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已发表论文
使用基因芯片技术和生物信息学进行的 ER 阳性亚型乳腺癌长非编码 RNA 的基因表达谱分析
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
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
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
