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Explore prognostic biomarker of bladder cancer based on competing endogenous network
Bladder cancer (BC) is the most common tumor of the urinary tract. Increasing evidence showed that long non-coding RNA (lncRNA) is a critical regulator in cancer development and progression. However, the functions of lncRNAs in the development of BC remain mostly undefined. In the present study, bas...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Portland Press Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711062/ https://www.ncbi.nlm.nih.gov/pubmed/33169791 http://dx.doi.org/10.1042/BSR20202463 |
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author | Li, Faping Guo, Hui Liu, Bin Liu, Nian Xu, Zhixiang Wang, Yishu Zhou, Honglan |
author_facet | Li, Faping Guo, Hui Liu, Bin Liu, Nian Xu, Zhixiang Wang, Yishu Zhou, Honglan |
author_sort | Li, Faping |
collection | PubMed |
description | Bladder cancer (BC) is the most common tumor of the urinary tract. Increasing evidence showed that long non-coding RNA (lncRNA) is a critical regulator in cancer development and progression. However, the functions of lncRNAs in the development of BC remain mostly undefined. In the present study, based on RNA sequence profiles from The Cancer Genome Atlas database, we identified 723 lncRNAs, 157 miRNAs, and 1816 mRNAs aberrantly expressed in BC tissues. A competing endogenous RNA network, including 49 lncRNAs, 17 miRNAs, and 36 mRNAs, was then established. The functional enrichment analyses showed that the mRNAs in the ceRNA network mainly participated in ‘regulation of transcription’ and ‘pathways in cancer’. Moreover, the Cox regression analyses demonstrated that three lncRNAs (AC112721.1, TMPRSS11GP, and ADAMTS9-AS1) could serve as independent risk factors. We established a risk prediction model with these lncRNAs. Kaplan–Meier curve analysis showed that high-risk patients’ prognosis was lower than that of low-risk patients (P=0.001). The present study provides novel insights into the lncRNA-mediated ceRNA network and the potential of lncRNAs to be candidate prognostic biomarkers in BC, which could help better understand the pathological changes and pathogenesis of BC and be useful for clinical studies in the future. |
format | Online Article Text |
id | pubmed-7711062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Portland Press Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77110622020-12-08 Explore prognostic biomarker of bladder cancer based on competing endogenous network Li, Faping Guo, Hui Liu, Bin Liu, Nian Xu, Zhixiang Wang, Yishu Zhou, Honglan Biosci Rep Bioinformatics Bladder cancer (BC) is the most common tumor of the urinary tract. Increasing evidence showed that long non-coding RNA (lncRNA) is a critical regulator in cancer development and progression. However, the functions of lncRNAs in the development of BC remain mostly undefined. In the present study, based on RNA sequence profiles from The Cancer Genome Atlas database, we identified 723 lncRNAs, 157 miRNAs, and 1816 mRNAs aberrantly expressed in BC tissues. A competing endogenous RNA network, including 49 lncRNAs, 17 miRNAs, and 36 mRNAs, was then established. The functional enrichment analyses showed that the mRNAs in the ceRNA network mainly participated in ‘regulation of transcription’ and ‘pathways in cancer’. Moreover, the Cox regression analyses demonstrated that three lncRNAs (AC112721.1, TMPRSS11GP, and ADAMTS9-AS1) could serve as independent risk factors. We established a risk prediction model with these lncRNAs. Kaplan–Meier curve analysis showed that high-risk patients’ prognosis was lower than that of low-risk patients (P=0.001). The present study provides novel insights into the lncRNA-mediated ceRNA network and the potential of lncRNAs to be candidate prognostic biomarkers in BC, which could help better understand the pathological changes and pathogenesis of BC and be useful for clinical studies in the future. Portland Press Ltd. 2020-12-02 /pmc/articles/PMC7711062/ /pubmed/33169791 http://dx.doi.org/10.1042/BSR20202463 Text en © 2020 The Author(s). https://creativecommons.org/licenses/by/4.0/ This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the . |
spellingShingle | Bioinformatics Li, Faping Guo, Hui Liu, Bin Liu, Nian Xu, Zhixiang Wang, Yishu Zhou, Honglan Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title | Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title_full | Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title_fullStr | Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title_full_unstemmed | Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title_short | Explore prognostic biomarker of bladder cancer based on competing endogenous network |
title_sort | explore prognostic biomarker of bladder cancer based on competing endogenous network |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711062/ https://www.ncbi.nlm.nih.gov/pubmed/33169791 http://dx.doi.org/10.1042/BSR20202463 |
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