An Integrative Roadmap for Advancing Colorectal Cancer Organoid

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Compared with traditional two-dimensional (2D) models, patient-derived CRC organoids more faithfully preserve the genomic, transcriptomic, and architectural features of primary tumors, making them a powerful intermediate platform bridging basic discovery and clinical translation. Over the past several years, organoid systems have rapidly expanded beyond conventional epithelial-only cultures toward increasingly complex architectures, including immune-organoid co-culture models and mini-colon systems that enable long-term, spatially resolved tracking of tumor evolution. These advanced platforms, combined with high-throughput technologies and clustered regularly interspaced short palindromic repeats (CRISPR)-based functional genomics, have substantially enhanced our ability to dissect CRC mechanisms, identify therapeutic vulnerabilities, and evaluate drug responses in a physiologically relevant context. However, current models still face critical limitations, such as the lack of systemic physiology (e.g., gut-liver or gut-brain axes), limited standardization across platforms, and the need for large-scale, prospective clinical validation. These gaps highlight an urgent need for next-generation platforms and computational frameworks. The development of high-throughput multi-omics, CRISPR-based perturbation, drug screening technologies, and artificial intelligence-driven predictive approaches will offer a promising avenue to address these challenges, accelerating mechanistic studies of CRC, enabling personalized therapy, and facilitating clinical translation. In this perspective, we propose a roadmap for CRC organoid research centered on two major technical pillars: advanced organoid platforms, including immune co-culture and mini-colon systems, and mechanistic investigations leveraging multi-omics and CRISPR-based functional genomics. We then discuss translational applications, such as high-throughput drug screening, and highlight emerging computational and translational strategies that may support future clinical validation and precision medicine.