Abstract

450 Background: EV, an antibody-drug conjugate (ADC) targeting Nectin-4, is used widely in treatment-refractory aUC, but limited data are available on biomarkers predictive of EV outcomes. We investigated potential biomarkers of response to EV in a pt cohort in the UNITE dataset. Methods: We included the retrospective UNITE study pts from 16 sites, with available next generation sequencing using institutional or commercial platforms, treated with EV alone outside clinical trials. Observed response (ORR) was determined by investigators for evaluable pts with scans after ≥1 dose of EV. Assessed molecular biomarkers included tumor mutation burden (TMB), PD-L1 status, somatic alterations (alts) in ≥ 10% of pts ( TERTp, TP53, ARID1A, CDKN2A, CDKN2B, FGFR3, ERBB2, CCND1, KDM6A, MTAP, PIK3CA, RB1, TSC1) and presence of ≥1 DNA damage response mutations ( ATM, BARD1, BRCA1, BRCA2, CDK12, CHEK2, PALB2, PPP2R2A, or RAD51B). ORRs were compared using Chi-squared test, while median progression-free and overall survival (mPFS, mOS) from EV start were compared with log-rank test and Cox proportional hazards in pts with and without biomarker presence. Results: A total of 170 pts had outcomes and NGS data available. Median age was 70, 133 (78%) were men, 144 (85%) Caucasian, 110 (65%) with pure urothelial histology, 118 (69%) with primary bladder tumor, and 116 (68%) had ≥ 2 lines of therapy before EV. For all pts, ORR 47%, mPFS 6 mos, mOS 12 mos. ORRs were higher in pts with ERBB2 (67% vs 44%; p = 0.05) and TSC1 (68% vs 25%; p=0.04) alts vs wild-type. Shorter mPFS was noted in pts with CDKN2A, CDKN2B, and MTAP alts, and longer mOS in pts with high TMB (table). Conclusions: This large, multi-site, retrospective cohort of pts with aUC identified several potential biomarkers associated with differential outcomes to EV. These findings, upon external validation, may help inform clinical decision making and potential therapy sequencing with available ADCs. Limitations include retrospective nature, pt selection, and confounding biases. [Table: see text]

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