The use of TF-Ag-α to selectively capture tumor-derived extracellular vesicles and enhance the predictive performance of extracellular vesicle PD-L1 for response to immune checkpoint inhibitors

Only a subset of non-small cell lung cancer (NSCLC) patients benefits from immune checkpoint inhibitors (ICIs). Tissue PD-L1 has limited accuracy in predicting ICI response and requires invasive biopsies, highlighting the urgent need for reliable, minimally invasive biomarkers. Extracellular vesicle PD-L1 (EV PD-L1) is a promising liquid biopsy marker, but its predictive performance is confounded by PD-L1 derived from non-tumor cells. We developed a tumor-specific EVs–based assay to predict ICI response. Tumor-derived extracellular vesicles (TEXs) were selectively captured using the tumor-specific Thomsen–Friedenreich glycoantigen alpha (TF-Ag-α), and PD-L1 levels in TEXs expressing TF-Ag-α (i.e., TEXTF-Ag-α PD-L1) were measured in sera from 91 NSCLC patients receiving anti-PD-1 therapy (40 responders and 51 non-responders). Predictive performance was evaluated at pre-treatment baseline, at the end of first treatment cycle, and via fold changes. At pre-treatment baseline, TEXTF-Ag-α PD-L1 showed moderate predictive ability (AUC: 0.76; sensitivity: 0.97; specificity: 0.56). By the end of the first treatment cycle, responders exhibited a ~4.18-fold increase in TEXTF-Ag-α PD-L1 expression, whereas non-responders showed an approximate 20% decrease. Dynamic fold changes after the first treatment cycle substantially improved predictive performance, achieving an AUC of 0.93, sensitivity of 0.95, and specificity of 0.80 for distinguishing responders from non-responders, outperforming both total EV PD-L1 and tissue PD-L1. These results demonstrated that selective TEX capture using TF-Ag-α significantly enhanced the predictive value of EV PD-L1. Dynamic changes in TEXTF-Ag-α PD-L1 provided a highly accurate, minimally invasive biomarker for early assessment of anti-PD-1 response, supporting tumor-specific EVs–based liquid biopsy for precision immunotherapy.