Abstract
BACKGROUND: Gliomas are common aggressive brain tumors with poor prognosis. Dephosphorylation-related biomarkers are in a void in gliomas. This study aims to construct a validated prognostic risk model for dephosphorylation, which will provide new directions for clinical treatment, prognostic assessment, and temozolomide (TMZ) resistance in glioma patients. METHODS: Screening dephosphorylation-related genes (DRGs) and transcriptome expression data from The Cancer Genome Atlas (TCGA), Molecular signatures database (MSigDB) and constructing risk scoring models. Kaplan-Meier (K-M), nomogram and ROC curve were used to assess the predictive efficacy of the model. Gene set enrichment analysis (GSEA), immune cell infiltration, immunotherapy response and chemotherapeutic drug sensitivity analysis were performed in this study. The correlation between chemotherapeutic drugs and the half maximal inhibitory concentration (IC(50)) values of 12 DRGs was analyzed. Cell division cycle 25A (CDC25A) and TMZ were screened and verified by experiments. Quantitative Real-Time PCR (qRT-PCR) detection of mRNA expression of 12 genes in human normal glial cells and two glioma cell lines. Transfection techniques overexpressed and knocked down CDC25A. qRT-PCR and Western Blot (WB) were used to detect the mRNA and protein expression levels of CDC25A. Subsequently, verify the effect of CDC25A on TMZ resistance in glioma cells. RESULTS: The model established in this study was able to accurately predict the prognosis of glioma patients. Besides, there were significant differences in GSEA, immune cell infiltration, immunotherapeutic response and chemotherapeutic drug sensitivity analysis between glioma patients in the high and low risk groups. The results of CCK8 experiments showed that overexpression of CDC25A increased the susceptibility of U251 and LN229 cells to TMZ, and knockdown of CDC25A attenuated the susceptibility of U251 and LN229 cells to TMZ.