Serum Levels of Soluble Urokinase Plasminogen Activator Receptor Predict Tumor Response and Outcome to Immune Checkpoint Inhibitor Therapy

Background: Immune checkpoint inhibitors (ICIs) have led to a paradigm shift in cancer therapy, improving outcomes in the treatment of various malignancies. However, not all patients benefit to the same extend from ICI. Reliable tools to predict treatment response and outcome are missing. Soluble urokinase plasminogen activator receptor (suPAR) is a marker of immune activation, whose levels are prognostic in various cancers. We evaluated circulating suPAR levels as a novel predictive and prognostic biomarker in patients receiving ICI therapy for solid tumors.

Methods: A total of n = 87 patients receiving ICI therapy for different solid malignancies as well as 32 healthy controls were included into this study. Serum levels of suPAR were measured by ELISA prior to and sequentially at two time points during ICI therapy.

Results: Baseline suPAR serum levels were significantly higher in solid tumor patients compared to healthy controls. Importantly, patients with low suPAR levels both before or during ICI treatment were more likely to have a favorable response to treatment at three and six months, respectively. This finding was confirmed by multivariate binary logistic regression analysis including several clinicopathological parameters. Moreover, circulating suPAR levels before and during therapy were an independent prognostic factor for overall survival (OS). As such, patients with initial suPAR levels above our ideal prognostic cut-off value (4.86 ng/ml) had a median OS of only 160 days compared to 705 days for patients with suPAR levels below this cut-off value. Finally, low baseline suPAR levels identified a subgroup of patients who experienced ICI-related side effects which in turn were associated with favorable treatment response and outcome.

Conclusion: Our data suggest that measurements of suPAR serum levels are a previously unknown, easily accessible tool to predict individual treatment response and outcome to ICI therapy. Circulating suPAR might therefore be implemented into stratification algorithms to identify the ideal candidates for ICI treatment.