To Explore the Inhibitory Mechanism of Quercetin in Thyroid Papillary Carcinoma through Network Pharmacology and Experiments.
Ying SunWenjun XieNing KangJiaoyu YiXianhui RuanLinfei HuJingzhu ZhaoXiangqian ZhengSongfeng WeiMing GaoPublished in: Disease markers (2022)
Quercetin, a flavonoid with anti-inflammatory and anticancer properties, is expected to be an innovative anticancer therapeutic agent for papillary thyroid carcinoma (PTC). However, the downstream signaling pathways that mediate quercetin-dependent anticancer properties remain to be deciphered. Herein, potential targets of quercetin were screened with several bioinformatic avenues including PharmMapper, Gene Expression Omnibus (GEO) database, protein-protein interaction (PPI) network, and molecular docking. Besides, western blot, CCK-8 transwell analysis of migration and invasion, flow cytometric analysis, and colony formation assays were performed to investigate the underlying mechanism. We found four core nodes (MMP9, JUN, SPP1, and HMOX1) by constructing a PPI network with 23 common targets. Through functional enrichment analysis, we confirmed that the above four target genes are enriched in the TNF, PI3K-AKT, and NF- κ B signaling pathways, which are involved in the inflammatory microenvironment and inhibit the development and progression of tumors. Furthermore, molecular docking results demonstrated that quercetin shows strong binding efficiency with the proteins encoded by these 4 key proteins. Finally, quercetin displayed strong antitumor efficacy in PTC cell lines. In this research, we demonstrated the application of network pharmacology in evaluating the mechanisms of action and molecular targets of quercetin, which regulates a variety of proteins and signaling pathways in PTC. These data might explain the mechanism underlying the anticancer effects of quercetin in PTC.
Keyphrases
- molecular docking
- signaling pathway
- pi k akt
- protein protein
- gene expression
- molecular dynamics simulations
- small molecule
- cell proliferation
- stem cells
- lymph node
- squamous cell carcinoma
- cell cycle arrest
- epithelial mesenchymal transition
- machine learning
- immune response
- dna methylation
- risk assessment
- induced apoptosis
- network analysis
- high throughput
- lps induced
- south africa
- toll like receptor
- inflammatory response