Characterizing genomic alterations in cancer by complementary functional associations.
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ABSTRACT:
SUBMITTER: Kim JW
PROVIDER: S-EPMC4868596 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
Publications
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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Project description:The Cancer Genome Atlas (TCGA) Research Network is an ambitious multi-institutional consortium effort aimed at characterizing sequence, copy number, gene (mRNA) expression, microRNA expression, and DNA methylation alterations in 30 cancer types. TCGA data have become an extraordinary resource for basic, translational, and clinical researchers and have the potential to shape cancer diagnostic and treatment strategies. DNA methylation changes are integral to all aspects of cancer genomics and have been shown to have important associations with gene expression, sequence, and copy number changes. This Review highlights the knowledge gained from DNA methylation alterations in human cancers from TCGA.
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Project description:PurposeSMARCA4 mutations are among the most common recurrent alterations in non-small cell lung cancer (NSCLC), but the relationship to other genomic abnormalities and clinical impact has not been established.Experimental designTo characterize SMARCA4 alterations in NSCLC, we analyzed the genomic, protein expression, and clinical outcome data of patients with SMARCA4 alterations treated at Memorial Sloan Kettering.ResultsIn 4,813 tumors from patients with NSCLC, we identified 8% (n = 407) of patients with SMARCA4-mutant lung cancer. We describe two categories of SMARCA4 mutations: class 1 mutations (truncating mutations, fusions, and homozygous deletion) and class 2 mutations (missense mutations). Protein expression loss was associated with class 1 mutation (81% vs. 0%, P < 0.001). Both classes of mutation co-occurred more frequently with KRAS, STK11, and KEAP1 mutations compared with SMARCA4 wild-type tumors (P < 0.001). In patients with metastatic NSCLC, SMARCA4 alterations were associated with shorter overall survival, with class 1 alterations associated with shortest survival times (P < 0.001). Conversely, we found that treatment with immune checkpoint inhibitors (ICI) was associated with improved outcomes in patients with SMARCA4-mutant tumors (P = 0.01), with class 1 mutations having the best response to ICIs (P = 0.027).ConclusionsSMARCA4 alterations can be divided into two clinically relevant genomic classes associated with differential protein expression as well as distinct prognostic and treatment implications. Both classes co-occur with KEAP1, STK11, and KRAS mutations, but individually represent independent predictors of poor prognosis. Despite association with poor outcomes, SMARCA4-mutant lung cancers may be more sensitive to immunotherapy.
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