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Development and validation of an oxidative stress—associated prognostic risk model for melanoma

BACKGROUND: Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear. METHODS: We used data of RNA sequencing from 471 tumor tissues and one...

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Autores principales: Yang, Yu, Long, Xuan, Li, Kun, Li, Guiyun, Yu, Xiaohong, Wen, Ping, Luo, Jun, Tian, Xiaobin, Zhao, Jinmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063880/
https://www.ncbi.nlm.nih.gov/pubmed/33976978
http://dx.doi.org/10.7717/peerj.11258
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author Yang, Yu
Long, Xuan
Li, Kun
Li, Guiyun
Yu, Xiaohong
Wen, Ping
Luo, Jun
Tian, Xiaobin
Zhao, Jinmin
author_facet Yang, Yu
Long, Xuan
Li, Kun
Li, Guiyun
Yu, Xiaohong
Wen, Ping
Luo, Jun
Tian, Xiaobin
Zhao, Jinmin
author_sort Yang, Yu
collection PubMed
description BACKGROUND: Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear. METHODS: We used data of RNA sequencing from 471 tumor tissues and one healthy tissue acquired from The Cancer Genome Atlas (TCGA)-SKCM cohort. The Genome Tissue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related genes that were differentially expressed between SKCM and healthy samples were investigated and 16 prognosis-associated OS genes were identified. The prognostic risk model was built using univariate and Cox multivariate regressions. The prognostic value of the hub genes was validated in the GSE65904 cohort, which included 214 SKCM patients. RESULTS: The overall survival rate of SKCM patients in the high-risk group was decreased compared to the low-risk group. In both TCGA and GSE65904 cohorts, the ROC curves suggested that our prognostic risk model was more accurate than other clinicopathological characteristics to diagnose SKCM. Moreover, risk score and nomograms associated with the expression of hub genes were developed. These presented reiterated our prognostic risk model. Altogether, this study provides novel insights with regards to the pathogenesis of SKCM. The 16 hub genes identified may help in SKCM prognosis and individualized clinical treatment.
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spelling pubmed-80638802021-05-10 Development and validation of an oxidative stress—associated prognostic risk model for melanoma Yang, Yu Long, Xuan Li, Kun Li, Guiyun Yu, Xiaohong Wen, Ping Luo, Jun Tian, Xiaobin Zhao, Jinmin PeerJ Bioinformatics BACKGROUND: Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear. METHODS: We used data of RNA sequencing from 471 tumor tissues and one healthy tissue acquired from The Cancer Genome Atlas (TCGA)-SKCM cohort. The Genome Tissue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related genes that were differentially expressed between SKCM and healthy samples were investigated and 16 prognosis-associated OS genes were identified. The prognostic risk model was built using univariate and Cox multivariate regressions. The prognostic value of the hub genes was validated in the GSE65904 cohort, which included 214 SKCM patients. RESULTS: The overall survival rate of SKCM patients in the high-risk group was decreased compared to the low-risk group. In both TCGA and GSE65904 cohorts, the ROC curves suggested that our prognostic risk model was more accurate than other clinicopathological characteristics to diagnose SKCM. Moreover, risk score and nomograms associated with the expression of hub genes were developed. These presented reiterated our prognostic risk model. Altogether, this study provides novel insights with regards to the pathogenesis of SKCM. The 16 hub genes identified may help in SKCM prognosis and individualized clinical treatment. PeerJ Inc. 2021-04-20 /pmc/articles/PMC8063880/ /pubmed/33976978 http://dx.doi.org/10.7717/peerj.11258 Text en ©2021 Yang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Yang, Yu
Long, Xuan
Li, Kun
Li, Guiyun
Yu, Xiaohong
Wen, Ping
Luo, Jun
Tian, Xiaobin
Zhao, Jinmin
Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title_full Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title_fullStr Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title_full_unstemmed Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title_short Development and validation of an oxidative stress—associated prognostic risk model for melanoma
title_sort development and validation of an oxidative stress—associated prognostic risk model for melanoma
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8063880/
https://www.ncbi.nlm.nih.gov/pubmed/33976978
http://dx.doi.org/10.7717/peerj.11258
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