Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

Autor:	Robertson AG; Canada's Michael Smith Genome Sciences Center, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada., Kim J; Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Al-Ahmadie H; Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA., Bellmunt J; PSMAR-IMIM Lab, Bladder Cancer Center, Department of Medicine, Dana-Farber Cancer Institute and Harvard University, Boston, MA 02215, USA., Guo G; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard University, Boston, MA 02115, USA., Cherniack AD; Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Hinoue T; Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI 49503, USA., Laird PW; Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI 49503, USA., Hoadley KA; Department of Genetics, Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA., Akbani R; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Castro MAA; Bioinformatics and Systems Biology Laboratory, Federal University of Paraná Polytechnic Center, Curitiba, PR CEP 80.060-000, Brazil., Gibb EA; Canada's Michael Smith Genome Sciences Center, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada., Kanchi RS; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Gordenin DA; Genome Integrity and Structural Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA., Shukla SA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard University, Boston, MA 02115, USA., Sanchez-Vega F; Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA., Hansel DE; Department of Pathology, School of Medicine, University of California, San Diego, La Jolla, CA 92093, USA., Czerniak BA; Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Reuter VE; Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA., Su X; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., de Sa Carvalho B; Biostatistics and Computational Biology Laboratory, Department of Statistics, University of Campinas, São Paulo, 13.083-859, Brazil., Chagas VS; Bioinformatics and Systems Biology Laboratory, Federal University of Paraná Polytechnic Center, Curitiba, PR CEP 80.060-000, Brazil., Mungall KL; Canada's Michael Smith Genome Sciences Center, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada., Sadeghi S; Canada's Michael Smith Genome Sciences Center, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada., Pedamallu CS; Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Lu Y; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Klimczak LJ; Integrative Bioinformatics Support Group, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709, USA., Zhang J; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Choo C; Canada's Michael Smith Genome Sciences Center, BC Cancer Agency, Vancouver, BC V5Z 4S6, Canada., Ojesina AI; Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA., Bullman S; Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Leraas KM; Biospecimen Core Resource, The Research Institute at Nationwide Children's Hospital, Columbus, OH 43205, USA., Lichtenberg TM; Biospecimen Core Resource, The Research Institute at Nationwide Children's Hospital, Columbus, OH 43205, USA., Wu CJ; Department of Medical Oncology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA., Schultz N; Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA., Getz G; Cancer Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Meyerson M; Pathology and Medical Oncology, Dana-Farber Cancer Institute and Harvard University, Boston, MA 02115, USA., Mills GB; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., McConkey DJ; Greenberg Bladder Cancer Institute, Johns Hopkins University, Baltimore, MD 21218, USA., Weinstein JN; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030 USA. Electronic address: jweinste@mdanderson.org., Kwiatkowski DJ; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. Electronic address: dk@rics.bwh.harvard.edu., Lerner SP; Scott Department of Urology, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA. Electronic address: slerner@bcm.edu.
Jazyk:	angličtina
Zdroj:	Cell [Cell] 2017 Oct 19; Vol. 171 (3), pp. 540-556.e25. Date of Electronic Publication: 2017 Oct 05.
DOI:	10.1016/j.cell.2017.09.007
Abstrakt:	We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments. (Copyright © 2017 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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