Uncovering the Adaptive Tumor Immunity Interactions from a Single‐Cell Level

The cellular, dynamics, and spatial heterogeneity of tumor adaptive immunity pose great challenges to tumor-immune cell co-culture studies. Conventional large-cell-scale models often mask the intrinsic diversity of tumor and immune cells, missing the essential information for elucidating immunotherapy mechanisms, discovering rare cell subtypes, and screening cell surface receptors. A single-cell-scale interaction model has the potential to unravel the dynamic processes among specific cell subtypes, uncovering the differences in cell interaction and the resulting divergent outcomes. This paper reports the 3D printing of a single-cell leveled immuno-oncology model to investigate adaptive immune interactions among dendritic cells, T cells, and melanoma cells. The cells within this model successfully recapitulate key motility characteristics of adaptive immunity, including recognition, presentation, cytotoxicity, and immunosuppression. The dynamic results revealed a strong correlation between cell interaction and both motility and spatial distribution, specifically showing that the duration required for contact increased by 4-6 times when the distance exceeds 60 µm. Tracking and analysis of T cells further revealed the consistency between motility and biofunctions under the stimulation of different dendritic cell types, T cell subtypes, and stimulatory factors. By reproducing cell contact events under controllable variables, the current model helps to refine and validate knowledge of immune synapses and immune-tumor cell interactions.

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Publication Details

Journal
Advanced Healthcare Materials
Published
2026-01-20
DOI
https://doi.org/10.1002/adhm.202503411
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00

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article

Uncovering the Adaptive Tumor Immunity Interactions from a Single‐Cell Level

Kaitai Zhang, Tao Li, Tiankun Liu, Yuan Pang et al.
Advanced Healthcare Materials
Cancer Immunotherapy and Biomarkers
article

Uncovering the Adaptive Tumor Immunity Interactions from a Single‐Cell Level

Kaitai Zhang, Tao Li, Tiankun Liu, Yuan Pang, Yupeng Zheng, Zhenzhen Zhou, Wen Zhang, Zhihua Liu, Shujun Cheng, Li Yu, Wei Sun, Weihao Hu, Chang Zhou
article en

Abstract

The cellular, dynamics, and spatial heterogeneity of tumor adaptive immunity pose great challenges to tumor-immune cell co-culture studies. Conventional large-cell-scale models often mask the intrinsic diversity of tumor and immune cells, missing the essential information for elucidating immunotherapy mechanisms, discovering rare cell subtypes, and screening cell surface receptors. A single-cell-scale interaction model has the potential to unravel the dynamic processes among specific cell subtypes, uncovering the differences in cell interaction and the resulting divergent outcomes. This paper reports the 3D printing of a single-cell leveled immuno-oncology model to investigate adaptive immune interactions among dendritic cells, T cells, and melanoma cells. The cells within this model successfully recapitulate key motility characteristics of adaptive immunity, including recognition, presentation, cytotoxicity, and immunosuppression. The dynamic results revealed a strong correlation between cell interaction and both motility and spatial distribution, specifically showing that the duration required for contact increased by 4-6 times when the distance exceeds 60 µm. Tracking and analysis of T cells further revealed the consistency between motility and biofunctions under the stimulation of different dendritic cell types, T cell subtypes, and stimulatory factors. By reproducing cell contact events under controllable variables, the current model helps to refine and validate knowledge of immune synapses and immune-tumor cell interactions.

Advanced Healthcare Materials
University of Electronic Science and Technology of China (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), National Cancer Center (US), Intelligent Health (United Kingdom) (GB), Center for Life Sciences (CN), Institute of Zoology (CN), Drexel University (US), Tsinghua University (CN)
National Natural Science Foundation of China, Higher Education Discipline Innovation Project, Beijing Nova Program, National Key Research and Development Program of China
Openalex Percentile: Top 82%
Cancer Immunotherapy and Biomarkers
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