Davod Jafari1,2, Amir Tiyuri3, Elmnaz Rezaei4, Yousef Moradi3, Rasool Jafari5, Farzaneh Jokar Shoorijeh6, Mahmood Barati2. 1. Student Research Committee, Faculty of Allied Medicine, Iran University of Medical Sciences , Tehran, Iran. 2. Department of Medical Biotechnology, Faculty of Allied Medicine, Iran University of Medical Sciences , Tehran, Iran. 3. Department of Epidemiology, School of Public Health, Iran University of Medical Sciences , Tehran, Iran. 4. Department of Biotechnology, Faculty of Natural Sciences, Imam Khomeini International University , Qazvin, Iran. 5. Department of Medical Parasitology and Mycology, School of Medicine, Urmia University of Medical Sciences , Urmia, Iran. 6. Department of Nanotechnology, Biotechnology Research Institute of Iran , Karaj, Iran.
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.
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.
Authors: Artur Słomka; Bingduo Wang; Tudor Mocan; Adelina Horhat; Arnulf G Willms; Ingo G H Schmidt-Wolf; Christian P Strassburg; Maria A Gonzalez-Carmona; Veronika Lukacs-Kornek; Miroslaw T Kornek Journal: Theranostics Date: 2022-08-01 Impact factor: 11.600