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Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma
Glioblastoma (GBM), originating in the brain, is a universally aggressive malignant tumor with a particularly poor prognosis. Therefore, insight into the critical role of underlying genetic mechanisms is essential to developing new therapeutic approaches. This study aims to identify potential marker...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8882732/ https://www.ncbi.nlm.nih.gov/pubmed/35237295 http://dx.doi.org/10.3389/fgene.2021.803257 |
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author | Liu, Ruifei Gao, Zhengzheng Li, Qiwei Fu, Qiang Han, Dongwei Wang, Jixi Li, Ji Guo, Ying Shi, Yuchen |
author_facet | Liu, Ruifei Gao, Zhengzheng Li, Qiwei Fu, Qiang Han, Dongwei Wang, Jixi Li, Ji Guo, Ying Shi, Yuchen |
author_sort | Liu, Ruifei |
collection | PubMed |
description | Glioblastoma (GBM), originating in the brain, is a universally aggressive malignant tumor with a particularly poor prognosis. Therefore, insight into the critical role of underlying genetic mechanisms is essential to developing new therapeutic approaches. This study aims to identify potential markers with clinical and prognostic significance in GBM. To this end, increasing numbers of differentially expressed RNA have been identified used to construct competitive endogenous RNA networks for prognostic analysis via comparison and analysis of RNA expression levels of tumor and normal tissues in glioblastoma. This analysis demonstrated that the RNA expression patterns of normal and tumor samples were significantly different. Thus, the resulting differentially expressed RNAs were used to construct competitive endogenous RNA (competing endogenous RNA, ceRNA) networks. The functional enrichment indicated mRNAs in the network are critically involved in a variety of biological functions. Additionally, the prognostic analysis suggested 27 lncRNAs, including LOXL1-AS1, AL356414.1, etc., were significantly associated with patient survival. Given the prognostic significance of these 27 lncRNAs in GBM, we sought to classify the samples. Importantly, Kaplan-Meier analysis revealed that survival times varied significantly among the different categories. Overall, these results identify that the candidate lncRNAs are potential prognostic markers of GBM and its corresponding mRNAs may be a potential target for therapy. |
format | Online Article Text |
id | pubmed-8882732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88827322022-03-01 Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma Liu, Ruifei Gao, Zhengzheng Li, Qiwei Fu, Qiang Han, Dongwei Wang, Jixi Li, Ji Guo, Ying Shi, Yuchen Front Genet Genetics Glioblastoma (GBM), originating in the brain, is a universally aggressive malignant tumor with a particularly poor prognosis. Therefore, insight into the critical role of underlying genetic mechanisms is essential to developing new therapeutic approaches. This study aims to identify potential markers with clinical and prognostic significance in GBM. To this end, increasing numbers of differentially expressed RNA have been identified used to construct competitive endogenous RNA networks for prognostic analysis via comparison and analysis of RNA expression levels of tumor and normal tissues in glioblastoma. This analysis demonstrated that the RNA expression patterns of normal and tumor samples were significantly different. Thus, the resulting differentially expressed RNAs were used to construct competitive endogenous RNA (competing endogenous RNA, ceRNA) networks. The functional enrichment indicated mRNAs in the network are critically involved in a variety of biological functions. Additionally, the prognostic analysis suggested 27 lncRNAs, including LOXL1-AS1, AL356414.1, etc., were significantly associated with patient survival. Given the prognostic significance of these 27 lncRNAs in GBM, we sought to classify the samples. Importantly, Kaplan-Meier analysis revealed that survival times varied significantly among the different categories. Overall, these results identify that the candidate lncRNAs are potential prognostic markers of GBM and its corresponding mRNAs may be a potential target for therapy. Frontiers Media S.A. 2022-02-14 /pmc/articles/PMC8882732/ /pubmed/35237295 http://dx.doi.org/10.3389/fgene.2021.803257 Text en Copyright © 2022 Liu, Gao, Li, Fu, Han, Wang, Li, Guo and Shi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liu, Ruifei Gao, Zhengzheng Li, Qiwei Fu, Qiang Han, Dongwei Wang, Jixi Li, Ji Guo, Ying Shi, Yuchen Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title | Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title_full | Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title_fullStr | Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title_full_unstemmed | Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title_short | Integrated Analysis of ceRNA Network to Reveal Potential Prognostic Biomarkers for Glioblastoma |
title_sort | integrated analysis of cerna network to reveal potential prognostic biomarkers for glioblastoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8882732/ https://www.ncbi.nlm.nih.gov/pubmed/35237295 http://dx.doi.org/10.3389/fgene.2021.803257 |
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