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

Citation:

Katherine A Hoadley, Christina Yau, Denise M Wolf, Andrew D Cherniack, David Tamborero, Sam Ng, Max DM 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 Laird, Benjamin J Raphael, Li Ding, Gordon A Robertson, Lauren A Byers, Gordon B Mills, John N Weinstein, Carter Van Waes, Zhong Chen, Eric A Collisson, TCGA Network, Christopher C Benz, Charles M Perou, and Joshua M Stuart. 2014. “Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.” Cell, 158, 4, Pp. 929-44.

Abstract:

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-of-origin 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 pan-cancer 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.
Last updated on 07/28/2017