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Characterizing genomic alterations in cancer by complementary functional associations.


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 ?-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.

SUBMITTER: Kim JW 

PROVIDER: S-EPMC4868596 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Characterizing genomic alterations in cancer by complementary functional associations.

Kim Jong Wook JW   Botvinnik Olga B OB   Abudayyeh Omar O   Birger Chet C   Rosenbluh Joseph J   Shrestha Yashaswi Y   Abazeed Mohamed E ME   Hammerman Peter S PS   DiCara Daniel D   Konieczkowski David J DJ   Johannessen Cory M CM   Liberzon Arthur A   Alizad-Rahvar Amir Reza AR   Alexe Gabriela G   Aguirre Andrew A   Ghandi Mahmoud M   Greulich Heidi H   Vazquez Francisca F   Weir Barbara A BA   Van Allen Eliezer M EM   Tsherniak Aviad A   Shao Diane D DD   Zack Travis I TI   Noble Michael M   Getz Gad G   Beroukhim Rameen R   Garraway Levi A LA   Ardakani Masoud M   Romualdi Chiara C   Sales Gabriele G   Barbie David A DA   Boehm Jesse S JS   Hahn William C WC   Mesirov Jill P JP   Tamayo Pablo P  

Nature biotechnology 20160418 5


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 depen  ...[more]

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