The ultimate genetic test prev diag prog 1 dr hasan by PROFICIO

Disclosure • “IMANA is committed to providing CME activities that are fair, balanced, and free of bias. Full and specific disclosure information is provided in your handouts.” • I have no relevant financial relationship with any commercial interest.

The ultimate genetic test for CRC: Prevention, diagnostic, and prognostic sequencing options in GI, Future of personalized medicine Hassan Ashktorab, Ph.D. Addis Ababa, Ethiopia August 6, 2014 Howard University, Washington DC, USA hashktorab@howard.edu

ሰሰሰ salam

Saadi Shirazi 1200-1292 â&#x20AC;˘ Of one Essence is the human race, Thusly has Creation put the Base; One Limb impacted is sufficient, For all Others to feel the Mace. The world honors Saadi today by gracing the entrance to the Hall of Nations in New York with this call for breaking all barriers:

The Bostan of Saadi and The Golestan of Saadi One of the world's greatest masterpieces

Saadi was born in Shiraz around 1200. He died in Shiraz around 1292. He lost his father in early childhood. With the help of his uncle, Saadi completed his early education in Shiraz. Later he was sent to study in Baghdad at the renowned Nezamiyeh College, where he acquired the traditional learning of Islam.

Colorectal Cancer in the Region

Jemal A et al Cancer Sept 15, 2012

Burden of Cancer in Africa â&#x20AC;˘ Overall, 715,000 new cancer cases and 542,000 cancer deaths were estimated to have occurred in 2008 in Africa

Jemal A et al Cancer Sept 15, 2012

Burden of Colorectal Cancer • World-wide about 782,000 people are diagnosed with colorectal cancer each year • Both women and men • All races • Second leading cause of cancer death in US • American Cancer Society estimates in 2014 –

103,000 new cases

–

50,000 deaths

Ten Leading Cancer Types for the Estimated New Cancer Cases and Deaths, by Sex, US, 2014.

Siegel et al, CA Cancer J Clin 2014; 64:104-117

Death Rates* From Cancer and Heart Disease for Ages Younger Than 85

Cancer is #1 killer in people under age of 85

Jemal et al, CA Cancer J Clin 2009; 59:225-249

Colorectal Cancer in the Region

Ethiopia

World Health Organization â&#x20AC;&#x201C; Non Communicable Disease Country Profiles, 2011.

ADDIS ABABA CANCER REGISTRY

http://afcrn.org/membership/members/100-Addisababa

http://www.worldlifeexpectancy.com/country-health-profile/ethiopia

The African Cancer Registry Network (AFCRN)

Tanzania Cancer Registry

http://afcrn.org/membership/members/114-tanzania

National Cancer Registry of South African

http://afcrn.org/membership/members/87-ncrsa

Nairobi, Kenya

7th

9th

http://afcrn.org/membership/members/85-nairobi-kenya

Colorectal Cancer Sporadic (average risk 65%â&#x20AC;&#x201C;85%) Epigenetics

Rare syndromes (<0.1%) Familial adenomatous polyposis (FAP) (1%)

Family history (10%â&#x20AC;&#x201C;30%) Hereditary nonpolyposis colorectal cancer (HNPCC) (5%)

Multistep genetic model of colorectal carcinogenesis. The initial step in colorectal tumorigenesis is the formation of aberrant crypt foci (ACF). Activation of the Wnt signaling pathway can occur at this stage as a result of mutations in the APC gene. Progression to larger adenomas and early carcinomas requires activating mutations of the proto-oncogene KRAS, mutations in TP53, and loss of heterozygosity at chromosome 18q. Mutational activation of PIK3CA occurs late in the adenoma窶田arcinoma sequence in a small proportion of colorectal cancers. Chromosomal instability is observed in benign adenomas and increases in tandem with tumor progression. Pino and Chung Gastroenterology 2010

Colorectal Cancer Type

Ashktorab et al 2010, 2011, 2012; 2013;2014; Brim et al 2012

Cost of NGS

Innovations in chemistry, optics, fluidics computational hardware, and bioinformatics solutions Transformative step

Genomics: ENCODE explained.

