Cargando…
Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer
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) databas...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187086/ https://www.ncbi.nlm.nih.gov/pubmed/34113127 http://dx.doi.org/10.2147/OTT.S290426 |
_version_ | 1783705073970315264 |
---|---|
author | Sun, Xi Ding, Shuning Lu, Shuangshuang Wang, Zheng Chen, Xiaosong Shen, Kunwei |
author_facet | Sun, Xi Ding, Shuning Lu, Shuangshuang Wang, Zheng Chen, Xiaosong Shen, Kunwei |
author_sort | Sun, Xi |
collection | PubMed |
description | 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 of these 12 genes were validated to be up-regulated in tamoxifen-resistant patients and were associated with poor prognosis in ER-positive patients. CONCLUSION: Our study suggested mitosis-related genes are mainly involved in tamoxifen resistance, and high expression of these genes could predict poor prognosis of patients receiving tamoxifen. These genes may be potential targets to improve efficacy of endocrine therapy in breast cancer, and inhibitors targeted these genes could be used in endocrine-resistant patients. |
format | Online Article Text |
id | pubmed-8187086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-81870862021-06-09 Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer Sun, Xi Ding, Shuning Lu, Shuangshuang Wang, Zheng Chen, Xiaosong Shen, Kunwei Onco Targets Ther Original Research 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 of these 12 genes were validated to be up-regulated in tamoxifen-resistant patients and were associated with poor prognosis in ER-positive patients. CONCLUSION: Our study suggested mitosis-related genes are mainly involved in tamoxifen resistance, and high expression of these genes could predict poor prognosis of patients receiving tamoxifen. These genes may be potential targets to improve efficacy of endocrine therapy in breast cancer, and inhibitors targeted these genes could be used in endocrine-resistant patients. Dove 2021-06-04 /pmc/articles/PMC8187086/ /pubmed/34113127 http://dx.doi.org/10.2147/OTT.S290426 Text en © 2021 Sun et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Sun, Xi Ding, Shuning Lu, Shuangshuang Wang, Zheng Chen, Xiaosong Shen, Kunwei Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title | Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title_full | Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title_fullStr | Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title_full_unstemmed | Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title_short | Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer |
title_sort | identification of ten mitosis genes associated with tamoxifen resistance in breast cancer |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187086/ https://www.ncbi.nlm.nih.gov/pubmed/34113127 http://dx.doi.org/10.2147/OTT.S290426 |
work_keys_str_mv | AT sunxi identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer AT dingshuning identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer AT lushuangshuang identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer AT wangzheng identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer AT chenxiaosong identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer AT shenkunwei identificationoftenmitosisgenesassociatedwithtamoxifenresistanceinbreastcancer |