Identification of hub prognosis-associated oxidative stress genes in skin cutaneous melanoma using integrated bioinformatic analysis.

ABSTRACT

OBJECTIVE: Oxidative stress (OS) significantly correlates with cancer progression. However, targeting OS has not been considered as a therapeutic strategy in skin cutaneous melanoma (SKCM) due to a lack of systematical studies on validated biomarkers. The work presented here aimed to identify hub prognosis-associated OS genes in SKCM and generated an effective predictive model. PATIENTS AND METHODS: Gene expression profiles of SKCM samples and normal skin tissues were obtained from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) databases to identify differentially expressed OS genes. The validation cohort was obtained from the Gene Expression Omnibus (GEO) database. RESULTS: Thirteen hub prognosis-associated OS genes were recognized and incorporated into the prognostic risk model. Our constructed model was significantly associated with overall survival of SKCM patients as well as was shown to be associated with cancer progression. Our prognostic risk model was found to improve the accuracy of diagnostics, as shown using both TCGA and GEO cohorts. Both hub gene expression and risk score were used to generated nomograms that displayed favorable discriminatory abilities for SKCM. CONCLUSIONS: Overall, our study presents a model that may provide novel insights into the prognosis and survival of SKCM patients, as well as the development of individualized treatment therapy.