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

Yu Yang; Xuan Long; Kun Li; Guiyun Li; Xiaohong Yu; Ping Wen; Jun Luo; Xiaobin Tian; Jinmin Zhao

doi:10.7717/peerj.11258

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

PeerJ. 2021 Apr 20:9:e11258. doi: 10.7717/peerj.11258. eCollection 2021.

Authors

Yu Yang¹, Xuan Long², Kun Li³, Guiyun Li³, Xiaohong Yu³, Ping Wen², Jun Luo², Xiaobin Tian⁴, Jinmin Zhao¹

Affiliations

¹ Department of Orthopedics Trauma and Hand Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
² Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
³ The Second People's Hospital of Guiyang, Guiyang, China.
⁴ Guizhou Medical University, Guiyang, China.

Abstract

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.

Keywords: Bioinformatics analysis; Oxidative stress; Prognostic signature; Risk model; Skin cutaneous melanoma.

Grants and funding

This study was supported by the Guangxi Key Research and Development Plan (Grant No. GuikeAD19254003), and the Guangxi Science and Technology Base and Talent Special Project (Grant No. GuikeAD17129012). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.