Background: Glioblastoma (GBM) is by far the most common primary malignant neoplasm of the central nervous system. In spite ofsome progress in diagnosis and treatment, GBM patients still have a poor prognosis. Hence, to improve GBM diagnosis, finding novel non-invasive biomarkers, e.g., miRNA-based biomarkers,is of importance.Methods: A pair of 50 GBM and healthy samples were used. The expression of each candidate miRNA (i.e.,hsa-let-7c-5p, hsa-miR-206-5p, and hsa-miR-1909-5p)was measured using quantitative reverse transcription PCR. To show the roles of each miRNA and their biological effects on GBM development, in silico tools were used. Receiver operating characteristic (ROC) curves were performed to assess the diagnostic accuracy of each miRNA; the possible association of their expression with clinicopathological characteristics wasalso analyzed. To find out any association between the miRNA expression and GBM prognosis, in silico tools were used.Results: We showed the downregulation of hsa-let-7c-5pand hsa-miR-206-5p, and upregulation of hsa-miR-1909-5p in GBM tumor compared to healthy samples. No association was detected between the expression of each candidate miRNA and ‘sex’. Except for hsa-let-7c-5p, other miRNAs did not show any correlation with ‘age’ status. ROC curve analysis showed that the signature of candidate miRNAsis a potential biomarker distinguishing between GBM and healthy samples. Only hsa-miR-206-5p showed the association with poor prognosis in GBM patients.Conclusions: We demonstrated that the dysregulation of three candidate miRNAs may be used as a biomarker for GBM diagnosis. These results are beneficial in clinical management of GBM patients.

Background: Glioblastoma is the most common primary malignant neoplasm of the central nervous system. Despite progress in diagnosis and treatment, glioblastoma still has a poor prognosis. This study aimed to examine whether a signature of three candidate miRNAs (i.e. hsa-let-7c-5p, hsa-miR-206-5p, and hsa-miR-1909-5p) can be used as a diagnostic biomarker for distinguishing glioblastoma from healthy brain tissues. Methods: In this study, 50 FFPE glioblastoma tissue samples and 50 healthy tissue samples adjacent to tumor were included. The expression of each candidate miRNA (i.e. hsa-let-7c-5p, hsa-miR-206-5p, and hsa-miR-1909-5p) was measured using RT-qPCR. To show the roles of each miRNA and their biological effects on glioblastoma development and clinicopathological characteristics, in silico tools were used. ROC curves were performed to assess the diagnostic accuracy of each miRNA. Results: Based on the results, hsa-let-7c-5p and hsa-miR-206-5p were downregulated, while hsa-miR-1909-5p was upregulated in glioblastoma tumors compared to healthy samples. No association was detected between the expression of each candidate miRNA and sex. Except for hsa-let-7c-5p, other miRNAs did not correlate with age status. ROC curve analysis indicated that the signature of candidate miRNAs is a potential biomarker distinguishing between glioblastoma and healthy samples. Only hsa-miR-206-5p suggested the association with poor prognosis in glioblastoma patients. Conclusion: Our findings revealed that the signature of three miRNAs is capable of distinguishing glioblastoma tumor and healthy tissues. These results are beneficial for the clinical management of glioblastoma patients.