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Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma
PURPOSE: Ferroptosis, as a novel regulated cell death form, has a close interaction with metabolism, which is largely unknown in cancer. In the present study, we conducted a comprehensive analysis of ferroptosis-related metabolic genes to delineate the metabolic signatures induced by ferroptosis and...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349220/ https://www.ncbi.nlm.nih.gov/pubmed/34377010 http://dx.doi.org/10.2147/PGPM.S319524 |
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author | Dai, Tianxing Li, Jing Lu, Xu Ye, Linsen Yu, Haoyuan Zhang, Lele Deng, Mingbin Zhu, Shuguang Liu, Wei Wang, Guoying Yang, Yang |
author_facet | Dai, Tianxing Li, Jing Lu, Xu Ye, Linsen Yu, Haoyuan Zhang, Lele Deng, Mingbin Zhu, Shuguang Liu, Wei Wang, Guoying Yang, Yang |
author_sort | Dai, Tianxing |
collection | PubMed |
description | PURPOSE: Ferroptosis, as a novel regulated cell death form, has a close interaction with metabolism, which is largely unknown in cancer. In the present study, we conducted a comprehensive analysis of ferroptosis-related metabolic genes to delineate the metabolic signatures induced by ferroptosis and evaluate its prognostic significance in hepatocellular carcinoma (HCC). METHODS: The ferroptosis-related metabolic genes (Fer-MRGs) were identified by correlation analyses with transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus. Then, univariate and the least absolute shrinkage and selection operator Cox regression analysis was used to establish a novel risk score model. Univariate and multivariate COX analyses were used to identify independent prognostic factors for overall survival (OS) of HCC, and a nomogram was developed. The Fer-MRGs’ expression was further evaluated by quantitative real-time polymerase chain reaction in HCC. RESULTS: A total of 77 metabolic genes were identified as Fer-MRGs, and 26 were found with prognostic values for OS of HCC. Then, a novel nine-gene (AKR1C3, ATIC, G6PD, GMPS, GNPDA1, IMPDH1, PRIM1, RRM2, and TXNRD1) risk score model was constructed. Survival analyses showed worse OS in high-risk patients both in the training and validation groups. The model was also identified as an independent prognostic factor for HCC, and a prognostic nomogram for OS was further established with superior discriminative capacity and prediction accuracy. Notably, close correlations were also identified between the risk score and the expression of immune checkpoint genes, immune subtypes of tumor, and susceptibility of HCC to chemotherapeutic agents. Finally, elevated expression of eight Fer-MRGs (except for IMPDH1) was further verified in 16 pairs of HCC tumor and adjacent tissues. CONCLUSION: These results indicated the intense interaction between ferroptosis and metabolism, the significant role of ferroptosis-related MRGs, and the great potential of the novel risk score model for prognosis prediction in HCC. |
format | Online Article Text |
id | pubmed-8349220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-83492202021-08-09 Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma Dai, Tianxing Li, Jing Lu, Xu Ye, Linsen Yu, Haoyuan Zhang, Lele Deng, Mingbin Zhu, Shuguang Liu, Wei Wang, Guoying Yang, Yang Pharmgenomics Pers Med Original Research PURPOSE: Ferroptosis, as a novel regulated cell death form, has a close interaction with metabolism, which is largely unknown in cancer. In the present study, we conducted a comprehensive analysis of ferroptosis-related metabolic genes to delineate the metabolic signatures induced by ferroptosis and evaluate its prognostic significance in hepatocellular carcinoma (HCC). METHODS: The ferroptosis-related metabolic genes (Fer-MRGs) were identified by correlation analyses with transcriptome data from The Cancer Genome Atlas and Gene Expression Omnibus. Then, univariate and the least absolute shrinkage and selection operator Cox regression analysis was used to establish a novel risk score model. Univariate and multivariate COX analyses were used to identify independent prognostic factors for overall survival (OS) of HCC, and a nomogram was developed. The Fer-MRGs’ expression was further evaluated by quantitative real-time polymerase chain reaction in HCC. RESULTS: A total of 77 metabolic genes were identified as Fer-MRGs, and 26 were found with prognostic values for OS of HCC. Then, a novel nine-gene (AKR1C3, ATIC, G6PD, GMPS, GNPDA1, IMPDH1, PRIM1, RRM2, and TXNRD1) risk score model was constructed. Survival analyses showed worse OS in high-risk patients both in the training and validation groups. The model was also identified as an independent prognostic factor for HCC, and a prognostic nomogram for OS was further established with superior discriminative capacity and prediction accuracy. Notably, close correlations were also identified between the risk score and the expression of immune checkpoint genes, immune subtypes of tumor, and susceptibility of HCC to chemotherapeutic agents. Finally, elevated expression of eight Fer-MRGs (except for IMPDH1) was further verified in 16 pairs of HCC tumor and adjacent tissues. CONCLUSION: These results indicated the intense interaction between ferroptosis and metabolism, the significant role of ferroptosis-related MRGs, and the great potential of the novel risk score model for prognosis prediction in HCC. Dove 2021-08-03 /pmc/articles/PMC8349220/ /pubmed/34377010 http://dx.doi.org/10.2147/PGPM.S319524 Text en © 2021 Dai et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Dai, Tianxing Li, Jing Lu, Xu Ye, Linsen Yu, Haoyuan Zhang, Lele Deng, Mingbin Zhu, Shuguang Liu, Wei Wang, Guoying Yang, Yang Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title | Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title_full | Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title_fullStr | Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title_full_unstemmed | Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title_short | Prognostic Role and Potential Mechanisms of the Ferroptosis-Related Metabolic Gene Signature in Hepatocellular Carcinoma |
title_sort | prognostic role and potential mechanisms of the ferroptosis-related metabolic gene signature in hepatocellular carcinoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349220/ https://www.ncbi.nlm.nih.gov/pubmed/34377010 http://dx.doi.org/10.2147/PGPM.S319524 |
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