Abstract
Checkpoint inhibitors (CPI) have significantly changed the therapeutic landscape of oncology. We adopted a non-invasive metabolomic approach to understand immunotherapy response and failure in 28 urological cancer patients. In total, 134 metabolites were quantified in patient sera before the first, second, and third CPI doses. Modeling the association between metabolites and CPI response and patient characteristics revealed that one predictive metabolite class (n = 9/10) were very long-chain fatty acid-containing lipids (VLCFA-containing lipids). The best predictive performance was achieved through a multivariate model, including age and a centroid of VLCFA-containing lipids prior to first immunotherapy (sensitivity: 0.850, specificity: 0.825, ROC: 0.935). We hypothesize that the association of VLCFA-containing lipids with CPI response is based on enhanced peroxisome signaling in T cells, which results in a switch to fatty acid catabolism. Beyond use as a novel predictive non-invasive biomarker, we envision that nutritional supplementation with VLCFA-containing lipids might serve as an immuno sensitizer.