Abstract
Background: Glioblastoma is the most common type of malignant brain tumor. Bioinformatics technology and structure biology were effectively and systematically used to identify specific targets in malignant tumors and screen potential drugs.Results: GBM patients have higher AURKA and KDR mRNA expression compared with normal samples. Then, we identified a small molecular compound, ENMD-2076, could effectively inhibit Aurora kinase A and VEGFR-2 (encoded by KDR) activities. ENMD-2076 is predicted without toxic properties and also has absorption and gratifying brain/blood barrier penetration ability. Further results demonstrated that ENMD-2076 could significantly inhibit GBM cell lines proliferation and vitality, it also suppressed GBM cells migration and invasion. ENMD-2076 induced glioblastoma cell cycle arrest in G2-M phase and apoptosis by inhibiting PI3K/AKT/mTOR signaling pathways. Additionally, ENMD-2076 prolonged the median survival time of tumor-bearing rats and restrained growth rate of tumor volume in vivo.Conclusions: Our findings reveal that ENMD-2076 is a promising drug in dealing with glioblastoma and have a perspective application.Methods: We show that AURKA and KDR genes are hub driver genes in glioblastoma with bioinformatics technology including WGCNA analysis, PPI network, GO, KEGG analysis and GSEA analysis. After identifying a compound via virtual screening analysis, further experiments were carried out to examine the anti-glioblastoma activities of the compound in vivo and in vitro.
Highlights
Glioblastoma is the most common type of malignant brain tumor characterized by poor prognosis and direct repercussions on cognitive function
We discovered that Aurora kinase A (AURKA) and Kinase insert domain receptor (KDR) mRNA were significantly overexpressed in GBM samples
12 gene modules were identified from the dataset GSE50161 with Weighted gene co-expression network analysis (WGCNA) analysis
Summary
Glioblastoma is the most common type of malignant brain tumor characterized by poor prognosis and direct repercussions on cognitive function. Owning to overall dismal prognosis and poor life quality of glioblastoma with standard treatment, it is urgent to explore novel treatment and screen effective medication for glioblastoma under better understanding of genetic and molecular biology. Glioblastoma is the most common type of malignant brain tumor. Bioinformatics technology and structure biology were effectively and systematically used to identify specific targets in malignant tumors and screen potential drugs. We identified a small molecular compound, ENMD-2076, could effectively inhibit Aurora kinase A and VEGFR-2 (encoded by KDR) activities. ENMD-2076 prolonged the median survival time of tumorbearing rats and restrained growth rate of tumor volume in vivo. After identifying a compound via virtual screening analysis, further experiments were carried out to examine the antiglioblastoma activities of the compound in vivo and in vitro
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