Zhu Houcheng, Huang Yue, Wang Xiangjin, Xiang Wang, Xie Yong
School of Sports Medicine and Health, Chengdu Sports University, Chengdu, China.
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Front Immunol. 2025 Aug 28;16:1604216. doi: 10.3389/fimmu.2025.1604216. eCollection 2025.
Tumor immune escape, a defining hallmark of malignant tumors, enables cancer cells to thrive within the host by evading detection and attack by the immune system. While immune checkpoint inhibitors, such as PD-1/PD-L1 antibodies, have delivered significant clinical advances, their effectiveness is tempered by modest response rates and a growing challenge of drug resistance. In this study, we aimed to explore the development process and trend of tumor immune escape, analyze the current hot spots, and predict the future research directions.
A bibliometric analysis was conducted in this study to retrieve and analyze 1839 publications from January 1, 2009 to February 14, 2025 related to tumor immune escape. Literature was obtained from Web of Science Core Collection (WoSCC) and data visualization and trend analysis were performed using VOSviewer, CiteSpace, Bibliometrix software package.
The bibliometric analysis indicates that research on tumor immune escape has primarily focused on China, the United States, and European countries. China ranks first in research output and impact, with notable contributions from institutions like the Sun Yat-sen University System and the University of Texas System. The journal with the most publications is Frontiers in Immunology, while the most cited article globally is Jiang P's 2018 publication in Nature Medicine, titled "Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response." Keyword co-occurrence and burst analysis indicate that the field has undergone a thematic evolution. Early research centered around classical immune checkpoint molecules and T cell exhaustion, while more recent trends have shifted toward the tumor microenvironment (TME), multi-target combination immunotherapies, and mechanisms of immune evasion involving metabolic reprogramming and the microbiome. The integration of artificial intelligence (AI) and machine learning (ML) in immunotherapy prediction and biomarker discovery has also gained momentum, highlighting a growing cross-disciplinary approach.
This bibliometric study provides a comprehensive overview of the intellectual landscape, research hotspots, and developmental trajectory of tumor immune escape research over the past 14 years. By mapping influential nation, authors, core journals, reference, and keyword bursts, this work not only summarizes major contributions in the field but also helps researchers better understand its evolution and emerging directions. Based on the observed patterns, we propose three key areas that warrant further exploration: (1) advancing interdisciplinary research at the intersection of the microbiome, metabolism, and immune regulation; (2) integrating artificial intelligence and multi-omics data to enhance predictive modeling and therapeutic precision; and (3) combining multi-modal therapeutic strategies to overcome immune escape more effectively.
肿瘤免疫逃逸是恶性肿瘤的一个决定性特征，它使癌细胞能够通过逃避免疫系统的检测和攻击在宿主体内生长。虽然免疫检查点抑制剂，如PD-1/PD-L1抗体，已经取得了显著的临床进展，但其有效性受到适度的缓解率和日益增长的耐药性挑战的限制。在本研究中，我们旨在探索肿瘤免疫逃逸的发展过程和趋势，分析当前的热点，并预测未来的研究方向。
本研究进行了文献计量分析，以检索和分析2009年1月1日至2025年2月14日期间与肿瘤免疫逃逸相关的1839篇出版物。文献来自科学网核心合集（WoSCC），并使用VOSviewer、CiteSpace、Bibliometrix软件包进行数据可视化和趋势分析。
文献计量分析表明，肿瘤免疫逃逸的研究主要集中在中国、美国和欧洲国家。中国在研究产出和影响力方面排名第一，中山大学系统和德克萨斯大学系统等机构做出了显著贡献。发表文章最多的期刊是《免疫学前沿》，而全球被引用最多的文章是蒋P于2018年发表在《自然医学》上的题为《T细胞功能障碍和排除的特征预测癌症免疫治疗反应》的文章。关键词共现和爆发分析表明，该领域经历了主题演变。早期研究集中在经典免疫检查点分子和T细胞耗竭，而最近的趋势已经转向肿瘤微环境（TME）、多靶点联合免疫疗法以及涉及代谢重编程和微生物群的免疫逃逸机制。人工智能（AI）和机器学习（ML）在免疫治疗预测和生物标志物发现中的整合也得到了发展，突出了日益增长的跨学科方法。
本文献计量研究全面概述了过去14年肿瘤免疫逃逸研究的知识格局、研究热点和发展轨迹。通过绘制有影响力的国家、作者、核心期刊、参考文献和关键词爆发情况，这项工作不仅总结了该领域的主要贡献，还帮助研究人员更好地了解其演变和新兴方向。基于观察到的模式，我们提出了三个值得进一步探索的关键领域：（1）推进微生物群、代谢和免疫调节交叉领域的跨学科研究；（2）整合人工智能和多组学数据以增强预测建模和治疗精度；（3）结合多模态治疗策略以更有效地克服免疫逃逸。
