Unraveling the Gut Microbiota-mediated Anti-tumor Mechanisms of ShenXia KuanZhong Decoction in Gastric Cancer: a Systems Biology and Dose-weighted Network Pharmacology Approach.
{"title":"Unraveling the Gut Microbiota-mediated Anti-tumor Mechanisms of ShenXia KuanZhong Decoction in Gastric Cancer: a Systems Biology and Dose-weighted Network Pharmacology Approach.","authors":"Ziyi Zhou, Yuan Fang, Lijie Song, Yuli Wang, Zhihong Fang","doi":"10.1186/s12575-025-00304-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Gastric cancer (GC) remains a formidable global health issue with limited therapeutic options. ShenXia KuanZhong Decoction (SXKZD), a classical traditional Chinese medicine (TCM) formula, is used to manage GC; however, its anti-tumor mechanisms remain poorly understood.</p><p><strong>Material and methods: </strong>The anti-GC effects of SXKZD were investigated in a GC model using dose-weighted network pharmacology, molecular docking, molecular dynamics (MD) simulations, and pharmacokinetic profiling. Its impacts on tumor metabolism, immunity, and gut microbiota were assessed. A gut microbiota-substrate-metabolite (GM-S-M) network was constructed, and key targets and pathways were analyzed using computational and experimental methods.</p><p><strong>Results: </strong>SXKZD treatment significantly alleviated tumor progression in GC models. Network analysis revealed upregulated TNF and IL6 expression in GC, which SXKZD reduced, alongside enrichment in IL-17 and TNF signaling pathways. Molecular docking and MD simulations confirmed stable binding of Ginsenoside Rh2 and 3-Indolepropionic acid to TNF, with binding energies of -147.63 kJ/mol and - 98.63 kJ/mol, respectively. Pharmacokinetic profiling showed 3-Indolepropionic acid's high bioavailability, while GM-S-M analysis identified key microbial taxa (e.g., Lactobacillus plantarum, Akkermansia muciniphila) modulated by SXKZD, enhancing anti-tumor immunity and metabolism.To further confirm these computational predictions, in vitro CCK-8 assays revealed that GRh2 and IPA inhibited AGS cell growth in a concentration-dependent manner, with IC<sub>50</sub> values of 68.74 ± 1.27 µg/mL and 780.60 ± 24.40 µg/mL at 24 hours, respectively. Western blot analysis demonstrated that GRh2 more effectively suppressed TNFα expression, whereas CETSA showed that IPA provided superior thermal stabilization of TNFα.</p><p><strong>Conclusions: </strong>SXKZD mitigates GC by modulating gut microbiota and inhibiting TNF signaling, offering a mechanistic basis for its therapeutic potential in GC management.</p>","PeriodicalId":8960,"journal":{"name":"Biological Procedures Online","volume":"27 1","pages":"41"},"PeriodicalIF":4.9000,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12533430/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Procedures Online","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s12575-025-00304-2","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Gastric cancer (GC) remains a formidable global health issue with limited therapeutic options. ShenXia KuanZhong Decoction (SXKZD), a classical traditional Chinese medicine (TCM) formula, is used to manage GC; however, its anti-tumor mechanisms remain poorly understood.
Material and methods: The anti-GC effects of SXKZD were investigated in a GC model using dose-weighted network pharmacology, molecular docking, molecular dynamics (MD) simulations, and pharmacokinetic profiling. Its impacts on tumor metabolism, immunity, and gut microbiota were assessed. A gut microbiota-substrate-metabolite (GM-S-M) network was constructed, and key targets and pathways were analyzed using computational and experimental methods.
Results: SXKZD treatment significantly alleviated tumor progression in GC models. Network analysis revealed upregulated TNF and IL6 expression in GC, which SXKZD reduced, alongside enrichment in IL-17 and TNF signaling pathways. Molecular docking and MD simulations confirmed stable binding of Ginsenoside Rh2 and 3-Indolepropionic acid to TNF, with binding energies of -147.63 kJ/mol and - 98.63 kJ/mol, respectively. Pharmacokinetic profiling showed 3-Indolepropionic acid's high bioavailability, while GM-S-M analysis identified key microbial taxa (e.g., Lactobacillus plantarum, Akkermansia muciniphila) modulated by SXKZD, enhancing anti-tumor immunity and metabolism.To further confirm these computational predictions, in vitro CCK-8 assays revealed that GRh2 and IPA inhibited AGS cell growth in a concentration-dependent manner, with IC50 values of 68.74 ± 1.27 µg/mL and 780.60 ± 24.40 µg/mL at 24 hours, respectively. Western blot analysis demonstrated that GRh2 more effectively suppressed TNFα expression, whereas CETSA showed that IPA provided superior thermal stabilization of TNFα.
Conclusions: SXKZD mitigates GC by modulating gut microbiota and inhibiting TNF signaling, offering a mechanistic basis for its therapeutic potential in GC management.
期刊介绍:
iological Procedures Online publishes articles that improve access to techniques and methods in the medical and biological sciences.
We are also interested in short but important research discoveries, such as new animal disease models.
Topics of interest include, but are not limited to:
Reports of new research techniques and applications of existing techniques
Technical analyses of research techniques and published reports
Validity analyses of research methods and approaches to judging the validity of research reports
Application of common research methods
Reviews of existing techniques
Novel/important product information
Biological Procedures Online places emphasis on multidisciplinary approaches that integrate methodologies from medicine, biology, chemistry, imaging, engineering, bioinformatics, computer science, and systems analysis.