 3-month or 6month visit, and responses were durable up to the 24month visit. Progression-free survival and overall survival at 2 years were 74% (95% confidence interval [CI] 58–85) and 88% (95% CI 75–95), respectively. In the 39 subjects who had both a baseline and an onstudy bone marrow evaluation, fibrosis improved in 11 subjects (9 subjects improved by 1 grade, 1 subject

A

B

Figure 2. (A) Nonhematologic treatment-emergent adverse events (>10% of total subjects) across all momelotinib dose levels. (B) Hematologic treatment-emergent adverse events (>10% of total subjects) across all momelotinib dose levels.

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Table 3. Overall therapeutic response to momelotinib (modified intention-to-treat (mITT) population).

Therapeutic response

Result

Received at least 1 dose of momelotinib and underwent at least 1 evaluation for response 60 (100%) Spleen response Spleen response by physical examination Baseline palpable spleen >5 cm 50 (83.3%) ≥50% reduction in palpable splenomegaly that lasted ≥8 weeks for baseline splenomegaly ≥10 cm: A (n=41) 28 (68.3%) Resolution of palpable splenomegaly that lasts ≥8 weeks for baseline splenomegaly >5 and <10 cm: B (n=9) 8 (88.9%) Spleen response: A + B 36 (72.0%) Median time to onset of spleen response (min, max) (n=36) 49.5 days (13,512) Median duration of spleen response (min, max) (n=36) 249.5 days (71, 976) Spleen response by MRI Baseline MRI 59 ≥35% reduction in spleen volume by MRI at 24 weeks 27 (45.8%) Baseline MRI of patients with palpable splenomegaly at baseline (>5 cm) 50 ≥35% reduction in spleen volume by MRI at 24 weeks 27 (56.2%) Anemia response 2006 IWG-MRT–based anemia Transfusion-dependent at baseline (≥2 units RBC transfusion in 30 days prior to the first dose of momelotinib) 29 (48.3%) Transfusion-independent with Hb <10 g/dL at baseline 11 (18.3%) 8-week response Achieved transfusion independence ≥8 weeks: A (n=29) 15 (51.7%) Median time to onset of transfusion independence (min, max) (n=15) 30 days (1, 250) Median duration of transfusion independence (min, max) (n=15) 85 days (56, 967) Rise in Hb ≥2 g/dL for ≥8 weeks: B (n=11) 3 (27.3%) Median duration of Hb response (min, max) 75 days (57, 113) Overall 8-week anemia response A + B (A + B/40) 18 (45%) 2013 IWG-MRT–based transfusion response Transfusion-dependent at baseline (≥6 units RBC transfusion in the 12 weeks prior to the first dose 19 (31.1) of momelotinib and the most recent transfusion ≤28 days) 12-week transfusion response Achieved transfusion independence ≥12 weeks: C (n=19) 4 (21.1%) Median time to onset of transfusion independence (min, max) (n=4) 58.5 days (1, 250) Median duration of transfusion independence (min, max) (n=4) 250 days (86, 967) Rise in Hb ≥2 g/dL for ≥12 weeks: D (n=11) 1 (9.1%) Duration of response 113 days Overall 12-week anemia response C + D (N=30) 5 (16.7%) Liver size reduction Baseline liver volume 2420 cm3 Mean reduction in liver volume at 24 weeks (n=38 subjects who underwent scans at baseline and 24 weeks) 161 cm3 Constitutional symptoms (MF-SAF) Patients with ≥50% Best response for patients with baseline symptom and at least 1 follow-up assessment decrease in baseline (%) Itching (n=25) 25 (100) Night sweats (n=35) 32 (91.4) Weight loss in last 6 months (n=27) 24 (88.9) Abdominal pain (n=29) 26 (89.7) Fever (>100°F) (n=11) 10 (90.9) Abdominal discomfort (n=39) 33 (84.6) Depression or sad mood (n=37) 31 (83.8) Bone pain (n=30) 25 (83.3) Headaches (n=23) 19 (82.6) Cough (n=29) 23 (79.3) Problems with sexual desire or function (n=32) 23 (71.9) Difficulty sleeping (n=39) 28 (71.8) Early satiety (n=48) 34 (70.8) Problems with concentration (n=37) 26 (70.3) Relations with other people (n=37) 26 (70.3) Dizziness/vertigo/lightheadedness (n=29) 20 (69.0) Mood (n=42) 28 (66.7) Fatigue (n=54) 34 (63.0) Inactivity (n=40) 25 (62.5) Enjoyment of life (n=41) 25 (61.0) Worst fatigue of previous 24 h (n=54) 32 (59.3) TSS: ≥50% decrease in baseline at 6 months (n=39) 12 (30.8) Bone marrow fibrosis response in subjects with fibrosis at baseline, n=39* No change 25 (64.1) Improvement 11 (28.2) Worsened 3 (8.0) Cytogenetic response in subjects with abnormal cytogenetics at baseline, n=27, and post-baseline assessment, n=14 No change 13 (50.0) Partial response (≥50% reduction in abnormal metaphases) 1 (13.3) JAK2V617F allele burden response in subjects with JAK2V617F mutation at baseline, n=41 Median decrease in allele burden (range) at week 12 (n=21) 16.6% (–100, 51) (P=0.0063) Median decrease in allele burden (range) at week 24 (n=18) 21.1% (–52, 64) (P=0.0019) *Post-baseline bone marrow fibrosis results were acquired after the baseline visit either on or before the last study visit and excluded post-treatment follow-up visits. Hb: hemoglobin; IWG-MRT: International Working Group for Myeloproliferative Neoplasm Research and Treatment; JAK: Janus kinase; MF-SAF: Myelofibrosis Symptom Assessment Form; MRI: magnetic resonance imaging; RBC: red blood cell; TSS: total symptom score.

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Figure 3. Spleen response showing percentage reduction from baseline in spleen volume by magnetic resonance imaging (MRI) for subjects with palpable splenomegaly at baseline (n=50). Baseline subjects included all subjects with spleens (n=59). At week 24, 38 subjects underwent MRI. Missed MRIs were due to adverse events (AEs) (9 subjects), withdrawal (5 subjects), missed appointments (4 subjects), progressive disease (2 subjects), and lost to follow-up (1 subject). Dashed red line indicates reduction of 35% from baseline.

improved by 2 grades, and 1 subject had complete resolution of a grade 3 fibrosis). In 3 subjects, fibrosis worsened by 1 grade. Eight of these 11 subjects also showed a clinical improvement according to IWG-MRT criteria. In the study population, 41 subjects (68%) were positive for JAK2V617F at study entry. The median JAK2V617F allele burden significantly declined from baseline by 16.6% at week 12 (P=0.0063), and by 21.1% at week 24 (P=0.0019; Table 3, Figure 4). A complete molecular response was achieved by one subject whose JAK2V617F allele burden decreased from a baseline level of 26.4% to undetectable at week 12 and week 16, when the subject went off study.

Cytokine assessments Blood samples were collected pre-dose, at 6 and 24 hours post–first dose, and at weeks 8 and 20 for exploratory assessments of the effect of momelotinib on cytokines. At baseline, epidermal growth factor, transforming growth factor beta (TGF-β), and vascular endothelial growth factor-A (VEGF-A) were positively correlated with each other, as were tumor necrosis factor-alpha (TNF-a), insulin-like growth factor binding protein-1, and TNF receptor type II (TNFRII) (Spearman correlation coefficients >0.5; data not shown). Additional positive correlations were observed between interleukin (IL)-6 and C-reactive protein (CRP), and between IL-6 and IL-10 (Spearman correlation coefficients >0.5; data not shown). By week 8, CRP, erythropoietin, IL-6, IL-10, IL-12p40, TNFRII, and TNF-a were significantly decreased; all of these except erythropoietin remained low to week 20 (Figure 5). IL-6 showed the most rapid response, with a reduction of 30.3% within 6 hours after the first dose of momelotinib.

Discussion This phase 1/2 study was designed to evaluate the safety and tolerability, to determine DLTs, MTD, and PK, and to obtain preliminary efficacy results of BID momelotinib in subjects with PMF or post–PV/ET myelofibrosis. BID 100

Figure 4. JAK2V617F allele burden. Plot shows baseline levels (n=41) and individual trajectories of allele burden to week 24 (n=18). BL: baseline; W24: week 24.

dosing allowed for testing a higher total daily dose of momelotinib than QD dosing. No additional safety signals were observed at the higher doses. The discontinuation rate (59%) reflects, in part, the prolonged study duration for subjects and the wider availability of alternative treatment options during the conduct of the study, including ruxolitinib as a marketed therapy, and an increase in myelofibrosis clinical trials. It is important to note that the majority of subjects (73.8%) did successfully complete the first 6 cycles of treatment with momelotinib. It is difficult to compare discontinuation rates with previously reported studies of ruxolitinib and other JAK inhibitors because ruxolitinib studies enrolled JAK-naïve subjects, whereas this trial included 21% of subjects previously treated with JAK inhibitors. Direct comparisons can be truly assessed only in a head-to-head trial. The most common AEs observed were diarrhea, peripheral neuropathy, thrombohaematologica | 2017; 102(1)


Momelotinib in twice-daily dosing for myelofibrosis

Figure 5. Heat map showing median percentage change in cytokine levels at each time point relative to pre-dose. Green and red represent decreased and increased levels from baseline, respectively. Changes from baseline tested using Wilcoxon signed-rank test. P values are indicated for median percent changes ≥10%: *0.01-0.05; †0.001-0.01; ‡<0.001. CRP: C-reactive protein; IGFBP1: insulin-like growth factor binding protein 1; IL: interleukin; IL-12P70: interleukin-12 subunit P70; RANK: receptor activator of nuclear factor kappa B; TGF-β: transforming growth factor beta; TNF-a: tumor necrosis factor alpha; TNFRII: tumor necrosis factor receptor type II; VEGFA: vascular endothelial growth factor A; lL-12P40: interleukin-12 subunit P40.

cytopenia, and dizziness. The dizziness was primarily associated with a first-dose effect—sometimes associated with low-grade hypotension and flushing—and these events were generally grade 1 and self-limiting. This firstdose effect appeared to be more common with momelotinib than has been reported in other JAK inhibitors,1,2,10,11 but did not lead to dose interruption or study discontinuation. Diarrhea was reported in 45.9% of subjects, with 31.1% reporting the diarrhea to be drug-related, although these events were generally grade 1 and self-limiting (23.0% were grade 1 and 8.2% were grade 2). Overall, the AE profile was favorable for continuing the evaluation of momelotinib as treatment for myelofibrosis. The evaluation of the frequency and severity of thrombocytopenia was partly confounded by existing thrombocytopenia in some subjects at baseline. Thrombocytopenia was also dose-dependent, and a higher frequency of grade 3/4 thrombocytopenia was seen in subjects treated with the 250 mg BID dose of momelotinib, and appeared to be reversible upon drug interruption. Peripheral sensory neuropathy was a frequent nonhematologic toxicity observed in this trial. The incidence (44%, with the onset at a median of 32 weeks) was similar to that reported in a prior momelotinib phase 1/2 study.12 However, in the aforementioned prior study a significant number of subjects (49%) had already reported numbness and tingling at baseline in the Myelofibrosis Symptom Assessment Form. In the present study, grade 2 neuropathy was reported in 24% of subjects, and 2 subjects (3.3%) reported grade 3 neuropathy; this is higher than the rates observed in the previous momelotinib study, where a lower total daily dose of momelotinib was used.12 Five subjects discontinued therapy due to neuropathy, although the reversibility of peripheral neuropathy could not be determined because of the study design. The mechanism by which momelotinib might contribute to sensory neuropathy has not been identified. One should therefore haematologica | 2017; 102(1)

remain vigilant about neurologic complications, as the development of three JAK inhibitors (XL019 [Exelixis, South San Francisco, CA, USA], fedratinib [Sanofi Aventis, Gentilly, France], and AZD1480 [AstraZeneca, London, UK]) have been halted due to neurologic complications primarily affecting the central nervous system.10,13,14 Spleen response rate by MRI at 24 weeks was similar to that which has been described for the JAK1/2 inhibitor ruxolitinib.1,2 Additionally, momelotinib demonstrated evidence of improvement in clinically important, anemiarelated endpoints of transfusion independence and increased hemoglobin, using both 8-week criteria and the more clinically relevant 12-week criteria. A potential mechanism of the anemia benefit observed with momelotinib has been hypothesized to be due to the targeting of ACVR1/ALK-2, a key mediator in the hepcidin/inflammation pathway.15 If supported with further data, this characteristic could distinguish momelotinib compared with other JAK inhibitors. Data from ongoing, blinded, randomized trials with prespecified, anemia-related endpoints are anticipated in the near future. Baseline cytokines were consistent with the inflammatory nature of myelofibrosis. Momelotinib treatment resulted in a rapid decrease in the inflammatory cytokine IL-6, with slower decreases in other inflammatory cytokines. After prolonged treatment, erythropoietin was increased relative to baseline. These changes are similar to those reported with the JAK1/2 inhibitor ruxolitinib.1 The current results provide evidence that momelotinib has therapeutic activity in the majority of subjects with myelofibrosis, as evidenced by the reduction of splenomegaly, improvements in anemia-related endpoints, and symptom response. This study confirms the findings of a previously conducted phase 1/2 study4 in a multicenter setting, and the results of these two studies helped in the selection of the dose used for phase 3 trials. 101


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Momelotinib is now under phase 3 evaluation for treatment of myelofibrosis in two ongoing randomized trials. Acknowledgments The authors thank Impact Communication Partners, Inc., for editorial assistance in preparing the manuscript.

References 1. Harrison C, Kiladjian JJ, Al-Ali HK, et al. JAK inhibition with ruxolitinib versus best available therapy for myelofibrosis. N Engl J Med. 2012;366(9):787-798. 2. Verstovsek S, Mesa RA, Gotlib J, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. 2012;366(9):799-807. 3. Hรถfener M, Pachl F, Kuster B, Sewald N. Inhibitor-based affinity probes for the investigation of JAK signaling pathways. Proteomics. 2015;15(17):3066-3074. 4. Pardanani A, Laborde RR, Lasho TL, et al. Safety and efficacy of CYT387, a JAK1 and JAK2 inhibitor, in myelofibrosis. Leukemia. 2013;27(6):1322-1327. 5. Pardanani A, Gotlib J, Gupta V, et al. Update on the long-term efficacy and safety of momelotinib, a JAK1 and JAK2 inhibitor, for the treatment of myelofibrosis. Blood. 2013;122(21):108. 6. Xin Y, Shao L, Jun S, et al. The relative bioavailability, food effect and drug interaction with omeprazole of momelotinib (GS0387, CYT387) tablet formulation in healthy

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8.

9.

10.

Funding This study was supported by Gilead Sciences, Inc. Previously presented in part at the European Hematology Association Meeting, Milan, Italy, June 2014. Cytokine data were presented at the American Society of Hematology Meeting, Orlando, FL, USA, December 2015.

subjects. Presented at: American Association of Pharmaceutical Scientists; November 2-6, 2014; San Diego, CA. Abstract M1320. Tefferi A, Thiele J, Orazi A, et al. Proposals and rationale for revision of the World Health Organization diagnostic criteria for polycythemia vera, essential thrombocythemia, and primary myelofibrosis: recommendations from an ad hoc international expert panel. Blood. 2007;110(4):10921097. Cervantes F, Dupriez B, Pereira A, et al. New prognostic scoring system for primary myelofibrosis based on a study of the International Working Group for Myelofibrosis Research and Treatment. Blood. 2009;113(13):2895-2901. Tefferi A, Barosi G, Mesa RA, et al. International Working Group (IWG) consensus criteria for treatment response in myelofibrosis with myeloid metaplasia, for the IWG for Myelofibrosis Research and Treatment (IWG-MRT). Blood. 2006;108(5): 1497-1503. Verstovsek S, Hoffman R, Mascarenhas J, et al. A phase I, open-label, multi-center study of the JAK2 inhibitor AZD1480 in patients

11.

12.

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with myelofibrosis. Leukemia Res. 2015; 39(2):157-163. Komrokji RS, Seymour JF, Roberts AW, et al. Results of a phase 2 study of pacritinib (SB1518), a JAK2/JAK2(V617F) inhibitor, in patients with myelofibrosis. Blood. 2015;125(17):2649-2655. Abdelrahman RA, Begna KH, Al-Kali A, et al. Momelotinib treatment-emergent neuropathy: prevalence, risk factors and outcome in 100 patients with myelofibrosis. Br J Haematol. 2015;169(1):77-80. Verstovsek S, Tam CS, Wadleigh M, et al. Phase I evaluation of XL019, an oral, potent, and selective JAK2 inhibitor. Leuk Res. 2014;38(3):316-322. Pardanani A, Harrison C, Cortes JE, et al. Safety and efficacy of fedratinib in patients with primary or secondary myelofibrosis: a randomized clinical trial. JAMA Oncol. 2015;1(5):643-651. Asshoff M, Warr M, Haschka D, et al. The Jak1/Jak2 inhibitor momelotinib inhibits Alk2, decreases hepcidin production and ameliorates anemia of chronic disease (ACD) in rodents. Blood. 2015;126 (23):538.

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ARTICLE

Myeloproliferative Disorders

Risk of thrombosis according to need of phlebotomies in patients with polycythemia vera treated with hydroxyurea

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Alberto Alvarez-Larrán,1 Manuel Pérez-Encinas,2 Francisca Ferrer-Marín,3 Juan Carlos Hernández-Boluda,4 María José Ramírez,5 Joaquín Martínez-López,6 Elena Magro,7 Yasmina Cruz,1 María Isabel Mata,8 Pilar Aragües,9 María Laura Fox,10 Beatriz Cuevas,11 Sara Montesdeoca,1 José Angel Hernández-Rivas,12 Valentín García-Gutiérrez,13 María Teresa Gómez-Casares,14 Juan Luis Steegmann,15 María Antonia Durán,16 Montse Gómez,4 Ana Kerguelen,17 Abelardo Bárez,18 Mari Carmen García,19 Concepción Boqué,20 José María Raya,21 Clara Martínez,22 Manuel Albors,23 Francesc García,1 Carmen Burgaleta,7 Carlos Besses1 and the Grupo Español de Neoplasias Mieloproliferativas Filadelfia Negativas

Hospital del Mar, IMIM, UAB, Barcelona; 2Hospital Clínico, Santiago de Compostela; Hospital Morales-Messeguer, IMIB, UCAM, Murcia; 4Hospital Clínico, Valencia; 5Hospital de Jerez, Jerez de la Frontera; 6Hospital 12 de Octubre, Madrid; 7Hospital Príncipe de Asturias, Alcalá de Henares; 8Hospital de la Costa del Sol, Marbella; 9Hospital de Cruces, Bilbao; 10Hospital Vall d’Hebron, Barcelona; 11Hospital de Burgos, Burgos; 12Hospital Infanta Leonor, Madrid; 13Hospital Ramón y Cajal, Madrid; 14Hospital Dr Negrín, Las Palmas de Gran Canaria; 15Hospital Universitario de la Princesa, Madrid; 16Hospital Son Espases, Palma de Mallorca; 17Hospital La Paz, Madrid; 18Complejo assistencial de Avila, Avila; 19Hospital General de Alicante; 20Hospital Duran i Reinals, Institut Català d’Oncologia, Hospitalet de Llobregat; 21Hospital Universitario de Canarias, Santa Cruz de Tenerife; 22Hospital de Sant Pau, Barcelona and 23Complexo Hospitalario Universitario de Ourense; on behalf of the Grupo Español de Enfermedades Mieloproliferativas Filadelfia Negativas

1

3

ABSTRACT

H

ematocrit control below 45% is associated with a lower rate of thrombosis in polycythemia vera. In patients receiving hydroxyurea, this target can be achieved with hydroxyurea alone or with the combination of hydroxyurea plus phlebotomies. However, the clinical implications of phlebotomy requirement under hydroxyurea therapy are unknown. The aim of this study was to evaluate the need for additional phlebotomies during the first five years of hydroxyurea therapy in 533 patients with polycythemia vera. Patients requiring 3 or more phlebotomies per year (n=85, 16%) showed a worse hematocrit control than those requiring 2 or less phlebotomies per year (n=448, 84%). There were no significant differences between the two study groups regarding leukocyte and platelet counts. Patients requiring 3 or more phlebotomies per year received significantly higher doses of hydroxyurea than the remaining patients. A significant higher rate of thrombosis was found in patients treated with hydroxyurea plus 3 or more phlebotomies per year compared to hydroxyurea with 0-2 phlebotomies per year (20.5% vs. 5.3% at 3 years; P<0.0001). In multivariate analysis, independent risk factors for thrombosis were phlebotomy dependency (HR: 3.3, 95%CI: 1.5-6.9; P=0.002) and thrombosis at diagnosis (HR: 4.7, 95%CI: 2.3-9.8; P<0.0001). The proportion of patients fulfilling the European LeukemiaNet criteria of resistance/intolerance to hydroxyurea was significantly higher in the group requiring 3 or more phlebotomies per year (18.7% vs. 7.1%; P=0.001) mainly due to extrahematologic toxicity. In conclusion, phlebotomy requirement under hydroxyurea therapy identifies a subset of patients with increased proliferation of polycythemia vera and higher risk of thrombosis. haematologica | 2017; 102(1)

Haematologica 2017 Volume 102(1):103-109

Correspondence: 95967@parcdesalutmar.cat

Received: July 15, 2016. Accepted: September 22, 2016. Pre-published: September 29, 2016. doi:10.3324/haematol.2016.152769

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/103

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is required for any other use.

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Introduction Polycythemia vera (PV) is a myeloproliferative neoplasm characterized by a high rate of thrombosis and bleeding.1,2 In the majority of patients, the disease is caused by the acquisition of mutations in the JAK2 gene resulting in an increased red cell mass and, frequently, in concomitant leukocytosis and thrombocytosis.3 The hyperviscosity resulting from red cell expansion has a central role in the pathogenesis of thrombosis in PV, whereas functional abnormalities of platelets and leukocytes have more recently been proposed as potential contributing factors.4-6 Control of symptoms and prevention of thrombosis and bleeding are the main objectives of treatment in PV.7 In order to achieve this, management with phlebotomies (PHL) and/or cytoreductive therapy is adopted according to risk of thrombosis and patient characteristics. When cytoreduction is indicated, hydroxyurea (HU) is the firstline therapy most commonly employed. Patients receiving HU are targeted to maintain the hematocrit (Hct) below 45%, since Hct control below 45% has been associated with a lower rate of thrombosis in both observational studies and randomized clinical trials.4,8 However, in daily clinical practice, a proportion of patients cannot adequate-

A

ly control the Hct with HU alone due to treatment sideeffects or lack of response, and therefore require the concomitant use of PHL to achieve this. The aim of the present study was to assess if PV patients treated with HU requiring frequent PHL have the same risk of thrombosis than those managed mainly with HU alone.

Methods Study design The Spanish Registry of Polycythemia Vera is a 'real-life' observational study which, by February 2016, included 1353 patients for whom baseline characteristics, therapies and complications during follow up are periodically up-dated. From this cohort, a total of 533 patients treated with HU with available data regarding hematologic values, PHL requirements, and HU dose were included for the present study. All patients included in the study were diagnosed after year 2000. In every case, the diagnosis of PV was reassessed using the criteria of the World Health Organization.9 The indication of HU was decided according to the criterion of the attending hematologist on the basis of the clinical guidelines and prevailing recommendations at that time. The treatment objective was to achieve Hct control below 45% without the need for PHL

B

HU with 3 or more PHL per year

C

HU with 3 or more PHL per year

HU with 0-2 PHL per year

D

HU with 0-2 PHL per year

HU with 3 or more PHL per year

HU with 0-2 PHL per year

Figure 1. Hematocrit, leukocyte and platelet counts under hydroxyurea (HU) therapy. (A) Hematocrit in the whole cohort of patients. (B) Hematocrit in the two study groups (month 6, P<0.001; month 12, P=0.003; month 18, P=0.03; month 24, P=0.007; month 36, P=0.007; month 48, P<0.0001; month 60, P=0.1). (C) Leukocyte count in the two study groups (P=not significant). (D) Platelet count in the two study groups (P=not significant). 25th, 50th (median) and 75th percentiles are shown. HU: hydroxyurea; PHL: phlebotomies.

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Hydroxyurea plus phlebotomies in polycythemia vera

to achieve this, HU dose titration was performed according to individual clinical practice and patient characteristics. Supplemental PHL were performed in those patients in whom the Hct was not controlled with Hu alone. In general, the policy of the different centers was to increase the HU dose to achieve Hct control reserving PHL as a complementary therapy. The study was approved by the Ethics Committee of the Hospital del Mar, Spain. Informed consent for the inclusion in the registry and the scientific use of the patients’ clinico-hematologic data was obtained in accordance with the requirements of the local ethics committees. Data from the first 60 months of therapy with HU were retrospectively recovered. Hematocrit, leukocyte count, platelet count, number of PHL, and dose of HU were assessed at months 6, 12, 18, 24, 36, 48 and 60 of HU therapy. The requirement of PHL in each patient was calculated as the total number of PHL/time of follow up and expressed as the number of PHL per year. Hematocrit response was defined as Hct less than 45%, regardless of any prior use of PHL. Complete hematologic response (CHR) was defined as the presence of Hct less than 45%, leukocyte count less than 10x109/L and platelet count less than 400 x109. Months in Hct response or in CHR were calculated taken into consideration the response status at the different time points. Time in response was calculated as months in response / total months of follow up x100 and expressed as percentage of follow up in response. Sustained response was defined as a response lasting more than 50% of the follow-up period. Intermittent response was defined as a response lasting less than 50% of follow-up period. The occurrence of resistance/intolerance to HU was recorded in those patients fulfilling at least one of the European LeukemiaNet (ELN) criteria.10 Different definitions of PHL requirement (> 2 PHL per year, > 3 PHL per year, and > 4 PHL per year) were explored for any possible association with the rate of thrombosis. Requirement of 3 or more PHL was selected to categorize the study groups due to its prognostic value and for its clinical relevance, since patients requiring 3 or more PHL per year require PHL at the majority of visits. The primary outcome of the study was time to first thrombotic event from HU start. Study duration was 60 months after HU start. Patients were censored at last visit, at time of HU discontin-

uation, or at 60 months if they completed the study period. Secondary end points included probability of bleeding (major or minor) while on treatment with HU, Hct response, CHR, and probability of resistance/intolerance to HU. Thrombosis was defined according to the International Classification of Diseases (9th revision) including superficial thrombophlebitis. Severe hemorrhage was defined as a symptomatic bleeding in a critical organ or an overt hemorrhage requiring transfusion or associated with an Hb decrease of more than 20 g/L without transfusion. Time-to-event curves were drawn up by the Kaplan-Meier method with the log-rank test for comparisons. Multivariate analysis was performed by Cox regression. All statistical analyses were performed with SPSS, v.22.

