Refining Flow Cytometry-based Sorting of Plasma-derived Extracellular Vesicles

Abstract

Background: Extracellular vesicles (EVs) are membrane-bound particles crucial for intercellular communication and serve as promising biomarkers for diseases, including cancer. Isolating and characterizing specific EV subpopulations, particularly those in plasma/serum, enhances biomarker precision and supports targeted therapies. Cancer-derived EVs often express unique surface markers, enabling distinction from other EVs. Accurate sorting of tumor-associated EVs provides insights into cancer progression, metastasis, and treatment response. Results: This study presents a robust method for isolating and sorting CD9 + plasma EVs as a proof-of-concept for broader EV subpopulation analyses. Plasma EVs were isolated via sucrose cushion ultracentrifugation, optimizing purity and yield. Flow cytometry with fluorescence threshold triggering was fine-tuned to detect and sort CD9 + EVs, with instrument calibration and parameter adjustments mitigating swarming and improving sorting accuracy. Size exclusion chromatography further enhanced efficiency by reducing background noise. Sorted CD9 + EVs retained size and marker expression, including Syntenin, Alix, Flotillin-1, and CD9, which were enriched post-sorting. Conclusions: These advancements enable high-purity EV subpopulation isolation, facilitating applications such as identifying cancer biomarkers and developing EV-based targeted therapies.