Prostate cancer (PCa) diagnosis faces limitations, including high invasiveness and inaccuracy, highlighting the need for improved non-invasive diagnostic methods. Due to the distal location of the prostate to the urinary bladder, PCa markers can be detected in urine. Urine contains extracellular vesicles (EVs), which are secreted by various cell types, including PCa cells. The EV content in-part mirrors the content of the cells it originates from and has previously been proven to contain disease specific markers.

To investigate whether PCa patients can be identified from the protein profiles in urinary EVs (uEVs), we performed in-depth LC-MS/MS-based proteomics profiling of uEVs from 222 individual patients, using multicenter-collected samples. We generated three datasets using DDA (n=43/D43, n=94/D94) and DIA (n=85/D85) and identified 2025, 2693, and 3891 proteins, respectively (30% data presence).

Prostate-specific proteins (e.g. KLK3, FOLH1) and EV-associated proteins (e.g. CD9, CD63) correlated to an EV-score, calculated based on the top 100 EV proteins from vesiclepedia, confirming the presence of EVs and prostate-proteins within the uEVs. Gene Ontology analysis shows a highly similar function of protein in the 3 datasets, with proteins involved in immunity, metabolism and cell adhesion. In uEVs of PCa patients, 15 proteins were significantly upregulated, and 17 significantly downregulated, in 2/3 datasets. (Single-sample) Gene-Set-Enrichment-Analysis showed enrichment of immune-related processes, and decreased cell cycle pathways/signaling. To develop a protein-signature with high sensitivity/specificity, we calculated a score based on the number of proteins that were above the specified threshold of 2 times the value of the standard deviation. The top 10 proteins that were above this threshold in most of the PCa patients were included in the signature. We achieved a sensitivity of 81, 82, 82% with a specificity of 83,81,82% in D43, D94, and D85, respectively. In conclusion, uEVs are a great source for accurate PCa detection.

This study was financially supported by the IMMPROVE Alpe d"HuZes grant of the Dutch Cancer Society (EMCR2015-8022), and Cancer Center Amsterdam and the Netherlands Organization for Scientific Research (NWO Middelgroot, #91116017) are acknowledged for support of the mass spectrometry infrastructure.