Abstract

4558 Background: Objective: To examine in a cohort of anti-PD-(L)1 immune checkpoint inhibitors (ICP) treated urothelial cancer patients a strategy combining treatment outcomes with molecular alterations, pathways, and immune/tumor microenvironment features to determine potential responder and rapid-progression signatures. Methods: De-identified clinical history and treatment outcomes were collected on 109 MIBC patients treated with ICP agents. Archived FFPE samples from these patients were obtained and processed for mRNAseq, exome-seq, tumor mutation burden (TMB), microsatellite instability (MSI) and mutation panel testing. Comprehensive tumor/immune profiling is being analyzed in the context of ICP treatments and RECIST 1.1 outcomes. A 60 gene MIBC 4-typer expression subtyper and other response associated predictors are used to stratify and identify positive/negative ICP response indicators. Results: 109 patients were identified (median age 75, 64% male, 78% white, 17% black). 74% of patients had received prior platinum-based chemotherapy, and 12% had received 2 or more prior lines of therapy. At initiation of ICP, 28% of patients had hemoglobin < 10, 30% had liver metastases, and 59% had ECOG performance status > 0. Mutation analysis of the first 66 patients showed TP53 (n = 34, 52%), FGFR (n = 17, 26%), CDKN2A (n = 13, 20%) and RB1 (n = 12, 18%) as the top alterations. No patients (0/8) with known pathogenic mutations in FGFR3 (S249C and TACC3-fusion) responded to ICP. Of patients with T2 staging prior to ICP (37/66), overall survival was markedly shorter (2.7 years) in those possessing FGFR3 mutations (n = 6/37) compared to that for FGFR3 WT patients (5.7 years, n = 31/37; p = 0.045). Further analyses of molecular features relative to treatment outcomes are ongoing to characterize response signatures. Conclusions: Our preliminary cohort of patients with pathogenic FGFR3 alterations showed 0% favorable response to ICP. We are expanding on this observation with further comprehensive molecular analyses and retrospective treatments/outcomes data. We anticipate identifying expression signatures that reflect ICP patient responder/non-responder signatures that may aid in future therapy decisions.

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