Abstract Glioblastoma (GBM) remains the most common and aggressive primary malignant brain tumor, with limited treatment options and poor overall survival. Diagnosis, prognosis, and assessment of treatment effectiveness are hampered by the lack of sensitive, tumor-specific, non-invasive blood-based assays which could be followed serially. Small extracellular vesicles (sEV) are nano-sized (≤200 nm) membrane-bound bodies secreted by all cells, encapsulating cargo reflective of their parent cells. sEVs have emerged as promising molecular disease indicators. Here, we report the feasibility of isolating glioma-specific sEV (sEVglioma) from plasma and characterizing them for GBM-specific molecular biomarkers. Plasma samples were collected from 31 glioma patients (grades 3 and 4 GBM, grades 2 and 3 astrocytoma) and 9 healthy individuals. Total sEVs (TE) were isolated from plasma by a modified precipitation (ExoQuick™) method, followed by immunoprecipitation to isolate sEVglioma employing surface markers targeting the cellular origin of gliomas, including astrocyte (GLAST and EAAT2), oligodendrocyte precursor cell (OSP and MOG), and neural stem cell (CD133). The average size of sEVglioma was less than 200 nm. Importantly, compared to TE, sEVglioma showed significant enrichment for glioma-specific biomarkers such as ephrin type-A receptor 2 (14.7-fold), tenascin-C (22.7-fold), and glial fibrillary acidic protein (8.4-fold). Similarly, sEVglioma demonstrated higher expression of the GBM biomarker EGFRvIII (3.6-fold). These results were confirmed by confocal microscopy. Interestingly, the expression of specific miRNAs (miR-9a-5p, miR-16-5p, miR-21-5p) in sEVglioma was higher in glioma patients with shorter survival (<12 months) compared to longer survival (>20 months). Lastly, we successfully detected the existence of wild-type IDH1 and absence of mutated IDH1 R132H in sEVglioma from GBM patients, validated with cell line experiments. In conclusion, we present a novel liquid biopsy approach for isolating sEVglioma from blood, providing valuable molecular and genetic information. This approach promises early detection, potential to distinguish pseudo-progression, and assessment of treatment effectiveness with remarkable precision.
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