Figure 1 | Beyond the sequence. The ENCODE project 2,3,4,5,6,7 provides information on the human genome far beyond that contained within the DNA sequence - it describes the functional genomic elements that orchestrate the development and function of a human. The project contains data about the degree of DNA methylation and chemical modifications to histones that can influence the rate of transcription of DNA into RNA molecules (histones are the proteins around which DNA is wound to form chromatin). ENCODE also examines long-range chromatin interactions, such as looping, that alter the relative proximities of different chromosomal regions in three dimensions and also affect transcription. Furthermore, the project describes the binding activity of transcription-factor proteins and the architecture (location and sequence) of gene-regulatory DNA elements, which include the promoter region upstream of the point at which transcription of an RNA molecule begins, and more distant (long-range) regulatory elements. Another section of the project was devoted to testing the accessibility of the genome to the DNA-cleavage protein DNase I. These accessible regions, called DNase I hypersensitive sites, are thought to indicate specific sequences at which the binding of transcription factors and transcription-machinery proteins has caused nucleosome displacement. In addition, ENCODE catalogues the sequences and quantities of RNA transcripts, from both non-coding and protein-coding regions. Ecker, Joseph et al ;Nature. 489(7414):52-55, September 6, 2012. DOI: 10.1038/489052a

Number of Genetic Markers for Genetic Studies Genome-wide Linkage Studies 300-400 Microsatellite Markers Genome-wide Association Studies 100,000-2,500,000 SNPs Exome Sequencing Studies 30,000,000 Base pairs Gene-based Studies 22,000 Genes Whole Genome Sequencing Studies 3,200,000,000 Base pairs

Exome Sequencing Deciphers Rare Diseases

Two years ago, NIH’s Undiagnosed Diseases Program began delivering genomics to the clinic on an unprecedented scale. Now, with 128 exomes sequenced and 39 rare diseases diagnosed, the program’s success is paving the way for widespread personal genomics while pioneering new techniques for reigning in the ‘‘tsunami’’ of genomics data. Cell 144, March 4, 2011 p 635

Next Generation Sequencing in Cancer Whole genome sequencing; 128

Driver mutations Whole Exome sequeincing; 790

Oncognes; 47 Tumor suppressor genes; 70

August-2014

Mutation frequencies in human CRC

a, Mutation frequencies in each of the tumour samples from 224 patients. Note a clear separation of hypermutated and nonhypermutated samples. Red, MSI high, CIMP high or MLH1 silenced; light blue, MSI low, or CIMP low; black, rectum; white, colon; grey, no data. Inset, mutations in mismatch-repair genes and POLE among the hypermutated samples. The order of the samples is the same as in the main graph. b, Significantly mutated genes in hypermutated and non-hypermutated tumours. Blue bars represent genes identified by the MutSig algorithm and black bars represent genes identified by manual examination of sequence data. The Cancer Genome Atlas Network Nature 487, 330-337 (2012) doi:10.1038

Colon Cancer Mutation

Incidence of Single Driver Mutations SMAD2/4

SMAD2/4; 10

APC

APC; 86

P53

P53; 60

PIK3CA

KRAS 35%

PIK3CA; 5

APC, TP53, SMAD2 [PERCENTAGE] BRAF; 8

BRAF

KRAS

KRAS; 35 0

PIK3CA 5% 50

BRAF 8% 70

100

Diversity and frequency of genetic changes leading to deregulation of signalling pathways in CRC

Non-hypermutated (nHM; n = 165) and hypermutated (HM; n = 30) samples with complete data were analysed separately. Alterations are defined by somatic mutations, homozygous deletions, high-level focal amplifications, and, in some cases, by significant up- or downregulation of gene expression (IGF2, FZD10, SMAD4). Alteration frequencies are expressed as a percentage of all cases. Red denotes activated genes and blue denotes inactivated genes. Bottom panel shows for each sample if at least one gene in each of the five pathways described in this figure is altered.

