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Network Pharmacology-Based Approach to Investigate the Mechanisms of Piwei-Peiyuan Decoction in the Treatment of Gastric Carcinoma

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Abstract Purpose Piwei-Peiyuan Decoction is a traditional Chinese medicine decoction, which has shown promising treatment in gastric carcinoma. However, the molecular mechanisms of gastric carcinoma (GC) have not been systematically revealed yet. In this work, a network pharmacology research was conducted to analyze mechanisms of Piwei-Peiyuan Decoction, aiming to provide a basis for the development and application of new drugs in treatment of GC. Methods In this study, a network pharmacology approach was used to predict targets, construct network maps and analyze relevant signaling pathways. We discovered active chemical ingredients and their targets in the Piwei-Peiyuan Decoction by the TCMSP and ADME database. Then we found main targets of GC by GeneCards (https://www.genecards.org), OMIM (http://www.omim.org) and DRUGBANK (https://go.drugbank.com) databases. According to the information of ingredients and GC, a PPI network was performed by the String (https://string-db.org) database. And a targets-pathways interaction network was constructed by Cytoscape (version 3.7.2), a bioinformatics software used for data visualization and integration. Results Our result indicated that the main active ingredients of Piwei-Peiyuan Decoction in treating GC are Isorhamnetin, Kaempferol, Quercetin and Luteolin, and main active targets are CASP-3, MAPK1, MYC, AKT1, P53. We found the mechanism of Piwei-Peiyuan Decoction for treating GC is mainly to regulate PI3K-Akt signaling pathway, MAPK signaling pathway, Ras signaling pathway, IL-17 signaling pathway, HIF-1α signaling pathway to inhibit cell proliferation, promote apoptosis and then exert anti-cancer effects. Conclusion This study preliminarily analyzed the multi-component, multi-target and multi-path mechanism of Peiwei-Peiyuan Decoction in the treatment of gastric carcinoma, providing a theoretical basis for its clinical application.
Title: Network Pharmacology-Based Approach to Investigate the Mechanisms of Piwei-Peiyuan Decoction in the Treatment of Gastric Carcinoma
Description:
Abstract Purpose Piwei-Peiyuan Decoction is a traditional Chinese medicine decoction, which has shown promising treatment in gastric carcinoma.
However, the molecular mechanisms of gastric carcinoma (GC) have not been systematically revealed yet.
In this work, a network pharmacology research was conducted to analyze mechanisms of Piwei-Peiyuan Decoction, aiming to provide a basis for the development and application of new drugs in treatment of GC.
Methods In this study, a network pharmacology approach was used to predict targets, construct network maps and analyze relevant signaling pathways.
We discovered active chemical ingredients and their targets in the Piwei-Peiyuan Decoction by the TCMSP and ADME database.
Then we found main targets of GC by GeneCards (https://www.
genecards.
org), OMIM (http://www.
omim.
org) and DRUGBANK (https://go.
drugbank.
com) databases.
According to the information of ingredients and GC, a PPI network was performed by the String (https://string-db.
org) database.
And a targets-pathways interaction network was constructed by Cytoscape (version 3.
7.
2), a bioinformatics software used for data visualization and integration.
Results Our result indicated that the main active ingredients of Piwei-Peiyuan Decoction in treating GC are Isorhamnetin, Kaempferol, Quercetin and Luteolin, and main active targets are CASP-3, MAPK1, MYC, AKT1, P53.
We found the mechanism of Piwei-Peiyuan Decoction for treating GC is mainly to regulate PI3K-Akt signaling pathway, MAPK signaling pathway, Ras signaling pathway, IL-17 signaling pathway, HIF-1α signaling pathway to inhibit cell proliferation, promote apoptosis and then exert anti-cancer effects.
Conclusion This study preliminarily analyzed the multi-component, multi-target and multi-path mechanism of Peiwei-Peiyuan Decoction in the treatment of gastric carcinoma, providing a theoretical basis for its clinical application.

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