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. Clin Cancer Res; 18(12); 3377–86. ©2012 AACR.

The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.

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 Ta and T1 tumors, respectively. In addition, we define gene signatures validated in two independent data sets that classify urothelial carcinoma into low-grade (G1/G2) and high-grade (G3) 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. Cancer Res; 70(9); 3463–72. ©2010 AACR.

Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

Global gene expression analysis has been a major tool for urothelial carcinoma subtype discovery. This approach has revealed extensive complexity both in intrinsic features of the tumor cells and in the microenvironment. However, global gene expression cannot distinguish between gene expression signals originating from the tumor cells proper and from normal cells in the biopsy. Here, we use a large cohort of advanced urothelial carcinomas for which both gene expression data and extensive immunohistochemistry are available to create a supervised mRNA expression centroid classifier. This classifier identifies the major Lund taxonomy tumor cell phenotypes as defined by IHC. We apply this classifier to the independent TCGA dataset and show excellent associations between identified subtypes and genomic features. We validate a progressed version of Urothelial-like A (UroA-Prog) that shows FGFR3 mutations and CDKN2A deletions, and we show that the variant Urothelial-like C is almost devoid of FGFR3 mutations. We show that Genomically Unstable tumors are very distinct from Urothelial-like tumors at the genomic level, and that tumors classified as Basal/SCC-like all complied with the established definition for Basal/SCC-like tumors. We identify the Mesenchymal-like and Small-cell/Neuroendocrine-like subtypes, and demonstrate that patients with UroB and Sc/NE-like tumors show the worst overall survival.

We recently defined molecular subtypes of urothelial carcinomas according to whole genome gene expression. Herein we describe molecular pathologic characterization of the subtypes using 20 genes and IHC of 237 tumors. In addition to differences in expression levels, the subtypes show important differences in stratification of protein expression. The selected genes included biological features central to bladder cancer biology, eg, cell cycle activity, cellular architecture, cell-cell interactions, and key receptor tyrosine kinases. We show that the urobasal (Uro) A subtype shares features with normal urothelium such as keratin 5 (KRT5), P-cadherin (P-Cad), and epidermal growth factor receptor (EGFR) expression confined to basal cells, and cell cycle activity (CCNB1) restricted to the tumor-stroma interface. In contrast, the squamous cell cancer-like (SCCL) subtype uniformly expresses KRT5, P-Cad, EGFR, KRT14, and cell cycle genes throughout the tumor parenchyma. The genomically unstable subtype shows proliferation throughout the tumor parenchyma and high ERBB2 and E-Cad expression but absence of KRT5, P-Cad, and EGFR expression. UroB tumors demonstrate features shared by both UroA and SCCL subtypes. A major transition in tumor progression seems to be loss of dependency of stromal interaction for proliferation. We present a simple IHC/histology-based classifier that is easy to implement as a standard pathologic evaluation to differentiate the three major subtypes: urobasal, genomically unstable, and SCCL. These three major subtypes exhibit important prognostic differences.