4.8 Article

Systematic Functional Annotation of Somatic Mutations in Cancer

Journal

CANCER CELL
Volume 33, Issue 3, Pages 450-+

Publisher

CELL PRESS
DOI: 10.1016/j.ccell.2018.01.021

Keywords

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Funding

  1. US NIH [CA168394, CA098258, CA143883, HG008100, CA175486, CA209851, CA176284, CA70907, CA204817, CA200266]
  2. Cancer Prevention and Research Institute of Texas [RP140462, RR160021, RP150535]
  3. Adelson Medical Research Foundation
  4. Hong Kong Research Grants Council [27103616]
  5. National Natural Science Foundation of China [81703066]
  6. AstraZeneca UK Limited
  7. AACR Project GENIE registry
  8. US NIH (Cancer Center) [CA016672]
  9. NATIONAL CANCER INSTITUTE [U01CA168394, U24CA209851, P50CA098258, U24CA143883, U24CA210950, U01CA176284, R01CA175486, R50CA221675, P30CA008748, P30CA016672, F31CA200266, P50CA070907, U01CA217842, U24CA204817] Funding Source: NIH RePORTER
  10. NATIONAL HUMAN GENOME RESEARCH INSTITUTE [U54HG008100] Funding Source: NIH RePORTER

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The functional impact of the vast majority of cancer somatic mutations remains unknown, representing a critical knowledge gap for implementing precision oncology. Here, we report the development of a moderate-throughput functional genomic platform consisting of efficient mutant generation, sensitive viability assays using two growth factor-dependent cell models, and functional proteomic profiling of signaling effects for select aberrations. We apply the platform to annotate >1,000 genomic aberrations, including gene amplifications, point mutations, indels, and gene fusions, potentially doubling the number of driver mutations characterized in clinically actionable genes. Further, the platform is sufficiently sensitive to identify weak drivers. Our data are accessible through a user-friendly, public data portal. Our study will facilitate biomarker discovery, prediction algorithm improvement, and drug development.

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