The Cancer Genome Atlas Network Nature 487, 330-337 (2012) doi:10.1038

Whole-exome sequencing data processing

Filter Somatic SNPs nonsynonymous, non-dbsnp, Mq squre pass, Validated by sanger method

Distribution of Identity by state (IBS) across genome for normal and tumor matched pair to determine the tumor status as a novel approach

CC1028 (data from NGS study) SNPs for CC1028

Nonsynonymou s Synonymous Nonsense Frameshift Non-Frameshift Splicing UK

AA/BB > AB Somatic (IBS1) 463

AB > AA/BB LOH (IBS1) 55

AA > BB IBS 0 7

525

189

217

243 1 2 5 14 9 463

26 0 0 2 2 1 55

2 0 0 0 1 0 7

271 1 2 7 17 10 525

Black in regions with no allele sharing, (IBS 0) Red in regions where one allele is shared, (IBS 1) Green in regions where both alleles are shared, (IBS 2)

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;? Ashktorab 2013, Gastro Darempipouran 2013 AACR

SNPs for CC1053

Nonsynonymous Synonymous Nonsense Frameshift Non-Frameshift Splicing UK

AA/BB > AB Somatic (IBS1) 990 424 522 4 7 4 13 16 990

AB > AA/BB LOH (IBS1) 46 18 26 0 0 0 1 1 46

Black in regions with no allele sharing, (IBS 0) Red in regions where one allele is shared, (IBS 1) Green in regions where both alleles are shared, (IBS 2)

AA > BB IBS 0 19 9 10 0 0 0 0 0 19

1055 451 558 4 7 4 14 17 1055

Ashktorab et al 2014, Cancer, “in Press” Ashktorab 2013, Gastro Darempipouran 2013 AACR

Circos Plot of CRC

From the outside to the inside of the plot, 1) Chromosome 2) Number of total mutations in 10 Mb (red implies >1000 combined mutations in 8 samples in 10Mb. Green implies <100) 3) Histogram in black of number of synonymous mutations in 10Mb 4) Histogram in orange of number of missense mutations in 10Mb 5) Tiled plot in red of nonsense mutations (we used tiled plot since the number of mutations are not very high) 6) Tiled plot in green of non-stop mutations 7) Tiled plot in dark green of frameshift insertions and deletions

Amino-acid changes based on gene mutations analysis in African Americans with CRC

Figure 1. We computed the total number of these variants and the number of variants that are aminoacid changing (variants belonging to the categories "frameshift deletion", "frameshift insertion", "nonframeshift deletion", "nonframeshift insertion", "nonsynonymous SNV", "stopgain SNV", "stoploss SNV"). The ratio of these two counts was plotted for each sample.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Mutations rate in African American colorectal samples

Figure 2. MSI status was evaluated, 3 non-hypermutated tumors were MSI-H (red), none of the hypermutated tumors were MSI-H. Hypermutated were defined as having >7 mutations per 106 bases (2 samples) and nonhypermutated defined as < 3 mutations per 106 bases (10 samples). Red, MSI high, light blue, MSI low. Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Altered pathways and genes plots for the 12 AA samples.

Figure 3. The dark horizontal lines separate the genes belonging to different pathways. Gene alteration defined as the presence of at least one protein changing mutation in the gene. The definition of altered pathway is at least one altered gene in the pathway.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Gene Mutations in African Americans with CRC

Figure 4. The genes with top highest frequency in the 12 samples indicated by white and dark bars. White bars indicate 6 genes (APC, KRAS, ZNF568, CACNA1C, TEL02, SRMS) that have a significantly (p<0.05) higher frequency of mutation above background (as determined by MuSiC). Background mutation rate (BMR) is defined as the number of mutations per length of genome with read coverage that is sufficient to call a mutation. Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Figure 1, supplement: APC Copy number variations using exome data. There was no copy number shift at the APC locus for any sample (blue bars).

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

African American exomes data comparison with 1000 Genome public dataset.

Figure 2, supplement: Normal samples have a higher proportion of variants that are present in the nominally normal 1000 Genomes population, compared to matched tumors. Sample CC1054 shows different profile with the number of variants present

in the tumor and normal at 75% and 88%, respectively.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Somatic SNSs pattern in the AA adenocarcinomas.

Figure 3, supplement. A) Somatic mutations spectrum in 12 colorectal adenocarcinomas showed a high rate of nucleotide C:G> T:A transition across individual samples and B) in all CRC samples combined.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Tumor suppressor and oncogenes alteration in the CRC samples.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Mutation spectra of SNS and preferential targeting of APC gene

Figure 6, supplement:. A) MSI tumors showed C>T transition, B) The location of tumor and C) the stage of the tumors showed the same C>A or C>T transition.

