摘要
BACKGROUND Gastric cancer(GC)is the most commonly diagnosed malignancy worldwide.Increasing evidence suggests that it is necessary to further explore genetic and immunological characteristics of GC.AIM To construct an immune-related gene(IRG)signature for accurately predicting the prognosis of patients with GC.METHODS Differentially expressed genes(DEGs)between 375 gastric cancer tissues and 32 normal adjacent tissues were obtained from The Cancer Genome Atlas(TCGA)GDC data portal.Then,differentially expressed IRGs from the ImmPort database were identified for GC.Cox univariate survival analysis was used to screen survival-related IRGs.Differentially expressed survival-related IRGs were considered as hub IRGs.Genetic mutations of hub IRGs were analyzed.Then,hub IRGs were selected to conduct a prognostic signature.Receiver operating characteristic(ROC)curve analysis was used to evaluate the prognostic performance of the signature.The correlation of the signature with clinical features and tumor-infiltrating immune cells was analyzed.RESULTS Among all DEGs,70 hub IRGs were obtained for GC.The deletions and amplifications were the two most common types of genetic mutations of hub IRGs.A prognostic signature was identified,consisting of ten hub IRGs(including S100A12,DEFB126,KAL1,APOH,CGB5,GRP,GLP2R,LGR6,PTGER3,and CTLA4).This prognostic signature could accurately distinguish patients into highand low-risk groups,and overall survival analysis showed that high risk patients had shortened survival time than low risk patients(P<0.0001).The area under curve of the ROC of the signature was 0.761,suggesting that the prognostic signature had a high sensitivity and accuracy.Multivariate regression analysis demonstrated that the prognostic signature could become an independent prognostic predictor for GC after adjustment for other clinical features.Furthermore,we found that the prognostic signature was significantly correlated with macrophage infiltration.CONCLUSION Our study proposed an immune-related prognostic signature fo
