Characterizing genomic alterations in cancer by complementary functional associations

Jong Wook Kim, Olga B Botvinnik, Omar Abudayyeh, Chet Birger, Joseph Rosenbluh, Yashaswi Shrestha, Mohamed E Abazeed, Peter S Hammerman, Daniel DiCara, David J Konieczkowski, Cory M Johannessen, Arthur Liberzon, Amir Reza Alizad-Rahvar, Gabriela Alexe, Andrew Aguirre, Mahmoud Ghandi, Heidi Greulich, Francisca Vazquez, Barbara A Weir, Eliezer M Van AllenAviad Tsherniak, Diane D Shao, Travis I Zack, Michael Noble, Gad Getz, Rameen Beroukhim, Levi A Garraway, Masoud Ardakani, Chiara Romualdi, Gabriele Sales, David A Barbie, Jesse S Boehm, William C Hahn, Jill P Mesirov, Pablo Tamayo

Research output: Contribution to journalArticleResearchpeer-review

44 Citations (Scopus)

Abstract

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes.
Original languageEnglish
Pages (from-to)539-546
Number of pages8
JournalNature Biotechnology
Volume34
Issue number5
DOIs
Publication statusPublished - 18 Apr 2016
Externally publishedYes

Keywords

  • cancer genomics
  • software
  • statistical methods

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