Abstract
Breast cancer is the most prevalent cancer, and it is accompanied by high heterogeneity. N6-methyladenosine (m6A) modification significantly contributes to breast cancer tumorigenesis and progression. However, how m6A-related genes affect the clinical outcomes and tumor immune microenvironment (TIME) of breast cancer is largely unknown. Our study developed an m6A-related gene signature on the basis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The m6A-related gene signature was constructed using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Breast cancer patients were classified into low- and high-risk groups depending on the median risk score. The reliability and efficiency of the signature were validated using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA). The risk score was validated as an independent indicator associated with overall survival, and a nomogram model was created to estimate the overall survival of patients with breast cancer. Functional annotation suggested that the risk score had a strong relationship with immune-related pathways. Different proportions of immune cell infiltration between the two groups were evaluated using various algorithms. The high-risk group had higher immune checkpoint expression levels. We discovered that one of the 6 prognostic genes, TMEM71, was downregulated in breast cancer tissues. In vitro experiments indicated that overexpression of TMEM71 suppressed breast cancer cell proliferation and migration. In conclusion, the m6A-related gene signature may be a sensitive biomarker for overall survival prediction and guide the individualized treatment for breast cancer patients.