The subclassification of glioblastoma (GBM) into clinically relevant subtypes using microRNA (miRNA)- and messenger RNA (mRNA)-based integrated analysis has been attempted. Because miRNAs regulate multiple gene-signaling pathways, understanding miRNA-mRNA interactions is a prerequisite for understanding glioma biology. However, such associations have not been thoroughly examined using high-throughput integrated analysis. To identify significant miRNA-mRNA correlations, we selected and quantified signature miRNAs and mRNAs in 82 gliomas (grade II: 14, III: 16, IV: 52) using real-time reverse-transcriptase polymerase chain reaction. Quantitative expression data were integrated into a single analysis platform that evaluated the expression relationship between miRNAs and mRNAs. The 21 miRNAs include miR-15b, -21, -34a, -105, -124a, -128a, -135b, -184, -196a-b, -200a-c, -203, -302a-d, -363, -367, and -504. In addition, we examined 23 genes, including proneural markers (DLL3, BCAN, and OLIG2), mesenchymal markers (YKL-40, CD44, and Vimentin), cancer stem cell-related markers, and receptor tyrosine kinase genes. Primary GBM was characterized exclusively by upregulation of mesenchymal markers, whereas secondary GBM was characterized by significant downregulation of mesenchymal markers, miR-21, and -34a, and by upregulation of proneural markers and miR-504. Statistical analysis showed that expression of miR-128a, -504, -124a, and -184 each negatively correlated with the expression of mesenchymal markers in GBM. Our functional analysis of miR-128a and -504 as inhibitors demonstrated that suppression of miR-128a and -504 increased the expression of mesenchymal markers in glioblastoma cell lines. Mesenchymal signaling in GBM may be negatively regulated by miR-128a and -504.
All Science Journal Classification (ASJC) codes
- Clinical Neurology
- Cancer Research