Values of a novel pyroptosis-related genetic signature in predicting outcome and immune status of pancreatic ductal adenocarcinoma

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Abstract
Pyroptosis is an emerging form of programmed cell death associated with progression in malignancies. Yet, there are few studies reporting on the association between pancreatic ductal adenocarcinoma (PDAC) and pyroptosis. Therefore, we aimed to construct a pyroptosis-related genetic signature to predict the clinical outcome and immune status in PDAC patients. RNA-seq data of 176 PDAC patients from The Cancer Genome Atlas (TCGA) and 167 PDAC patients from the Genotype-Tissue Expression Project were analysed for pyroptosis-related differentially expressed genes (DEGs) between PDAC and normal pancreas. The risk signature of DEGs was analysed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis and its accuracy was validated in the Gene Expression Omnibus (GEO) cohort (n = 190). Functional enrichment analyses were performed to explore the mechanisms of the DEGs. The immune characteristics were evaluated using single-sample gene set enrichment analysis and ESTIMATE algorithms for each group. A nine-gene risk signature was generated from LASSO Cox regression analysis and classified PDAC patients into either a high- or low-risk group according to the median risk score. The high-risk group had significantly shorter overall survival than the low-risk group and it was verified in the external GEO database. A nomogram based on the risk signature was constructed and showed an ideal prediction performance. Functional enrichment analyses revealed that pyroptosis might regulate the tumor immune microenvironment in PDAC. Immune infiltration evaluation suggested that immune status was more activated in the low-risk group than in the high-risk group. The risk signature encompassing nine pyroptosis-related genes may be a prognostic marker for PDAC. Pyroptosis might affect the prognosis of PDAC patients via regulating the tumor immune microenvironment.
Funding Information
  • National Natural Science Foundation of China (82072644, 81772522)

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