Abstract 2969: Progress in The Cancer Genome Atlas bladder cancer project

Comprehensive immune transcriptomic analysis in bladder cancer reveals subtype specific immune gene expression patterns of prognostic relevance

Recent efforts on genome wide profiling of muscle invasive bladder cancer (MIBC) have led to its classification into distinct genomic and transcriptomic molecular subtypes that exhibit variability in prognosis. Evolving evidence from recent immunotherapy trials has demonstrated the significance of pre-existing tumour immune profiles that could guide treatment decisions. To identify immune gene expression patterns associated with the molecular subtypes, we performed a comprehensive in silico immune transcriptomic profiling, utilizing transcriptomic data from 347 MIBC cases from The Cancer Genome Atlas (TCGA). To investigate subtype-associated immune gene expression patterns, we assembled 924 immune response genes and specifically those involved in T-cell cytotoxicity and the Type I/II interferon pathways. A set of 157 ranked genes was able to distinguish the four subtypes in an unsupervised analysis in an original training cohort (n=122) and an expanded, validation cohort (n=225). The most common overrepresented pathways distinguishing the four molecular subtypes, included JAK/STAT signaling, Toll-like receptor signaling, interleukin signaling, and T-cell activation. Some of the most enriched biological processes were responses to IFN-γ, antigen processing and presentation, cytokine mediated signaling, hemopoeisis, cell proliferation and cellular defense response in the TCGA cluster IV. Our novel findings provide further insights into the association between genomic subtypes and immune activation in MIBC and may open novel opportunities for their exploitation towards precise treatment with immunotherapy.

Relationship of smoking status to genomic profile, chemotherapy response and clinical outcome in patients with advanced urothelial carcinoma

Smoking has been linked to urothelial carcinoma (UC), but the implications on genomic profile and therapeutic response are poorly understood. To determine how smoking history impacts genomic profile and chemotherapy response, clinicopathologic data was collected for patients with metastatic UC (mUC) across 3 academic medical centers and comprehensive genomic profiling (CGP) was performed through a CLIA-certified lab. Unsupervised hierarchical clustering based on smoking status was used to categorize the frequency of genomic alterations (GAs) amongst current smokers (CS), ex-smokers (ES) and non-smokers (NS), and survival was compared in these subsets. Fisher's exact test identified significant associations between GAs and smoking status. Amongst 83 patients, 23%, 55% and 22% were CS, ES, and NS, respectively, and 95% of patients had stage IV disease. With a median follow up of 14.4 months, the median overall survival (OS) was significantly higher in NS and ES (combined) as compared to CS (51.6 vs 15.6 months; P = 0.04). Of 315 cancer-related genes and 31 genes often related to rearrangement tested, heatmaps show some variations amongst the subsets. GAs in NSD1 were more frequent in CS as compared to other groups (P < 0.001). CS status negatively impacts OS in patients with mUC and is associated with genomic alterations that could have therapeutic implications.