Abstract
Abstract Diagnosis of Glioblastoma (GBM) remains a clinical challenge, currently relying on symptomatic presentation of the tumour, brain imaging and invasive biopsy. Description of effective biomarkers in biofluids could prove invaluable in GBM diagnosis. Extracellular vesicles (EVs) are essential to intercellular crosstalk in the tumour bulk and circulating EVs have been described as a potential reservoir of GBM biomarkers. Our work focuses on the: (i) isolation of EVs from blood liquid biopsies of GBM patients. (ii) Characterisation of their transcriptomic and proteomic cargoes to identify/validate novel candidate GBM biomarkers that could improve GBM diagnosis/prognosis. (iii) For cases where the original GBM tumour tissues are available, we will examine the expression of the identified biomarker signatures (derived from blood-EVs) to see if the content of EVs mirrors the transcriptomic/proteomic profile of the original tissue. Similar comparisons will be performed in GBM cohorts available in TCGA. Ultimately, in future studies, transcriptomic/proteomic analyses will be assessed during patients’ follow-ups to correlate the observed biomarker profiles with MRI data,treatment,recurrence, including molecular and clinical features.Our preliminary data comparing the proteomic cargoes of EVs derived from GBM patients (n=15) and those from healthy volunteers (n=10) indicated the presence of a GBM inflammatory biomarker signature comprising members of the complement and regulators of inflammation and coagulation. Bioinformatic analysis highlighted that all potential markers exclusively identified in patient samples have been linked with either GBM diagnosis,prognosis or associated signalling, suggesting that sEVs protein cargo could mirror the landscape of the original tumour and that selective circulating sEV-derived proteins might be used as hallmarks for GBM patients.Overall, this study is a step forward in the development of a non-invasive liquid biopsy approach for the identification of valuable biomarkers that could significantly improve GBM diagnosis and, consequently, patients’ prognosis and quality of life.
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