Purpose: 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.Experimental Design: 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.Results: 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.Conclusions: We anticipate that the molecular taxonomy will be useful in future clinical investigations.

In the present investigation, we sought to refine the classification of urothelial carcinoma by combining information on gene expression, genomic, and gene mutation levels. For these purposes, we performed gene expression analysis of 144 carcinomas, and whole genome array-CGH analysis and mutation analyses of FGFR3, PIK3CA, KRAS, HRAS, NRAS, TP53, CDKN2A, and TSC1 in 103 of these cases. Hierarchical cluster analysis identified two intrinsic molecular subtypes, MS1 and MS2, which were validated and defined by the same set of genes in three independent bladder cancer data sets. The two subtypes differed with respect to gene expression and mutation profiles, as well as with the level of genomic instability. The data show that genomic instability was the most distinguishing genomic feature of MS2 tumors, and that this trait was not dependent on TP53/MDM2 alterations. By combining molecular and pathologic data, it was possible to distinguish two molecular subtypes of T a and T 1 tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low-grade (G 1 /G 2 ) and high-grade (G 3 ) tumors as well as non-muscle and muscle-invasive tumors with high precisions and sensitivities, suggesting molecular grading as a relevant complement to standard pathologic grading. We also present a gene expression signature with independent prognostic effect on metastasis and disease-specific survival. We conclude that the combination of molecular and histopathologic classification systems might provide a strong improvement for bladder cancer classification and produce new insights into the development of this tumor type.

We analyzed 34 cases of urothelial carcinomas by miRNA, mRNA and genomic profiling. Unsupervised hierarchical clustering using expression information for 300 miRNAs produced 3 major clusters of tumors corresponding to Ta, T1 and T2-T3 tumors, respectively. A subsequent SAM analysis identified 51 miRNAs that discriminated the 3 pathological subtypes. A score based on the expression levels of the 51 miRNAs, identified muscle invasive tumors with high precision and sensitivity. MiRNAs showing high expression in muscle invasive tumors included miR-222 and miR125b and in Ta tumors miR-10a. A miRNA signature for FGFR3 mutated cases was also identified with miR-7 as an important member. MiR-31, located in 9p21, was found to be homozygously deleted in 3 cases and miR-452 and miR-452* were shown to be over expressed in node positive tumors. In addition, these latter miRNAs were shown to be excellent prognostic markers for death by disease as outcome. The presented data shows that pathological subtypes of urothelial carcinoma show distinct miRNA gene expression signatures.