Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer (PC). Numerous studies have reported that the tumor microenvironment (TME) was signi cantly correlated with the oncogenesis, progress, and prognosis of various malignancies. Therefore, mining of TME-related genes is reasonably important to improve the overall survival (OS) of patients with PDAC. Methods: The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was applied to identify differential expressed genes (DEGs). Functional and pathway enrichment analyses, protein-protein interaction (PPI) network construction and module analysis, overall survival analysis and tumor immune estimation resource (TIMER) database analysis were then performed on DEGs. Results: Data analysis indicated that higher immune scores were correlated with better overall survival (P = 0.033). Differential expression analysis obtained 90 intersection genes in uencing both stromal and immune scores. Among these intersection genes, CA9, EBI3, SPOCK2, WDFY4, CD1D and CCL22 were signi cantly correlated with OS in PDAC patients. Moreover, multivariate Cox analysis revealed that CA9, SPOCK2 and CD1D were the most signi cant prognostic genes, and were closely correlated with immune in ltration in TCGA cohort. Further analysis indicated that CD1D were signi cantly related with immune cell biomarkers for PDAC patients. Conclusions: In summary, our ndings provide a more comprehensive insight into TME and show a list of prognostic immune associated genes in PDAC. However, further studies on these genes need to be performed to gain additional understanding of the association between TME and prognosis in PDAC.