H3 lysine 4 trimethylation (H3K4me3) modification and related regulators extensively regulate various crucial transcriptional courses in health and disease. However, the regulatory relationship between H3K4me3 modification and anti-tumor immunity has not been fully elucidated. We identified 72 independent prognostic genes of lung adenocarcinoma (LUAD) whose transcriptional expression were closely correlated with known 27 H3K4me3 regulators. We constructed three H3K4me3 modification patterns utilizing the expression profiles of the 72 genes, and patients classified in each pattern exhibited unique tumor immune infiltration characteristics. Using the principal component analysis (PCA) of H3K4me3-related patterns, we constructed a H3K4me3 risk score (H3K4me3-RS) system. The deep learning analysis using 12,159 cancer samples from 26 cancer types and 725 cancer samples from 5 immunotherapy cohorts revealed that H3K4me3-RS was significantly correlated with cancer immune tolerance and sensitivity. Importantly, this risk-score system showed satisfactory predictive performance for the ICB therapy responses of patients suffering from several cancer types, and we identified that SLAMF9 was one of the immunosuppressive phenotype and immunotherapy resistance-determined genes of H3K4me3-RS. The mice melanoma model showed Slamf9 knockdown remarkably restrained cancer progression and enhanced the efficacy of anti-CTLA-4 and anti-PD-L1 therapies by elevating CD8 + T cell infiltration. This study provided a new H3K4me3-associated biomarker system to predict tumor immunotherapy response and suggested the preclinical rationale for investigating the roles of SLAMF9 in cancer immunity regulation and treatment.
© 2025. The Author(s).