Biom-10. Circulating Extracellular Vesicles as a Tool for Diagnosis, Prognosis and Monitoring in Glioma

Abstract

OBJECTIVE Extracellular vesicles (EVs) represent a population of lipid bilayer nanoparticles released by all cell types, including tumor cells that can serve as a noninvasive source for liquid biopsy. To date, MRI images have been the established method for monitoring treatment efficacy in brain tumor patients. We investigated the potential of pure EV count for diagnosis, prognosis, and treatment monitoring in gliomas. METHODS Plasma samples, differential blood counts, at multiple timepoints before and after surgery of glioblastoma patients (n=101) were collected. Follow-up samples were obtained every 3 months. Healthy donors served as controls (n=29). Plasma EVs concentration was measured by Nanoparticle Tracking Analysis (NTA). EVs were characterized by electron microscopy and imaging flow cytometry. Tumor burden was measured by MRI images. Clinical characteristics were prospectively recorderd. In addition plasma EVs from Mut3 tumor bearing mice were analysed at d3, d5, d7, d10, d12 after tumor injection (n=20). MRI images and differential blood counts were analyzed. RESULTS Glioblatoma patients have a 5-fold increase of plasma EVs compared to HD; p < 0.0001). Circulating EVs counts correlated only with FLAIR hyperintensity and with no other MRI or blood-based parameter. Similar results were obtained from Mut3 tumor mice. Dichotomisation of GBM patients in EVhigh and low revealed a significant overall survival and progression free survival benefit for EVlow patients (p=0.004). After surgery, EVs decreased significantly (5-fold, p< 0.0001). A massive drop in EVs was associated with gross-total resection (p < 0.05). At the time of tumor recurrence, the number of circulating EVs increased in all patients during a follow-up (9 months). CONCLUSION Our findings highlight the potential of circulating EVs as a biomarker tool for diagnosis, prognosis and treatment monitoring in GBM patietns, as they seem to reflect the presence of a tumor mass and thus may assist in clinical decision making.