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Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma
A number of experimental and computational studies have demonstrated the key roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the tumorigenesis of lung adenocarcinoma (LUAC). However, there remains a requirement for prognostic candidate biomarkers acting as ceR...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196588/ https://www.ncbi.nlm.nih.gov/pubmed/30272355 http://dx.doi.org/10.3892/or.2018.6719 |
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author | Wang, Xiaojuan Ding, Yawen Da, Bangming Fei, Yan Feng, Gang |
author_facet | Wang, Xiaojuan Ding, Yawen Da, Bangming Fei, Yan Feng, Gang |
author_sort | Wang, Xiaojuan |
collection | PubMed |
description | A number of experimental and computational studies have demonstrated the key roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the tumorigenesis of lung adenocarcinoma (LUAC). However, there remains a requirement for prognostic candidate biomarkers acting as ceRNAs for the prediction of overall survival in patients with LUAC. The main goal of the present study was to identify novel lncRNAs associated with LUAC overall survival and assess their prognostic values. The study analyzed coding RNA and ncRNA expression profiles of patients with LUAC by retrieving existing RNA-sequencing datasets from The Cancer Genome Atlas database, and 2,507 differentially expressed mRNAs, 1,633 lncRNAs and 113 miRNAs were screened from patients with LUAC compared with those of adjacent normal samples (P<0.01 and |logFC|>2). Of these LUAC-specific RNAs, 134 lncRNAs, 21 miRNAs and 34 mRNAs were used to build an lncRNA-mRNA-miRNA ceRNA network, among which 8 lncRNAs and 9 mRNAs were associated with overall survival in patients with LUAC by acting as ceRNAs. Next, an lncRNA-based prognostic signature was constructed by risk scoring approach based on the expression levels of 9 prognosis-associated lncRNAs using Cox's regression analysis. Moreover, the prognostic capacity of the 9-lncRNA signature was independent of known clinical prognostic factors. These results provide novel insight into the potential of lncRNA ceRNAs to be candidate biomarkers associated with LUAC overall survival. |
format | Online Article Text |
id | pubmed-6196588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-61965882018-10-23 Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma Wang, Xiaojuan Ding, Yawen Da, Bangming Fei, Yan Feng, Gang Oncol Rep Articles A number of experimental and computational studies have demonstrated the key roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the tumorigenesis of lung adenocarcinoma (LUAC). However, there remains a requirement for prognostic candidate biomarkers acting as ceRNAs for the prediction of overall survival in patients with LUAC. The main goal of the present study was to identify novel lncRNAs associated with LUAC overall survival and assess their prognostic values. The study analyzed coding RNA and ncRNA expression profiles of patients with LUAC by retrieving existing RNA-sequencing datasets from The Cancer Genome Atlas database, and 2,507 differentially expressed mRNAs, 1,633 lncRNAs and 113 miRNAs were screened from patients with LUAC compared with those of adjacent normal samples (P<0.01 and |logFC|>2). Of these LUAC-specific RNAs, 134 lncRNAs, 21 miRNAs and 34 mRNAs were used to build an lncRNA-mRNA-miRNA ceRNA network, among which 8 lncRNAs and 9 mRNAs were associated with overall survival in patients with LUAC by acting as ceRNAs. Next, an lncRNA-based prognostic signature was constructed by risk scoring approach based on the expression levels of 9 prognosis-associated lncRNAs using Cox's regression analysis. Moreover, the prognostic capacity of the 9-lncRNA signature was independent of known clinical prognostic factors. These results provide novel insight into the potential of lncRNA ceRNAs to be candidate biomarkers associated with LUAC overall survival. D.A. Spandidos 2018-12 2018-09-21 /pmc/articles/PMC6196588/ /pubmed/30272355 http://dx.doi.org/10.3892/or.2018.6719 Text en Copyright: © Wang 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 Wang, Xiaojuan Ding, Yawen Da, Bangming Fei, Yan Feng, Gang Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title | Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title_full | Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title_fullStr | Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title_full_unstemmed | Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title_short | Identification of potential prognostic long non-coding RNA signatures based on a competing endogenous RNA network in lung adenocarcinoma |
title_sort | identification of potential prognostic long non-coding rna signatures based on a competing endogenous rna network in lung adenocarcinoma |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6196588/ https://www.ncbi.nlm.nih.gov/pubmed/30272355 http://dx.doi.org/10.3892/or.2018.6719 |
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