Genomic and Transcriptomic Characterization of Metastatic Urothelial Carcinoma

Abstract

Standard treatment for patients with metastatic urothelial carcinoma (mUC) consists of platinum-based chemotherapy, and recently systemic immunotherapy has become available. Nevertheless, the overall survival of mUC patients remains poor and new therapies are needed. To identify novel targets for therapy, large-scale sequencing efforts are mandatory. The Cancer Genome Atlas (TCGA) initiative substantially improved our knowledge on the genomic and transcriptomic characteristics of primary UC, however, our knowledge on mUC is still scarce. We performed whole genome DNA sequencing (WGS) on 116 biopsies of mUC, and mRNA sequencing (RNAseq) on 90 matched biopsies. We applied genomic alteration analysis on the WGS data and used consensus clustering on the RNAseq data. WGS analysis showed that TP53 mutations were enriched in mUC compared to primary UC. APOBEC mutagenesis was detected in 91% of the samples and correlated with APOBEC expression. Two major mutational processes covering 92% of the samples were identified in mUC and validated in TCGA data. Tumors with high APOBEC mutagenesis had high ploidy, more somatic mutations and more copy number aberrations. Furthermore, five molecular subtypes were identified by RNAseq analysis. Two subtypes (40%) resembled the luminal subtypes identified in primary UC, the other subtypes had a stroma rich (24%), basal/squamous (23%) or unspecific phenotype (12%). The subtypes were different in gene expression, genomic alterations, pathway activity and immune cell infiltration. These differences suggest that these subtypes are clinically relevant. The luminal subtypes showed high frequency of FGFR3 and PPARG alterations as well as high expression of these genes and may be the group benefitting most from FGFR and PPARG inhibitors. The basal/squamous subtype had high levels of CD274, the gene that encodes PD-L1 for which checkpoint inhibitors could be effective. The stroma rich subtype seems highly PDGFRA driven and therefore PDGFR inhibitors may be the way to improve treatment in this group. Using WGS and RNAseq analyses, we described a comprehensive overview of the molecular landscape of mUC that can serve as a framework for further research on personalizing systemic treatment for mUC patients.