Computational approaches to identify functional genetic variants in cancer genomes

2013 Nature Methods  
perspective nature methods | VOL.10 NO.8 | AUGUST 2013 | 723 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
more » ... to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. Large-scale sequencing of cancer genomes often reveals many thousands of somatic missense (amino acid-changing) mutations in proteins. However, not all cancer mutations provide a selective ('driving') advantage to cancer cells 1,2 . Many mutations are socalled 'passengers' because their impact on protein function is either minor or the affected protein is not important for tumor progression. The important practical problem is to determine which mutations are likely drivers. Although the carcinogenicity of a particular mutation depends on concurrent genomic alterations in the cell, one can considerably decrease the number of potential driver candidates by determining the functional impact of each mutation. Thus, a key challenge is to distinguish between functional and nonfunctional mutations, and by extension between those that contribute to tumorigenesis (drivers) and those that do not (passengers) (see Box 1 for definitions). Cancer has been likened to an evolutionary process by which tumor cells gain a fitness advantage over their neighboring cells 2 . The process creates cells with altered abilities such as the circumvention of apoptosis and senescence, deregulated cell division and failed responses to external cues such as contactcontact inhibition and ligand-mediated cell signaling 3,4 . Normal cells are reprogrammed by changes in the genome that are subsequently selected and
doi:10.1038/nmeth.2562 pmid:23900255 pmcid:PMC3919555 fatcat:6v3wgyr36jgibnqc3y2isl4cjq