RESUMEN
Conventional diagnostic tools for prostate cancer (PCa), such as prostate-specific antigen (PSA), transrectal ultrasound (TRUS), digital rectal examination (DRE), and tissue biopsy face, limitations in individual risk stratification due to invasiveness or reliability issues. Liquid biopsy is a less invasive and more accurate alternative. Metabolomic analysis of extracellular vesicles (EVs) holds a promise for detecting non-genetic alterations and biomarkers in PCa diagnosis and risk assessment. The current research gap in PCa lies in the lack of accurate biomarkers for early diagnosis and real-time monitoring of cancer progression or metastasis. Establishing a suitable approach for observing dynamic EV metabolic alterations that often occur earlier than being detectable by other omics technologies makes metabolomics valuable for early diagnosis and monitoring of PCa. Using four distinct metabolite extraction approaches, the metabolite cargo of PC3-derived large extracellular vesicles (lEVs) was evaluated using a combination of methanol, cell shearing using microbeads, and size exclusion filtration, as well as two fractionation chemistries (pHILIC and C18 chromatography) that are also examined. The unfiltered methanol-microbeads approach (MB-UF), followed by pHILIC LC-MS/MS for EV metabolite extraction and analysis, is effective. Identified metabolites such as L-glutamic acid, pyruvic acid, lactic acid, and methylmalonic acid have important links to PCa and are discussed. Our study, for the first time, has comprehensively evaluated the extraction and separation methods with a view to downstream sample integrity across omics platforms, and it presents an optimised protocol for EV metabolomics in PCa biomarker discovery.
RESUMEN
Prostate cancer (PCa) is a global health concern, ranking as the most common cancer among men in Western countries. Traditional diagnostic methods are invasive with adverse effects on patients. Due to the heterogeneous nature of PCa and their multifocality, tissue biopsies often yield false-negative results. To address these challenges, researchers are exploring innovative approaches, particularly in the realms of proteomics and metabolomics, to identify more reliable biomarkers and improve PCa diagnosis. Liquid biopsy (LB) has emerged as a promising non-invasive strategy for PCa early detection, biopsy selection, active surveillance for low-risk cases, and post-treatment and progression monitoring. Extracellular vesicles (EVs) are lipid-bilayer nanovesicles released by all cell types and play an important role in intercellular communication. EVs have garnered attention as a valuable biomarker resource in LB for PCa-specific biomarkers, enhancing diagnosis, prognostication, and treatment guidance. Metabolomics provides insight into the body's metabolic response to both internal and external stimuli, offering quantitative measurements of biochemical alterations. It excels at detecting non-genetic influences, aiding in the discovery of more accurate cancer biomarkers for early detection and disease progression monitoring. This review delves into the potential of EVs as a resource for LB in PCa across various clinical applications. It also explores cancer-related metabolic biomarkers, both within and outside EVs in PCa, and summarises previous metabolomic findings in PCa diagnosis and risk assessment. Finally, the article addresses the challenges and future directions in the evolving field of EV-based metabolomic analysis, offering a comprehensive overview of its potential in advancing PCa management.