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Table 1 supplement. Mutation types in colorectal cancer associated genes. Gene

APC TP53

Nonsyn synSNV SNV

1 2

1 0

frame shift deletion

5 0

stopgain SNV

5 0

Frame shift Non-frame insertion shift deletion

2 0

1 0

MSH3

MSH6

ATM

PIK3CA

AXIN2

CACNA1 C

Function

Pathway

Regulation WNT of proliferati on Anti cancer DNA repair DNA repair Phosphory lation Fatty acid synthesis Stabilize B-catenin CRC with defectivemismatch repair? MSI

Signalling

Regulate Ca release

MAPK/cal cium channel

DNA damage DNA damage DSB/cell cycle AKT signaling WNT

Ashktorab et al 2014, Cancer, “in Press”

Table 2 supplement: Total number of novel variants in 12 CRC tumors and matched normals from AA patients in this study

Total called Tumors Normals

3,422 3,405

Total in dbSNP135 1,117 1,118

dbSNP %

Novel

32.6 32.8

2,305 2,287

Table 3 supplement: Total number of novel small insertions and deletions (>1 base) in 12 CRCs and matched normals from AA

Total called Tumors Normals

241,309 238,867

Total in dbSNP135 212,732 212,181

dbSNP %

Novel

88.1 88.8

28,577 26,695

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Novel APC SNV

APC gene for validation

Sample #

Frameshift

CC1016

c.4648_4649insA

CC1017

c.4378_4384del

Frameshift

SNP

c.4401delT

CC1028

c.A7650G (A> G)

CC1029

c.1231delC

CC1060

c.648_657del

c.1234_1245del c.C4294T (C >T)

http://www.ncbi.nlm.nih.gov/SNP/tranSNP/tranSNP.cgi

c.A3418T (A>T) Ashktorab 2013, AACR Daremipouran 2013 DDW

Table 4 supplement: Known and novel APC SNVs in regard to their protein change, highly associated with CRC risk.

Sample CC1016 CC1017 CC1017 CC1028 CC1028 CC1029 CC1029 CC1029 CC1054 CC1054 CC1057 CC1060 CC1060 CC1062 CC1062

ExonicFunc frameshift insertion frameshift deletion frameshift deletion stopgain SNV synonymous SNV frameshift deletion nonframeshift deletion stopgain SNV stopgain SNV nonsynonymous SNV frameshift insertion frameshift deletion stopgain SNV stopgain SNV frameshift deletion

Ref AGGGTCC T G G C GGCATGGACCAG C C C CTGCCAGGAT A C AAAAG

Obs A T A T A A A T T -

Mutation Novel Novel Novel Novel Known Novel Novel Novel Novel Novel Novel Novel Novel Novel Novel

Nucleotide change 4648_4649insA 4378_4384del 4401delT G3862T G5826A 1231delC 1234_1245del C4294T C380A C7666A 4648_4649insA 648_657del A3418T C3313T 3867_3871del

Amino-acid change D1550fs 1460_1462del A1467fs E1288X P1942P P411fs 412_415del R1432X S127X L2556I D1550fs 216_219del R1140X Q1105X 1289_1291del

Potential APC protein changes Near MCR, should test binding to b-catenine an Near MCR, should test binding to b-catenine an Near MCR, should test binding to b-catenine an Very short APC protein, Loss the ability to regu Silent, no effect Very short APC protein, Loss the ability to regu Not sure Truncated protein with loss of normal b-cateni Extremely short truncated proteins, normally a Not sure, but should not have a big effect Near MCR, should test binding to b-catenine an Not sure, but should not have a big effect The crytstal structures should be checked for th The crytstal structures should be checked for th The crytstal structures should be checked for th

Ashktorab et al 2014, Cancer, â&#x20AC;&#x153;in Pressâ&#x20AC;?

