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Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics

BACKGROUND: The estrogen receptor (ER)-positive subtype of breast cancer (BC) is the most common type of BC. A number of long noncoding RNAs (lncRNAs) play critical roles in cancer biology, including BC. Previous lncRNA profiling studies have focused only on triple-negative BC and HER 2-positive BC,...

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Autores principales: Peng, Jing, Zhang, Lei, Yuan, Chenwei, Zhou, Liheng, Xu, Shuguang, Lin, Yanping, Zhang, Jie, Yin, Wenjin, Lu, Jinsong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5733923/
https://www.ncbi.nlm.nih.gov/pubmed/29276409
http://dx.doi.org/10.2147/CMAR.S151120
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author Peng, Jing
Zhang, Lei
Yuan, Chenwei
Zhou, Liheng
Xu, Shuguang
Lin, Yanping
Zhang, Jie
Yin, Wenjin
Lu, Jinsong
author_facet Peng, Jing
Zhang, Lei
Yuan, Chenwei
Zhou, Liheng
Xu, Shuguang
Lin, Yanping
Zhang, Jie
Yin, Wenjin
Lu, Jinsong
author_sort Peng, Jing
collection PubMed
description BACKGROUND: The estrogen receptor (ER)-positive subtype of breast cancer (BC) is the most common type of BC. A number of long noncoding RNAs (lncRNAs) play critical roles in cancer biology, including BC. Previous lncRNA profiling studies have focused only on triple-negative BC and HER 2-positive BC, and no studies have specifically focused on lncRNAs in ER-positive BC. In this study, we analyzed the expression profile of the lncRNAs and mRNAs found in this particular subtype of BC for the first time. METHODS: We evaluated lncRNA microarray data from four pairs of primary BC and adjuvant nontumor breast tissues. Then, we screened out the differently expressed genes and measured the correlation of the expression levels of lncRNAs and ERalpha by Pearson’s correlation coefficient analysis. We also performed classification and length distribution of the dysregulated lncRNAs. KEGG pathway analysis was used to understand the biological roles of these differently expressed genes. lncRNA–mRNA coexpression networks were constructed. Finally, RT-PCR was employed to validate the microarray analysis findings. RESULTS: We screened out 2,178 differently expressed lncRNAs, and 13 lncRNAs were found to be associated with the ER expression level. Classification analysis showed that most lncRNAs belonged to intergenic lncRNA and were from 400 to 800 nt in length. Chromosome distribution showed that many of the lncRNAs were mapped to chromosome 1. In the pathway analysis, most of the genes were related to cancer-associated behaviors, such as p53 signaling pathway, cell cycle, focal adhesion, and ECM–receptor interaction. lncRNA–mRNA coexpression networks were constructed, and the lncRNAs related to ESR1, BRCA1, and BRCA2 in the two groups were significantly different. The RT-PCR results were consistent with the data obtained from the microarrays. CONCLUSION: These results provide useful information for exploring potential novel biomarkers as diagnosis and therapy targets for the clinical treatment of ER-positive BC.
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spelling pubmed-57339232017-12-22 Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics Peng, Jing Zhang, Lei Yuan, Chenwei Zhou, Liheng Xu, Shuguang Lin, Yanping Zhang, Jie Yin, Wenjin Lu, Jinsong Cancer Manag Res Original Research BACKGROUND: The estrogen receptor (ER)-positive subtype of breast cancer (BC) is the most common type of BC. A number of long noncoding RNAs (lncRNAs) play critical roles in cancer biology, including BC. Previous lncRNA profiling studies have focused only on triple-negative BC and HER 2-positive BC, and no studies have specifically focused on lncRNAs in ER-positive BC. In this study, we analyzed the expression profile of the lncRNAs and mRNAs found in this particular subtype of BC for the first time. METHODS: We evaluated lncRNA microarray data from four pairs of primary BC and adjuvant nontumor breast tissues. Then, we screened out the differently expressed genes and measured the correlation of the expression levels of lncRNAs and ERalpha by Pearson’s correlation coefficient analysis. We also performed classification and length distribution of the dysregulated lncRNAs. KEGG pathway analysis was used to understand the biological roles of these differently expressed genes. lncRNA–mRNA coexpression networks were constructed. Finally, RT-PCR was employed to validate the microarray analysis findings. RESULTS: We screened out 2,178 differently expressed lncRNAs, and 13 lncRNAs were found to be associated with the ER expression level. Classification analysis showed that most lncRNAs belonged to intergenic lncRNA and were from 400 to 800 nt in length. Chromosome distribution showed that many of the lncRNAs were mapped to chromosome 1. In the pathway analysis, most of the genes were related to cancer-associated behaviors, such as p53 signaling pathway, cell cycle, focal adhesion, and ECM–receptor interaction. lncRNA–mRNA coexpression networks were constructed, and the lncRNAs related to ESR1, BRCA1, and BRCA2 in the two groups were significantly different. The RT-PCR results were consistent with the data obtained from the microarrays. CONCLUSION: These results provide useful information for exploring potential novel biomarkers as diagnosis and therapy targets for the clinical treatment of ER-positive BC. Dove Medical Press 2017-12-14 /pmc/articles/PMC5733923/ /pubmed/29276409 http://dx.doi.org/10.2147/CMAR.S151120 Text en © 2017 Peng et al. 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/). 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.
spellingShingle Original Research
Peng, Jing
Zhang, Lei
Yuan, Chenwei
Zhou, Liheng
Xu, Shuguang
Lin, Yanping
Zhang, Jie
Yin, Wenjin
Lu, Jinsong
Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title_full Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title_fullStr Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title_full_unstemmed Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title_short Expression profile analysis of long noncoding RNA in ER-positive subtype breast cancer using microarray technique and bioinformatics
title_sort expression profile analysis of long noncoding rna in er-positive subtype breast cancer using microarray technique and bioinformatics
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5733923/
https://www.ncbi.nlm.nih.gov/pubmed/29276409
http://dx.doi.org/10.2147/CMAR.S151120
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