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    Preliminary reports suggest that extracellular vesicles (EVs) might be a promising biomarker for breast cancer (BC). However, the quantification of plasmatic levels of EVs is a complex task. To overcome these limitations, we developed a new, fast, and easy to use assay for the quantification of EVs directly in plasma based on the use of Single-Molecule Array (SiMoA). By using SiMoA to identify CD9+/CD63+ EVs, we analyzed plasma samples of 181 subjects (95 BC and 86 healthy controls, HC). A calibration curve, made of a serial dilution of lyophilized standards from human plasma, was used in each run to ensure the obtainment of quantitative results from the assay. In a subgroup of patients, EVs concentrations were estimated in plasma before and after 30 days from cancer surgery. Additional information on the size of EVs were also acquired using a Nanosight system to obtain a clearer understanding of the mechanism underlying the releases of EVs associated with the presence of cancer. The measured levels of EVs resulted significantly higher in BC patients (median values 1179.1 ng/µl vs 613.0 ng/µl, p < 0.0001). ROC curve was used to define the optimal cut-off level of the test at 1034.5 ng/µl with an AUC of 0.75 [95% CI 0.68-0.82]. EVs plasmatic concentrations significantly decreased after cancer surgery compared to baseline values (p = 0.014). No correlation was found between EVs concentration and clinical features of BC. SiMoA assay allows plasmatic EVs levels detection directly without any prior processing. EVs levels are significantly higher in BC patients and significantly decreases after cancer surgery. © 2021. The Author(s).

    Citation

    Carlo Morasso, Alessandra Ricciardi, Daisy Sproviero, Marta Truffi, Sara Albasini, Francesca Piccotti, Federico Sottotetti, Ludovica Mollica, Cristina Cereda, Luca Sorrentino, Fabio Corsi. Fast quantification of extracellular vesicles levels in early breast cancer patients by Single Molecule Detection Array (SiMoA). Breast cancer research and treatment. 2022 Feb;192(1):65-74

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    PMID: 34935096

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