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中医药在癌症免疫治疗中作用的文献计量学与可视化分析

A bibliometric and visualization analysis of the role of traditional Chinese medicine in cancer immunotherapy.

作者信息

Lian Yixiao, Sun Jie, Yang Lin, Yu Weidong

机构信息

Department of Library, Peking University People's Hospital, Beijing, China.

Department of Central Laboratory and Institute of Clinical Molecular Biology, Peking University People's Hospital, Beijing, China.

出版信息

Front Immunol. 2025 Feb 14;16:1499026. doi: 10.3389/fimmu.2025.1499026. eCollection 2025.

DOI:10.3389/fimmu.2025.1499026
PMID:40028340
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11868050/
Abstract

OBJECTIVE

Traditional Chinese medicine (TCM) is used as a complementary treatment for patients with cancer, especially in immunotherapy. Although extensive clinical and basic research has been conducted on TCM in cancer immunotherapy, a comprehensive bibliometric analysis of this field has not yet been performed. This study aimed to investigate the progress and status of TCM, and the research focused on cancer immunotherapy.

METHODS

We collected 1,657 articles on TCM in cancer immunotherapy from 1994 to 2024 from the Web of Science Core Collection database. VOSviewer, CiteSpace, and the Bibliometrix R package were used to analyze countries, institutions, journals, authors, references, and keywords to predict future trends in cancer immunotherapy with TCM.

RESULTS

The publication rate of TCM in cancer immunotherapy research steadily increased from 1994 to 2018, with a swift growth from 2018 to 2023. China and TCM universities have achieved the most research advancements in this field. The most studied types of cancer are liver, lung, and colorectal cancers. However, few studies exist on upper respiratory tract tumors, cervical cancer, and melanoma, which deserve more attention. The study trend has gradually shifted from and models to clinical efficacy. Simultaneously, the focus of research transitioned from compound TCM preparations or classes of ingredients to specific pharmacodynamic ingredients, and the corresponding targets transitioned from cytokines to immune checkpoints. In general, molecular docking combined with multi-omics analysis is a popular and trending research method in TCM for cancer immunotherapy, helping researchers understand the mechanisms of TCM in cancer immunotherapy more comprehensively and accurately. By analyzing the literature, it is evident that TCM-based immunotherapy should contribute to effective maintenance or adjuvant therapy throughout the entire course of cancer rather than only in the late stages.

CONCLUSION

This study comprehensively summarized and identified research frontiers providing a reference for promoting the development of TCM immunotherapy preparations and guiding clinical practice. Consequently, more patients with cancer can benefit from immunotherapy.

摘要

目的

中医药被用作癌症患者的辅助治疗手段,尤其是在免疫治疗方面。尽管针对中医药在癌症免疫治疗领域已开展了广泛的临床和基础研究,但尚未对该领域进行全面的文献计量分析。本研究旨在调查中医药在癌症免疫治疗方面的进展和现状,并聚焦于相关研究。

方法

我们从Web of Science核心合集数据库中收集了1994年至2024年期间1657篇关于中医药在癌症免疫治疗方面的文章。使用VOSviewer、CiteSpace和Bibliometrix R包对国家、机构、期刊、作者、参考文献和关键词进行分析,以预测中医药在癌症免疫治疗方面的未来趋势。

结果

中医药在癌症免疫治疗研究中的发表率从1994年到2018年稳步上升,在2018年到2023年期间迅速增长。中国和中医药院校在该领域取得了最多的研究进展。研究最多的癌症类型是肝癌、肺癌和结直肠癌。然而,关于上呼吸道肿瘤、宫颈癌和黑色素瘤的研究较少,值得更多关注。研究趋势已逐渐从[此处原文缺失相关内容]模型转向临床疗效。同时,研究重点从复方中药制剂或成分类别转向特定的药效成分,相应的靶点从细胞因子转向免疫检查点。总体而言,分子对接结合多组学分析是中医药用于癌症免疫治疗的一种流行且趋势性的研究方法,有助于研究人员更全面、准确地了解中医药在癌症免疫治疗中的机制。通过分析文献可知,基于中医药的免疫治疗应在癌症的整个病程中发挥有效的维持或辅助治疗作用,而不仅仅是在晚期。

结论

本研究全面总结并确定了研究前沿,为促进中医药免疫治疗制剂的发展和指导临床实践提供了参考。从而使更多癌症患者能够从免疫治疗中获益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/563822fc8f04/fimmu-16-1499026-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/a7ad04975223/fimmu-16-1499026-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/91df69fe7d7e/fimmu-16-1499026-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/a34275368db9/fimmu-16-1499026-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/e3717e932999/fimmu-16-1499026-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/563822fc8f04/fimmu-16-1499026-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/a7ad04975223/fimmu-16-1499026-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/91df69fe7d7e/fimmu-16-1499026-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/a34275368db9/fimmu-16-1499026-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/e3717e932999/fimmu-16-1499026-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a270/11868050/563822fc8f04/fimmu-16-1499026-g007.jpg

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