Abstract Human tumor organoids represent a paradigm shift in cancer modeling, overcoming critical limitations of conventional systems by faithfully recapitulating genetic heterogeneity, three-dimensional architecture, and tumor microenvironment dynamics of patient tumors. Our review explores how human tumor organoids serve as a transformative preclinical platform, bridging the gap between basic research and clinical translations. We highlight recent advances in tumor organoid generation, spanning patient-derived organoids to genetically engineered platforms from normal tissue and human pluripotent stem cells, and their applications in deciphering carcinogenesis, clonal evolution, and metastatic mechanisms. We further examine technological innovations in culture systems that enhance the interpretability and translatability of tumor phenotypes and drug responses. We present an in-depth exploration of how integrated tumor microenvironment co-culture systems—combining immune cells, cancer-associated fibroblasts, and vascular components–enable novel investigations into tumor-stroma-immune crosstalk. Clinically, human tumor organoid biobanks have shown great promise in predicting personalized therapy responses. Emerging technologies like organoids-on-chip platforms, three-dimensionally bioprinting and artificial intelligence-driven analytics are enhancing high-throughput drug screening efficiency and biomarker identification. Despite advances, complete microenvironmental modeling remains challenging, particularly in replicating vascular complexity and systemic immune responses. Future advancements will demand convergence of synthetic biology, functional genomics, and machine learning to transform human tumor organoids from static avatars into dynamic “living biosensors”. In summary, this review provides an in-depth exploration of the organoid field and presents a clear and actionable framework for positioning tumor organoids as indispensable tools in functional precision medicine—a strategy that ultimately bridges mechanistic discoveries with clinical translation.
Zhou et al. (Mon,) studied this question.