Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer

Abstract Oxidative stress (OS) reactions are reported to be associated with oncogenesis and tumor progression. However, little is known about the potential diagnostic value of OS in gastric cancer (GC). This study identified hub OS genes associated with the prognosis and progression of GC and illust...

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Autores principales:	Zhengyuan Wu, Lin Wang, Zhenpei Wen, Jun Yao
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/14f447aca7944d639b01df87d880314f
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spelling	oai:doaj.org-article:14f447aca7944d639b01df87d880314f2021-12-02T14:27:02ZIntegrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer10.1038/s41598-021-82976-w2045-2322https://doaj.org/article/14f447aca7944d639b01df87d880314f2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82976-whttps://doaj.org/toc/2045-2322Abstract Oxidative stress (OS) reactions are reported to be associated with oncogenesis and tumor progression. However, little is known about the potential diagnostic value of OS in gastric cancer (GC). This study identified hub OS genes associated with the prognosis and progression of GC and illustrated the underlying mechanisms. The transcriptome data and corresponding GC clinical information were collected from The Cancer Genome Atlas (TCGA) database. Aberrantly expressed OS genes between tumors and adjacent normal tissues were screened, and 11 prognosis-associated genes were identified with a series of bioinformatic analyses and used to construct a prognostic model. These genes were validated in the Gene Expression Omnibus (GEO) database. Furthermore, weighted gene co-expression network analysis (WGCNA) was subsequently conducted to identify the most significant hub genes for the prediction of GC progression. Analysis revealed that a good prognostic model was constructed with a better diagnostic accuracy than other clinicopathological characteristics in both TCGA and GEO cohorts. The model was also significantly associated with the overall survival of patients with GC. Meanwhile, a nomogram based on the risk score was established, which displayed a favorable discriminating ability for GC. In the WGCNA analysis, 13 progression-associated hub OS genes were identified that were also significantly associated with the progression of GC. Furthermore, functional and gene ontology (GO) analyses were performed to reveal potential pathways enriched with these genes. These results provide novel insights into the potential applications of OS-associated genes in patients with GC.Zhengyuan WuLin WangZhenpei WenJun YaoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zhengyuan Wu Lin Wang Zhenpei Wen Jun Yao Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
description	Abstract Oxidative stress (OS) reactions are reported to be associated with oncogenesis and tumor progression. However, little is known about the potential diagnostic value of OS in gastric cancer (GC). This study identified hub OS genes associated with the prognosis and progression of GC and illustrated the underlying mechanisms. The transcriptome data and corresponding GC clinical information were collected from The Cancer Genome Atlas (TCGA) database. Aberrantly expressed OS genes between tumors and adjacent normal tissues were screened, and 11 prognosis-associated genes were identified with a series of bioinformatic analyses and used to construct a prognostic model. These genes were validated in the Gene Expression Omnibus (GEO) database. Furthermore, weighted gene co-expression network analysis (WGCNA) was subsequently conducted to identify the most significant hub genes for the prediction of GC progression. Analysis revealed that a good prognostic model was constructed with a better diagnostic accuracy than other clinicopathological characteristics in both TCGA and GEO cohorts. The model was also significantly associated with the overall survival of patients with GC. Meanwhile, a nomogram based on the risk score was established, which displayed a favorable discriminating ability for GC. In the WGCNA analysis, 13 progression-associated hub OS genes were identified that were also significantly associated with the progression of GC. Furthermore, functional and gene ontology (GO) analyses were performed to reveal potential pathways enriched with these genes. These results provide novel insights into the potential applications of OS-associated genes in patients with GC.
format	article
author	Zhengyuan Wu Lin Wang Zhenpei Wen Jun Yao
author_facet	Zhengyuan Wu Lin Wang Zhenpei Wen Jun Yao
author_sort	Zhengyuan Wu
title	Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
title_short	Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
title_full	Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
title_fullStr	Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
title_full_unstemmed	Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
title_sort	integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/14f447aca7944d639b01df87d880314f
work_keys_str_mv	AT zhengyuanwu integratedanalysisidentifiesoxidativestressgenesassociatedwithprogressionandprognosisingastriccancer AT linwang integratedanalysisidentifiesoxidativestressgenesassociatedwithprogressionandprognosisingastriccancer AT zhenpeiwen integratedanalysisidentifiesoxidativestressgenesassociatedwithprogressionandprognosisingastriccancer AT junyao integratedanalysisidentifiesoxidativestressgenesassociatedwithprogressionandprognosisingastriccancer
_version_	1718391293518807040

Integrated analysis identifies oxidative stress genes associated with progression and prognosis in gastric cancer

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