| Objective Gastric cancer is one of the most common malignant tumors in the world,which seriously threatens human life.This paper mainly studies the multi-molecular prognostic model of gastric cancer immune genes and constructs the lnc RNA-mi RNAimmune genes ce RNA network,and explores the biological functions and prognostic correlations of related molecules.Methods We downloaded gastric cancer RNA expression data from The Cancer Genome Atlas（TCGA）database.Differentially expressed long non-coding RNAs（lnc RNAs）and micro RNAs（mi RNAs）were screened out by comparing gastric cancer samples with normal tissue samples.The immune gene data set was downloaded from the Innate DB database,and the RNA expression data of TCGA gastric cancer patients were used to extract the RNA expression data of immune genes,and conduct differential expression analysis to screen out differentially expressed immune genes.Download the transcription factor dataset from the JASPAR database,use the RNA expression data of TCGA gastric cancer patients,extract the transcription factor RNA expression data,conduct differential expression analysis,and screen out the differentially expressed transcription factors.Based on the functional enrichment of the differential immune gene and transcription factor dataset,the ce RNA regulatory network was constructed according to the interaction relationship between mi RNA and lnc RNA/m RNA proposed by the ce RNA hypothesis.In addition,we also performed survival analysis on RNAs in the ce RNA network to screen out RNAs associated with gastric cancer prognosis.At the same time,according to the differentially expressed immune genes,immune-related prognostic genes were predicted by COX regression analysis and random survival forest（RSF）and a survival model was constructed,and then the multi-molecular prognosis model of gastric cancer immune genes was verified by TCGA and GEO database analysis.Then we downloaded the data set from gse15886 and analyzed the immune infiltration of the data set.Further,we explored the relationship between kng1 and 22 immune cells.Finally,we verified the gene in TCGA database.Results By comparing gastric cancer samples with normal samples,a total of 26 lnc RNAs,12 mi RNAs and 10 m RNAs were incorporated into our ce RNA network.The results of gene function enrichment analysis indicated that the target genes in ce RNA functioned with extracellular matrix structural components,cell adhesion molecule binding and peptidase regulatory activity,metal ion transmembrane transporter activity,channel activity and passive transmembrane activity transporter activity related.Finally,two core immune genes（ADCY5,KNG1）were identified to be associated.A total of 233 highly significantly differentially expressed immunerelated genes were screened between gastric cancer and normal tissues,and the immune prognostic model consisting of 5 immune-related prognostic genes（CGB2,CGB8,DEFB126,GHR,and RBP4）was associated with the overall population of gastric cancer.Survival rate（OS）is closely related.Patients were divided into high-risk and low-risk groups based on risk score cutoffs.Patients in the high-risk group had significantly shorter overall survival than those in the low-risk group in both the training group（P < 0.0001）and the test group（P = 0.0021）.We found a significant relationship between gastric cancer gene and B cell CD4 memory T cell.In the relationship between kng1 and immune cells,we found that kng1 had a significant negative correlation with follicular helper T cells and a significant positive correlation with activated mast cells.Conclusion1.We found that five immune genes CGB2,CGB8,DEFB126,GHR and RBP4 were closely related to the overall survival rate of gastric cancer2.ADCY5 gene plays a key role in the immune verification of gastric cancer.KNG1 was negatively correlated with follicular helper T cells and positively correlated with activated mast cells. |
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