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SELECTBIO Conferences Advances in NGS & Big Data


Signatures of Tumor Clonal Evolution Reveal Novel Driver Genes and Networks in Chronic Lymphocytic Leukemia

Stephan Ossowski, Group Leader, Centre for Genomic Regulation

Tumors evolve over time and accumulate somatic mutations, which can increase proliferation, decreased apoptosis or generally enhance fitness of tumor cells. Acquisition of alterations conferring a selective growth advantage to a neoplastic tissue over surrounding normal or tumor cells leads to a rapid increase of the mutated clone within the tumor, thus resulting in tumor heterogeneity. The predominant subpopulation of tumors can change over time, is heavily influenced by treatment and often differs in metastasizing tumor cells. Cancer treatment can be thought of as a strong form of selective pressure, leading to the selection and growth of cancer cells that acquired resistance mediated by specific mutations. Today next generation sequencing (NGS) technologies allow for the identification of heterogeneous alterations and the quantification of the fraction of tumor cells harboring a specific alteration. Circulating tumors, such as leukemias, are particularly suitable models for cancer clonal evolution, as cancerous lymphocytes are evenly distributed by blood flow and fitness of clones can be measured by their cancer cell fraction (CCF) within all cancerous lymphocytes. Here we studied 350 cases of chronic lymphocytic leukemia (CLL), a slowly progressing tumor of the B-lymphocytes. Exome-seq data of 350 CLL tumor-normal pairs from the ICGC-CLL project was analyzed to identify germline and somatic SNVs, indels and copy number variants. Using the deviation of non-reference allele frequency (BAF) values of SNPs, indels and CNVs from perfect heterozygosity we characterized tumor sub-clones down to 10% cancer cell fraction. To take advantage of this data for discovery of CLL driver genes we developed a novel Bayesian model for identification of recurrently mutated genes taking into account measures of positive selection and clonal fitness, e.g. CCF of variants, Ka/Ks and enrichment of highly damaging mutations, as well as locally adjusted background mutation rates. Our m

Add to Calendar ▼2014-05-14 00:00:002014-05-15 00:00:00Europe/LondonAdvances in NGS and Big DataAdvances in NGS and Big Data in Barcelona, SpainBarcelona,