{"title":"Luteolin: A Comprehensive and Visualized Analysis of Research Hotspots and its Antitumor Mechanisms.","authors":"Jiaxuan Wang, Hao Li, Zhenru Wang, Shanming Ruan","doi":"10.1142/S0192415X24500903","DOIUrl":null,"url":null,"abstract":"<p><p>The aim of this study was to analyze the research hotspots and mechanisms of luteolin in tumor-related fields using bibliometric and bioinformatic approaches to guide future research. We conducted a comprehensive screening of all articles on luteolin and tumors in Web of Science from 2008 to 2023. The extracted words from these publications were visualized using VOSviewer, Scimago Graphica, and CiteSpace. Public databases were used to collect luteolin and tumor-related targets. GO and KEGG analyses of luteolin antitumor-related genes were performed using Metascape. Protein interaction networks were built with Cytoscape and STRING, identifying hub targets of luteolin in antitumor activity. Subsequently, the binding capacity of luteolin to these hub targets was assessed using molecular docking technology. We found that China dominated this field, the Egyptian Knowledge Bank published the most articles, and <i>Molecules</i> had the highest number of related publications. Recently, network pharmacology, target, traditional Chinese medicine, and nanoparticles have become research hotspots in luteolin's antitumor research. A total of 483 overlapping genes between luteolin and tumors were identified, and they were closely associated with the cancer-associated pathways, PI3K-Akt, and MAPK signaling pathways. Luteolin forms a complex network of antitumor-related genes, with TP53, TNF, STAT3, AKT1, JUN, IL6, and SRC playing key roles and showing strong binding affinity to luteolin. Computer technology is becoming increasingly integral to the discipline, and future research will focus on more precise antitumor mechanisms and effective clinical applications.</p>","PeriodicalId":94221,"journal":{"name":"The American journal of Chinese medicine","volume":" ","pages":"1-25"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The American journal of Chinese medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S0192415X24500903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The aim of this study was to analyze the research hotspots and mechanisms of luteolin in tumor-related fields using bibliometric and bioinformatic approaches to guide future research. We conducted a comprehensive screening of all articles on luteolin and tumors in Web of Science from 2008 to 2023. The extracted words from these publications were visualized using VOSviewer, Scimago Graphica, and CiteSpace. Public databases were used to collect luteolin and tumor-related targets. GO and KEGG analyses of luteolin antitumor-related genes were performed using Metascape. Protein interaction networks were built with Cytoscape and STRING, identifying hub targets of luteolin in antitumor activity. Subsequently, the binding capacity of luteolin to these hub targets was assessed using molecular docking technology. We found that China dominated this field, the Egyptian Knowledge Bank published the most articles, and Molecules had the highest number of related publications. Recently, network pharmacology, target, traditional Chinese medicine, and nanoparticles have become research hotspots in luteolin's antitumor research. A total of 483 overlapping genes between luteolin and tumors were identified, and they were closely associated with the cancer-associated pathways, PI3K-Akt, and MAPK signaling pathways. Luteolin forms a complex network of antitumor-related genes, with TP53, TNF, STAT3, AKT1, JUN, IL6, and SRC playing key roles and showing strong binding affinity to luteolin. Computer technology is becoming increasingly integral to the discipline, and future research will focus on more precise antitumor mechanisms and effective clinical applications.