Research ArticleCancer

ARID1A mutation plus CXCL13 expression act as combinatorial biomarkers to predict responses to immune checkpoint therapy in mUCC

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Science Translational Medicine  17 Jun 2020:
Vol. 12, Issue 548, eabc4220
DOI: 10.1126/scitranslmed.abc4220

Two markers can be better than one

Therapies targeting immune checkpoints in cancer are achieving increasing prominence because they can achieve long-lasting responses in patients with difficult-to-treat tumors. Unfortunately, not all tumors respond to these treatments, and it is not clear how to identify patients most likely to benefit. Previous studies have suggested individual biomarkers, such as expression of the immune checkpoints themselves, but this was not sufficient. To address this problem, Goswami et al. investigated potential biomarker combinations and identified a genetic change and an immune marker, which together helped predict response to immune checkpoint therapy in multiple cohorts of patients with metastatic urothelial carcinoma.


Immune checkpoint therapy (ICT) can produce durable antitumor responses in metastatic urothelial carcinoma (mUCC); however, the responses are not universal. Despite multiple approvals of ICT in mUCC, we lack predictive biomarkers to guide patient selection. The identification of biomarkers may require interrogation of both the tumor mutational status and the immune microenvironment. Through multi-platform immuno-genomic analyses of baseline tumor tissues, we identified the mutation of AT-rich interactive domain-containing protein 1A (ARID1A) in tumor cells and expression of immune cytokine CXCL13 in the baseline tumor tissues as two predictors of clinical responses in a discovery cohort (n = 31). Further, reverse translational studies revealed that CXCL13−/− tumor-bearing mice were resistant to ICT, whereas ARID1A knockdown enhanced sensitivity to ICT in a murine model of bladder cancer. Next, we tested the clinical relevance of ARID1A mutation and baseline CXCL13 expression in two independent confirmatory cohorts (CheckMate275 and IMvigor210). 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). We then interrogated CXCL13 expression plus ARID1A mutation as a combination biomarker in predicting response to ICT in CheckMate275 and IMvigor210. Combination of the two biomarkers in baseline tumor tissues suggested improved OS compared to either single biomarker. Cumulatively, this study revealed that the combination of CXCL13 plus ARID1A may improve prediction capability for patients receiving ICT.

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