通过网络药理学和实验验证,探索六味地黄煎剂在前列腺癌中的作用和潜在机制。

IF 3.3 2区 医学 Q1 INTEGRATIVE & COMPLEMENTARY MEDICINE
Xiangyang Zhan, Haoze Li, Jingyun Jin, Xiran Ju, Jiawei Gao, Xinglin Chen, Fuwen Yuan, Jianyi Gu, DongLiang Xu, Guanqun Ju
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引用次数: 0

摘要

目的采用实验验证、网络药理学、生物信息学分析和分子对接等方法,评价六味地黄汤(LWDHD)对前列腺癌(PCa)的抗肿瘤作用机制:方法:采用CCK试验、克隆形成试验和伤口愈合试验确定龙胆泻肝汤对前列腺癌生长和转移的影响。从 TCMSP 数据库中获取 LWDHD 的有效成分和靶点,并从 PCa 的 GeneCards、OMIM 和 DisGeNET 数据库中筛选出相关靶点。将药物与疾病的交叉靶点导入 STRING 数据库,构建蛋白质相互作用网络。还使用 Cytoscape 软件将网络可视化,并使用网络分析器插件筛选核心靶点。使用 R 软件分析了基因本体(GO)和京都基因组百科全书(KEGG)通路富集。TCGA 数据库用于分析生物信息学基因的相关性。使用 AutoDock vina 预测活性成分与关键靶点的分子对接和结合能力。通过WB和q-PCR实验检测上述基因靶点,以验证LWDHD对PCa的作用:结果:CCK和划痕实验证实,LWDHD能抑制前列腺癌细胞的增殖、侵袭和迁移。克隆形成实验表明,LWDHD 可抑制 PC3 细胞的长期增殖能力。LWDHD与PCa共有99个共同靶点,建立了 "药物-成分-共同靶点 "网络。通过GO和KEGG富集分析,发现了PI3K/AKT、MAPK、TP53通路、MYC、TNF通路等信号通路。生物信息学分析表明,前列腺癌组织中 MYC 基因高表达,CCND1 和 MAPK1 低表达。此外,TP53、AKT1、MYC、TNF和CCND1与MAPK1呈正相关,其中AKT1和CCND1与MAPK1的关系最为密切。分子对接结果显示,槲皮素、山柰醇、β-谷甾醇等治疗 PCa 的主要活性成分与核心蛋白 MAPK1 和 AKT1 结合良好。WB和q-PCR结果显示,LWDHD抑制了PC3细胞中PI3K和AKT的表达:LWDHD治疗PCa的机制是一个多靶点、多通路的复杂过程,可能与MAPK1和AKT1通路介导的细胞增殖、抑制转移等生物学过程以及信号通路的调控有关。PI3K/AKT 信号通路可能是 LWDHD 抑制前列腺癌增殖的核心通路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network pharmacology and experimental validation to explore the role and potential mechanism of Liuwei Dihuang Decoction in prostate cancer.

Objective: To evaluate the anti-tumor effector of Liuwei Dihuang Decoction (LWDHD) in prostate cancer (PCa) and explore the potential mechanism using experimental validation, network pharmacology, bioinformatics analysis, and molecular docking.

Methods: CCK test, Clone formation assay and wound-healing assays were used to determine the effect of LWDHD on prostate cancer growth and metastasis. The active ingredients and targets of LWDHD were obtained from the TCMSP database, and the relevant targets were selected by GeneCards, OMIM and DisGeNET databases for PCa. The cross-targets of drugs and disease were imported into the STRING database to construct protein interactions. The network was also visualized using Cytoscape software and core targets are screened using the Network Analyzer plug-in. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using R software. TCGA database was used to analyze the correlation of bioinformatics genes. AutoDock vina was used to predict the molecular docking and binding ability of active ingredients to key targets. Through WB and q-PCR experiments, the above gene targets were detected to verify the effect of LWDHD on PCa.

Results: CCK and scratch tests confirmed that LWDHD could inhibit the proliferation, invasion and migration of prostate cancer cells. Clone formation experiments showed that LWDHD inhibited the long-term proliferative capacity of PC3 cells. LWDHD and PCa had a total of 99 common targets, establishing a "drug-ingredient-common target" network. Through GO and KEGG enrichment analysis, PI3K/AKT, MAPK, TP53 pathway, MYC, TNF pathway and other signaling pathways were found. Bioinformatics analysis showed that MYC gene was highly expressed and CCND1 and MAPK1 were low expressed in prostate cancer tissues. In addition, TP53, AKT1, MYC, TNF and CCND1 were positively correlated with MAPK1, among which AKT1 and CCND1 were most closely correlated with MAPK1. Molecular docking results showed that quercetin, kaempferol, β-sitosterol and other main active ingredients of LWDHD treatment for PCa were combined with core proteins MAPK1 and AKT1 well. WB and q-PCR results showed that LWDHD inhibited the expression of PI3K and AKT in PC3 cells.

Conclusion: The mechanism of LWDHD therapy for PCa is a multi-target and multi-pathway complex process, which may be related to the biological processes mediated by MAPK1 and AKT1 pathways, such as cell proliferation and inhibition of metastasis, and the regulation of signaling pathways. The PI3K/AKT signaling pathway may be a central pathway of LWDHD to inhibit prostate cancer proliferation.

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来源期刊
BMC Complementary Medicine and Therapies
BMC Complementary Medicine and Therapies INTEGRATIVE & COMPLEMENTARY MEDICINE-
CiteScore
6.10
自引率
2.60%
发文量
300
审稿时长
19 weeks
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