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Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation

Ferroptosis is a new type of programmed cell death that is different from apoptosis, cell necrosis, and autophagy, which might be involved in development of sepsis. However, the potential role of ferroptosis-related genes (FRGs) in sepsis remained unclear. We identified 41 ferroptosis-related differ...

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Autores principales: Zhu, Sizhe, Huang, Yabing, Ye, Chenglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159884/
https://www.ncbi.nlm.nih.gov/pubmed/35663048
http://dx.doi.org/10.1155/2022/8178782
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author Zhu, Sizhe
Huang, Yabing
Ye, Chenglin
author_facet Zhu, Sizhe
Huang, Yabing
Ye, Chenglin
author_sort Zhu, Sizhe
collection PubMed
description Ferroptosis is a new type of programmed cell death that is different from apoptosis, cell necrosis, and autophagy, which might be involved in development of sepsis. However, the potential role of ferroptosis-related genes (FRGs) in sepsis remained unclear. We identified 41 ferroptosis-related differential expression genes by weighted correlation network and differential expression analysis. The hub module of 41 ferroptosis-related differential expression genes in the protein-protein interaction network was identified. Next, we estimated diagnostic values of genes in hub modules. TLR4, WIPI1, and GABARAPL2 with high diagnostic value were selected for construction of risk prognostic model. The high risk-scored patients had significantly higher mortality than the patients with low risk scores in discovery dataset. Furthermore, the risk scores of nonsurvivor were higher than those of survivor in validation dataset. It suggested that risk score was significantly correlated to prognosis in sepsis. Then, we constructed a nomogram for improving the clinical applicability of risk signature. Moreover, the risk score was significantly associated with immune infiltration in sepsis. Our comprehensive analysis of FRGs in sepsis demonstrated the potential roles in diagnosis, prognosis, and immune infiltration. This work may benefit in understanding FRGs in sepsis and pave a new path for diagnosis and assessment of prognosis.
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spelling pubmed-91598842022-06-02 Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation Zhu, Sizhe Huang, Yabing Ye, Chenglin Biomed Res Int Research Article Ferroptosis is a new type of programmed cell death that is different from apoptosis, cell necrosis, and autophagy, which might be involved in development of sepsis. However, the potential role of ferroptosis-related genes (FRGs) in sepsis remained unclear. We identified 41 ferroptosis-related differential expression genes by weighted correlation network and differential expression analysis. The hub module of 41 ferroptosis-related differential expression genes in the protein-protein interaction network was identified. Next, we estimated diagnostic values of genes in hub modules. TLR4, WIPI1, and GABARAPL2 with high diagnostic value were selected for construction of risk prognostic model. The high risk-scored patients had significantly higher mortality than the patients with low risk scores in discovery dataset. Furthermore, the risk scores of nonsurvivor were higher than those of survivor in validation dataset. It suggested that risk score was significantly correlated to prognosis in sepsis. Then, we constructed a nomogram for improving the clinical applicability of risk signature. Moreover, the risk score was significantly associated with immune infiltration in sepsis. Our comprehensive analysis of FRGs in sepsis demonstrated the potential roles in diagnosis, prognosis, and immune infiltration. This work may benefit in understanding FRGs in sepsis and pave a new path for diagnosis and assessment of prognosis. Hindawi 2022-05-25 /pmc/articles/PMC9159884/ /pubmed/35663048 http://dx.doi.org/10.1155/2022/8178782 Text en Copyright © 2022 Sizhe Zhu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhu, Sizhe
Huang, Yabing
Ye, Chenglin
Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title_full Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title_fullStr Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title_full_unstemmed Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title_short Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation
title_sort identification of a ferroptosis-related prognostic signature in sepsis via bioinformatics analyses and experiment validation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9159884/
https://www.ncbi.nlm.nih.gov/pubmed/35663048
http://dx.doi.org/10.1155/2022/8178782
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