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Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma
Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cance...
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/PMC9614324/ https://www.ncbi.nlm.nih.gov/pubmed/36313444 http://dx.doi.org/10.3389/fgene.2022.1016871 |
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author | Lv, Yanju Xiao, Yajie Cui, Xiaoli Luo, Haitao Xu, Long |
author_facet | Lv, Yanju Xiao, Yajie Cui, Xiaoli Luo, Haitao Xu, Long |
author_sort | Lv, Yanju |
collection | PubMed |
description | Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD. Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy. Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application. |
format | Online Article Text |
id | pubmed-9614324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96143242022-10-29 Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma Lv, Yanju Xiao, Yajie Cui, Xiaoli Luo, Haitao Xu, Long Front Genet Genetics Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD. Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy. Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application. Frontiers Media S.A. 2022-10-14 /pmc/articles/PMC9614324/ /pubmed/36313444 http://dx.doi.org/10.3389/fgene.2022.1016871 Text en Copyright © 2022 Lv, Xiao, Cui, Luo and Xu. 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 Lv, Yanju Xiao, Yajie Cui, Xiaoli Luo, Haitao Xu, Long Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title | Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title_full | Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title_fullStr | Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title_full_unstemmed | Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title_short | Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
title_sort | identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614324/ https://www.ncbi.nlm.nih.gov/pubmed/36313444 http://dx.doi.org/10.3389/fgene.2022.1016871 |
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