Comprehensive analysis of a new immune-related prognostic signature for esophageal cancer and its correlation with infiltrating immune cells and target genes

Background: The incidence of esophageal cancer (ESCA) is increasing rapidly, and the 5-year survival rate is less than 20%. This study provides new ideas for clinical treatment by establishing a prognostic signature composed of immune-related genes (IRGs), and fully analyzing its relationship with target genes and the tumor microenvironment (TME). Methods: We downloaded the ESCA expression matrix and clinical information from The Cancer Genome Atlas (TCGA) database. Differential expression genes (DEGs) were identified with the edgeR package and crossed with the IRGs we obtained from the ImmPort database to obtain differential IRGs (DEIRGs). The prognostic signature was then obtained through univariate Cox, LASSO-Cox, and multivariate Cox analyses. The receiver operating characteristic (ROC) curve was used to evaluate the prediction effect of the model. The immune cell infiltration abundance obtained by ssGSEA and therapeutic target genes was used to perform sufficient correlation analysis with the obtained prognostic signature and related genes. Results: A total of 173 samples were obtained from TCGA database, including 162 tumor and 11 normal samples. The 3,033 differential genes were used to obtain 254 DEIRGs by intersections with 2,483 IRGs (IRGs) obtained from the ImmPort Database. Finally, multivariate Cox regression analysis identified eight prognostic DEIRGs and established a new prognostic signature (HR: 2.49, 95% CI: 1.68-3.67; P<0.001). Based on the expression of the eight genes, the cohort was then divided into high and low risk groups and Kaplan-Meier (K-M) curves were plotted with the log-rank test P<0.0001 and 1-, 3-year area under the curve (AUC) >0.7. The K-M curves grouped according to high and low risks performed well in the two subgroup validation cohorts, with log-rank test P<0.05. There were differences in the degree of infiltration of 16 kinds of immune cells in tumor and normal samples, and the infiltration abundance of 12 kinds of immune cells was different in the high and low-risk groups. Conclusions: An effective and validated prognostic signature composed of IRGs was established and had a strong correlation with immune cells and target genes of drug therapy.