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Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer

BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. LncRNAs regulate gene expression at various levels as RNAs; thus, both autophagy and lncRNAs are closely related to the occurrence and development of tumours. METHODS: A total of 232 autophagy-related genes were used to construct...

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Autores principales: Zhang, Xinyang, Cao, Yu, Chen, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364711/
https://www.ncbi.nlm.nih.gov/pubmed/34391383
http://dx.doi.org/10.1186/s12885-021-08654-2
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author Zhang, Xinyang
Cao, Yu
Chen, Li
author_facet Zhang, Xinyang
Cao, Yu
Chen, Li
author_sort Zhang, Xinyang
collection PubMed
description BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. LncRNAs regulate gene expression at various levels as RNAs; thus, both autophagy and lncRNAs are closely related to the occurrence and development of tumours. METHODS: A total of 232 autophagy-related genes were used to construct a coexpression network to extract autophagy-related lncRNAs. A prognostic signature was constructed by multivariate regression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was applied to analyse enrichment in cancer-related pathways. Immune infiltration analysis was used to analyse the relationship between the prognostic signature and the tumour microenvironment. RESULTS: Nine autophagy-related lncRNAs were used to construct a prognostic model for non-small-cell lung cancer. The median risk score was used to discriminate the high- and low-risk groups, and the low-risk group was found to have better survival. Because KEGG pathway analysis showed that the prognostic signature was enriched in some immune pathways, further analysis of immune infiltration was conducted, and it was found that the prognostic signature did play a unique role in the immune microenvironment. Additionally, the prognostic signature was associated with clinical factors. CONCLUSION: We constructed a prognostic model of autophagy-related lncRNAs that can predict the prognosis of non-small-cell lung cancer.
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spelling pubmed-83647112021-08-17 Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer Zhang, Xinyang Cao, Yu Chen, Li BMC Cancer Research BACKGROUND: Autophagy inhibits tumorigenesis by limiting inflammation. LncRNAs regulate gene expression at various levels as RNAs; thus, both autophagy and lncRNAs are closely related to the occurrence and development of tumours. METHODS: A total of 232 autophagy-related genes were used to construct a coexpression network to extract autophagy-related lncRNAs. A prognostic signature was constructed by multivariate regression analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was applied to analyse enrichment in cancer-related pathways. Immune infiltration analysis was used to analyse the relationship between the prognostic signature and the tumour microenvironment. RESULTS: Nine autophagy-related lncRNAs were used to construct a prognostic model for non-small-cell lung cancer. The median risk score was used to discriminate the high- and low-risk groups, and the low-risk group was found to have better survival. Because KEGG pathway analysis showed that the prognostic signature was enriched in some immune pathways, further analysis of immune infiltration was conducted, and it was found that the prognostic signature did play a unique role in the immune microenvironment. Additionally, the prognostic signature was associated with clinical factors. CONCLUSION: We constructed a prognostic model of autophagy-related lncRNAs that can predict the prognosis of non-small-cell lung cancer. BioMed Central 2021-08-14 /pmc/articles/PMC8364711/ /pubmed/34391383 http://dx.doi.org/10.1186/s12885-021-08654-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhang, Xinyang
Cao, Yu
Chen, Li
Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title_full Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title_fullStr Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title_full_unstemmed Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title_short Construction of a prognostic signature of autophagy-related lncRNAs in non-small-cell lung cancer
title_sort construction of a prognostic signature of autophagy-related lncrnas in non-small-cell lung cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8364711/
https://www.ncbi.nlm.nih.gov/pubmed/34391383
http://dx.doi.org/10.1186/s12885-021-08654-2
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