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Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer
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 we...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720728/ https://www.ncbi.nlm.nih.gov/pubmed/33335811 http://dx.doi.org/10.7717/peerj.10468 |
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author | Zhang, Kai Jiang, Kuikui Hong, Ruoxi Xu, Fei Xia, Wen Qin, Ge Lee, Kaping Zheng, Qiufan Lu, Qianyi Zhai, Qinglian Wang, Shusen |
author_facet | Zhang, Kai Jiang, Kuikui Hong, Ruoxi Xu, Fei Xia, Wen Qin, Ge Lee, Kaping Zheng, Qiufan Lu, Qianyi Zhai, Qinglian Wang, Shusen |
author_sort | Zhang, Kai |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7720728 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77207282020-12-16 Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer Zhang, Kai Jiang, Kuikui Hong, Ruoxi Xu, Fei Xia, Wen Qin, Ge Lee, Kaping Zheng, Qiufan Lu, Qianyi Zhai, Qinglian Wang, Shusen PeerJ Bioinformatics 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. PeerJ Inc. 2020-12-04 /pmc/articles/PMC7720728/ /pubmed/33335811 http://dx.doi.org/10.7717/peerj.10468 Text en © 2020 Zhang et al. https://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc/4.0) , which permits using, remixing, and building upon the work non-commercially, as long as it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Zhang, Kai Jiang, Kuikui Hong, Ruoxi Xu, Fei Xia, Wen Qin, Ge Lee, Kaping Zheng, Qiufan Lu, Qianyi Zhai, Qinglian Wang, Shusen Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title | Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title_full | Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title_fullStr | Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title_full_unstemmed | Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title_short | Identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
title_sort | identification and characterization of critical genes associated with tamoxifen resistance in breast cancer |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720728/ https://www.ncbi.nlm.nih.gov/pubmed/33335811 http://dx.doi.org/10.7717/peerj.10468 |
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