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A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors...

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Autores principales: Di, Huang, Zhao, Jiting, Zhu, Xue, Zhou, Xinpeng, Hu, Yuanlong, Wang, Mengjie, Qiu, Zhanjun, Zhang, Wei, Chen, Xianhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750635/
https://www.ncbi.nlm.nih.gov/pubmed/36626411
http://dx.doi.org/10.1097/MD.0000000000031924
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author Di, Huang
Zhao, Jiting
Zhu, Xue
Zhou, Xinpeng
Hu, Yuanlong
Wang, Mengjie
Qiu, Zhanjun
Zhang, Wei
Chen, Xianhai
author_facet Di, Huang
Zhao, Jiting
Zhu, Xue
Zhou, Xinpeng
Hu, Yuanlong
Wang, Mengjie
Qiu, Zhanjun
Zhang, Wei
Chen, Xianhai
author_sort Di, Huang
collection PubMed
description Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors in cancer patients. The effect of cuproptosis-related lncRNAs (CRlncRNAs) on LUAD has not been clarified. Based on the Cancer Genome Atlas database, CRlncRNAs were screened by co-expression analysis of cuproptosis- related genes and lncRNAs. Using CRlncRNAs, Cox and LASSO regression analyses constructed a risk prognostic model. The predictive efficacy of the model was assessed and validated using survival analysis, receiver operating characteristic curve, univariate and multifactor Cox regression analysis, and principal component analysis. A nomogram was constructed and calibration curves were applied to enhance the predictive efficacy of the model. Tumor Mutational Burden analysis and chemotherapeutic drug sensitivity prediction were performed to assess the clinical feasibility of the risk model. The novel prognostic signature consisted of 5 potentially high-risk CRlncRNAs, MAP3K20-AS1, CRIM1-DT, AC006213.3, AC008035.1, and NR2F2-AS1, and 5 potentially protective CRlncRNAs, AC090948.1, AL356481.1, AC011477.2, AL031600.2, and AC026355.2, which had accurate and robust predictive power for LUAD patients. Collectively, the novel prognostic signature constructed based on CRlncRNAs can effectively assess and predict the prognosis of patients and provide a new perspective for the diagnosis and treatment of LUAD.
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spelling pubmed-97506352022-12-28 A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review Di, Huang Zhao, Jiting Zhu, Xue Zhou, Xinpeng Hu, Yuanlong Wang, Mengjie Qiu, Zhanjun Zhang, Wei Chen, Xianhai Medicine (Baltimore) 5700 Lung adenocarcinoma (LUAD) is a highly heterogeneous disease with complex pathogenesis, high mortality, and poor prognosis. Cuproptosis is a new type of programmed cell death triggered by copper accumulation that may play an important role in cancer. LncRNAs are becoming valuable prognostic factors in cancer patients. The effect of cuproptosis-related lncRNAs (CRlncRNAs) on LUAD has not been clarified. Based on the Cancer Genome Atlas database, CRlncRNAs were screened by co-expression analysis of cuproptosis- related genes and lncRNAs. Using CRlncRNAs, Cox and LASSO regression analyses constructed a risk prognostic model. The predictive efficacy of the model was assessed and validated using survival analysis, receiver operating characteristic curve, univariate and multifactor Cox regression analysis, and principal component analysis. A nomogram was constructed and calibration curves were applied to enhance the predictive efficacy of the model. Tumor Mutational Burden analysis and chemotherapeutic drug sensitivity prediction were performed to assess the clinical feasibility of the risk model. The novel prognostic signature consisted of 5 potentially high-risk CRlncRNAs, MAP3K20-AS1, CRIM1-DT, AC006213.3, AC008035.1, and NR2F2-AS1, and 5 potentially protective CRlncRNAs, AC090948.1, AL356481.1, AC011477.2, AL031600.2, and AC026355.2, which had accurate and robust predictive power for LUAD patients. Collectively, the novel prognostic signature constructed based on CRlncRNAs can effectively assess and predict the prognosis of patients and provide a new perspective for the diagnosis and treatment of LUAD. Lippincott Williams & Wilkins 2022-12-09 /pmc/articles/PMC9750635/ /pubmed/36626411 http://dx.doi.org/10.1097/MD.0000000000031924 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 5700
Di, Huang
Zhao, Jiting
Zhu, Xue
Zhou, Xinpeng
Hu, Yuanlong
Wang, Mengjie
Qiu, Zhanjun
Zhang, Wei
Chen, Xianhai
A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title_full A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title_fullStr A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title_full_unstemmed A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title_short A novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncRNAs: A Review
title_sort novel prognostic signature for lung adenocarcinoma based on cuproptosis-related lncrnas: a review
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750635/
https://www.ncbi.nlm.nih.gov/pubmed/36626411
http://dx.doi.org/10.1097/MD.0000000000031924
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