Identification of pyroptosis-related gene signature for predicting prognosis of patients with pancreatic cancer using bioinformatics.

Abstract

Pancreatic cancer, a common digestive system malignancy, is dubbed the “king of cancers”. The role of pyrophosis-related genes (PRGs) in pancreatic cancer prognosis is yet unknown. In pancreatic cancer and normal tissue, we discovered 9 PRGs that are expressed differently in pancreatic cancer and healthy tissue. Based on the differential expression of PRGs, 2 clusters of pancreatic cancer cases could be identified. The 2 groups had significant disparities in total survival time. The prognostic model of a 5-PRGs signature was created using least absolute shrinkage and selection operator (LASSO) method. The median risk score was used to split pancreatic cancer patients in The Cancer Genome Atlas (TCGA) cohort into 2 groups: low risk and high risk. Patients classified as low-risk had significantly higher survival rates than those classified as high-risk (P < .01). The same results were obtained by validating them against the Gene Expression Omnibus database (P = .030). Cox regression statistical analysis showed that risk score was an independent predictor of overall survival in pancreatic cancer patients. Functional enrichment analysis revealed that apoptosis, cell proliferation, and cell cycle-related biological processes and signaling pathways were enriched. Additionally, the immunological status of the high-risk group worsened. In conclusion, a novel pyroptosis-related gene signature can be used to predict pancreatic cancer patient prognosis.