Hence, we conducted the present bioinformatics study to detect the expression levels of MEG3 in gliomas using Oncomine and “Tumor Immune Estimation Resource (TIMER)” databases, analyze CNV using GSCALite database, and analyze its prognostic significance using PrognoScan and “Gene Expression Profiling Interactive Analysis (GEPIA)” databases. Here, MEG3 is linked to neoplasm.