The early detection of pancreatic ductal adenocarcinoma (PDAC) is a complex clinical obstacle yet is key to improving the overall likelihood of patient survival. Current and prospective carbohydrate biomarkers carbohydrate antigen 19-9 (CA19-9) and sialylated tumor-related antigen (sTRA) are sufficient for surveilling disease progression yet are not approved for delineating PDAC from other abdominal cancers and noncancerous pancreatic pathologies. To further understand these glycan epitopes, an imaging mass spectrometry (IMS) approach was used to assess the N-glycome of the human pancreas and pancreatic cancer in a cohort of patients with PDAC represented by tissue microarrays and whole-tissue sections. Orthogonally, these same tissues were characterized by multiround immunofluorescence that defined expression of CA19-9 and sTRA as well as other lectins toward carbohydrate epitopes with the potential to improve PDAC diagnosis. These analyses revealed distinct differences not only in N-glycan spatial localization across both healthy and diseased tissues but importantly between different biomarker-categorized tissue samples. Unique sulfated biantennary N-glycans were detected specifically in normal pancreatic islets. N-glycans from CA19-9–expressing tissues tended to be biantennary, triantennary, and tetra-antennary structures with both core and terminal fucose residues and bisecting GlcNAc. These N-glycans were detected in less abundance in sTRA-expressing tumor tissues, which favored triantennary and tetra-antennary structures with polylactosamine extensions. Increased sialylation of N-glycans was detected in all tumor tissues. A candidate new biomarker derived from IMS was further explored by fluorescence staining with selected lectins on the same tissues. The lectins confirmed the expression of the epitopes in cancer cells and revealed different tumor-associated staining patterns between glycans with bisecting GlcNAc and those with terminal GlcNAc. Thus, the combination of lectin-immunohistochemistry and lectin-IMS techniques produces more complete information for tumor classification than the individual analyses alone. These findings potentiate the development of early assessment technologies to rapidly and specifically identify PDAC in the clinic that may directly impact patient outcomes. Display omitted •N-glycan structures localize to distinct regions in normal and PDAC tumor tissue.•N-glycan composition differs between biomarker-stratified PDAC subtypes.•Modeling with N-glycan IMS and biomarker data improves tumor/normal discrimination.•Multiplexed IMS and lectin staining potentiates new PDAC classification strategies. N-glycosylation is an attractive target for PDAC biomarker discovery because of its well-understood roles in oncogenesis, cancer maintenance, and metastasis. Using MALDI-IMS, we observed distinct histopathology localized differences in N-glycosylation distributions between healthy and cancerous tissues. We combined the tumor-to-normal ratio of N-glycan changes determined from IMS with biomarker IHC data into modeling which improved PDAC identification over models utilizing either data set individually. This multiplexed approach potentiates the development of cross-disciplinary biomarker panels for pancreatic cancer detection.