Click to edit Master text styles Second level ● Third level ● Fourth level Ch5 ● Fifth level

Sever desmoid disease

Cancer pathways & APC

WNT

APC Number of deleterious mutations in gene 0 1 2 3 4 5 6 7 8 10 11

1 12 316 18 19 20 24 27 36 41 43 46 47 51 56 62

25 0 0 0 0 0 0 0 0 0 0

00 0 0 0 0 0 1 0 0 0 0 0 0 0 0

Adenoma 17 3 1 0 0 0 0 0 0 0 0

00 1 0 0 0 0 0 0 0 0 0 0 0 0 0

Normal

Ad. Adenoma CRC

17 4 3 1 0 1 0 0 1 0 1

10 0 0 1 1 0 2 0 0 0 0 0 0 0 0

32 1 3 0 2 1 1 3 0 1 1

01 0 1 0 0 1 0 1 2 1 1 1 1 1 1

CD44-SLC1A2 Gene Fusions in Gastric Cancer

CD44-SLC1A2 overexpression in gastric cells stimulated these pro-oncogenic traits. CD44-SLC1A2 silencing caused significant reductions in intracellular glutamate concentrations and sensitized SNU16 cells to cisplatin, a commonly used chemotherapeutic agent in gastric cancer. We conclude that fusion of the SLC1A2 gene coding region to CD44 regulatory elements likely causes SLC1A2 transcriptional dysregulation, because tumors expressing high SLC1A2 levels also tended to be CD44SLC1A2â&#x20AC;&#x201C;positive. CD44-SLC1A2 may represent a class of gene fusions in cancers that establish a prooncogenic metabolic milieu favoring tumor growth and survival. Tao, Ashktorab et al 2011 Science Trans

Genotyping in personalized care

• Germline

– Elevated LAEs, abnormal iron studies – Human hemochromatosis protein also known as the HFE. HFE-related hereditary haemochromatosis is a hereditary disease characterized by excessive intestinal absorption of dietary iron resulting in a pathological increase in total body iron stores . Elevated serum liver enzymes or elevation of the transferrin saturation. The hereditary form of the disease is most common among those of Northern European ancestry, in particular those of Celtic descent.

HFE genotyping  prophylactic

phlebotomy

– FAP syndrome – APC gene testing  colectomy

– Amsterdam criteria – Lynch syndrome/MMR genes  Surgery (colectomy, TAH/BSO)

– Azathioprine in Crohn’s disease – TPMT (thiopurine S-methyltransferade) genotyping

Genotyping in personalized care • Somatic – Metastatic colon cancer – Kras and BRAF mutations predict response to EGFR inhibitors

– Gastrointestinal Stromal Tumors (GIST) – Diagnosis: c-kit and PDGFR mutation analysis more sensitive than IHC – Treatment: Tyrosine kinase inhibitors (imatinib and sunitinib)

The Hunt for Missing Genes

Science 16 May 2014: vol. 344 no. 6185 687-689

Considering genomic risk information in the context of disease association ď&#x192;&#x2DC; Two common genetic variants: on chromosomes -6p21 -16q24 were found to be associated with Barrettâ&#x20AC;&#x2122;s esophagus in the first geneome-wide association study of susceptibility to the disorder. Su Z et al Nature Genetic Nat Genet. 2012 Sep 9;44(10):1131-1136.

Considering genomic risk information in the context of public health messages -Diabetes risk -Cardiovascular risk -Alzheimer risk

Considering genomic risk information in the context of tumor biology and populations Aggressiveness and tumor biology -White (Caucasians) -Black (African Americans) Menashe I, et al JNCI 2009, 101, 984 Ph.D., Surveillance, Epidemiology, and End Results program to investigate almost 250,000 women diagnosed with breast cancer from January 1990 through December 2003. Researchers calculated black-to-white ratios of mortality, incidence, hazard of breast cancer death (probability of dying from the disease), and incidence- based mortality, with some analyses stratified by estrogen receptor (ER) status and age.

-Chines

Epstein-Barr virus (EBV) infection is malignant transformation and cancer development in various forms, including Burkittâ&#x20AC;&#x2122;s lymphoma and nasopharyngeal carcinoma, one of the most common cancers in southern China.

