ArticleDiscover oncology2024
Optimized workflow of EV enrichment from human plasma samples for downstream mass spectrometry analysis.
Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
9 authors.
Funding
Abstract
To improve the prognosis of bladder and prostate cancer, highly specific and sensitive biomarkers are needed for early detection, prognosis prediction, and therapeutic stratification. Extracellular vesicles (EV) from plasma could fill this gap due to their potential to serve as cancer biomarkers. However, the enrichment of EV is a major challenge, because the highly abundant plasma proteins are interfering with analytical downstream applications like mass spectrometry (MS). Therefore, the purity requirements of the EV samples must be carefully considered when selecting or developing a suitable EV enrichment method. The aim of this study was to compare a self-designed EV enrichment method based on density cushion centrifugation (DCC) combined with size exclusion chromatography (SEC) and concentration (method 1) with the exoRNeasy midi kit from Qiagen (method 2) and with unprocessed plasma. Furthermore, the single steps of method 1 were evaluated for their effectiveness to enrich EV from plasma. The results showed that the EV samples enriched with method 1 contained the highest levels of EV and exosome markers with simultaneously low levels of highly abundant plasma proteins. In summary, the combination of DCC, SEC and concentration proved to be a promising approach to discover EV-based biomarkers from plasma of cancer patients.
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Registered trials
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