Imaging flow cytometry facilitates multiparametric characterization of extracellular vesicles in malignant brain tumours


Cells release heterogeneous nano-sized vesicles either as exosomes, being derived from endosomal compartments, or through budding from the plasma membrane as so-called microvesicles, commonly referred to as extracellular vesicles (EVs). EVs are known for their important roles in mammalian physiology and disease pathogenesis and provide a potential biomarker source in cancer patients. EVs are generally often analysed in bulk using Western blotting or by bead-based flow-cytometry or, with limited parameters, through nanoparticle tracking analysis. Due to their small size, single EV analysis is technically highly challenging. Here we demonstrate imaging flow cytometry (IFCM) to be a robust, multiparametric technique that allows analysis of single EVs and the discrimination of distinct EV subpopulations. We used IFCM to analyse the tetraspanin (CD9, CD63, CD81) surface profiles on EVs from human and murine cell cultures as well as plasma samples. The presence of EV subpopulations with specific tetraspanin profiles suggests that EV-mediated cellular responses are tightly regulated and dependent on cell environment. We further demonstrate that EVs with double positive tetraspanin expression (CD63+/CD81+) are enriched in cancer cell lines and patient plasma samples. In addition, we used IFCM to detect tumour-specific GFP-labelled EVs in the blood of mice bearing syngeneic intracerebral gliomas, indicating that this technique allows unprecedented disease modelling. In summary, our study highlights the heterogeneous and adaptable nature of EVs according to their marker profile and demonstrates that IFCM facilitates multiparametric phenotyping of EVs not only in vitro but also in patient plasma at a single EV level, with the potential for future functional studies and clinically relevant applications. Abbreviation: EDTA = ethylenediamine tetraacetic acid.

Bibliografische Daten

StatusVeröffentlicht - 2019
PubMed 30949309