Multi-omics Analysis of Prostate Derived Extracellular Vesicles: an Observational Retrospective Study for Prostate Cancer Diagnosis and Monitoring (EXOMAP)

Prostate cancer (PCa) is the most commonly diagnosed malignancy in men and a leading cause of cancer-related mortality worldwide. Over 1.4 million new cases of prostate cancer are estimated to occur worldwide each year, with more than 375,000 related deaths. High-risk PCa poses significant challenges due to the aggressive nature of the disease and the ability to create an immunosuppressive tumor microenvironment (TME), thereby hampering the effectiveness of existing therapies. Despite advances in diagnostics and treatment, the mechanisms driving immune evasion and tumor progression in high-risk PCa remain poorly understood. These considerations underscore the urgent need for innovative strategies to address these challenges and improve patient outcomes.

Extracellular vesicles (EVs) have emerged as critical players in cancer biology. EVs carry molecular cargo, including proteins, RNA, lipids, and metabolites, enabling mediation of intercellular communication and influence on cancer progression. Tumor-derived EVs (TDEVs) are particularly implicated in promoting tumor growth, reprogramming the TME, and suppressing antitumor immune responses. Owing to the intrinsic ability to mediate intercellular communication and transport biomolecules to distant sites, EVs represent key contributors to cancer pathogenesis.

A previous study demonstrated, through comprehensive metabolomics profiling, a combination of small molecules extracted from expressed prostatic secretion (EPS)-urine, integrated with clinical parameters, that could effectively identify and stratify PCa patients, highlighting the potential of this biofluid in PCa diagnostics. EPS-urine represents a unique biofluid enriched with EVs secreted directly by prostate tissue, offering a valuable source for the study of prostate-specific EVs. Based on this evidence, the potential of prostate cancer (PCa)-derived EVs is being explored as a transformative approach for the management of high-risk prostate cancer.

The project qualifies as a basic research study with potential translational relevance. An observational retrospective study has been designed with the objective of comprehensively characterizing extracellular vesicles (EVs) derived from EPS-urine using multi-omics approaches. The analysis will be conducted on samples from 100 patients, all recruited exclusively at the Department of Urology at IRCCS San Raffaele Hospital. Patients are categorized into two groups: patients with clinically significant prostate cancer (csPCa), including intermediate-risk PCa (ISUP grade 2-3) and high-risk PCa (ISUP grade 4-5), and patients with non-clinically significant PCa (non-csPCa), including low-risk PCa (ISUP grade 1) and patients with benign prostatic hypertrophy. The study is expected to provide unprecedented insights into prostate tissue-derived EVs, laying the foundation for functional validation of key molecular markers and pathways implicated in PCa progression.

Study Overview

• Status: Completed
• Conditions: Prostate Cancer Adenocarcinoma

• Study Type: Observational
• Enrollment (Actual): 100

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

100 patients who received diagnosis of PCa or BPH through prostate biopsies between 2016 and 2018. EPS-urine samples were collected from all patients.

Description

Inclusion Criteria:

• Patients who received diagnosis of PCa or BPH through prostate biopsies between 2016 and 2018 and subsequently have signed the informed consent (URBBAN protocol "Regulation for the collection, storage and use of human biological material" v.4 of 14/02/2014 or v.5 of 10/04/2017)
• EPS-urine samples collected from patients undergoing prostate biopsies
• Aged > 18 years old

Exclusion Criteria:

• Aged < 18 years old
• Concomitant other urological malignancies
• Previous systemic oncological treatments for prostate cancer

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identify a multi-omics signature from EPS-urine derived EVs in prostate cancer	Identification of a multi-omics signature from EPS-urine-derived extracellular vesicles (EVs) in prostate cancer patients, defined through integrated LC-MS/MS analysis of EV-associated proteins (relative peak intensities).; Identification of a multi-omics lipid signature in EPS-urine-derived EVs, defined as relative abundance (peak intensities) of EV-associated lipids measured by LC-MS/MS.; Identification of a multi-omics metabolite signature in EPS-urine-derived EVs, defined as relative abundance (peak intensities) of EV-associated metabolites measured by LC-MS/MS.; EV concentration and size distribution in EPS-urine, measured as particles/mL and particle size distribution by nanoparticle tracking analysis (NTA).; Prostate-specific EV enrichment, assessed using fluorescence-based quantification and specific markers.	Baseline / Time zero

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correlation between EVs multiomics profiling and prostate cancer clinical progression.	The secondary objective is to evaluate if there is a correlation between EVs multiomics profiling and prostate cancer clinical progression. To determine this correlation, the patients will be divided in two groups: clinically significant prostate cancer (csPCa), including intermediate-risk PCa (ISUP grade 2-3) and high-risk PCa (ISUP grade 4-5); non-clinically significant PCa (non-csPCa): including low-risk PCs (ISUP grade 1) and patients with benign prostatic hypertrophy. Samples will be characterized by multi-comics approaches in LC-MS/MS. The data collected from the two groups will be compared and evaluated using t-test statistical method. Based on the results obtained in this first phase of the study, the next step will be the validation of a predictive model using EVs multi-omics profile and patients' clinical data along with imaging data, through artificial intelligence (AI). This second part will be the object of a future study on an independent cohort of patients.	Baseline / Time zero

Collaborators and Investigators

• Sponsor: IRCCS San Raffaele

Study record dates

Study Major Dates

• Study Start (Actual): January 1, 2016
• Primary Completion (Actual): February 1, 2016
• Study Completion (Actual): December 31, 2018

Study Registration Dates

• First Submitted: December 10, 2025
• First Submitted That Met QC Criteria: January 13, 2026
• First Posted (Actual): January 21, 2026

Study Record Updates

• Last Update Posted (Actual): May 15, 2026
• Last Update Submitted That Met QC Criteria: May 13, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: EXOMAP

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No