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Identification of cancer driver genes based on nucleotide context
Name
nihms-1546846.pdf
Description
Accepted version
Size
8.61 MB
Format
Adobe PDF
Checksum (MD5)
91a01ccb7eaf638e78f23868acf6e7f2
Author(s)
Dietlein, Felix
Weghorn, Donate
Taylor-Weiner, Amaro
Richters, André
Reardon, Brendan
Liu, David
Lander, Eric S
Van Allen, Eliezer M
Sunyaev, Shamil R
Date Issued
2020
Journal
Nature Genetics
Publisher
Springer Science and Business Media LLC
Version
Author's final manuscript
Abstract
© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. 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.
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
10.1038/S41588-019-0572-Y
