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Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients

The model of immune-related lncRNA pairs (IRLPs) seems to be an available predictor in lung adenocarcinoma (LUAD) patients. The aim of our study was to construct a model with IRLPs to predict the survival status and immune landscape of LUAD patients. Based on TCGA-LUAD dataset, a risk assessment mod...

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Autores principales: Liu, Junhui, Wu, Hao, Gao, Zhaojia, Lou, Ming, Yuan, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806830/
https://www.ncbi.nlm.nih.gov/pubmed/34288805
http://dx.doi.org/10.1080/21655979.2021.1953215
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author Liu, Junhui
Wu, Hao
Gao, Zhaojia
Lou, Ming
Yuan, Kai
author_facet Liu, Junhui
Wu, Hao
Gao, Zhaojia
Lou, Ming
Yuan, Kai
author_sort Liu, Junhui
collection PubMed
description The model of immune-related lncRNA pairs (IRLPs) seems to be an available predictor in lung adenocarcinoma (LUAD) patients. The aim of our study was to construct a model with IRLPs to predict the survival status and immune landscape of LUAD patients. Based on TCGA-LUAD dataset, a risk assessment model with IRLPs was established. Then, ROC curves were used to assess the predictive accuracy and effectiveness of our model. Next, we identified the difference of survival, immune cell infiltration, immune checkpoint inhibitor-related (ICI-related) biomarkers, and chemotherapeutics between high-risk group and low-risk group. Finally, A nomogram was built for predicting the survival rates of LUAD patients. 464 LUAD samples were randomly and equally divided into a training set and a test set. Six IRLPs were screened out to construct a risk model. K-M analysis and risk-plot suggested the prognosis of high-risk group was worse than low-risk group (p < 0.001). Multivariate analysis shows risk score was independent risk factor of LUAD (p < 0.001). In addition, the expression of immune cell infiltration, ICI-related biomarkers, chemotherapeutics all demonstrate significant difference in two groups. A nomogram was built that could predict the 1-, 3-, and 5-year survival rates of LUAD patients. Our immune-related lncRNA pairs risk model is expected to be a reliable model for predicting the prognosis and immune landscape of LUAD patients.
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spelling pubmed-88068302022-02-02 Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients Liu, Junhui Wu, Hao Gao, Zhaojia Lou, Ming Yuan, Kai Bioengineered Research Paper The model of immune-related lncRNA pairs (IRLPs) seems to be an available predictor in lung adenocarcinoma (LUAD) patients. The aim of our study was to construct a model with IRLPs to predict the survival status and immune landscape of LUAD patients. Based on TCGA-LUAD dataset, a risk assessment model with IRLPs was established. Then, ROC curves were used to assess the predictive accuracy and effectiveness of our model. Next, we identified the difference of survival, immune cell infiltration, immune checkpoint inhibitor-related (ICI-related) biomarkers, and chemotherapeutics between high-risk group and low-risk group. Finally, A nomogram was built for predicting the survival rates of LUAD patients. 464 LUAD samples were randomly and equally divided into a training set and a test set. Six IRLPs were screened out to construct a risk model. K-M analysis and risk-plot suggested the prognosis of high-risk group was worse than low-risk group (p < 0.001). Multivariate analysis shows risk score was independent risk factor of LUAD (p < 0.001). In addition, the expression of immune cell infiltration, ICI-related biomarkers, chemotherapeutics all demonstrate significant difference in two groups. A nomogram was built that could predict the 1-, 3-, and 5-year survival rates of LUAD patients. Our immune-related lncRNA pairs risk model is expected to be a reliable model for predicting the prognosis and immune landscape of LUAD patients. Taylor & Francis 2021-07-21 /pmc/articles/PMC8806830/ /pubmed/34288805 http://dx.doi.org/10.1080/21655979.2021.1953215 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (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 Research Paper
Liu, Junhui
Wu, Hao
Gao, Zhaojia
Lou, Ming
Yuan, Kai
Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title_full Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title_fullStr Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title_full_unstemmed Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title_short Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
title_sort construction of an immune-related lncrna pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806830/
https://www.ncbi.nlm.nih.gov/pubmed/34288805
http://dx.doi.org/10.1080/21655979.2021.1953215
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