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A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis

PURPOSE: Xiang-Sha-Liu-Jun-Zi-Tang(XSLJZT) is a common formula for the treatment of Gastric Cancer(GC) and is widely used in clinical practice, however, there is a lack of investigation into its mechanism. METHODS: We collected and organized drug and disease targets, constructed the “XSLJZT-Active I...

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Autores principales: Jiang, Ke, Liu, Heli, Ge, Jie, Yang, Bo, Wang, Yu, Wang, Wenbo, Wen, Yuqi, Zeng, Siqing, Chen, Quan, Huang, Jun, Xiong, Xingui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558807/
https://www.ncbi.nlm.nih.gov/pubmed/37809372
http://dx.doi.org/10.1016/j.heliyon.2023.e19546
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author Jiang, Ke
Liu, Heli
Ge, Jie
Yang, Bo
Wang, Yu
Wang, Wenbo
Wen, Yuqi
Zeng, Siqing
Chen, Quan
Huang, Jun
Xiong, Xingui
author_facet Jiang, Ke
Liu, Heli
Ge, Jie
Yang, Bo
Wang, Yu
Wang, Wenbo
Wen, Yuqi
Zeng, Siqing
Chen, Quan
Huang, Jun
Xiong, Xingui
author_sort Jiang, Ke
collection PubMed
description PURPOSE: Xiang-Sha-Liu-Jun-Zi-Tang(XSLJZT) is a common formula for the treatment of Gastric Cancer(GC) and is widely used in clinical practice, however, there is a lack of investigation into its mechanism. METHODS: We collected and organized drug and disease targets, constructed the “XSLJZT-Active Ingredient-Target” visualization network, and performed GO and KEGG functional enrichment analysis of crossover genes, followed by molecular docking of active ingredients and core targets. The best docked monomers were combined with weighted gene co-expression network analysis(WGCNA) and macroscopically analyzed by GO and KEGG enrichment techniques. The results of cluster gene difference analysis, ROC evaluation, and CIBERSORT immune infiltration analysis were evaluated and finally supported by cellular experiments. RESULTS: The main components of XSLJZT are quercetin, stigmasterol, and naringenin, effectively treat GC by targeting STAT3, TP53 and MAPK3, which are involved in IL-17, TNF and HIF-1 signaling pathways. The results of molecular docking showed that quercetin bound better to the core targets. We performed an in-depth analysis of this monomer and found that quercetin acts on the core targets of TP53, MMP9, TIMP1 and MYC, and is involved in two key signaling pathways, TNF and IL-17, thus effectively treating GC. The experimental results are consistent with our analysis that quercetin inhibits the proliferation of GC cells and promotes apoptosis, and TP53, MYC and TIMP1 are the quercetin targets for the treatment of GC. CONCLUSION: The present study tentatively suggests that quercetin, the main active ingredient in XSLJZT, can exert a therapeutic effect on GC by targeting TIMP1.
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spelling pubmed-105588072023-10-08 A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis Jiang, Ke Liu, Heli Ge, Jie Yang, Bo Wang, Yu Wang, Wenbo Wen, Yuqi Zeng, Siqing Chen, Quan Huang, Jun Xiong, Xingui Heliyon Research Article PURPOSE: Xiang-Sha-Liu-Jun-Zi-Tang(XSLJZT) is a common formula for the treatment of Gastric Cancer(GC) and is widely used in clinical practice, however, there is a lack of investigation into its mechanism. METHODS: We collected and organized drug and disease targets, constructed the “XSLJZT-Active Ingredient-Target” visualization network, and performed GO and KEGG functional enrichment analysis of crossover genes, followed by molecular docking of active ingredients and core targets. The best docked monomers were combined with weighted gene co-expression network analysis(WGCNA) and macroscopically analyzed by GO and KEGG enrichment techniques. The results of cluster gene difference analysis, ROC evaluation, and CIBERSORT immune infiltration analysis were evaluated and finally supported by cellular experiments. RESULTS: The main components of XSLJZT are quercetin, stigmasterol, and naringenin, effectively treat GC by targeting STAT3, TP53 and MAPK3, which are involved in IL-17, TNF and HIF-1 signaling pathways. The results of molecular docking showed that quercetin bound better to the core targets. We performed an in-depth analysis of this monomer and found that quercetin acts on the core targets of TP53, MMP9, TIMP1 and MYC, and is involved in two key signaling pathways, TNF and IL-17, thus effectively treating GC. The experimental results are consistent with our analysis that quercetin inhibits the proliferation of GC cells and promotes apoptosis, and TP53, MYC and TIMP1 are the quercetin targets for the treatment of GC. CONCLUSION: The present study tentatively suggests that quercetin, the main active ingredient in XSLJZT, can exert a therapeutic effect on GC by targeting TIMP1. Elsevier 2023-08-28 /pmc/articles/PMC10558807/ /pubmed/37809372 http://dx.doi.org/10.1016/j.heliyon.2023.e19546 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Jiang, Ke
Liu, Heli
Ge, Jie
Yang, Bo
Wang, Yu
Wang, Wenbo
Wen, Yuqi
Zeng, Siqing
Chen, Quan
Huang, Jun
Xiong, Xingui
A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title_full A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title_fullStr A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title_full_unstemmed A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title_short A study related to the treatment of gastric cancer with Xiang-Sha-Liu-Jun-Zi-Tang based on network analysis
title_sort study related to the treatment of gastric cancer with xiang-sha-liu-jun-zi-tang based on network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10558807/
https://www.ncbi.nlm.nih.gov/pubmed/37809372
http://dx.doi.org/10.1016/j.heliyon.2023.e19546
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