ABSTRACT
Background
Glioblastoma (GBM) is the most malignant brain cancer because there are no available biopsy-free methods for the diagnosis or the preoperative early detection. In this regard, the development of a non- or minimally invasive methods for early detection could increase the survival rate of GBM patients.
Methods
The present study aimed to assess the diagnostic accuracy of extracellular vesicles (EVs) derived RNAs, isolated from patients’ CSF or serum for GBM diagnosis. For this purpose, we searched all literature databases and performed a backward and forward reference checking procedure to retrieve appropriate studies. We conducted a meta-analysis on EVs derived biomarkers as well as sensitivity analysis and meta-regression.
Results
We identified EVs-derived 24 RNAs, which can diagnose GBM. The analyzed pooled data showed 76% sensitivity, 80% specificity, and 0.85 AUC, for 16 biomarkers. Besides, the pooled PLR, NLR, and DOR were 3.7, 0.30, and 12, respectively. Subgroup analysis did not show a significant difference between serum and CSF.
Conclusions
According to the pooled sensitivity, specificity, and AUC for EVs derived biomarkers, we suggest that EVs-derived biomarkers might serve as a high potential and noninvasive diagnostic tool for GBM detection using serum and CSF samples.
Article highlights
Extracellular vesicles derived RNA biomarkers could diagnose glioblastoma with 76% sensitivity and 80% specificity.
The overall AUC for extracellular vesicle-derived biomarkers for the diagnosis of glioblastoma is 0.85.
There are no significant differences in diagnostic accuracy between serum- and CSF derived EVs for glioblastoma..
Author contributions
D. Jafari was responsible for the conception and design of the study. D.Jafari, A. Tiyuri and E. Rezaei acquired the data. A. Tiyuri, D. Jafari were responsible for analysis and/or interpretation of the data. D. Jafari, A. Tiyuri, R. Jafari, F.J. Shoorijeh and Y. Moradi all drafted the manuscript. D.Jafari, A. Tiyuri, R. Jafari, M. Barati all revised the manuscript in a manner critically for important intellectual content.
Availability of data and material
Input data for the analyses are available from the corresponding author on request.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Supplementary material
Supplemental data for this article can be accessed here.