Luteolin: A Comprehensive and Visualized Analysis of Research Hotspots and Its Antitumor Mechanisms
Jiaxuan Wang1, Hao Li1, Zhenru Wang1
1The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, Zhejiang 310006, P. R. China.
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.
Insights
This study maps luteolin
Area of Science:
- Phytochemistry and Pharmacology
- Bioinformatics and Computational Biology
- Cancer Research
Background:
- Luteolin, a natural flavonoid, exhibits potential antitumor properties.
- Understanding its complex mechanisms and research trends is crucial for therapeutic development.
Purpose of the Study:
- To identify research hotspots and elucidate the antitumor mechanisms of luteolin using bibliometric and bioinformatic analyses.
- To guide future research directions for luteolin's application in oncology.
Main Methods:
- Bibliometric analysis of publications (2008-2023) using VOSviewer and CiteSpace.
- Bioinformatic analysis including gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment.
- Protein-protein interaction network construction and molecular docking to identify key targets.
Main Results:
- China leads research in this field; network pharmacology, targets, traditional Chinese medicine, and nanoparticles are current hotspots.
- Identified 483 overlapping genes associated with cancer pathways like PI3K-Akt and MAPK.
- Key targets (TP53, TNF, STAT3, AKT1, JUN, IL6, SRC) show strong binding affinity with luteolin.
Conclusions:
- Luteolin's antitumor activity involves a complex gene network, particularly impacting PI3K-Akt and MAPK signaling.
- Computational approaches are vital for precise mechanism elucidation and clinical application of luteolin.
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