Serial proteomic characterization of plasma extracellular vesicles (EV) to identify changes that predict outcomes in metastatic castrate-resistant prostate cancer (mCRPC) patients receiving 177 Lu-PSMA-617.

258 Background: Extracellular vesicles (EVs) in plasma offer a minimally invasive window into tumor biology. We hypothesized that deep proteomic profiling of plasma EVs can characterize dynamic molecular changes and predict outcomes in patients with mCRPC treated with 177 Lu-PSMA-617. Methods: Of 100 prospectively enrolled patients receiving 177 Lu-PSMA-617 (Arafa, et al. ASCO 2025), 58 men had serial (baseline and on-treatment) plasma samples. EVs were isolated using differential ultracentrifugation and analyzed by shotgun mass spectrometry. Protein expression patterns (e.g. PSMA, B7-H3) were categorized as undetected at both baseline and follow-up (U->U) or detectable at both timepoints (D->D). Relative protein expression changes were dichotomized as increasing (>10% increase) versus no change/decreasing (not a >10% increase). Surface protein changes were quantified and associations with overall survival (OS) were sought using log-rank tests. Pathway-level analysis was conducted using pre-ranked gene set enrichment analysis (GSEA) to identify pathways associated with outcomes. Results: A total of 6,306 proteins were identified, with about 20% mapping to key cell-surface markers including PSMA, B7-H3, Trop-2, and STEAP1. When patients were stratified by the detection of the key 4 surface proteins (0–1, 2, or 3–4); increasing numbers of detected proteins were associated with progressively shorter OS using both baseline and follow-up samples (pD) or non-detection (U->U) patterns are shown in the Table. Increases in EV-derived PSMA (HR 2.7, 95% CI 1.3–5.9, p=0.002), Trop-2 (HR 4.8, 95% CI 1.5–15.7, pU (days) D->D (days) OS HR (difference) P PSMA 297 141 4.52 0.002 B7-H3 NR 175 7.3 p<0.0001 Trop-2 247 79 5.27 p<0.0001 STEAP1 268 79 10.76 p<0.0001