Identification of cancer driver genes based on nucleotide context.

TitleIdentification of cancer driver genes based on nucleotide context.
Publication TypeJournal Article
Year of Publication2020
AuthorsDietlein, F, Weghorn, D, Taylor-Weiner, A, Richters, A, Reardon, B, Liu, D, Lander, ES, Van Allen, EM, Sunyaev, SR
JournalNat Genet
Date Published2020 02
KeywordsCluster Analysis, Computational Biology, Humans, Mutation, Neoplasms, Nucleotides, Proteins, Whole Exome Sequencing

Cancer genomes contain large numbers of somatic mutations but few of these mutations drive tumor development. Current approaches either identify driver genes on the basis of mutational recurrence or approximate the functional consequences of nonsynonymous mutations by using bioinformatic scores. Passenger mutations are enriched in characteristic nucleotide contexts, whereas driver mutations occur in functional positions, which are not necessarily surrounded by a particular nucleotide context. We observed that mutations in contexts that deviate from the characteristic contexts around passenger mutations provide a signal in favor of driver genes. We therefore developed a method that combines this feature with the signals traditionally used for driver-gene identification. We applied our method to whole-exome sequencing data from 11,873 tumor-normal pairs and identified 460 driver genes that clustered into 21 cancer-related pathways. Our study provides a resource of driver genes across 28 tumor types with additional driver genes identified according to mutations in unusual nucleotide contexts.

Alternate JournalNat. Genet.
PubMed ID32015527
PubMed Central IDPMC7031046
Grant ListK08 CA188615 / CA / NCI NIH HHS / United States
R21 CA242861 / CA / NCI NIH HHS / United States
R01 CA227388 / CA / NCI NIH HHS / United States
R35 GM127131 / GM / NIGMS NIH HHS / United States
R01 MH101244 / MH / NIMH NIH HHS / United States
U01 HG009088 / HG / NHGRI NIH HHS / United States