Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

The Cancer Genome Atlas Research Network

Research output: Contribution to journalArticlepeer-review

1046 Scopus citations


Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-oforigin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pancancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies.

Original languageAmerican English
Pages (from-to)929-944
Number of pages16
Issue number4
StatePublished - 14 Aug 2014

Bibliographical note

Funding Information:
We thank the thousands of patients and their loved ones who contributed materially, emotionally, and intellectually to this study. We thank D.A. Wheeler and M.L. Meyerson for scientific review of the work and M.P. Schroeder for help setting up Gitools. We thank K.R. Shaw, B.A. Ozenberger, H.J. Sofia, C.M. Hutter, and J.C. Zenklusen for administrative support. This work was supported by grants from the Chapman Foundation and Dell Foundation to J.N.W., a MD Anderson Physician Scientist Award to L.A.B., a Burroughs Welcome Career Award at the Scientific Interface to B.J.R., and support from the following grants from the United States National Institutes of Health: K08 CA137153, K08 CA176561, P50 CA083639, R01 CA071468, R01 HG005690, R01 HG007069, R01CA180006, R21 CA155679, U01 CA168394, U24 CA143858, U24 CA143867-05, U24 CA143883, U24 CA143848, U24 CA143858, U24 CA143866, U54 CA112970, U24 CA143799, U24 CA143835, U24 CA143840, U24 CA143843, U24 CA143845, U24 CA143848, U24 CA143858, U24 CA143866, U24 CA143867, U24 CA143882, U24 CA143883, U24 CA144025, U54 HG003273, U54 HG003067, U54 HG003079, ZIA-DC-000073, ZIA-DC-000074, and P30 CA016672 for the MD Anderson CCSG Functional Proteomics Core.

Publisher Copyright:
© 2014 Elsevier Inc.


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