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基于网络药理学和医学图像的曲妥珠单抗在乳腺癌中的差异基因分析

Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images.

作者信息

Lu Yuan, Bi Juan, Li Fei, Wang Gang, Zhu Junjie, Jin Jiqing, Liu Yueyun

机构信息

Shanghai Eighth People's Hospital, Shanghai, China.

Department of Pharmacy, First Affiliated Hospital, Naval Medical University, Shanghai, China.

出版信息

Front Physiol. 2022 Jul 8;13:942049. doi: 10.3389/fphys.2022.942049. eCollection 2022.

Abstract

The purpose of this study was to use network pharmacology, biomedical images and molecular docking technology in the treatment of breast cancer to investigate the feasible therapeutic targets and mechanisms of trastuzumab. In the first place, we applied pubchem swisstarget (http://www.swisstargetprediction.ch/), (https://pubchem.ncbi.nlm.nih.gov/) pharmmapper (http://lilab-ecust.cn/pharmmapper/), and the batman-tcm (http://bionet.ncpsb.org.cn/batman-tcm/) database to collect the trastuzumab targets. Then, in NCBI-GEO, breast cancer target genes were chosen (https://www.ncbi.nlm.nih.gov/geo/). The intersection regions of drug and disease target genes were used to draw a Venn diagram. Through Cytoscape 3.7.2 software, and the STRING database, we then formed a protein-protein interaction (PPI) network. Besides, we concluded KEGG pathway analysis and Geen Ontology analysis by using ClueGO in Cytospace. Finally, the top 5 target proteins in the PPI network to dock with trastuzumab were selected. After screening trastuzumab and breast cancer in databases separately, we got 521 target genes of the drug and 1,464 target genes of breast cancer. The number of overlapping genes was 54. PPI network core genes include GAPDH, MMP9, CCNA2, RRM2, CHEK1, etc. GO analysis indicated that trastuzumab treats breast cancer through abundant biological processes, especially positive regulation of phospholipase activity, linoleic acid metabolic process, and negative regulation of endothelial cell proliferation. The molecular function is NADP binding and the cellular component is tertiary granule lumen. The results of KEGG enrichment analysis exhibited four pathways related to the formation and cure of breast cancer, containing Drug metabolism, Glutathione metabolism, Pyrimidine metabolism and PPAR signaling pathway. Molecular docking showed that trastuzumab has good binding abilities with five core target proteins (GAPDH, MMP9, CCNA2, RRM2, CHEK1). This study, through network pharmacology and molecular docking, provides new pieces of evidence and ideas to understand how trastuzumab treats breast cancer at the gene level.

摘要

本研究的目的是利用网络药理学、生物医学图像和分子对接技术来研究曲妥珠单抗治疗乳腺癌的可行治疗靶点及机制。首先,我们应用pubchem swisstarget(http://www.swisstargetprediction.ch/)、(https://pubchem.ncbi.nlm.nih.gov/)pharmmapper(http://lilab-ecust.cn/pharmmapper/)以及batman-tcm(http://bionet.ncpsb.org.cn/batman-tcm/)数据库来收集曲妥珠单抗的靶点。然后,在NCBI-GEO中选择乳腺癌靶基因(https://www.ncbi.nlm.nih.gov/geo/)。利用药物和疾病靶基因的交集区域绘制维恩图。通过Cytoscape 3.7.2软件以及STRING数据库,我们构建了一个蛋白质-蛋白质相互作用(PPI)网络。此外,我们在Cytospace中使用ClueGO进行KEGG通路分析和基因本体分析。最后,选择PPI网络中与曲妥珠单抗对接的前5个靶蛋白。分别在数据库中筛选曲妥珠单抗和乳腺癌后,我们得到了该药物的521个靶基因和乳腺癌的1464个靶基因。重叠基因的数量为54个。PPI网络核心基因包括GAPDH、MMP9、CCNA2、RRM2、CHEK1等。基因本体分析表明,曲妥珠单抗通过丰富的生物学过程治疗乳腺癌,尤其是磷脂酶活性的正调控、亚油酸代谢过程以及内皮细胞增殖的负调控。分子功能是NADP结合,细胞成分是三级颗粒腔。KEGG富集分析结果显示有四条与乳腺癌形成和治疗相关的通路,包括药物代谢、谷胱甘肽代谢、嘧啶代谢和PPAR信号通路。分子对接表明曲妥珠单抗与五个核心靶蛋白(GAPDH、MMP9、CCNA2、RRM2、CHEK1)具有良好的结合能力。本研究通过网络药理学和分子对接,为从基因水平理解曲妥珠单抗治疗乳腺癌提供了新的证据和思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e81/9304584/99efdad3ac4c/fphys-13-942049-g001.jpg

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