Network-based Approach to Identify Prognosis-related Genes in Tamoxifen-treated Patients With Estrogen Receptor-positive Breast Cancer

Abstract Background: The estrogen receptor (ER) antagonist tamoxifen is the most commonly used endocrine therapy for ER-positive breast cancer. However, tamoxifen resistance remains a major cause of cancer recurrence and progression. Here, we aimed to identify hub genes involved in the progression and prognosis of ER-positive breast cancer following tamoxifen treatment.Results: Microarray data (GSE9838) for 155 tamoxifen-treated primary ER-positive breast cancer samples were obtained from the Gene Expression Omnibus database. In total, 1706 differentially expressed genes (DEGs) associated with tamoxifen resistance, including 859 upregulated genes and 847 downregulated genes, were identified. These DEGs were mainly enriched in functions such as protein targeting to the ER and pathways such as ribosome and oxidative phosphorylation.Weighted correlation network analysis (WGCNA) clustered genes into 13 modules, among which the tan and blue modules were the most significantly related to prognosis. From these two modules, we further identified three prognosis-related hub genes (GRSF1, MAPT, and REC8) via survival analysis. High expression ofGRSF1 predicted poor prognosis, whereas MAPT andREC8indicated favorable survival outcomes in all patients with breast cancer and in patients with ER-positive breast cancer based on The Cancer Genome Atlas database. These hub genes were further verified by reverse transcription quantitative polymerase chain reaction.Conclusion: Our findings established novel prognostic biomarkers to predict tamoxifen sensitivity, which may facilitate individualized management of breast cancer.