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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...

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Autores principales: Zhong, Sheng, Bai, Yang, Wu, Bo, Ge, Junliang, Jiang, Shanshan, Li, Weihang, Wang, Xinhui, Ren, Junan, Xu, Haiyang, Chen, Yong, Zhao, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2019
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
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author Zhong, Sheng
Bai, Yang
Wu, Bo
Ge, Junliang
Jiang, Shanshan
Li, Weihang
Wang, Xinhui
Ren, Junan
Xu, Haiyang
Chen, Yong
Zhao, Gang
author_facet Zhong, Sheng
Bai, Yang
Wu, Bo
Ge, Junliang
Jiang, Shanshan
Li, Weihang
Wang, Xinhui
Ren, Junan
Xu, Haiyang
Chen, Yong
Zhao, Gang
author_sort Zhong, Sheng
collection PubMed
description 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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spelling pubmed-68744592019-12-03 Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats Zhong, Sheng Bai, Yang Wu, Bo Ge, Junliang Jiang, Shanshan Li, Weihang Wang, Xinhui Ren, Junan Xu, Haiyang Chen, Yong Zhao, Gang Aging (Albany NY) Research Paper 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. Impact Journals 2019-11-09 /pmc/articles/PMC6874459/ /pubmed/31706255 http://dx.doi.org/10.18632/aging.102422 Text en Copyright © 2019 Zhong et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Zhong, Sheng
Bai, Yang
Wu, Bo
Ge, Junliang
Jiang, Shanshan
Li, Weihang
Wang, Xinhui
Ren, Junan
Xu, Haiyang
Chen, Yong
Zhao, Gang
Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title_full Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title_fullStr Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title_full_unstemmed Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title_short Selected by gene co-expression network and molecular docking analyses, ENMD-2076 is highly effective in glioblastoma-bearing rats
title_sort selected by gene co-expression network and molecular docking analyses, enmd-2076 is highly effective in glioblastoma-bearing rats
topic Research Paper
url 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
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