A tumor analysis approach based on a â&#x20AC;&#x153;sequence everythingâ&#x20AC;? approach. Combines whole-genome and whole-transcriptome sequencing

Alterations in gene structure, copy number, and expression within a tumor

Evaluation of the findings by a multidisciplinary tumor board ensures that any resulting treatment recommendations are based on all available biological and clinical data as well as ethical considerations

Modified by Asktorab [Christopher L. Corless; Science 2 December 2011: Vol. 334 no. 6060 pp. 1217-1218]

OncoDx panel for CRC

Challenges for future research • Understanding the molecular pathways in the cancer genome using WGS or WES • Studies in human cells or humanized systems. • Adding to these are development of new biologic therapies to exploit cancer genetics and • focus on early detection and new prevention strategies based on sophisticated molecular genomic technologies and imaging for detection and prevention.

Medicine of the past: â&#x20AC;&#x153;Trial-and-Errorâ&#x20AC;? medicine

Observe

Diagnose

Monitor response

Treat

Adjust

Personalized Medicine New Paradigm: Personalized Medicine Linking Tests to Action and Therapy

Observation

Test

Action

Predictable Response

Breaking The Cycle of Trial and Error Medicine

The search.A scheme to identify new treatments for disease is shown that begins with screening large populations of seemingly healthy people for disease-associated variations in their genomes.

S H Friend, and E E Schadt Science 2014;344:970-972

Published by AAAS

Next-Generation Stool DNA Test Accurately Detects Colorectal Cancer and Large Adenomas

David A. Ahlquist et al 2012, Gastrojournal

Dr. Gobena Ameni Addis Ababa University Systems Biology for Molecular Analysis of Tuberculosis in Ethiopia (NIH U01HG007472)

H3=Human Heredity and Health

Rotimi C, Science June 2014, Vol 334,(1690);1347

Gaps in the delivery of routine WGS of healthy individuals.

R Drmanac Science 2012;336:1110-1112

Acknowledgements Howard University Daremipouran, Brim, Lee, Shokrani, Laiyemo, Sanderson, Begum, Nouraie, Rahi,

HiThru Analytics Sudhir Varma

Children National Hospital Joe Devaney Grant support: NIH and RCMI, GHUCCTS, PI: Ashktorab

No longer an abstract concept for the future, the exciting reality of powerful genome testing has decisively arrived…….

አአአአአአአ (ameseginalehugn) Dr. Sherif Zaki, and Dr. Ahmed

Thank you

ሰሰሰሰሰ ሰሰሰሰሰሰሰ ሰሰሰሰሰሰ ሰሰሰሰሰሰሰ ሰሰሰሰሰሰ ሰሰሰሰሰ ሰሰሰሰሰ ሰሰሰሰሰሰ ሰሰሰ ሰሰሰሰሰሰ ሰሰሰ ሰሰሰሰሰሰ Latest Research Results and Possible Interventions and Therapeutic Approaches for Gastrointestinal Cancers

Rotimi C, Science June 2014, Vol 334,(1690);1347

Colorectal Cancer Type

Ashktorab et al 2010, 2011, 2012

Methods o

Normal, Adenoma and Colon Cancer

o CpG island o

Chip-Array

Whole genome methylation sequencing

CpG island methylation in the normal to cancer sequence using Illumina 27K chip array

A clear [7 adenoma + 2normal] cluster and 12 cancer cluster were observed indicating the significance and importance of DNA methylation in CRC progression. Ashktorab et al PLoS One 2010, Gastroenterology. 2011, Vol. 140, Issue 5, Supplement 1, Page S-191

CpG island hypermethylation in colon cancer and the proposed DNA methylation signature for prognosis.

Carmona F J , Esteller M Clin Cancer Res 2011;17:1215-1217 Cai et al 2012 PLoSone , Mokarram 2009 PLoSone 2009

RRBS Methods

RRBS of Normal vs. Tubular A

Figure 1. A) Average methylation of promoter in normal and tubular colon based on RefSeq gene annotations. Promoters that were hypermethylated only in normal colon shown in red, those hypermethlylated only in colon tubular in blue and promoters hypermethylated in both are shaded orange. 1 B). Promoters from figure 1A filtered to include genes associated with various Gene Ontology terms. The Y axis shows the average methylation in normal and the X-axis shows the average in colon tubular adenoma.

