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视网膜母细胞瘤生物标志物的全球研究格局:基于多个数据库的多学科文献计量分析(2005 - 2025年)

Global research landscape of retinoblastoma biomarkers: a multidisciplinary bibliometric analysis based on multiple databases (2005-2025).

作者信息

Peng Zhixin, Hu Qi, Chen Xiangdong

机构信息

The First Clinical Chinese Medicine College of Hunan University of Chinese Medicine, Changsha, Hunan, China.

The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.

出版信息

J Cancer Res Clin Oncol. 2025 Aug 15;151(8):231. doi: 10.1007/s00432-025-06279-7.

Abstract

OBJECTIVE

Research exploring biomarkers for retinoblastoma (RB) diagnosis exists; however, their specific impact on RB has not been thoroughly investigated through systematic quantitative analysis. This study aims to analyze the research landscape and hotspots of RB biomarkers from 2005 to 2025, providing a theoretical reference for future investigations.

METHODS

We retrieved publications from the Web of Science and Scopus databases published between 2005 and 2025, followed by analysis using R software, VOSviewer, and CiteSpace tools.

RESULTS

From 2005 to 2025, annual publication output exhibited a steady upward trajectory, with notably accelerated growth observed between 2013 and 2021, followed by a moderated pace from 2021 to 2024. China led in publication volume, followed by the United States, India, and Italy. While China dominated in quantitative output, the United States established a broader network of international collaborations. Cancers emerged as the journal with the highest publication count, whereas Cancer Research ranked first in citation frequency. Current research hotspots primarily include: liquid biopsy and circulating tumor biomarkers; molecular subtyping and tumor heterogeneity; targeted therapies and drug resistance mechanisms; tumor microenvironment and immune evasion; and artificial intelligence with multimodal data integration. Investigations into RB biomarkers focus on: (1) dynamically reflecting tumor burden (short half-life properties); (2) regulating oncogene transcription/translation (targeting E2F3, PI3K, and m6A); (3) driving epithelial-mesenchymal transition (EMT) and cellular proliferation; (4) mediating immune evasion; and (5) deep learning-based identification of tumor heterogeneity. The exploration of biomarkers to optimize individualized retinoblastoma treatment has emerged as a notable research trend.

CONCLUSION

As an emerging tool for achieving personalized therapeutic optimization, biomarkers have garnered significant attention from global scholars and are poised to become a major focus in future research on the management of RB. This study systematically reviewed and analyzed the current research landscape and key issues surrounding RB biomarkers, aiming to provide valuable references and insights for subsequent research in this field.

摘要

目的

存在探索视网膜母细胞瘤(RB)诊断生物标志物的研究;然而,它们对RB的具体影响尚未通过系统的定量分析进行深入研究。本研究旨在分析2005年至2025年RB生物标志物的研究现状和热点,为未来的研究提供理论参考。

方法

我们检索了2005年至2025年期间在科学网和Scopus数据库上发表的文献,随后使用R软件、VOSviewer和CiteSpace工具进行分析。

结果

2005年至2025年期间,年度出版物产出呈稳定上升趋势,2013年至2021年增长显著加速,2021年至2024年增速放缓。中国在出版物数量上领先,其次是美国、印度和意大利。虽然中国在定量产出方面占主导地位,但美国建立了更广泛的国际合作网络。《Cancers》成为发表文章数量最多的期刊,而《Cancer Research》在被引频次方面排名第一。当前的研究热点主要包括:液体活检和循环肿瘤生物标志物;分子亚型和肿瘤异质性;靶向治疗和耐药机制;肿瘤微环境和免疫逃逸;以及人工智能与多模态数据整合。对RB生物标志物的研究集中在:(1)动态反映肿瘤负荷(半衰期短的特性);(2)调节癌基因转录/翻译(靶向E2F3、PI3K和m6A);(3)驱动上皮-间质转化(EMT)和细胞增殖;(4)介导免疫逃逸;(5)基于深度学习识别肿瘤异质性。探索生物标志物以优化个体化视网膜母细胞瘤治疗已成为一个显著的研究趋势。

结论

作为实现个性化治疗优化的新兴工具,生物标志物已引起全球学者的高度关注,并有望成为未来RB管理研究的主要焦点。本研究系统地回顾和分析了当前围绕RB生物标志物的研究现状和关键问题,旨在为该领域的后续研究提供有价值的参考和见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca85/12356788/c3bc7882de70/432_2025_6279_Fig1_HTML.jpg

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