Results Patients’ characteristics, treatment and response Baseline characteristics at time of HU start are shown in Table 1. Median interval between PV diagnosis and HU start was 35 days, with 75% of patients starting on HU within the first year after diagnosis. Reasons for initiating HU were: age over 60 years n=334 (62.7%), previous thrombosis n=81 (15.2%), extreme thrombocytosis n=45 (8.4%), microvascular symptoms n=26 (4.9%), bleeding n=5 (0.9%), other n=20 (3.8%), not determined n=22 (4.1%). Median follow up under HU therapy was 36 months (range 6-60 months). Median starting dose of HU was 5 g per week (range 1-14 g). Complete data regarding antiplatelet and anticoagulant therapy were available in 448 and 516 patients, respectively, with 358 (80%) patients having received antiplatelet therapy and 48 (9%) anticoagulation therapy while on treatment with HU. There were no statistically significant differences in the proportion of patients receiving antiplatelet therapy or oral anticoagulants among the two study groups. The majority of patients achieved a stable Hct less than 45% during the study period (Figure 1A). Overall, 304 (57%) patients required one or more PHL at any time dur-

Table 1. Main clinical and hematologic characteristics at time of hydroxyurea start in 533 patients with polycythemia vera.

Age, years* Sex, male/female History of thrombosis previous to PV diagnosis Thrombosis at PV diagnosis Cardiovascular risk factors Microvascular symptoms Pruritus Palpable spleen Hematocrit, %* Leukocyte count, x109/L* Platelet count, x109/L* JAK2V617F allele burden¶

Total N=533

HU with ≥3 PHL per year N=85

HU with 0-2 PHL per year N=448

P

69 (18-96) 285/248 126 (24) 45 (8) 394 (74) 186 (35) 170 (32) 86 (16) 52 (29-74) 11.3 (3.5-56) 555 (106-1661) 44 (1-100)

65 (22-92) 52/33 18 (21) 7 (8) 66 (78) 29 (34) 32 (38) 19 (22) 55 (43-70) 12.2 (3.6-29) 536 (106-1383) 45 (12-100)

70 (18-96) 233/215 108 (24) 38 (8) 328 (73) 157 (35) 138 (31) 67 (15) 51 (29-74) 11.2 (3.5-56) 560 (129-1661) 44 (1-100)

0.02 0.1 0.6 0.9 0.4 0.9 0.2 0.1 <0.0001 0.1 0.9 0.6

*At time of hydroxyurea start: median (range). ¶Available in 278 patients. N: number; HU: hydroxyurea; PHL: phlebotomies; PV: polycythemia vera.

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ing the study. A total of 85 (16%) patients received 3 or more PHL per year (median 4, range 3-23). The remaining patients were included in the HU with 0-2 PHL per year group, in which the PHL requirements were significantly lower (median number of PHL per year 0, range 0-2). PHL requirements during follow up in the two study groups are shown in Table 2. The group of patients requiring 3 or more PHL per year had an inadequate Hct control, with the Hct levels being significantly higher than those requiring 0-2 PHL per year (Figure 1B). Leukocyte counts were slightly higher in the HU with 3 and more PHL patients, but the differences were not statistically significant (Figure 1C). Regarding platelet counts, both groups of patients presented similar values, mostly within the normal range (Figure 1D). Hematocrit response and CHR at any time point was achieved in 69% and 55% of patients, respectively. However, only 51% and 34% of the total patients had a sustained response in hematocrit and CHR, respectively. Hematocrit response and CHR at different time points in the two study groups are shown in Table 2. The proportion of patients achieving either Hct response or CHR was significantly lower in the group of patients requiring HU and 3 or more PHL per year. Patients requiring 3 or more PHL per year were treated with significantly higher doses of HU than the remainder. There was a trend to a progressive increase of the HU dose through follow up in patients with frequent PHL requirements (Table 2). A total of 108 (20%) patients stopped HU during the study period. Reported reasons for discontinuation were:

toxicity n=63, absence of response n=11, bleeding n=4, myeloid transformation n=1, chemotherapy for second neoplasia n= 4, other n=13, not available n=12. Resistance/intolerance to HU according to ELN criteria was observed in 51 (10%) patients. The proportion of patients fulfilling each of the definition criteria were: need for PHL despite 2 g/day of HU n=8 (1.5%), uncontrolled myeloproliferation n=3 (0.6%), failure to reduce massive splenomegaly n=0, cytopenia at the lowest dose of HU to achieve a response n=6 (1.1%), extrahematologic toxicity n=35 (6.6%). The 3-year probability of resistance/intolerance to HU was significantly higher in patients requiring 3 or more PHL per year than in those with 0-2 PHL per year (18.7% vs. 7.1%; P=0.001) (Figure 2).

Thrombosis and bleeding A total of 36 thrombotic events (22 arterial, 14 venous) were recorded resulting in a 3- and 5-year probability of thrombosis of 6.9% and 11%, respectively. Type of thrombotic events according to study groups are shown in Table 3. The probability of thrombosis was significantly higher in patients treated with HU and 3 or more PHL per year than in those treated with HU and 0-2 PHL per year (20.5% vs. 5.3% at 3 years; P<0.0001) (Figure 3). Hematocrit response and CHR status at month 6, 12, 18, 24, 36, 48 or 60 was not associated with a different rate of thrombosis. Patients with sustained hematocrit response or sustained CHR experienced similar rate of thrombosis than those with intermittent or absence of response. Other variables associated with a higher or a tendency

Table 2. Frequency of hematocrit response, complete hematologic response, number of phlebotomies and hydroxyurea dose at different time points of treatment according to phlebotomy requirement in polycythemia vera.

Hematocrit response HU > 3 PHL per year HU 0-2 PHL per year P CHR HU > 3 PHL per year HU 0-2 PHL per year P N. of phlebotomies** HU > 3 PHL per year HU 0-2 PHL per year P HU dose* HU > 3 PHL per year HU 0-2 PHL per year P

Month of therapy with HU 24

6

12

18

n=469 23/79 (29%) 204/390 (52%) <0.0001 n=477 9/73 (12%) 150/404 (37%) <0.0001

n=387 17/49 (35%) 201/338 (59%) 0.002 n=399 9/47 (19%) 146/352 (41%) 0.004

n=350 11/39 (28%) 178/311 (57%) 0.001 n=367 7/39 (18%) 120/328 (37%) 0.021

3 (0-11) 0 (0-8) <0.0001 n=497 6.2 (5.7-6.7) 5.4 (5.2-5.5) 0.001

2 (0-12) 0 (0-7) <0.0001 n=413 6.6 (5.9-7.3) 5.4 (5.2-5.6) <0.0001

2 (0-8) 0 (0-4) <0.0001 n=370 6.2 (5.4-7) 5.6 (5.4-5.9) 0.1

36

48

60

n=304 7/32 (22%) 145/272 (53%) 0.001 n=319 6/32 (19%) 105/287 (37%) 0.05

n=258 5/22 (23%) 132/236 (56%) 0.003 n=272 3/22 (14%) 98/250 (39%) 0.02

n=206 3/16 (19%) 117/190 (62%) 0.001 n=216 2/16 (12.5%) 78/200 (39%) 0.06

n=181 4/13 (31%) 99/168 (59%) 0.08 n=188 2/13 (15%) 73/175 (42%) 0.08

2 (0-8) 0 (0-4) <0.0001 n=318 6.3 (5.5-7.2) 5.6 (5.3-5.8) 0.07

3 (0-16) 0 (0-4) <0.0001 n=274 7.1 (5.9-8.4) 5.7 (5.4-5.9) 0.003

4 (0-12) 0 (0-4) <0.0001 n=216 6.1 (4.6-7.6) 5.7 (5.4-6) 0.5

2 (0-10) 0 (0-4) 0.01 n=184 7.5 (5.9-9.2) 5.8 (5.5-6.2) 0.01

HU: hydroxyurea; PHL: phlebotomies; CHR: complete hematologic response; N: number. Hematocrit response and CHR are provided as number of patients in response/total number of patients and percentage. *Grams (g) per week as mean [95% confidence interval (CI)]. **Median (range) number of phlebotomies performed since the previous time point.

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Hydroxyurea plus phlebotomies in polycythemia vera

towards a higher probability of thrombosis were: male sex (P=0.05), presence of either diabetes mellitus, active smoking, arterial hypertension or hypercholesterolemia (P=0.06), thrombosis prior to PV diagnosis (P=0.07), thrombosis at PV diagnosis (P<0.0001), and leukocyte count at time of HU start more than 10x109/L (P=0.09). Age and platelet count at time of HU start were not associated with a higher probability of thrombosis. Multivariate analysis including sex, cardiovascular risk factors, thrombosis at PV diagnosis and need for PHL is shown in Table 4. Patients treated with HU and 3 or more PHL per year had a 3.3 fold increase (95%CI: 1.5-6.9) in the risk of thrombosis. In addition, patients with thrombosis at PV diagnosis showed the highest risk of developing thrombosis under HU therapy. When sustained hematocrit response or sustained CHR were included in the multivariate model, PHL requirement retained its prognostic value while hematocrit response or CHR were not associated with the risk of thrombosis. Twenty-five bleeding events (6 major, 19 minor) were registered, resulting in a 3- and 5-year probability of 4.4% and 6.7%, respectively. The 3-year probability of bleeding was higher in the group of patients requiring 3 or more PHL per year than in the remaining patients, but the difference was not statistically significant (7.4% vs. 4.2%, respectively; P=0.4) (Figure 4). In multivariate analysis, therapy with HU and 3 or more PHL per year was not associated with a higher risk of bleeding (HR: 5.5, 95%CI: 0.55.1; P=0.4) after adjusting for treatment with antiplatelet agents or oral anticoagulants.

Discussion Hydroxyurea is the cytoreductive therapy most often used in PV. However, few studies have evaluated in detail the optimal management of this agent in clinical practice. In particular, no studies have examined whether the need of PHL under treatment with HU has any impact on the

major complications of the disease. In the present study, we have shown that patients with PV treated with HU requiring 3 or more PHL per year have an increased risk of thrombosis and more frequently develop resistance/intolerance to HU. According to current recommendations, PV patients under cytoreduction are targeted to maintain the Hct less than 45%.7,11 In this regard, most patients in the present study were able to keep the hematocrit below 45%, with the values observed being superimposable on to those reported in the higher intensity group of the CytoPV study.8 Moreover, our cohort of patients received HU dosages that were comparable or even higher than those previously reported by others.8,12 However, we identified a subgroup of patients requiring a higher intensity of treatment consisting of both higher HU doses and higher number of PHL. These patients, representing 16% of the total series, experienced a higher rate of thrombosis and, on multivariate analysis, PHL requirement while on HU therapy was an independent risk factor for thrombosis. This finding emphasizes the importance of an adequate HU Table 3. Type of thrombotic events under therapy with hydroxyurea according to phlebotomy requirements.

Arterial thrombosis Stroke/TIA Coronary artery disease Peripheral artery disease Venous thrombosis DVT/PE Superficial thrombophlebitis Espleno-portal

HU with â&#x2030;Ľ3 PHL per year N=85

HU with 0-2 PHL per year N=448

5 (5.9) 4 (4.7) 1 (1.2) 5 (5.9) 2 (2.3) 2 (2.3) 1 (1.2)

17 (3.8) 9 (2) 2 (0.4) 6 (1.3) 9 (2) 6 (1.3) 2 (0.4) 1 (0.2)

Results are given as number of events (%). HU: hydroxyurea; PHL: phlebotomies; N: number; TIA: transient ischemic attack; DVT/PE: deep vein thrombosis/pulmonary embolism.

% %

Figure 2. Time to resistance/intolerance to hydroxyurea according to European LeukemiaNet (ELN) criteria in patients with polycythemia vera treated with hydroxyurea (HU) and 3 or more phlebotomies per year (solid line) or with HU and 0-2 phlebotomies per year (dotted line). P=0.0001.

haematologica | 2017; 102(1)

Figure 3. Time to thrombosis in patients with polycythemia vera treated with hydroxyurea (HU) and 3 or more phlebotomies per year (solid line) or with HU and 0-2 phlebotomies per year (dotted line). P<0.0001.

107


A.A. Larrรกn et al. Table 4. Multivariate analysis of factors predicting thrombosis in 533 patients with polycythemia vera treated with hydroxyurea. Male sex Cardiovascular risk factors Thrombosis at PV diagnosis HU with 3 or more PHL per year

%

Figure 4. Time to bleeding (major or minor) in patients with polycythemia vera treated with hydroxyurea (HU) and 3 or more phlebotomies per year (solid line) or with HU and 0-2 phlebotomies per year (dotted line) (P=0.4).

dose adjustment to maintain the Hct below 45% without significant fluctuations. Alternatively, if HU dose cannot be increased, more frequent PHL or change to second-line therapy is advised. It could be argued that the need for PHL could result from a lower intensity of cytoreductive treatment. In our series, however, the situation was just the opposite since patients with high PHL requirements received significantly higher doses of HU than those treated with HU alone. This finding suggests that this subgroup of patients have a disease with an increased proliferative capacity requiring a higher treatment intensity to achieve Hct control. This is supported by the observation that the hematocrit values prior to HU start were also significantly higher in the group of patients treated with HU and 3 or more PHL per year. An alternative explanation could be a lower individual sensitivity to treatment with HU that could result in poorer control of the disease when conventional doses of HU are used. Although up to 16% of patients required 3 or more PHL per year to control the disease, the majority of these patients could not be classified as resistant to HU since the dose intensity of 2 g per day was not reached. In fact, only 1.5% of patients met the Hct resistance criterion defined by ELN as reported in previous studies.12,13 Nevertheless, a higher rate of resistance/intolerance to HU was observed in patients requiring 3 or more PHL per year mainly due to more frequent extrahematologic toxicity; this could be explained by the higher HU doses employed in the group requiring supplemental PHL. These features illustrate how difficult it is to apply ELN resistance criteria in daily clinical practice. In this regard, the concept of maximum tolerated dose of HU to maintain the Hct below 45% instead of a dose 2 g or more per day may be more appropriate when evaluating whether a patient is resistant to HU.14 An intriguing finding of the present work was the absence of a clear association between the Hct response

108

HR

95%CI

P

0.5 2.2 4.7 3.3

0.25-1.1 0.8-5.6 2.3-9.8 1.5-6.9

0.08 0.1 <0.0001 0.002

HR: hazard ratio; 95%CI: 95% confidence intervals; PV: polycythemia vera; HU: hydroxyurea; PHL: phlebotomies.

and the risk of thrombosis. This does not in any way mean that patients should not be controlled according to the well-established criteria of response. In fact, patients treated with HU plus 3 or more PHL per year had poorer hematocrit control throughout the study and, therefore, a lower response rate. However, classification of patients based on the PHL requirement seems to better discriminate those patients at high risk of thrombosis than the categorization of responders/non-responders. Although our results suggest that the thrombotic risk of patients requiring frequent PHL is related to an inadequate Hct control, a detrimental effect of frequent phlebotomies PHL should still be taken into consideration. On the other hand, we have observed no significant differences in the leukocyte and platelet counts during treatment with HU between the two study groups, suggesting a predominant role of the increased red cell mass in the thrombotic risk of PV. The main limitation of the present study is its retrospective design. The absence of a protocol that includes a standardized titration of the HU dose or the indication for PHL can result in significant bias that could affect the validity of the observed findings. On the other hand, the definition of study groups according to requirement of 3 or more PHL per year may also be criticized. The only way to solve these biases would be to conduct a prospective study with a pre-established definition of study groups, including a precise protocol of both dose titration and indication for PHL. Despite the aforementioned limitations, the detailed analysis of the treatment received by patients included in registries such as the present one is an excellent opportunity to evaluate and improve clinical practice in a 'real-life' scenario, which is often difficult to carry out within clinical trials. In conclusion, PV patients treated with HU requiring 3 or more PHL per year have a higher risk of thrombotic complications. These findings highlight the importance of timely dose adjustment adapted to the proliferative activity of the disease. Acknowledgments We are indebted to all members of GEMFIN participating in the Spanish Registry of Polycythemia Vera. Funding This work was supported by a grant from the Instituto de Salud Carlos III, Spanish Health Ministry, PI13/00557, PI1300393. The GEMFIN received a grant from Novartis for the development of the Spanish Registry of Polycythemia Vera and for conducting the present project.

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Hydroxyurea plus phlebotomies in polycythemia vera

References 1. Gruppo Italiano Studio Policitemia. Polycythemia vera: the natural history of 1213 patients followed for 20 years. Gruppo Italiano Studio Policitemia. Ann Intern Med. 1995;123(9):656-664. 2. Marchioli R, Finazzi G, Landolfi R, et al. Vascular and neoplastic risk in a large cohort of patients with polycythemia vera. J Clin Oncol. 2005;23(10):2224-2232. 3. James C, Ugo V, Le Couedic JP, et al. A unique clonal JAK2 mutation leading to constitutive signalling causes polycythaemia vera. Nature. 2005; 434(7037): 1144-1148. 4. Pearson TC, Wetherley-Mein G. Vascular occlusive episodes and venous hematocrit in primary proliferative polycythaemia. Lancet. 1978;2(8102):1219-1222. 5. Landolfi R, Di Gennaro L, Barbui T, et al. Leukocytosis as a major thrombotic risk factor in patients with polycythemia vera. Blood. 2007;109(6):2446-2452.

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6. Cervantes F, Arellano-Rodrigo E, AlvarezLarrรกn A. Blood cell activation in myeloproliferative neoplasms. Haematologica. 2009; 94(11):1484-1488. 7. Barbui T, Barosi G, Birgegard G, et al. Philadelphia-negative classical myeloproliferative neoplasms: critical concepts and management recommendations from European LeukemiaNet. J Clin Oncol. 2011;29(6):761-770. 8. Marchioli R, Finazzi G, Specchia G, et al. Cardiovascular events and intensity of treatment in polycythemia vera. N Engl J Med. 2013;368(1):22-33. 9. Tefferi A, Thiele J, Orazi A, et al. Proposals and rationale for revision of the World Health Organization diagnostic criteria for polycythemia vera, essential thrombocythemia, and primary myelofibrosis: recommendations from an ad hoc international expert panel. Blood. 2007;110(4):10921097. 10. Barosi G, Birgegard G, Finazzi G, et al. A unified definition of clinical resistance and

11. 12.

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intolerance to hydroxycarbamide in polycythaemia vera and primary myelofibrosis: results of a European LeukemiaNet (ELN) consensus process. Br J Haematol. 2010; 148(6):961-963. Spivak JL. Polycythemia vera: myths, mechanisms, and management. Blood. 2002;100(13):4272-4290. Alvarez-Larrรกn A, Pereira A, Cervantes F, et al. Assessment and prognostic value of the European LeukemiaNet criteria for clinicohematologic response, resistance, and intolerance to hydroxyurea in polycythemia vera. Blood. 2012;119(6):1363-1369. Alvarez-Larrรกn A, Kerguelen A, Hernรกndez-Boluda JC, et al. Frequency and prognostic value of resistance/intolerance to hydroxyurea in 890 patients with polycythemia vera. Br J Haematol. 2016;172 (5):786-793. McMullin MF, Wilkins BS, Harrison CN. Management of polycythaemia vera: a critical review of current data. Br J Haematol. 2016;172(3):337-349.

109


ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Acute Myeloid Leukemia

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):110-117

Pre-transplantation minimal residual disease with cytogenetic and molecular diagnostic features improves risk stratification in acute myeloid leukemia

BetĂźl Oran,1 Jeff L. Jorgensen,2 David Marin,1 Sa Wang,2 Sairah Ahmed,1 Amin M. Alousi,1 Borje S. Andersson,1 Qaiser Bashir,1 Roland Bassett,3 Genevieve Lyons,3 Julianne Chen,1 Katy Rezvani,1 Uday Popat,1 Partow Kebriaei,1 Keyur Patel,2 Gabriela Rondon,1 Elizabeth J. Shpall1 and Richard E. Champlin1 Department of Stem Cell Transplantation and Cellular Therapy; 2Department of Hematopathology and 3Department Biostatistics, the University of Texas MD Anderson Cancer Center, Houston, TX, USA

1

ABSTRACT

O Correspondence: boran@mdanderson.org

Received: April 19, 2016. Accepted: August 18, 2016. Pre-published: August 18, 2016. doi:10.3324/haematol.2016.144253

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/110

Š2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to the Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. Permission in writing from the publisher is required for any other use.

110

ur aim was to improve outcome prediction after allogeneic hematopoietic stem cell transplantation in acute myeloid leukemia by combining cytogenetic and molecular data at diagnosis with minimal residual disease assessment by multicolor flow-cytometry at transplantation. Patients with acute myeloid leukemia in first complete remission in whom minimal residual disease was assessed at transplantation were included and categorized according to the European LeukemiaNet classification. The primary outcome was 1-year relapse incidence after transplantation. Of 152 patients eligible, 48 had minimal residual disease at the time of their transplant. Minimal residual disease-positive patients were older, required more therapy to achieve first remission, were more likely to have incomplete recovery of blood counts and had more adverse risk features by cytogenetics. Relapse incidence at 1 year was higher in patients with minimal residual disease (32.6% versus 14.4%, P=0.002). Leukemiafree survival (43.6% versus 64%, P=0.007) and overall survival (48.8% versus 66.9%, P=0.008) rates were also inferior in patients with minimal residual disease. In multivariable analysis, minimal residual disease status at transplantation independently predicted 1-year relapse incidence, identifying a subgroup of intermediate-risk patients, according to the European LeukemiaNet classification, with a particularly poor outcome. Assessment of minimal residual disease at transplantation in combination with cytogenetic and molecular findings provides powerful independent prognostic information in acute myeloid leukemia, lending support to the incorporation of minimal residual disease detection to refine risk stratification and develop a more individualized approach during hematopoietic stem cell transplantation.

Introduction Disease relapse is the most common cause of treatment failure after allogeneic hematopoietic stem cell transplantation (HCT) for acute myeloid leukemia (AML).1 In most series, the median time to relapse after HCT is 4-6 months,2,3 suggesting that identifying patients with a higher risk of relapse early after HCT is important to tailor transplant and post-transplant management strategies with an aim to reduce the relapse incidence (RI).4 Cytogenetic and molecular abnormalities detected at diagnosis are important prognostic factors for RI, leukemia-free survival (LFS) and overall survival (OS).5-7 Specific gene abnormalities, such as mutations in FLT3 and NPM1 genes, allow subsets of patients with distinct treatment outcomes to be identified, even within homogeneous cytogenetic groups.8-10 The current standard framework for risk stratification guiding transplant practice in AML has, therefore, been largely based on cytogenetics and a panel of molecular genetic markers, couhaematologica | 2017; 102(1)


MRD at HCT by cytogenetic/molecular risk groups

pled with morphological assessment of bone marrow response to chemotherapy. Recent studies assessing minimal residual disease (MRD) have highlighted the limitations of morphology for reliable determination of remission status and several studies have shown that MRD status independently predicts disease relapse after antileukemia treatment.11-14 Multiparametric flow cytometry (MFC) has been successfully used to quantify MRD in AML expressing leukemia-associated phenotypes.13,15 Previous studies have demonstrated that MRD detectable by MFC is a powerful, independent predictor of subsequent relapse and shorter survival for AML patients in complete remission and can be used to risk-stratify both younger and older patients after chemotherapy and following HCT.16-19 Based on these findings, it is conceivable that outcome prediction after HCT in AML could be improved by a combination of standard prognostic factors, such as cytogenetic and molecular data, with MRD assessment by MFC. In the present study, we analyzed a large group of consecutive AML patients undergoing HCT in first morphological remission (CR1) for whom cytogenetics, molecular data at diagnosis and MRD assessment by MFC at HCT were available. We aimed to evaluate whether the combination of these determinants would help to optimize risk stratification for relapse in patients with AML undergoing HCT in CR1.

Methods Study cohort At our institution, eight-color flow cytometry analysis from bone marrow samples has been part of the standard pre-transplant work-up in AML patients since September 2012. Of 169 consecutive adult AML patients who underwent allogeneic HCT in CR1 from September 2012 through March 2015, 152 (90%) had MFC performed on bone marrow aspirates preceding allogeneic HCT and they were included in the current analyses. Patients were categorized by the European LeukemiaNet (ELN) classification incorporating both cytogenetic and selected molecular abnormalities at diagnosis, separating AML patients into four distinct genetic risk groups20-23 (Online Supplementary Table S1). All patients provided written informed consent to transplantation in accordance with the Declaration of Helsinki. The University of Texas MD Anderson Cancer Center institutional review board approved this retrospective analysis.

Flow cytometric immunophenotyping of minimal residual disease Eight-color flow cytometry analysis was performed using previously described methods.24,25 In brief, the panel included four tubes as follows: (i) CD7FITC, CD33 PE, CD19 PerCP-Cy5.5, CD34 PECy7, CD13 APC, CD38 BV421, CD45 V500; (ii) HLADR-FITC, CD117 PE, CD4 PerCP-Cy5.5, CD34 PE-Cy7, CD123 APC, CD19-eF780, CD38 BV421, CD45 V500; (iii) HLA-DR-FITC, CD36 PE, CD56 PerCP-Cy5.5, CD34 PE-Cy7, CD64 APC, CD19eF780, CD14 V450, CD45 V500; and (iv) CD5-FITC, CD2 PE, CD22 PerCP-Cy5.5, CD34 PE-Cy7, CD38 APC, CD19-eF780, CD15 V450, CD45 V500. All antibodies were obtained from Becton Dickinson (San Jose, CA; USA) or eBioscience (San Diego, CA, USA). Samples were acquired on FACSCanto II instruments (BD Biosciences, San Diego, CA, USA) that were standardized daily using CS&T beads. A minimum of 200,000 live events were acquired to achieve a potential sensitivity of at least 10-4 (0.01%). haematologica | 2017; 102(1)

MRD was defined as a neoplastic blast population with an abnormal pattern of antigen expression deviating from normal regenerating myeloid progenitors. The abnormal blast population was qualified as a percentage of total events. Any level of an abnormal blast population (≥0.01%) detected by MFC was considered MRD positive. The first sample aspirated was used for morphological preparations (smears and clot sections), and subsequent draws were sent for flow cytometric analysis and other ancillary testing. This may have affected the quality of some of the samples analyzed by MFC.

