Detection of Tumor-Associated Autoantibodies in the Sera of Pancreatic Cancer Patients Using Engineered MUC1 Glycopeptide Nanoparticle Probes

Pancreatic cancer is one of the deadliest cancers worldwide, mainly due to late diagnosis. Therefore, there is anurgent need for novel diagnostic approaches to identify the disease as early as possible. We have developed a diagnosticassay for pancreatic cancer based on the detection of naturally occurring tumor associated autoantibodies against Mucin-1 (MUC1) using engineered glycopeptides on nanoparticle probes. We used a structure-guided approach to developunnatural glycopeptides as model antigens for tumor-associated MUC1. We designed a collection of 13 glycopeptides tobind either SM3 or 5E5, two monoclonal antibodies with distinct epitopes known to recognize tumor associated MUC1.Glycopeptide binding to SM3 or 5E5 was confirmed by surface plasmon resonance and rationalized by moleculardynamics simulations. These model antigens were conjugated to gold nanoparticles and used in a dot-blot assay to detectautoantibodies in serum samples from pancreatic cancer patients and healthy volunteers. Nanoparticle probes withglycopeptides displaying the SM3 epitope did not have diagnostic potential. Instead, nanoparticle probes displayingglycopeptides with high affinity for 5E5 could discriminate between cancer patients and healthy controls. Remarkably,the best-discriminating probes show significantly better true and false positive rates than the current clinical biomarkersCA19-9 and carcinoembryonic antigen (CEA).