{"doi":"10.3390/cancers16244261","title":"Isolation of Plasma Extracellular Vesicles for High-Depth Analysis of Proteomic Biomarkers in Metastatic Castration-Resistant Prostate Cancer Patients","abstract":"Introduction: Prostate cancer treatment has been revolutionized by targeted therapies, including PARP inhibitors, checkpoint immunotherapies, and PSMA-targeted radiotherapies. Despite such advancements, accurate patient stratification remains a challenge, with current methods relying on genomic markers, tissue staining, and imaging. Extracellular vesicle (EV)-derived proteins offer a novel non-invasive alternative for biomarker discovery, holding promise for improving treatment precision. However, the characterization of plasma-derived EVs in prostate cancer patients remains largely unexplored. Methods: We conducted proteomic analyses on EVs isolated from plasma in 27 metastatic castration-resistant prostate cancer (mCRPC) patients. EVs were purified using ultracentrifugation and analyzed via mass spectrometry. Proteomic data were correlated with clinical markers such as serum prostate-specific antigen (PSA) and bone lesion counts. Statistical significance was assessed using Mann–Whitney t-tests and Spearman correlation. Results: The median age of patients was 74 (range: 44–94) years. At the time of blood collection, the median PSA level was 70 (range: 0.5–1000) ng/mL. All patients had bone metastasis. A total of 5213 proteins were detected, including EV-related proteins (CD9, CD81, CD63, FLOT1, TSG101) and cancer-related proteins (PSMA, B7-H3, PD-L1). Proteomic profiling of plasma EVs revealed a significant correlation between specific EV-derived proteins and clinical prognostic markers. B7-H3, LAT1, and SLC29A1 showed a strong association with serum PSA levels and number of bone lesions, indicating potential for these proteins to serve as biomarkers of disease burden and therapy response. Conclusions: Our findings demonstrate the potential of EV-based proteomics for identifying biomarkers in mCRPC patients. Proteins such as B7-H3 and LAT1 could guide precision oncology approaches, improving patient stratification. Future research incorporating outcomes data and EV subpopulation analysis is needed to establish clinical relevance.","journal":"Cancers","year":2024,"id":448127,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9551,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":590383,"name":"Megan Ludwig","orcid":"0000-0003-3133-3679","position":1,"is_corresponding":false},{"id":1266777,"name":"Onur Tuncer","orcid":"0000-0003-3345-9208","position":2,"is_corresponding":false},{"id":1267172,"name":"Lily Kollitz","orcid":null,"position":3,"is_corresponding":false},{"id":1267173,"name":"Ava Gustafson","orcid":null,"position":4,"is_corresponding":false},{"id":1237727,"name":"Ella Boytim","orcid":"0009-0007-8062-6431","position":5,"is_corresponding":false},{"id":394296,"name":"Christine Luo","orcid":null,"position":6,"is_corresponding":false},{"id":1267174,"name":"Barbara Sabal","orcid":null,"position":7,"is_corresponding":false},{"id":1266778,"name":"Daniel Steinberger","orcid":"0000-0002-7410-3630","position":8,"is_corresponding":false},{"id":1266779,"name":"Yingchun Zhao","orcid":"0000-0002-8958-4406","position":9,"is_corresponding":false},{"id":292251,"name":"Scott M. Dehm","orcid":"0000-0002-7827-5579","position":10,"is_corresponding":false},{"id":730402,"name":"Zuzan Caycı","orcid":"0000-0002-2542-9087","position":11,"is_corresponding":false},{"id":351741,"name":"Justin H. Hwang","orcid":"0000-0003-1686-7103","position":12,"is_corresponding":false},{"id":473662,"name":"Peter W. Villalta","orcid":"0000-0002-0067-3083","position":13,"is_corresponding":false},{"id":272258,"name":"Emmanuel S. Antonarakis","orcid":"0000-0003-0031-9655","position":14,"is_corresponding":false},{"id":351743,"name":"Justin M. Drake","orcid":"0000-0002-8329-7748","position":15,"is_corresponding":false},{"id":1219963,"name":"Ali T. Arafa","orcid":null,"position":0,"is_corresponding":true}],"reference_count":42,"raw_metadata":null,"created_at":"2026-07-19T02:02:08.018689Z","pmid":"39766159","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}