Aims
Pancreatic adenocarcinoma (PAAD) is highly aggressive and characterized by a poor prognosis. Oxidative stress has great impacts on the occurrence and development of tumors. However, the predictive role of oxidative stress related genes on PAAD patients' prognosis remains unclear. In this study, we aimed to construct a prognostic model for PAAD based on oxidative stress genes and to evaluate its predictive value.
Background and aims
Pancreatic adenocarcinoma (PAAD) is highly aggressive and characterized by a poor prognosis. Oxidative stress has great impacts on the occurrence and development of tumors. However, the predictive role of oxidative stress related genes on PAAD patients' prognosis remains unclear. In this study, we aimed to construct a prognostic model for PAAD based on oxidative stress genes and to evaluate its predictive value.
Conclusion
We have successfully constructed a four oxidative stress gene prognostic model that has important predictive value for PAAD patients, and this model might be a promising guidance for prognostic prediction and efficacy monitoring in clinical individualized therapy.
Methods
The Cancer Genome Atlas (TCGA) and three Gene Expression Omnibus (GEO) datasets were used to identify differentially expressed oxidative stress genes. Univariate Cox regression, Kaplan-Meier and multivariate Cox regression analysis were used to select genes and to construct a prognosis model. According to the median value of the model's risk score, patients were divided into high and low risk groups, and gene set enrichment analysis (GSEA), immune infiltration and immunotherapy effect, drug resistance and the expression of immune checkpoint related genes and synthetic driver genes of T cell proliferation were analyzed. Finally, the mRNA and protein levels of four genes in PAAD were verified by the clinical proteomic tumor analysis consortium (CPTAC) database and the immunostaining of patients' tissue.
Results
55 differentially expressed oxidative stress genes were identified, and four genes including MET, FYN, CTTN and CDK1 were selected to construct a prognosis model. GESA indicated that immune related pathways, metabolic pathways and DNA repair pathways were significantly enriched in the high risk group as compared to the low risk group. The frequency of genetic mutations was also significantly higher in high risk groups than that in low risk groups. Moreover, the infiltration level of 23 immune cells as well as the expression of immune checkpoint related and synthetic driver genes of T cell proliferation were significantly altered, with the better immunotherapy effect occurring in low risk group. In patient PAAD tissues, the mRNA and protein levels of these four genes were up-regulated.