A novel prognostic and therapeutic target biomarker based on necroptosis-related gene signature and immune microenvironment infiltration in gastric cancer

Background: Gastric cancer is a major global public health burden worldwide. Although treatment strategies are continuously improving, the overall prognosis remains poor. Necroptosis is a newly discovered form of cell death associated with anti-tumor immunity. Methods: Gastric cancer (GC) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded. Bioinformatics analysis was performed to construct a necroptosis-related risk model and to establish cancer subtypes. Potential associations of the tumor immune microenvironment and immunotherapy response with necroptosis-related prognostic risk score (NRG risk score) were comprehensively explored. 16 GC and paired normal tissues were collected and RT-PCR was performed to examine expression of NRG related genes. Results: GC samples were stratified into three subtypes according to prognostic necroptosis gene expression. A necroptosis risk model based on 12 genes (NPC1L1, GAL, RNASE1, PCDH7, NOX4, GJA4, SLC39A4, BASP1, BLVRA, NCF1, PNOC, and CCR5) was constructed and validated. The model was significantly associated with the OS and PFS of GC patients and the tumor immune microenvironment including immune cell infiltration, microsatellite instability (MSI) status, tumor mutational burden (TMB) score, immune checkpoint, and human leukocyte antigen (HLA) gene expression. A prognostic nomogram based on the NRG_score was additionally constructed. A low NRG risk score was correlated with high tumor immunogenicity and might benefit from immunotherapy. Conclusion: We have identified a useful prognostic model based on necroptosis-related genes in GC and comprehensively the relationship between necroptosis and tumor immunity. Predicting value to immunotherapy response is promising, and further research to validate the model in clinical practice is needed.