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Background: Pancreatic adenocarcinoma (PAAD) is a highly lethal disease with a poor prognosis. Increasing evidence indicates that immunophenotyping can reveal the combined immune status of the tumor, which is closely related to treatment response and patient prognosis. Therefore, in this study, a comprehensive analysis of the potential prognostic values of immune-related genes in PAAD was performed.

Methods: The data of PAAD patients were obtained from TCGA and GEO databases. Immune cell infiltration (ICI) analysis was conducted using the CIBERSORT algorithm. ICI classification was then performed with the ConsensusClusterPlus package based on the CIBERSORT results. Immune-related differentially expressed genes (DEGs), which were screened from the ICI subtypes, were applied to identify the prognosis-related feature genes in PAAD. Further univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were performed to determine the hub genes. ROC curves, survival analysis and a nomogram were used to assess the risk score model constructed with hub genes. The biological functions of the hub genes were annotated via GSEA. Furthermore, the correlation between the expression of hub genes and the infiltration of macrophages and CD8+ T cells was assessed via immunohistochemistry (IHC) in 19 PAAD samples.

Results: Analyses of the TCGA and GEO databases revealed that both KRT7 and ITGB6 were strongly linked to a worse prognosis in PAAD. Then, KRT7 and ITGB6 were used to stratify the PAAD patients into low- and high-risk subgroups. The high-risk group had a poorer prognosis and less immune cell infiltration than the low-risk group. GSEA showed that ITGB6 and KRT7 were mainly enriched in the P53 signaling, cadherin binding and NF-κB binding pathways. Furthermore, KRT7 and ITGB6 expression was correlated with the infiltration of macrophages and CD8+ T cells in the TME, which was verified by IHC analysis.

Conclusion: Both KRT7 and ITGB6 are promising biomarkers of PAAD prognosis.