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A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma

BACKGROUND: Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. This study aims to investigate the potential correlation between ferroptosis and the prognosis of lung adenocarcinoma (LUAD). METHODS: RNA-seq data were collected from the LUAD datase...

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Autores principales: Li, Fei, Ge, Dongcen, Sun, Shu-lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276441/
https://www.ncbi.nlm.nih.gov/pubmed/34256754
http://dx.doi.org/10.1186/s12890-021-01588-2
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author Li, Fei
Ge, Dongcen
Sun, Shu-lan
author_facet Li, Fei
Ge, Dongcen
Sun, Shu-lan
author_sort Li, Fei
collection PubMed
description BACKGROUND: Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. This study aims to investigate the potential correlation between ferroptosis and the prognosis of lung adenocarcinoma (LUAD). METHODS: RNA-seq data were collected from the LUAD dataset of The Cancer Genome Atlas (TCGA) database. Based on ferroptosis-related genes, differentially expressed genes (DEGs) between LUAD and paracancerous specimens were identified. The univariate Cox regression analysis was performed to screen key genes associated with the prognosis of LUAD. LUAD patients were divided into the training set and validation set. Then, we screened out key genes and built a prognostic prediction model involving 5 genes using the least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation and the multivariate Cox regression analysis. After dividing LUAD patients based on the median level of risk score as cut-off value, the generated prognostic prediction model was validated in the validation set. Moreover, we analyzed the somatic mutations, and estimated the scores of immune infiltration in the high-risk and low-risk groups. Functional enrichment analysis of DEGs was performed as well. RESULTS: High-risk scores indicated the worse prognosis of LUAD. The maximum area under curve (AUC) of the training set and the validation set in this study was 0.7 and 0.69, respectively. Moreover, we integrated the age, gender, and tumor stage to construct the composite nomogram. The charts indicated that the AUC of LUAD cases with the survival time of 1, 3 and 5 years was 0.698, 0.71 and 0.73, respectively. In addition, the mutation frequency of LUAD patients in the high-risk group was significantly higher than that in the low-risk group. Simultaneously, DEGs were mainly enriched in ferroptosis-related pathways by analyzing the functional results. CONCLUSIONS: This study constructs a novel LUAD prognosis prediction model involving 5 ferroptosis-related genes, which can be used as a promising tool for decision-making of clinical therapeutic strategies of LUAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01588-2.
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spelling pubmed-82764412021-07-13 A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma Li, Fei Ge, Dongcen Sun, Shu-lan BMC Pulm Med Research BACKGROUND: Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. This study aims to investigate the potential correlation between ferroptosis and the prognosis of lung adenocarcinoma (LUAD). METHODS: RNA-seq data were collected from the LUAD dataset of The Cancer Genome Atlas (TCGA) database. Based on ferroptosis-related genes, differentially expressed genes (DEGs) between LUAD and paracancerous specimens were identified. The univariate Cox regression analysis was performed to screen key genes associated with the prognosis of LUAD. LUAD patients were divided into the training set and validation set. Then, we screened out key genes and built a prognostic prediction model involving 5 genes using the least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation and the multivariate Cox regression analysis. After dividing LUAD patients based on the median level of risk score as cut-off value, the generated prognostic prediction model was validated in the validation set. Moreover, we analyzed the somatic mutations, and estimated the scores of immune infiltration in the high-risk and low-risk groups. Functional enrichment analysis of DEGs was performed as well. RESULTS: High-risk scores indicated the worse prognosis of LUAD. The maximum area under curve (AUC) of the training set and the validation set in this study was 0.7 and 0.69, respectively. Moreover, we integrated the age, gender, and tumor stage to construct the composite nomogram. The charts indicated that the AUC of LUAD cases with the survival time of 1, 3 and 5 years was 0.698, 0.71 and 0.73, respectively. In addition, the mutation frequency of LUAD patients in the high-risk group was significantly higher than that in the low-risk group. Simultaneously, DEGs were mainly enriched in ferroptosis-related pathways by analyzing the functional results. CONCLUSIONS: This study constructs a novel LUAD prognosis prediction model involving 5 ferroptosis-related genes, which can be used as a promising tool for decision-making of clinical therapeutic strategies of LUAD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12890-021-01588-2. BioMed Central 2021-07-13 /pmc/articles/PMC8276441/ /pubmed/34256754 http://dx.doi.org/10.1186/s12890-021-01588-2 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 Research
Li, Fei
Ge, Dongcen
Sun, Shu-lan
A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title_full A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title_fullStr A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title_full_unstemmed A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title_short A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
title_sort novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8276441/
https://www.ncbi.nlm.nih.gov/pubmed/34256754
http://dx.doi.org/10.1186/s12890-021-01588-2
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