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Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer

Xi Sun, Shuning Ding, Shuangshuang Lu, Zheng Wang, Xiaosong Chen, Kunwei Shen

OncoTargets and Therapy, 2021

2 citations

Abstract

BACKGROUND: Endocrine therapy is the backbone therapy in estrogen receptor α (ER)-positive breast cancer, and tamoxifen resistance is a great challenge for endocrine therapy. Tamoxifen-resistant and sensitive samples from the international public repository, the Gene Expression Omnibus (GEO) database, were used to identify therapeutic biomarkers associated with tamoxifen resistance. MATERIALS AND METHODS: In this study, integrated analysis was used to identify tamoxifen resistance-associated genes. Differentially expressed genes (DEGs) were identified. Gene ontology and pathway analysis were then analyzed. Weighted correlation network analysis (WGCNA) was performed to find modules correlated with tamoxifen resistance. Protein-protein interaction (PPI) network was used to find hub genes. Genes of prognostic significance were further validated in another GEO dataset and cohort from Shanghai Ruijin Hospital using RT-PCR. RESULTS: A total of 441 genes were down-regulated and 123 genes were up-regulated in tamoxifen-resistant samples. Those up-regulated genes were mostly enriched in the cell cycle pathway. Then, WGCNA was performed, and the brown module was correlated with tamoxifen resistance. An overlap of 81 genes was identified between differentially expressed genes (DEGs) and genes in the brown module. These genes were also enriched in the cell cycle. Twelve hub genes were identified using PPI network, which were involved in the mitosis phase of the cell cycle. Finally, 10…

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