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Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma
The interactions of microRNAs (miRNAs), transcription factors (TFs) and their common target long non-coding RNAs (lncRNAs) can lead to the production of TF-miRNA-lncRNA (TML) network motifs. These motifs are functional regulators that perform a wide range of biological processes, such as carcinogene...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323226/ https://www.ncbi.nlm.nih.gov/pubmed/30569133 http://dx.doi.org/10.3892/mmr.2018.9769 |
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author | Zhao, Shuai Chen, Hong Ding, Beichen Li, Jianing Lv, Fuzhen Han, Kaiyu Zhou, Dan Yu, Baiquan Yu, Yao Zhang, Wei |
author_facet | Zhao, Shuai Chen, Hong Ding, Beichen Li, Jianing Lv, Fuzhen Han, Kaiyu Zhou, Dan Yu, Baiquan Yu, Yao Zhang, Wei |
author_sort | Zhao, Shuai |
collection | PubMed |
description | The interactions of microRNAs (miRNAs), transcription factors (TFs) and their common target long non-coding RNAs (lncRNAs) can lead to the production of TF-miRNA-lncRNA (TML) network motifs. These motifs are functional regulators that perform a wide range of biological processes, such as carcinogenesis. However, TML network motifs have not been systematically identified, and their roles in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) are largely unknown. In the present study, a computational integration approach was performed using multiple sources in order to construct a global TML network for LUAD and LUSC. The analysis revealed several dysregulated TML network motifs, which were common between the two lung cancer subtypes or specific to a single cancer subtype. In addition, functional analysis further indicated that the TML network motifs may potentially serve as putative biomarkers in LUAD and LUSC. The associations between drug treatments and dysregulated TML network motifs were also examined. Collectively, the present study elucidated the roles of TML network motifs in LUAD and LUSC, which may be beneficial for understanding the pathogenesis of lung cancer and its potential treatment. |
format | Online Article Text |
id | pubmed-6323226 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-63232262019-01-15 Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma Zhao, Shuai Chen, Hong Ding, Beichen Li, Jianing Lv, Fuzhen Han, Kaiyu Zhou, Dan Yu, Baiquan Yu, Yao Zhang, Wei Mol Med Rep Articles The interactions of microRNAs (miRNAs), transcription factors (TFs) and their common target long non-coding RNAs (lncRNAs) can lead to the production of TF-miRNA-lncRNA (TML) network motifs. These motifs are functional regulators that perform a wide range of biological processes, such as carcinogenesis. However, TML network motifs have not been systematically identified, and their roles in lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) are largely unknown. In the present study, a computational integration approach was performed using multiple sources in order to construct a global TML network for LUAD and LUSC. The analysis revealed several dysregulated TML network motifs, which were common between the two lung cancer subtypes or specific to a single cancer subtype. In addition, functional analysis further indicated that the TML network motifs may potentially serve as putative biomarkers in LUAD and LUSC. The associations between drug treatments and dysregulated TML network motifs were also examined. Collectively, the present study elucidated the roles of TML network motifs in LUAD and LUSC, which may be beneficial for understanding the pathogenesis of lung cancer and its potential treatment. D.A. Spandidos 2019-02 2018-12-14 /pmc/articles/PMC6323226/ /pubmed/30569133 http://dx.doi.org/10.3892/mmr.2018.9769 Text en Copyright: © Zhao 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 Zhao, Shuai Chen, Hong Ding, Beichen Li, Jianing Lv, Fuzhen Han, Kaiyu Zhou, Dan Yu, Baiquan Yu, Yao Zhang, Wei Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title | Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title_full | Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title_fullStr | Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title_full_unstemmed | Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title_short | Construction of a transcription factor-long non-coding RNA-microRNA network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
title_sort | construction of a transcription factor-long non-coding rna-microrna network for the identification of key regulators in lung adenocarcinoma and lung squamous cell carcinoma |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323226/ https://www.ncbi.nlm.nih.gov/pubmed/30569133 http://dx.doi.org/10.3892/mmr.2018.9769 |
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