A prognostic model for breast cancer was built based on the signature of these hub genes predicted as above, which was constructed by a linear combination of the Cox regression coefficients (β) multiplied with its mRNA expression pattern. In brief, the risk score of each patient was calculated by the formula that risk score = (βGene1 × expressionGene1) + (βGene2 × expressionGene2) +…+(βGeneN × expressionGeneN). Patients were grouped into high- or low-risk set according to the Youden index of their risk score, and the survival difference between these two sets was analyzed by the Kaplan–Meier estimation combined with a log-rank test in the testing datasets (TCGA-BRCA and METABRIC). Moreover, the predictive value of this model was further applied and validated into other datasets, such as the public GSE20685 cohort, GSE4922 cohort and our local FUSCC-TNBC dataset (GSE118527).

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