Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with poor prognosis, largely due to its late-stage diagnosis, dense desmoplastic stroma, and limited efficacy of current treatment modalities—including cytotoxic chemotherapy, molecularly targeted agents, and immunotherapy. These approaches have shown only modest clinical benefits, highlighting the urgent need for innovative strategies that can more effectively and selectively target the tumor. Recombinant adeno-associated virus (AAV) vectors represent a promising platform due to their low immunogenicity and capacity for long-term transgene expression; however, efficient and selective delivery to pancreatic tumors remains a critical challenge. This is primarily attributed to the fibrotic and immunosuppressive tumor microenvironment, which impairs vector penetration and transduction, and the absence of naturally occurring serotypes with high PDAC specificity. To address these limitations, we present an integrative AAV capsid engineering strategy that leverages rational design, in silico modeling, and directed evolution to enhance PDAC targeting. Our approach involves designing Plectin-1–binding ligands based on the overexpression of Plectin-1 on PDAC cells, optimizing ligand affinity through structure-based computational modeling, and identifying novel targeting motifs via in vivo selection using an AAV peptide display library coupled with next-generation sequencing. This multi-faceted platform is expected to yield AAV variants with superior tumor tropism and gene delivery efficiency. By combining computational insight with empirical evolution, this study establishes a versatile framework for the development of more effective and selective gene therapies for PDAC—offering a promising therapeutic avenue for this intractable disease.
