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The genomic and epigenomic evolution of cancer
Wednesday, February 26, 2014, 12:00-1:00 pm Calendar
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Abstract

Cancer is a fundamentally Darwinian process where millions of genetically and epigenetically heterogeneous tumor cells compete in the presence of diverse and changing selective pressures imposed by the cells themselves, the microenvironment and treatment, e.g. chemotherapy. As illustrated by the nearly systematic acquisition of resistance in patients treated with targeted anticancer agents, this Darwinian process presents formidable challenges for cancer therapy.
In the first part of the talk, I will describe our attempts to study clonal heterogenity and tumor evolution at the genomic and epigenomic level in B cell lymphomas. As their name indicates, B cell lymphomas originate from B cells,which undergo a unique process of VDJ recombination and somatic hypermutation. These unique features of B cells and B cell lymphomas effectively tag clonal populations of tumor cells. I will show how the combination of high-throughput sequencing of VDJ junctions and exome sequencing provides unique insights into clonal heterogeneity and evolutionary patterns in patients with relapsed lymphoma. I will describe additional new insights on the epigenomic evolution of lymphomas.
In the second part of the talk, I will describe how the Darwinian process that drives populations of tumor cells also provides key opportunities for unraveling mechanisms of action and targets of anticancer molecules directly in human cells. I will present an unbiased, genomewide approach that combines next-generation sequencing and bioinformatic analysis for identification of these mechanisms of action. This approach is based on the isolation of multiple drug resistant clones and rapid sequencing using RNA-seq. Importantly, this approach can identify mechanisms of resistance to anticancer drugs long before any patients are treated with these molecules, thus paving the way for pre-treatment genotyping of patients. It also predicts combinations of drugs that should slow down or prevent the acquisition of resistance.

Bio

Dr. Elemento initially trained as a mechanical enginneer at INSA Toulouse in France. He then obtained a master in Intelligent Sytems from University of Paris, and a PhD in Computational Biology from the CNRS. He was then a postdoctoral fellow and lecturer at Princeton University, working on unravelling and characterizing transcriptional and posttranscriptional networks using computational genomic approaches. In 2009, he joined Weill Cornell Medical College as Assistant Professor.  At Weill Cornell, Dr Elemento directs the Laboratory of Cancer Systems Biology. The Elemento lab at Weill Cornell uses ultrafast genome and DNA sequencing, high-performance computing, mathematical modeling, Big Data and machine learning techniques to develop entirely new ways to help prevent, diagnose, treat and ultimately cure cancer. In addition, Dr Elemento oversees the development of analytic pipelines for clinical sequencing at Weill Cornell's Institute for Precision Medicine. Dr Elemento is the recipient of several awards including the NSF CAREER award, the Hirschl trust Career Scientist Award and the Starr Cancer Consortium award and organizes several educational activities such as the the NIH-funded Summer Course on Statistical Methods for Functional Genomics at the Cold Spring Harbor Laboratories.

This talk is organized by Steve Mount