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A ferroptosis-related gene signature for graft loss prediction following renal allograft

Allogeneic kidney transplantation (renal allograft) is the most effective treatment for advanced kidney disease. Previous studies have indicated that ferroptosis participates in the progression of acute kidney injury and renal transplant failure. However, few studies have evaluated the prognostic va...

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Autores principales: Fan, Zhenlei, Liu, Tao, Huang, Hanfei, Lin, Jie, Zeng, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806795/
https://www.ncbi.nlm.nih.gov/pubmed/34338139
http://dx.doi.org/10.1080/21655979.2021.1953310
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author Fan, Zhenlei
Liu, Tao
Huang, Hanfei
Lin, Jie
Zeng, Zhong
author_facet Fan, Zhenlei
Liu, Tao
Huang, Hanfei
Lin, Jie
Zeng, Zhong
author_sort Fan, Zhenlei
collection PubMed
description Allogeneic kidney transplantation (renal allograft) is the most effective treatment for advanced kidney disease. Previous studies have indicated that ferroptosis participates in the progression of acute kidney injury and renal transplant failure. However, few studies have evaluated the prognostic value of ferroptosis on renal transplantation outcomes. In this study, a total of 22 differentially expressed ferroptosis-related genes (DFGs) were identified, which were mainly enriched in infection-related pathways. Next, a ferroptosis-related gene signature, including GA-binding protein transcription factor subunit beta 1 (GABPB1), cyclin-dependent kinase inhibitor 1A (CDKN1A), Toll-like receptor 4 (TLR4), C-X-C motif chemokine ligand 2 (CXCL2), caveolin 1 (CAV1), and ribonucleotide reductase subunit M2 (RRM2), was constructed to predict graft loss following renal allograft. Moreover, receiver operating characteristic (ROC) curves (area under the ROC curve [AUC] > 0.8) demonstrated the accuracy of the gene signature and univariate Cox analysis suggested that the gene signature could play an independent role in graft loss (p < 0.05). Furthermore, the nomogram and calibration plots also indicated the good prognostic capability of the gene signature. Finally, immune-related and cytokine signaling pathways were mostly enriched in renal allograft patients with poor outcomes. Considered together, a ferroptosis-related gene signature and nomogram based on DFGs were created to predict the 1-, 2- and 3- year graft loss probability of renal allograft patients.The gene signature could serve as a valuable biomarker for predicting graft loss, contributing to improving the outcome of allogeneic kidney transplantation.
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spelling pubmed-88067952022-02-02 A ferroptosis-related gene signature for graft loss prediction following renal allograft Fan, Zhenlei Liu, Tao Huang, Hanfei Lin, Jie Zeng, Zhong Bioengineered Research Paper Allogeneic kidney transplantation (renal allograft) is the most effective treatment for advanced kidney disease. Previous studies have indicated that ferroptosis participates in the progression of acute kidney injury and renal transplant failure. However, few studies have evaluated the prognostic value of ferroptosis on renal transplantation outcomes. In this study, a total of 22 differentially expressed ferroptosis-related genes (DFGs) were identified, which were mainly enriched in infection-related pathways. Next, a ferroptosis-related gene signature, including GA-binding protein transcription factor subunit beta 1 (GABPB1), cyclin-dependent kinase inhibitor 1A (CDKN1A), Toll-like receptor 4 (TLR4), C-X-C motif chemokine ligand 2 (CXCL2), caveolin 1 (CAV1), and ribonucleotide reductase subunit M2 (RRM2), was constructed to predict graft loss following renal allograft. Moreover, receiver operating characteristic (ROC) curves (area under the ROC curve [AUC] > 0.8) demonstrated the accuracy of the gene signature and univariate Cox analysis suggested that the gene signature could play an independent role in graft loss (p < 0.05). Furthermore, the nomogram and calibration plots also indicated the good prognostic capability of the gene signature. Finally, immune-related and cytokine signaling pathways were mostly enriched in renal allograft patients with poor outcomes. Considered together, a ferroptosis-related gene signature and nomogram based on DFGs were created to predict the 1-, 2- and 3- year graft loss probability of renal allograft patients.The gene signature could serve as a valuable biomarker for predicting graft loss, contributing to improving the outcome of allogeneic kidney transplantation. Taylor & Francis 2021-08-01 /pmc/articles/PMC8806795/ /pubmed/34338139 http://dx.doi.org/10.1080/21655979.2021.1953310 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Fan, Zhenlei
Liu, Tao
Huang, Hanfei
Lin, Jie
Zeng, Zhong
A ferroptosis-related gene signature for graft loss prediction following renal allograft
title A ferroptosis-related gene signature for graft loss prediction following renal allograft
title_full A ferroptosis-related gene signature for graft loss prediction following renal allograft
title_fullStr A ferroptosis-related gene signature for graft loss prediction following renal allograft
title_full_unstemmed A ferroptosis-related gene signature for graft loss prediction following renal allograft
title_short A ferroptosis-related gene signature for graft loss prediction following renal allograft
title_sort ferroptosis-related gene signature for graft loss prediction following renal allograft
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806795/
https://www.ncbi.nlm.nih.gov/pubmed/34338139
http://dx.doi.org/10.1080/21655979.2021.1953310
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