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Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma
BACKGROUND: Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in lung adenocarcinoma (LUAD) is essential for new diagnostic an...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254945/ https://www.ncbi.nlm.nih.gov/pubmed/34217273 http://dx.doi.org/10.1186/s12935-021-02027-2 |
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author | Yao, Jie Chen, Xiao Liu, Xiao Li, Rui Zhou, Xijia Qu, Yiqing |
author_facet | Yao, Jie Chen, Xiao Liu, Xiao Li, Rui Zhou, Xijia Qu, Yiqing |
author_sort | Yao, Jie |
collection | PubMed |
description | BACKGROUND: Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in lung adenocarcinoma (LUAD) is essential for new diagnostic and therapeutic strategies. METHODS: FIRLs were obtained through Pearson correlation analysis between ferroptosis and iron-metabolism related genes and all lncRNAs. Univariate and multivariate Cox regression analysis were used to identify optimal prognostic lncRNAs. Next, a novel signature was constructed and risk score of each patient was calculated. Survival analysis and ROC analysis were performed to evaluate the predictive performance using The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus (GEO) datasets, respectively. Furthermore, multivariate Cox and stratification analysis were used to assess prognostic value of this signature in whole cohort and various subgroups. The correlation of risk signature with immune infiltration and gene mutation was also discussed. The expression of lncRNAs was verified by quantitative real-time PCR (qRT-PCR). RESULTS: A 7-FIRLs signature including ARHGEF26-AS1, LINC01137, C20orf197, MGC32805, TMPO-AS1, LINC00324, and LINC01116 was established in the present study to assess the overall survival (OS) of LUAD. The survival analysis and ROC curve indicated good predictive performance of the signature in both the TCGA training set and the GEO validation set. Multivariate Cox and stratification analysis indicated that the 7‐FIRLs signature was an independent prognostic factor for OS. Nomogram exhibited robust validity in prognostic prediction. Differences in immune cells, immune functions and gene mutation were also found between high-risk and low-risk groups. CONCLUSIONS: This risk signature based on the FIRLs may be promising for the clinical prediction of prognosis and immunotherapeutic responses in LUAD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02027-2. |
format | Online Article Text |
id | pubmed-8254945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82549452021-07-06 Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma Yao, Jie Chen, Xiao Liu, Xiao Li, Rui Zhou, Xijia Qu, Yiqing Cancer Cell Int Primary Research BACKGROUND: Long non-coding RNAs (lncRNAs) are increasingly recognized as the crucial mediators in the regulation of ferroptosis and iron metabolism. A systematic understanding of ferroptosis and iron-metabolism related lncRNAs (FIRLs) in lung adenocarcinoma (LUAD) is essential for new diagnostic and therapeutic strategies. METHODS: FIRLs were obtained through Pearson correlation analysis between ferroptosis and iron-metabolism related genes and all lncRNAs. Univariate and multivariate Cox regression analysis were used to identify optimal prognostic lncRNAs. Next, a novel signature was constructed and risk score of each patient was calculated. Survival analysis and ROC analysis were performed to evaluate the predictive performance using The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus (GEO) datasets, respectively. Furthermore, multivariate Cox and stratification analysis were used to assess prognostic value of this signature in whole cohort and various subgroups. The correlation of risk signature with immune infiltration and gene mutation was also discussed. The expression of lncRNAs was verified by quantitative real-time PCR (qRT-PCR). RESULTS: A 7-FIRLs signature including ARHGEF26-AS1, LINC01137, C20orf197, MGC32805, TMPO-AS1, LINC00324, and LINC01116 was established in the present study to assess the overall survival (OS) of LUAD. The survival analysis and ROC curve indicated good predictive performance of the signature in both the TCGA training set and the GEO validation set. Multivariate Cox and stratification analysis indicated that the 7‐FIRLs signature was an independent prognostic factor for OS. Nomogram exhibited robust validity in prognostic prediction. Differences in immune cells, immune functions and gene mutation were also found between high-risk and low-risk groups. CONCLUSIONS: This risk signature based on the FIRLs may be promising for the clinical prediction of prognosis and immunotherapeutic responses in LUAD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12935-021-02027-2. BioMed Central 2021-07-03 /pmc/articles/PMC8254945/ /pubmed/34217273 http://dx.doi.org/10.1186/s12935-021-02027-2 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 | Primary Research Yao, Jie Chen, Xiao Liu, Xiao Li, Rui Zhou, Xijia Qu, Yiqing Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title | Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title_full | Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title_fullStr | Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title_full_unstemmed | Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title_short | Characterization of a ferroptosis and iron-metabolism related lncRNA signature in lung adenocarcinoma |
title_sort | characterization of a ferroptosis and iron-metabolism related lncrna signature in lung adenocarcinoma |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254945/ https://www.ncbi.nlm.nih.gov/pubmed/34217273 http://dx.doi.org/10.1186/s12935-021-02027-2 |
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