Published in

Elsevier, Cell, 4(158), p. 929-944, 2014

DOI: 10.1016/j.cell.2014.06.049

Links

Tools

Export citation

Search in Google Scholar

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Journal article published in 2014 by Jiashan Zhang, Jianhua Zhang, Nianxiang Zhang, Qunyuan Zhang, Wei Zhang, Wei Zhao, Siyuan Zheng, Jing Zhu, Erik Zmuda, Lihua Zou, Katherine A. Hoadley ORCID, Michael D. Mclellan, Laura J. Van 't Veer, A. Gordon Robertson, Carter and other authors.
This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Recent genomic analyses of pathologically defined tumor types identify ''within-a-tissue'' disease sub-types. However, the extent to which genomic sig-natures 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 inde-pendent information for predicting clinical outcomes. All data sets are available for data-mining from a uni-fied resource to support further biological discov-eries and insights into novel therapeutic strategies. INTRODUCTION