A three-gene expression score for predicting clinical benefit to anti-PD-1 blockade in advanced renal cell carcinoma

Background: In the advanced renal cell carcinoma (RCC) scenario there are no consistent biomarkers to predict the clinical benefit patients derived from immune checkpoint blockade. We conducted a retrospective study in order to develop and to validate a gene expression score for predicting clinical benefit to nivolumab in the advanced clear cell RCC setting and to characterize its underlying clinical, molecular, and immune features. Methods: This is a post hoc pooled analysis of 311 patients with available clinical, molecular, and immune tumor data from the CheckMate-009, -010 and -025 trials. Efficacy endpoints were overall survival (OS), disease control rate, and overall response rate. Survival estimates were calculated by the Kaplan-Meier method, and groups were compared with the log-rank test. The Cox proportional hazards regression model was used to evaluate factors independently associated with OS. Factors associated with disease control and response were tested with logistic regression. Biomarker-treatment interaction was evaluated with the likelihood ratio test (LRT). Results: First, a three-gene expression score (3GES) with prognostic value for OS integrating HMGA1, NUP62, and ARHGAP42 transcripts was developed in a cohort of patients treated with nivolumab. Favorable 3GES risk category was significantly associated with a better OS in univariable (HR = 0.32, 95% CI 0.21 - 0.48, P<0.001) and multivariable (HR = 0.36, 95% CI 0.24 - 0.56, P<0.001) analyses. Consistent and significant correlation was found with disease control (P=0.066) and response (P=0.002). The 3GES prognostic value was validated in the TCGA-KIRC cohort (HR=0.35, P<0.001). Next, the predictive value for nivolumab was confirmed in a set of patients from the CheckMate-025 trial (LRT P<0.001). Conclusions: In accRCC, 3GES is not only an independent prognostic factor for OS but also a positive predictive biomarker for nivolumab. The predictive value deserves further validation in other retrospective and large-scale, randomized prospective studies.