Plasma extracellular vesicles as biomarkers of primary versus acquired resistance to immune checkpoint inhibitors (ICI) in patients (pts) with solid tumors.

Abstract

2551 Background: Plasma extracellular vesicles (pEVs) have emerged as promising biomarkers in the field of oncology. They can be obtained through minimally invasive methods, and hold the potential to help differentiate the clinically relevant subgroups of primary (PR) vs acquired resistance (AR) to ICI treatments. We hypothesized that individual pEV-derived protein cargo, or combinations thereof, associate with PR vs AR to ICI. Methods: A cohort of patients was derived from the Immune Resistance Interrogation Study (IRIS; NCT04243720), with plasma collected at the time of progression on ICI in advanced or adjuvant settings (n = 69; n = 44 primary resistance [PR], n = 25 acquired resistance [AR]). Plasma-derived extracellular vesicles (pEVs) were isolated using serial ultracentrifugation and characterized per ISEV guidelines. All samples were analyzed using OLink Immuno-Oncology proteomics to evaluate 92 proteins. Statistical analyses included the Mann–Whitney U test, binary logistic regression, and log-rank tests. Primary and acquired resistance were defined according to trial protocol. Results: A total of 57 out of 69 samples (n = 37 PR, n = 20 AR) generated evaluable proteomics data. Of the 92 proteins analyzed, 11 were significantly overexpressed in AR compared to PR (ADGRG1, CD28, FGF2, IL10, IL12RB1, IL2, IL33, IL4, MCP3, PD-L2, PTN) (p < 0.05), with IL10 and IL33 showing the strongest associations (p< 0.01). When stratified by cancer type, 9/11 proteins were overexpressed in AR vs PR among melanoma pts (n = 39; ADGRG1, CD28, FGF2, IL10, IL33, IL4, MCP3, PD-L2, PTN) (p < 0.05), whereas only IL12RB1 (p < 0.01) was overexpressed in HNSCC pts (n = 16). Analysis of 5 proteins most strongly associated with AR (IL10, IL33, IL4, MCP3, CD28) yielded a sensitivity of 70% and specificity of 95% for AR vs PR, with a positive and negative predictive value of 88% and 85%, respectively; AUC 0.853 (p < 0.001; 95% CI 0.742-0.963). Conclusions: In summary, 11 pEV-derived proteins from blood samples at progression on ICI independently statistically associated with AR vs PR, and a combination of 5 of them generated a highly accurate predictive model for AR. Immuno-modulatory cytokines IL10 and IL33 held the strongest associations, known to activate signaling cascades implicated in ICI resistance through the JAK-STAT and NF-Kappa-B/MAPK pathways, respectively. Differentially expressed proteins may signify distinct mechanisms of ICI escape. Despite requiring validation, our results highlight the potential of pEV-derived proteins as predictive biomarkers for ICI resistance in solid tumors. Future studies of pEV proteomics in the pre-treatment setting, as well as exploring other cargo such as RNA, may provide additional insights into the biology of resistance, and discover minimally invasive clinically relevant biomarkers. Clinical trial information: NCT04243720 .