Lin Chen, Zhang Zilin, Yang Feili, Gu Shanshan, Zuo Jiyang, Wu Yi, Zhang Jing, Zhou Tiantian, Zhang Yuna, Chen Zaozao, Gu Zhongze, Shen Zhisen
Department of Otolaryngology-Head and Neck Surgery, The Affiliated Lihuili Hospital, Ningbo University, Ningbo, 315040, Zhejiang, China.
State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, SiPaiLou #2, Nanjing, 210096, China.
J Transl Med. 2025 Jul 16;23(1):798. doi: 10.1186/s12967-025-06824-5.
Head and neck cancer (HNC) presents significant research challenges due to the complexity of its tumor microenvironment (TME) and the heterogeneity across different cancer subtypes. Recent advancements in three-dimensional (3D) culture models and organ-on-a-chip (OOC) technology offer new avenues for mimicking the TME and enhancing the study of tumor biology, drug responses, and personalized treatment strategies. This study aims to summarize the current state of these models in HNC research and their potential in bridging the gap between preclinical models and clinical applications.
This review synthesizes findings from recent literature on the use of 3D models such as tumor spheroids, organoids, and co-culture systems in HNC research. A focus is placed on their applications in different cancer types, including laryngeal, oral, and nasopharyngeal cancers. Additionally, the integration of OOC technology in studying cancer metastasis, immunotherapy, and radiotherapy is discussed. Relevant studies on the role of AI and robotics in improving model efficiency and scalability are also examined.
The review identifies key developments in 3D model systems and OOC technologies, highlighting their ability to replicate patient-specific tumor behaviors and predict therapeutic responses. While these models have advanced the understanding of HNC pathophysiology, challenges remain in terms of technical limitations, validation, and physiological relevance. The integration of AI and robotics has shown promise in enhancing the scalability and data analysis capabilities of these models.
Advancements in 3D and OOC technologies are essential for overcoming the current limitations in HNC research. These models offer valuable insights into tumor biology and therapeutic efficacy, and their integration with artificial intelligence (AI) can further accelerate the development of personalized treatment strategies. However, further validation and refinement are needed before these models can be widely translated into clinical practice, offering a more effective and individualized approach to treating HNC.
头颈部癌（HNC）因其肿瘤微环境（TME）的复杂性以及不同癌症亚型之间的异质性而面临重大研究挑战。三维（3D）培养模型和芯片器官（OOC）技术的最新进展为模拟TME以及加强肿瘤生物学、药物反应和个性化治疗策略的研究提供了新途径。本研究旨在总结这些模型在HNC研究中的现状及其在弥合临床前模型与临床应用之间差距方面的潜力。
本综述综合了近期关于在HNC研究中使用3D模型（如肿瘤球体、类器官和共培养系统）的文献研究结果。重点关注它们在不同癌症类型中的应用，包括喉癌、口腔癌和鼻咽癌。此外，还讨论了OOC技术在研究癌症转移、免疫治疗和放射治疗中的整合。还研究了关于人工智能和机器人技术在提高模型效率和可扩展性方面作用的相关研究。
该综述确定了3D模型系统和OOC技术的关键进展，突出了它们复制患者特异性肿瘤行为和预测治疗反应的能力。虽然这些模型推进了对HNC病理生理学的理解，但在技术限制、验证和生理相关性方面仍存在挑战。人工智能和机器人技术的整合在提高这些模型的可扩展性和数据分析能力方面显示出了前景。
3D和OOC技术的进步对于克服当前HNC研究中的局限性至关重要。这些模型为肿瘤生物学和治疗效果提供了有价值的见解，并且它们与人工智能（AI）的整合可以进一步加速个性化治疗策略的发展。然而，在这些模型能够广泛转化为临床实践之前，还需要进一步验证和完善，以提供一种更有效、个性化的HNC治疗方法。
