Isolation of Plasma Extracellular Vesicles for High-Depth Analysis of Proteomic Biomarkers in Metastatic Castration-Resistant Prostate Cancer Patients.

Autor: Arafa, Ali T., Ludwig, Megan, Tuncer, Onur, Kollitz, Lily, Gustafson, Ava, Boytim, Ella, Luo, Christine, Sabal, Barbara, Steinberger, Daniel, Zhao, Yingchun, Dehm, Scott M., Cayci, Zuzan, Hwang, Justin, Villalta, Peter W., Antonarakis, Emmanuel S., Drake, Justin M.
Zdroj: Cancers; Dec2024, Vol. 16 Issue 24, p4261, 16p
Abstrakt: Simple Summary: We explored the potential of using proteins found in extracellular vesicles (EVs), which are tiny particles released by cancer cells, to predict treatment response and identify new drug targets. Unlike traditional tissue biopsies, analyzing EVs from blood samples offers a non-invasive way to obtain valuable information about the cancer. Our findings showed that certain proteins in EVs, such as B7-H3 and LAT1, are correlated with clinical markers such as PSA levels, PET scans, and serum alkaline phosphatase levels that are used to monitor disease burden and cancer progression. This approach could lead to more precise and personalized treatment options for patients with advanced prostate cancer, helping doctors choose the most effective therapies and improve outcomes. 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje