A High-Throughput Analytic Strategy for Discovery of Molecular Targeting Ligands for Pancreatic Diseases

Pancreatic diseases are worldwide public health issues and account for substantial health care utilization and spending. Thus far, effective therapeutic options remain limited. The emergence of proteomic technologies has improved our understanding of differential protein expression in chronic pancreatitis (CP) and pancreatic cancer. Yet, developing target-specific interventions based on proteomic profiles will require significant improvement in the methodologies to generating targeting moieties. In this dissertation, we explore phage display as a method for selecting molecular ligands in pancreatic diseases. Phage display is a versatile screening technique that has been used in drug discovery, epitope mapping, and ligand identification. Next-generation sequencing has dramatically increased the throughput of phage display, and a large database of potential moieties can be easily generated. However, methods to guide ligand selection has yet to be matured, especially for in vivo phage display because there are more diverse targets present in the system. Thus, the overarching goal of this dissertation is to establish an in vivo phage display-based pipeline and utilize quantitative methods to advance the identification of targeting moieties and their molecular targets for pancreatic diseases.

The first aim of this dissertation is to evaluate four analytical methods in selecting high specific targeting ligands for deep-sequenced in vivo phage display. Using the mouse model of CP as a disease model, we identify seven 7-mer peptides that demonstrate preferential binding to the CP over the healthy pancreas. In the second aim of this dissertation, we further evaluate the cellular selectivity of CP-targeted peptides and utilize these findings to design a targeted liposomal formulation to deliver a small molecular drug, apigenin, to achieve targeted antifibrotic therapy for CP. Finally, we leverage phage display beyond ligand identification by using functional proteomics to identify the binding partner of a peptide specific to pancreatic cancer-associated fibroblasts. The finding of a novel molecular target motivates the development of a stromal targeted drug delivery platform to reprogram the crosstalk between cancer cells and cancer- associated fibroblasts in pancreatic cancer. Collectively, these aims establish a streamline from ligand identification to the development of target-specific nanomedicine for pancreatic diseases.