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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.
Affiliation
  • Yang Y; Department of Orthopedics Trauma and Hand Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Long X; Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Li K; The Second People's Hospital of Guiyang, Guiyang, China.
  • Li G; The Second People's Hospital of Guiyang, Guiyang, China.
  • Yu X; The Second People's Hospital of Guiyang, Guiyang, China.
  • Wen P; Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Luo J; Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Tian X; Guizhou Medical University, Guiyang, China.
  • Zhao J; Department of Orthopedics Trauma and Hand Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
PeerJ ; 9: e11258, 2021.
Article in En | MEDLINE | ID: mdl-33976978
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PeerJ Year: 2021 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: PeerJ Year: 2021 Document type: Article Affiliation country: Country of publication: