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Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
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 expres...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874459/ https://www.ncbi.nlm.nih.gov/pubmed/31706255 http://dx.doi.org/10.18632/aging.102422 |
Sumario: | 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. |
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