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An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients
Long non-coding RNAs (lncRNAs) can influence the proliferation, autophagy, and apoptosis of non-small cell lung cancer (NSCLC). LncRNAs also emerge as valuable prognostic factors for NSCLC patients. Consequently, we set out to discover more autophagy-associated lncRNAs. We acquired autophagy-associa...
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/PMC9479339/ https://www.ncbi.nlm.nih.gov/pubmed/36118862 http://dx.doi.org/10.3389/fgene.2022.919857 |
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author | Hu, Jing Zhang, Pei-Jin Zhang, Di Chen, Zhao-Hui Cao, Xu-Chen Yu, Yue Ge, Jie |
author_facet | Hu, Jing Zhang, Pei-Jin Zhang, Di Chen, Zhao-Hui Cao, Xu-Chen Yu, Yue Ge, Jie |
author_sort | Hu, Jing |
collection | PubMed |
description | Long non-coding RNAs (lncRNAs) can influence the proliferation, autophagy, and apoptosis of non-small cell lung cancer (NSCLC). LncRNAs also emerge as valuable prognostic factors for NSCLC patients. Consequently, we set out to discover more autophagy-associated lncRNAs. We acquired autophagy-associated genes and information on lncRNAs from The Cancer Genome Atlas database (TCGA), and the Human Autophagy Database (HADb). Then, the prognostic prediction signature was constructed through using co-expression and Cox regression analysis. The signature was constructed including 7 autophagy-associated lncRNAs (ABALON, NKILA, LINC00941, AL161431.1, AL691432.2, AC020765.2, MMP2-AS1). After that, we used univariate and multivariate Cox regression analysis to calculate the risk score. The survival analysis and ROC curve analysis confirmed good performances of the signature. GSEA indicated that the high-risk group was principally enriched in the adherens junction pathway. In addition, biological experiments showed that ABALON promoted the proliferation, metastasis and autophagy levels of NSCLC cells. These findings demonstrate that the risk signature consisting of 7 autophagy-associated lncRNAs accurately predicts the prognosis of NSCLC patients and should be investigated for potential therapeutic targets in clinic. |
format | Online Article Text |
id | pubmed-9479339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94793392022-09-17 An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients Hu, Jing Zhang, Pei-Jin Zhang, Di Chen, Zhao-Hui Cao, Xu-Chen Yu, Yue Ge, Jie Front Genet Genetics Long non-coding RNAs (lncRNAs) can influence the proliferation, autophagy, and apoptosis of non-small cell lung cancer (NSCLC). LncRNAs also emerge as valuable prognostic factors for NSCLC patients. Consequently, we set out to discover more autophagy-associated lncRNAs. We acquired autophagy-associated genes and information on lncRNAs from The Cancer Genome Atlas database (TCGA), and the Human Autophagy Database (HADb). Then, the prognostic prediction signature was constructed through using co-expression and Cox regression analysis. The signature was constructed including 7 autophagy-associated lncRNAs (ABALON, NKILA, LINC00941, AL161431.1, AL691432.2, AC020765.2, MMP2-AS1). After that, we used univariate and multivariate Cox regression analysis to calculate the risk score. The survival analysis and ROC curve analysis confirmed good performances of the signature. GSEA indicated that the high-risk group was principally enriched in the adherens junction pathway. In addition, biological experiments showed that ABALON promoted the proliferation, metastasis and autophagy levels of NSCLC cells. These findings demonstrate that the risk signature consisting of 7 autophagy-associated lncRNAs accurately predicts the prognosis of NSCLC patients and should be investigated for potential therapeutic targets in clinic. Frontiers Media S.A. 2022-09-02 /pmc/articles/PMC9479339/ /pubmed/36118862 http://dx.doi.org/10.3389/fgene.2022.919857 Text en Copyright © 2022 Hu, Zhang, Zhang, Chen, Cao, Yu and Ge. 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 Hu, Jing Zhang, Pei-Jin Zhang, Di Chen, Zhao-Hui Cao, Xu-Chen Yu, Yue Ge, Jie An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title | An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title_full | An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title_fullStr | An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title_full_unstemmed | An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title_short | An autophagy-associated lncRNAs model for predicting the survival in non-small cell lung cancer patients |
title_sort | autophagy-associated lncrnas model for predicting the survival in non-small cell lung cancer patients |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9479339/ https://www.ncbi.nlm.nih.gov/pubmed/36118862 http://dx.doi.org/10.3389/fgene.2022.919857 |
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