Modeling Context-Dependent Tumor Metabolism in 3D Systems: Implications for Functional Precision Oncology

Cancer metabolism is a dynamic and context-dependent process shaped by both tumor-intrinsic programs and microenvironmental cues. Capturing this complexity remains a major challenge, which limits the translation of metabolic insights into clinically actionable strategies. Patient-derived tumor organoids, together with emerging engineered platforms such as organ-on-chip systems, vascularized assembloids, and bioprinted tumor models, have opened new avenues for investigating tumor metabolism in physiologically relevant settings. These models enable the study of metabolic heterogeneity across tumor types, disease stages, and treatment conditions while preserving clinically relevant tumor features. Importantly, they provide functional platforms for ex vivo metabolic profiling, identification of metabolic vulnerabilities, and prediction of therapeutic responses. In this review, we discuss recent advances in the use of patient-derived and engineered 3D tumor models to characterize context-dependent metabolic states and treatment-induced metabolic rewiring. We first review technologies currently available to interrogate metabolism in these systems, including optical metabolic imaging, spatial metabolomics, isotope tracing, and bioenergetic profiling. We then discuss how 3D tumor models are used to investigate metabolic interactions within the tumor microenvironment (TME), including stromal and immune crosstalk, acidosis, nutrient availability, and circadian regulation. Finally, we critically examine current limitations, particularly the insufficient physiological relevance of standard organoid culture conditions for metabolic studies, and discuss how advanced engineering approaches and computational modeling may contribute to metabolism-driven functional precision oncology.