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      A molecular taxonomy for urothelial carcinoma.

      Clinical cancer research : an official journal of the American Association for Cancer Research
      Carcinoma, Transitional Cell, classification, genetics, pathology, Cell Adhesion, Cell Cycle, Female, Gene Expression Profiling, Genetic Markers, Humans, Keratins, Male, Mutation Rate, Receptor Protein-Tyrosine Kinases, Tumor Markers, Biological, Urinary Bladder Neoplasms
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          Abstract

          Even though urothelial cancer is the fourth most common tumor type among males, progress in treatment has been scarce. A problem in day-to-day clinical practice is that precise assessment of individual tumors is still fairly uncertain; consequently efforts have been undertaken to complement tumor evaluation with molecular biomarkers. An extension of this approach would be to base tumor classification primarily on molecular features. Here, we present a molecular taxonomy for urothelial carcinoma based on integrated genomics. We use gene expression profiles from 308 tumor cases to define five major urothelial carcinoma subtypes: urobasal A, genomically unstable, urobasal B, squamous cell carcinoma like, and an infiltrated class of tumors. Tumor subtypes were validated in three independent publically available data sets. The expression of 11 key genes was validated at the protein level by immunohistochemistry. The subtypes show distinct clinical outcomes and differ with respect to expression of cell-cycle genes, receptor tyrosine kinases particularly FGFR3, ERBB2, and EGFR, cytokeratins, and cell adhesion genes, as well as with respect to FGFR3, PIK3CA, and TP53 mutation frequency. The molecular subtypes cut across pathologic classification, and class-defining gene signatures show coordinated expression irrespective of pathologic stage and grade, suggesting the molecular phenotypes as intrinsic properties of the tumors. Available data indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathologic classification. We anticipate that the molecular taxonomy will be useful in future clinical investigations. ©2012 AACR.

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