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

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  • Uzunangelov, Vladislav
    • Other Affiliation: Department of Biomolecular Engineering, Center for Biomolecular Sciences and Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
  • Yau, Christina
    • Other Affiliation: Buck Institute for Research on Aging, Novato, CA 94945, USA
  • Collisson, Eric A.
    • Other Affiliation: Department of Medicine, University of California San Francisco, 450 35d St, San Francisco, CA, 94148, USA
  • Niu, Beifang
    • Other Affiliation: The Genome Institute, Washington University, St Louis, MO 63108, USA
  • Shen, Hui
    • Other Affiliation: USC Epigenome Center, University of Southern California Keck School of Medicine, 1450 Biggy Street, Los Angeles, CA 90033, USA
  • Tomborero, David
    • Other Affiliation: Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona 08003, Spain
  • Zhang, Jiashan
    • Other Affiliation: National Cancer Institute, NIH, Bethesda, MD 20892, USA
  • Robertson, A. Gordon
    • Other Affiliation: Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada
  • The Cancer Genome Atlas Research Network
  • Chen, Zhong
    • Other Affiliation: Head and Neck Surgery Branch, NIDCD/NIH, 10 Center Drive, Room 5D55, Bethesda, MD 20892
  • Mills, Gordon B.
    • Other Affiliation: UT MD Anderson Cancer Center, Bioinformatics and Computational Biology, 1400 Pressler Street, Unit 1410, Houston, TX 77030, USA
  • Ding, Li
    • Other Affiliation: The Genome Institute, Washington University, St Louis, MO 63108, USA
  • Ng, Sam
    • Other Affiliation: Department of Biomolecular Engineering, Center for Biomolecular Sciences and Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
  • Benz, Christopher C.
    • Other Affiliation: Buck Institute for Research on Aging, Novato, CA 94945, USA
  • Van't Veer, Laura J.
    • Other Affiliation: Department of Laboratory Medicine, University of California San Francisco, 2340 Sutter St, San Francisco, CA, 94115, USA
  • Weinstein, John W.
    • Other Affiliation: UT MD Anderson Cancer Center, Bioinformatics and Computational Biology, 1400 Pressler Street, Unit 1410, Houston, TX 77030, USA
  • Leiserson, Max D.M.
    • Other Affiliation: Department of Computer Science and Center for Computational Molecular Biology, Brown University, 115 Waterman St, Providence RI 02912, USA
  • Lopez-Bigas, Nuria
    • Other Affiliation: Research Unit on Biomedical Informatics, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, Barcelona 08003, Spain
  • Van Waes, Carter
    • Other Affiliation: Building 10, Room 4-2732, NIDCD/NIH, 10 Center Drive, Bethesda, MD 20892
  • Akbani, Rehan
    • Other Affiliation: UT MD Anderson Cancer Center, Bioinformatics and Computational Biology, 1400 Pressler Street, Unit 1410, Houston, TX 77030, USA
  • Kandoth, Cyriac
    • Other Affiliation: The Genome Institute, Washington University, St Louis, MO 63108, USA
  • Perou, Charles
    • ORCID: https://orcid.org/0000-0001-9827-2247
    • Affiliation: School of Medicine, Department of Genetics, School of Dentistry, Oral Pathology Section, Oral and Maxillofacial Pathology Graduate Program, N.C. Cancer Hospital, UNC Lineberger Comprehensive Cancer Center
  • Chu, Andy
    • Other Affiliation: Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada
  • Cherniack, Andrew D.
    • Other Affiliation: The Eli and Edythe Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
  • Hoadley, Katherine
    • Affiliation: N.C. Cancer Hospital, UNC Lineberger Comprehensive Cancer Center, School of Medicine
  • Raphael, Benjamin J.
    • Other Affiliation: Department of Computer Science and Center for Computational Molecular Biology, Brown University, 115 Waterman St, Providence RI 02912, USA
  • Margolin, Adam A.
    • Other Affiliation: Sage Bionetworks 1100 Fairview Avenue North, M1-C108, Seattle, WA 98109-1024, USA
  • McLellan, Michael
    • Other Affiliation: The Genome Institute, Washington University, St Louis, MO 63108, USA
  • Laird, Peter W.
    • Other Affiliation: USC Epigenome Center, University of Southern California Keck School of Medicine, 1450 Biggy Street, Los Angeles, CA 90033, USA
  • Omberg, Larsson
    • Other Affiliation: Sage Bionetworks 1100 Fairview Avenue North, M1-C108, Seattle, WA 98109-1024, USA
  • Stuart, Joshua M.
    • Other Affiliation: Department of Biomolecular Engineering, Center for Biomolecular Sciences and Engineering, University of California, Santa Cruz, 1156 High St., Santa Cruz, CA 95064, USA
  • Wolf, Denise M.
    • Other Affiliation: Department of Laboratory Medicine, University of California San Francisco, 2340 Sutter St, San Francisco, CA, 94115, USA
  • Byers, Lauren A.
    • Other Affiliation: UT MD Anderson Cancer Center, Bioinformatics and Computational Biology, 1400 Pressler Street, Unit 1410, Houston, TX 77030, USA
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
Date of publication
Identifier
  • doi:10.1016/j.cell.2014.06.049
  • 2-s2.0-84908460595
Related resource URL
Resource type
  • Article
Rights statement
  • In Copyright
Journal title
  • Cell
Journal volume
  • 158
Journal issue
  • 4
Page start
  • 929
Page end
  • 944
Language
  • English
Version
  • Postprint
ISSN
  • 0092-8674
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