Basic Research ???
Basic Research
Bioinformatics and Evolutionary Genomics of Cancer Francesca CICCARELLI, PhD Director
STAFF Post-doctoral Fellows: Matteo Cereda, PhD, Matteo D’Antonio, PhD, Fabio Iannelli, PhD, Elena Gatti, PhD, Fiorella Guerra, PhD PhD Students: Omer An, Vera Pendino, Shruti Sihna VisitorS: Marco Gentilini, Emanuele Ratti
Activities 2012.
Our group studies the effects of genomic instability in the development of human cancer. We tackle this issue using a combination of experimental and computational methods, with the aim of: 1. tracing the progressive acquisition of mutations during cancer development; 2. identifying systems-level properties of cancer genes; 1. Measure of somatic and constitutional genomic instability In addition to searching for cancer-specific mutations, we exploit deep next generation sequencing (NGS) to re-sequence several thousands single DNA filaments in parallel and unravel different aspects of cancer progression. For example, we developed a procedure for the quantification of somatic and constitutional genomic instability that is based on the detection of random mutations. We performed an ultradeep screening to identify random modifications that occur in a tiny fraction of cells, even prior to the establishment of the tumoral clone. To account for the occurrence of sequencing errors, we developed a statistical framework that relies on the ultraconserved elements of the human genome as error normalization. Using this method we were able to measure the constitutional genomic instability in individuals with heterozygous mutations in MMR genes, thus suggesting a predisposition of these individuals to acquire the second hit needed for tumor initiation. Our study constitutes the proof of principle for the development of a more sensitive molecular assay of genomic instability. We further used this feature of NGS to rebuild the
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proliferative tree of cancer clonal expansion. Mutation frequency indeed reflects the proportion of cells that bear each individual mutation while the number of somatic mutations is informative of the relative occurrence of cell death, cell proliferation, and cell quiescence during the clone formation. Following this idea, we reconstructed the proliferation trees of four colorectal tumors using their mutation profiles. We showed that the majority of the tumor mass in all four tumors is formed of a dominant subclone that started to prevail very early, although its establishment varied over time between and within tumors and seemed to be correlated with tumor genetics and clinical aggressiveness. 2. Systems biology of cancer genes We undertook a systematic study of the properties of cancer genes in the attempt of rationalizing the genetic heterogeneity of human cancer. We set out to analyze the relationship between the propensity of cancer genes to duplicate (i.e. gene duplicability) and the network properties of the encoded proteins, because connectivity and duplicability are usually indicative of gene fragility towards perturbations. We showed that cancer genes are mostly singletons and tend to encode central hubs at the crossroads of multiple biological processes. Although these properties are rare within the human gene repertoire, they are recurrent within known cancer genes, thus confirming the existence of systems-level properties – not detectable from the individual gene function – that explain the role of these genes in tumor development in terms of systems perturbation. We also discovered that most cancer genes appeared at two time points in evolution: caretakers and tumor suppressors are ancient genes that have orthologs also in prokaryotes, while gatekeepers and oncogenes were acquired with metazoans. These two time points correspond to two main transitions in evolution that led to an increase in complexity of the whole protein interaction network.
Web Servers and Public Databases a) Network of Cancer Genes: a web resource to analyze duplicability, orthology and network properties of cancer genes (http://bio.ieo.eu/ncg/) This public resource collects and integrates data on systems-level properties of cancer genes. It provides information on duplicability, orthology, evolutionary appearance and topological properties of the encoded protein in a comprehensive version of the human proteinprotein interaction network. NCG also stores information on all primary interactors of cancer proteins, thus providing a complete overview of 5357 proteins that constitute direct and indirect determinants of human cancer. b) FancyGene: dynamic visualization of gene structures and protein domain architectures on genomic loci http:// bio.ieo.eu/fancygene/) FancyGene is a web-based interactive tool for producing representations of one or more genes directly on the corresponding genomic loci. It is extremely flexible and allows the user to change the resulting image dynamically, to modify colors and shapes and to add and/or to remove objects. FancyGene is a useful tool to draw scientific pictures for scientific publications and presentations.
Publications De Grassi A, Segala C, Iannelli F, Volorio S, Bertario L, Radice P, Bernard L, Ciccarelli FD: Ultradeep sequencing of a human ultraconserved region reveals somatic and constitutional genomic instability. PloS Biol 2010, 8:e1000275. Rambaldi D, Giorgi FM, Capuani F, Ciliberto A, Ciccarelli FD: Low duplicability and network fragility of cancer genes. Trends in Genetics 2008, 24:427-430. Ciccarelli F: The (r)evolution of cancer genetics. BMC Biology 2010, 8:74. D’Antonio M, Ciccarelli F: Modification of gene duplicability during the evolution of protein interaction network. PLoS Comput Biol 2011, 7:e1002029. D’Antonio M, Pendino V, Sihna S, FD C: Network of Cancer Genes (NCG 3.0): integration and analysis of genetic and network properties of cancer genes. Nucl Acids Res 2012.
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