Researchers have identified a previously unknown immunosuppressive barrier in gastric cancer that may explain why many patients fail to respond to immune checkpoint inhibitor therapy. The comprehensive study, published in Frontiers in Immunology, used advanced single-cell sequencing and spatial analysis techniques to map the complex interactions within the gastric cancer immune microenvironment.
Mapping the Immune Landscape
The research team analyzed single-cell RNA sequencing data from 29 gastric cancer samples, along with spatial transcriptomics and bulk RNA sequencing datasets. They identified 20 distinct immune cell subtypes and classified them into three functional modules: anti-tumor, pro-tumor, and anti-promoting interaction modules.
"We identified an immunosuppressive barrier composed of three types of dysfunctional immune cell cluster (Macro_SPP1, Macro_C1QC and CD8_Tex_C1)," the researchers reported. This barrier appears to form a physical and functional obstacle that prevents effective anti-tumor immune responses.
The Stromal Barrier Mechanism
Using spatial transcriptomics analysis of three gastric cancer tissue sections, the team discovered that the immunosuppressive barrier is primarily located in the stromal area surrounding tumors. The barrier consists of SPP1+ and C1QC+ tumor-associated macrophages working in concert with exhausted CD8+ T cells (CD8_Tex_C1).
The spatial analysis revealed that "Macro_C1QC, Macro_SPP1, and CD8_Tex_C1 predominantly enriched in the stromal area, while CD8_Tex_C2 exhibited higher abundance in the tumor area." This suggests that CD8+ T cells become progressively more exhausted as they migrate from the peripheral stroma into the tumor core.
MIF Signaling Drives Resistance
The study identified macrophage migration inhibitory factor (MIF) as a key molecular driver of immunotherapy resistance. In patients who did not respond to immune checkpoint blockade, signaling pathways including MIF-CD74/CXCR4/CD44, LGALS9-CD45, and CXCL16-CXCR6 were significantly enhanced.
"Within the immune interaction network, MIF, LGALS9, and CXCL16 signaling pathways appear to be the primary drivers promoting the functional decline of CD8_Tex_C1 cells," the researchers noted. This finding was validated through immunofluorescence staining of gastric cancer biopsy specimens, which showed higher MIF expression in patients with progressive disease compared to those with partial response.
Clinical Validation and Patient Outcomes
The research team analyzed immune therapy response data from multiple cohorts, including their own Nanfang Hospital gastric cancer immunotherapy cohort of 8 patients. They found that patients with higher proportions of barrier-associated immune cells (CD8_Tex_C1, CD8_Tex_C2, B_Stress, and Macro_C1QC) were more likely to be non-responders to immunotherapy.
Survival analysis of 323 gastric cancer patients from The Cancer Genome Atlas (TCGA) database confirmed that high enrichment of these immunosuppressive cell populations was associated with poor prognosis, while enrichment of anti-tumor cells like CD8_Teff and cDC2 was linked to better outcomes.
Four-Subtype Classification System
Based on their findings, the researchers developed a barrier-associated immune classification system that divides gastric cancer patients into four distinct subtypes:
- TME1 ("Immune Barrier Dominant"): Characterized primarily by the immunosuppressive barrier with limited CD8+ T cell infiltration
- TME2 ("Immune Barrier with CD8+ T Cell Exhaustion"): Features both the barrier and significant T cell exhaustion
- TME3 ("Immune Desert"): Shows minimal immune cell infiltration
- TME4 ("CD8+ T Cell Exhaustion Dominant"): Marked by T cell exhaustion but better immune infiltration
Patients with TME2 and TME1 subtypes had the worst prognosis, while those with TME4 had the best outcomes and higher TMEscores, indicating better potential for immunotherapy response.
Therapeutic Implications
The study's findings suggest several potential therapeutic strategies to overcome the stromal immunosuppressive barrier. The researchers used computational drug prediction tools to identify potential targeted therapies, including anti-tumor agents like Catumaxomab and Carfilzomib, as well as immune-modulating drugs such as Abatacept and Belatacept.
"CD8_Tex_C1 cells mainly express PD-1 as the immune checkpoint molecule, whereas CD8_Tex_C2 is distinguished by CTLA-4 expression," the study noted, suggesting that different exhausted T cell populations may require distinct therapeutic approaches.
Future Directions
The identification of this stromal immunosuppressive barrier provides new insights into why many gastric cancer patients develop resistance to immune checkpoint inhibitors. The barrier-associated classification system could serve as a biomarker to guide treatment selection and predict patient outcomes.
However, the researchers acknowledge that further validation through in vitro and in vivo experiments will be necessary before these findings can be translated to clinical practice. The study was also limited by the relatively small sample size of spatial transcriptomics data and the absence of matched single-cell sequencing data before and after immunotherapy treatment.
The research represents a significant advance in understanding the complex mechanisms underlying immunotherapy resistance in gastric cancer and offers a roadmap for developing more effective combination treatment strategies.
