Beyond PD-L1: novel predictive biomarkers for adjuvant immunotherapy in renal cell and urothelial carcinoma

Immuno-Oncology Insights 2022; 3(3), 135–153

DOI: 10.18609/ioi.2022.016

Published: 27 March 2022
Commentary
J Brown, A Rajkumar, J Garcia

Within the past year, immune checkpoint inhibitors have been approved by the Food and Drug Administration for adjuvant treatment of both renal cell carcinoma and urothelial carcinoma following definitive surgery. The landmark clinical trials on which these approvals were based stratified patients by PD-L1 status. Unfortunately, this biomarker inadequately distinguished the patients who would receive benefit, given PD-L1 negative responders. Combining additional novel biomarkers with PD-L1 could potentially enhance its predictive power. Such potential biomarkers that have been studied include tumor mutation burden, neoantigens, immune microenvironment components, microbes inhabiting the gastrointestinal and urinary system, metabolic byproducts, gene expression signatures, and non-invasively detected circulating tumor DNA. Machine learning can synthesize these biomarkers with histopathologic, radiographic, and clinical data to optimize prediction of response to immunotherapy. This commentary reviews recent scientific advances in developing predictive biomarkers and suggests potential applications to adjuvant immunotherapy in renal cell and urothelial cancer.