The Diagnostic Value of Plasma Small Extracellular Vesicle-Derived CAIX Protein in Prostate Cancer and Clinically Significant Prostate Cancer: A Study on Predictive Models.

BACKGROUND: Current diagnostic tools are inaccurate and not specific to prostate cancer (PCa) diagnosis. Cancer-derived small extracellular vehicles (sEVs) play a key role in intercellular communication. In this study, we examined the diagnostic value of plasma sEV-derived carbonic anhydrase IX (CAIX) protein for PCa and clinically significant prostate cancer (csPCa) diagnosis and avoiding unnecessary biopsies. METHODS: Plasma samples (n = 230) were collected from the patients who underwent prostate biopsy with elevated prostate-specific antigen (PSA) levels. sEVs were isolated and characterized, and sEV protein CAIX was measured using an enzyme-linked immunosorbent assay. Independent predictors of csPCa (Gleason score ≥ 7) were identified, and a predictive model was established. A Nomogram for predicting csPCa was developed using data from the training cohort. RESULTS: The expression of sEV protein CAIX was significantly higher in both PCa and csPCa compared to benign patients and nonsignificant PCa (nsPCa) (Gleason score < 7, p < 0.001). sEV protein CAIX performed well in distinguishing PCa from benign patients. The predictive model defined by sEV protein CAIX and PSA density (PSAD) demonstrated the highest discriminative ability for csPCa (AUC = 0.895), with diagnostic sensitivity and specificity of 82.5% and 85.8%, respectively. Furthermore, sEV protein CAIX is an effective predictor of 2-year biochemical recurrence (BCR) in PCa patients (p = 0.013), and its high expression is significantly associated with poorer BCR-free survival (p < 0.05). CONCLUSIONS: Our findings demonstrate the excellent performance of sEV protein CAIX in PCa and csPCa diagnosis. The Nomogram-based csPCa predictive model incorporating sEV protein CAIX and PSAD exhibits strong predictive value. Additionally, assessing plasma sEV protein CAIX expression levels can further aid in evaluating patient prognosis and provide a basis for making effective treatment decisions.