Predicting the pathologic complete response after neoadjuvant pembrolizumab in muscle-invasive bladder cancer
Menée à partir de données clinicopathologiques portant sur 112 patients atteints d'un cancer invasif de la vessie, cette étude évalue la possibilité de prédire, à l'aide de biomarqueurs tumoraux et cliniques (charge mutationnelle de la tumeur et score basé sur le profil génomique de la tumeur et l'expression de PD-L1, stade de la tumeur), la réponse pathologique complète (pT0N0) après un traitement par pembrolizumab
Background : In the PURE-01 study (NCT02736266), we aimed to evaluate the ability to predict the pathologic complete response (pT0N0) after pembrolizumab by using clinical and tumor biomarkers.
Methods : In an open-label, single-arm, phase 2 study, 3 courses of 200 mg pembrolizumab preceding radical cystectomy (RC) were administered in patients with T2-4aN0M0 muscle-invasive bladder cancer (MIBC). The analyses included a comprehensive genomic profiling and programmed cell-death-ligand-1 (PD-L1) combined positive score assessment (CPS, Dako 22C3 antibody) of pre- and post-therapy samples. Multivariable logistic regression analyses (MVA) evaluated baseline clinical T-stage and tumor biomarkers in association with pT0N0 response. Corresponding coefficients were used to develop a calculator of pT0N0 response based on the tumor mutational burden (TMB), CPS and the clinical T-stage. Decision-curve analysis was also performed. All statistical tests were two-sided.
Results : From February 2017 to June 2019, 112 patients with biomarker data were enrolled (105 with complete TMB and CPS data). Increasing TMB and CPS values featured a linear association with logistic pT0N0 probabilities (p = 0.02 and p = 0.004, respectively). For low TMB values (≤11 Mut/Mb, median value, N = 53), pT0N0 probability was not associated with increasing CPS. Conversely, for high TMB values (>11 Mut/Mb, N = 52), pT0N0 was statistically significantly associated with higher CPS (p = 0.004). The c-index of the pT0N0 probability calculator was 0.77. On decision-curve analysis, the net-benefit of the model was higher than the “treat-all” option within the clinically-meaningful threshold probabilities of 40-50%.
Conclusion : The study presents a composite biomarker-based pT0N0 probability calculator that reveals the complex interplay between TMB and CPS, added to the clinical T-stage.
Journal of the National Cancer Institute , résumé, 2019