Identification of a stromal immunosuppressive barrier orchestrated by SPP1/C1QC macrophages and CD8 exhausted T cells driving gastric cancer immunotherapy resistance.

[PURPOSE] The heterogeneity of immune cells is a critical manifestation of gastric cancer (GC) heterogeneity and significantly contributes to immune therapy resistance. Although previous studies have focused on the roles of specific myeloid cells and exhausted CD8 T cells in immune resistance, the immune cell interaction network and its spatiotemporal distribution in GC immune resistance remain underexplored.

[METHODS] This study integrated multiple GC single-cell RNA sequencing, spatial transcriptomics, bulk-RNA sequencing, and single-cell immunotherapy datasets of our cohort (NFHGC Cohort). Methods such as single-cell subpopulation identification, transcriptomic analysis, spatial colocalization, cell communication network analysis and tissue immunofluorescence of gastric cancer were employed to investigate immune cell interactions and their molecular mechanisms in immune resistance.

[RESULTS] By leveraging a comprehensive approach that integrates single-cell RNA sequencing, spatial transcriptomics, and bulk RNA-seq profiles, we identified 20 immune subsets with potential prognostic and therapeutic implications. Our findings suggest a stromal immunosuppressive network orchestrated by Macro_SPP1/C1QC macrophages and CD8_Tex_C1 T cells, which may form a barrier impeding antitumor immunity. Macrophage-derived MIF signaling appears to drive immunosuppression via the MIF-CD74/CXCR4/CD44 axis. Based on these observations, we developed a preliminary TME classification system using a gene signature derived from barrier-associated immune cell markers and unsupervised clustering.

[CONCLUSIONS] Our study identified a potential stromal immunosuppressive barrier in gastric cancer, driven by Macro_SPP1/C1QC macrophages and CD8_Tex_C1 T cells, which may contribute to immune dysfunction and therapy resistance. Molecular subtyping based on this barrier's presence could inform personalized immune therapy strategies.