A novel immunogenomic signature to predict prognosis and reveal immune infiltration characteristics in pancreatic ductal adenocarcinoma

Background The immune response in the tumor microenvironment (TME) plays a crucial role in cancer progression and recurrence. We aimed to develop an immune-related gene (IRG) signature to improve prognostic predictive power and reveal immune infiltration characteristics of pancreatic ductal adenocarcinoma (PDAC). Methods The Cancer Genome Atlas (TCGA) PDAC was used to construct a prognostic model as a training cohort. International Cancer Genome Consortium (ICGC) and the Gene Expression Omnibus (GEO) database were set as validation datasets. Prognostic genes were screened by using univariate cox regression. Then, a novel optimal prognostic model was developed by using least absolute shrinkage and selection operator (LASSO) Cox regression. Cibersort and Estimate algorithms were used to characterize tumor immune infiltrating patterns. TIDE algorithm was used to predict immunotherapy responsiveness. Results A prognostic signature based on five IRGs (MET, ERAP2, IL20RB, EREG, and SHC2) was constructed in TCGA-PDAC and comprehensively validated in ICGC and GEO cohorts. Multivariate cox regression analysis demonstrated that this signature had an independent prognostic value. The area under curve (AUC) value of the receiver operating characteristic (ROC) curve at 1-year, 3-year, and 5-year of survival were 0.724, 0.702, and 0.776 respectively. We further demonstrated that our signature has better prognostic performance than the recently published ones and is superior to traditional clinical factors such as grade and TNM stage in predicting survival. Moreover, we found higher abundance of CD8+ T cells and lower M2-like macrophages in the low-risk group of TCGA-PDAC, and predicted a higher proportion of immunotherapeutic responders in the low-risk group. Conclusions We constructed and validated an optimal prognostic model of independent prognostic value. This five-gene signature could predict immune infiltration characteristics. The signature helps to stratify PDAC patients according to the responsiveness to immunotherapy.