Identification of novel antioxidant gene signature to predict the prognosis of patients with gastric cancer

Abstract

Abstract Background Gastric cancer (GC) commonly relates to dismal prognosis and lacks efficient biomarkers. This study aimed to establish an antioxidant-related gene signature and a comprehensive nomogram to explore novel biomarkers and predict GC prognosis. Methods Clinical and expression data of GC patients were extracted from The Cancer Genome Atlas database. Univariate and multivariate Cox analyses were utilized to construct a score-based gene signature and survival analyses were conducted between high- and low-risk groups. Furthermore, we established a prognostic nomogram integrating clinical variables and antioxidant-related gene signature. Its predictive ability was validated by Harrell' concordance index and calibration curves and an independent internal cohort verified the consistency of the antioxidant gene signature-based nomogram. Results Four antioxidant-related genes (CHAC1, GGT5, GPX8, and PXDN) were significantly associated with overall survival of GC patients but only two genes, CHAC1 (HR = 0.803, P < 0.05) and GPX8 (HR = 1.358, P < 0.05), were confirmed as independent factors. A score-based signature was constructed and could act as an independent prognosis predictor (P < 0.05). Patients with lower scores showed significantly better prognosis (P < 0.05). Comprehensive nomogram combining the antioxidant-related gene signature and clinical parameters (age, gender, grade, and stage) was established and effectively predicted overall survival of GC patients [3-year survival AUC = 0.680, C index = 0.665 (95% CI 0.614–0.716)]. The independent internal validation cohort verified the reliability and good consistency of the model [3-year survival AUC = 0.703, C index = 0.706 (95% CI 0.612–0.800)]. Conclusions Innovative antioxidant-related gene signature and nomogram performed well in assessing GC prognoses. This study enlightened further investigation of antioxidant system and provided novel tools for GC patient management.