Identification of the 'Danger Zone' Promoting Gastric Cancer Progression: Elucidating the Immunosuppressive Mechanism by CCDC80-Positive Fibroblasts

A research team led by Project Associate Professor Wenchao Gu of the Chiba University Graduate School of Medicine and Mo Shaocong of Huashan Hospital Fudan University performed spatial transcriptomics on mouse and human gastric cancer tissues to clarify how the spatial structure of the tumor microenvironment (TME) affects cancer progression and resistance to immunotherapy. The results revealed the existence of a 'Danger Zone' within gastric cancer tissue. In this area, CCDC80-positive fibroblasts capture CD8-positive T cells, which attack cancer, weakening their function and hindering the effects of immunotherapy. These research findings are expected to lead to methods for identifying patients who do not respond well to immunotherapy and the development of new treatments.

This research was published in the academic journal Apoptosis on March 7, 2026.

## Research Background
In gastric cancer, the variation in TME is deeply associated with treatment resistance and poor prognosis. While recent technological advancements have improved our understanding of the cellular composition and functional characteristics of the TME, it has not been fully clarified which parts of the tumor suppress immune function and promote cancer progression. Therefore, this study used spatial transcriptomics of gastric cancer tissues to identify spatial structures involved in tumor progression and elucidate their molecular mechanisms.

## Key Research Points
1. Discovery of the 'Danger Zone': Spatial transcriptomics identified a specific spatial structure in gastric cancer tissue called the 'Danger Zone.' This zone is frequently observed in diffuse-type gastric cancer and is strongly associated with advanced-stage gastric cancer and an immunosuppressive TME.
2. Patient Stratification and Prognosis Prediction: By stratifying gastric cancer patients into two types based on gene expression patterns in the danger zone, one type was shown to have a poor prognosis and low response to immunotherapy. Furthermore, the XGBoost machine learning model enabled accurate prediction of gastric cancer type and prognosis in multiple patients.
3. Elucidation of Immunosuppressive Mechanism: This study demonstrated that CCDC80-positive fibroblasts within the danger zone sequester CD8-positive T cells via the CXCL12-CXCR4 signaling pathway. This leads to significantly increased expression of inhibitory receptors (brakes) PD-1 and TIM-3 on the T cell surface, thereby inhibiting their function.
4. Prediction Model from H&E Images: An AI (LightGBM) model was created that can predict areas with a high risk of disease progression simply by analyzing H&E images.

## Future Outlook
This research has significantly advanced the understanding of the spatial mechanisms of immunosuppression in gastric cancer. Future efforts will focus on developing new treatment strategies targeting CCDC80-positive fibroblasts and the CXCL12-CXCR4 signaling pathway, as well as promoting verification through prospective cohort studies for the clinical application of H&E image-based danger zone scores.