Journal
Cell, 2017
Authors
Robertson, A Gordon, Kim, Jaegil, Al-Ahmadie, Hikmat, Bellmunt, Joaquim, Guo, Guangwu, Cherniack, Andrew D, Hinoue, Toshinori, Laird, Peter W, Hoadley, Katherine A, Akbani, Rehan, Castro, Mauro A A, Gibb, Ewan A, Kanchi, Rupa S, Gordenin, Dmitry A, Shukla, Sachet A, Sanchez-Vega, Francisco, Hansel, Donna E, Czerniak, Bogdan A, Reuter, Victor E, Su, Xiaoping, de Sa Carvalho, Benilton, Chagas, Vinicius S, Mungall, Karen L, Sadeghi, Sara, Pedamallu, Chandra Sekhar, Lu, Yiling, Klimczak, Leszek J, Zhang, Jiexin, Choo, Caleb, Ojesina, Akinyemi I, Bullman, Susan, Leraas, Kristen M, Lichtenberg, Tara M, Wu, Catherine J, Schultz, Nicholaus, Getz, Gad, Meyerson, Matthew, Mills, Gordon B, McConkey, David J, , , Weinstein, John N, Kwiatkowski, David J, Lerner, Seth P
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.
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Title
Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.
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