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Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury
Acute lung injury (ALI) and respiratory distress syndrome are common, potentially lethal injuries that predominantly occur following chest trauma. Circular RNAs (circRNAs) are stable conserved non-coding RNAs that are widely expressed in different organs. To the best of our knowledge, no previous st...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271735/ https://www.ncbi.nlm.nih.gov/pubmed/32509009 http://dx.doi.org/10.3892/etm.2020.8686 |
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author | Jiang, Yong Zhu, Feng Wu, Guo-Sheng Wang, Kang-An Wang, Chen Yu, Qing Zhu, Bang-Hui Sun, Yu Xia, Zhao-Fan |
author_facet | Jiang, Yong Zhu, Feng Wu, Guo-Sheng Wang, Kang-An Wang, Chen Yu, Qing Zhu, Bang-Hui Sun, Yu Xia, Zhao-Fan |
author_sort | Jiang, Yong |
collection | PubMed |
description | Acute lung injury (ALI) and respiratory distress syndrome are common, potentially lethal injuries that predominantly occur following chest trauma. Circular RNAs (circRNAs) are stable conserved non-coding RNAs that are widely expressed in different organs. To the best of our knowledge, no previous studies have shown whether circRNAs are involved in traumatic lung injury (TLI). The aim of the present study was to identify highly expressed circRNAs in plasma samples from patients with TLI and explore their potential functions in the pathogenesis of TLI. A high-throughput circRNA microarray was used to investigate the expression profile of circRNAs in plasma samples from five patients with TLI and paired control samples. Subsequently, a total of five abnormally expressed circRNAs were investigated using reverse transcription-quantitative PCR (RT-qPCR). A bioinformatics analysis was performed to predict a competitive endogenous RNA (ceRNA) network. In addition, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to identify the main biological processes and pathways. Finally, additional samples were tested to identify the expression profiles of the selected circRNAs. Among the 310 circRNAs that were highly expressed in the microarray analysis, 60 were upregulated and 250 were downregulated in patients with TLI. RT-qPCR results indicated that two downregulated circRNAs (circ_102927 and circ_100562) and one upregulated circRNA (circ_101523) matched the microarray results. The bioinformatics analysis constructed a targeting network based on the three validated circRNAs. GO and KEGG analyses identified the top ten enriched annotations. The expression of homo sapiens circular RNA 102927 (hsa_circRNA_102927) in the plasma of patients with TLI was 0.34-fold compared with the control group in expanded size validation. The results of the present study identified the differentially expressed circRNAs in the plasma of patients with TLI and provided evidence that highly expressed circRNAs involved in the ceRNA network may serve a role in the pathophysiology of TLI. |
format | Online Article Text |
id | pubmed-7271735 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-72717352020-06-05 Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury Jiang, Yong Zhu, Feng Wu, Guo-Sheng Wang, Kang-An Wang, Chen Yu, Qing Zhu, Bang-Hui Sun, Yu Xia, Zhao-Fan Exp Ther Med Articles Acute lung injury (ALI) and respiratory distress syndrome are common, potentially lethal injuries that predominantly occur following chest trauma. Circular RNAs (circRNAs) are stable conserved non-coding RNAs that are widely expressed in different organs. To the best of our knowledge, no previous studies have shown whether circRNAs are involved in traumatic lung injury (TLI). The aim of the present study was to identify highly expressed circRNAs in plasma samples from patients with TLI and explore their potential functions in the pathogenesis of TLI. A high-throughput circRNA microarray was used to investigate the expression profile of circRNAs in plasma samples from five patients with TLI and paired control samples. Subsequently, a total of five abnormally expressed circRNAs were investigated using reverse transcription-quantitative PCR (RT-qPCR). A bioinformatics analysis was performed to predict a competitive endogenous RNA (ceRNA) network. In addition, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to identify the main biological processes and pathways. Finally, additional samples were tested to identify the expression profiles of the selected circRNAs. Among the 310 circRNAs that were highly expressed in the microarray analysis, 60 were upregulated and 250 were downregulated in patients with TLI. RT-qPCR results indicated that two downregulated circRNAs (circ_102927 and circ_100562) and one upregulated circRNA (circ_101523) matched the microarray results. The bioinformatics analysis constructed a targeting network based on the three validated circRNAs. GO and KEGG analyses identified the top ten enriched annotations. The expression of homo sapiens circular RNA 102927 (hsa_circRNA_102927) in the plasma of patients with TLI was 0.34-fold compared with the control group in expanded size validation. The results of the present study identified the differentially expressed circRNAs in the plasma of patients with TLI and provided evidence that highly expressed circRNAs involved in the ceRNA network may serve a role in the pathophysiology of TLI. D.A. Spandidos 2020-07 2020-04-23 /pmc/articles/PMC7271735/ /pubmed/32509009 http://dx.doi.org/10.3892/etm.2020.8686 Text en Copyright: © Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Jiang, Yong Zhu, Feng Wu, Guo-Sheng Wang, Kang-An Wang, Chen Yu, Qing Zhu, Bang-Hui Sun, Yu Xia, Zhao-Fan Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title | Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title_full | Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title_fullStr | Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title_full_unstemmed | Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title_short | Microarray and bioinformatics analysis of circular RNAs expression profile in traumatic lung injury |
title_sort | microarray and bioinformatics analysis of circular rnas expression profile in traumatic lung injury |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7271735/ https://www.ncbi.nlm.nih.gov/pubmed/32509009 http://dx.doi.org/10.3892/etm.2020.8686 |
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