High grade serous ovarian carcinoma (HGSOC) is the main histological subtype of ovarian cancer and the main cause of death out of all gynaecological cancers. Chemoresistance, along with late diagnosis, is the main cause for poor prognosis, while there is no predictive biomarker available for predicting chemoresistance. Extracellular vesicles (EV), released by cells, are present in all bodily fluids and enable sample collection at the time of diagnosis, during treatment and after treatment in contrast with biopsy. EV cargo molecules resemble molecules from parent tumour cells. EpCAM molecule is linked to epithelial cancers, including HGSOC. The aim of this study was to determine the potential of overall EV determination and EpCAM positive EV determination to predict chemoresistance. The size of EVs is in the nanometer scale, and so isolation and detection are challenging. Another aim of this study was to optimize the protocol for EV determination from clinical samples. In this study we included three serous ovarian cancer cell lines: OAW28 (isolated from clinically chemoresistant patient with HGSOC), PEO1 (isolated from patient with advanced HGSOC, who was sensitive to chemotherapy) and OAW42 (isolated from patient with early-stage cancer of serous type who was sensitive to chemotherapy). We also included 12 samples of ascites and plasma from advanced HGSOC patients. We determined the concentration of EV with nanoscale flow cytometry (NFC) and nanoparticle tracking analysis (NTA). We used different methods of EV isolation from clinical samples. The highest EV concentration was determined for cell line PEO1 compared to two other cell lines (p < 0,001). There was no statistically significant difference between EV concentrations for cell lines OAW28 and OAW42 (p > 0,05). EpCAM expression for cell line OAW28 was higher than for cell lines PEO1 (p < 0,01) and OAW42 (p < 0,001). The highest concentration and proportion of EpCAM positive EV was for cell line OAW28. The proportion of EpCAM positive EV was highest for OAW28 (45,0 %), compared to PEO1 (10,0 %; p < 0,001) and OAW42 (3,7 %, p < 0,001). EpCAM positive EV concentrations were positively correlated to EpCAM expression on the membranes of serous cancer cells, which EV originate from (r = 0,99; p = 0,02). Both methods of detection showed great diversity of EV concentrations. With NTA we determined higher average size of nanoparticles in ascites than in plasma (ascites: ascites: 130 ± 10,23 nm; plasma 70 ± 3,84 nm; p = 0,028). Out of all isolation methods we determined highest EV concentrations with filtration and lowest with ultracentrifugation. For isolation with size exclusion chromatography (SEC) size distribution of plasma nanoparticles increased (p < 0,05). NFC reported lower EV concentrations than NTA, but results between two methods gave a positive correlation (r = 0,85; p < 0,001). In this study we found that higher EV concentration and proportion of EpCAM positive EV were determined for the cell line, isolated from clinically confirmed chemoresistant HGSOC patient, while overall EV concentrations were not the highest. EpCAM positive EV concentration reflected EpCAM expression on the membrane of cells that EV originated from. This is the first research that shows EpCAM positive EV concentration but not overall EV concentration
is a promising predictive biomarker for chemoresistance in HGSOC. EV detection with NFC is possible for clinical samples of ascites with filtration as an isolation method. This is important for clinical application, where an analysis has to be quick and simple. Methods for EV isolation and methods for EV detection greatly affect measured EV concentrations, so the protocol for clinical determination should be additionally improved before we can continue the research of EpCAM positive EV concentration potential as a predictive biomarker for chemoresistance in HGSOC.
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