Disease characteristics, conditioning regimens and graft-versus-host disease prophylaxis We identified 152 patients in CR1 who had MRD by MFC assessment just prior to HCT. Cytogenetic and molecular data at diagnosis were evaluable for 140 of 152 patients for ELN classification. The clinical characteristics of the study population, donors, and transplants are summarized in Table 1. Donors were human leukocyte antigen (HLA)-identical siblings in 41 (27%) cases, HLA-matched unrelated in 75 (49.3%), mismatched unrelated in 5 (3.3%), haploidentical in 20 (13.2%) and cord blood in 11 (7.2%) cases. Mismatched unrelated, haploidentical and cord blood patients were analyzed together because of their small numbers. Sixty-four patients (42.1%) received a reduced intensity conditioning regimen which consisted of: (i) intravenous busulfan either at a dose calculated to target an average daily systemic exposure dose, represented by the area under the concentration versus time curve (AUC) of 4,000 mMol-min ±10%, or 100 mg/m2 with fludarabine 40 mg/m2 given for 4 days; or (ii) melphalan 100-140 mg/m2 as a single dose with fludarabine 40 mg/m2 given for 4 days. Eighty-eight patients (57.9%) received a myeloablative conditioning regimen consisting of intravenous busulfan either at a dose calculated to target an AUC of 5,000-6,000 mMolmin ±10%, or 130 mg/m2 in combination with fludarabine 40 mg/m2 given daily for 4 days (66 patients) or the same busulfan treatment in combination with fludarabine, 10 mg/m2. Tacrolimus and methotrexate were used as graft-versus-host disease prophylaxis in the majority of the patients (73.4%). The recipients of matched unrelated donor grafts and cord blood received rabbit anti-thymocyte globulin (Thymoglobulin, Genzyme, Cambridge, MA, USA) as a part of their conditioning regimen. Graft-versus-host disease prophylaxis for recipients of grafts from haploidentical and mismatched unrelated donors consisted of post-transplant cyclophosphamide, tacrolimus, and mycophenolate mofetil.26

Statistical analyses Outcomes analyzed included LFS, cumulative RI, transplantrelated mortality and OS. All outcomes were measured from the time of stem cell infusion. LFS was defined as survival without leukemia progression or relapse; patients alive without disease progression or relapse were censored at the time of last contact. OS was based on death from any cause. Surviving patients were censored at the time of last contact. Relapse was defined as leukemia recurrence at any site. LFS and OS were estimated using the Kaplan-Meier method. The probability of relapse was summarized using a cumulative incidence estimate. Non-relapse mortality was considered a competing risk for relapse. All outcomes were treated as time-to-event endpoints. Multivariate analysis was performed using Cox regression. Patients’ characteristics that were significant in the univariate models at the 0.10 level and clinically relevant were included in the multivariate model. Backward elim111


B. Oran et al.

ination was implemented until all remaining predictors had a Pvalue less than 0.05. Categorical characteristics were compared using the Fisher exact test, and continuous characteristics were compared with the two-sample t test. Statistical analyses were performed with STATA (StataCorp LP, College Station, TX, USA).

and incomplete count recovery (CRi/p) at HCT compared with 104 MRD-negative patients, as presented in Table 1. MRD-positive, intermediate-risk patients by ELN classification were also less likely to have mutated NPM1 compared with MRD-negative patients.

Results

Minimal residual disease-positive patients are more likely to relapse within 1 year after transplantation

The presence of minimal residual disease at transplantation is associated with poor-risk disease features The cohort with MRD at HSCT had high-risk features including older age, AML with adverse risk features by ELN, requirement of more lines of therapy to achieve CR1

Overall, the 1-year RI was higher among MRD-positive patients than among MRD-negative ones [32.6% versus 14.4%, respectively: hazard ratio (HR) =3.1, 95% confidence interval (CI): 1.5-6.5; P=0.002] (Figure 1A). Among patients who were MRD-positive at HCT, no significant effect of increasing levels of MRD was observed on RI, LFS or OS. This observation held true when MRD was evaluated as a continuous variable (on a log scale) and as a categorical variable using the quartiles of MRD in our

Table 1. Patient and disease characteristics.

MRD-negative, n=104 N. % Age, median, IQR 54 (40-61) Age >60 years 31 30 Sex Male 56 54 Female 48 46 t-AML 17 16 N. of lines of induction 1 86 83 â&#x2030;Ľ2 18 17 ELN risk group Favorable 12 12 Intermediate-I 33 32 Intermediate-II 28 27 Adverse 22 21 Adverse vs. others 22 21 FLT3 status (intermediate risk patients) Wild-type 27 49 Mutated 28 51 NPM1 status (CN patients) Wild-type 30 57 Mutated 23 43 Count recovery in CR1 CRi/p 10 10 CR w/count recovery 94 90 Time to HCT from diagnosis Median, days (IQR) 159 131-233 Conditioning intensity MAC 63 61 RIC 40 39 Source of stem cells Peripheral blood 56 54 Bone marrow 41 39 Cord blood 7 7 Donor MRD 28 27 MUD 52 51 MMUD 23 22 Follow-up after HCT, survivors Median, days 454 348-696

MRD-positive, n=48 N. %

P A

60 (51-67) 24

50

0.005 0.016

29 19 11

60 40 23

0.4 0.3

30 18

62 38

2 17 8 17 17

5 39 18 39 39

0.06

15 10

60 40

0.4

21 3

88 12

0.008

28 20

58 42

<0.001

190

152-323

0.01

24 24

50 50

27 17 4

56 35 9

12 23 13

25 48 27

531

346-757

0.006 0.2

B

C 0.2

0.9 0.8

0.5

MRD: minimal residual disease; IQR: interquartile range; t-AML: therapy-related AML; ELN: European LeukemiaNet; CN: normal cytogenetics; CR1: first complete remission; CRi/p: complete remission without count recovery; HCT: hematopoietic stem cell transplantation; MAC: myeloablative conditioning; RIC: reduced intensity conditioning; MRD: matched related donor; MUD: matched unrelated donor; MMUD: mismatched unrelated donor.

112

Figure 1. The presence of MRD using MFC at HCT increased (A) 1-year RI while it decreased (B) 1-year LFS (C) OS compared with those in MRD-negative patients at HCT.

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MRD at HCT by cytogenetic/molecular risk groups cohort as ≤0.3%, >0.3% to 1.3%, >1.3% to 2% (Online Supplementary Figure S1). Similarly, LFS and OS estimates at 1-year were inferior for patients who were MRD-positive at HCT compared with the MRD-negative group (Figure 1B,C). The cumulative incidence of non-relapse mortality at 1 year was 22% and there was no difference between MRD-negative and MRD-positive patients (P=0.97). Univariate analysis revealed that older age and adverse risk according to the ELN classification were other poor prognostic factors for 1-year RI, as presented in Table 2. There was no difference between intermediate-I and –II risk patients for 1-year RI (HR=0.5, 95% CI: 0.2-1.7; P=0.3) and none of the patients with a favorable risk according to the ELN classification relapsed at 1 year after HCT. Analyses for 1-year LFS and OS revealed that ELNdefined adverse risk, MRD at HCT, older age, CRi/p at HCT and use of reduced intensity conditioning were poor prognostic factors (Table 2). LFS and OS at 1 year were similar for intermediate-I and -II risk patients. The variables significant in univariate analysis and/or clinically relevant were forced into the multivariate regression model for 1-year RI. We added an interaction term for the MRD status at HCT and ELN risk categorization at

diagnosis into the model. Multivariate regressions confirmed the independent prognostic value of MRD at HCT, ELN-defined adverse risk and use of reduced intensity conditioning for 1-year RI, as presented in Table 3. The interaction term was also significant indicating that the effect of MRD on 1-year RI was different for different ELN-defined risk groups (P=0.013). Multivariate regression analysis for 1-year LFS and OS also revealed the independent prognostic impact of MRD at HCT, adverse risk according to the ELN classification and CRi/p at HCT (Table 3).

The presence of minimal residual disease at transplantation identifies a subgroup of intermediate-risk patients with poor prognosis for early relapse after transplantation MRD-negative and MRD-positive adverse risk patients had a high 1-year RI independently of their MRD status at HCT (31.6% versus 31.8% respectively, P=0.98) (Figure 2A). However, patients in the intermediate risk group had different prognoses depending on their MRD status at HCT. MRD-positive intermediate-I/II risk patients had a 1-year RI of 42.7% while MRD-negative intermediate-I/II risk patients had a 1-year RI of only 6.9% (P<0.001) (Figure 2B).

Table 2. Univariate regression analyses for the impact of prognostic factors on relapse incidence, leukemia-free survival and overall survival. Age (>60 vs. ≤60 years) t-AML (yes vs. no) Line of induction (>1 vs. 1) MRD-positive vs. MRD-negative Intermediate-II vs. intermediate-I (ELN) Favorable vs. intermediate-I (ELN) Adverse vs. intermediate-I/II (ELN) Adverse vs. others (ELN) CRi/p vs. CR w/count recovery Conditioning intensity Myeloablative Reduced intensity Donor Matched related Matched unrelated Mismatched

1-year RI 95% CI

P

HR

1-year TRM 95% CI

P

HR

1-year LFS 95% CI

P

HR

1-year OS 95% CI

P

1.03-4.4 0.95-4.6 0.98-4.4 1.5-6.5 0.2-1.7

0.04 0.07 0.057 0.002 0.3

0.9-4.2 1.1-5.0 0.8-3.6

0.08 0.03 0.2

1.5 1.5 0.7 1.01 0.9 1.1 1.4 1.4 2.2

0.8-3.1 0.7-3.3 0.3-1.7 0.5-2.2 0.4-2.5 0.3-4.3 0.6-3.1 0.6-3.0 1.1-4.4

0.2 0.3 0.4 0.97 0.9 0.9 0.4 0.4 0.03

2.0 1.9 1.3 2.0 1.4 0.7 1.8 1.9 2.2

1.2-3.4 1.1-3.4 0.7-2.2 1.2-3.5 0.6-2.9 0.2-2.3 1.04-3.1 1.1-3.3 1.3-3.7

0.005 0.02 0.4 0.007 0.4 0.5 0.035 0.002 0.003

2.1 1.6 1.3 2.1 1.3 0.7 1.7 1.8 2.6

1.2-3.6 0.9-2.9 0.7-2.4 1.2-3.5 0.6-2.8 0.2-2.6 0.9-3.0 1.005-3.2 1.5-4.4

0.006 0.1 0.3 0.008 0.5 0.6 0.08 0.048 0.001

1.0 1.8

0.8-3.7

0.1

1.0 1.7

0.9-3.4

0.1

1.0 1.9

1.1-3.1

0.01

1.0 1.7

1.01-2.9

0.045

1.0 0.8 0.7

0.3-1.8 0.2-1.9

0.6 0.5

1.0 1.5 3.1

0.5-4.2 1.1-8.8

0.4 0.03

1.0 1.0 1.6

0.5-2.0 0.8-3.1

0.9 0.2

1.0 1.2 1.9

0.6-2.4 0.9-4.1

0.6 0.08

HR 2.1 2.1 2.1 3.1 0.5 NE 2.0 2.3 1.7

RI: relapse incidence; TRM: transplant-related mortality; LFS: leukemia-free survival; OS: overall survival; HR: hazard ratio; CI: confidence interval; MRD: minimal residual disease; t-AML: therapy-related AML; ELN: European LeukemiaNet; CRi/p: complete remission without count recovery.

Table 3. Multivariate regression model for 1-year relapse incidence, leukemia-free survival and overall survival*.

CRi/p vs. CR w/count recovery MRD-positive vs. MRD-negative Adverse vs. others (ELN) RIC vs. MAC

HR

1-year RI 95% CI

P

6.4 6.7 2.4

1.9-21.4 2.1-21.7 1.1-5.6

0.003 0.001 0.03

HR

1-year LFS 95% CI

P

HR

1-year OS 95% CI

P

3.6 2.2 1.8

1.6-8.1 1.05-4.5 1.01-3.1

0.002 0.037 0.047

4.6 2.5

2.0-10.3 1.1-5.4

<0.001 0.02

RI: relapse incidence; LFS: leukemia-free survival; OS: overall survival; HR, hazards ratio; CI: confidence interval; MRD: minimal residual disease; t-AML: therapy-related AML; ELN: European LeukemiaNet; CRi/p: complete remission without count recovery; MAC: myeloablative conditioning; RIC: reduced intensity conditioning. *The variables included were age older than 60 years, t-AML, line of induction chemotherapy, MRD, risk groups according to ELN and conditioning intensity for RI. For leukemia-free-survival; age older than 60 years, t-AML, CRi/p, MRD, risk groups according to ELN and conditioning intensity were included. For overall survival, age older than 60 years, CRi/p, MRD and cytogenetics according to ELN were included.

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These results enabled us to identify two risk groups for 1-year RI: (i) a high-risk group with a 1-year RI of 36% including patients with adverse risk according to ELN criteria and those with intermediate-I/II risk who were MRD-positive; (ii) a lower risk group with a 1-year RI of 6.9% including intermediate-I/II risk, MRD-negative patients and favorable risk patients (Figure 3A). The favorable risk group that did not have any relapse at 1 year on follow-up was not included in this risk group classification. In the adverse risk group, the LFS rate at 1 year was 48.7% versus 31.4% (P=0.17) and OS was 58.4% versus 37.7% (P=0.16) in MRD-negative and MRD-positive patients, respectively; these differences in outcome expectation did not reach statistical significance. However, MRD-positive, intermediate-I/II risk patients had a significantly inferior 1-year LFS of 46.8% and 1-year OS of 47% compared with the 68.9% and 73.2%, respectively, observed in MRD-negative patients (P=0.02 and P=0.03). This difference, which was seen for LFS and OS, but not for RI can be explained by the fact that LFS and OS are composite outcomes taking into account not only RI but also transplant-related mortality. Therefore, other patient, disease- and transplant-related characteristics in addition to post-transplant relapse therapy might have an impact on LFS and OS. We then analyzed the impact of risk groups defined by

the ELN classification and MRD status at HCT on LFS and OS and found significantly different results for outcomes in high and low risk groups, similar to RI (Figure 3B,C).

Intermediate-risk minimal residual disease-negative patients who harbor the FLT3-ITD mutation enjoy a lower risk of relapse after transplantation Intermediate risk patients with mutated FLT3-internal tandem duplication (FLT3-ITDmut) who were MRD-negative at HCT had a lower 1-year RI than that of patients who were MRD-positive at HCT (7.4% versus 45.7%, P=0.014). These results were comparable with outcomes

A

B A

C B

Figure 2. Prognostication based on MFC assessment of MRD. (A) The presence of MRD assessed using MFC at HCT in patients in the adverse risk group did not reveal distinct subgroups for 1-year RI. (B) Intermediate risk patients, however, had a higher RI at 1-year, comparable to that of adverse risk patients, if they were MRD-positive at HCT.

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Figure 3. Prognostication based on ELN classification diagnostic cytogenetic/molecular data and MFC assessment of MRD. (A) Two risk groups were identified for 1-year RI using the ELN classification based on diagnostic cytogenetic/molecular data and MRD assessment by MFC at HCT: a high risk group, including intermediate I/II MRD-positive and adverse risk patients, with a RI of 36%, and a low-risk group, including intermediate I/II MRD-negative and favorable risk patients, with a RI of 5.5%%. This risk classification by ELN and MRD at HSCT also predicted (B) LFS and (C) OS outcomes after HCT.

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observed in patients with wild-type FLT3-ITD (FLT3ITDwt) divided according to their MRD status at HCT (4% versus 40.3% for MRD-negative and MRD-positive, respectively; P=0.017) (Figure 4). The impact of MRD by MFC could not be analyzed in patients with NPM1 mutations because of the significant association between NPM1 mutation and MRD-negative status at HCT.

Risk stratification by disease and transplant characteristics predicts post-transplant relapse incidence We explored the possibility of developing a predictive model of 1-year relapse outcome in AML patients using MRD status at HCT. Considering the significance of the interaction term at multivariate regression indicating the different prognostic impact of MRD at HCT on 1-year RI among different ELN-defined risk groups, we re-ran multivariate regressions with variables generated by the combination of cytogenetics and MRD status at HCT: (i) high risk including adverse risk and intermediate risk MRDpositive patients and (ii) low risk including intermediate risk MRD-negative patients. Each factor was assigned a score proportional to the regression coefficient obtained from the multivariable regression model (Online Supplementary Table S1). Accordingly, a score of 1 was assigned to the risk factor of using reduced intensity conditioning. Then, a score of 2 was assigned to those with high-risk disease. A post-transplant relapse risk index was calculated as the sum of these weighted scores, and this index was then categorized into three risk groups: low (score = 0 or 1), intermediate (score = 2), high (score = 3). The 1-year RI was 6.9% in patients with a low relapse risk index, 26.9% in patients with an intermediate index, and 47.2% in patients with a high relapse risk index (P< 0.001; Online Supplementary Figure S2).

Discussion Our study is unique for investigating the impact of MFC-determined MRD status at HCT on 1-year RI not only by adjusting for the cytogenetic risk at diagnosis but also for distinct molecular abnormalities including FLT3ITD mutation per ELN classification. The analyses including 152 patients who underwent HCT in CR1 over the last 3 years at our institution confirm that MRD detected by MFC at HCT identifies a group with a poor prognosis with regards to relapse at 1 year after HCT. Our results were comparable to those recently reported showing that the presence of MRD determined by MFC increases the risk of relapse not only after myeloablative conditioning but also after reduced intensity conditioning regimens and it signifies a poor prognosis in addition to that conferred by other patient- and disease-related characteristics including cytogenetics.27 Moreover, our results suggest that the impact of MRD at HCT on RI differs in distinct prognostic groups defined by using diagnostic cytogenetics and molecular findings. Assessment of MRD at HCT appeared to have the potential to differentiate a large group of patients with intermediate risk features according to the ELN classification, including those with FLT3-ITD mutations. MRDpositive intermediate risk patients represented a worse prognostic group with a 1-year RI of 42.7% compared haematologica | 2017; 102(1)

with MRD-negative counterparts who had a 1-year RI of 7.4%. This observation remained the same when FLT3ITD mutations were taken into account. Patients with FLT3-ITDmut, who are known to have a high risk of relapse after HCT,28,29 enjoyed a lower RI of 7.4% at 1 year if MRD-negative compared with 45.7% if MRD-positive. On the other hand, intermediate risk patients with FLT3ITDwt, a group that is thought to have better results than FLT3-ITDmut patients, had a 1-year RI of 40.3% if they were MRD-positive at HCT, comparable to outcomes observed in FLT3-ITDmut, MRD-positive patients. These findings suggest that MRD status at HCT alters the initial prognosis dictated by genetic abnormalities at diagnosis within intermediate risk patients. On the other hand, we could not investigate whether NPM1-mutated intermediate risk patients had worse outcomes if they were MRDpositive at HCT by MCF because of the significant association of MRD-negative status and NPM1 mutation. We believe that addition of further genetic markers (e.g., DNMT3, TET2, ASXL1, RUNX mutations) and novel molecular abnormalities emerging from next-generation sequencing may further refine the accuracy of patient risk stratification by MRD using MFC after transplantation. Differently from what we observed for the intermediate risk group, MRD assessment at HCT did not identify different prognostic groups for 1-year RI in patients with adverse risk according to the ELN classification. These results are similar to those of previously published studies in the non-transplant setting showing that MRD determined by MFC had better prediction to identify prognostic groups in intermediate risk patients.30,31 We were not able to investigate the prognostic impact of MRD determined by MFC in the favorable risk group since there were few favorable risk patients who were MRD-positive in our series. Moreover, none of the favorable risk patients had experienced relapse by 1 year after HCT. MRD detection using more sensitive quantitative polymerase chain reaction assays32 merits further investigation in this group. As a result, given the limitations inherent in a retrospectively designed study, the implementation of MRD assessment by MFC at HCT allowed us to simplify risk groups

Figure 4. Effect of the FLT3-ITD mutation on relapse incidence. FLT3-ITDmut MRD-negative patients had a comparable 1-year RI (7.4%) to that of FLT3-ITDwt MRD-negative patients (4%) (P=0.8). Similarly, FLT3-ITDmut MRD-positive and FLT3-ITDwt MRD-positive patients had high incidences of relapse at 1 year (45.7% and 40.3%, respectively), which were not statistically different (P=0.4).

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for RI at 1 year using the ELN classification, which incorporates both cytogenetic and selected molecular abnormalities: a low risk group with a 1-year RI of 6.9%, including intermediate-I/II risk MRD-negative patients and a high risk group with a 1-year RI of 36% including intermediate-I/II risk MRD-positive and adverse risk patients. In our study, the use of reduced intensity conditioning was also a poor prognostic factor for 1-year RI suggesting that patients at high risk of early relapse should be considered for myeloablative conditioning if they are medically fit to tolerate the regimen. A recent Blood and Marrow Transplant Clinical Trial Network phase III randomized clinical trial showed significantly improved RI in AML patients if transplanted with myeloablative conditioning regimens rather than reduced intensity conditioning.33 Our group also reported that HCT with myeloablative conditioning using pharmacokinetics to target an average daily systemic exposure dose in a timed sequential approach allows even older patients to tolerate more intensive regimens without increased regimen-related toxicity.34 These results support the concept of treating high risk patients with myeloablative conditioning rather than reduced intensity conditioning. In addition to conditioning intensity modification, the MRD assessment at HCT combined with diagnostic cytogenetic and molecular characteristics may help to identify the target population in which to investigate innovative approaches for pre-emptive strategies to decrease the risk of relapse and improve transplant outcomes. A recent study by Platzbecker et al. showed that hematologic relapse after HCT could be prevented with the pre-emptive use of azacitidine and donor lymphocyte infusion in high risk patients defined by losing chimerism in the post-

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transplant setting.35 Similarly, post-transplant maintenance therapy, with various agents including DNA methytransferase inhibitors, deacetylase inhibitors and tyrosine kinase inhibitors, has been investigated to determine its efficacy at decreasing relapse and improving post-transplant outcomes.36-40 Despite the encouraging results reported, pre-emptive strategies including pharmacological, immunological and cellular therapies pose the dilemma of administering potentially toxic therapy without evidence of relapse. Proper risk assessment with the use of MRD status determined by MFC at HCT could overcome this potential problem. One important question implicit in the detection of MRD prior to HCT is whether those patients should receive additional pre-transplant treatment with the goal of achieving MRD-negative status or should such patients proceed to HCT without delay. To date, studies evaluating the role of post-remission chemotherapy before HCT with myeloablative or reduced intensity conditioning have not shown any improvement in post-transplantation outcomes.41-44 Information on MRD at HCT was not available in any of those retrospective studies and it is unknown whether additional post-remission therapy before HCT could benefit a subset of patients who are MRD-positive. In conclusion, our study indicates that, in AML, the combination of diagnostic cytogenetic/molecular findings and MRD status determined by MFC at HCT enable a better definition of distinct prognostic categories for transplant outcomes. This approach may potentially lead to an improvement in tailoring the intensity of transplantation and use of post-transplant interventions to prevent relapse, with the aim of preventing both under-treatment as well as overtreatment of AML patients.

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27. Walter RB, Gyurkocza B, Storer BE, et al. Comparison of minimal residual disease as outcome predictor for AML patients in first complete remission undergoing myeloablative or nonmyeloablative allogeneic hematopoietic cell transplantation. Leukemia. 2015;29(1):137-144. 28. Schmid C, Labopin M, Socie G, et al. Outcome of patients with distinct molecular genotypes and cytogenetically normal AML after allogeneic transplantation. Blood. 2015;126(17):2062-2069. 29. Brunet S, Labopin M, Esteve J, et al. Impact of FLT3 internal tandem duplication on the outcome of related and unrelated hematopoietic transplantation for adult acute myeloid leukemia in first remission: a retrospective analysis. J Clin Oncol. 2012;30(7):735-741. 30. Kohnke T, Sauter D, Ringel K, et al. Early assessment of minimal residual disease in AML by flow cytometry during aplasia identifies patients at increased risk of relapse. Leukemia. 2015;29(2):377-386. 31. Freeman SD, Virgo P, Couzens S, et al. Prognostic relevance of treatment response measured by flow cytometric residual disease detection in older patients with acute myeloid leukemia. J Clin Oncol. 2013;31 (32):4123-4131. 32. Yin JAL, O'Brien MA, Hills RK, Daly SB, Wheatley K, Burnett AK. Minimal residual disease monitoring by quantitative RT-PCR in core binding factor AML allows risk stratification and predicts relapse: results of the United Kingdom MRC AML-15 trial. Blood. 2012;120(14):2826-2835. 33. Scott BL, Pasquini MC, Logan B, et al. Results of a phase III randomized, multi-center study of allogeneic stem cell transplantation after high versus reduced intensity conditioning in patients with myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML): Blood and Marrow Transplant Clinical Trials Network (BMT CTN) 0901. Blood (ASH Annual Meeting Abstracts) 2015;126(23):LBA-8. 34. Popat UR, Fox PS, Bassett R, et al. Myeloablative timed sequential busulfan is safe in older patients. Blood. 2014;124(21): 3859 abstr. 35. Platzbecker U, Wermke M, Radke J, et al. Azacitidine for treatment of imminent relapse in MDS or AML patients after allogeneic HSCT: results of the RELAZA trial. Leukemia. 2012;26(3):381-389.

36. Oran B. Is there a role for therapy after transplant? Best Pract Res Clin Haematol. 2015;28(2-3):124-132. 37. de Lima M, Giralt S, Thall PF, et al. Maintenance therapy with low-dose azacitidine after allogeneic hematopoietic stem cell transplantation for recurrent acute myelogenous leukemia or myelodysplastic syndrome: a dose and schedule finding study. Cancer. 2010;116(23):5420-5431. 38. Pusic I, Choi J, Fiala MA, et al. Maintenance therapy with decitabine after allogeneic stem cell transplantation for acute myelogenous leukemia and myelodysplastic syndrome. Biol Blood Marrow Transplant. 2015;21(10):1761-1769. 39. Bug G, Burchert A, Nicolaus K, et al. Posttransplant maintenance with the deacetylase inhibitor panobinostat in patients with highrisk AML or MDS: results of the phase I part of the Panobest trial. Blood. 2013;122 (21):3315 abstr. 40. Chen YB, Li SL, Lane AA, et al. Phase I trial of maintenance sorafenib after allogeneic hematopoietic stem cell transplantation for fms-like tyrosine kinase 3 internal tandem duplication acute myeloid leukemia. Biol Blood Marrow Trasplant. 2014;20(12):20422048. 41. Tallman MS, Rowlings PA, Milone G, et al. Effect of postremission chemotherapy before human leukocyte antigen-identical sibling transplantation for acute myelogenous leukemia in first complete remission. Blood. 2000;96(4):1254-1258. 42. Sproat L, Bolwell B, Rybicki L, et al. Effect of post-remission chemotherapy preceding allogeneic hematopoietic cell transplant in patients with acute myeloid leukemia in first remission. Leuk Lymphoma. 2010;51(9): 1699-1704. 43. Cahn JY, Labopin M, Sierra J, et al. No impact of high-dose cytarabine on the outcome of patients transplanted for acute myeloblastic leukaemia in first remission. Acute Leukaemia Working Party of the European Group for Blood and Marrow Transplantation (EBMT). Br J Haematol. 2000;110(2):308-314. 44. Warlick ED, Tomblyn M, Cao Q, et al. Reduced-intensity conditioning followed by related allografts in hematologic malignancies: long-term outcomes most successful in indolent and aggressive non-Hodgkin lymphomas. Biol Blood Marrow Transplant. 2011;17(7):1025-1032.

