Pancreatic ductal adenocarcinoma (PDA) is the 3rd leading cause of cancer-death in the U.S.. Glycans, such as CA-19-9, are biomarkers of PDA and are emerging as important modulators of cancer phenotypes. Herein, we utilized a systems-based approach integrating glycomic analysis of human PDA and the well-established KC mouse model, with transcriptomic data to identify and probe the functional significance of aberrant glycosylation in pancreatic cancer. We observed both common and distinct patterns of glycosylation in pancreatic cancer across species. Common alterations included increased levels of α-2,3- and α-2,6-sialic acids, bisecting GlcNAc and poly-LacNAc. However, core fucose, which was increased in human PDAC, was not seen in the mouse, indicating that not all human glycomic changes can be modeled in the KC mouse. In silico analysis of bulk and single cell sequencing data identified ST6GAL1, which underlies α-2,6-sialic acid, as overexpressed in human PDA, concordant with histological data. Enzymes levels correlated with the stage of clinical disease. To test whether ST6GAL1 promotes pancreatic cancer we created a novel mouse in which a pancreas-specific genetic deletion of this enzyme overlays the KC mouse model. Analysis of our new model showed delayed cancer formation and a significant reduction in fibrosis. Our results highlight the importance of a strategic systems-approach to identifying glycans whose functions can be modeled in mouse, a crucial step in the development of therapeutics targeting glycosylation in pancreatic cancer.