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A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma

Background: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research. Methods: We calculated the immune scor...

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Detalles Bibliográficos
Autores principales: Lu, Songmei, Shan, Nan, Chen, Xingyue, Peng, Fangliang, Wang, Yiming, Long, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714149/
https://www.ncbi.nlm.nih.gov/pubmed/34905504
http://dx.doi.org/10.18632/aging.203772
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author Lu, Songmei
Shan, Nan
Chen, Xingyue
Peng, Fangliang
Wang, Yiming
Long, Hao
author_facet Lu, Songmei
Shan, Nan
Chen, Xingyue
Peng, Fangliang
Wang, Yiming
Long, Hao
author_sort Lu, Songmei
collection PubMed
description Background: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research. Methods: We calculated the immune score of each sample according to the expression levels of immune-related genes (IRGs) and screened the survival-related IRLNRs (sIRLNRs) by Cox regression analysis. The expression levels of AC068338.3 and AL691432.2 in tissues and cell lines were confirmed by RT-qPCR. Results: 36 IRLNRs were selected by Pearson correlation analysis. Ten sIRLNRs were significantly correlated with the clinical outcomes of LUAC patients. Five sIRLNRs were identified by multivariate COX regression analysis to establish the immune-related risk score model (IRRS). The overall survival (OS) in the high-risk group was shorter than that in the low-risk group. IRRS could be an independent prognostic factor with significant survival correlation The distributions of immune gene concentrations were different between high-risk group and low-risk group. Furthermore, we further verified that the expression levels of AC068338.3 and AL691432.2 in different LUAC cell lines and tumor tissues were lower than that in Human bronchial epithelial cell (HBE) and adjacent tissues respectively. The lower expression levels of AC068338.3 and AL691432.2 were detected with the more advance T-stages. Conclusions: Our results highlighted some sIRLNRs with significant clinical correlations and demonstrated their monitored and prognostic values for LUAC patients. The results of this study may provide a new perspective for immunological research and immunotherapy strategies.
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spelling pubmed-87141492021-12-29 A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma Lu, Songmei Shan, Nan Chen, Xingyue Peng, Fangliang Wang, Yiming Long, Hao Aging (Albany NY) Research Paper Background: The abundant immune-related long non-coding RNA (IRLNRs) in immune cells and immune microenvironment have the potential to forecast prognosis and evaluate the effect of immunotherapy. IRLNRs analysis will provide a new perspective for LUAC research. Methods: We calculated the immune score of each sample according to the expression levels of immune-related genes (IRGs) and screened the survival-related IRLNRs (sIRLNRs) by Cox regression analysis. The expression levels of AC068338.3 and AL691432.2 in tissues and cell lines were confirmed by RT-qPCR. Results: 36 IRLNRs were selected by Pearson correlation analysis. Ten sIRLNRs were significantly correlated with the clinical outcomes of LUAC patients. Five sIRLNRs were identified by multivariate COX regression analysis to establish the immune-related risk score model (IRRS). The overall survival (OS) in the high-risk group was shorter than that in the low-risk group. IRRS could be an independent prognostic factor with significant survival correlation The distributions of immune gene concentrations were different between high-risk group and low-risk group. Furthermore, we further verified that the expression levels of AC068338.3 and AL691432.2 in different LUAC cell lines and tumor tissues were lower than that in Human bronchial epithelial cell (HBE) and adjacent tissues respectively. The lower expression levels of AC068338.3 and AL691432.2 were detected with the more advance T-stages. Conclusions: Our results highlighted some sIRLNRs with significant clinical correlations and demonstrated their monitored and prognostic values for LUAC patients. The results of this study may provide a new perspective for immunological research and immunotherapy strategies. Impact Journals 2021-12-14 /pmc/articles/PMC8714149/ /pubmed/34905504 http://dx.doi.org/10.18632/aging.203772 Text en Copyright: © 2021 Lu et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Lu, Songmei
Shan, Nan
Chen, Xingyue
Peng, Fangliang
Wang, Yiming
Long, Hao
A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title_full A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title_fullStr A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title_full_unstemmed A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title_short A novel immune-related long non-coding RNAs risk model for prognosis assessment of lung adenocarcinoma
title_sort novel immune-related long non-coding rnas risk model for prognosis assessment of lung adenocarcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714149/
https://www.ncbi.nlm.nih.gov/pubmed/34905504
http://dx.doi.org/10.18632/aging.203772
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