Definition of an Inflammatory Biomarker Signature in Plasma-Derived Extracellular Vesicles of Glioblastoma Patients.

Glioblastoma (GB) is an aggressive type of tumour for which therapeutic options and biomarkers are limited. GB diagnosis mostly relies on symptomatic presentation of the tumour and, in turn, brain imaging and invasive biopsy that can delay its diagnosis. Description of easily accessible and effective biomarkers present in biofluids would thus prove invaluable in GB diagnosis. Extracellular vesicles (EVs) derived from both GB and stromal cells are essential to intercellular crosstalk in the tumour bulk, and circulating EVs have been described as a potential reservoir of GB biomarkers. Therefore, EV-based liquid biopsies have been suggested as a promising tool for GB diagnosis and follow up. To identify GB specific proteins, sEVs were isolated from plasma samples of GB patients as well as healthy volunteers using differential ultracentrifugation, and their content was characterised through mass spectrometry. Our data indicate the presence of an inflammatory biomarker signature comprising members of the complement and regulators of inflammation and coagulation including VWF, FCGBP, C3, PROS1, and SERPINA1. 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 GB diagnosis and, consequently, patients' prognosis and quality of life.

Cell-derived extracellular vesicles can be used as a biomarker reservoir for glioblastoma tumor subtyping.

Glioblastoma (GBM) is one of the most aggressive solid tumors for which treatment options and biomarkers are limited. Small extracellular vesicles (sEVs) produced by both GBM and stromal cells are central in the inter-cellular communication that is taking place in the tumor bulk. As tumor sEVs are accessible in biofluids, recent reports have suggested that sEVs contain valuable biomarkers for GBM patient diagnosis and follow-up. The aim of the current study was to describe the protein content of sEVs produced by different GBM cell lines and patient-derived stem cells. Our results reveal that the content of the sEVs mirrors the phenotypic signature of the respective GBM cells, leading to the description of potential informative sEV-associated biomarkers for GBM subtyping, such as CD44. Overall, these data could assist future GBM in vitro studies and provide insights for the development of new diagnostic and therapeutic methods as well as personalized treatment strategies.