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Acute Lymphoblastic Leukemia

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):118-129

ZNF384-related fusion genes define a subgroup of childhood B-cell precursor acute lymphoblastic leukemia with a characteristic immunotype

Shinsuke Hirabayashi,1,2 Kentaro Ohki,1 Kazuhiko Nakabayashi,3 Hitoshi Ichikawa,4 Yukihide Momozawa,5 Kohji Okamura,6 Akinori Yaguchi,1,7 Kazuki Terada,1 Yuya Saito,1,8 Ai Yoshimi,1,9 Hiroko Ogata-Kawata,3 Hiromi Sakamoto,4 Motohiro Kato,1,10 Junya Fujimura,7 Moeko Hino,11 Akitoshi Kinoshita,12 Harumi Kakuda,13 Hidemitsu Kurosawa,14 Keisuke Kato,9 Ryosuke Kajiwara,15 Koichi Moriwaki,16 Tsuyoshi Morimoto,17 Kozue Nakamura,18 Yasushi Noguchi,19 Tomoo Osumi,1,20 Kazuo Sakashita,21 Junko Takita,22 Yuki Yuza,8 Koich Matsuda,23 Teruhiko Yoshida,4 Kenji Matsumoto,24 Kenichiro Hata,3 Michiaki Kubo,5 Yoichi Matsubara,25 Takashi Fukushima,26 Katsuyoshi Koh,27 Atsushi Manabe,2 Akira Ohara28 and Nobutaka Kiyokawa1 for the Tokyo Children’s Cancer Study Group (TCCSG)

Department of Pediatric Hematology and Oncology Research, National Research Institute for Child Health and Development, Setagaya-ku, Tokyo; 2Department of Pediatrics, St. Luke's International Hospital, Chuo-ku, Tokyo; 3Department of MaternalFetal Biology, National Research Institute for Child Health and Development, Setagayaku, Tokyo; 4Division of Genetics, National Cancer Center Research Institute, Chuo-ku, Tokyo; 5Laboratory for Genotyping Development, Center for Integrative Medical Sciences (IMS), RIKEN, Yokohama-shi, Kanagawa; 6Department of Systems BioMedicine, National Research Institute for Child Health and Development, Setagaya-ku, Tokyo; 7Department of Pediatrics and Adolescent Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo; 8Department of Hematology/Oncology, Tokyo Metropolitan Children’s Medical Center, Fuchu-shi, Tokyo; 9Division of Pediatric Hematology and Oncology, Ibaraki Children’s Hospital, Mito-shi, Ibaraki; 10Division of Stem Cell Transplant and Cellular Therapy, Children’s Cancer Center, National Center for Child Health and Development, Setagaya-ku, Tokyo; 11Department of Pediatrics, Chiba University Graduate School of Medicine, Chiba-shi, Chiba; 12Department of Pediatrics, St. Marianna University School of Medicine, Kawasaki-shi, Kanagawa; 13Department of Haematology/Oncology, Chiba Children’s Hospital, Chiba-shi, Chiba; 14Department of Pediatrics, Dokkyo Medical University, Mibu, Tochigi; 15Department of Pediatrics, Yokohama City University Hospital, Yokohama-shi, Kanagawa; 16Department of Pediatrics, Saitama Medical Center, Saitama Medical University, Kawagoe-shi, Saitama; 17 Department of Pediatrics, Tokai University School of Medicine, Isehara-shi, Kanagawa; 18 Department of Pediatrics, Teikyo University School of Medicine, Itabashi-ku, Tokyo; 19 Department of Pediatrics, Japanese Red Cross Narita Hospital, Narita-shi, Chiba; 20 Division of Leukemia and Lymphoma, Children’s Cancer Center, National Center for Child Health and Development, Setagaya-ku, Tokyo; 21Department of Hematology/Oncology, Nagano Children's Hospital, Azumino-shi, Nagano; 22Department of Pediatrics, Graduate School of Medicine, University of Tokyo, Bunkyo-ku, Tokyo; 23 Laboratory of Clinical Sequence,Department of Computational biology and medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Minato-ku, Tokyo; 24Department of Allergy and Clinical Immunology, National Research Institute for Child Health and Development, Setagaya-ku, Tokyo; 25National Research Institute for Child Health and Development, Setagaya-ku, Tokyo; 26Department of Child Health, Faculty of Medicine, University of Tsukuba, Tsukuba-shi, Ibaraki; 27Department of Hematology/Oncology, Saitama Children’s Medical Center, Saitama-shi, Saitama and 28 Department of Pediatrics, Toho University Omori Medical Center, Ohta-ku, Tokyo, Japan

1

Correspondence: kiyokawa-n@ncchd.go.jp/ oki-kn@ncchd.go.jp

Received: June 14, 2016. Accepted: September 14, 2016. Pre-published: September 15, 2016. doi:10.3324/haematol.2016.151035

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/118

ABSTRACT

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is required for any other use.

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usion genes involving ZNF384 have recently been identified in Bcell precursor acute lymphoblastic leukemia, and 7 fusion partners have been reported. We further characterized this type of fusion gene by whole transcriptome sequencing and/or polymerase chain reaction. In addition to previously reported genes, we identified BMP2K as a novel fusion partner for ZNF384. Including the EP300-ZNF384 that we reported recently, the total frequency of ZNF384-related fusion genes was 4.1% in 291 B-cell precursor acute lymphoblastic leukemia patients enrolled in a single clinical trial, and TCF3-ZNF384 was the most recurrent, with a frequency of 2.4%. The characteristic haematologica | 2017; 102(1)


Fusion genes involving ZNF384 in BCP-ALL

immunophenotype of weak CD10 and aberrant CD13 and/or CD33 expression was revealed to be a common feature of the leukemic cells harboring ZNF384-related fusion genes. The signature gene expression profile in TCF3-ZNF384-positive patients was enriched in hematopoietic stem cell features and related to that of EP300-ZNF384-positive patients, but was significantly distinct from that of TCF3-PBX1-positive and ZNF384-fusion-negative patients. However, clinical features of TCF3ZNF384-positive patients are markedly different from those of EP300-ZNF384-positive patients, exhibiting higher cell counts and a younger age at presentation. TCF3-ZNF384-positive patients revealed a significantly poorer steroid response and a higher frequency of relapse, and the additional activating mutations in RAS signaling pathway genes were detected by whole exome analysis in some of the cases. Our observations indicate that ZNF384-related fusion genes consist of a distinct subgroup of B-cell precursor acute lymphoblastic leukemia with a characteristic immunophenotype, while the clinical features depend on the functional properties of individual fusion partners.

Introduction B-cell precursor acute lymphoblastic leukemia (BCPALL) is a heterogeneous disease that can be subdivided according to primary recurrent genetic abnormalities that are strongly associated with characteristic biological and clinical features.1 The detection of these abnormalities can facilitate diagnosis, risk stratification, and targeted therapy. In approximately two-thirds of pediatric patients with BCP-ALL, well-characterized genetic abnormalities, including t(9;22) BCR-ABL1, the rearrangement of MLL at 11q23, t(1;19) TCF3-PBX1, t(17;19) TCF3-HLF, t(12;21) ETV6-RUNX1, hyperdiploidy, and hypodiploidy, can be detected by standard genetic analyses.1 In the remaining BCP-ALL patients, major pathogenic or driver cytogenetic abnormalities have yet to be clarified, and they are called "B-others". Recent studies using advanced analytical approaches have stratified a variety of subgroups harboring novel genetic abnormalities. For example, a high-risk subtype in B-others with a number of fusion genes involving tyrosine kinases, so-called "Ph-like acute lymphoblastic leukemia (Ph-like ALL)", was recently discovered.2-3 Besides Ph-like ALL, other subgroups such as iAMP21, dic(9;20), and patients with PAX5 abnormalities have also been identified in B-others.4-7 However, a certain portion of B-others still remain genetically unclassified. The zinc-finger protein 384 (ZNF384) gene encodes a transcription factor that regulates promoters of the extracellular matrix genes8 and is known to be involved in ALL through fusion with the TET family genes, such as the Ewing sarcoma breakpoint region 1 gene {EWSR1, t(12;22)}, TATA box binding protein-associated factor {TAF15, t(12;17)}, and transcription factor 3 {TCF3 or E2A, t(12;19)}.9-10 In addition to those previously reported ZNF384-related fusion genes, we identified EP300ZNF384, t(12;22), as a novel recurrent fusion gene with an incidence of approximately 1% in B-others in a Japanese cohort.11 The recurrence of EP300-ZNF384 in pediatric BCP-ALL patients as well as a higher incidence in adolescent and young adult (AYA) BCP-ALL patients was confirmed by other groups.12-15 Furthermore, the CREB binding protein gene {CREBBP, t(12;16)(p13;p13)} has been most recently identified as another novel fusion partner for ZNF384.13 So far, however, patients harboring ZNF384-related fusion genes have been considered to be a minor subgroup in pediatric BCP-ALL.8-15 The BCP-ALL patients with EP300-ZNF384 possess a characteristic haematologica | 2017; 102(1)

immunophenotype of weak CD10 and aberrant CD13 and/or CD33 expression.11 Although certain immunophenotypic features were still observed in some of the remaining B-others patients, cytogenetic abnormalities in these cases have yet to be clarified. In order to further investigate unknown cytogenetic alterations in the remaining B-others, we employed whole transcriptome sequencing (WTS). Herein, we report the identification of an unexpectedly high incidence of fusion genes involving ZNF384 genes in BCP-ALL in our cohort. The immunophenotypic and gene-expression characteristics, accompanying genetic abnormalities as well as the clinical features of BCP-ALL harboring the ZNF384-related fusion gene are evaluated and discussed.

Methods Patient selection Following previous publication,11 91 ribonucleic acid (RNA) samples obtained from pediatric BCP-ALL patients classified as Bothers were selected from the Tokyo Childrenâ&#x20AC;&#x2122;s Cancer Study Group (TCCSG) biobank as a discovery cohort for WTS to screen for unknown fusion genes. We then extended analysis to another 122 B-others' RNA samples that were available in our biobank as a validation cohort by employing reverse transcription polymerase chain reaction (RT-PCR) (detailed information is presented in Figure 1, Online Supplementary Information and Online Supplementary Table S1). Diagnoses were made on the basis of the morphology and routine examinations, including the immunophenotype, cytogenetic analysis, DNA content analysis, and the RT-PCR detection of 7 conventional fusion transcripts, as described previously.16 The investigations were approved by the institutional review boards of all participating institutions. Informed consent was obtained from parents or guardians, and informed assent was obtained from the patients when appropriate, based on their age and level of understanding. In the TCCSG study, we first assigned patients to standard- (SR), intermediate- (IR) and highrisk (HR) groups based on their age and leukocyte count, and risk assessment was revised on day 8 based on the response of the patients to steroid monotherapy.17

Whole transcriptome sequencing and RT-PCR Using total RNA extracted from the bone marrow or peripheral blood samples of the patients, WTS was performed and the fusion transcripts were investigated by employing deFuse, an algorithm for gene fusion discovery, as described in the Online Supplementary 119


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Table 1A. Clinical characteristics of acute lymphoblastic leukemia (ALL) with ZNF384-related fusion genes.

ID

Fusion Age Gender Initial partner (years) WBC count

Case-1 TCF3 Case-2 TCF3 Case-3 TCF3 Case-4 TCF3 Case-5 TCF3 Case-6 TCF3 Case-7 TCF3 Case-8 TCF3 Case-9 TCF3 Case-10 TCF3 Case-11 TCF3 Case-12 TCF3 Case-13 TCF3 Case-14 TCF3 Case-15 TCF3 Case-16 TAF15 Case-17 TAF15 Case-18 TAF15 Case-19 CREBBP

2 9 3 2 1 9 1 11 2 10 3 2 2 3 8 5 3 8 3

F M M M F F M F F F F M M M M M M M F

Case-20 CREBBP Case-21 CREBBP Case-22 BMP2K

12 2 5

F M F

Karyotype

Initial Day 8 CNS Current Relapse risk blasts involvement status (date, site) (/mL)

36,600 46,XX 3,200 46,XY 137,260 46,XY 4,000 46,XY 21,100 46,XX 2,750 ND 49,970 46,XY 1,220 46,XX 150,200 46,XX 4,800 46,XX 130,900 46,XX 49,160 46,XY 27,450 46,XY 105,900 46,XY 76,500 46,XY 12,200 46,XY 22,000 46XY 34,100 46,XY 19,270 47,X,add(X)(p22), t(12;12)(p13:q13),+21 58,000 46,XX 26,500 46,XY 4,100 46,XX

IR IR HR SR IR IR IR IR HR IR HR IR IR HR IR SR IR IR SR

0 14 639 0 1,617 1,824 11,941 10 44,156 0 16,816 7,443 5,425 17,797 52 224 537 2,704 3,076

CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS1 CNS2 CNS1 CNS1 CNS1 CNS1

1st CR Relapse 1st CR 1st CR 1st CR 1st CR Relapse 1st CR 1st CR 1st CR Relapse Relapse Relapse 1st CR 1st CR 1st CR Relapse 1st CR 1st CR

HR IR SR

574 538 17

CNS1 CNS1 CNS1

1st CR Relapse 1st CR

Salvage therapy after relapse

4.7y, BM

SCT

1.6y, BM

SCT

3.4y, BM 2.9y, BM 1.6y, BM

SCT SCT SCT

FUP (years)

Status

3.5 7.0 6.1 6.4 4.5 2.0 2.5 6.7 3.6 0.7 4.3 3.6 2.4 2.4 2.3 4.7 6.3 1.5 5.7

Alive Alive Alive Alive Alive Alive Death Alive Alive Alive Alive Death Death Alive Alive Alive Alive Alive Alive

6.4 6.5 10.1

Alive Alive Alive

5.7y, BM Chemotherapy

3.5y, BM Chemotherapy

F: female; M: male; WBC: white blood cell; CNS: central nervous system; FUP: follow up; SR, standard-risk; IR: intermediate-risk; HR: high-risk; CR: complete remission; SCT: stem cell transplantation; BM: bone marrow.

Table 1B. Additional genetic characteristics of acute lymphoblastic leukemia (ALL) with ZNF384-related fusion genes.

ID

Case-1 Case-2 Case-3 Case-4 Case-5 Case-6 Case-7 Case-8 Case-9 Case-10 Case-11 Case-12 Case-13 Case-14 Case-15 Case-16 Case-17

Fusion partner TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TCF3 TAF15 TAF15

Case-18 TAF15 Case-19 CREBBP Case-20 CREBB Case-21 CREBBP Case-22 BMP2K

Methods MLPA Whole Whole transcriptome exome sequencing sequencing ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○ ○

○ ○

○ ○

○ ○ ○ ○

○ ○

Additional genetic mutation Samples obtained at

MLPA Signaling/adhesion Epigenetic regulator

Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed 1st relapse Newly diagnosed Newly diagnosed Newly diagnosed Newly diagnosed, 1st relapse Newly diagnosed Newly diagnosed Newly diagnosed

NP NP NP RB1 del NP NP NP PTPN11 NT NP NT CDKN2A/2B del NP NP NRAS NP KRAS, PTPN11 NP NT NP

NT NT NT NP

NT NP

NP CDKN2A/2B del NP

NP NT

Newly diagnosed

NT

NT

Newly diagnosed

NP

NP

ASH1L NP NT NT NT NT NT EZH2 MLL2 ASH1L

NRAS

MLL2

Fusion points Ex11-Ex3 Ex13-Ex3 Ex17-Ex7 Ex13-Ex3 Ex13-Ex3 Ex13-Ex3 Ex13-Ex3 Ex17-Ex7 Ex11-Ex3 Ex16-Ex2 Ex17-Ex7 Ex13-Ex3 Ex11-Ex3 Ex13-Ex3 Ex13-Ex2 Ex6-Ex3 Ex6-Ex3 Ex6-Ex3 Ex6-Ex2, Ex5-Ex3 Ex6-Ex3, Ex5-Ex3, Ex4-Ex3 Ex6-Ex3, Ex4-Ex3, Ex7-Ex3 Ex14-Ex3, Ex15-Ex3

MLPA: Multiplex Ligation-dependent Probe Amplification; NP: not particular; NT: not tested; del: deletion; Ex: exon.

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Figure 1. Flow chart of the analysis of patients. The respective numbers of patients and cohorts that were investigated are presented in a hierarchical fashion. See also the Online Supplementary Information and Online Supplementary Table S1. ALL: acute lymphoblastic leukemia; BCP-ALL: B-cell precursor ALL; B-others: BCP-ALL without conventional genetic abnormalities; RNA: ribonucleic acid; RNA-seq-Ex1 and Ex2: RNA-sequencing experiment 1 and 2; RT-PCR-Ex1 and Ex2: reverse transcription polymerase chain reaction experiment 1 and 2; Ex: experiment.

Information. For the confirmation of the whole transcriptome screening results and screening for additional cases in the validation cohort, RT-PCR was performed as described previously,18 using the primers listed in the Online Supplementary Table S2, followed by Sanger sequencing. The details of the data analyses of WTS to identify genetic mutations and deletions are also described in the Online Supplementary Information.

Whole exome sequencing (WES) Exome libraries were prepared from 100 ng of genomic DNA using the Nextera Rapid Capture Exome Kit (Illumina, Inc., San Diego, CA, USA), and sequenced using SBS v4 reagents with the HiSeq2500 sequencing system (Illumina). More than 10 Gb of sequence was obtained for each library by paired-end sequencing (126 bp x2). The details of the whole exome data analyses are described in the Online Supplementary Information.

Microarray and data analyses The complementary DNAs (cDNAs) were amplified and labeled using the Ovation® Pico WTA System and Encore™ Biotin Module (NuGEN Technologies Inc., San Carlos, CA, USA), as instructed by the manufacturer. The labeled probes were hybridized to Human Genome U133 Plus 2.0 Arrays (Affymetrix, Santa Clara, CA, USA). The arrays were analyzed using GeneChip Operating Software 1.2 (Affymetrix, Santa Clara, CA, USA) and GeneSpring GX 13.1 software (Agilent Technologies, Santa Clara, haematologica | 2017; 102(1)

CA, USA), and the details of data analyses, including gene set enrichment analysis (GSEA), are described in the Online Supplementary Information.

Statistical analysis An unpaired t-test with Welch's correction was performed for the positivity of cell surface antigens. Mutual univariable analysis of characteristics were conducted using the Fisher’s exact test or χ2 test for qualitative variables. Overall survival (OS) and event-free survival (EFS) were estimated by the Kaplan-Meier method and compared with the log-rank test. Analyses were performed with the use of Prism software, version 6.0 (GraphPad Software, Inc., La Jolla, CA, USA).

Results Detection of the fusion genes involving ZNF384 in pediatric BCP-ALL patients The 213 selected RNA samples from B-others patients were analyzed by WTS and/or RT-PCR followed by Sanger sequencing (Figure 1 and Online Supplementary Tables S1 and S3). We identified a total of 15, 3 and 3 patients with TCF3-ZNF384, TAF15-ZNF384 and CREBBP-ZNF384, respectively. Three fusion genes were reported previously.9,10,12-15,19-22 In addition, we identified a 121


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B

C

D

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Figure 2. Structure of the ZNF384-related fusions. Structures of fusion proteins and nucleotide sequences of fusion points of (A) TCF3-ZNF384, (B) TAF15-ZNF384, (C) CREBBP-ZNF384, and (D) BMP2K-ZNF384 are presented. Exon numbers and boundaries are marked below the protein structures. The black arrowhead shows the donor site fusion point. The white arrowhead shows the acceptor site fusion point. Five and four different in-frame fusions for TCF3-ZNF384 and CREBBP -ZNF384, respectively, are depicted with the nucleotide sequence, predicted amino acids, and chromatogram. The patients in whom a particular fusion isoform was found are indicated on the right. Ex: exon; TAZ2: transcription adaptor putative zinc finger; KIX: kinase-inducible domain interacting; RING: really interesting new gene; PHD: plant homeodomain; CREB: cyclic adenosine monophosphate (AMP) response element binding protein; RNA: ribonucleic acid; ZN: zinc finger; RAN: Ras-related nuclear proteins; BMP-2: bone morphogenetic protein 2.

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Fusion genes involving ZNF384 in BCP-ALL

Table 2. Statistical comparison of clinical characteristics between TCF3-ZNF384-, EP300-ZNF384-, TCF3-PBX1-positive, and ZNF384-related fusion gene-negative B-cell precursor acute lymphoblastic leukemia (BCP-ALL).

TCF3-ZNF384 (N=15)

EP300-ZNF384 (N=9)

TCF3-PBX1* (N=17)

ZNF384 wild-type* (N=115)

8 (53%) 7 (47%)

6 (67%) 3 (33%)

10 (59%) 7 (41%)

63 (55%) 50 (43%)

10 (67%) 3 (20%) 2 (13%)

1 (11%) 2 (22%) 6 (67%)

10 (59%) 3 (18%) 4 (24%)

71(62%) 14 (12%) 26 (23%)

#1

5 (33%) 5 (33%) 1 (7%) 4 (27%)

7 (78%) 0 (0%) 1 (11%) 1 (11%)

7 (41%) 6 (35%) 2 (12%) 2 (12%)

80 (70%) 17 (15%) 5 (4%) 4 (3%)

#2

1 (7%) 10 (67%) 4 (27%)

1 (11%) 6 (67%) 2 (14%)

3 (18%) 12 (71%) 2 (12%)

42 (37%) 53 (46%) 4 (3%)

#3

7 (47%) 8 (53%)

8 (89%) 1 (11%)

14 (82%) 3 (18%)

99 (86%) 5 (4%)

#4

Sex Male Female Age (years) 1-6 7-9 >10 WBC (x109/L) <20 20-50 50-100 >=100 Initial risk SR IR HR Treatment response PGR PPR

Wild-type ZNF384; BCP-ALL without conventional genetic abnormalities as well as ZNF384-related fusions; SR: standard-risk; IR: intermediate-risk; HR: high-risk; WBC: white blood cells; PGR: predonine good responder; PPR: predonine poor responder. *L0416/0616-registered cases. #1P<0.01 EP300-ZNF384 vs. wild-type ZNF384; P<0.05 EP300-ZNF384 vs. TCF3-ZNF384. #2P<0.05 TCF3ZNF384 vs. wild-type ZNF384, TCF3-PBX1 vs. wild-type ZNF384. #3P<0.01 TCF3-ZNF384 vs. wild-type ZNF384; P<0.05 EP300-ZNF384 vs. wild-type ZNF384. #4P<0.01 TCF3-ZNF384 vs. wild-type ZNF384.

novel ZNF384-related fusion gene, namely BMP2KZNF384 (1 patient). Although we recently reported 6 patients with EP300-ZNF384,11 another 3 patients with this fusion gene were further identified in this study (Figure 1 and Online Supplementary Tables S1 and S4).

Structure of the fusion genes involving ZNF384 The structure and sequences of the fusion points of each fusion gene as well as a schematic representation of the predicted fusion proteins are depicted in Figure 2. In 3 out of 15 TCF3-ZNF384 patients, the fusion point of ZNF384 was the same as those previously reported, and exon 11 of TCF3 was fused to exon 3 of ZNF384 (presented in Figure 2A as Type (a)).10 In addition to this known fusion point, we identified several novel fusion points of this fusion gene. Most frequently, for example, exon 13 of TCF3 was fused to exon 3 of ZNF384 with in-frame joining in 7 patients (Figure 2A Type (c)). The predicted protein from all of the fusions does not have the principal functional domains of wild-type TCF3, whereas it retains almost all of the part of the ZNF384 protein. The structure and sequences of the fusion point of TAF15-ZNF384 are depicted in Figure 2B. Although several isoforms have been reported in this fusion gene,16 only one isoform joining exon 6 of TAF15 to exon 3 of ZNF384 was observed in 3 of our patients. In the case of CREBBP-ZNF384, we identified 5 isoforms in 3 patients (Figure 2C). The exons 4, 5, and 6 of CREBBP fused in-frame to exon 3 or 2 of ZNF384 (Figure 2C Type (a-d)). Among all of the fusion points, most functional domains of CREBBP were lacking in the resulting fusion proteins, while the complete ZNF384 protein was retained. In contrast, exon 7 of CREBBP was fused out-offrame to exon 3 of ZNF384 in 1 patient (Figure 2C Type (e)). In the case of BMP2K-ZNF384, 2 isoforms were identihaematologica | 2017; 102(1)

fied in one patient and nucleotide 2228 (exon 15) and nucleotide 2117 (exon 14) of BMP2K were fused in-frame to nucleotide 266 (exon 3) of ZNF384 (Figure 2D, Type (a, b)), and the predicted protein retained the kinase domain of BMP2K but lacked the c-terminus portion. The 3 patients with EP300-ZNF384 exhibited identical split sequences, as we reported previously (data not shown).11

Frequency of ZNF384-related fusion gene-positive patients A consecutive series of 333 ALL patients enrolled in the TCCSG L0416/0616 study11 included 130 B-others patients and 161 BCP-ALL patients with conventional genetic abnormalities (291 BCP-ALL patients, Figure 1 and Online Supplementary Table S1). Since the majority of these B-others patients of the L0416/0616 cohort (121 patients, 93.1% of B-others) were studied in the present analysis, we estimated the frequency of ZNF384-related fusion genes in childhood ALL based on this cohort. As we reported previously, 3 patients with EP300-ZNF384 were included in the L0416/0616 cohort.11 In the study herein, we identified another 9 patients with ZNF384-related fusion genes in this cohort. Therefore, the frequency of the total of 12 patients with ZNF384-related fusion genes in B-others was estimated as 9.2% (4.1% in BCP-ALL, Figure 1 and Online Supplementary Table S1). Of those fusion genes, TCF3-ZNF384 was the most recurrent (7 patients), with a frequency of 5.4% in B-others (2.4% in BCP-ALL).

Immunophenotypic characteristics of BCP-ALL patients with ZNF384-related fusion genes As we reported previously, all BCP-ALL patients with EP300-ZNF384 showed a dull or negative expression of CD10 and aberrant expression of one or more myeloid antigens based on immunophenotypic examination.11,13 123


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Similar to EP300-ZNF384-positive patients, all of the other BCP-ALL patients with ZNF384-related fusion genes were found to have a weak or negative expression of CD10, ranging from 0.39% to 67.34% (mean: 19.44±18.23%, Figure 3 and Online Supplementary Table S5), and there was a significant difference compared with TCF3-PBX1-positive patients and B-others in which ZNF384-related fusion genes were not identified (wild-type ZNF384), for the most part strongly expressing CD10 (mean: 98.66±0.89%, P<0.001 and mean: 77.71±25.79%, P<0.001, respectively).

In addition, 7 and 17 patients out of 22 patients with ZNF384-related fusion genes (31.82% and 77.27%, respectively) exhibited more than 20% expression of CD13 (mean: 10.70±10.37%) and CD33 (mean: 59.86±34.01%), significantly distinct from BCP-ALL patients with TCF3-PBX1 and wild-type ZNF384 expressing neither CD13 (mean: 0.26±0.33%, P<0.001 and mean: 2.76±7.9%, P<0.0015, respectively), nor CD33 (mean: 0.59±0.76%, P<0.001 and mean: 6.63±1.72%, P<0.0001, respectively).

