Dataset Information

A landscape of driver mutations in melanoma.

ABSTRACT: Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic UV light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19, and ARID2), three of which-RAC1, PPP6C, and STK19-harbored recurrent and potentially targetable mutations. Integration with chromosomal copy number data contextualized the landscape of driver mutations, providing oncogenic insights in BRAF- and NRAS-driven melanoma as well as those without known NRAS/BRAF mutations. The landscape also clarified a mutational basis for RB and p53 pathway deregulation in this malignancy. Finally, the spectrum of driver mutations provided unequivocal genomic evidence for a direct mutagenic role of UV light in melanoma pathogenesis.

SUBMITTER: Hodis E

PROVIDER: S-EPMC3600117 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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A landscape of driver mutations in melanoma.

Hodis Eran E Watson Ian R IR Kryukov Gregory V GV Arold Stefan T ST Imielinski Marcin M Theurillat Jean-Philippe JP Nickerson Elizabeth E Auclair Daniel D Li Liren L Place Chelsea C Dicara Daniel D Ramos Alex H AH Lawrence Michael S MS Cibulskis Kristian K Sivachenko Andrey A Voet Douglas D Saksena Gordon G Stransky Nicolas N Onofrio Robert C RC Winckler Wendy W Ardlie Kristin K Wagle Nikhil N Wargo Jennifer J Chong Kelly K Morton Donald L DL Stemke-Hale Katherine K Chen Guo G Noble Michael M Meyerson Matthew M Ladbury John E JE Davies Michael A MA Gershenwald Jeffrey E JE Wagner Stephan N SN Hoon Dave S B DS Schadendorf Dirk D Lander Eric S ES Gabriel Stacey B SB Getz Gad G Garraway Levi A LA Chin Lynda L

Cell 20120701 2

Despite recent insights into melanoma genetics, systematic surveys for driver mutations are challenged by an abundance of passenger mutations caused by carcinogenic UV light exposure. We developed a permutation-based framework to address this challenge, employing mutation data from intronic sequences to control for passenger mutational load on a per gene basis. Analysis of large-scale melanoma exome data by this approach discovered six novel melanoma genes (PPP6C, RAC1, SNX31, TACC1, STK19, and ...[more]

PMID: 22817889

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Project description:ImportanceFrequent mutations have been described in the following 5 genes in uveal melanoma (UM): BAP1, EIF1AX, GNA11, GNAQ, and SF3B1. Understanding the prognostic significance of these mutations could facilitate their use in precision medicine.ObjectiveTo determine the associations between driver mutations, gene expression profile (GEP) classification, clinicopathologic features, and patient outcomes in UM.Design, setting, and participantsRetrospective study of patients with UM treated by enucleation by a single ocular oncologist between November 1, 1998, and July 31, 2014.Main outcomes and measuresClinicopathologic features, patient outcomes, GEP classification (class 1 or class 2), and mutation status were recorded.ResultsThe study cohort comprised 81 participants. Their mean age was 61.5 years, and 37% (30 of 81) were female. The GEP classification was class 1 in 35 of 81 (43%), class 2 in 42 of 81 (52%), and unknown in 4 of 81 (5%). BAP1 mutations were identified in 29 of 64 (45%), GNAQ mutations in 36 of 81 (44%), GNA11 mutations in 36 of 81 (44%), SF3B1 mutations in 19 of 81 (24%), and EIF1AX mutations in 14 of 81 (17%). Sixteen of the mutations in BAP1 and 6 of the mutations in EIF1AX were previously unreported in UM. GNAQ and GNA11 mutations were mutually exclusive. BAP1, SF3B1, and EIF1AX mutations were almost mutually exclusive with each other. Using multiple regression analysis, BAP1 mutations were associated with class 2 GEP and older patient. EIF1AX mutations were associated with class 1 GEP and the absence of ciliary body involvement. SF3B1 mutations were associated with younger patient age. GNAQ mutations were associated with the absence of ciliary body involvement and greater largest basal diameter. GNA11 mutations were not associated with any of the analyzed features. Using Cox proportional hazards modeling, class 2 GEP was the prognostic factor most strongly associated with metastasis (relative risk, 9.4; 95% CI, 3.1-28.5) and melanoma-specific mortality (relative risk, 15.7; 95% CI, 3.6-69.1) (P < .001 for both). After excluding GEP class, the presence of BAP1 mutations was the factor most strongly associated with metastasis (relative risk, 10.6; 95% CI, 3.4-33.5) and melanoma-specific mortality (relative risk, 9.0; 95% CI, 2.8-29.2) (P < .001 for both).Conclusions and relevanceBAP1, SF3B1, and EIF1AX mutations occur during UM tumor progression in an almost mutually exclusive manner and are associated with different levels of metastatic risk. These mutations may have value as prognostic markers in UM.

Dataset Information

A landscape of driver mutations in melanoma.

Publications

A landscape of driver mutations in melanoma.

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