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The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma

BACKGROUND: Competitive Endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce. METHOD: The profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database. Bioinformatics methods we...

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Autores principales: Li, Jinglong, Liu, Wenyao, Dong, Xiaocheng, Dai, Yunfeng, Chen, Shaosen, Zhao, Enliang, Liu, Yunlong, Bao, Hongguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594182/
https://www.ncbi.nlm.nih.gov/pubmed/34781924
http://dx.doi.org/10.1186/s12885-021-08932-z
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author Li, Jinglong
Liu, Wenyao
Dong, Xiaocheng
Dai, Yunfeng
Chen, Shaosen
Zhao, Enliang
Liu, Yunlong
Bao, Hongguang
author_facet Li, Jinglong
Liu, Wenyao
Dong, Xiaocheng
Dai, Yunfeng
Chen, Shaosen
Zhao, Enliang
Liu, Yunlong
Bao, Hongguang
author_sort Li, Jinglong
collection PubMed
description BACKGROUND: Competitive Endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce. METHOD: The profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database. Bioinformatics methods were used to evaluate differentially-expressed genes (DEGs) and to form a ceRNA network. Preliminary verification of clinical specimens was utilized to detect the expressions of key biomarkers at the tissues. Cox and Lasso regressions were used to identify key genes, and prognosis prediction nomograms were formed. The mRNA levels of 9 genes in the risk score model in independent clinical LUAD samples were detected by qRT-PCR. The interconnection between the risk of cancer and immune cells was evaluated using the CIBERSORT algorithm, while the conformation of notable tumor-infiltrating immune cells (TIICs) in the LUAD tissues of the high and low risk groups was assessed using the RNA transcript subgroup in order to identify tissue types. Finally, co-expression study was used to examine the interconnection between the key genes in the ceRNA networks and the immune cells. RESULT: A ceRNA network of 115 RNAs was established, and nine key genes were identified to construct a Cox proportional-hazard model and create a prognostic nomogram. This risk-assessment model might serve as an independent factor to forecast the prognosis of LUAD, and it was consistent with the preliminary verification of clinical specimens. Survival analysis of clinical samples further validated the potential value of high risk groups in predicting LUAD prognosis. Five immune cells were identified with significant differences in the LUAD tissues of the high and low risk groups. Besides, two pairs of biomarkers associated with the growth of LUAD were found, i.e., E2F7 and macrophage M1 (R = 0.419, p = 1.4e(− 08)) and DBF4 and macrophage M1 (R = 0.282, p < 2.2 e(− 16)). CONCLUSION: This study identified several important ceRNAs, i.e. (E2F7 and BNF4) and TIICs (macrophage M1), which might be related to the development and prognosis of LUAD. The established risk-assessment model might be a potential tool in predicting LUAD of prognosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08932-z.
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spelling pubmed-85941822021-11-16 The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma Li, Jinglong Liu, Wenyao Dong, Xiaocheng Dai, Yunfeng Chen, Shaosen Zhao, Enliang Liu, Yunlong Bao, Hongguang BMC Cancer Research BACKGROUND: Competitive Endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce. METHOD: The profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database. Bioinformatics methods were used to evaluate differentially-expressed genes (DEGs) and to form a ceRNA network. Preliminary verification of clinical specimens was utilized to detect the expressions of key biomarkers at the tissues. Cox and Lasso regressions were used to identify key genes, and prognosis prediction nomograms were formed. The mRNA levels of 9 genes in the risk score model in independent clinical LUAD samples were detected by qRT-PCR. The interconnection between the risk of cancer and immune cells was evaluated using the CIBERSORT algorithm, while the conformation of notable tumor-infiltrating immune cells (TIICs) in the LUAD tissues of the high and low risk groups was assessed using the RNA transcript subgroup in order to identify tissue types. Finally, co-expression study was used to examine the interconnection between the key genes in the ceRNA networks and the immune cells. RESULT: A ceRNA network of 115 RNAs was established, and nine key genes were identified to construct a Cox proportional-hazard model and create a prognostic nomogram. This risk-assessment model might serve as an independent factor to forecast the prognosis of LUAD, and it was consistent with the preliminary verification of clinical specimens. Survival analysis of clinical samples further validated the potential value of high risk groups in predicting LUAD prognosis. Five immune cells were identified with significant differences in the LUAD tissues of the high and low risk groups. Besides, two pairs of biomarkers associated with the growth of LUAD were found, i.e., E2F7 and macrophage M1 (R = 0.419, p = 1.4e(− 08)) and DBF4 and macrophage M1 (R = 0.282, p < 2.2 e(− 16)). CONCLUSION: This study identified several important ceRNAs, i.e. (E2F7 and BNF4) and TIICs (macrophage M1), which might be related to the development and prognosis of LUAD. The established risk-assessment model might be a potential tool in predicting LUAD of prognosis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08932-z. BioMed Central 2021-11-16 /pmc/articles/PMC8594182/ /pubmed/34781924 http://dx.doi.org/10.1186/s12885-021-08932-z 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
Li, Jinglong
Liu, Wenyao
Dong, Xiaocheng
Dai, Yunfeng
Chen, Shaosen
Zhao, Enliang
Liu, Yunlong
Bao, Hongguang
The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title_full The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title_fullStr The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title_full_unstemmed The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title_short The construction and analysis of ceRNA network and patterns of immune infiltration in lung adenocarcinoma
title_sort construction and analysis of cerna network and patterns of immune infiltration in lung adenocarcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594182/
https://www.ncbi.nlm.nih.gov/pubmed/34781924
http://dx.doi.org/10.1186/s12885-021-08932-z
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