Identification of potential prognostic markers associated with lung metastasis in breast cancer by coexpression network analysis

Abstract

Breast cancer (BC) is an aggressive cancer with a high percentage recurrence and metastasis. As one of the most common distant metastasis organ in BC, lung metastasis has a worse prognosis than that of liver and bone. Therefore, it’s important to explore some potential prognostic markers associated with the lung metastasis in BC for preventive treatment. In this study, transcriptomic data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Co-expression modules constructed by weighted gene co-expression network analysis (WGCNA) found the royal blue module was significantly associated with lung metastasis in BC. Then, co-expression genes of this module were analyzed for functional enrichment. Furthermore, the prognostic value of these genes was assessed by GEPIA Database and Kaplan-Meier Plotter. Results showed that the hub genes, LMNB and CDC20, were up-regulated in BC and had a worse survival of the patients. Therefore, we speculate that these two genes play crucial roles in the process of lung metastasis in BC, which can be used as potential prognostic markers in lung metastasis of BC. Collectively, our study identified two potential key genes in the lung metastasis of BC, which might be applied as the prognostic markers of the precise treatment in breast cancer with lung metastasis.