High-throughput Phenotyping of Lung Cancer Somatic Mutations

Alice H. Berger, Angela N. Brooks, Xiaoyun Wu, Yashaswi Shrestha, Candace Chouinard, Federica Piccioni, Mukta Bagul, Atanas Kamburov, Marcin Imielinski, Larson Hogstrom, Cong Zhu, Xiaoping Yang, Sasha Pantel, Ryo Sakai, Jacqueline Watson, Nathan Kaplan, Joshua D. Campbell, Shantanu Singh, David E. Root, Rajiv NarayanTed Natoli, David L. Lahr, Itay Tirosh, Pablo Tamayo, Gad Getz, Bang Wong, John Doench, Aravind Subramanian, Todd R. Golub, Matthew Meyerson, Jesse S. Boehm

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)214-228
Number of pages15
JournalCancer Cell
Volume30
Issue number2
DOIs
StatePublished - Aug 8 2016
Externally publishedYes

ASJC Scopus subject areas

  • Oncology
  • Cell Biology
  • Cancer Research

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