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. Supplementary information: The online version contains supplementary material available at 10.1186/s12575-025-00293-2.
Refining Flow Cytometry-based Sorting of Plasma-derived Extracellular Vesicles
Reverberi D.;Ciferri M. C.;Rosenwasser N.;Quarto R.;Santamaria S.;Coco S.;Tasso R.
2025-01-01
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. Supplementary information: The online version contains supplementary material available at 10.1186/s12575-025-00293-2.
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