Combinatorial biomarkers to predict responses to immune checkpoint therapy in metastatic urothelial cancer.

488 Background: Immune checkpoint therapy can produce durable anti-tumor responses in metastatic urothelial carcinoma (mUCC); however, the responses are not universal. Despite multiple approvals of immune checkpoint therapy in mUCC, we lack predictive biomarkers to guide patient selection. Therefore, there is a critical need to develop clinically useful biomarkers to refine patient selection. The single biomarker studies either focused on tumor mutations or immune response biomarkers, which may limit predictive power due to lack of integration between cancer cell biology and immune cell responses. The identification of biomarkers may require interrogation of both the tumor mutational status and the immune microenvironment. Methods: We performed retrospective multi-platform immuno-genomic analyses of pre-treatment tumor tissues in a discovery cohort (n = 31). Next, we tested the clinical relevance of ARID1A mutation and pre-treatment CXCL13 expression in two independent confirmatory cohorts (CheckMate275 and IMvigor210). Additionally, we performed reverse translational studies using murine model of bladder cancer to demonstrate direct association of the biomarkers in anti-PD-(L)-1 mediated anti-tumor immunity. Results: We identified genomic mutation of AT-rich interactive domain-containing protein 1A ( ARID1A) in tumor cells and expression of immune cytokine CXCL13 in the pre-treatment tumor tissues as two predictors of clinical responses. We found that ARID1A mutation and expression of CXCL13 in the baseline tumor tissues correlated with improved overall survival (OS) in both confirmatory cohorts (CheckMate275, CXCL13 data, n = 217; ARID1A data, n = 139, and IMvigor210, CXCL13 data, n = 348; ARID1A data, n = 275). Further, reverse translational studies revealed that CXCL13 −/− tumor-bearing mice were resistant to immune checkpoint therapy whereas ARID1A knockdown enhanced sensitivity to immune checkpoint therapy in a murine model of bladder cancer. We then interrogated CXCL13 expression plus ARID1A mutation as a combination biomarker in predicting response to immune checkpoint therapy in CheckMate275 and IMvigor210. Combination of the 2 biomarkers in baseline tumor tissues showed improved OS compared to either single biomarker. Conclusions: Cumulatively, this study revealed that the combination of CXCL13 plus ARID1A mutation may improve patient selection in mUCC for immune checkpoint therapy.