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Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes
PURPOSE: Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model. PATIENTS AND METHODS: The data of LGG were downloaded from public databa...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085428/ https://www.ncbi.nlm.nih.gov/pubmed/35548585 http://dx.doi.org/10.2147/IJGM.S352773 |
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author | Sun, Liwei Li, Bing Wang, Bin Li, Jinduo Li, Jing |
author_facet | Sun, Liwei Li, Bing Wang, Bin Li, Jinduo Li, Jing |
author_sort | Sun, Liwei |
collection | PubMed |
description | PURPOSE: Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model. PATIENTS AND METHODS: The data of LGG were downloaded from public databases. Through LASSO analysis of characteristic genes, a gene signature was constructed. Patients into were divided two groups based on risk score. Subsequently, survival, clinical phenotype, functional enrichment, immune cell infiltration and somatic mutation analysis were performed. In addition, whether ferroptosis-related genes (FRGs) signature can predict the patient’s response to anti-PD-1/PD-L1 immunotherapy was also investigated. RESULTS: FRGs signature had strong prognostic assessment ability, and high risk score was associated with poor overall survival (OS) of LGG. The high risk score group had higher degree of immune cell infiltration, stronger stromal activity, higher immune score, and high expression of immune checkpoint. In low risk score group anti-PD-1/PD-L1 immunotherapy has significant therapeutic advantages and clinical response. Genes and frequency of somatic mutations and clinical phenotypes in the high and low risk score groups were significantly different. CONCLUSION: A prognostic model based on 7 FRGs can be used to predict the prognosis and immunotherapeutic response of LGG. |
format | Online Article Text |
id | pubmed-9085428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-90854282022-05-10 Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes Sun, Liwei Li, Bing Wang, Bin Li, Jinduo Li, Jing Int J Gen Med Original Research PURPOSE: Ferroptosis is closely associated with tumors. The purpose of this study was to investigate the correlation between ferroptosis and prognosis of low grade glioma (LGG) via construction and verification of a risk model. PATIENTS AND METHODS: The data of LGG were downloaded from public databases. Through LASSO analysis of characteristic genes, a gene signature was constructed. Patients into were divided two groups based on risk score. Subsequently, survival, clinical phenotype, functional enrichment, immune cell infiltration and somatic mutation analysis were performed. In addition, whether ferroptosis-related genes (FRGs) signature can predict the patient’s response to anti-PD-1/PD-L1 immunotherapy was also investigated. RESULTS: FRGs signature had strong prognostic assessment ability, and high risk score was associated with poor overall survival (OS) of LGG. The high risk score group had higher degree of immune cell infiltration, stronger stromal activity, higher immune score, and high expression of immune checkpoint. In low risk score group anti-PD-1/PD-L1 immunotherapy has significant therapeutic advantages and clinical response. Genes and frequency of somatic mutations and clinical phenotypes in the high and low risk score groups were significantly different. CONCLUSION: A prognostic model based on 7 FRGs can be used to predict the prognosis and immunotherapeutic response of LGG. Dove 2022-05-05 /pmc/articles/PMC9085428/ /pubmed/35548585 http://dx.doi.org/10.2147/IJGM.S352773 Text en © 2022 Sun 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 Sun, Liwei Li, Bing Wang, Bin Li, Jinduo Li, Jing Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title | Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title_full | Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title_fullStr | Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title_full_unstemmed | Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title_short | Construction of a Risk Model to Predict the Prognosis and Immunotherapy of Low-Grade Glioma Ground on 7 Ferroptosis-Related Genes |
title_sort | construction of a risk model to predict the prognosis and immunotherapy of low-grade glioma ground on 7 ferroptosis-related genes |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085428/ https://www.ncbi.nlm.nih.gov/pubmed/35548585 http://dx.doi.org/10.2147/IJGM.S352773 |
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