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

Authors Peng J, Zhang L, Yuan CW, Zhou LH, Xu SG, Lin YP, Zhang J, Yin WJ, Lu JS

Received 7 September 2017

Accepted for publication 1 November 2017

Published 14 December 2017 Volume 2017:9 Pages 891—901

DOI https://doi.org/10.2147/CMAR.S151120

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Akshita Wason

Peer reviewer comments 2

Editor who approved publication: Professor Nakshatri


Jing Peng,* Lei Zhang,* Chenwei Yuan, Liheng Zhou, Shuguang Xu, Yanping Lin, Jie Zhang, Wenjin Yin, Jinsong Lu

Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, People’s Republic of China

*These authors contributed equally to this work

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.

Keywords: breast cancer, long noncoding RNA, estrogen receptor

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