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- W2895910708 abstract "Extracellular Vesicles (EVs) have significant potential as non-invasive biomarkers. We have developed a first-in-class pipeline to characterize EV heterogeneity and provide high-sensitivity quantification of informative EVs in biofluids throughout treatment. By combining multiplex assays with high-resolution, single EV flow cytometric methods together into a Mutiplex-to-Single EV Analysis (Mt-SEA) pipeline, we characterized a broad range of EV subsets, while also measuring the concentration of specific EV populations. Exploratory studies validate the Mt-SEA method by confirming strong correlations of liquid biopsy EV repertoires with tumor burden and responses to treatment. Plasma was obtained before and after treatment from patients receiving palliative radiation. Multiplex EV capture beads were used with additional detection antibodies to identify major EV subsets. General exosome and EV detection epitopes included CD63, CD9, and CD81. Tumor-specific epitopes for each patient were also selected. High-resolution single EV analyses were performed with a prototype nanoFCM analyzer with single molecule sensitivity. Tumor-derived EVs were detected in each pre-treatment sample, with reduced specific tumor-derived EV subsets concentrations at the end of treatment. Furthermore, tumor-specific EVs from patients with progressive systemic disease prior to treatment were found to carry stemness-associated epitopes, consistent with increasing tumor aggressiveness. Responses to treatment that were clinically evident mirrored changes in the Mt-SEA EV profiles, and Mt-SEA identified new candidate prognostic EV profiles associated with clinical outcomes. Our study demonstrates that Mt-SEA provides unexpected insights into tumor biology, along with robust estimations of concentrations of EV subsets of interest. Detection of tumor-associated EVs and detection of EV repertoire changes during treatment paves the way to future evaluation of the Mt-SEA pipeline for personalized therapies in a wider range of tumor types." @default.
- W2895910708 created "2018-10-26" @default.
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- W2895910708 date "2018-11-01" @default.
- W2895910708 modified "2023-10-04" @default.
- W2895910708 title "Development of an Exosome Analysis Pipeline for Precision Oncology" @default.
- W2895910708 doi "https://doi.org/10.1016/j.ijrobp.2018.07.645" @default.
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