Expression analysis of human glioma susceptibility gene and P53 in human glioma and its clinical significance based on bioinformatics.

Abstract

The exact mechanism of glioblastoma multiforme (GBM) remains unclear. This study was to clarify the expression of P53 in glioma and its molecular mechanism, and to explore the possibility of P53 as a potential therapeutic target of glioma and its clinical application value, so as to provide a new theoretical basis for the treatment of glioma. Firstly, a dataset was established to analyze the expression of P53 in different stages of glioma and its relationship with prognosis by using The Cancer Genome Atlas (TCGA) database, RNA-seq data, and survival data of glioma and normal control samples in gene expression profiling and interactive analysis (GEPIA). The genes co-expressed with P53 were screened out, their differential expression between glioma and normal control group was analyzed, and their functions were analyzed by enrichment analysis. The TGGA database was used for data verification and analysis. The correlation between P53 expression and clinicopathological parameters was analyzed. Kaplan-Meier survival analysis was used to analyze the relationship between P53 expression and overall survival (OS) and progression-free survival (PFS) of glioma patients, and Cox regression analysis was used to analyze the independent factors affecting OS and PFS of glioma patients. The results of TCGA data analysis were as follows: The expression level of P53 was different from that of different stages of glioma, namely, the expression level of P53 between grade II and grade III, grade III and grade IV, and grade II and grade IV were significantly different (P<0.05). The results of P53 gene-related survival analysis showed that KNL1 high expression and low expression were significantly different in OS, and the high expression group was associated with poor prognosis (P<0.05). The P53 expression can be an effective biological indicator of poor prognosis of glioma.