Identification of miRNAs as promising biomarkers for diagnosis with combined analysis of mRNA transcriptome using next-generation sequencing in glioblastoma patients

Applying Next Generation Sequencing technique we compared the mRNA expression pattern of tumor tissue sample of 5 GPs and peritumoral region of 5 lower grade (I-II) Glioma patients, serving as control group. To determine the difference on mRNA expresion level between GBM and control cases, we performed cluster analysis on the NGS dataset of 6 replicates for each of the two goups of samples with iDEP 96 software. In order to characterize the extent of up- or downregulation, log2FC values were calculated using the iDEP.96 web tool applying the DESeq2 algorithm. On the base of that 6125 known mRNAs were identified to be differentially expressed using a threshold of false discovery rate (FDR) <0.05 and fold-change> 2 during the analysis. Among them, 2253 mRNAs were upregulated (log2FC > 2) and 3872 mRNAs were downregulated (log2FC < -2) with biological revelance in tissue samples comparing with the control samples. To validate our results obtained by NGS, seven upregulated mRNAs: E2F2, HOXD13, VEGFA, CDC45, AURKB, HOXC10, MYBL2 and seven downregulated mRNAs:FABP6, PRLHR, NEUROD6, CBLN1, HRH3, HCN1, RELN were chosen for RT-qPCR analysis. As the result of that E2F2, HOXD13, VEGFA, CDC45, AURKB, HOXC10, MYBL2 was significantly upregulated while FABP6, PRLHR, NEUROD6, CBLN1, HRH3, HCN1, RELN was significantly downregulated, compared with those in the control samples.