Mutational landscape and significance across 12 major cancer types

Cyriac Kandoth, Michael D. McLellan, Fabio Vandin, Kai Ye, Beifang Niu, Charles Lu, Mingchao Xie, Qunyuan Zhang, Joshua F. McMichael, Matthew A. Wyczalkowski, Mark D. M. Leiserson, Christopher A. Miller, John S. Welch, Matthew J. Walter, Michael C. Wendl, Timothy J. Ley, Richard K. Wilson, Benjamin J. Raphael and Li Ding ()
Additional contact information
Cyriac Kandoth: The Genome Institute, Washington University in St Louis
Michael D. McLellan: The Genome Institute, Washington University in St Louis
Fabio Vandin: Brown University
Kai Ye: The Genome Institute, Washington University in St Louis
Beifang Niu: The Genome Institute, Washington University in St Louis
Charles Lu: The Genome Institute, Washington University in St Louis
Mingchao Xie: The Genome Institute, Washington University in St Louis
Qunyuan Zhang: The Genome Institute, Washington University in St Louis
Joshua F. McMichael: The Genome Institute, Washington University in St Louis
Matthew A. Wyczalkowski: The Genome Institute, Washington University in St Louis
Mark D. M. Leiserson: Brown University
Christopher A. Miller: The Genome Institute, Washington University in St Louis
John S. Welch: Washington University in St Louis
Matthew J. Walter: Washington University in St Louis
Michael C. Wendl: The Genome Institute, Washington University in St Louis
Timothy J. Ley: The Genome Institute, Washington University in St Louis
Richard K. Wilson: The Genome Institute, Washington University in St Louis
Benjamin J. Raphael: Brown University
Li Ding: The Genome Institute, Washington University in St Louis

Nature, 2013, vol. 502, issue 7471, 333-339

Abstract: Abstract The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known (for example, mitogen-activated protein kinase, phosphatidylinositol-3-OH kinase, Wnt/β-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the number of driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment.

Date: 2013
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DOI: 10.1038/nature12634

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