Gonzalez-Perez, Abel4; Mustonen, Ville5; Reva, Boris18; Ritchie, Graham R S18; Creixell, Pau1; Karchin, Rachel19; Vazquez, Miguel8; Fink, J Lynn20; Kassahn, Karin S20; Pearson, John V20; Bader, Gary D21; Boutros, Paul C22; Muthuswamy, Lakshmi22; Ouellette, B F Francis22; Reimand, Jüri21; Linding, Rune1; Shibata, Tatsuhiro12; Valencia, Alfonso13; Butler, Adam5; Dronov, Serge5; Flicek, Paul14; Shannon, Nick B15; Carter, Hannah19; Ding, Li16; Sander, Chris18; Stuart, Josh M17; Stein, Lincoln D21; Lopez-Bigas, Nuria4
1 Department of Systems Biology, Technical University of Denmark2 Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark3 Cellular Signal Integration, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark4 Pompeu Fabra University5 Wellcome Trust Genome Campus6 Memorial Sloan-Kettering Cancer Center7 Johns Hopkins University8 Spanish National Cancer Research Centre9 University of Queensland10 University of Toronto11 Ontario Institute for Cancer Research12 National Cancer Center13 Spanish National Bioinformatics Institute14 European Bioinformatics Institute15 Cambridge Research Institute16 Washington University in St. Louis17 University of California18 Memorial Sloan-Kettering Cancer Center19 Johns Hopkins University20 University of Queensland21 University of Toronto22 Ontario Institute for Cancer Research
The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.