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High-throughput Phenotyping of Lung Cancer Somatic Mutations

Authors :
Sasha Pantel
Jesse S. Boehm
Federica Piccioni
John G. Doench
Nathan O. Kaplan
Matthew Meyerson
David L. Lahr
Shantanu Singh
Ryo Sakai
Yashaswi Shrestha
Jacqueline Watson
Marcin Imielinski
Gad Getz
Todd R. Golub
Itay Tirosh
Alice H. Berger
Xiaoping Yang
David E. Root
Bang Wong
Xiaoyun Wu
Candace R. Chouinard
Joshua D. Campbell
Larson Hogstrom
Rajiv Narayan
Cong Zhu
Pablo Tamayo
Angela N. Brooks
Mukta Bagul
Ted Natoli
Atanas Kamburov
Aravind Subramanian
Source :
Cancer cell, vol 30, iss 2
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Recent genome sequencing efforts have identified millions of somatic mutations in cancer. However, the functional impact of most variants is poorly understood. Here we characterize 194 somatic mutations identified in primary lung adenocarcinomas. We present an expression-based variant-impact phenotyping (eVIP) method that uses gene expression changes to distinguish impactful from neutral somatic mutations. eVIP identified 69% of mutations analyzed as impactful and 31% as functionally neutral. A subset of the impactful mutations induces xenograft tumor formation in mice and/or confers resistance to cellular EGFR inhibition. Among these impactful variants are rare somatic, clinically actionable variants including EGFR S645C, ARAF S214C and S214F, ERBB2 S418T, and multiple BRAF variants, demonstrating that rare mutations can be functionally important in cancer.

Details

ISSN :
15356108
Volume :
32
Database :
OpenAIRE
Journal :
Cancer Cell
Accession number :
edsair.doi.dedup.....2abf300db707973c151c98eba6e68494
Full Text :
https://doi.org/10.1016/j.ccell.2017.11.008