Tumor immune organoids support preclinical evaluation of cancer immunotherapies through comparative modelling and translational investigation
- 1Department of Oncology, Jilin Cancer Hospital
- 2Department of Radiotherapy, Jilin Cancer Hospital
Abstract
The response of cancer patients to immunotherapy varies significantly. However, there is still a lack of functional models that can accurately predict efficacy in vitro while preserving individual tumor immune characteristics of patients. This to some extent restricts the development and clinical application of precision tumor immunotherapy. Patient-derived tumor organoids, as a three-dimensional preclinical model, can compensate for the shortcomings of traditional two-dimensional culture and animal models in tissue structure and microenvironment simulation, and better preserve the spatial relationships and interactions between tumor cells, immune cells, matrix components, and extracellular matrix. Therefore, it has gradually become an important tool for immunotherapy research. This article reviews four types of models: endogenous immune-intact tumor organoids, immune cell-reconstituted co-culture models, vascularized stromal tumor immune organoids, and microfluidic organoid-on-a-chip platforms. The focus is on comparing their detection indicators, model fidelity, and experimental reproducibility, and discussing their applications in predicting immunotherapy efficacy and studying tumor immune resistance mechanisms. At present, such models still have some shortcomings, including a gradual decrease in immune cells during in vitro culture, insufficient reconstruction of vascular and stromal structures, lack of unified experimental procedures, limited scale preparation, and insufficient evidence for prospective clinical validation. In response to the above issues, the introduction of artificial intelligence, multi-omics analysis, and gene editing technology may provide new research ideas for the optimization and clinical translation of tumor immune organoids, and provide reference for precision tumor immunotherapy.
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BibTeX
@article{zhang2026tumor,
title = {{Tumor immune organoids support preclinical evaluation of cancer immunotherapies through comparative modelling and translational investigation}},
author = {Yang Zhang and Zhuo Wang and Yuting Xiu and Hongyu Wang and Kangkang Zhao and Zhishen Chen},
journal = {Frontiers in Oncology},
year = {2026},
month = oct,
doi = {10.3389/fonc.2026.1988538},
url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.1988538/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Tumor immune organoids support preclinical evaluation of cancer immunotherapies through comparative modelling and translational investigation
AU - Yang Zhang
AU - Zhuo Wang
AU - Yuting Xiu
AU - Hongyu Wang
AU - Kangkang Zhao
AU - Zhishen Chen
PY - 2026
DA - 2026/10/29
JO - Frontiers in Oncology
DO - 10.3389/fonc.2026.1988538
UR - https://www.frontiersin.org/articles/10.3389/fonc.2026.1988538/full
AB - The response of cancer patients to immunotherapy varies significantly. However, there is still a lack of functional models that can accurately predict efficacy in vitro while preserving individual tumor immune characteristics of patients. This to some extent restricts the development and clinical application of precision tumor immunotherapy. Patient-derived tumor organoids, as a three-dimensional preclinical model, can compensate for the shortcomings of traditional two-dimensional culture and animal models in tissue structure and microenvironment simulation, and better preserve the spatial relationships and interactions between tumor cells, immune cells, matrix components, and extracellular matrix. Therefore, it has gradually become an important tool for immunotherapy research. This article reviews four types of models: endogenous immune-intact tumor organoids, immune cell-reconstituted co-culture models, vascularized stromal tumor immune organoids, and microfluidic organoid-on-a-chip platforms. The focus is on comparing their detection indicators, model fidelity, and experimental reproducibility, and discussing their applications in predicting immunotherapy efficacy and studying tumor immune resistance mechanisms. At present, such models still have some shortcomings, including a gradual decrease in immune cells during in vitro culture, insufficient reconstruction of vascular and stromal structures, lack of unified experimental procedures, limited scale preparation, and insufficient evidence for prospective clinical validation. In response to the above issues, the introduction of artificial intelligence, multi-omics analysis, and gene editing technology may provide new research ideas for the optimization and clinical translation of tumor immune organoids, and provide reference for precision tumor immunotherapy.
SN - 2234-943X
ER -