RRBS of Normal vs. Tumor A

Figure 2. A) Average methylation of promoter in tumor and normal based on RefSeq gene annotations. Promoters that were hypermethylated only in tumor shown in red, those hypermethlylated only in normal in blue and promoters hypermethylated in both are shaded orange. Figure 2 B). Promoters from 2A filtered to include genes associated with various Gene Ontology terms. The Y axis shows the average methylation in tumor and the Xaxis shows the average in Normal colon.

List of Top Candidate Genes RGS3 EID3 GNAS

chr9 Regulator of G-protein signaling (Breast-ca) chr12 EP300 interacting inhibitor of differentiation chr20 highly complex imprinted expression pattern (prostate-

ATXN7L1 GAS7 HNRNPF GPR75 SOX15 TNFAIP2

chr7 chr17 chr10 chr2 G protein-coupled receptor chr17 SRY (sex determining region Y)-box chr14 Tumor necrosis factor, alpha-induced protein (Head-Neck-

CHD5 chr1 Septin 9 chr17 Vimentin chr10

ca) HAT activity Growth arrest-specific associated with pre-mRNAs and regulate mRNA

ca) Effect on chromatin structure and gene expression as TS Cytokinesis and cell cycle control as TS Maintaining cell shape, integrity of the cytoplasm, and stabilizing cytoskeletal interactions

Validation of Methylation

17 CpG

Epigenetic Markers During Colon Cancer Progression Vimentin SLC5A8 FAT1 RASGFR2 MINT1 MINT31 SFRP1 SFRP2 CHD13 CRB1 RUNX3

GAS7, CHD5 P14 hMLH1 HLTFARF HIC1 ITGA CDKN2A/p16 CDH1 RASSF1A ESR1

DKK-1 Sept9 TIMP3 CXCL12 ID4 IRF8 miR-34b/c , -148a, -9-1

Multistep epigenetic model of colorectal carcinogenesis.

Candidate Gene and Targeted Therapeutic -Stage IIIb, male, 58, Shirazi -5Fu-based chemotherapy -186 gene hyper methylated, -13 hypomethylated -28 was found in the literature -One gene was novel for the hypomethylation cartilage oligomeric matrix protein (COMP). This protein is found in the extracellular matrix, which is an intricate lattice of proteins and other molecules that forms in the spaces between cells. Specifically, the COMP protein is located in the extracellular matrix surrounding the cells that make up ligaments and tendons and near cartilage-forming cells (chondrocytes). -COMP believed to play a role in cell growth and division (proliferation) and, as well as in the regulation of cell movement and attachment.

Summary â&#x20AC;˘ This work provides insight into differential CpG island methylation profiles and methylation drivers in CRA, CRC vs. normal colon tissue and provides an opportunity in early detection, diagnosis and prognosis of CRC.

Past, Present and Future history of CpG Island Methylation in Colorectal Cancer

Modified by Ashktorab (Karen Curtin et al, Pathology Research International Volume 2011).

Genetic and epigenetic

Gradient of CpG island DNA methylation and MSI in colon cancers in the large intestine

Personalized Medicine New Paradigm: Personalized Medicine Linking Tests to Action and Therapy

Observation

Test

Action

Predictable Response

Breaking The Cycle of Trial and Error Medicine

METHODS (Cont’d) • RRBS – The alignment algorithm used was based on a modified BSSeeker program. The pairwise analysis data was generated using a proprietary analysis software (based on R and Python). – The top 100 hypermethylated genes in adenoma and tumor were chosen. Those CAN genes which were part of Wnt, EGRF, Notch, and MAP-ERK pathway were selected based on the literature review. – The CpG islands in the promoter, LINE, SINE and miRNA region was analyzed using USC genes browser. – Twelve genes selected for loci validation and ACTB was used as a reference gene.

Demography of the samples Sample

Type

Sex

Locatio Age n

Normal tissue

Normal colon mucosa

Adenoma

Tubular

Cancer

T3N1M1, stage 4

Normal healthy colon (cc0734T), tubular adenoma (CC0231) and cancer (CC07-353)

