Breast Cancer Prognostic Hub Genes Identified by Integrated Transcriptomic and Weighted Network Analysis: A Road Toward Personalized Medicine

Abstract

Breast cancer (BC) is the second-most common type and among the leading causes of worldwide cancer-related deaths. There is marked person-to-person variability in susceptibility to, and phenotypic expression and prognosis of BC, a predicament that calls for personalized medicine and individually tailored therapeutics. In this study, we report new observations on prognostic hub genes and key pathways involved in BC. We used the data set GSE109169, comprising 25 pairs of BC and adjacent normal tissues. Using a high-throughput transcriptomic approach, we selected data on 293 differentially expressed genes to establish a weighted gene coexpression network. We identified three age-linked modules where the light-gray module strongly correlated with BC. Based on the gene significance and module membership features, peptidase inhibitor 15 (PI15) and KRT5 were identified as our hub genes from the light-gray module. These genes were further verified at transcriptional and translational levels across 25 pairs of BC and adjacent normal tissues. Their promoter methylation profiles were assessed based on various clinical parameters. In addition, these hub genes were used for Kaplan–Meier survival analysis, and their correlation with tumor-infiltrating immune cells was investigated. We found that PI15 and KRT5 may be potential biomarkers and potential drug targets. These findings call for future research in a larger sample size, which could inform diagnosis and clinical management of BC, thus paving the way toward personalized medicine.