A Novel Immune-related Model For Predicting Clinical Outcome And Evaluating The Immune Microenvironment In Lung Adenocarcinoma

Objective:In recent years,immunotherapy of lung adenocarcinoma(LUAD)has attracted much attention due to its remarkable efficacy.Immune-related genes may be important predictors for the prognosis of LUAD.Although immunomarkers such as Programmed cell death ligand 1(PD-L1)and tumor mutational burden(TMB)have been widely used in clinical practice,there are still a lot of patients with LUAD who do not benefit from immunotherapy.Therefore,we constructed an immune-related prognostic model to predict the prognosis of LUAD patients and explored its association with immune microenvironment.Methods:We obtained RNA sequencing data of LUAD patients from TCGA.The prognostic differentially expressed immune-related genes(PDEIRGs)were identified by differential expression analysis and univariate Cox regression analysis.Multivariate Cox regression analysis was used to establish an immune-related prognostic model,which was confirmed in the GEO cohort.In addition,we established Normogram based on four PDEIRGs and calculated the differences in immune cell expression levels in different risk groups using Cibersort method.Finally,we evaluated the potential clinical efficacy of immunotherapy in high-and low-risk LUAD patients using TIDE algorithm.Results:We obtained 256 up-regulated and 135 down-regulated immune-related differential genes,56 of which were associated with prognosis.Multivariate Cox regression analysis was used to establish a prognosis model composed of four immune-related genes(CCL20,ARRB1,CXCR2,PDGFB).Survival analysis of both training and test groups showed that the survival rate of the low-risk group was higher than that of the high-risk group(P<0.05).In addition,the results of immune infiltration analysis based on the TCGA expression matrix showed that in the high-risk group,a high abundance of CD4memory-activated T cells was associated with poor overall survival(OS).Finally,the TIDE algorithm showed that the risk of immune escape was greater in the high-risk group than in the low-risk group and that the patients in high-risk group was less likely to benefit from immunotherapy than the low-risk group.Conclusion:We constructed a new immune-related prognostic model based on four PDEIRGs for predicting the potential efficacy of immunotherapy in patinets with LUAD,facilitating further personalized and precise immunotherapy.