Comprehensive Genomic Characterization of Upper Tract Urothelial Carcinoma.

Abstract

Upper urinary tract urothelial cancer (UTUC) may have unique etiologic and genomic factors compared to bladder cancer. To characterize the genomic landscape of UTUC and provide insights into its biology using comprehensive integrated genomic analyses. We collected 31 untreated snap-frozen UTUC samples from two institutions and carried out whole-exome sequencing (WES) of DNA, RNA sequencing (RNAseq), and protein analysis. Adjusting for batch effects, consensus mutation calls from independent pipelines identified DNA mutations, gene expression clusters using unsupervised consensus hierarchical clustering (UCHC), and protein expression levels that were correlated with relevant clinical variables, The Cancer Genome Atlas, and other published data. WES identified mutations in FGFR3 (74.1%; 92% low-grade, 60% high-grade), KMT2D (44.4%), PIK3CA (25.9%), and TP53 (22.2%). APOBEC and CpG were the most common mutational signatures. UCHC of RNAseq data segregated samples into four molecular subtypes with the following characteristics. Cluster 1: no PIK3CA mutations, nonsmokers, high-grade <pT2 tumors, high recurrences. Cluster 2: 100% FGFR3 mutations, low-grade tumors, tobacco use, noninvasive disease, no bladder recurrences. Cluster 3: 100% FGFR3 mutations, 71% PIK3CA, no TP53 mutations, five bladder recurrences, tobacco use, tumors all <pT2. Cluster 4: KMT2D (62.5%), FGFR3 (50%), TP53 (50%) mutations, no PIK3CA mutations, high-grade pT2+ disease, tobacco use, carcinoma in situ, shorter survival. We identified a novel SH3KBP1-CNTNAP5 fusion. Mutations in UTUC occur at differing frequencies from bladder cancer, with four unique molecular and clinical subtypes. A novel SH3KBP1 fusion regulates RTK signaling. Further studies are needed to validate the described subtypes, explore their responses to therapy, and better define the novel fusion mutation. We conducted a comprehensive study of the genetics of upper urinary tract urothelial cancer by evaluating DNA, RNA and protein expression in 31 tumors. We identified four molecular subtypes with distinct behaviors. Future studies will determine if these subtypes appear to have different responses to treatments.