Single-cell profiling of gastric cancer ascites reveals an epithelial-immune dual phenotype signature predictive for anti-PD-1 immunotherapy responses

BACKGROUND: Gastric cancer (GC) with peritoneal metastasis frequently leads to malignant ascites (MA), a highly immunosuppressive "liquid tumor microenvironment" associated with poor prognosis. Although immune checkpoint blockade (ICB) demonstrate efficacy in some GC patients, treatment response to gastric cancer-associated peritoneal metastasis (GCPM) remains heterogeneous. The immune mechanisms driving this variability and predictive biomarkers remain unclear. METHODS: We performed single-cell transcriptomics and TCR/BCR repertoire analyses on paired MA and peripheral blood mononuclear cell (PBMC) samples from 10 advanced GC patients. Cellular clustering, trajectory inference, and intercellular communication analyses characterized immune remodeling. Clinical cohorts were used to validate prognostic and therapeutic predictive significance. RESULTS: Immune landscape of GCMA was delineated, which unveils extensive remodeling of T cells, B cells, and myeloid lineages. Notably, we identified a novel epithelial-immune dual-phenotype cell (EIDPC) population, validated by single-cell RNA sequencing and flow cytometry, exhibiting moderate malignant characteristics and potent immunoregulatory capacity. Transcriptomic and trajectory analyses suggest an epithelial origin with reprogramming toward immune evasion. Based on 10 EIDPC core genes, we developed the immune response signature of EIDPC (IRS-EIDPC), which accurately predicts anti-PD-1 therapy response and prognosis in independent gastric cancer cohort (AUC 0.929). CONCLUSIONS: This study reveals the immune landscape of malignant ascites in gastric cancer, and confirms EIDPC as a transitional malignant subpopulation with potent immunomodulatory functions. The IRS-EIDPC signature may aid in predicting immunotherapy responses and survival outcomes, provides insights into immune plasticity in malignant gastric ascites, and may help inform future precision therapeutic strategies.