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

Katherine A. Hoadley, Christina Yau, Denise M. Wolf, Andrew D. Cherniack, David Tamborero, Sam Ng, Max D.M. Leiserson, Beifang Niu, Michael D. McLellan, Vladislav Uzunangelov, Jiashan Zhang, Cyriac Kandoth, Rehan Akbani, Hui Shen, Larsson Omberg, Andy Chu, Adam A. Margolin, Laura J. Van't Veer, Nuria Lopez-Bigas, Peter W. LairdBenjamin J. Raphael, Li Ding, A. Gordon Robertson, Lauren A. Byers, Gordon B. Mills, John N. Weinstein, Carter Van Waes, Zhong Chen, Eric A. Collisson, Christopher C. Benz*, Charles M. Perou, Joshua M. Stuart, Rachel Abbott, Scott Abbott, B. Arman Aksoy, Kenneth Aldape, Adrian Ally, Samirkumar Amin, Dimitris Anastassiou, J. Todd Auman, Keith A. Baggerly, Miruna Balasundaram, Saianand Balu, Stephen B. Baylin, Stephen C. Benz, Benjamin P. Berman, Brady Bernard, Ami S. Bhatt, Inanc Birol, Lihua Zou, The Cancer Genome Atlas Research Network

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

843 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 languageEnglish (US)
Pages (from-to)929-944
Number of pages16
Issue number4
StatePublished - Aug 14 2014

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)


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