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Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer
Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear. Methods: RNA sequencing data, DNA methylation data,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425056/ https://www.ncbi.nlm.nih.gov/pubmed/36052170 http://dx.doi.org/10.3389/fmolb.2022.942402 |
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author | Miao, Ti-wei Yang, De-qing Gao, Li-juan Yin, Jie Zhu, Qi Liu, Jie He, Yan-qiu Chen, Xin |
author_facet | Miao, Ti-wei Yang, De-qing Gao, Li-juan Yin, Jie Zhu, Qi Liu, Jie He, Yan-qiu Chen, Xin |
author_sort | Miao, Ti-wei |
collection | PubMed |
description | Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear. Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan–Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC. Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4(+) T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC. Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting. |
format | Online Article Text |
id | pubmed-9425056 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94250562022-08-31 Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer Miao, Ti-wei Yang, De-qing Gao, Li-juan Yin, Jie Zhu, Qi Liu, Jie He, Yan-qiu Chen, Xin Front Mol Biosci Molecular Biosciences Background: An imbalance in the redox homeostasis has been reported in multiple cancers and is associated with a poor prognosis of disease. However, the prognostic value of redox-related genes in non-small-cell lung cancer (NSCLC) remains unclear. Methods: RNA sequencing data, DNA methylation data, mutation, and clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Redox-related differentially expressed genes (DEGs) were used to construct the prognostic signature using least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan–Meier survival curve and receiver operator characteristic (ROC) curve analyses were applied to validate the accuracy of the gene signature. Nomogram and calibration plots of the nomogram were constructed to predict prognosis. Pathway analysis was performed using gene set enrichment analysis. The correlations of risk score with tumor stage, immune infiltration, DNA methylation, tumor mutation burden (TMB), and chemotherapy sensitivity were evaluated. The prognostic signature was validated using GSE31210, GSE26939, and GSE68465 datasets. Real-time polymerase chain reaction (PCR) was used to validate dysregulated genes in NSCLC. Results: A prognostic signature was constructed using the LASSO regression analysis and was represented as a risk score. The high-risk group was significantly correlated with worse overall survival (OS) (p < 0.001). The area under the ROC curve (AUC) at the 5-year stage was 0.657. The risk score was precisely correlated with the tumor stage and was an independent prognostic factor for NSCLC. The constructed nomogram accurately predicted the OS of patients after 1-, 3-, and 5-year periods. DNA replication, cell cycle, and ECM receptor interaction were the main pathways enriched in the high-risk group. In addition, the high-risk score was correlated with higher TMB, lower methylation levels, increased infiltrating macrophages, activated memory CD4(+) T cells, and a higher sensitivity to chemotherapy. The signature was validated in GSE31210, GSE26939, and GSE68465 datasets. Real-time PCR validated dysregulated mRNA expression levels in NSCLC. Conclusions: A prognostic redox-related gene signature was successfully established in NSCLC, with potential applications in the clinical setting. Frontiers Media S.A. 2022-08-16 /pmc/articles/PMC9425056/ /pubmed/36052170 http://dx.doi.org/10.3389/fmolb.2022.942402 Text en Copyright © 2022 Miao, Yang, Gao, Yin, Zhu, Liu, He and Chen. 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 | Molecular Biosciences Miao, Ti-wei Yang, De-qing Gao, Li-juan Yin, Jie Zhu, Qi Liu, Jie He, Yan-qiu Chen, Xin Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title | Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title_full | Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title_fullStr | Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title_full_unstemmed | Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title_short | Construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
title_sort | construction of a redox-related gene signature for overall survival prediction and immune infiltration in non-small-cell lung cancer |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9425056/ https://www.ncbi.nlm.nih.gov/pubmed/36052170 http://dx.doi.org/10.3389/fmolb.2022.942402 |
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