An oxidative stress-related signature for predicting the prognosis of liver cancer
Introduction: This study aimed to screen for oxidative stress-related genes (OSRGs) and build an oxidative stress-related signature to predict the prognosis of liver cancer.Methods: OSRGs with a protein domain correlation score ≥ 6 were downloaded from the GeneCards database and intersected with The...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.975211/full |
| _version_ | 1797962174505680896 |
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| author | Luling Wang Xing Liu |
| author_facet | Luling Wang Xing Liu |
| author_sort | Luling Wang |
| collection | DOAJ |
| description | Introduction: This study aimed to screen for oxidative stress-related genes (OSRGs) and build an oxidative stress-related signature to predict the prognosis of liver cancer.Methods: OSRGs with a protein domain correlation score ≥ 6 were downloaded from the GeneCards database and intersected with The Cancer Genome Atlas (TCGA) data for subsequent analyses. Differential immune cells (DICs) and immune and stromal scores between the normal and tumor samples were determined, followed by unsupervised hierarchical cluster analysis. Immune-related OSRGs were identified using weighted gene co-expression network analysis. An OSRG-related risk signature was then built, and the GSE14520 dataset was used for validation. A nomogram evaluation model was used to predict prognosis.Results: Nine DICs were determined between the normal and tumor groups, and three subtypes were obtained: clusters 1, 2, and 3. Cluster 1 had the best prognosis among the clusters. One hundred thirty-eight immune-related OSRGs were identified, and seven prognosis-related OSRGs were used to build the OSRG score prognostic model. Patients in the high OSRG score group had a poorer prognosis than those in the low OSRG score group. Six immune cell infiltration and enrichment scores of the 16 immune gene sets showed significant differences between the high and low OSRG score groups. Moreover, a nomogram was constructed based on the prognostic signature and clinicopathological features and had a robust predictive performance and high accuracy.Conclusion: The OSRG-related risk signature and the prognostic nomogram accurately predicted patient survival. |
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| format | Article |
| id | doaj.art-f1ae9ccb5c634ffe94c01a26a38520c6 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T01:10:20Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-f1ae9ccb5c634ffe94c01a26a38520c62023-01-04T08:39:26ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-01-011310.3389/fgene.2022.975211975211An oxidative stress-related signature for predicting the prognosis of liver cancerLuling WangXing LiuIntroduction: This study aimed to screen for oxidative stress-related genes (OSRGs) and build an oxidative stress-related signature to predict the prognosis of liver cancer.Methods: OSRGs with a protein domain correlation score ≥ 6 were downloaded from the GeneCards database and intersected with The Cancer Genome Atlas (TCGA) data for subsequent analyses. Differential immune cells (DICs) and immune and stromal scores between the normal and tumor samples were determined, followed by unsupervised hierarchical cluster analysis. Immune-related OSRGs were identified using weighted gene co-expression network analysis. An OSRG-related risk signature was then built, and the GSE14520 dataset was used for validation. A nomogram evaluation model was used to predict prognosis.Results: Nine DICs were determined between the normal and tumor groups, and three subtypes were obtained: clusters 1, 2, and 3. Cluster 1 had the best prognosis among the clusters. One hundred thirty-eight immune-related OSRGs were identified, and seven prognosis-related OSRGs were used to build the OSRG score prognostic model. Patients in the high OSRG score group had a poorer prognosis than those in the low OSRG score group. Six immune cell infiltration and enrichment scores of the 16 immune gene sets showed significant differences between the high and low OSRG score groups. Moreover, a nomogram was constructed based on the prognostic signature and clinicopathological features and had a robust predictive performance and high accuracy.Conclusion: The OSRG-related risk signature and the prognostic nomogram accurately predicted patient survival.https://www.frontiersin.org/articles/10.3389/fgene.2022.975211/fullliver canceroxidative stressprognostic signaturenomogramimmune microenviroment |
| spellingShingle | Luling Wang Xing Liu An oxidative stress-related signature for predicting the prognosis of liver cancer Frontiers in Genetics liver cancer oxidative stress prognostic signature nomogram immune microenviroment |
| title | An oxidative stress-related signature for predicting the prognosis of liver cancer |
| title_full | An oxidative stress-related signature for predicting the prognosis of liver cancer |
| title_fullStr | An oxidative stress-related signature for predicting the prognosis of liver cancer |
| title_full_unstemmed | An oxidative stress-related signature for predicting the prognosis of liver cancer |
| title_short | An oxidative stress-related signature for predicting the prognosis of liver cancer |
| title_sort | oxidative stress related signature for predicting the prognosis of liver cancer |
| topic | liver cancer oxidative stress prognostic signature nomogram immune microenviroment |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.975211/full |
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