A

B

Figure 3. Immunophenotypic characteristics of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients with ZNF384-related fusion genes. (A) Typical histograms of CD19, CD10, aberrant myeloid antigens (CD13 and CD33), and CD66c of ZNF384-related fusion gene-positive patients and TCF3-PBX1 patients are indicated with a positive rate (%). X-axis, fluorescence intensity; Y-axis, relative cell number. (B) The positivity (percentage) of CD10, 13, and 33 of ZNF384-related fusion gene-positive BCP-ALL patients (22 cases, excepting EP300-ZNF384) and TCF3-PBX1-positive or wild-type ZNF384 BCP-ALL patients was plotted on a scattergram. The detailed list of positivity for each immunophenotypic marker of the patients is presented in the Online Supplementary Table S5. ZNF384-WT indicates cases without ZNF384 rearrangement.

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A

B

C

Figure 4. Characteristics of gene expression profile in TCF3-ZNF384-positive acute lymphoblastic leukemia (ALL). (A) Two-way hierarchical clustering was performed on filtered microarray probes, those up- or downregulated by 2-fold or more in TCF3-ZNF384- (red, n=10), in comparison with TCF3-PBX1-positive (blue, n=19) ALL. The results are displayed using a heat map as a dendrogram. (B) Among the genes that exhibited a 2 times higher or lower expression in either TCF3-ZNF384- and TCF3-PBX1-positive ALL (listed in the Online Supplementary Table S6), the expressions of PAX5 and VPREB genes measured by microarray analysis were plotted on a scatter diagram, and bars representing the meanÂąSD are presented. The data of wild-type ZNF384 B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients are also presented. (C) Gene set enrichment analysis (GSEA) for curated gene sets of hematopoietic precursors was performed on the differentially expressed genes between TCF3-ZNF384- (red) and TCF3-PBX1-positive (blue) ALL. Enrichment plots for the hematopoietic stem cells (HSCs), multi-lymphoid progenitor (MLP), pro-B cell (Pro-B), early T-cell precursors (ETP), common myeloid progenitors (CMP), granulocyte-monocyte progenitor (GMP), and megakaryocyte-erythroid progenitor cell (MEP) signatures are presented. Bold lines represent significant enrichments {false discovery rate (FDR) q-value<0.25 and/or nominal (NOM) P-value<0.05)}. NES: normalized enrichment score.

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Additional genetic abnormalities in ZNF384-related fusion gene-positive patients To detect the additional genetic abnormalities in BCPALL with ZNF384-related fusion genes, we performed multiplex ligation-dependent probe amplification (MLPA) analysis. However, MLPA analysis did not reveal that ZNF384-translocated cases had deleted or amplified regions in IKZF1, PAX5, ETV6, BTG1, EBF1, CRLF2, and ERG, and only 2 patients with CDKN2A/B deletion and 1 patient with RB1 deletion out of 15 were detected (Table 1 and Online Supplementary Figure S1). We preliminarily identified 126 genes as candidates for recurrent genetic abnormalities occurring in BCP-ALL by performing somatic point mutation calling from matched leukemia-normal patient samples based on the results from WES data from 100 patients with pediatric BCPALL. We therefore subjected 7 DNA samples of patients with ZNF384-related fusion genes to WES to filtrate the 126 genes by multi-sample calling for single-nucleotide variants and short insertions/deletions (Online Supplementary Information). Together with the data of WTS performed for 9 patients (6 patients were subjected to both WES and WTS), we analyzed them to identify somatic mutations impacting coding sequences. As a consequence, we identified 7 recurrently mutated genes which had been recognized earlier as abnormalities involved in leukemia, including NRAS, KRAS, PTPN11, EZH2, MLL2, and ASH1L (Table 1 and Online Supplementary Figure S1). Principally, activating mutations in RAS signaling pathway genes, including NRAS, KRAS, and PTPN11, were detected in 4 out of 10 ZNF384-translocated patients subjected to WES and/or WTS. On the other hand, mutations in B-cell developmental genes, such as PAX5, VPREB1, BTG1, and IKZF1, were not detected at all in DNA samples from BCP-ALL with ZNF384-related fusion genes.

A

wild-type

B

wild-type

Figure 5. Outcomes of patients with ZNF384-related fusion genes. (A) KaplanMeier estimates of event-free survival (EFS) for patients with TCF3-ZNF384, EP300-ZNF384, and wild-type ZNF384 (log-rank P=0.35 in wild-type ZNF384 vs. TCF3-ZNF384, log-rank P=0.17 in TCF3-ZNF384 vs. EP300-ZNF384. (B) Overall survival (OS) for the same as above (log-rank P=0.15 in wild-type ZNF384 vs. TCF3-ZNF384, log-rank P=0.14 in TCF3-ZNF384 vs. EP300ZNF384.

Gene expression profile of TCF3-ZNF384-positive patients To assess the functional aspects of TCF3-ZNF384, we performed DNA microarray-based expression profiling. Hierarchical clustering analysis using the selected gene probe sets2,3 showed that the major subtypes of BCP-ALL patients with conventional genetic abnormalities separated into distinct clusters. Remarkably, ZNF384-related fusion gene positive patients were located in the same cluster and clearly separated from those of other conventional genetic subtypes (Online Supplementary Figure S2A) as well as TCF3-PBX1-positive patients (Online Supplementary Figure S2B). The data indicate that the gene expression profile of TCF3-ZNF384-positive ALL is related to EP300-ZNF384- and CREBBP-ZNF384-positive ALL, but not to other conventional genetic subtypes. Therefore, we proceeded to directly compare the gene expression of the most frequent TCF3-ZNF384-positive ALL to that of TCF3-PBX1-positive ALL possessing the same fusion partner, and with both translocations disrupting one allele of TCF3 that drives the B-cell differentiation program. As shown in the Online Supplementary Figure S2C and Figure 4A, TCF3-ZNF384-positive patients were clearly separated in a distinct cluster from TCF3-PBX1positive patients by hierarchical clustering, and the differential expression of 3,698 genes (up: 1,984, down: 1,714, >2.0) were identified (Online Supplementary Table S6), indicating that two TCF3-translocated subtypes were signifi126

cantly distinct. Interestingly, the B-cell developmental genes VPREB1, PAX5, and IKZF1-3 were listed as more highly expressed genes in TCF3-PBX1-positive ALL than in TCF3-ZNF384-positive ALL (Online Supplementary Table S6 and Figure 4B). The transcriptional regulators, such as BACH2, HIST1H3A, and LEF,1 were also upregulated in TCF3-PBX1-positive ALL, while GATA3, ERG, NCOR1, and TOX were upregulated in TCF3-ZNF384-positive ALL. It is noteworthy that gene set enrichment analysis revealed a significant enrichment for hematopoietic stem cell (HSC) signatures in TCF3-ZNF384-positive ALL while lymphoid features, such as Pro-B cells and early T-cell precursors (ETP), were more prominent in TCF3-PBX1-positive ALL (Figure 4C and Online Supplementary Table S7). The signatures of granulocyte-macrophage progenitor (GMP)/multi-lymphoid progenitor (MLP) and megakaryocyte-erythroid progenitor (MEP) were enriched in TCF3ZNF384- and TCF3-PBX1-positive ALL, respectively, whereas statistical significance was not observed. The above analyses could just as well detect the lack of specific TCF3-PBX1 features rather than the common features among cases with TCF3-ZNF384. Thus we subsequently compared the gene expression of TCF3-ZNF384positive ALL to that of wild-type ZNF384. There is the possibility that the wild-type ZNF384 patients still include a variety of subgroups harboring novel genetic abnormalihaematologica | 2017; 102(1)


Fusion genes involving ZNF384 in BCP-ALL

ties, and some of them might be related to ZNF384-related fusion genes by their gene expression. Indeed, hierarchical clustering analysis showed that wild-type ZNF384 patients were not necessarily located in the same cluster, and some of the cases were dispersed in the clusters of the major subtypes of BCP-ALL with conventional genetic abnormalities (Online Supplementary Figure S2D), indicating the heterogeneity of wild-type ZNF384 patients. Furthermore, hierarchical clustering of ZNF384-related fusion gene positive patients and wild-type ZNF384 patients indicated that 21 out of 104 wild-type ZNF384 patients located in the same cluster as ZNF384-related fusion gene positive patients (Online Supplementary Figure S2E). However, when we compared TCF3-ZNF384-positive patients and wild-type ZNF384 patients; excepting those located in the ZNF384related fusion gene positive cluster; they were clearly separated into a distinct cluster by hierarchical clustering (Online Supplementary Figure S2F), and the differential expression of 4,515 genes (up: 2,485, down: 2,030, >2.0) were identified (Online Supplementary Table S8). The B-cell developmental genes VPREB1 and IKZF1, but not IKZF2 or IKZF3, were listed as more highly expressed genes in wildtype ZNF384 ALL than in TCF3-ZNF384-positive ALL, and PAX5 also listed as a relatively highly expressed gene in wild-type ZNF384 ALL (1.83-fold). The transcriptional regulators such as BACH2, HIST1H3A, and LEF1 were also upregulated in wild-type ZNF384 ALL, while GATA3 and NCOR1, but not ERG and TOX, were upregulated in TCF3-ZNF384-positive ALL. The gene set enrichment analysis also revealed an enrichment for HSC, GMP and MLP signatures in TCF3-ZNF384-positive ALL while ProB, ETP and MEP were more prominent in wild-type ZNF384 ALL, whereas statistical significance was not obvious (Online Supplementary Figure S2G and Online Supplementary Table S7).

Clinical characteristics and outcomes of ZNF384-related fusion gene positive patients The clinical findings and outcomes of BCP-ALL patients with ZNF384-related fusion genes, other than EP300ZNF384, are summarized in Table 1. They were aged between 1 and 12 years (median: 3) at presentation and comprised of 12 males and 10 females. Their initial white blood cell (WBC) counts at presentation ranged from 1,220 to 150,200 (median: 26,975). The analysis of fluids obtained by lumbar puncture revealed no indication of central nervous system involvement, with the exception of one patient with TCF3-ZNF384 (Case-15). Thirteen out of 22 patients (59.1%) were classified into an IR at the initial diagnosis, based on an advanced age (4 patients), elevated WBC counts (7 patients), or both (2 patients). In addition, 5 patients were classified as HR (22.7%) based on markedly elevated WBC counts, but not an advanced age, and thus the SR included only 4 patients (18.2%). Five out of 15 (33.3%) patients with TCF3-ZNF384 had a relapse in the bone marrow, all of the patients received stem-cell transplantation, and 3 patients died. One patient each of TAF15- and CREBBP-ZNF384-positive patients had a relapse in the bone marrow, but both patients were salvaged by chemotherapy. It should be emphasized that no patient died in those with ZNF384-related fusion genes, other than TCF3-ZNF384. Importantly, 21 out of 22 patients showed a normal karyotype on cytogenetic analysis by conventional Gbanding, but the predicted chromosomal translocations, haematologica | 2017; 102(1)

including t(12;19)(p13;p13) for TCF3-ZNF384, t(12;17)(p13;q11) for TAF15-ZNF384, t(12;16)(p13;p13) for CREBBP-ZNF384, and t(4;12)(q21;p13) for BMP2KZNF384 were not detected at all (Table 1). The remaining patient with CREBBP-ZNF384 (Case-19) showed 47,X,add(X)(p22),t(12;12)(p13:q13),+21 at the initial diagnosis, but this was not consistent with the predicted chromosomal translocation. Since TCF3-ZNF384 was the most recurrent among ZNF384-related fusion genes detected in the pediatric BCP-ALL patients, we next compared the characteristics of TCF3-ZNF384-positive patients with those of wildtype ZNF384, as well as EP300-ZNF384- and TCF3-PBX1positive patients (Table 2). When compared with wildtype ZNF384, initial WBC counts and a trend to be classified in higher risk groups (IR and HR) were significantly higher in TCF3-ZNF384-positive patients (P<0.05 and P<0.01, respectively). In contrast, the age at diagnosis was not significantly different between TCF3-ZNF384-positive patients and those with wild-type ZNF384. The response to steroid monotherapy using the cut-off of 1,000/mL for the blast count in peripheral blood on day 8 was significantly poorer in TCF3-ZNF384-positive patients than in those with wild-type ZNF384 (P<0.01). As we reported previously, BCP-ALL patients with EP300-ZNF384 exhibit an advanced age but not significantly elevated WBC counts.11 Indeed, compared to the patients with wild-type ZNF384, those with EP300ZNF384 exhibit a significantly older age at presentation (P<0.01) but not significantly elevated WBC counts (P=0.37), as presented in Table 2. Therefore, the clinical features of TCF3-ZNF384-positive patients were clearly distinct from those of EP300-ZNF384-positive patients. In the case of TCF3-PBX1-positive ALL, initial WBC counts were significantly higher than in wild-type ZNF384, whereas other features were not significantly different. The 5-year EFS among TCF3-ZNF384-positive patients and those with wild-type ZNF384 were 50.0% and 73.3% (P=0.35) and the 5-year OS rates were 72.2% and 89.8% (P=0.15), respectively (Figure 5). Although there was no statistic significance, the clinical outcomes of TCF3ZNF384-positive patients were more unfavorable than in wild-type ZNF384 patients. In contrast, the 5-year EFS and the 5-year OS rates of EP300-ZNF384-positive patients were 83.3% and 100%, respectively, thus being more favorable than in TCF3-ZNF384-positive and wild-type ZNF384 patients.

Discussion We identified a novel fusion gene, BMP2K-ZNF384, in addition to the previously reported ZNF384-related fusion genes, including TCF3-, TAF15-, EWSR-, EP300-, "CREBBP-", "SYNRG-", and ARID1B-ZNF384, and thus 8 fusion partners for the ZNF384 gene have been identified so far.9-15,19-22 Considering the current condition, whereby the frequency of B-others in which specific cytogenetic abnormalities are not present are markedly decreasing, the incidence of ZNF384 -related fusion genes in our cohort was unexpectedly high. In the literature, 8 ALL patients with TAF15-ZNF384 have been reported.9,19-21 Similarly, 2 and 3 ALL patients with EWSR1- and TCF3-ZNF384, respectively, have also been described previously.9-10,20-22 Because 6 out of 13 patients in the literature are adults 127


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(>21 years), this is the first report on the high frequency of the recurrence of ZNF384-related fusion genes in childhood BCP-ALL in a single nation. It is possible that the differences in the outbreak frequency of ZNF384-related fusion genes in BCP-ALL depending on racial differences are present, and this type of fusion might be common in Asians but not in Caucasians. Alternatively, since ZNF384related fusion genes are difficult to detect with conventional G-banding, as we presented in this report, ZNF384related fusion genes may be found in Caucasians at a similar frequency to that in our cohort upon using more sensitive methods such as PCR or fluorescence in situ hybridization (FISH). As we presented herein, BCP-ALL patients with ZNF384-related fusion genes possess a characteristic immunophenotype. All of the BCP-ALL patients with ZNF384-related fusion genes, including EP300-ZNF384 that we reported recently, exhibit the dull or negative expression of CD10 and for the most part express CD13 and/or CD33. Our observations are consistent with previous reports because at least 8 among 13 patients with ZNF384-related fusion genes were CD10-negative and expressed CD13 and/or CD33 based on the literature.10,2022 Since ZNF384 is a commonality in all of these fusion genes, the aberrant function of the ZNF384 protein may be responsible for the characteristics of the immunophenotype. The fact that BCP-ALL patients with TCF3-PBX1 are clearly positive for CD10 and have no aberrant myeloid antigens should support the above notion. A correlation between the high expression of the GATA3 gene and CD13/CD33 expression on primary BCP-ALL blasts with ZNF384-related fusion genes was suggested,13 whereas the role of ZNF384-fusion proteins in the expression characteristics of the antigen remains largely unknown. BCP-ALL harboring MLL rearrangement also reveals the negative expression of CD10 and aberrant expression of myeloid antigens, while such patients frequently express CD65 and CD15 as aberrant myeloid antigens and are mainly accompanied by NG2 (7.1) expression.23 Thus, the presence of ZNF384-related fusion genes should be predictable, based on the characteristic immunophenotype of dull or negative CD10 expression accompanied by the aberrant expression of CD13 and/or CD33. In contrast to the similarity of the immunophenotypic characteristics, the clinical features of BCP-ALL with the ZNF384-related fusion gene are not uniform, and are thought to depend on the fusion partner gene of ZNF384. In the TCF3-ZNF384 fusion gene-positive ALL patients, more than half of the patients were classified into an IR or HR group because of an elevated WBC count at presentation, while their onset age was not advanced and there was no significant difference compared with wild-type ZNF384 patients. In addition, approximately half of the patients exhibited a poor response to prednisolone, and one-third relapsed, indicating that BCP-ALL patients with the TCF3-ZNF384 fusion gene include a certain proportion of patients with a poor response to conventional chemotherapy. It is noteworthy that stem cell transplantation is effective as salvage therapy for a part of the relapsed TCF3-ZNF384-positive patients. On the other hand, we previously reported that EP300-ZNF384 fusion gene-positive patients exhibited a relatively advanced age but no significant elevation of the WBC count at presentation, and showed a good response to prednisolone as well as a favorable response to conventional chemotherapy.11 128

Moreover, although one patient has relapsed, the OS rate of 9 patients with EP300-ZNF384 is currently 100%. Therefore, the clinical features are significantly different between TCF3-ZNF384-positive and EP300-ZNF384-positive patients. As the fusion genes involving the TCF3 gene, TCF3PBX1, TCF3-ZNF384, and TCF3-HLF are known, recent reports have indicated that the genomic and transcriptomic landscape of TCF3-HLF-positive ALL differs markedly from TCF3-PBX1-positive ALL, and that TCF3-HLF-positive ALL exhibited enriched stem cell and myeloid features, while lymphoid features were more prominent in TCF3-PBX1â&#x20AC;&#x201C;positive ALL.24 Moreover, the recurrent intragenic deletions of PAX5 or VPREB1 as well as activating mutations in the RAS signaling pathway genes (NRAS, KRAS, and PTPN11) were common in TCF3-HLF-positive ALL but rare in TCF3-PBX1-positive ALL. In the case of TCF3-ZNF384-positive ALL, abnormalities in such B-cell developmental genes were also revealed to be rare. However, the gene expression analysis of TCF3-ZNF384positive ALL revealed that PAX5 as well as VPREB1 expressions were lower compared with TCF3-PBX1-positive and wild-type ZNF384 ALL, and the gene expression profile of TCF3-ZNF384-positive ALL was markedly distinct from that of TCF3-PBX1-positive and wild-type ZNF384 ALL. In addition, the signature of TCF3-ZNF384positive ALL exhibited enrichment of the stem cell signature, similar to that of TCF3-HLF-positive ALL. The low expression of the gene regulating the pro- to pre-B-cell transition and expression of a HSC/myeloid-signature could be features of TCF3-ZNF384-positive ALL. Our data also indicate the activating mutations in RAS signaling pathway genes and CDKN2A/B-deletion in a part of the patients with TCF3-ZNF384. Further studies involving a large series of patients would be required to elucidate the prognostic impact of these gene abnormalities in a part of TCF3-ZNF384-positive patients. It has been shown that TAF15-, EWSR1-, and TCF3ZNF384 induce 3T3 fibroblast transformation.9,25 Since ZNF384 is a commonality in 8 related fusion genes identified in BCP-ALL, the aberrant function of the ZNF384 protein may participate in the development of BCP-ALL, whereas the precise function of ZNF384 in cellular transformation has yet to be clarified. Furthermore, the role of the defects in the function of TET family partner molecules in the development of ALL is still controversial. On the other hand, the loss of functions of both EP300 and CREBBP has been reported to participate in tumorigenesis by means of epigenetic alterations mediated by reduced histone acetylation activities.26-29 Recent reports also described the marked involvement of CREBBP mutations in the relapse of high hyperdiploid BCP-ALL.27-28 Therefore, both the loss of function in CREBBP or EP300 and the gain of aberrant ZNF384 function could cooperatively affect leukemogenesis in ALL harboring these two fusion genes. In contrast, the role of BMP2K abnormality in leukemogenesis is unclear. Further studies to investigate the molecular basis of ZNF384-related fusion proteins are required to clarify the precise role of the abnormalities of ZNF384 as well as its fusion partner genes in leukemogenesis. In conclusion, we clarified that ALL patients harboring ZNF384-related fusion genes constitute a subgroup with a characteristic immunophenotype in B-others of a Japanese cohort with an unexpectedly high incidence, and that the haematologica | 2017; 102(1)


Fusion genes involving ZNF384 in BCP-ALL

TCF3-ZNF384 fusion gene is the most recurrent. The clinical features of BCP-ALL with ZNF384-related fusion genes, however, depend on the functional defect of the fusion partner gene of ZNF384. Additional studies to elucidate the biological function of the ZNF384-related fusion protein should shed light on the molecular basis of the development of BCP-ALL. Acknowledgments We thank K. Itagaki, H. Yagi, Y. Katayama, A. Tamura, K. Takeda, K. Hayashi, and the staff of the Laboratory for Genotyping Development, Riken Center for Integrative Medical Sciences for their excellent data management and experimental assistance. We thank all members of the Committees of ALL and of Research and Diagnosis of TCCSG.

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Funding This work was supported in part by a Health and Labour Sciences Research Grant (3rd-term comprehensive 10-year strategy for cancer control H22-011), the Grant of the National Center for Child Health and Development (26-20), and the Advanced Research for Medical Products Mining Programme of the National Institute of Biomedical Innovation (NIBIO, 10-41, -42, -43, -44, -45), and Biobank Japan project funded by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and the Japan Agency for Medical Research and Development (AMED), and the Practical Research for Innovative Cancer Control from AMED. These funding sources played no role in the collection, analysis, or interpretation of the results, or in the writing of the manuscript and decision to submit it.

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ARTICLE EUROPEAN HEMATOLOGY ASSOCIATION

Acute Lymphoblastic Leukemia

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):130-138

Adults with Philadelphia chromosome–like acute lymphoblastic leukemia frequently have IGH-CRLF2 and JAK2 mutations, persistence of minimal residual disease and poor prognosis Tobias Herold,1,2,3 Stephanie Schneider,1 Klaus H. Metzeler,1,2,3 Martin Neumann,2,3,4 Luise Hartmann,1,2,3 Kathryn G. Roberts,5 Nikola P. Konstandin,1 Philipp A. Greif,1,2,3 Kathrin Bräundl,1,2,3 Bianka Ksienzyk,1 Natalia Huk,1 Irene Schneider,1 Evelyn Zellmeier,1 Vindi Jurinovic,6 Ulrich Mansmann,6 Wolfgang Hiddemann,1,2,3 Charles G. Mullighan,5 Stefan K. Bohlander,7 Karsten Spiekermann,1,2,3 Dieter Hoelzer,8 Monika Brüggemann,9 Claudia D. Baldus,2,3,4 Martin Dreyling1* and Nicola Gökbuget8* Department of Internal Medicine 3, University Hospital Grosshadern, LudwigMaximilians-Universität (LMU), München, Germany; 2German Cancer Consortium (DKTK), Heidelberg, Germany; 3German Cancer Research Center (DKFZ), Heidelberg, Germany; 4Department of Hematology, Oncology and Tumor Immunology, Charité Universitätsmedizin Berlin, Germany; 5Department of Pathology, St. Jude Children’s Research Hospital, Memphis, USA; 6Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität (LMU), München, Germany; 7Department of Molecular Medicine and Pathology, The University of Auckland, New Zealand; 8 Department of Medicine II, Goethe University Hospital, Frankfurt, Germany and 9 Department of Hematology, University Hospital Schleswig-Holstein Campus Kiel, Germany

1

*

MD and NG contributed equally to this work.

ABSTRACT

Correspondence: tobias.herold@med.uni-muenchen.de

Received: September 8, 2015. Accepted: August 23, 2016. Pre-published: August 25, 2016. doi:10.3324/haematol.2015.136366

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hiladelphia-like B-cell precursor acute lymphoblastic leukemia (Ph-like ALL) is characterized by distinct genetic alterations and inferior prognosis in children and younger adults. The purpose of this study was a genetic and clinical characterization of Ph-like ALL in adults. Twenty-six (13%) of 207 adult patients (median age: 42 years) with B-cell precursor ALL (BCP-ALL) were classified as having Ph-like ALL using gene expression profiling. The frequency of Ph-like ALL was 27% among 95 BCP-ALL patients negative for BCR-ABL1 and KMT2A-rearrangements. IGH-CRLF2 rearrangements (6/16; P=0.002) and mutations in JAK2 (7/16; P<0.001) were found exclusively in the Ph-like ALL subgroup. Clinical and outcome analyses were restricted to patients treated in German Multicenter Study Group for Adult ALL (GMALL) trials 06/99 and 07/03 (n=107). The complete remission rate was 100% among both Ph-like ALL patients (n=19) and the “remaining BCP-ALL” cases (n=40), i.e. patients negative for BCR-ABL1 and KMT2A-rearrangements and the Ph-like subtype. Significantly fewer Phlike ALL patients reached molecular complete remission (33% versus 79%; P=0.02) and had a lower probability of continuous complete remission (26% versus 60%; P=0.03) and overall survival (22% versus 64%; P=0.006) at 5 years compared to the remaining BCP-ALL patients. The profile of genetic lesions in adults with Ph-like ALL, including older adults, resembles that of pediatric Ph-like ALL and differs from the profile in the remaining BCP-ALL. Our study is the first to demonstrate that Ph-like ALL is associated with inferior outcomes in intensively treated older adult patients. Ph-like adult ALL should be recognized as a distinct, high-risk entity and further research on improved diagnostic and therapeutic approaches is needed. (NCT00199056, NCT00198991)

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Characterization of Ph-like ALL in adults

Introduction Acute lymphoblastic leukemia (ALL) is a heterogeneous disease with a complex pattern of molecular changes including fusion proteins, copy number alterations, and gene mutations.1 Considerable research is being dedicated to achieving better molecular characterization of ALL patients without known prognostic factors and to identifying patients with molecular aberrations that can be targeted by specific compounds (e.g. tyrosine kinase inhibitors in the case of the BCR-ABL1 fusion). In children, a subgroup of B-cell precursor ALL (BCP-ALL) with a gene expression profile similar to BCR-ABL1 (Philadelphia chromosome; Ph)-positive ALL, but lacking the BCR-ABL1 fusion gene, has been described and found to be associated with inferior outcomes compared to those of other subtypes of BCP-ALL.2,3 In pediatric patients this subgroup of ALL, named Ph-like or BCRABL1-like ALL, is associated with a number of genetic lesions that are potential candidates for targeted treatment.4 One study identified rearrangements of CRLF2 (IGH-CRLF2 or P2RY8-CRLF2) in approximately 50% of Ph-like ALL patients, and concomitant JAK1/JAK2 mutations in 50% of the CRLF2-rearranged patients.5 The remaining Ph-like ALL patients harbor a variety of kinase alterations, including translocations involving ABL class kinases or JAK2.4,5 Alterations (sequence mutations or deletions) of IKZF1 are also frequently observed in patients with Ph-like ALL.4,5 Several groups have verified these findings in children, adolescents and younger adults and demonstrated an increasing incidence of Ph-like ALL in adolescents and younger adults compared to children.59 We recently showed that the incidence of the Ph-like ALL subtype is highest in adolescents and younger adults (19-27%) and then decreases significantly with increasing age.10 So far, the data on the prognostic impact and molecular characteristics of Ph-like ALL in adults are limited and inconsistent.5,11 We set out to study the genetic characteristics of Ph-like ALL in adults, in comparison to other BCR-ABL1- and KMT2A-negative BCP-ALL, using gene expression profiling, mutational profiling by targeted amplicon sequencing and assessment of common copy number alterations. Furthermore, we analyzed the clinical characteristics and prognostic impact of the Ph-like ALL subtype in patients treated in prospective trials of the German Multicenter Study Group for Adult ALL (GMALL) for adult patients aged 15-65 years.

