Abstract

Glioblastoma (GBM) is a malignant tumor. The long-term prognosis of the patients is poor. Therefore, it is of important clinical value to further explore the pathogenesis and look for molecular markers for early diagnosis and targeted treatment. Two expression profiling datasets [GSE50161 (GPL570 platform), GSE116520 (GPL10558 platform)] were respectively downloaded from the gene expression omnibus database. Volcano diagrams show the Differently expressed genes (DEGs) of GSE50161 and GSE116520. A Venn diagram revealed 467 common DEGs between the 2 datasets. Lysyl oxidase (LOX), serpin family H member 1 (SERPINH1) and transforming growth factor beta induced (TGFBI) were negatively correlated with the overall survival rate in patients with GBM. The hub genes are high in GBM tumor tissues. The relative expression levels of LOX, SERPINH1 and TGFBI were significantly higher in GBM samples, compared with the normal brain tissues groups. Bioinformatics technology could be a useful tool to predict progression of GBM and to explore the mechanism of GBM.LOX, SERPINH1 and TGFBI may be involved in the mechanism of the occurrence and development of GBM, and may be used as molecular targets for early diagnosis and specific treatment. DEGs identified using GEO2R. Functional annotation of DEGs using Kyoto Encyclopedia of Genes and Genomes and gene body pathway enrichment analysis. Construction of a protein-protein interaction network. The pathway and process enrichment analysis of the hub genes were performed by Metascape. Survival analysis was performed in gene expression profiling interactive analysis. Real-time fluorescent quantitative polymerase chain reaction assay was performed to verify. The animal model was established for western blot test analysis.

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