Construction and validation of an aging‐related gene signature for prognosis prediction of patients with breast cancer

BACKGROUND: Breast cancer (BC) is an aging‐related disease. Aging‐related genes (ARGs) participate in the initiation and development of lung and colon cancer, but the prognosis signature of ARGs in BC has not been clearly studied. AIMS: This study aimed to construct an ARGs signature to predict the prognosis of patients with breast cancer. METHOD: Firstly, the expression data of ARGs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were collected. Then COX and least absolulute shrinkage and selection operator(LASSO) were performed to construct the ARGs prognostic signature. The correlation between the signature and immune cell infiltration, immunotherapeutic response and drug sensitivity were subsequently analysed. The TCGA nomogram was constructed by combining the signature with other clinical features, and was validated by using GEO database. RESULTS: After LASSO and COX regression analyses, a prognostic signature based on nine ARGs, namely, HSP90AA1, NFKB2, PLAU, PTK2, RECQL4, CLU, JAK2, MAP3K5, and S100B, was built by using the TCGA dataset. Moreover, this risk signature is closely related to immune cell infiltration, immunotherapeutic response, and responses to chemotherapy and targeted therapy. Subsequently, The calibration curve demonstrates that the nomogram agrees well with practical prediction results. The receiver operating characteristic curve and decision‐making curve analysis demonstrate that ARG signature has the better prognosis diagnosis ability and clinical net benefits. CONCLUSIONS: Therefore, the proposed ARG prognosis signature is a new prognosis molecular marker of patients with BC, and it can provide good references to individual clinical therapy.