Methods Patients This analysis included 207 consecutive patients with newly diagnosed BCP-ALL studied between 1999 and 2005 at two reference laboratories.12,13 The routine diagnostic work-up included immunophenotyping, fluorescent in situ hybridization (FISH) for BCR-ABL1 and KMT2A (MLL) rearrangements (MLL-t), cytogenetics and molecular analyses of BCR-ABL1 translocations and MLL-t. Details of the patients’ characteristics are shown in Online Supplementary Table S1. The selection of patients for further molecular analysis was focused on two molecular BCP-ALL subgroups and based on available material: Ph-like ALL (n=16) and remaining BCP-ALL (Ph-negative, MLL-t-negative, non-Ph-like)

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(n=27). The study design is shown in Figure 1. Analyses of clinical characteristics and outcome were focused on patients treated in the GMALL trials 06/99 and 07/03. These trials incorporated intensive, pediatric-based therapy and risk-adapted allocation to allogeneic stem cell transplantation as previously described.14 Phnegative BCP-ALL patients with high white blood cell count (>30,000/mL), pro-B-ALL, or failure to achieve complete remission after induction phase I were allocated to the high-risk group. Both studies were approved by the institutional review board of the University of Frankfurt, Germany and are registered at clinicaltrials.gov (NCT00199056, NCT00198991). All patients had given signed informed consent to participation in the trials.

Gene expression analysis All patients were analyzed with the Affymetrix HGU-133 A, B Set (n=109) or with the Affymetrix HGU-133 Plus 2.0 chip (n=98). Details of sample preparation, hybridization and image acquisition have been described previously.15 No cell sorting was performed. The median percentage of leukemic cells in the samples analyzed was 90% (range, 30%-100%). The mean percentage was 87%. The HG-U133 A, B chips and HG-U133 Plus 2.0 chips were normalized separately by the robust multichip average method as described by Irizarry et al.16 Only the 44,754 probe sets present on both the Affymetrix HG-U133A, B chips and the HG-U133 Plus 2.0 chips were included in the analysis. To correct the batch effect resulting from the use of different chip designs, we applied an empirical Bayesian method as described previously.17 We used the published classification algorithm of Roberts et al. to identify Ph-like ALL patients by clustering.4 The analysis was performed based on 240 of the 257 probe sets used by Roberts et al. present in both chips (Online Supplementary Table S2). To validate this classification, microarray files were independently analyzed and classified using prediction analysis of microarrays.4 Patients with a predicted class 2 coefficient ≥0.5 were classified as having the Ph-like ALL gene expression signature. A direct comparison of the results from both algorithms is shown in the Online Supplement (Online Supplementary Table S3). Patients with high CRLF2 expression we defined as those with CRLF2 expression in the highest quintile of the whole dataset (Online Supplementary Figure S1). The gene expression dataset is publicly available (Gene Expression Omnibus ID GSE66006).

Analysis of minimal residual disease Minimal residual disease (MRD) was measured by quantitative polymerase chain reaction of individual IGH and TR rearrangements in a central laboratory as described previously.14 Molecular remission was defined as no MRD detection above the level of 10-4, confirmed with a minimum sensitivity of 10-4 according to published standards.18 The preferred time-point for evaluation of molecular response was before first consolidation. If not available, results of samples collected immediately after induction or after first consolidation were considered.

Analysis of IGH and CRLF2 rearrangements and P2RY8 deletions FISH analyses were performed on pretreatment samples using standard techniques and commercial probes according to the manufacturers’ instructions. The presence of IGH translocations was determined by interphase FISH using the LSI IGH Dual Color, Break Apart Rearrangement Probe (Abbott). In addition, a CRLF2 break apart probe and a P2RY8 deletion probe (both Cytocell aquarius) were used.

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Quantitative polymerase chain reaction for detection of the genomic P2RY8-CRLF2 fusion Genomic DNA was amplified using primers designed to flank the fusion breakpoint (P2RY8_q_fw: 5’-AGCCACCCTTCCTTTAATAACTCAT-3’, CRLF2_q_rv: 5’-TCTGAGCTCCATGGTTCGTCA-3’).19 Quantitative polymerase chain reaction was performed on a LightCycler 480 (Roche) using a probe for realtime detection of the fusion amplicons (P-C_q_pr: FAMTGGGCGGATCACGAGGTCAGGA-TAMRA).

Analysis of copy number alterations Copy number alterations were analyzed using the SALSA multiplex ligation-dependent probe amplification kit P335-B1 (MRC Holland) according to the manufacturer’s protocol.20 The probe mix contains probes for IKZF1, PAX5, ETV6, RB1, BTG1 and the BTG1 downstream region, EBF1, CDKN2A-CDKN2B, ZFY, JAK2 and for the Xp22.33 region (PAR region, CRLF2, CSF2RA, IL3RA and P2RY8 genes). The multiplex ligation-dependent probe amplification data were analyzed using Coffalyser.Net analysis software version 131211.1524 provided by the manufacturer using default settings. Reference samples were used as recommended in the manufacturer’s protocol.

Targeted amplicon sequencing A selection of 131 genes (Online Supplementary Table S4) known to be recurrently mutated in ALL were studied by targeted amplicon sequencing (Haloplex, Agilent) in 16 patients with Ph-like ALL and 23 with remaining BCP-ALL. The resulting libraries were sequenced in three runs on a MiSeq instrument. A quality metrics summary of sequencing data is shown in Online Supplementary Table S5. Sequence data were aligned to the human reference genome (version hg19) using BWA-MEM.21,22 Single nucleotide variants and short insertions or deletions were called using VarScan 2 and Pindel, respectively.23 Only genomic regions with a coverage of ≥30 fold were analyzed. Non-synonymous variants (single nucleotide polymorphisms and indels) in coding regions with ≥10 variant reads of specific leukemia-associated genes were

reported (Online Supplementary Table S6). Details regarding the analysis algorithm have been published previously.17

Statistics Statistical analyses were performed using R 3.0.1 software24 and routines from the biostatistics software repository Bioconductor and SPSS version 21.0 (SPSS Inc., Chicago, IL, USA). The twosided Fisher exact test was used to compare categorical variables, while the Wilcoxon - Mann-Whitney test was applied for continuous variables. All patients whose clinical characteristics and outcome were analyzed were registered at the GMALL Study Center, where statistical analysis was performed with the SAS program (SAS-PC, version 8.02; SAS Institute, Cary, NC, USA). For statistical comparisons of the clinical variables, the two-sided Fisher exact test was applied for categorical variables and the Wilcoxon test for continuous variables. The survival analysis was based on the Kaplan-Meier method. Overall survival was calculated from date of diagnosis until death or last follow-up. Continuous complete remission (remission duration) was calculated from date of first complete remission to relapse or last follow-up in complete remission including patients with death in complete remission. Disease-free survival was calculated from date of first complete remission to relapse or death from any cause. Survival rates are given as probabilities of survival at 5 years, with a 95% confidence interval. The log-rank test was used to compare survival curves. A Cox model was used for multivariate analysis of the impact of different factors on remission duration and overall survival. For all analyses, P values ≤0.05 are considered statistically significant.

Results Identification of patients with a Philadelphia-like gene expression profile In total, 207 patients with BCP-ALL were analyzed (Figure 1), of whom 95 were negative for BCR-ABL1 and

Figure 1 Study design. Flow chart showing the study design and distribution of patients.

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Characterization of Ph-like ALL in adults

MLL-t. Of the 207 patients, we classified 26 patients (13%) as having Ph-like ALL based on their gene expression profile and the absence of the BCR-ABL1 fusion: this corresponds to a prevalence of 27% (26/95) in patients negative for BCR-ABL1 and MLL-t. The other 69 patients were then classified as having â&#x20AC;&#x153;remaining BCP-ALLâ&#x20AC;? (Phnegative, MLL-t-negative, non-Ph-like) and served as the reference group, similarly to another recent study in adults.11 Other studies, particularly in pediatric populations, compared Ph-like ALL to B-other patients defined as patients negative for the BCR-ABL1, MLL-t, ETV6-RUNX1 or TCF3-PBX1 fusions and hyperdiploidy or hypodiploidy. The incidence of Ph-like ALL in B-other patients in our cohort was 32% (26/82). Since there is no generally accepted definition of highrisk features of adult ALL, it is unclear whether the B-other or remaining BCP-ALL group is a better control group for comparison with the Ph-like subtype. To account for this difficulty, we mention both comparisons in this report. A detailed description of the age distribution of the patients and their immunophenotypic and molecular parameters is given in Online Supplementary Figure S2 and in Online Supplementary Table S1.

Philadelphia-like acute lymphoblastic leukemia is associated with specific genetic lesions and expression changes Most patients with high CRLF2 expression clustered in the Ph-like ALL subgroup (15/26, 58% versus 7/69, 10% of remaining BCP-ALL; P<0.001). Online Supplementary Figure S3 shows the distribution of CRLF2 expression in BCP-ALL subtypes. Further molecular analysis was focused on the 43 patients of the Ph-like and remaining BCP-ALL subgroups (Ph-like ALL: n=16; remaining BCP-ALL: n=27; Figure 2A/B). The selection was based on available material. Unfortunately, no RNA or cDNA for further molecular characterization, especially for ABL or JAK fusions, was available. All patients with an IGH-CRLF2 rearrangement (n=6) were in the Ph-like subgroup (only 29/43 patients could be analyzed), whereas P2RY8-CRLF2 fusions (n=2) were only found in the remaining BCP-ALL group (P=0.002 and P>0.05, respectively). Analysis of common copy number alterations by multiplex ligation-dependent probe amplification revealed that 77% of patients (33/43) had at least one deletion. Deletions of IKZF1 were significantly more common in Ph-like ALL than in remaining BCP-ALL (13/16, 81% versus 7/27, 30%; P<0.001). Mutational profiling of 131 genes recurrently mutated in ALL was performed by targeted amplicon sequencing (Online Supplementary Table S4). A total of 115 non-synonymous mutations affecting 50 genes was identified. At least one mutation could be identified in 92% (36/39) of patients. The distribution of the most common mutations is shown in Figure 2A and in more detail in Online Supplementary Table S6. Nine mutations in JAK2 were identified in seven patients. These mutations were found exclusively in the Ph-like ALL subgroup (7/16, 44% versus 0/23, 0%; P<0.001), and commonly associated with CRFL2 over-expression. The majority of JAK2 mutations (7/9) resulted in the change of amino acid R683 to G (n=5) or S (n=2). All mutations spared codon V617 and were located in the protein tyrosine kinase (PTK) domains (Online Supplementary Figure S4). Rearrangements or sequence mutations of CRLF2 were found exclusively in the Ph-like subgroup (7/16 versus 0/23; haematologica | 2017; 102(1)

P<0.001). Molecular alterations associated with ALL subtypes and co-occurrence of certain molecular alterations are shown in Figure 2B. The Ph-like ALL subgroup was associated with alterations of IKZF1 (P<0.001), CRLF2 (P<0.001), JAK2 (P<0.001), BTG1 (P=0.02) and high CRLF2 expression (P<0.001).

Clinical characteristics and prognosis of Philadelphialike acute lymphoblastic leukemia The clinical and outcome analyses were restricted to BCP-ALL patients intensively treated in GMALL trials 06/99 and 07/03 (n=107). This group contained Ph-positive (n=37), Ph-like (n=19), MLL-t (n=11) and remaining BCP-ALL (n=40) patients. The analysis focused on the comparison of Ph-like and remaining BCP-ALL patients. No significant differences in baseline characteristics, including age, sex, white-cell count, hemoglobin, platelet count and risk group, were observed between the Ph-like and remaining BCP-ALL subgroups (Table 1). Fifty-eight percent (11/19) of the Ph-like patients belonged to the standard-risk group, compared to 50% of the remaining BCP-ALL group. The complete remission rate after induction was 100% for both the Ph-like and the remaining BCP-ALL patients. However, significantly fewer patients reached molecular remission in the Ph-like ALL subgroup (4/12, 33% versus 15/19, 79%; P=0.02) (Table 2). Patients with Ph-like ALL had a significantly inferior probability of continuous complete remission at 5 years (26% versus 60%; P=0.03) (Figure 3). Overall, 12/19 Ph-like patients relapsed very rapidly after induction therapy with a median time to relapse of only 122 days (range, 25-844) compared to 555 days (range, 96-1248) in the remaining BCPALL group (P=0.03). Consequently, the realization of stem cell transplantation in first complete remission as stipulated in the protocol was significantly lower among high-risk patients in the Ph-like subgroup than among high-risk patients in the remaining BCP-ALL group (2/8, 25% versus 15/20, 75%; P=0.01). Overall, three patients with Ph-like ALL (2 high risk, 1 standard risk) received a stem cell transplant in first complete remission (1 relapsed after the transplant, 1 died in complete remission and 1 patient is in continuous complete remission). Overall survival (22% versus 64% at 5 years; P=0.006) and disease-free survival (19% versus 57% at 5 years, P<0.001) were significantly inferior in the Ph-like group than in the remaining BCPALL group (Figure 3). The outcome of Ph-like ALL patients was particularly poor within the high-risk group, mainly because of early relapse (Online Supplementary Figure S5AD). There was no significant difference in results when patients who underwent stem cell transplantation in first complete remission were excluded (Online Supplementary Figure S5E-F) and if Ph-like ALL patients were compared to the more stringently defined B-other ALL group (Table 3). For Ph-like ALL patients with available MRD data (n=12), the molecular response was a significant predictor of relapse. One of four patients with molecular complete remission relapsed compared to seven of eight patients who did not achieve molecular complete remission. The remission duration was significantly different between patients with Ph-like ALL who did or did not achieve molecular complete remission (log-rank test, P=0.02).

Association of molecular alterations with survival To further characterize the influence of different variables on survival in Ph-like and remaining BCP-ALL, uni133


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variate Cox analyses were used. The variables age (>35 years), JAK2 and NRAS mutation, IKZF1 alteration and the Ph-like subtype were significant predictors of inferior overall survival (Table 4), whereas Ph-like subtype, BTG deletion, IKZF1 alterations and JAK2 mutations were significant predictors of remission duration. Because of the limited overlap of patients with MRD

analyses and further molecular characterization we calculated a multivariate model focusing the analysis on remission duration in 31 patients with information on Ph-like subtype and MRD. Both factors maintained significance with P=0.008 and a hazard ratio of 3.4 for molecular response and P=0.04 with a hazard ratio of 1.8 for Ph-like status. In a similar model for overall survival only molecular response main-

Figure 2. Distribution of genetic alterations in Ph-like and remaining BCP-ALL. (A) Panel A shows the distribution of common mutations, deletions and fusions and CRLF2 expression in Ph-like and remaining BCPALL (Ph-negative, MLL-t negative, non-Ph-like) patients. The definition of kinase and B-cell pathway reported by Roberts et al.5 was used. Patients represented by light gray boxes for Relapse and Death were not treated in GMALL trials 06/99 and 07/03 and no clinical data were available for them. Patients marked with â&#x20AC;&#x153;*â&#x20AC;? had either ETV6-RUNX1 or TCF3-PBX1 fusions or ALL with high hyperdiploidy. (B) Panel B shows the correlation of common mutations, deletions and fusions and CRLF2 expression in Phlike and remaining BCP-ALL (Ph-negative, MLL-t negative, non-Ph-like).

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Characterization of Ph-like ALL in adults

tained significance with P=0.002 and a hazard ratio of 4.7.

In our data set, FISH analysis for IGH-CRLF2 rearrangements and sequencing of JAK2 PTK was sufficient to identify Ph-like cases with a sensitivity and

specificity of 63% and 100%, respectively. Using these parameters we were able to predict the Ph-like ALL subtype (Online Supplementary Figure S6) in a publicly available dataset (n=1,726)5 with a sensitivity of 33% and specificity of 100% regardless of age groups. If only patients aged ≥16 years were considered 41% of Ph-like cases could be identified (specificity 100%). The frequency of JAK2 mutations and IGH-CRLF2 rearrangements

Table 1. Characteristics of BCP-ALL patients treated in GMALL studies 06/99 and 07/03.

Table 2. Clinical and molecular response of Ph-like and remaining BCP-ALL treated on GMALL studies 06/99 and 07/03.

IGH-CRLF2 and/or JAK2 mutations identify a subset of Philadelphia-like acute lymphoblastic leukemia with high specificity

Evaluable

Ph-like ALL N=19

Age median (range) 31 (16-59) ≤ 35 years 12 (63%) > 35 years 7 (37%) Gender male 14 (74%) female 5 (26%) Subtype pro-B 1 (5%) common pre-B 18 (95%) Risk group high risk 8 (42%) standard risk 11 (58%) WBC /mL* ≤ 30,000 13 (68%) > 30,000 6 (32%)

Remaining BCP-ALL N=40

P-value

27 (16-64) 29 (73%) 11 (28%)

0.31 0.55

25 (63%) 15 (38%)

0.56

2 (5%) 38 (95%)

1.00

20 (50%) 20 (50%)

0.59

23 (61%) 15 (39%)

0.77

Ph-like ALL

Evaluable Complete remission Molecular remission (n=31 evaluable)

Remaining BCP-ALL

Response to induction N=19 N=40 19 (100%) 40 (100%) 4/12 (33%) 15/19 (79%)

Long-term outcome Continuous complete remission 5 (26%) 24 (60%) Death in complete remission 2 (11%) 3 (7%) Relapse 12 (63%) 13 (32%) Median time to relapse (days) 122 (25-844) 555 (96-1248)

P-value

n.a. 0.02

0.03 0.05 0.03

* Two patients did not have a documented white blood cell count (WBC).

A

B

C

Figure 3. Disease-free survival, remission duration and overall survival of patients with Ph-like or remaining BCP-ALL. (A) Disease-free survival, (C) remission duration and (C) overall survival in ALL patients treated in GMALL trials 06/99 and 07/03, comparing the Ph-like ALL subgroup with remaining BCP-ALL patients (Ph-negative, MLL-t negative, non-Ph-like).

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increased significantly with older age (<16 years versus ≥16 years; P=0.008).

Table 3. Comparison of outcomes of the Ph-like ALL subgroup with patients classified as having B-other ALL (negative for the BCR-ABL1, MLLt, ETV6-RUNX1 or TCF3-PBX1 fusions and hyperdiploidy or hypodiploidy).

Discussion

Analysis

Group

N. Probability at 5 years P-value

Overall survival

B-other Ph-like B-other Ph-like B-other Ph-like

33 19 33 19 33 19

The aim of our study was to retrospectively identify Phlike ALL in a cohort of adult patients up to the age of 64 years treated on prospective protocols of the GMALL study group. Several groups have demonstrated the adverse prognostic impact of the Ph-like ALL subtype in children, adolescents and younger adults and more recent-

Remission duration Disease-free survival

0.65 0.22 0.62 0.24 0.60 0.19

0.006 0.001 0.0005

Table 4. Univariate prognostic factors in Ph-like ALL and remaining BCP-ALL patients treated in GMALL studies 06/99 and 07/03.

Variable Age (years) ≤ 35 > 35 CRLF2 higha no yes Ph-like subtype no yes Risk group high risk standard risk White blood cell count ≤ 30,000/mL > 30,000/mL BTG deletion no yes CDKN2 deletion no yes EBF1 deletion no yes ETV6 deletion no yes IKZF1 alterationb no yes CRLF2 alterationb no yes JAK2 mutation no yes NRAS mutation no yes PAX5 alterationb no yes SETD2 mutation no yes

Nc

5-year overall survival

P

N.

5-year continuos complete remission

P

5-year disease free survival

P

41 18

0.64 0.17

0.001

41 18

0.55 0.38

0.25

0.53 0.24

0.02

44 15

0.58 0.29

0.08

44 15

0.55 0.38

0.13

0.5 0.3

0.05

40 19

0.64 0.22

0.006

40 19

0.62 0.24

0.0005

0.57 0.19

0.0004

28 31

0.46 0.53

0.35

28 31

0.55 0.48

0.87

0.43 0.46

0.39

36 21

0.55 0.48

0.46

36 21

0.52 0.5

0.53

0.48 0.43

0.37

21 6

0.48 0.17

0.13

29 6

0.64 0

<0.0001

0.5 0

0.0001

16 11

0.36 0.7

0.16

16 11

0.47 0.45

0.51

0.33 0.45

0.84

23 4

0.49 0.5

0.99

23 4

0.45 0.67

0.35

0.37 0.5

0.53

18 9

0.46 0.56

0.82

18 9

0.38 0.63

0.3

0.29 0.56

0.23

10 13

0.9 0.23

0.0075

10 13

0.7 0.15

0.02

0.79 0.2

0.02

19 4

0.52 0.33

0.34

19 4

0.48 0.37

0.67

0.41 0.25

0.43

18 5

0.61 0

0.04

18 5

0.57 0

0.04

0.49 0

0.03

17 6

0.29 1

0.009

17 6

0.37 0.67

0.25

0.28 0.67

0.12

13 10

0.58 0.4

0.46

13 10

0.56 0.36

0.38

0.46 0.3

0.48

17 6

0.42 0.67

0.3

17 6

0.44 0.5

0.9

0.34 0.5

0.57

High CRLF2 expression was defined as the highest quintile of CRLF2 expression in the whole dataset. bAlteration means any genetic change (e.g. mutations, deletions and translocations) .cSubgroup sizes for clinical, copy number and gene sequencing variables differ because of limitations in material availability. Statistically significant differences are shown in bold.

a

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Characterization of Ph-like ALL in adults

ly in adults.2,3,5,11 However, data from adults with Ph-like ALL are still limited and inconsistent with regards to classification algorithms, the frequency of additional genetic alterations and the impact of this ALL subtype on survival.5,11 Our study used a simplified version of the St. Jude classifier2 to identify Ph-like ALL patients. The classification approach was independently validated using prediction analysis of microarrays and showed high concordance.4 There were three additional cases classified as Ph-like ALL by prediction analysis of microarrays, but they had weaker coefficients, and likely harbored sequence mutations rather than kinase rearrangements (Online Supplementary Table S3). A recently published study comparing the St. Jude classifier with the DCOG/Erasmus MC signature3,9 has shown poor concordance, with the DCOG/Erasmus MC classifier identifying nearly twice as many patients as Ph-like compared to the St. Jude classifier.25 In our study, using the St. Jude classification algorithm, the overall frequency of the Ph-like subtype in adults with BCP-ALL was 13% and 32% in B-other ALL, which is in the range of published data.5,10,11 Beside our analysis, two other studies investigated Phlike ALL in adult patients.5,11 When comparing these studies, it is important to note the difference in patient cohorts, classification algorithms and treatment protocols. A recently reported study by the HOVON group analyzed the clinical course of 21 Ph-like adolescents, younger adults and older adults (median age 25 years; range, 15-59) and compared it to that of 50 patients with remaining BCP-ALL (median age 34 years; range, 16-68).11 The landmark study by Roberts et al. included 710 adolescents and young adults with B-other ALL (n=169 Ph-like), with a median age of <20 years and an upper age limit of 39 years.5 The 19 Ph-like patients in our trial who were evaluable for outcome analysis had a median age of 31 years (range, 16-59) and were compared to 40 remaining BCPALL patients with a median age of 27 years (range, 16-64). Whereas the study by Roberts et al. focused on younger ALL patients, the HOVON trial and our study analyzed the clinical course of a cohort of older adults with BCPALL. Regarding the treatment schedule, only three of the 21 Ph-like ALL patients in the HOVON cohort were treated according to pediatric-inspired, high-intensive protocols (HOVON-70 or HOVON-71). The adolescents and younger adults analyzed by Roberts et al. were treated in eight different clinical trials by the Childrenâ&#x20AC;&#x2122;s Oncology Group (COG), the Eastern Cooperative Oncology Group (ECOG), the MD Anderson Cancer Center (MDACC), Alliance â&#x20AC;&#x201C; Cancer and Leukemia Group B protocols (CALGB) and St. Jude Hospital. These trials included various protocols and treatment schedules. Our own study included only patients intensively treated with GMALL pediatric-based protocols (06/99 and 07/03) and these patients therefore constitute a homogenously treated cohort with approaches comparable to current therapeutic strategies. This may explain the differences in complete remission rates (HOVON: 71%, St. Jude: not reported, GMALL: 100%) in Ph-like ALL patients between our analyses.5,11 In the HOVON study there were no significant differences in event-free survival and overall survival between adult patients with Ph-like ALL and those with remaining haematologica | 2017; 102(1)

BCP-ALL, although there was a trend to higher relapse rates among the former.11 Roberts et al. reported that adolescents and younger adults with Ph-like ALL had inferior event-free survival and overall survival and a significant association with elevated MRD levels (analyzed only among patients included in COG trials).5 Our study demonstrated inferior disease-free survival, remission duration and overall survival, higher relapse rates and persistence of MRD in adults with Ph-like ALL. The most obvious reason for the discrepancies between the study by Roberts et al., our study and the HOVON analysis is the different classification algorithm used in the HOVON study which identified a different subset of patients. This is further accentuated by the differences in molecular findings. Deletions of IKZF1 were found in only 35% of cases of Ph-like ALL in the HOVON study (mutations not analyzed), whereas Roberts et al. found IKZF1 alterations (point mutations or deletions) in 68% of patients. We identified alterations of IKZF1 in 81% of the patients with Ph-like ALL. The higher incidence in our cohort compared to that in the St. Jude study could be due to an association of these alterations with older age. CRLF2 expression, JAK2 mutations or IGH-CRLF2 translocations were not reported in the HOVON study. We found that adult Phlike ALL is also strongly associated with JAK2 mutations (44%), CRLF2 alterations (44%) and increased CRLF2 expression (58%), which is in accordance with the results in adolescents and younger adults reported by Roberts et al. Furthermore, we show that the frequency of JAK2 mutations and IGH-CRLF2 translocations increases significantly with age. Unfortunately, a full genetic characterization, for example by RNA-sequencing, was not possible because of limitations in available material, especially in cases with low CRLF2 expression. The results of studies using the St. Jude classification algorithm demonstrate that some cases of Ph-like ALL are characterized by highly specific molecular alterations (especially JAK2 mutations and IGH-CRLF2). As gene expression analysis26 is not performed in routine diagnostics, testing for JAK2 PTK mutations and the IGH-CRLF2 translocation may represent a first and easily implementable option to identify at least a subgroup of patients with Ph-like ALL with high specificity until a consensus classification is available. It is, however, important to note that other studies showed that JAK2 mutations and IGHCRLF2 fusions were not associated with the Ph-like ALL subtype in all cases.4 Furthermore, we were not able to demonstrate a prognostic impact of the combined analysis of these variables in our dataset (data not shown). This analysis is preliminary and has currently no clinical consequence but could help to promote further research. Further studies are warranted to evaluate the specificity and prognostic impact of these alterations for the classification of Ph-like ALL. The optimal treatment of Ph-like ALL, and particularly of those patients with persistent MRD remains to be defined. Specifically, the potential impact of stem cell transplantation in Ph-like ALL needs to be established. In a recent pediatric trial, the negative prognostic impact of Ph-like ALL was almost completely eliminated by MRDbased treatment stratification including more intensive post-remission therapy and stem cell transplantation in Ph-like ALL patients with persistent MRD.8 Due to the limited number of patients in whom MRD was evaluated in our study, it remains unclear whether the Ph-like sub137


