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Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy

BACKGROUND: Tamoxifen is the first-line hormone therapy for estrogen receptor alpha positive (ERα+) breast cancer. However, about 40% of patients with ERα + breast cancer who receive tamoxifen therapy eventually develop resistance resulting in a poor prognosis. The aim of this study was to mine avai...

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Autores principales: Zhu, Qiong-Ni, Renaud, Helen, Guo, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769523/
https://www.ncbi.nlm.nih.gov/pubmed/29371858
http://dx.doi.org/10.1186/s41065-018-0055-7
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author Zhu, Qiong-Ni
Renaud, Helen
Guo, Ying
author_facet Zhu, Qiong-Ni
Renaud, Helen
Guo, Ying
author_sort Zhu, Qiong-Ni
collection PubMed
description BACKGROUND: Tamoxifen is the first-line hormone therapy for estrogen receptor alpha positive (ERα+) breast cancer. However, about 40% of patients with ERα + breast cancer who receive tamoxifen therapy eventually develop resistance resulting in a poor prognosis. The aim of this study was to mine available data sets in the Gene Expression Omnibus (GEO) database, including in vitro (cell lines) and in vivo (tissue samples), and to identify all miRNAs associated with tamoxifen resistance (TamR) in breast cancer. Secondly, this study aimed to predict the key gene regulatory networks of newly found TamR-related miRNAs and evaluate the potential role of the miRNAs and targets as potential prognosis biomarkers for breast cancer patients. RESULT: Microarray data sets from two different studies were used from the GEO database: 1. GSE66607: miRNA of MCF-7 TamR cells; 2. GSE37405: TamR tissues. Differentially expressed microRNAs (miRNAs) were identified in both data sets and 5 differentially expressed miRNAs were found to overlap between the two data sets. Profiles of GSE37405 and data from the Kaplan-Meier Plotter Database (KMPD) along with Gene Expression Profiling Interactive Analysis (GEPIA) were used to reveal the relationship between these 5 miRNAs and overall survival. The results showed that has-miR-542-5p was the only miRNA associated with overall survival of ERα + breast cancer patients who received adjuvant tamoxifen. Targets of has-miR-542-5p were predicted by miRanda and TargetScan, and the mRNA expression of the three 3 target gene, Tyrosine 3-Monooxygenase/Tryptophan 5-Monooxygenase Activation Protein Beta (YWHAB), Lymphocyte Antigen 9 (LY9), and Secreted Frizzled Related Protein 1 (SFRP1) were associated with overall survival in 2 different databases. Copy-number alterations (CNAs) of SFRP1 confer survival disadvantage to breast cancer patients and alter the mRNA expression of SFRP1 in cBioPortal database. CONCLUSION: This study indicates that miRNA has-miR-542-5p is associated with TamR and can predict prognosis of breast cancer patients. Furthermore, has-miR-542-5p may be acting through a mechanism involving the target genes YWHAB, LY9, and SFRP1. Overall, has-miR-542-5p is a predictive biomarker and potential target for therapy of breast cancer patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41065-018-0055-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-57695232018-01-25 Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy Zhu, Qiong-Ni Renaud, Helen Guo, Ying Hereditas Research BACKGROUND: Tamoxifen is the first-line hormone therapy for estrogen receptor alpha positive (ERα+) breast cancer. However, about 40% of patients with ERα + breast cancer who receive tamoxifen therapy eventually develop resistance resulting in a poor prognosis. The aim of this study was to mine available data sets in the Gene Expression Omnibus (GEO) database, including in vitro (cell lines) and in vivo (tissue samples), and to identify all miRNAs associated with tamoxifen resistance (TamR) in breast cancer. Secondly, this study aimed to predict the key gene regulatory networks of newly found TamR-related miRNAs and evaluate the potential role of the miRNAs and targets as potential prognosis biomarkers for breast cancer patients. RESULT: Microarray data sets from two different studies were used from the GEO database: 1. GSE66607: miRNA of MCF-7 TamR cells; 2. GSE37405: TamR tissues. Differentially expressed microRNAs (miRNAs) were identified in both data sets and 5 differentially expressed miRNAs were found to overlap between the two data sets. Profiles of GSE37405 and data from the Kaplan-Meier Plotter Database (KMPD) along with Gene Expression Profiling Interactive Analysis (GEPIA) were used to reveal the relationship between these 5 miRNAs and overall survival. The results showed that has-miR-542-5p was the only miRNA associated with overall survival of ERα + breast cancer patients who received adjuvant tamoxifen. Targets of has-miR-542-5p were predicted by miRanda and TargetScan, and the mRNA expression of the three 3 target gene, Tyrosine 3-Monooxygenase/Tryptophan 5-Monooxygenase Activation Protein Beta (YWHAB), Lymphocyte Antigen 9 (LY9), and Secreted Frizzled Related Protein 1 (SFRP1) were associated with overall survival in 2 different databases. Copy-number alterations (CNAs) of SFRP1 confer survival disadvantage to breast cancer patients and alter the mRNA expression of SFRP1 in cBioPortal database. CONCLUSION: This study indicates that miRNA has-miR-542-5p is associated with TamR and can predict prognosis of breast cancer patients. Furthermore, has-miR-542-5p may be acting through a mechanism involving the target genes YWHAB, LY9, and SFRP1. Overall, has-miR-542-5p is a predictive biomarker and potential target for therapy of breast cancer patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41065-018-0055-7) contains supplementary material, which is available to authorized users. BioMed Central 2018-01-15 /pmc/articles/PMC5769523/ /pubmed/29371858 http://dx.doi.org/10.1186/s41065-018-0055-7 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhu, Qiong-Ni
Renaud, Helen
Guo, Ying
Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title_full Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title_fullStr Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title_full_unstemmed Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title_short Bioinformatics-based identification of miR-542-5p as a predictive biomarker in breast cancer therapy
title_sort bioinformatics-based identification of mir-542-5p as a predictive biomarker in breast cancer therapy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5769523/
https://www.ncbi.nlm.nih.gov/pubmed/29371858
http://dx.doi.org/10.1186/s41065-018-0055-7
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