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To Explore the Inhibitory Mechanism of Quercetin in Thyroid Papillary Carcinoma through Network Pharmacology and Experiments.

ABSTRACT: 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-κB 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.

SUBMITTER: Sun Y

PROVIDER: S-EPMC9741536 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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To Explore the Inhibitory Mechanism of Quercetin in Thyroid Papillary Carcinoma through Network Pharmacology and Experiments.

Sun Ying Y Xie Wenjun W Kang Ning N Yi Jiaoyu J Ruan Xianhui X Hu Linfei L Zhao Jingzhu J Zheng Xiangqian X Wei Songfeng S Gao Ming M

Disease markers 20221203

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 molecu ...[more]

PMID: 36510497

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Project description:The aim of the study was to investigated the mechanism of Strychnos nux-vomica L. (Semen Strychni, SS) against papillary carcinoma thyroid (PTC) by combined of network pharmacology and experimental verification. By searching the TCMSP, SEA and SwissTarget Prediction database, the main active ingredients and related targets were obtained. Utilizing Venny 2.1.0 String database and Cytoscape 3.7.2 to screened the intersection target and constructed protein-protein interaction (PPI) network diagram. Using R 4.0.4 software carried out the enrichment analysis of GO and KEGG. HPLC was carried out using LC-20A modular HPLC system to identify the bioactive compound brucine present in SS. Molecular docking was performed using Discovery 2019 software. The inhibition rate was detected by CCK8 method. Western blot was used to detect the expression levels of brucine anti-PTC related pathway proteins. 14 active components were screened out, of which 4 main components showed tight relationship with PTC. SS may play the anti-PTC role by acting on two main pathways (TNF signaling pathway and MAPK signaling pathway) and mediating various biological functions. HPLC analysis revealed that brucine was a suitable marker for standardization of the SS. 4 active components exhibit strong binding energy with core protein. Brucine could significantly reduce the activity of BCPAP cells compared with isobrucine, stigmasterol, (+)-catechin. Brucine may reduce the protein expression levels of IL-6, VEGFA, JUN, TP53, 1L1B, PTGS2, BCL2, CASP3, CASP8, and CASP9 while increase the protein expression levels of BAD, cleaved-CASP3, cleaved-CASP8, and cleaved-CASP9 in BCPAP cells, respectively. The active components of SS against PTC mainly include isobrucine, stigmasterol, (+)-catechin, brucine. Among them, brucine exhibits the strongest anti-PTC activity in BCPAP cells, which may reduce the PTC-related protein expression levels. Therefore, SS may exhibits the anti-PTC activities through multiple targets and pathways.

Project description:BackgroundWith fast rising incidence, papillary thyroid carcinoma (PTC) is the most common head and neck cancer. Parthenolide, isolated from traditional Chinese medicine, inhibits various cancer cells, including PTC cells. The aim was to investigate the lipid profile and lipid changes of PTC cells when treated with parthenolide.MethodsComprehensive lipidomic analysis of parthenolide treated PTC cells was conducted using a UHPLC/Q-TOF-MS platform, and the changed lipid profile and specific altered lipid species were explored. Network pharmacology and molecular docking were performed to show the associations among parthenolide, changed lipid species, and potential target genes.ResultsWith high stability and reproducibility, a total of 34 lipid classes and 1736 lipid species were identified. Lipid class analysis indicated that parthenolide treated PTC cells contained higher levels of fatty acid (FA), cholesterol ester (ChE), simple glc series 3 (CerG3) and lysophosphatidylglycerol (LPG), lower levels of zymosterol (ZyE) and Monogalactosyldiacylglycerol (MGDG) than controlled ones, but with no significant differences. Several specific lipid species were changed significantly in PTC cells treated by parthenolide, including the increasing of phosphatidylcholine (PC) (12:0e/16:0), PC (18:0/20:4), CerG3 (d18:1/24:1), lysophosphatidylethanolamine (LPE) (18:0), phosphatidylinositol (PI) (19:0/20:4), lysophosphatidylcholine (LPC) (28:0), ChE (22:6), and the decreasing of phosphatidylethanolamine (PE) (16:1/17:0), PC (34:1) and PC (16:0p/18:0). Four key targets (PLA2G4A, LCAT, LRAT, and PLA2G2A) were discovered when combining network pharmacology and lipidomics. Among them, PLA2G2A and PLA2G4A were able to bind with parthenolide confirmed by molecular docking.ConclusionsThe changed lipid profile and several significantly altered lipid species of parthenolide treated PTC cells were observed. These altered lipid species, such as PC (34:1), and PC (16:0p/18:0), may be involved in the antitumor mechanisms of parthenolide. PLA2G2A and PLA2G4A may play key roles when parthenolide treated PTC cells.

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Project description:The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA‑sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE‑miRNAs), long non‑coding RNAs (DE‑lncRNAs) and genes (DEGs). Subsequently, lncRNA‑miRNA, miRNA‑gene (that is, miRNA‑mRNA) and gene‑gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA‑mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE‑lncRNAs, 917 DEGs and 30 DE‑miRNAs were screened. The miRNA‑mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand‑receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine‑cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA‑206 and kallikrein‑related peptidase 10 were nodes in the ceRNA regulatory network of the selected feature gene, and they may serve import roles in the development of PTC.

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Dataset Information

To Explore the Inhibitory Mechanism of Quercetin in Thyroid Papillary Carcinoma through Network Pharmacology and Experiments.

Publications

To Explore the Inhibitory Mechanism of Quercetin in Thyroid Papillary Carcinoma through Network Pharmacology and Experiments.

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