| Literature DB >> 29533785 |
Patrick Kwok-Shing Ng1, Jun Li2, Kang Jin Jeong3, Shan Shao1, Hu Chen4, Yiu Huen Tsang5, Sohini Sengupta6, Zixing Wang2, Venkata Hemanjani Bhavana5, Richard Tran1, Stephanie Soewito1, Darlan Conterno Minussi7, Daniela Moreno5, Kathleen Kong5, Turgut Dogruluk5, Hengyu Lu5, Jianjiong Gao8, Collin Tokheim9, Daniel Cui Zhou6, Amber M Johnson1, Jia Zeng1, Carman Ka Man Ip3, Zhenlin Ju2, Matthew Wester3, Shuangxing Yu3, Yongsheng Li3, Christopher P Vellano3, Nikolaus Schultz8, Rachel Karchin10, Li Ding11, Yiling Lu3, Lydia Wai Ting Cheung12, Ken Chen2, Kenna R Shaw1, Funda Meric-Bernstam13, Kenneth L Scott5, Song Yi14, Nidhi Sahni15, Han Liang16, Gordon B Mills3.
Abstract
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.Entities:
Keywords: TCGA; cellular assay; clinical marker; driver mutation; drug sensitivity; functional genomics; functional proteomics; therapeutic target
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Year: 2018 PMID： 29533785 PMCID： PMC5926201 DOI： 10.1016/j.ccell.2018.01.021
Source DB: PubMed Journal: Cancer Cell ISSN： 1535-6108 Impact factor: 31.743