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type would still have an independent prognostic impact, if MRD evaluation were to be performed in all adult patients. However, so far, our study is the first to report MRD data for older adults with Ph-like ALL. In our study only 4/12 (25%) patients with Ph-like ALL achieved a molecular complete remission and three of them remain in continuous complete remission. Whether the same would occur in larger cohorts of adult patients needs to be addressed by future studies. The relevance of molecular response in the general BCP-ALL subgroup has already been shown in far larger groups of patients who have undergone MRD assessment at distinct, well-defined time-points.14 The current strategy of the GMALL study group includes stem cell transplantation preceded by targeted therapies, such as antibody therapies,27 whenever available in patients with persistent MRD after first consolidation (including Ph-like ALL). In summary, our study shows that the molecular and clinical features of adults with Ph-like ALL resemble those characteristic of pediatric Ph-like ALL patients. For the first time, our study demonstrates the negative prognostic impact on survival of the Ph-like ALL subtype in

References 1. Inaba H, Greaves M, Mullighan CG. Acute lymphoblastic leukaemia. Lancet. 2013;381 (9881):1943-1955. 2. Mullighan CG, Su X, Zhang J, et al. Deletion of IKZF1 and prognosis in acute lymphoblastic leukemia. N Engl J Med. 2009;360 (5):470-480. 3. Den Boer ML, van Slegtenhorst M, De Menezes RX, et al. A subtype of childhood acute lymphoblastic leukaemia with poor treatment outcome: a genome-wide classification study. Lancet Oncol. 2009;10(2):125134. 4. Roberts KG, Morin RD, Zhang J, et al. Genetic alterations activating kinase and cytokine receptor signaling in high-risk acute lymphoblastic leukemia. Cancer Cell. 2012;22(2):153-166. 5. Roberts KG, Li Y, Payne-Turner D, et al. Targetable kinase-activating lesions in Phlike acute lymphoblastic leukemia. N Engl J Med. 2014;371(11):1005-1015. 6. Iijima K, Yoshihara H, Ohki K, et al. An analysis of Ph-like ALL in Japanese patients. Blood. 2013;122(21):352-352. 7. Silvestri D, Vendramini E, Fazio G, et al. Philadelphia-like signature in childhood acute lymphoblastic leukemia: the AIEOP Experience. Blood. 2013;122(21):353-353. 8. Roberts KG, Pei D, Campana D, et al. Outcomes of children with BCR-ABL1-like acute lymphoblastic leukemia treated with risk-directed therapy based on the levels of minimal residual disease. J Clin Oncol. 2014;32(27):3012-3020. 9. van der Veer A, Waanders E, Pieters R, et al. Independent prognostic value of BCRABL1-like signature and IKZF1 deletion, but not high CRLF2 expression, in children with B-cell precursor ALL. Blood. 2013;122(15): 2622-2629. 10. Herold T, Baldus CD, Gokbuget N. Ph-like acute lymphoblastic leukemia in older

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intensively treated older adults. Future studies should elucidate the role of thorough MRD monitoring and allogeneic transplantation, which are potentially effective in the Ph-like ALL subgroup. Acknowledgments The authors thank all participants and recruiting centers of the GMALL trials. Funding This work was supported by a grant from the Friedrich-Baur Stiftung to TH, start-up funding from the Ludwig-MaximiliansUniversität to KHM (FöFoLe 783) and by grant support from Deutsche Forschungsgemeinschaft [DFG SFB 1243, TP A06 (KHM, KS)]; Wilhelm Sander Stiftung [no. 2013.086.1 (TH, UM and KS)]; and the German Cancer Consortium (Deutsches Konsortium für Translationale Krebsforschung, Heidelberg, Germany). The CRLF2 and P2RY8 FISH probes were kindly provided by Cytocell aquarius. The GMALL studies were supported by Deutsche Krebshilfe (702657Ho2) and the José Carreras Leukämie-Stiftung (DJCLS R10/11). SKB is supported by Leukaemia & Blood Cancer New Zealand and the family of Marijanna Kumerich.

adults. N Engl J Med. 2014;371(23):2235. 11. Boer JM, Koenders JE, van der Holt B, et al. Expression profiling of adult acute lymphoblastic leukemia identifies a BCR-ABL1like subgroup characterized by high nonresponse and relapse rates. Haematologica. 2015;100(7):e261-264. 12. Haferlach T, Kohlmann A, Wieczorek L, et al. Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group. J Clin Oncol. 2010;28(15):2529-2537. 13. Haferlach T, Kohlmann A, Schnittger S, et al. Global approach to the diagnosis of leukemia using gene expression profiling. Blood. 2005;106(4):1189-1198. 14. Gokbuget N, Kneba M, Raff T, et al. Adult patients with acute lymphoblastic leukemia and molecular failure display a poor prognosis and are candidates for stem cell transplantation and targeted therapies. Blood. 2012;120(9):1868-1876. 15. Herold T, Jurinovic V, Metzeler KH, et al. An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia. Leukemia. 2011;25(10):1639-1645. 16. Irizarry RA, Hobbs B, Collin F, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003;4(2):249-264. 17. Herold T, Metzeler KH, Vosberg S, et al. Isolated trisomy 13 defines a homogeneous AML subgroup with high frequency of mutations in spliceosome genes and poor prognosis. Blood. 2014;124(8):13041311. 18. Bruggemann M, Schrauder A, Raff T, et al. Standardized MRD quantification in European ALL trials: proceedings of the Second International Symposium on MRD assessment in Kiel, Germany, 18-20 September 2008. Leukemia. 2010;24(3):521535.

19. Morak M, Attarbaschi A, Fischer S, et al. Small sizes and indolent evolutionary dynamics challenge the potential role of P2RY8-CRLF2-harboring clones as main relapse-driving force in childhood ALL. Blood. 2012;120(26):5134-5142. 20. Schwab CJ, Jones LR, Morrison H, et al. Evaluation of multiplex ligation-dependent probe amplification as a method for the detection of copy number abnormalities in B-cell precursor acute lymphoblastic leukemia. Genes Chromosomes Cancer. 2010;49(12):1104-1113. 21. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):17541760. 22. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics. 2010;26(5):589-595. 23. Li H, Handsaker B, Wysoker A, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16): 2078-2079. 24. R_Core_Team. R: A Language and Environment for Statistical Computing. 25. Boer JM, Marchante JR, Evans WE, et al. BCR-ABL1-like cases in pediatric acute lymphoblastic leukemia: a comparison between DCOG/Erasmus MC and COG/St. Jude signatures. Haematologica. 2015;100(9):e354357. 26. Kang H, Roberts KG, Chen I-ML, et al. Development and validation of a highly sensitive and specific gene expression classifier to prospectively screen and identify B-precursor acute lymphoblastic leukemia (ALL) patients with a Philadelphia chromosomelike (“Ph-like” or “BCR-ABL1-Like”) Signature Blood. 2013;122(21):826-826. 27. Topp MS, Gokbuget N, Zugmaier G, et al. Long-term follow-up of hematologic relapse-free survival in a phase 2 study of blinatumomab in patients with MRD in Blineage ALL. Blood. 2012;120(26):51855187.

haematologica | 2017; 102(1)


ARTICLE

Acute Lymphoblastic Leukemia

Improving results of allogeneic hematopoietic cell transplantation for adults with acute lymphoblastic leukemia in first complete remission: an analysis from the Acute Leukemia Working Party of the European Society for Blood and Marrow Transplantation

Sebastian Giebel,1 Myriam Labopin,2,3 Gerard Socié,4 Dietrich Beelen,5 Paul Browne,6 Liisa Volin,7 Slawomira Kyrcz-Krzemien,8 Ibrahim Yakoub-Agha,9 Mahmoud Aljurf,10 Depei Wu,11 Mauricette Michallet,12 Renate Arnold,13 Mohamad Mohty2* and Arnon Nagler3,14*

EUROPEAN HEMATOLOGY ASSOCIATION

Ferrata Storti Foundation

Haematologica 2017 Volume 102(1):139-149

Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Poland; 2Hospital St. Antoine, Paris, France; 3Acute Leukemia Working Party of the EBMT; 4Hospital St. Louis, Paris, France; 5University Hospital, Essen, Germany; 6St. James’s Hospital - Trinity College, Dublin, Ireland; 7Helsinki University Central Hospital, Finland; 8Silesian Medical University, Katowice, Poland; 9University Lille, Inserm, CHU Lille, U995 - LIRIC - Lille Inflammation Research, International Center, Lille, France; 10 King Faisal Specialist Hospital & Research Centre, Riyadh, Saudi Arabia; 11First Affiliated Hospital of Soochow University, Suzhou, China; 12Centre Hospitalier Lyon Sud Service Hematologie, Lyon, France; 13Charité Universitätsmedizin Berlin - Campus Virchow Klinikum Berlin, Germany and 14Chaim Sheba Medical Center, Tel-Hashomer, Israel

1

*MM and AN contributed equally to this work

ABSTRACT

A

llogeneic hematopoietic cell transplantation is widely used to treat adults with high-risk acute lymphoblastic leukemia. The aim of this study was to analyze whether the results changed over time and to identify prognostic factors. Adult patients treated between 1993 and 2012 with myeloablative allogeneic hematopoietic cell transplantation from HLA matched sibling (n=2681) or unrelated (n=2178) donors in first complete remission were included. For transplantations from sibling donors performed between 2008 and 2012, 2year probabilities of overall survival were: 76% (18-25 years old), 69% (26-35 and 36-45 years old) and 60% (46-55 years old). Among recipients of transplantations from unrelated donors, the respective survival rates were 66%, 70%, 61%, and 62%. In comparison with the 19932007 period, significant improvements were observed for all age groups except for the 26-35-year old patients. In a multivariate model, transplantations performed between 2008 and 2012, when compared to 1993-2007, were associated with significantly reduced risks of nonrelapse mortality (Hazard Ratio 0.77, P=0.00006), relapse (Hazard Ratio 0.85, P=0.007), treatment failure (Hazard Ratio 0.81, P<0.00001), and overall mortality (Hazard Ratio 0.79, P<0.00001). In the analysis restricted to transplantations performed between 2008 and 2012, the use of total body irradiation-based conditioning was associated with reduced risk of relapse (Hazard Ratio 0.48, P=0.004) and treatment failure (Hazard Ratio 0.63, P=0.02). We conclude that results of allogeneic hematopoietic cell transplantation for adults with acute lymphoblastic leukemia improved significantly over time. Total body irradiation should be considered as the preferable type of myeloablative conditioning.

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Correspondence: sgiebel@io.gliwice.pl

Received: March 3, 2016. Accepted: September 22, 2016. Pre-published: September 29, 2016. doi:10.3324/haematol.2016.145631

Check the online version for the most updated information on this article, online supplements, and information on authorship & disclosures: www.haematologica.org/content/102/1/139

©2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is required for any other use.

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Introduction Allogeneic hematopoietic cell transplantation (alloHCT) is widely used for the treatment of adult patients with acute lymphoblastic leukemia (ALL) in first complete remission (CR1) with high risk of relapse. It allows for administration of high doses of total body irradiation (TBI) or myeloablative chemotherapy, which may contribute to eradication of residual disease. The effect may be further strengthened by graft-versus-leukemia reaction driven by lymphocytes of donor origin.1 Unfortunately, alloHCT is also associated with high risk of early and late complications, including infections, graft-versus-host disease (GvHD) and secondary malignancies, which result in significant mortality and morbidity. Hence, the balance between potential advantages and disadvantages should be carefully considered in all clinical situations.2 Over the past two decades, advances have been made in the care of patients undergoing transplantation. Results of several studies indicated reduced risk of non-relapse mortality (NRM) after alloHCT, observed over the period 1990-2007, which could be a consequence of improved supportive care and more accurate donor selection.3-5 Those studies, however, included heterogenous populations, most frequently patients with acute myeloid leukemia. Trends in outcome of alloHCT for patients with ALL are less well documented. In particular, no large scale analyses are available for patients treated after 2007. In addition, prognostic factors for alloHCT performed in recent years are still not known. Such data are essential for proper patient selection and optimization of the transplantation procedure. The goal of this study was to analyze the results of myeloablative alloHCT for patients with ALL in various age groups and according to donor type, as well as to evaluate whether results changed over time during the 20-year period (1993-2012). In addition, we performed an analysis of prognostic factors for transplantations performed in more recent years (2008-2012).

Methods Study design and data collection This was a retrospective, multicenter analysis. Data were provided by the registry of the Acute Leukemia Working Party (ALWP) of the European Society for Blood and Marrow Transplantation (EBMT). The EBMT is a non-profit, scientific society representing more than 600 transplant centers, mainly in Europe. Data are entered, managed, and maintained in a central database; each EBMT center is represented in this database. The validation and quality control program includes verification of the computer printout of the entered data, cross-checking with the national registries, and on-site visits of selected teams. The study was approved by the ALWP of the EBMT. Patients provided informed consent authorizing the use of their personal information for research purposes.

Criteria of selection Inclusion criteria were: 1) patients with ALL in CR1; 2) age 1855 years; 3) alloHCT from either matched sibling donor (MSDHCT) or unrelated donor (URD-HCT) performed between 1993 and 2012 in centers reporting to the EBMT; 4) T-replete bone marrow or peripheral blood used as a source of stem cells (cord blood transplantations were excluded); 5) myeloablative condi140

tioning, i.e. regimen based on busulfan administered at the total dose of 8 mg/kg or more or total body irradiation (TBI) applied at 6 Gy or more. For the analysis of prognostic factors, only transplantations performed between 2008 and 2012 were considered. The population was restricted to subjects with available data regarding initial disease characteristics (cytogenetics, immune subtype, white blood cell count).

Patients, donors, and HSCT procedure Altogether data on 4859 patients treated in 203 transplant centers were included in the analysis. Median age was 33.3 years (range 18-55 years). Data on cytogenetics were available for 2577 patients among whom 1242 (50.1%) had Philadelphia (Ph)-positive ALL. Transplantations were performed from HLA identical sibling in 2681 patients (55%) and from unrelated volunteer in 2178 cases (45%). Peripheral blood was used as a source of stem cells in 3174 (65.8%) cases. The analysis of prognostic factors included a subgroup of 562 patients treated with either MSD-HCT (n=252, 44.8%) or URDHCT (n=310, 55.2%), between 2008-2012. Ph-positive ALL was reported in 225 cases (40%). Detailed patients' and procedural characteristics are listed in Table 1.

Statistical analysis Study end points were probabilities of NRM, relapse incidence (RI), leukemia-free survival (LFS), and overall survival (OS). The LFS was defined as time interval from alloHCT to either relapse or death in remission. Probabilities of OS and LFS were calculated using the Kaplan-Meier estimate. The RI and NRM were calculated using cumulative incidence curves in a competing risks setting, death in remission being treated as a competing event to relapse.6,7 Univariate analyses were made with the use of logrank test for LFS and OS, while Gray test was used to compare RI and NRM. In a univariate analysis we compared results of alloHCT performed in three periods: 1993-2002 (10 years), 20032007 (5 years), and 2008-2012 (5 years). The first period was longer than subsequent ones to ensure a representative number of observations. Multivariate analyses were performed with the use of Cox proportional hazard model, adjusted for potential risk factors. The effect of year of alloHCT (2008-2012 vs. 1993-2007) was analyzed in a model adjusted for donor type and recipient age. The analysis of prognostic factors was restricted to years 2008-2012. Median follow up for survivors was 38 months. All P-values are two-sided with type 1 error rate fixed at 0.05. Statistical analyses were performed with SPSS 22.0 (IBM Corp., Armonk, NY, USA) and R 3.1.1 software packages (R Development Core Team, Vienna, Austria).

Results Outcome of MDS-HCT: changes over time according to recipient age Results of alloHCT were analyzed separately for MSDHCT and URD-HCT in four age groups: 18-25 years, 2635 years, 36-45 years, and 46-55 years. Outcome of alloHCT performed in three study periods was compared. Detailed results are presented in Table 2. The cumulative incidence of NRM at two years after MSD-HCT decreased over time for all age groups; however, the differences reached statistical significance only among patients aged 36-45 years. In this age category, the haematologica | 2017; 102(1)


Improving results of alloHCT for adult ALL

incidence of NRM decreased from 21% and 23.3% in years 1993-2002 and 2003-2007, respectively, to 14.7% in the period 2008-2012 (P=0.02). No significant changes over time could be demonstrated for the incidence of relapse after MSD-HCT; however, there was significant improvement of LFS in all age groups except for patients

Table 1. Patients and donors: transplantation procedure.

Whole group (years 1993-2012)

N 4859 Median patient age, range (years) 33.3 (18-55) Median year of transplantation, 2007 (range) (1993-2012) Median WBC at diagnosis, 21 range (x109/L) (0.1-829)** High WBC at diagnosis* 722 (37.7%)*** Philadelphia chromosome Positive 1337 (48.5%) Negative 1419 (51.5%) Unknown 2103 Immune subtype B-cell 2846 (71.4%) T-cell 1140 (28.6%) Unknown 873 Median interval from diagnosis 166 to transplantation, range (days) (40-364) Donor type Matched sibling donor 2681 (55%) Unrelated donor 2178 (45%) 10/10 HLA matched 918 (69%) 9/10 HLA matched 318 (23.9%) 8/10 HLA matched 94 (7.1%) Unknown HLA compatibility 848 Donor/recipient sex Female/male 997 (20.8%) Other combinations 3794 (79.2%) Donor/recipient CMV serological status Negative/negative 1194 (31.3%) Negative/positive 802 (21.0%) Positive/negative 420 (11.0%) Positive/positive 1399 (36.7%) Unknown 1044 Type of conditioning Busulfan + cyclophosphamide 433 (8.9%) Busulfan + fludarabine 78 (1.6%) Melphalan-based 49 (1%) Other chemotherapy-based 247 (5.1%) TBI-based 4052 (83.4%) Source of stem cells Bone marrow 1660 (34.2%) Peripheral blood 3174 (65.8%)

Subgroup analyzed for prognostic factors (years 2008-2012) 562 34.9 (18-55) 2010 (2008-2012) 21.2 (0.3-775) 215 (38.3%) 219 (39%) 343 (61%) 430 (76.5%) 132 (23.5%) 160 (70-361) 252 (44.8%) 310 (55.2%) 191 (71.0%) 60 (22.3%) 18 (6.7%) 41 106 (18.9%) 456 (81.1%) 207 (36.8%) 117 (20.8%) 79 (14.1%) 159 (28.3%) 35 (6.2%) 16 (2.8%) 7 (1.2%) 504 (89.7%) 216 (38.4%) 346 (61.6%)

*High white blood cell (WBC) count was defined as more than 30x109/L for B-precursor acute lymphoblastic leukemia (ALL) and more than 100x109/L for T-precursor ALL. **Data available for 2011 patients. ***Data available for 1914 patients. N: number; HLA: human leukocyte antigen; CMV: cytomegalovirus; TBI: total body irradiation.

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aged 26-35 years. Among the youngest patients (18-25 years old) LFS rates increased from 53.5% between 19932002 to 66.2% between 2003 and 2007 and 65.4% between 2008 and 2012 (P=0.05). Respective LFS rates for patients aged 36-45 years were 47.7%, 58.7%, and 62.7% (P=0.002), while in the oldest group (46-55 years old) they equaled 33%, 45.5%, and 52.8% (P=0.03). In parallel, significant improvement could be demonstrated for the probabilities of OS. The 2-year OS rates for MSD-HCT performed between 2008-2012 in various age groups reached 76.3% (18-25 years), 69.3% (26-35 years), 68.6% (36-45 years), and 59.7% (46-55 years).

Outcome of URD-HCT: changes over time according to recipient age In a univariate analysis, NRM after URD-HCT did not change significantly over time; however, a tendency was observed in the youngest study group. For patients aged 18-25 years the 2-year NRM rates decreased from 32.1% between 1993 and 2002 to 15.6% between 2003 and 2007 and 17.9% between 2008 and 2012 (P=0.08) (Table 2). Significant reduction of the incidence of RI after URDHCT could be demonstrated for older adults. For patients aged 36-45 years, the 2-year RI rates decreased from 39.8% between 1993 and 2002 to 20.9% between 2003 and 2007 and 18.6% between 2008 and 2012 (P=0.02). In the oldest study groups (46-55 years), respective RI rates were 34.6%, 22%, and 13.9% (P=0.0002). Although the probabilities of LFS and OS increased over time in all age groups, significant differences could be demonstrated only for older adults. For patients aged 3645 years, the 2-year LFS rates in subsequent study periods were 23.5%, 50%, and 55% (P<0.0001) while OS was 37.5%, 57.3% and 60.9%, respectively (P=0.005). Among those aged 46-55 years, the probabilities of LFS increased from 30.8% between 1993 and 2002 to 39.8% between 2003 and 2007 and 57.7% between 2008 and 2012 (P<0.0001) while OS rates were 34.6%, 44.5%, and 61.8%, respectively (P=0.0007).

Outcome of alloHCT: general trends Univariate and multivariate analyses were performed for MSD-HCT and URD-HCT, including all age groups to see if outcome changed over time for a general population of adults aged 18-55 years (Tables 2 and 3). In a univariate model, improvement regarding LFS and OS rates could be demonstrated for both types of transplantations (Table 2 and Figures 1 and 2). As for NRM, a significant reduction could be demonstrated after MSDHSCT (18.8%, 20%, and 14.7% in subsequent study periods; P=0.003) while the differences after URD-HCT were not statistically significant (Table 2). In contrast, significant reduction of RI rates was observed after URDHCT (28.5%, 22%, and 18.5%, respectively, P=0.006), while not after MSD-HCT. In a multivariate analysis adjusted for recipient age and donor type significant effects of the treatment period were observed with regard to all study end points (Table 3). AlloHCT procedures performed between 2008-2012 were associated with reduced risk of NRM [Hazard Ratio (HR) 0.77, P=0.00006], relapse (HR 0.85, P=0.007), treatment failure (either relapse or NRM; HR 0.81, P<0.00001), and overall mortality (HR 0.79, P<0.00001). Additional analyses were performed for patients with known Ph-status. Survival improvement was observed for 141


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patients with Ph-positive ALL and Ph-negative ALL (Online Supplementary Tables S1 and S2).

Prognostic factors for alloHCT performed between 2008-2012 Results of univariate and multivariate analyses restricted

to transplantations performed in the most recent era are reported in Tables 4 and 5. Among disease-related factors, increased risk of relapse was observed for patients with high leukocyte count at diagnosis (HR 1.89, P=0.001) and the presence of Philadelphia chromosome (HR 1.61, P=0.02). High initial

Table 2. Results of transplantation from matched sibling donors and unrelated donors in various different age groups and time periods.

MSD-HCT Age 18-25 years

26-35 years

36-45 years

46-55 years

18-55 years

URD-HCT Age

18-25 years

26-35 years

36-45 years

46-55 years

18-55 years

Period

N

NRM % (95%CI)

RI % (95%CI)

LFS % (95%CI)

OS % (95%CI)

1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P

126 278 298

18.5 (13.7-24) 10.9 (7.3-15.3) 11.7 (8-16.3) 0.47 14 (10-18.7) 17.3 (12.8-22.4) 11.2 (7.7-15.5) 0.06 21 (15.8-26.7) 23.3 (17.9-29.1) 14.7 (10.4-19.8) 0.02 26.1 (19.7-32.9) 31.1 (24.4-38) 23.5 (17.4-30.1) 0.20 18.8 (16.2-21.5) 20 (17.4-22.8) 14.7 (12.4-17.1) 0.003

28 (20.3-36.2) 22.9 (18-28.3) 22.9 (17.5-28.7) 0.34 25.8 (19.3-32.7) 24 (19-29.5) 32.4 (26.7-38.3) 0.08 31.4 (23.8-39.3) 27 (21.9-32.2) 22.2 (16.9-28) 0.19 40.9 (29.3-52.2) 23.4 (17.7-29.6) 23.7 (17.6-30.4) 0.09 30 (26-34.1) 24.5 (21.9-27.2) 25.7 (22.8-28.7) 0.07

53.5 (44.6-62.4) 66.2 (60.4-72) 65.4 (58.9-71.8) 0.05 60.2 (52.7-67.7) 58.7 (52.6-64.7) 56.1 (49.9-62.4) 0.68 47.7 (39.3-56) 49.4 (43.5-55.2) 62.7 (56.2-69.2) 0.002 33 (22-44) 45.5 (38.5-52.5) 52.8 (45.1-60.6) 0.03 51.2 (46.7-55.6) 55.4 (52.3-58.5) 59.5 (56.2-62.9) 0.009

60.5 (51.8-69.2) 73 (67.5-78.5) 76.3 (70.5-82.2) 0.04 68.1 (60.9-75.2) 68.2 (62.4-74) 69.3 (63.1-75.5) 0.63 58.2 (49.8-66.5) 58.6 (52.8-64.4) 68.6 (62.2-75) 0.002 41.2 (29.6-52.7) 53.3 (46.3-60.3) 59.7 (52-67.4) 0.02 59.6 (55.2-63.9) 63.8 (60.7-66.8) 69.1 (65.8-72.3) 0.00006

167 279 318 139 303 283 74 207 209 506 1067 1108

Period

N

NRM % (95%CI)

RI % (95%CI)

LFS % (95%CI)

OS % (95%CI)

1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P 1993-2002 2003-2007 2008-2012 P

44 207 312

32.1 (26.6-37.7) 15.6 (11.5-20.3) 17.9 (13.5-22.8) 0.08 17.7 (13.4-22.4) 20.2 (15.6-25.2) 18.1 (13.8-23) 0.53 36.7 (31.3-42.1) 28.9 (23.7-34.2) 26.4 (21.3-31.7) 0.24 34.6 (28-41.3) 38.2 (31.6-44.9) 28.5 (22.2-35.1) 0.19 28.2 (22-35.2) 24.4 (21.7-27.1) 22.4 (19.8-25) 0.27

21 (10.2-34.3) 22.9 (17.3-29.1) 20.5 (15.7-25.6) 0.99 23.8 (14.4-34.6) 22.2 (17.1-27.8) 19.7 (15.2-24.6) 0.68 39.8 (25-54.3) 20.9 (15.8-26.5) 18.6 (14.3-23.4) 0.02 34.6 (16.9-53.1) 22 (15.1-29.7) 13.9 (9.4-19.2) 0.0002 28.5 (25.4-31) 22 (19.1-25) 18.5 (16.1-21) 0.006

46.9 (32-61.8) 61.5 (54.7-68.3) 61.7 (55.7-67.7) 0.11 58.5 (46.7-70.3) 57.6 (51.2-64) 62.2 (56.4-68) 0.30 23.5 (10.8-36.2) 50 (43.4-56.6) 55 (49.2-60.9) <0.0001 30.8 (13-48.5) 39.8 (31.1-48.4) 57.7 (50.6-64.7) <0.0001 43.4 (36.1-50.6) 53.6 (50-57.1) 59.1 (56-62.2) 0.0001

53.9 (39-68.8) 72 (65.7-78.3) 65.8 (59.7-71.8) 0.08 64.4 (53-75.9) 63.9 (57.7-70.1) 70 (64.4-75.5) 0.49 37.5 (23.1-52) 57.3 (50.7-63.9) 60.9 (55.1-66.6) 0.005 34.6 (16.3-52.9) 44.5 (35.7-53.3) 61.8 (54.9-68.8) 0.0007 51.2 (43.8-58.5) 61 (57.5-64.5) 64.8 (61.7-67.8) 0.003

69 240 313 44 223 334 26 132 234 183 802 1193

Probabilities are reported at two years after transplantation. MSD-HCT: matched sibling donor-hematopoietic cell transplantation; N: number; NRM: non-relapse mortality; RI: relapse incidence; LFS: leukemia-free survival; OS: overall survival; CI: confidence interval; URD-HCT: unrelated donor hematopoietic cell transplantation.

