Identification of an Independent Immune-Genes Prognostic Index for Breast Cancer

Abstract Objective: There are increasing evidences that the immune micro-environment of breast cancer (BC) seriously affects the clinical outcome. This study aims to explore the role of tumor immune genes in the prognosis of BC patients.Methods: We obtained the list of 2498 immune genes from ImmPort database. In addition, we obtained gene expression data and clinical characteristics data of BC patients from the TCGA database. The prognostic correlation of the differential genes was analyzed through Survival package. Cox regression analysis was performed to analyze the prognostic effect of immune genes. According to the regression coefficients of prognostic immune genes in regression analysis, an immune risk scores model was established. Gene set enrichment analysis (GSEA) was performed to probe the biological correlation of immune gene scores. P< 0.05 was considered to be statistically significant. Results: In total, 556 immune genes were differentially expressed in normal tissues and BC tissues (p<0. 05). In univariate cox regression analysis, a total of 66 immune genes were statistically significant for survival risk, of which 30 were associated with overall survival (P<0.05). Through lasso regression analysis, a 15 immune genes risk scores model was established. KM survival analysisrevealed that high immune risk scores represented worse survival (p<0.001). ROC curve indicated that the immune genes risk scores model had good a reliability in predicting prognosis (5-year OS, AUC=0.752). The established risk model showed splendid AUC value in the validation dataset (3-year over survival (OS) AUC=0.685, 5-year OS AUC=0.717, P=0.00048). Moreover, immune risk scoreswere proved to be an independent influencing factor for BC patients. Finally, we found that 15 immune genes and risk scores had significant clinical correlations, and were involved in a variety of carcinogenic pathways.Conclusion:In a word, our study provides a new perspective for the expression of immune genes in BC. In addition, the immune risk scores have considerable advantages in predicting the survival of BC, which ares associated with a variety of oncogenic pathways.