Deciphering IFN signaling in gastric cancer: A single-cell and bulk transcriptomic integration reveals CXCR4 as a key immunomodulator and prognostic determinant

BACKGROUND: Gastric cancer (GC), a prevalent solid tumor, features a complex tumor microenvironment (TME) that influences immunotherapy responses. Leveraging single-cell RNA sequencing (scRNA-seq) and bulk transcriptomics, we dissect the interplay between interferon (IFN) signaling and GC TME to identify actionable targets. METHODS: We analyzed bulk and scRNA-seq datasets. Gene Set Variation Analysis evaluated IFN pathway activity. The Scissor (single-cell identification of subpopulations with bulk sample phenotype correlation) algorithm and weighted gene co-expression network analysis identified survival-associated, IFN-correlated cellular subpopulations. Cell-cell communication within TME was mapped. A multi-gene prognostic signature was constructed and validated. qRT-PCR and Western blot detected marker gene expression. Flow cytometry assessed the proportion of macrophage polarization. CCK-8, Transwell, and scratch assays evaluated cell proliferation and migration. RESULTS: ) exhibited the strongest IFN-γ-driven communication with tumor cells. We established a robust IFN-related prognostic model and pinpointed CXCR4 as a key adverse prognostic biomarker tightly coupled to IFN signaling. Low CXCR4 with high IFN activity defined a favorable prognostic profile. In cell experiments, CXCR4 deficiency in macrophages activated the IFN signaling pathway. Its overexpression reversed the inhibitory effect of IFN-γ treatment on malignant phenotype of AGS cells. CONCLUSIONS: This study elucidates IFN signaling network within the GC TME at single-cell resolution. We provide a prognostic model and identify CXCR4 as a promising therapeutic target, shedding mechanistic insights for refining immunotherapy strategies in GC.