A prognostic model for gastric cancer based on histamine-associated prognostic genes

Histamine has various associations with gastric cancer (GC); however, the mechanisms underlying histamine functions in GC have not been established. This study aimed to examine histamine-linked prognostic genes and mechanisms in GC. Relevant data were sourced from public databases, and differential expression, multivariate Cox, univariate Cox, and machine learning regression analyses were performed to identify prognostic genes associated with histamine in GC. Subsequently, a prognostic model was constructed. Independent prognostic factors linked to GC prognosis were determined through regression analyses and used for nomogram model construction. Furthermore, Gene Set Enrichment Analysis (GSEA) and drug sensitivity and immune infiltration analyses were conducted to explore the potential function of these genes in GC from various perspectives. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the expression of GRP, NPPB, SERPINE1, GAMT, MMRN1, and SLC22A16 in GC and paracarcinoma tissue. GRP, NPPB, SERPINE1, GAMT, MMRN1, and SLC22A16 were identified as putative prognostic genes, and a prognostic model was constructed. Compared with the low-risk group (LRG), the survival rates in the high-risk group (HRG) were reduced. Moreover, only M, N, age, and risk scores could be used to construct the nomogram model, which could precisely predict the survival status of patients with GC. GSEA indicated that the development of GC may be associated with certain metabolic pathways. Furthermore, there were 23 distinct infiltrating immune cells between the HRG and LRG, including activated B cells. HRG and LRG showed remarkable variation in sensitivity to 100 drugs (e.g., AP.24534, pazopanib, and AZD8055). RT-qPCR revealed that GRP, NPPB, SERPINE1, GAMT, MMRN1, and SLC22A16 expression was markedly upregulated in GC tissues compared with paracarcinoma tissue. We identified six prognostic genes and constructed a prognostic model, which provides a theoretical basis for the relationship between histamine and GC as well as potential therapeutic targets for GC.