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leukocyte count was also associated with increased risk of treatment failure (HR 1.45, P=0.01) and overall mortality (HR 1.5, P=0.01). The effect of Ph-status on LFS was significant in a univariate analysis (P=0.007) (Online Supplementary Figure S1), but not in a multivariate model.

Neither immune subgroups (B- vs. T-ALL) nor time to achieve CR were associated with outcome. The risk of NRM was increased for URD-HCT compared to MSD-HCT (HR 2.11, P=0.002) (Online Supplementary Figure S1), and in the case of female

B Cumulative incidence of NRM

Cumulative incidence of relapse

A

Leukemia-free survival

Overall survival

D

C

Figure 1. Outcome of matched sibling donor â&#x20AC;&#x201C; hematopoietic cell transplantation for adults with acute lymphoblastic leukemia (ALL) in first complete remission (CR1). Changes over time in the period 1993-2012. (A) Relapse incidence (RI), (B) non-relapse mortality (NRM), (C) leukemia-free survival (LFS), (D) overall survival (OS).

Table 3. Effect of the year of allogeneic HCT on outcome adjusted for recipient age and type of donor.

Factor NRM

Relapse

Treatment failure

Overall mortality

Year of alloHCT 2008-2012 vs. 1993-2007 Recipient age (per 10 years) MSD vs. URD Year of alloHCT 2008-2012 vs. 1993-2007 Recipient age (per 10 years) MSD vs. URD Year of alloHCT 2008-2012 vs. 1993-2007 Recipient age (per 10 years) MSD vs. URD Year of alloHCT 2008-2012 vs. 1993-2007 Recipient age (per 10 years) MSD vs. URD

HR (95% CI)

P

0.77 (0.68-0.87) 1.38 (1.31-1.47) 0.71 (0.62-0.8) 0.85 (0.75-0.96) 1.07 (1.01-1.13) 1.15 (1.02-1.29) 0.81 (0.74-0.88) 1.21 (1.16-1.26) 0.91 (0.84-0.99) 0.79 (0.72-0.87) 1.24 (1.19-1.3) 0.85 (0.78-0.93)

0.00006 <0.00001 <0.00001 0.007 0.01 0.02 <0.00001 <0.00001 0.04 <0.00001 <0.00001 0.0005

HCT: hematopoietic cell transplantation; HR: hazard ratio; CI: confidence interval; NRM: non-relapse mortality; alloHCT: allogeneic hematopoietic cell transplantation; MSD: matched sibling donor; URD: unrelated donor.

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donor/male recipient sex combination (HR 1.85, P=0.02). Both these factors were also associated with increased risk of the overall mortality (HR 1.52, P=0.01 and HR 1.59, P=0.02, respectively). In addition, the risk of mortality was increased for patients with CMV-positive serological status receiving transplantation from CMV-negative donors (HR 1.53, P=0.04). Among procedure-related variables, decreased risk of relapse was demonstrated for transplantations preceded by total body irradiation (TBI)-based preparative regimens (HR=0.48, P=0.001). The use of TBI was also associated with reduced risk of treatment failure (HR=0.63, P=0.02) (Figure 3). The choice of stem cell source did not significantly affect outcome; however, there was a trend to reduced risk of relapse after peripheral blood compared to bone marrow transplantations (P=0.06). Data on minimal residual disease (MRD) status before transplantation were available for 716 patients, including 502 patients with Ph-positive ALL (MRD-positive, n=314; MRD-negative, n=188) and 214 subjects with Ph-negative disease (MRD-positive, n=162; MRD-negative, n=52) treated between 2008-2012. Methods for MRD assessment were not specified. In a univariate analysis, among patients with Ph-negative ALL, the positive MRD status was associated with increased incidence of relapse (36.5%

A

Discussion AlloHCT is used as part of consolidation treatment of adults with ALL with intention to reduce the risk of relapse. However, this benefit may be counterbalanced by NRM. Results of the UK ALL XII/ECOG 2993 trial revealed that, among standard-risk patients with a sibling donor, the cumulative incidence of NRM was 19.5%, compared with 35.8% in the high-risk group.8 Consequently, survival advantage could be demonstrated for standard- but not high-risk ALL. In the HOVON studies, NRM among patients with a sibling donor was lower: 16% for standard-risk and 15% for high-risk ALL.2 Collectively, it has been concluded that patients with an over 50% risk of relapse and a less than 20%-25% risk of NRM are most likely to benefit from alloHCT performed in CR1. Therefore, assessing the risk of transplantationrelated mortality is imperative in the decision-making

Cumulative incidence of NRM

Cumulative incidence of relapse

B

C

Overall survival

D Leukemia-free survival

144

vs. 17.6%; P=0.0005) and decreased probability of LFS (54.3% vs. 65.9%; P=0.04), while no significant effect was observed with regard to OS and NRM. For patients with Ph-positive ALL, the MRD status did not significantly affect outcome.

Figure 2. Outcome of unrelated donor â&#x20AC;&#x201C; hematopoietic cell transplantation for adults with acute lymphoblastic leukemia (ALL) in first complete remission (CR1). Changes over time in the period 1993-2012. (A) Relapse incidence (RI), (B) non-relapse mortality (NRM), (C) leukemia-free survival (LFS), (D) overall survival (OS).

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process and there is a need for estimates related to procedures performed in the most recent era.2 In the current study, we focused on alloHCT performed in the period of 2008-2012, which reflected current clinical practice with regard to supportive care, HLA typing and other factors potentially influencing outcome. Results were compared with preceding periods. We were able to demonstrate a significant improvement in OS and LFS over time, which for the major part was related to reduced risk of NRM, and to a lesser extent the risk of relapse. For the entire population of adults between 18-55 years old treated between 2008 and 2012, the cumulative incidence of NRM at two years was 14.7% after MSD-HCT and 22.4% after URD-HCT. The improvement over time has already been reported

by Gooley et al. who compared results of transplantations performed between 2003 and 2007 with those performed between 1993 and 1997. In a heterogeneous population including 13% patients with ALL in various disease phases, the authors demonstrated reduction of the NRM rates from 41% to 26%.4 Hahn et al. reported general survival improvement for patients with hematologic malignancies observed over the period 1994-2005; however, the analysis included children, and data on NRM were not reported.5 In the previous analysis of the ALWP of the EBMT, we demonstrated that, for patients with acute leukemia treated with MSD-HCT in Eastern European countries, the rates of NRM decreased from 22% between 1990 and 2002 to 15% in the period 2002 and 2005.3 Two studies were restricted to patients with ALL, transplanted

Table 4. Univariate analysis of factors affecting outcome after allogeneic HCT performed between 2008-2012.

Factor Ph-status

Age at HSCT (years)

Initial WBC (x109/L) Subtype

Time to achieve CR (days) Donor type

Patient CMV status

Donor CMV status

Female donor/ male recipient Conditioning

Stem cell source

Negative Positive P 18-25 26-35 36-45 46-55 P Low High* P B-cell T-cell P < 42 â&#x2030;Ľ 42 P MSD URD P Negative Positive P Negative Positive P No Yes P CHT TBI P BM PB P

N

NRM (%, 95%CI)

RI (%, 95%CI)

LFS (%, 95%CI)

OS (%, 95%CI)

337 225

17 (13.1 - 21.5) 17.7 (13.7 - 22.2) 0.48 18.6 (12.6 - 25.6) 13.5 (8.5 - 19.7) 18.2 (12.3 - 25.1) 19.3 (13.2 - 26.3) 0.39 17.7 (13.7 - 22) 16.6 (12.8 - 20.9) 0.73 17.5 (14 - 21.5) 16.7 (13.2 - 20.5) 0.52 16.4 (12.4 - 20.8) 18.6 (14.4 - 23.2) 0.55 12.6 (8.7 - 17.3) 21.2 (16 - 26.8) 0.002 16.3 (12.1 - 21) 18.3 (13.9 - 23.3) 0.48 17.1 (13.1 - 21.6) 17.6 (13.5 - 22.1) 0.87 16.3 (12.9 - 19.9) 22.4 (18.5 - 26.5) 0.18 17.6 (9 - 28.6) 17.3 (8.8 - 28.2) 0.62 15.6 (11 - 21) 18.4 (13.4 - 24.1) 0.18

18.9 (14.7 - 23.6) 27.3 (21.3 - 33.5) 0.01 20.4 (13.6 - 28.2) 24.1 (17.4 - 31.5) 25.6 (18.7 - 33.1) 17.7 (11.1 - 25.5) 0.47 16.6 (12.6 - 21) 31.5 (25.1 - 38.1) <0.0001 23.1 (19 - 27.5) 19.6 (13.1 - 27.1) 0.39 23.1 (18.4 - 28.1) 21.2 (16 - 27) 0.49 25.9 (20.4 - 31.8) 19.3 (14.9 - 24.2) 0.08 18.6 (14 - 23.6) 26.1 (20.8 - 31.6) 0.06 22.5 (17.8 - 27.5) 22.1 (16.8 - 27.8) 0.44 22.6 (18.6 - 26.7) 20.9 (13.3 - 29.8) 0.86 32.7 (20.6 - 45.5) 21.1 (17.4 - 24.9) 0.04 24.9 (19.1 - 31.2) 20.6 (16.3 - 25.3) 0.18

64 (58.6 - 69.5) 54.8 (48 - 61.7) 0.007 61 (52 - 70) 62.2 (54.1 - 70.2) 56.1 (48 - 64.3) 63 (53.8 - 72.2) 0.86 65.6 (60.3 - 71) 51.9 (44.8 - 58.9) 0.002 59.2 (54.3 - 64.2) 63.7 (55.2 - 72.2) 0.24 60.5 (54.8 - 66.1) 60.1 (53.5 - 66.6) 0.97 61.3 (54.9 - 67.7) 59.5 (53.7 - 65.3) 0.35 65 (59.1 - 70.9) 55.6 (49.4 - 61.8) 0.03 60.4 (54.8 - 66.1) 60.2 (53.6 - 66.7) 0.44 61.1 (56.4 - 65.8) 56.7 (46.5 - 66.9) 0.36 49.7 (36.3 - 63) 61.6 (57.1 - 66.1) 0.02 59.3 (52.4 - 66.2) 61 (55.5 - 66.5) 0.83

69.8 (64.5 - 75) 67.8 (61.3 - 74.3) 0.53 67.2 (58.5 - 75.9) 76.2 (68.9 - 83.5) 65.1 (57.3 - 72.9) 66.9 (57.9 - 76) 0.57 73.7 (68.7 - 78.6) 61.7 (54.8 - 68.7) 0.01 68.4 (63.7 - 73.2) 70.5 (62.3 - 78.6) 0.41 70.8 (65.6 - 76.1) 66.3 (59.9 - 72.8) 0.28 71.4 (65.4 - 77.5) 66.9 (61.4 - 72.5) 0.04 73.9 (68.4 - 79.4) 64.1 (58.1 - 70.1) 0.03 69.6 (64.2 - 74.9) 68.2 (61.9 - 74.6) 0.96 70.1 (65.6 - 74.5) 63.7 (53.5 - 73.8) 0.23 64 (51.2 - 76.7) 69.5 (65.2 - 73.9) 0.09 67.5 (60.9 - 74.2) 69.8 (64.6 - 75) 0.68

131 152 165 114 347 215 430 132 320 242 252 310 286 276 324 238 456 106 58 504 216 346

Probabilities are reported at two years after transplantation. *High white blood cell (WBC) count was defined as more than 30x109/L for B-precursor acute lymphoblastic leukemia (ALL) and more than 100x109/L for T-precursor ALL. HCT: hematopoietic cell transplantation; N: number; NRM: non-relapse mortality; RI: relapse incidence; LFS: leukemia-free survival; OS: overall survival; CI: confidence interval; Ph: Philadelphia chromosome; WBC: white blood cell count; CR: complete remission; MSD: matched sibling; URD: unrelated donor; CMV: cytomegalovirus; CHT: chemotherapy; TBI: total body irradiation; BM: bone marrow; PB: peripheral blood.

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in both CR1 and CR2. In a single center experience from the University of Minnesota, USA, alloHCT performed between 2000 and 2005 were associated with a significant reduction of NRM compared to preceding periods (19901994 and 1995-1999).9 In a study by Wood et al., reduction of NRM from 43% between 1990 and 1995 to 31% between 2002 and 2007 was reported among adolescents and young adults, i.e. patients 18-40 years old.10 In the current analysis, the estimated rates of NRM were lower compared to most previously reported results. This may reflect further improvement which occurred in the

most recent time period. As suggested by Gooley et al., reduction of NRM may be dependent on improving supportive care, but also on the reduction of the incidence of graft-versus-host disease.4 The latter could be a consequence of more accurate HLA typing, and in particular, the introduction of high resolution techniques in the process of unrelated donor search.11 On the other hand, it may be speculated that decreased NRM may be a consequence of more appropriate patient selection and that toxicity of conventional-dose chemotherapy decreased in parallel, positively affecting biological status of the transplant

Table 5. Multivariate analysis of factors affecting outcome after allogeneic HCT performed between 2008-2012.

Factor NRM

RI

LFS

OS

Age (years, continuous) High WBC at diagnosis* T-ALL vs. B-ALL Ph-positive vs. Ph-negative ALL Interval from diagnosis to CR1 >42 days URD-HCT vs. MSD-HCT CMV status D-neg/R-pos vs. D-neg/R-neg Female D to male R vs. other combinations TBI- vs. chemotherapy-based conditioning Peripheral blood vs. bone marrow transplantation Age (years, continuous) High WBC at diagnosis T-ALL vs B-ALL Ph-positive vs. Ph-negative ALL Interval from diagnosis to CR1 >42 days URD-HCT vs. MSD-HCT CMV status D-neg/R-pos vs. D-neg/R-neg Female D to male R vs. other combinations TBI- vs. chemotherapy-based conditioning Peripheral blood vs. bone marrow transplantation Age (years, continuous) High WBC at diagnosis T-ALL vs. B-ALL Ph-positive vs. Ph-negative ALL Interval from diagnosis to CR1 >42 days URD-HCT vs. MSD-HCT CMV status D-neg/R-pos vs. D-neg/R-neg Female D to male R vs. other combinations TBI- vs. chemotherapy-based conditioning Peripheral blood vs. bone marrow transplantation Age (years, continuous) High WBC at diagnosis T-ALL vs. B-ALL Ph-positive vs. Ph-negative ALL Interval from diagnosis to CR1 >42 days URD-HCT vs. MSD-HCT CMV status D-neg/R-pos vs. D-neg/R-neg Female D to male R vs. other combinations TBI- vs. chemotherapy-based conditioning Peripheral blood vs. bone marrow transplantation

HR (95% CI)

P

1.01 (0.99-1.03) 1.02 (0.67-1.56) 0.88 (0.52-1.51) 1.05 (0.66-1.65) 1.18 (0.79-1.76) 2.11 (1.33-3.34) 1.29 (0.75-2.24) 1.85 (1.12-3.05) 0.90 (0.49-1.66) 1.06 (0.68-1.64) 0.99 (0.97-1.01) 1.89 (1.31-2.72) 1.14 (0.71-1.84) 1.61 (1.08-2.4) 0.92 (0.64-1.32) 0.76 (0.52-1.11) 1.55 (0.95-2.55) 1.05 (0.65-1.7) 0.48 (0.3-0.79) 0.69 (0.48-1.01) 1 (0.99-1.01) 1.45 (1.1-1.9) 1.03 (0.72-1.47) 1.33 (0.98-1.79) 1.03 (0.79-1.34) 1.16 (0.87-1.55) 1.41 (0.98-2.04) 1.33 (0.94-1.88) 0.63 (0.43-0.92) 0.83 (0.62-1.1) 1.01 (0.99-1.02) 1.5 (1.11-2.04) 0.9 (0.61-1.33) 0.93 (0.67-1.3) 1.20 (0.89-1.62) 1.52 (1.1-2.1) 1.53 (1.02-2.28) 1.59 (1.08-2.32) 0.72 (0.47-1.11) 0.8 (0.58-1.09)

0.26 0.91 0.65 0.84 0.42 0.002 0.36 0.02 0.73 0.79 0.34 0.001 0.59 0.02 0.64 0.16 0.08 0.85 0.004 0.06 0.99 0.01 0.87 0.07 0.84 0.30 0.06 0.11 0.02 0.19 0.31 0.01 0.59 0.67 0.22 0.01 0.04 0.02 0.14 0.15

*High white blood cell (WBC) count was defined as more than 30x109/L for B-precursor acute lymphoblastic leukemia (B-ALL) and more than 100x109/L for T-precursor ALL (T-ALL). HCT: hematopoietic cell transplantation; HR: hazard ratio; CI: confidence interval; NRM: non-relapse mortality; PB: peripheral blood; BM: bone marrow; Ph: Philadelphia chromosome; CR1: complete first remission; URD: unrelated donor; MSD: matched sibling donor; CMV: cytomegalovirus; pos: positive; neg: negative; D: donor; R: recipient; TBI: total body irradiation; RI: relapse incidence; LFS: leukemia-free survival; OS: overall survival.

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recipients. Results of our study indicate survival improvement after MSD-HCT for all age groups except for patients 26-35 years old. A trend towards reduction of NRM in this age category was counterbalanced by a tendency to increased RI. It may be speculated that selection criteria for alloHCT changed over time, and patients with higher risk of relapse were referred for transplantation in recent years. Among recipients of URD-HCT, the most prominent improvement could be shown in older age groups (36-55 years old), which, however, was mainly attributed to reduced RI. Identification of prognostic factors in the most recent time period was a secondary goal of our study. Among donor/recipient-related variables, the use of unrelated donor and female donor to male recipient sex combination had the strongest impact, negatively affecting both the risk of NRM and survival. Several previous reports had suggested that results of MSD-HSCT and URD-HCT for patients with ALL may be comparable. In an analysis by Tomblyn et al., the use of well-matched or partially matched unrelated donor was not associated with inferior outcome compared to MSD.9 In a Japanese study, the OS rates after URD-HCT and MSD-HCT for patients in CR1 were superimposable; however, HLA disparities were associated with increased risk of NRM.12 In the present analysis, 29% of URD-HCT were performed across single or double HLA mismatch. However, in a univariate analysis this factor did not influence significantly any of the study outcomes (data not shown). Female donor to male

B

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Overall survival

D Leukemia-free survival

C

Cumulative incidence of NRM

Cumulative incidence of relapse

A

recipient sex combination is a well-recognized risk factor associated with increased risk of graft-versus-host disease and NRM.13 Results of our study confirm that, whenever possible, this combination should be avoided. The definition of high risk in adult ALL varies among countries and study groups; however, most of the stratification systems include high initial leukocyte count. This factor influences the overall outcome but its impact on results of alloHCT has not been well recognized. In our study, high WBC at diagnosis was a strong predictor of risk of relapse, treatment failure and survival. Our findings suggest the need for additional intervention in this patient population, e.g. therapy oriented to eradicate MRD prior to alloHSCT, intensification of the conditioning regimen, and close monitoring of MRD after alloHSCT followed by pre-emptive donor lymphocyte infusions. General outcome of Ph-positive ALL improved with the introduction of tyrosine kinase inhibitors (TKIs).14 Results of a recent analysis by the ALWP of the EBMT indicate that using TKIs both pre- and post-transplant is associated with reduced risk of relapse and improved survival.15 Both pre-emptive or prophylactic use of imatinib after alloHCT may be considered.16 In the current analysis, the presence of t(9;22) was associated with increased risk of relapse but not overall mortality. As our study population was quite young, longer follow up may be needed in order to obtain a final evaluation of the effect on OS. On the other hand, it may be speculated that some patients with Ph-positive ALL who relapse after alloHCT may still be salvaged, pos-

Figure 3. Outcome of allogeneic hematopoietic stem cell transplantation (alloHSCT) performed in the period 2008-2012 according to the type of conditioning (total body irradiation-based vs. chemotherapy-based). (A) Relapse incidence (RI), (B) non-relapse mortality (NRM), (C) leukemia-free survival (LFS), (D) overall survival (OS).

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sibly with the use of 2nd- or 3rd-generation TKIs. Furthermore, the probabilities of LFS for Ph-positive ALL improved markedly between 2008 and 2012 compared to preceding periods as a consequence of reduced incidence of both relapse and NRM (Online Supplementary Table S1 and Online Supplementary Figure S3). It could be speculated that the introduction of TKIs not only increased the treatment efficacy but also, by allowing for a reduction in chemotherapy intensity, contributed to a reduction in the overall toxicity. Among procedure-related factors, the use of TBI-based conditioning was the strongest predictor of relapse and was associated with an over 50% reduction of the risk of this event. Although comparison of TBI with myeloblative chemotherapy in a setting of ALL has never been a subject of a prospective trial, some retrospective analyses confirmed the advantage of TBI.17,18 Results of the current study strongly support this statement. New, irradiationfree regimens based on the use of thiotepa are under development; however, their utility requires further evaluation.19 Our study is the largest to focus on alloHCT performed in a very large cohort of adults with ALL in CR1. However, it does have several limitations related to its retrospective nature. We were unable to analyze the reasons of NRM after transplantation. In addition, some important variables related to the disease characteristics were unavailable. Among karyotype features we focused on the Ph-status, while the effect of other known high-risk abberrations, e.g. t(4;11) and molecular markers, could not be evaluated. Furthermore, for the majority of patients, we were unable to collect MRD data, which is a well-recognized risk factor in a setting of ALL.20,21 Finally, selection procedures for patients to go forward to alloHCT could vary among centers and countries. The effect of center experience and national socio-economic status could have caused an additional bias.22 The role of alloHCT in first-line treatment of adults with ALL is a matter of debate in view of improving results of conventional-dose chemotherapy.23 In this study, we demonstrate that results of alloHCT improved in parallel, due to the reduced risk of both NRM and relapse. The improvement is observed in most age categories after both MSD-HCT and URD-HCT. Therefore, we conclude that current estimates of NRM justify the use of alloHCT as consolidation in patients with a high risk of relapse. TBI-based regimens should still be considered the preferable type of conditioning for patients with ALL in CR1. Acknowledgments The authors would like to thank all EBMT centers reporting their data for the purpose of this analysis. Fifty centers with the highest number of patients, are listed below:

References 1. Weiden PL, Flournoy N, Thomas ED, et al. Antileukemic effect of graft-versus-host disease in human recipients of allogeneicmarrow grafts. N Engl J Med. 1979; 300(19):1068-1073. 2. Cornelissen JJ, van der Holt B, Verhoef GE, et al. Myeloablative allogeneic versus autol-

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Karolinska University Hospital, Stockholm, Sweden; CHU Bordeaux, Hôpital Haut-leveque, Pessac, France; University of Freiburg, Freiburg, Germany; University Hospital Eppendorf, Hamburg, Germany; University Hospital Leipzig, Leipzig, Germany; National University Hospital, Rigshospitalet, Copenhagen, Denmark; University Hospital Birmingham NHSTrust, Queen Elizabeth Medical Centre, Edgbaston, Birmingham, United Kingdom; University of Münster, Münster, Germany; Universitaetsklinikum Dresden, Dresden, Germany; Royal Marsden Hospital, London, United Kingdom; Medizinische Universitaet Wien, Vienna, Austria; Hannover Medical School, Hannover, Germany; Universität Tübingen, Tübingen, Germany; CHU Nantes, Nantes, France; University Hospital, Basel, Switzerland; Deutsche Klinik für Diagnostik, KMT Zentrum, Wiesbaden, Germany; West of Scotland Cancer Centre, Gartnaval General Hospital, Glasgow, United Kingdom; Ospedale di Careggi, Firenze, Italy; Azienda Ospedaliera Papa Giovanni XXIII, Bergamo, Italy; University Hospital, Bratislava, Slovakia; Institute of Hematology and Blood Transfusion, Prague, Czech Republic; A.O.U Citta della Salute e della Scienza di Torino, Torino, Italy; Imperial College, Hammersmith Hospital, London, United Kingdom; Inst. Português de Oncologia do Porto, Porto, Portugal; University of Heidelberg, Heidelberg, Germany; Northern Centre for Bone Marrow Transplantation, Newcastle-Upon-Tyne, United Kingdom; University Hospital, Zürich, Switzerland; George Papanicolaou General Hospital, Thessaloniki, Greece; Nottingham City Hospital, Nottingham, United Kingdom; Institut Universitaire du Cancer Toulouse, Toulouse, France; University Medical Center Mainz, Mainz, Germany; University Hospital Center Rebro, Zagreb, Croatia; Klinikum Grosshadern, Munich, Germany; Hopital Saint Antoine, Paris, France; Bologna University, S.Orsola-Malpighi Hospital, Institute of Hematology & Medical, Oncology L & A Seràgnoli, Bologna, Italy; Rambam Medical Center, Haifa, Israel; Centre Hospitalier Universitaire de Rennes, Rennes, France; Hopital d`Enfants, Vandoeuvre_Les_Nancy, France; Charles University Hospital, Pilsen, Czech Republic; Cliniques Universitaires St. Luc, Brussels, Belgium; St. István and St. László Hospital, Semmelweis University St. Laszlo, Budapest, Hungary; Nouvel Hopital Civil, Strasbourg, France; Heinrich Heine