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DOI 10.1002/cam4.72251

Медицинская библиотека · Cancer medicine · 2026

Organoids in Precision Radiotherapy: Methodological Foundations, Tumor-Specific Evidence, and Translational Roadmaps.

Zhu Yixian, Jiao Yawei, Xue Jiao, Lv Xiaoli, Qin Songbing

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Аннотация

BACKGROUND

Radiotherapy remains a cornerstone of cancer treatment, while its efficacy is often limited by tumor radioresistance and the risk of normal tissue toxicity. Conventional preclinical models, including two-dimensional (2D) cell cultures and murine xenografts, exhibit significant limitations in recapitulating human tumor pathophysiology, thereby impeding the clinical translation of novel radiotherapeutic strategies. Patient-derived organoids (PDOs) have emerged as transformative three-dimensional (3D) ex vivo models that recapitulate key aspects of original tumor heterogeneity and are increasingly applied in oncology research.

METHODS

This article provides a comprehensive review of the literature on the application of PDOs in radiation oncology, with a focused analysis of their pathway toward clinical translation.

RESULTS

PDOs demonstrate significant utility in predicting radiosensitivity, elucidating radioresistance mechanisms, optimizing combination therapies, modeling radiation injury, and screening targeted drugs. The integration of organoid technology with microfluidic organ-on-a-chip (OoC) platforms also offers unprecedented capability to dynamically simulate the tumor microenvironment and conduct high-throughput dose-response studies. A translational roadmap is presented for leveraging these biomimetic systems to advance personalized radiotherapy, ultimately aiming to accelerate the clinical translational application of organoids.

CONCLUSIONS

Despite challenges in standardization and immune component recapitulation, PDOs represent a powerful platform for advancing personalized radiotherapy.

Для цитирования: Zhu Yixian, Jiao Yawei, Xue Jiao, Lv Xiaoli, Qin Songbing. Organoids in Precision Radiotherapy: Methodological Foundations, Tumor-Specific Evidence, and Translational Roadmaps.. Cancer medicine. 2026. DOI: 10.1002/cam4.72251.

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