TY - JOUR
T1 - Mutational landscape and significance across 12 major cancer types
AU - Kandoth, Cyriac
AU - McLellan, Michael D.
AU - Vandin, Fabio
AU - Ye, Kai
AU - Niu, Beifang
AU - Lu, Charles
AU - Xie, Mingchao
AU - Zhang, Qunyuan
AU - McMichael, Joshua F.
AU - Wyczalkowski, Matthew A.
AU - Leiserson, Mark D.M.
AU - Miller, Christopher A.
AU - Welch, John S.
AU - Walter, Matthew J.
AU - Wendl, Michael C.
AU - Ley, Timothy J.
AU - Wilson, Richard K.
AU - Raphael, Benjamin J.
AU - Ding, Li
N1 - Funding Information:
Acknowledgements This work was supported by the National Cancer Institute grants R01CA180006 to L.D. and PO1CA101937 to T.J.L., and National Human Genome Research Institute grants R01HG005690 to B.J.R., U54HG003079 to R.K.W., and U01HG006517 to L.D., and National Science Foundation grant IIS-1016648 to B.J.R. We gratefully acknowledge the contributions from TCGA Research Network and its TCGA Pan-Cancer Analysis Working Group. We also thank M. Bharadwaj for technical assistance.
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
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U2 - 10.1038/nature12634
DO - 10.1038/nature12634
M3 - Article
C2 - 24132290
AN - SCOPUS:84885735554
SN - 0028-0836
VL - 502
SP - 333
EP - 339
JO - Nature
JF - Nature
IS - 7471
ER -