Jiaxuan Wang, Hao Li, Zhenru Wang, Shanming Ruan
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摘要

本研究旨在利用文献计量学和生物信息学方法分析叶黄素在肿瘤相关领域的研究热点和机制,以指导未来的研究。我们对 2008 年至 2023 年 Web of Science 中所有关于叶黄素和肿瘤的文章进行了全面筛选。我们使用 VOSviewer、Scimago Graphica 和 CiteSpace 对这些出版物中的提取词进行了可视化处理。公共数据库用于收集木犀草素和肿瘤相关靶标。使用 Metascape 对叶黄素抗肿瘤相关基因进行 GO 和 KEGG 分析。利用Cytoscape和STRING建立了蛋白质相互作用网络,确定了木犀草素抗肿瘤活性的中心靶点。随后,利用分子对接技术评估了木犀草素与这些中心靶点的结合能力。我们发现,中国在这一领域占据主导地位,埃及知识库发表了最多的文章,而《分子》杂志发表了最多的相关文章。近年来,网络药理学、靶点、中药、纳米颗粒等成为叶黄素抗肿瘤研究的热点。研究发现,叶黄素与肿瘤之间共有483个重叠基因,它们与癌症相关通路、PI3K-Akt和MAPK信号通路密切相关。木犀草素形成了一个复杂的抗肿瘤相关基因网络,其中TP53、TNF、STAT3、AKT1、JUN、IL6和SRC发挥了关键作用,并与木犀草素表现出很强的结合亲和力。计算机技术正日益成为该学科不可或缺的一部分,未来的研究将侧重于更精确的抗肿瘤机制和有效的临床应用。
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Luteolin: A Comprehensive and Visualized Analysis of Research Hotspots and its Antitumor Mechanisms.

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.

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