OS1.3 Clinical significance of plasma EVs in Glioblastoma patients

Abstract

Background

Glioblastoma (GBM) is the most common primary brain tumor. Despite aggressive treatment (surgery, chemo- and radiotherapy), the prognosis is dismal (median overall survival: 14m). Actually, early diagnosis and treatment monitoring represent major unmet needs. Extracellular vesicles (EVs) are potentially optimal biomarkers owing to high stability and their presence in blood and cerebrospinal fluid. These features, combined to their genetic and proteomic composition that mirrors the intratumoral environment, highlight EV applicability as blood-based biomarkers for disease diagnosis and therapeutic monitoring.

Material and Methods

We collected plasma samples from healthy controls (n=33), GBMs (n=43) and different central nervous system malignancies (n=25). EVs were isolated and subjected to an integrated analysis relying on transmission electron microscopy, Nanoparticle Tracking Analysis, and mass spectrometry in order to assess morphology, size, concentration and protein composition. An orthotopic mouse model of human GBM was employed to confirm human plasma EV quantifications. Possible associations between plasma EV concentration and clinical features were analyzed. All statistical tests were two-sided.

Results

We observed a significant EVs enrichment in GBM patients plasma if compared to healthy control and patients harboring other CNS malignancies. GBM surgical removal was accompanied by a relevant drop in the concentration of circulating EVs followed by a re-increase at the relapse; this indicates the tumor mass as the major donor of circulating EVs in GBM patients. This phenomenon was confirmed by mouse model. The analyses of EV protein cargo revealed a specific signature, which included members of the complement/coagulation cascade and regulators of iron metabolism.

Conclusion

Our work demonstrates the potential applicability of circulating EVs as reliable cancer biomarker for GBM patients. Furthermore we observed that EV concentration and protein cargo might provide information about response to therapies and tumor progression.