Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer

Kai Zhang; Kuikui Jiang; Ruoxi Hong; Fei Xu; Wen Xia; Ge Qin; Kaping Lee; Qiufan Zheng; Qianyi Lu; Qinglian Zhai; Shusen Wang

doi:10.7717/peerj.10468

Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer

PeerJ. 2020 Dec 4:8:e10468. doi: 10.7717/peerj.10468. eCollection 2020.

Authors

Kai Zhang^#¹, Kuikui Jiang^#², Ruoxi Hong², Fei Xu², Wen Xia², Ge Qin², Kaping Lee², Qiufan Zheng², Qianyi Lu², Qinglian Zhai², Shusen Wang²

Affiliations

¹ Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Molecular Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
² Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.

^# Contributed equally.

Abstract

Background: Tamoxifen resistance in breast cancer is an unsolved problem in clinical practice. The aim of this study was to determine the potential mechanisms of tamoxifen resistance through bioinformatics analysis.

Methods: Gene expression profiles of tamoxifen-resistant MCF-7/TR and MCF-7 cells were acquired from the Gene Expression Omnibus dataset GSE26459, and differentially expressed genes (DEGs) were detected with R software. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction (PPI) network was generated, and we analyzed hub genes in the network with the Search Tool for the Retrieval of Interacting Genes database. Finally, we used siRNAs to silence the target genes and conducted the MTS assay.

Results: We identified 865 DEGs, 399 of which were upregulated. GO analysis indicated that most genes are related to telomere organization, extracellular exosomes, and binding-related items for protein heterodimerization. PPI network construction revealed that the top 10 hub genes-ACLY, HSPD1, PFAS, GART, TXN, HSPH1, HSPE1, IRAS, TRAP1, and ATIC-might be associated with tamoxifen resistance. Consistently, RT-qPCR analysis indicated that the expression of these 10 genes was increased in MCF-7/TR cells comparing with MCF-7 cells. Four hub genes (TXN, HSPD1, HSPH1 and ATIC) were related to overall survival in patients who accepted tamoxifen. In addition, knockdown of HSPH1 by siRNA may lead to reduced growth of MCF-7/TR cell with a trend close to significance (P = 0.07), indicating that upregulation of HSPH1 may play a role in tamoxifen resistance.

Conclusion: This study revealed a number of critical hub genes that might serve as therapeutic targets in breast cancer resistant to tamoxifen and provided potential directions for uncovering the mechanisms of tamoxifen resistance.

Keywords: Bioinformatics analysis; Breast cancer; Crucial genes; Drug resistance; Tamoxifen.

Grants and funding

The authors received no funding for this work.