An immune-related prognostic signature for predicting breast cancer recurrence

Breast cancer (BC) is the most common cancer among women worldwide and is the second leading cause of cancer-related deaths in women. Increasing evidence has validated the vital role of the immune system in BC development and recurrence. In this study, we identified an immune-related prognostic signature of BRCA that could help delineate risk scores of poor outcome for each patient. This prognostic signature comprised information on five danger genes-TSLP, BIRC5, S100B, MDK, andS100P-and three protect genesRARRES3, BLNK, andACO1. Kaplan-Meier survival curve showed that patients classified as low-risk according to optimum cut-off risk score had better prognosis than those identified within the high-risk group. ROC analysis indicated that the identified prognostic signature had excellent diagnostic efficiency for predicting 3- and 5-years relapse-free survival (RFS). Multivariate Cox regression analysis proved that the prognostic signature is independent of other clinical parameters. Stratification analysis demonstrated that the prognostic signature can be used to predict the RFS of BC patients within the same clinical subgroup. We also developed a nomogram to predict the RFS of patients. The calibration plots exhibited outstanding performance. The validation sets (, , and ) were used to external validation. More convincingly, the real time RT-PCR results of clinical samples demonstrated that danger genes were significantly upregulated in BC samples, whereas protect genes were downregulated. In conclusion, we developed and validated an immune-related prognostic signature, which exhibited excellent diagnostic efficiency in predicting the recurrence of BC, and will help to make personalized treatment decisions for patients at different risk score.