RNA-seq and microarray data were retrieved from the GEO database (http://www.ncbi.nlm.nih.gov/geo/). Microarray data comprised GSE35493 (based on Affymetrix Human Genome U133 Plus 2.0 Array, GPL570) (11 (link)) and GSE39182 (based on Agilent-014850 Whole Human Genome Microarray 4×44K G4112F, GPL6480) (12 (link)). GSE35493 included 21 MB and 9 normal brain samples. GSE39182 included 20 MB and 5 normal samples. In addition, RNA-seq data GSE148389 (based on NextSeq 550, GPL21697) contained 14 normal and 26 tumor tissues (13 (link)). All probes were annotated by annotation files. Data processing was performed using R 3.6.0 software (https://www.r-project.org/). DEGs between MB and normal samples in the GSE35493 and GSE39182 microarray datasets were screened using the Limma package (14 (link)), and GSE148389 RNA-seq data were analyzed using the edgeR package (15 (link)). An adjusted P<0.05 and |log2 fold change (FC)|≥1 were set as thresholds to identify the DEGs. Venn diagrams (http://bioinformatics.psb.ugent.be/webtools/Venn/) were utilized to detect and present the common DEGs among the three datasets.