Catechin is a kind of flavonoids, mainly derived from the plant Camellia sinensis. It has a strong antioxidant effect, and it also has significant therapeutic effects on anti-cancer, anti-diabetes, and anti-infection. This study was intended to look at how catechin affected the malignant biological activity of gastric cancer cells. We used databases to predict the targets of catechin and the pathogenic targets of gastric cancer. Venn diagram was used to find the intersection genes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed on intersection genes. Using the STRING database, the Protein-Protein Interaction (PPI) network was built. The top 8 genes were screened by Cytoscape 3.9.1, then their binding was verified by molecular docking. The proliferation ability, cell cycle, apoptosis and migration of gastric cancer cells were detected, as well as the protein expression levels of PI3K, p-AKT, and AKT and the mRNA expression levels of AKT1, VEGFA, EGFR, HRAS, and HSP90AA1 in gastric cancer cells. Our research revealed that different concentrations of catechin could effectively inhibit the proliferation and migration of gastric cancer cells, regulate the cell cycle, and promote the death of these cells, and it's possible that the PI3K/Akt pathway was crucial in mediating this impact. Moreover, adding the PI3K/Akt pathway agonist significantly reduced the promoting effect of catechin on the apoptosis of gastric cancer cells. This study suggested that catechin was a potential drug for the treatment of gastric cancer.
Keyphrases
- human health
- cell cycle
- signaling pathway
- cell proliferation
- cell cycle arrest
- genome wide
- molecular docking
- protein protein
- pi k akt
- genome wide identification
- induced apoptosis
- oxidative stress
- cell death
- small molecule
- endoplasmic reticulum stress
- bioinformatics analysis
- small cell lung cancer
- epithelial mesenchymal transition
- epidermal growth factor receptor
- dna methylation
- gene expression
- metabolic syndrome
- machine learning
- insulin resistance
- combination therapy
- weight loss
- cell wall
- network analysis