Novel Immune-Related Gene Signature for Risk Stratification and Prognosis of Survival in Estrogen Receptor (ER) or Progesterone Receptor (PR) Positive and Human Epidermal Growth Factor Receptor 2 (HER2) Negative Breast Cancer

Abstract

\n Background: Although intrinsic molecular subtype has been extensively used, the risk stratification have not been fully elucidated in estrogen receptor (ER) or progesterone receptor (PR) positive and human epidermal growth factor receptor 2 (HER2) negative breast cancer. Methods: RNA transcriptional data from The Cancer Genome Atlas (TCGA), METABRIC and GEO were used. Immune-related genes were obtained from the datasets and literature search. Univariate, lasso regression and multivariate cox regression were employed to identify prognostic immune-related genes and establish the risk signature. Relationships between the risk signature and clinical parameters, tumor-infiltrating immune cell abundances and cancer phenotypes were further evaluated.Results: Noted, 102 immune-related prognostic genes were identified in METABRIC dataset by univariate cox analysis. Consecutively, 7 immune genes (SHMT2, AGA, COL17A1, FLT3, SLC7A2, ATP6AP1 and CCL19) were selected as risk signature by lasso regression and multivariate cox analysis. Its performance was further verified in TCGA,GSE20685 and GSE9195 datasets. Multivariate Cox regression indicated that the risk signature was an independent predictor. The prognostic signature showed significant correlation with intrinsic molecular subtypes, 70-gene signature and tamoxifen resistance signature. The CIBERSORT algorithm revealed that CD4+ memory T cells were significant higher in low-risk group. Conversely, M0-type macrophages were significant higher in high-risk group in both TCGA and METABRIC cohorts, which may have effect on the prognosis. Furthermore, we found that low-risk group may be associated with immune-related pathway and high-risk group was with cell cycle-related pathway, which also showed impact on the prognosis.Conclusion: The present study constructed a robust seven immune-related gene signature and established an effective method in risk stratification and prediction of clinical outcome in ER or PR positive and HER2 negative breast cancer.