Extracellular-Vesicle-Based Cancer Panels Diagnose Glioblastomas with High Sensitivity and Specificity

Simple Summary In this study, we used the RNA sequencing of serum EVs isolated from a large cohort of IDH-wt glioblastoma patients and cancer-free healthy controls to uncover new biological tumor markers with prognostic and diagnostic utility. To our knowledge, this is the first study showing that serum-EV-based biomarker panels can be used to predict/diagnose tumor tissue status in terms of IDH1 mutation, MGMT promoter methylation, TERT promoter mutation, and p53 mutation with a high sensitivity and specificity for glioblastoma. These cancer biomarkers are next-generation precision oncology tools that can be used to (i) predict cancer risk at early stages of the disease, which might offer patients more options and a better chance at overcoming these deadly tumors through surgery or other treatment approaches, and (ii) improve patient stratification and treatment regimes. Abstract Glioblastoma is one of the most devastating neoplasms of the central nervous system. This study focused on the development of serum extracellular vesicle (EV)-based glioblastoma tumor marker panels that can be used in a clinic to diagnose glioblastomas and to monitor tumor burden, progression, and regression in response to treatment. RNA sequencing studies were performed using RNA isolated from serum EVs from both patients (n = 85) and control donors (n = 31). RNA sequencing results for preoperative glioblastoma EVs compared to control EVs revealed 569 differentially expressed genes (DEGs, 2XFC, FDR < 0.05). By using these DEGs, we developed serum-EV-based biomarker panels for the following glioblastomas: wild-type IDH1 (96% sensitivity/80% specificity), MGMT promoter methylation (91% sensitivity/73% specificity), p53 gene mutation (100% sensitivity/89% specificity), and TERT promoter mutation (89% sensitivity/100% specificity). This is the first study showing that serum-EV-based biomarker panels can be used to diagnose glioblastomas with a high sensitivity and specificity.

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