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通过基因共表达网络和分子对接分析筛选出的ENMD-2076对荷胶质母细胞瘤大鼠具有高效性。

Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats.

作者信息

Zhong Sheng, Bai Yang, Wu Bo, Ge Junliang, Jiang Shanshan, Li Weihang, Wang Xinhui, Ren Junan, Xu Haiyang, Chen Yong, Zhao Gang

机构信息

Department of Neurosurgery, The First Hospital of Jilin University, Changchun, China.

Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

出版信息

Aging (Albany NY). 2019 Nov 9;11(21):9738-9766. doi: 10.18632/aging.102422.

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 .

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 and .

摘要

背景

胶质母细胞瘤是最常见的恶性脑肿瘤类型。生物信息学技术和结构生物学被有效且系统地用于识别恶性肿瘤中的特定靶点并筛选潜在药物。

结果

与正常样本相比,胶质母细胞瘤患者的AURKA和KDR mRNA表达更高。然后,我们鉴定出一种小分子化合物ENMD-2076,它能有效抑制极光激酶A和VEGFR-2(由KDR编码)的活性。ENMD-2076预计无毒性,并且具有吸收性和令人满意的血脑屏障穿透能力。进一步的结果表明,ENMD-2076能显著抑制胶质母细胞瘤细胞系的增殖和活力,还能抑制胶质母细胞瘤细胞的迁移和侵袭。ENMD-2076通过抑制PI3K/AKT/mTOR信号通路诱导胶质母细胞瘤细胞周期停滞在G2-M期并诱导凋亡。此外,ENMD-2076延长了荷瘤大鼠的中位生存时间并抑制了肿瘤体积的生长速率。

结论

我们的研究结果表明,ENMD-2076是一种有前景的治疗胶质母细胞瘤的药物,具有应用前景。

方法

我们通过包括WGCNA分析、PPI网络、GO、KEGG分析和GSEA分析在内的生物信息学技术表明,AURKA和KDR基因是胶质母细胞瘤中的关键驱动基因。通过虚拟筛选分析鉴定出一种化合物后,进行了进一步的实验以检测该化合物的抗胶质母细胞瘤活性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e7a/6874459/4eea9d6ce6f1/aging-11-102422-g001.jpg

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