Gastric cancer (GC) represents a formidable global health challenge characterized by profound molecular heterogeneity and a dynamically evolving tumor microenvironment (TME). Although genomic sequencing facilitates precision medicine, its capacity to capture intricate tumor microenvironment interactions or predict individual therapeutic outcomes remains limited. Recently, patient-derived cancer organoids (PDCOs) have emerged as high-fidelity three-dimensional (3D) models that faithfully recapitulate the histological architecture, mutational landscapes, and functional phenotypes of their parent tumors. This review systematically delineates advances in using GC-PDCOs to simulate the TME and elucidate immune evasion mechanisms, specifically camouflage, coercion, and cytoprotection. We emphasize the transformative potential of PDCOs as “patient avatars” in functional precision oncology, highlighting their promising predictive value for sensitivities to chemotherapy, targeted therapies, and immunotherapies, with early small-cohort studies demonstrating high clinical concordance. Furthermore, we evaluate the integration of emerging technologies, such as artificial intelligence and 3D bioprinting, to overcome current translational bottlenecks. Finally, we propose a strategic roadmap for integrating organoid technology into clinical workflows to achieve truly individualized therapeutic regimens for every gastric cancer patient.
Ma et al. (2026) studied this question.