Ovarian cancer (OC) has one of the poorest survival rates of gynaecological malignancies, due to absence of effective screening tools and reliable biomarkers for early detection. However, extracellular vesicle-encapsulated microRNAs (miRNAs) have recently emerged as promising biomarker candidates. While small EVs of exosomal size (30–150 nm) have been isolated from cervicovaginal secretions in endometriosis [1], their use in OC diagnostics remains unexplored. This study investigates whether EVs can be isolated from vaginal swabs collected from OC patients and whether these EVs contain candidate early OC-associated miRNAs previously identified by our group [2].
Matched serum and vaginal swab samples were collected from patients across varying OC stages (n=18). Swab samples were collected into 1mL 1xPBS pH 7.4 supplemented with 25 mM trehalose and HEPES, cleared via differential centrifugation and applied to a qEV1 Gen2 35 nm size exclusion column (Izon Science) to isolate EVs. EVs were characterised using established protocols according to MISEV2024 guidelines. Expression of identified candidate early OC-associated miRNAs (miR-200a/b/c-3p, miR-375-3p and miR-42) were assessed in serum and swab-derived EVs using qPCR. CA-125 concentration, in whole and EV-associated serum in parallel with vaginal-swab derived-EVs, was quantified via ELISA (Human CA125 DuoSet ELISA, R&D Systems) from matched patient samples. Diagnostic potential was assessed using receiver operating characteristic (ROC) curve analysis, comparing miRNA markers and EV CA-125 with conventional CA-125 serum levels.
Preliminary data suggests comparable CA-125 concentrations between whole serum and serum derived-EVs, with the expectation this translates to vaginal swab derived-EVs. Future analyses will identify EV-derived candidate biomarker miRNA expression and the success of vaginal-swab EV characterisation.
This is one of the first studies to assess feasibility of vaginal swab-derived EVs as a non-invasive biospecimen for OC biomarker discovery. Our findings will highlight the translational potential of vaginal EVs in developing novel early detection strategies for ovarian cancer.