Al-Kabani Ahad, Huda Bintul, Haddad Jewel, Yousuf Maryam, Bhurka Farida, Ajaz Faika, Patnaik Rajashree, Jannati Shirin, Banerjee Yajnavalka
Department of Basic Medical Sciences, College of Medicine and Health Sciences, Mohammed Bin Rashid University of Medicine and Health Sciences (MBRU), Dubai Health, AMC Building 14, Dubai 505055, United Arab Emirates.
Cancers (Basel). 2025 Jun 26;17(13):2163. doi: 10.3390/cancers17132163.
Colorectal cancer (CRC) remains a major global health burden, marked by complex tumor-microenvironment interactions, genetic heterogeneity, and varied treatment responses. Effective preclinical models are essential for dissecting CRC biology and guiding personalized therapeutic strategies. This review aims to critically evaluate current experimental CRC models, assessing their translational relevance, limitations, and potential for integration into precision oncology. A systematic literature search was conducted across PubMed, Scopus, and Web of Science, focusing on studies employing defined in vitro, in vivo, and emerging integrative CRC models. Studies were included based on experimental rigor and relevance to therapeutic or mechanistic investigation. Models were compared based on molecular fidelity, tumorigenic capacity, immune interactions, and predictive utility. CRC models were classified into in vitro (2D cell lines, spheroids, patient-derived organoids), in vivo (murine, zebrafish, porcine, canine), and integrative platforms (tumor-on-chip systems, humanized mice, AI-augmented simulations). Traditional models offer accessibility and mechanistic insight, while advanced systems better mimic human tumor complexity, immune landscapes, and treatment response. Tumor-on-chip and AI-driven models show promise in simulating dynamic tumor behavior and predicting clinical outcomes. Cross-platform integration enhances translational validity and enables iterative model refinement. Strategic deployment of complementary CRC models is critical for advancing translational research. This review provides a roadmap for aligning model capabilities with specific research goals, advocating for integrated, patient-relevant systems to improve therapeutic development. Enhancing model fidelity and interoperability is key to accelerating the bench-to-bedside translation in colorectal cancer care.
结直肠癌（CRC）仍然是一项重大的全球健康负担，其特征是复杂的肿瘤-微环境相互作用、基因异质性和多样的治疗反应。有效的临床前模型对于剖析CRC生物学特性和指导个性化治疗策略至关重要。本综述旨在严格评估当前的实验性CRC模型，评估它们的转化相关性、局限性以及整合到精准肿瘤学中的潜力。我们在PubMed、Scopus和Web of Science上进行了系统的文献检索，重点关注采用特定的体外、体内和新兴整合性CRC模型的研究。根据实验严谨性以及与治疗或机制研究的相关性纳入研究。基于分子保真度、致瘤能力、免疫相互作用和预测效用对模型进行比较。CRC模型分为体外模型（二维细胞系、球体、患者来源的类器官）、体内模型（小鼠、斑马鱼、猪、犬）和整合平台（芯片上肿瘤系统、人源化小鼠、人工智能增强模拟）。传统模型具有易获取性并能提供机制性见解，而先进系统能更好地模拟人类肿瘤的复杂性、免疫格局和治疗反应。芯片上肿瘤模型和人工智能驱动的模型在模拟动态肿瘤行为和预测临床结果方面显示出前景。跨平台整合可提高转化有效性并实现模型的迭代优化。互补性CRC模型的战略部署对于推进转化研究至关重要。本综述提供了一个路线图，用于使模型能力与特定研究目标相匹配，倡导采用与患者相关的整合系统以改善治疗开发。提高模型保真度和互操作性是加速结直肠癌护理从 bench 到 bedside 转化的关键。
