2026/07/26 by Xu Hui, Hui Xu, Quan Fang +6
Biochemistry, Genetics and Molecular Biology · Medicine · #Curcumin's Biomedical Applications #Flavonoids in Medical Research #Silymarin and Mushroom Poisoning
paper · doi:10.2174/0109298673419982260715095639
openalex publication_date 2026/07/26 · openalex created_date 2026/07/30 · openalex updated_date 2026/07/30
INTRODUCTION: Gastric Cancer (GC) is still one of the leading causes of cancer-related deaths worldwide. Curcumin, a natural polyphenol found in turmeric, has been reported to have anti-tumor properties. However, the mechanism by which curcumin acts against GC remains unclear. In this study, we combined approaches such as network pharmacology, GEO microarray analysis, molecular docking and molecular dynamics, bioinformatics, and in vitro experiments to explore the various ways in which curcumin may act on GC. METHODS: Curcumin targets were predicted using TCMSP, SwissTargetPrediction, TargetNet, and PharmMapper, and standardized using UniProt. GC differential genes were derived from GEO GSE54129. Overlapping targets were analyzed using STRING protein-protein interaction networks, with hubs identified using cytoHubba and MCODE. GO and KEGG enrichment analyses were performed to determine significantly enriched biological functions and pathways. Docking and 100-ns Molecular Dynamics (MD) were used to assess binding stability. GEPIA and TCGA validated target expression and immune-correlated gene expression. in vitro, SGC-7901 cells underwent CCK-8, colony formation, wound-healing, and Western blot analysis to evaluate CYP1A2, CYP3A4, and CYP2D6 expression. RESULTS: We identified 439 curcumin targets, 1,619 GC differential genes, and 83 overlaps. Hubs were MMP9, SERPINE1, PLAU, and MMP3. GO terms highlighted responses to chemicals and oxygen-containing compounds, extracellular vesicle processes, and related processes. KEGG pathways included cytochrome P450 metabolism, arachidonic acid metabolism, apoptosis, etc. Docking (Vina) predicted favorable binding poses, with binding energies (kcal/mol) of -7.3 for SERPINE1, -6.8 for MMP3, -6.7 for MMP9, and -5.9 for PLAU. MD supported structural plausibility across all four hubs. GEPIA and TCGA showed higher mRNA levels of these targets in GC and significant associations with neutrophils, macrophages, and dendritic cells. Curcumin reduced SGC-7901 viability in a concentration-dependent manner (IC50 24.4 μM), suppressed colony formation and migration, and increased CYP1A2, CYP3A4, and CYP2D6 expression (P < 0.01). DISCUSSION: Data indicate curcumin targets ECM remodeling and proteolysis via MMP9, MMP3, SERPINE1, and PLAU, and modulates metabolic and inflammatory signaling, including cytochrome P450. Concordance across in silico, bioinformatics, and cell assays supports a multi-target mechanism. Limitations include reliance on a single dataset and cell line, lack of in vivo validation, and curcumin's low bioavailability. CONCLUSION: Curcumin engages MMP9, SERPINE1, PLAU, and MMP3 and regulates cytochrome P450 and inflammation-related pathways, thereby inhibiting GC cell proliferation, clonogenicity, and migration. These findings provide a mechanistic basis for further in vivo and translational studies of curcumin-based strategies in GC.