‫ععتععع شکر دارم و از‬ ‫از بخ‬

‫‪ ‬ديدار شد ميسر و بوس و کنار‬

‫روزگار همجامم به دست باشد‬

‫عدععع برو کعهعع طالععع اگر‬ ‫همزاه‬

‫و زلععفع نگار هملعل بتان‬

‫طالع من استما عيب کس به‬

‫عتععع و می خوشگوار‬ ‫خوش اس‬

‫یکنيمای دل‬ ‫مستی و رندی نم ‌‬

‫همو از می جهان پر است و‬

‫محتسب‬

‫بععتع‬

‫ميگسار‬

‫بشارتعععیع‬

‫دهمععتعع‬ ‫ع‬

‫هممجموع‌های‬

‫عتععع تفرقه‬ ‫عرععع بعهع دس‬ ‫نماندخاط‬

‫عرعععاحی بيار همتا‬ ‫بخواه و عص‬

‫دادن نععهع زيرکيستبر خاکيان‬

‫خاک لعل گون شود و مشکبار‬

‫عشق فشان جرعه لبشآن شد‬

‫عمععع از ميان برفت و‬ ‫همخص‬ ‫ع‬

‫عمععع بد نگران بودی از‬ ‫کعه ع چش‬

‫سرشک از کنار همای آفتاب‬

‫کمينچون کانات جملعهع به بوی‬

‫عاعععيه ز ما برمدار همای ابر‬ ‫س‬

‫هاندچون آب روی لله و‬ ‫تو زند ‌‬

‫عفععع بر معنعع خاکعی ع ببار همو‬ ‫لط‬

‫عنععع توستحافظ‬ ‫گعلعع فيعضع حس‬

‫عفععع جم اقتدار‬ ‫عاعععف آص‬ ‫از انتص‬

‫عيعععر زلعفع تعوع شد از خدا‬ ‫اس‬

‫وعنع که ز‬ ‫رسیدو دي‬ ‫بترسبرهان ملک‬ ‫بهو دريا‬ ‫عدععع‬ ‫زودی ش‬ ‫به کان يميعنع‬ ‫همايام‬ ‫روزگار‬ ‫هدف و آرزوی خود خواهی‬ ‫تعبیر‪:‬‬ ‫حسادترای انور‬ ‫عتعععووزارتشبر ياد‬ ‫دس‬ ‫یکند‬ ‫همجان م ‌‬ ‫عاعععر‬ ‫يس‬ ‫دیگران‬ ‫بدخواهی‬ ‫فدا وفرا می رسد‪.‬‬ ‫نیکبختی‬ ‫سعادت و‬ ‫عبعععحگوی زمين‬ ‫بهبعهع ص‬ ‫عمعععان‬ ‫او آس‬ ‫کواکعبعع‬ ‫خود را‬ ‫نفس‬ ‫اعتماد‬ ‫برکشيدهتو نخواهد داشت‪.‬‬ ‫همويناراده‬ ‫نثار در‬ ‫تأثیری‬

Acknowledgements Howard University Daremipouran, Brim, Lee, Shokrani, Laiyemo, Sanderson, Begum, Nouraie, Rahi,

Zymo Research Ron Leavitt, Xueguang Sun,

HiThru Analytics Sudhir Varma

Children National Hospital Joe Devaney Grant support: NIH and RCMI, GHUCCTS, PI: Ashktorab

Proprotein convertase subtilisin/kexin type 9, also known as PCSK9, is an enzyme that in humans is encoded by thePCSK9 gene.[1] Similar genes (orthologs) are found across many species. Many enzymes, including PSCK9, are inactive when they are first synthesized, because they have a section of peptide chains that blocks their activity; proprotein convertasesremove that section to activate the enzyme. PCSK9 has medical significance because it acts in cholesterol homeostasis. Drugs that block PCSK9 can lower low-density lipoprotein cholesterol (LDL-C), and are beginning Phase III clinical trials to assess their safety and efficacy in humans, and to determine if they can improve outcomes in heart disease.[2][3] As a drug target Drugs can inhibit PCSK9, and lower cholesterol much more than available drugs. It is biologically plausible that this would also lower the risk of heart attack and other diseases for which raised cholesterol is a risk factor. Studies with humans, including phase III clinical trials are now underway to find out whether PCSK9 inhibition actually does lower disease, with acceptable side effects.[8][9][10][11] Among those inhibitors which were under development in December 2013 are the antibodies alirocumab, evolocumab, bococizumab, RG-7652 and LY3015014, as well as the RNAi therapeutic ALN-PCS02.[12]