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基于网络药理学的黄芩治疗骨肉瘤作用及机制研究。

Network pharmacology-based research on the effect of Scutellaria baicalensis on osteosarcoma and the underlying mechanism.

机构信息

Department of Integrated Traditional and Western Medicine, Union Hospital, Tong ji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

出版信息

Medicine (Baltimore). 2023 Nov 17;102(46):e35957. doi: 10.1097/MD.0000000000035957.

DOI:10.1097/MD.0000000000035957
PMID:37986331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10659624/
Abstract

To explore the anti-tumor effects of Scutellaria baicalensis on osteosarcoma and its mechanism. Network pharmacology and molecular docking techniques were applied to investigate the effect and mechanism of Scutellaria baicalensis on osteosarcoma (OS). We analyzed the protein-protein interaction (PPI) network for potential targets of Scutellaria baicalensis for treating osteosarcoma and identified hub targets. We used KM curves to screen for hub targets that could effectively prolong the survival time of OS patients. We systematically performed gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the Scutellaria baicalensis potential targets and predicted the Scutellaria baicalensis molecular mechanism and function in treating osteosarcoma. Through molecular docking, the binding process between the hub targets, which could prolong the survival time of sarcoma patients, and Scutellaria baicalensis was simulated. PPI network analysis of potential therapeutic targets discriminated 12 hub targets. The KM curves of the hub targets showed that upregulation of RXRA, RELA, ESR1, TNF, IL6, IL1B, and RB1 expression, and downregulation of MAPK1, VEGFA, MAPK14, CDK1, and PPARG expression were effective in improving the 5-year survival rate of OS patients. GO and KEGG enrichment demonstrated that Scutellaria baicalensis regulated multiple signaling pathways of OS. Molecular docking results indicated that Scutellaria baicalensis could bind freely to the above hub target, which could prolong the survival time of sarcoma patients. Scutellaria baicalensis acted on osteosarcoma by regulating a signaling network formed by hub targets connecting multiple signaling pathways. Scutellaria baicalensis appears to have the potential to serve as a therapeutic drug for osteosarcoma and to prolong the survival of OS patients.

摘要

目的

探讨黄芩对骨肉瘤的抗肿瘤作用及其机制。采用网络药理学和分子对接技术研究黄芩治疗骨肉瘤(OS)的作用及机制。我们分析了黄芩治疗骨肉瘤的潜在靶点的蛋白质-蛋白质相互作用(PPI)网络,并鉴定了枢纽靶点。我们使用 KM 曲线筛选出能有效延长 OS 患者生存时间的枢纽靶点。我们系统地对黄芩潜在靶点进行了基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析,预测了黄芩治疗骨肉瘤的分子机制和功能。通过分子对接,模拟了能延长肉瘤患者生存时间的枢纽靶点与黄芩的结合过程。潜在治疗靶点的 PPI 网络分析鉴别出 12 个枢纽靶点。枢纽靶点的 KM 曲线显示,上调 RXRA、RELA、ESR1、TNF、IL6、IL1B 和 RB1 的表达,下调 MAPK1、VEGFA、MAPK14、CDK1 和 PPARG 的表达,可有效提高 OS 患者的 5 年生存率。GO 和 KEGG 富集表明,黄芩调节了 OS 的多个信号通路。分子对接结果表明,黄芩可自由结合上述枢纽靶点,从而延长肉瘤患者的生存时间。黄芩通过调节由枢纽靶点连接多个信号通路形成的信号网络作用于骨肉瘤。黄芩似乎具有作为骨肉瘤治疗药物的潜力,并能延长 OS 患者的生存时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/4d0286880e10/medi-102-e35957-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/3fa0c11b499b/medi-102-e35957-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/83da899e263a/medi-102-e35957-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/4d0286880e10/medi-102-e35957-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/7cd45b175f78/medi-102-e35957-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/e44d3b399ab3/medi-102-e35957-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/df00854461eb/medi-102-e35957-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/ce46389da129/medi-102-e35957-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/a37aa6ec8ee2/medi-102-e35957-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/ad9f0d894e1c/medi-102-e35957-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/3fa0c11b499b/medi-102-e35957-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/83da899e263a/medi-102-e35957-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04ef/10659624/4d0286880e10/medi-102-e35957-g010.jpg

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