ABSTRACT
Objective:To investigate the relationship between glutathione peroxidases (GPXs) gene expression in colorectal cancer tissues and survival prognosis, and to construct and evaluate a nomogram prediction model of GPXs for survival prognosis of colorectal cancer patients.Methods:The GPXs gene expresion data and other clinical data of 620 patients with colorectal cancer (455 cases of colon cancer and 165 cases of rectal cancer) were downloaded from The Cancer Genome Atlas (TCGA) database, and the GPXs gene expression data of 820 normal people were downloaded as controls, preprocessed by R language, and the gene expression data were analyzed for differential expression. Spearman rank correlation was used to analyze the correlation between GPXs gene expression and tumor mutation burden (TMB) in colorectal cancer tissues. Cox risk regression model was used to analyze the influencing factors of survival and prognosis of colorectal cancer patients. Nomogram models were constructed to predict overall survival (OS) of colon cancer and rectal cancer patients, and its predictive performance was evaluated by calibration curve.Results:In the GPXs family, there were statistically significant differences in the mRNA expressions of GPX1, GPX2, GPX3, GPX4, GPX5, GPX7 and GPX8 between colon cancer patients and normal population, and the mRNA expressions of GPX1, GPX2, GPX4 and GPX8 in colon cancer patients were higher than those in normal population (all P<0.05) . There were statistically significant differences in the mRNA expressions of GPX1, GPX2, GPX3, GPX4, GPX7 and GPX8 between rectal cancer patients and normal population, and the mRNA expressions of GPX1, GPX2, GPX4, GPX7 and GPX8 in rectal cancer patients were higher than those in normal population (all P<0.05) . Spearman rank correlation analysis showed that GPX2 ( r s=-0.27, P<0.001) and GPX7 ( r s=-0.11, P=0.043) expressions were negatively correlated with TMB in colon cancer. There were no significant correlations between GPXs genes expressions and TMB in rectal cancer tissues (all P>0.05) . In colon cancer, univariate analysis showed that GPX3 ( HR=1.22, 95% CI: 1.05-1.43, P=0.012) , GPX4 ( HR=1.39, 95% CI: 1.01-1.92, P=0.045) , age ( HR=1.02, 95% CI: 1.01-1.04, P=0.010) and pTNM-stage ( HR=1.78, 95% CI: 1.43-2.21, P<0.001) were the influencing factors of OS. Multivariate analysis showed that GPX4 ( HR=1.96, 95% CI: 1.09-3.51, P=0.024) , age ( HR=1.02, 95% CI: 1.00-1.04, P=0.042) and pTNM-stage ( HR=1.61, 95% CI: 1.21-2.15, P=0.001) were the independent risk factors of OS. In rectal cancer, univariate analysis showed that age ( HR=1.08, 95% CI: 1.04-1.13, P<0.001) was the influencing factor of OS. Multivariate analysis showed that GPX7 ( HR=0.44, 95% CI: 0.22-0.88, P=0.020) , GPX8 ( HR=3.17, 95% CI: 1.63-6.17, P=0.001) and age ( HR=1.10, 95% CI: 1.04-1.16, P=0.001) were the independent influencing factors of OS. The consistency index (C-index) of the nomogram model for predicting OS in patients with colon cancer and rectal cancer were 0.71 (95% CI: 0.63-0.79) and 0.88 (95% CI: 0.82-0.94) respectively. The calibration curve showed that the prediction curve of the two models had a good fit with the real curve. Conclusion:GPX4 is an independent risk factor affecting the prognosis of colon cancer patients. Patients with high GPX4 expression have a poor prognosis. GPX7 and GPX8 are independent prognostic factors for rectal cancer patients, and the rectal cancer patients with low GPX7 expression and high GPX8 expression have poor prognosis. The nomogram constructed based on the above factors can better predict the prognosis of patients with colon cancer and rectal cancer.