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BackgroundChronic inflammation and immune cell dysfunction in the tumor microenvironment are key factors in the development and progression of gastric tumors. However, inflammation-related genes associated with gastric cancer prognosis and their relationship with the expression of immune genes are not fully understood.MethodIn this study, we established an inflammatory response model score called “Riskscore”, based on differentially expressed genes in gastric cancer. We used Survival and Survminer packages in R to analyze patient survival and prognosis in risk groups. The survival curve was plotted using the Kaplan–Meier method, and the log-rank test was used to assess statistical significance, and we performed the ROC analysis using the R language package to analyze the 1-, 3-, and 5-year survival of patients in the GEO and TCGA databases. Single-factor and multi-factor prognostic analyses were carried out for age, sex, T, N, M, and risk score. Pathway enrichment analysis indicated immune factor-related pathway enrichment in both patient groups. Next, we screened for important genes that are involved in immune cell regulation. Finally, we created a correlation curve to explore the correlation between Riskscore and the expression of these genes.ResultsThe prognosis was significantly different between high- and low-risk groups, and the survival rate and survival time of the high-risk group were lower than those of the low-risk group. we found that the pathways related to apoptosis, hypoxia, and immunity were most enriched in the risk groups. we found two common tumor-infiltrating immune cell types (i.e., follicular helper T cells and resting dendritic cells) between the two risk groups and identified 10 genes that regulate these cells. Additionally, we found that these 10 genes are positively associated with the two risk groups.ConclusionFinally, a risk model of the inflammatory response in gastric cancer was established, and the inflammation-related genes used to construct the model were found to be directly related to immune infiltration. This model can improve the gastric cancer prognosis prediction. Our findings contribute to the development of immunotherapy for the treatment of gastric cancer patients.

BackgroundHelicobacter pylori (H. pylori) is a type I biological carcinogen, which may cause about 75% of the total incidence of gastric cancer worldwide. H. pylori infection can induce and activate the cancer-promoting signaling pathway and affect the occurrence and outcome of gastric cancer through controlling the regulatory functions of long non-coding RNAs (lncRNAs). However, we have no understanding of the prognostic worth of lncRNAs for gastric cancer patients infected with H. pylori.MethodWe screened differentially expressed lncRNAs using DESeq2 method among TCGA database. And we built the H. pylori infection-related lncRNAs regulatory patterns. Then, we constructed H. pylori infection-based lncRNAs prognostic signatures for gastric cancer patients together with H. pylori infection, via uni-variable and multi-variable COX regression analyses. Based on receiver operator characteristic curve (ROC) analysis, we evaluated the prediction effectiveness for this model.ResultsWe identified 115 H. pylori infection–related genes were differentially expressed among H. pylori–infected gastric cancer tissues versus gastric cancer tissues. Functional enrichment analysis implies that H. pylori infection might interfere with the immune-related pathways among gastric cancer tissues. Then, we built H. pylori infection–related dys-regulated lncRNA regulatory networks. We also identified 13 differentially expressed lncRNAs were associated with prognosis for gastric cancer patients together with H. pylori infection. Kaplan-Meier analysis demonstrated that the lncRNA signatures were correlated with the poor prognosis. What is more, the AUC of the lncRNA signatures was 0.712. Also, this prognostic prediction model was superior to the traditional clinical characters.ConclusionWe successfully constructed a H. pylori–related lncRNA risk signature and nomogram associated with H. pylori–infected gastric cancer patients prognosis, and the signature and nomogram can predict the prognosis of these patients.