Functional Genomics of Solid Tumors , Centre de Recherche des Cordeliers, Paris
Biography
After a general training in life sciences at the Ecole Normale Supérieure of Lyon, Eric Letouze specialized in the bioinformatic analysis of high-throughput genomic data, applied to cancer research. During his PhD at Institut Curie and as a post-doc at the Ligue Nationale Contre le Cancer, he was involved in the identification of novel therapeutic targets and molecular markers of prognosis.He also designed innovative computational tools for the analysis of high-throughput genomic data. He joined the INSERM team "Genomics of liver and mesothelial tumors", led by Jessica Zucman-Rossi, in May 2014 to develop a new research area on the genetic and epigenetic signatures of oncogenic processes, with an emphasis on liver tumors.
His research project aims at understanding how the interaction of the genetic background and environmental exposures lead a healthy cell to become malignant, and how the genetic diversity of liver tumors is established. To do so, his team develops innovative computational approaches to extract biological insights from large genomic datasets, including whole-exome and whole-genome sequencing,RNA-sequencing and DNA methylation data. His current projects include identifying rare variants predisposing to liver cancer in whole-exome data, analyzing mutational signatures and the clonal architecture of tumors using whole-genome data, or exploring the transcriptome of liver tumors and its interaction with epigenetic alterations.
His research project aims at understanding how the interaction of the genetic background and environmental exposures lead a healthy cell to become malignant, and how the genetic diversity of liver tumors is established. To do so, his team develops innovative computational approaches to extract biological insights from large genomic datasets, including whole-exome and whole-genome sequencing,RNA-sequencing and DNA methylation data. His current projects include identifying rare variants predisposing to liver cancer in whole-exome data, analyzing mutational signatures and the clonal architecture of tumors using whole-genome data, or exploring the transcriptome of liver tumors and its interaction with epigenetic alterations.
