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A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma
Background: Ferroptosis is an iron-dependent cell death mode and closely linked to various cancers, including skin cutaneous melanoma (SKCM). Although attempts have been made to construct ferroptosis-related gene (FRG) signatures for predicting the prognosis of SKCM, the prognostic impact of ferropt...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849373/ https://www.ncbi.nlm.nih.gov/pubmed/36685905 http://dx.doi.org/10.3389/fgene.2022.988909 |
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author | He, Jia Huang, Wenting Li, Xinxin Wang, Jingru Nie, Yaxing Li, Guiqiang Wang, Xiaoxiang Cao, Huili Chen, Xiaodong Wang, Xusheng |
author_facet | He, Jia Huang, Wenting Li, Xinxin Wang, Jingru Nie, Yaxing Li, Guiqiang Wang, Xiaoxiang Cao, Huili Chen, Xiaodong Wang, Xusheng |
author_sort | He, Jia |
collection | PubMed |
description | Background: Ferroptosis is an iron-dependent cell death mode and closely linked to various cancers, including skin cutaneous melanoma (SKCM). Although attempts have been made to construct ferroptosis-related gene (FRG) signatures for predicting the prognosis of SKCM, the prognostic impact of ferroptosis-related genetic mutations in SKCM remains lacking. This study aims to develop a prediction model to explain the relationship between ferroptosis-related genetic mutations and clinical outcomes of SKCM patients and to explore the potential value of ferroptosis in SKCM treatment. Methods: FRGs which significantly correlated with the prognosis of SKCM were firstly screened based on their single-nucleotide variant (SNV) status by univariate Cox regression analysis. Subsequently, the least absolute shrinkage and selection operator (LASSO) and Cox regressions were performed to construct a new ferroptosis-related genetic mutation risk (FerrGR) model for predicting the prognosis of SKCM. We then illustrate the survival and receiver operating characteristic (ROC) curves to evaluate the predictive power of the FerrGR model. Moreover, independent prognostic factors, genomic and clinical characteristics, immunotherapy, immune infiltration, and sensitive drugs were compared between high—and low—FerrGR groups. Results: The FerrGR model was developed with a good performance on survival and ROC analysis. It was a robust independent prognostic indicator and followed a nomogram constructed to predict prognostic outcomes for SKCM patients. Besides, FerrGR combined with tumor mutational burden (TMB) or MSI (microsatellite instability) was considered as a combined biomarker for immunotherapy response. The high FerrGR group patients were associated with an inhibitory immune microenvironment. Furthermore, potential drugs target to high FerrGR samples were predicted. Conclusion: The FerrGR model is valuable to predict prognosis and immunotherapy in SKCM patients. It offers a novel therapeutic option for SKCM. |
format | Online Article Text |
id | pubmed-9849373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98493732023-01-20 A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma He, Jia Huang, Wenting Li, Xinxin Wang, Jingru Nie, Yaxing Li, Guiqiang Wang, Xiaoxiang Cao, Huili Chen, Xiaodong Wang, Xusheng Front Genet Genetics Background: Ferroptosis is an iron-dependent cell death mode and closely linked to various cancers, including skin cutaneous melanoma (SKCM). Although attempts have been made to construct ferroptosis-related gene (FRG) signatures for predicting the prognosis of SKCM, the prognostic impact of ferroptosis-related genetic mutations in SKCM remains lacking. This study aims to develop a prediction model to explain the relationship between ferroptosis-related genetic mutations and clinical outcomes of SKCM patients and to explore the potential value of ferroptosis in SKCM treatment. Methods: FRGs which significantly correlated with the prognosis of SKCM were firstly screened based on their single-nucleotide variant (SNV) status by univariate Cox regression analysis. Subsequently, the least absolute shrinkage and selection operator (LASSO) and Cox regressions were performed to construct a new ferroptosis-related genetic mutation risk (FerrGR) model for predicting the prognosis of SKCM. We then illustrate the survival and receiver operating characteristic (ROC) curves to evaluate the predictive power of the FerrGR model. Moreover, independent prognostic factors, genomic and clinical characteristics, immunotherapy, immune infiltration, and sensitive drugs were compared between high—and low—FerrGR groups. Results: The FerrGR model was developed with a good performance on survival and ROC analysis. It was a robust independent prognostic indicator and followed a nomogram constructed to predict prognostic outcomes for SKCM patients. Besides, FerrGR combined with tumor mutational burden (TMB) or MSI (microsatellite instability) was considered as a combined biomarker for immunotherapy response. The high FerrGR group patients were associated with an inhibitory immune microenvironment. Furthermore, potential drugs target to high FerrGR samples were predicted. Conclusion: The FerrGR model is valuable to predict prognosis and immunotherapy in SKCM patients. It offers a novel therapeutic option for SKCM. Frontiers Media S.A. 2023-01-05 /pmc/articles/PMC9849373/ /pubmed/36685905 http://dx.doi.org/10.3389/fgene.2022.988909 Text en Copyright © 2023 He, Huang, Li, Wang, Nie, Li, Wang, Cao, Chen and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics He, Jia Huang, Wenting Li, Xinxin Wang, Jingru Nie, Yaxing Li, Guiqiang Wang, Xiaoxiang Cao, Huili Chen, Xiaodong Wang, Xusheng A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title | A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title_full | A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title_fullStr | A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title_full_unstemmed | A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title_short | A new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
title_sort | new ferroptosis-related genetic mutation risk model predicts the prognosis of skin cutaneous melanoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849373/ https://www.ncbi.nlm.nih.gov/pubmed/36685905 http://dx.doi.org/10.3389/fgene.2022.988909 |
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