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Diagnosis of Prostate Cancer through the Multi-Ligand Binding of Prostate-Derived Extracellular Vesicles and miRNA Analysis. | LitMetric

AI Article Synopsis

Article Abstract

Background: The development of new non-invasive markers for prostate cancer (PC) diagnosis, prognosis, and management is an important issue that needs to be addressed to decrease PC mortality. Small extracellular vesicles (SEVs) secreted by prostate gland or prostate cancer cells into the plasma are considered next-generation diagnostic tools because their chemical composition might reflect the PC development. The population of plasma vesicles is extremely heterogeneous. The study aimed to explore a new approach for prostate-derived SEV isolation followed by vesicular miRNA analysis.

Methods: We used superparamagnetic particles functionalized by five types of DNA-aptamers binding the surface markers of prostate cells. Specificity of binding was assayed by AuNP-aptasensor. Prostate-derived SEVs were isolated from the plasma of 36 PC patients and 18 healthy donors and used for the assessment of twelve PC-associated miRNAs. The amplification ratio (amp-ratio) value was obtained for all pairs of miRNAs, and the diagnostic significance of these parameters was evaluated.

Results: The multi-ligand binding approach doubled the efficiency of prostate-derived SEVs' isolation and made it possible to purify a sufficient amount of vesicular RNA. The neighbor clusterization, using three pairs of microRNAs (miR-205/miR-375, miR-26b/miR375, and miR-20a/miR-375), allowed us to distinguish PC patients and donors with sensitivity-94%, specificity-76%, and accuracy-87%. Moreover, the amp-ratios of other miRNAs pairs reflected such parameters as plasma PSA level, prostate volume, and Gleason score of PC.

Conclusions: Multi-ligand isolation of prostate-derived vesicles followed by vesicular miRNA analysis is a promising method for PC diagnosis and monitoring.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10141197PMC
http://dx.doi.org/10.3390/life13040885DOI Listing

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