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◆ Frontiers in Oncology2026-05-18· Colorectal cancer

Global research trends and hotspots of colorectal cancer organoids: a bibliometric insight and visualization analysis via multiple databases

Xiaoyi Zhang, Xingyu Zhu, Yibing Chen, Bingye Lu

原始摘要(英文原文)· Original abstract
Objectives Bibliometrics was adopted to analyze the research trends of colorectal cancer organoids, and to identify the global research hotspots and prospective directions. Methods Publications related to colorectal cancer organoids published from January 1, 2010 to December 31, 2025 were obtained from the Web of Science Core Collection (WOSCC) and Scopus databases. Bibliometric and visualization analyses were conducted utilizing Bibliometrix R package, Python, CiteSpace and VOSviewer to explore the publication trends, countries, institutions, journals, authors and thematic evolution. Results A total of 2239 relevant publications were included. The analysis revealed an explosive growth in the number of publications in this field over the past 16 years. China and the United States were the main contributors, and Utrecht University was the most productive institution. Hans Clevers had the highest total citations and number of publications, reflecting his leading influence in the field. Cancers was the most productive journal, while Nature was the most frequently cited. Keyword analysis and thematic evolution revealed that the current research hotspots primarily include drug screening, the tumor microenvironment, tumor immunity, and precision oncology. Conclusion Research on colorectal cancer organoids is shifting from the construction and optimization of conventional organoid models to the development of high-fidelity disease models. Current studies focus on the simulation of the tumor microenvironment and personalized cancer therapy, and colorectal cancer organoids will achieve broader clinical applications in precision oncology in the future.
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Global research trends and hotspots of colorectal cancer organoids: a bibliometric insight and visualization analysis via multiple databases — 科研速览 Science Skim