| Objective: Gastric cancer is one of the most common malignant tumors in the world,which seriously threatens the safety of human life.The purpose of this study is to explore new prognostic markers of gastric cancer by constructing a competing endogenous RNA(ceRNA)regulatory network.Immune cells have become a key regulator in the occurrence and development of many tumor types.We use immune genes to construct a prognostic model of gastric cancer,so as to better predict the prognosis of patients with gastric cancer.Method: We downloaded RNA expression data from the Cancer Genome Atlas(TCGA)database.By comparing gastric cancer samples and normal tissue samples,the differentially expressed long non-coding RNA(lnc RNA),mRNA and micro RNA(miRNA)were screened out according to the ceRNA hypothesis.The interaction relationship between miRNA and lnc RNA/mRNA was constructed,and a ceRNA regulatory network was constructed.And carried out a functional enrichment analysis of target genes in the ceRNA network.The RNA in the ceRNA network was analyzed by generative analysis to screen the RNA related to the prognosis of gastric cancer.Immport database and differential expression algorithm were used to screen out the immune-related differentially expressed genes of gastric cancer.COX regression and random survival forest(RSF)are used to predict immune-related prognostic genes and construct survival models,and then analyze the correlation between immune gene expression and various immune cell infiltrations through TIMER database.Results: By comparing gastric cancer samples with normal samples,a total of 64 lnc RNAs,10 miRNAs and 10 mRNAs were included in our ceRNA network.The results of gene function enrichment analysis showed that the target genes in ceRNA were related to ATPase activity,receptor binding,angiogenesis and the function of extracellular exosomes.Survival analysis identified 7 lnc RNAs,2 miRNAs and 2 mRNAs related to the prognosis of gastric cancer.A total of 155 differentially expressed immune-related genes were screened between gastric cancer and normal tissues,and the immune prognostic model composed of 4 immune-related prognostic genes(NRP1,PPP3R1,IL17 RA and FGF16)was associated with the overall survival rate of gastric cancer(OS).closely related.According to the cut-off value of risk score,patients were divided into high-risk group and low-risk group.In the training(P <0.0001)and test groups(P = 0.0021),the overall survival of patients in the high-risk group was significantly shorter than that of patients in the low-risk group.Conclusion: In this study,the ceRNA regulatory network of gastric cancer was constructed and the prognostic analysis of the genes in the network was carried out.In addition,we used 4 immune genes to construct an immune prognostic model of gastric cancer.Our research provides new biomarkers for the diagnosis,treatment and evaluation of gastric cancer. |
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