Identification of a potential prognostic model combining pyroptosis-related gene with immune microenvironment for pancreatic ductal adenocarcinoma

Background Pancreatic ductal adenocarcinoma (PDAC) is a fatal tumor with grave prognosis. Pyroptosis, a programmed cell death, is involved in tumorigenesis. However, a few studies have elucidated the functions of pyroptosis in PDAC. Methods The mRNA expression profiles were downloaded from the TCGA and GEO databases. Univariate and LASSO Cox regression analyses were used to screen out differentially expressed genes (DEGs) and construct the pyroptosis-related genes (PRGs) risk model. The efficiency of model was examined by Kaplan–Meier curve, ROC curve, and nomogram. Univariate and multivariate Cox regression analyses were utilized to assess whether the risk model could be used as an independent prognostic factor. The biological function was analyzed by GO, KEGG, and GSEA enrichment analysis. qRT-PCR and immunohistochemical staining detected gene expression. Results Totally 9 PRGs with differential expression were identified between normal and PDAC tissues. Then, according to PRGs, we filtered out three key DEGs and constructed the prognostic risk model. Kaplan–Meier curve, ROC curve, and nomogram indicated that the prognostic risk model had high survival prediction efficiency. Meanwhile, the risk model had also shown to be an independent prognostic factor. Further functional enrichment analysis showed that cell adhesion, PI3K–AKT signaling pathway, and dysregulated immune status may be associated with PDAC development. External validation of the model was carried out in the GEO cohort, and the results were similar to that in the TCGA cohort. Finally, the expression of three genes was verified by qRT-PCR and immunohistochemical staining. Conclusion The prognostic risk model established in this study can give a good prediction of the prognosis of PDAC patients, which might provide insights into clinical treatments and prognostic prediction of PDAC.