A regulator-based immunoscore predicts prognosis and immunotherapy response in gastric cancer

Abstract

Immune checkpoint inhibitors (ICIs) have improved treatment outcomes in gastric cancer (GC); however, only a subset of patients benefit due to tumor heterogeneity. Current biomarkers have limited predictive value, highlighting the need for improved stratification strategies. We analyzed RNA-seq and clinical data from 375 TCGA-STAD patients to identify immune infiltration subtypes using CIBERSORT and consensus clustering, followed by differential expression analysis to obtain 1,454 DEGs. A transcription factor-gene regulatory network was reconstructed using ARACNe, and regulatory protein activity of candidate regulators was inferred with VIPER. Key prognostic regulators were selected through LASSO regression and survival analysis, leading to four master regulators (MYB, NFE2L3,SETBP1,TFAP2A) that were integrated into a PCA-based Immunoscore model. The model was validated in an independent cohort of 45 advanced gastric cancer patients treated with PD-1 inhibitors. Four immune infiltration subtypes with distinct immune cell compositions were identified. Four master regulators (MYB, NFE2L3, SETBP1, TFAP2A) were incorporated into the Immunoscore model. Patients with a high Immunoscore showed significantly improved overall survival in the TCGA cohort ( p = 0.00042). Validation in the PD-1 cohort further confirmed its predictive value ( p = 0.00459), achieving an AUC of 0.838. Comparative benchmarking against PREDICTIO and TIDE demonstrated comparatively favorable predictive performance of the ImmunoScore model for immunotherapy response. Functional enrichment analysis revealed that the model was primarily associated with immune response, inflammatory response, and chemokine signaling pathways. This study presents a regulator-based Immunoscore that is associated with prognosis and immunotherapy response in gastric cancer. Despite limitations, including a small validation cohort and reliance on public datasets, the model offers insights into immune-related regulatory mechanisms and may serve as a potential tool for patient stratification.