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11 May 2020 : Database Analysis  

Glutathione Peroxidase 8 as a Prognostic Biomarker of Gastric Cancer: An Analysis of The Cancer Genome Atlas (TCGA) Data

Xinxin Zhang1ABCDEF, Dankai Zhan1BC, Yingying Li2CD, Hui Wang1DF, Chen Cheng3D, Yue Yao4F, Jianguang Jia1G*

DOI: 10.12659/MSM.921775

Med Sci Monit 2020; 26:e921775

Abstract

BACKGROUND: Glutathione peroxidase 8 (GPX8) has previously been shown to play a role in Keshan disease. In the present study, we explored the prognostic relevance of GPX8 expression in patients with gastric cancer (GC) based upon The Cancer Genome Atlas (TCGA) data.

MATERIAL AND METHODS: We assessed the relationship between the expression of GPX8 and clinicopathological findings in GC patients via logistic regression analyses, Kruskal-Wallis tests, and Wilcoxon signed-rank tests. We further assessed the prognostic relevance of specific variables using Kaplan-Meier and Cox regression analyses. We lastly conducted gene set enrichment analyses (GSEA).

RESULTS: We detected a significant association between elevated GPX8 levels and more advanced GC tumor stage (OR=5.92 for I vs. IV), as well as more advanced T (OR=22.91 for T1 vs. T4) and N classification (OR=1.82 for N0 vs. N3). We found worse prognosis in patients expressing high levels of GPX8 relative to those with lower expression of this gene (P=0.021). In a univariate analysis, we found high GPX8 expression was strongly correlated with worse OS (hazard ratio [HR]: 1.05; 95% confidence interval [CI]: 1.01–1.08; P=0.018), and multivariate analysis confirmed that GPX8 expression independently predicts GC patient OS (HR: 1.04; CI: 1.00–1.08, P=0.041). GSEA revealed that elevated GPX8 expression was associated with enrichment of pathways consistent with MAPK signaling, JAK/STAT signaling, TGF-β signaling, melanoma, and basal cell carcinoma.

CONCLUSIONS: The expression of GPX8 may have prognostic relevance, being positively associated with worse OS in GC patients. 

Keywords: Biomarkers, Tumor, Databases, Genetic, Peroxidases, Proportional Hazards Models

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750