The recent introduction of the "precision medicine" concept in oncology pushed cancer research to focus on dynamic measurable biomarkers able to predict responses to novel anticancer therapies in order to improve clinical outcomes. Recently, the involvement of extracellular vesicles (EVs) in cancer pathophysiology has been described, and given their release from all cell types under specific stimuli, EVs have also been proposed as potential biomarkers in cancer. Among the techniques used to study EVs, flow cytometry has a high clinical potential. Here, we have applied a recently developed and simplified flow cytometry method for circulating EV enumeration, subtyping, and isolation from a large cohort of metastatic and locally advanced nonhaematological cancer patients ( = 106); samples from gender- and age-matched healthy volunteers were also analysed. A large spectrum of cancer-related markers was used to analyse differences in terms of peripheral blood circulating EV phenotypes between patients and healthy volunteers, as well as their correlation to clinical outcomes. Finally, EVs from patients and controls were isolated by fluorescence-activated cell sorting, and their protein cargoes were analysed by proteomics. Results demonstrated that EV counts were significantly higher in cancer patients than in healthy volunteers, as previously reported. More interestingly, results also demonstrated that cancer patients presented higher concentrations of circulating CD31+ endothelial-derived and tumour cancer stem cell-derived CD133 + CD326- EVs, when compared to healthy volunteers. Furthermore, higher levels of CD133 + CD326- EVs showed a significant correlation with a poor overall survival. Additionally, proteomics analysis of EV cargoes demonstrated disparities in terms of protein content and function between circulating EVs in cancer patients and healthy controls. Overall, our data strongly suggest that blood circulating cancer stem cell-derived EVs may have a role as a diagnostic and prognostic biomarker in cancer.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6885781PMC
http://dx.doi.org/10.1155/2019/5879616DOI Listing

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