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基于网络药理学的薏苡仁抗结直肠癌潜在生物学机制分析

Network Pharmacology-Based Analysis of the Potential Biological Mechanisms of Coix Seed against Colorectal Cancer.

作者信息

Sun Yi, Jiang Peishi, Yang Hongjie, Zhang Zhichun, Zhou Yuanda, Li Peng, Zeng Qingsheng, Zhang Xipeng

机构信息

Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin 300121, China.

出版信息

Evid Based Complement Alternat Med. 2022 Oct 6;2022:9261768. doi: 10.1155/2022/9261768. eCollection 2022.

Abstract

OBJECTIVE

The aim of this study was to explore the potential biological mechanisms of coix seed in the treatment of colorectal cancer (CRC) based on network pharmacology analysis.

METHODS

The active components of coix seed and their potential action targets were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP). The disease targets related to CRC were obtained from the DisGeNET database. The intersection targets of the drug targets and disease targets were selected, and a component-target-disease network was built using Cytoscape 3.8.0 tool. A global network of the core target protein interactions was constructed using String database. Biological function analysis and pathway enrichment analysis of core targets were conducted to explore the potential.

RESULTS

A total of nine active components were obtained from the TCMSP database corresponding to 37 targets. Further analysis showed that 18 overlapping targets were associated with CRC. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted based on the 18 targets and 11 significantly enriched signaling pathways implicated in CRC were identified.

CONCLUSION

The multicomponent and multitarget characteristics of coix seed are preliminarily verified, and the potential biological mechanisms of coix seed in the treatment of CRC are predicted, which provides a theoretical basis for the experimental research.

摘要

目的

本研究旨在基于网络药理学分析探索薏苡仁治疗结直肠癌(CRC)的潜在生物学机制。

方法

从中药系统药理学数据库与分析平台(TCMSP)检索薏苡仁的活性成分及其潜在作用靶点。从DisGeNET数据库获取与CRC相关的疾病靶点。选取药物靶点与疾病靶点的交集靶点,使用Cytoscape 3.8.0工具构建成分-靶点-疾病网络。利用String数据库构建核心靶点蛋白相互作用的全局网络。对核心靶点进行生物学功能分析和通路富集分析以探索其潜在机制。

结果

从TCMSP数据库共获得9种活性成分,对应37个靶点。进一步分析表明,18个重叠靶点与CRC相关。基于这18个靶点进行京都基因与基因组百科全书(KEGG)富集分析,确定了11条与CRC相关的显著富集信号通路。

结论

初步验证了薏苡仁的多成分、多靶点特性,预测了薏苡仁治疗CRC的潜在生物学机制,为实验研究提供了理论依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/976c/9560812/aea7aaa4feb0/ECAM2022-9261768.001.jpg

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