Abstract
Abstract BACKGROUND We previously demonstrated that extracellular vesicles (EV) from CNS tumors reflect the molecular subtype of the original tumor and mediate an exchange of pro-oncogenic signals. EVs are commonly characterized by nanoparticle analysis (NTA), electron microscopy and tetraspanin markers, including CD9, CD81 and CD63. It is unclear, however, to what extent circulating tumor EVs are utilizable for diagnostic purposes and how their marker profile overlaps with EVs derived from other cell types. Aiming to define markers that allow distinction and enrichment of glioma EVs from patient blood, we utilized Imaging Flow Cytometry (IFC) to discriminate single EVs via multiple surface markers. METHODS EVs were isolated from blood of patients suffering from glioblastoma (n=24), anaplastic astrocytoma (n=8), brain metastasis (n=7), meningioma (n=12), pituitary gland tumor (n=11), epilepsy (n=11) and from healthy controls (n=18) and were analyzed by IFC, immunoblotting, electron microscopy and NTA. In addition, circulating EVs from PALM-GFP-GL261 and PALM-GFP-CT2A tumor-bearing mice (n=5) as well as from glioblastoma stem-like (GSC) cultures (n=4), neural stem cells (NSC), cerebral endothelial cells (cEC) and T-cells (n=4) were characterized. RESULTS CNS tumor patients have significantly elevated levels of circulating EVs (P < 0.001), as measured by NTA and IFC. In particular, the proportion of double positive CD9+/CD81+, CD9+/CD63+and CD63+/CD81+EVs is increased in glioblastoma patients (p=0.018) compared with healthy controls[L1]. In accordance, cultured GSCs secrete increased levels of CD9+/CD81+EVs in vitro. In the two syngeneic murine PALM-GFP glioma models, only 0.1-0.01% of circulating plasma EVs were found to be derived from intracranial tumors, underlining the need to identify markers that can enrich tumor-specific EVs for molecular profiling. CONCLUSION Glioma patients display increased levels of circulating plasma EVs that can be profiled by IFC, which is a unique and novel technique that facilitates discrimination of different EV subpopulations.
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