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DOI 10.1016/j.prp.2026.156562

Медицинская библиотека · Pathology, research and practice · 2026

New insights in tumor-on-a-chip models for studying cancer drug resistance.

Wang Yunbo, Shi Lin, Li Jianqiao, Zhang Xiangrong, Ren Jiabao, Jia Qian, Lv Litao, Yang Lijuan, Zhang Zhengzheng, Yang Jiankai, Dakal Tikam Chand, Zhang Yining, Shen Wenjing, Liu Wei

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Аннотация

Cancer presents significant challenges due to its high incidence, frequent recurrence, elevated mortality, and generally poor prognosis, making it a serious threat to human life and an obstacle to societal progress. A major difficulty in cancer treatment is the development of drug resistance, which undermines the effectiveness of therapies and limits patient survival, creating a substantial challenge for clinical oncology. In-vitro models, such as two-dimensional (2D) and three-dimensional (3D) cell cultures, have historically been used to study cancer cells responses to antitumor drugs and treatments. However, these models have faced limitations in reproducibility and scalability. Animal models, while commonly used, also fall short in accurately forecasting treatment outcomes in patients and casting doubts on their utility in fundamental research. Moreover, tumors at different stages of differentiation present varying levels of complexity, making it increasingly difficult to assess treatment resistance using traditional 2D/3D culturing and animal models. Hence, there remains a critical need for the creation of a novel platform that possesses the ability to manipulate cancer cells and tumor microenvironment in a scalable and reliable manner. In this review, we explore emerging microfluidic technologies and advanced tumor-chip systems that efficiently offer dynamic assessment of drug resistance.

Для цитирования: Wang Yunbo, Shi Lin, Li Jianqiao, Zhang Xiangrong, Ren Jiabao, Jia Qian, Lv Litao, Yang Lijuan, Zhang Zhengzheng, Yang Jiankai, Dakal Tikam Chand, Zhang Yining, Shen Wenjing, Liu Wei. New insights in tumor-on-a-chip models for studying cancer drug resistance.. Pathology, research and practice. 2026. DOI: 10.1016/j.prp.2026.156562.

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