Ligand-modified liposomes as drug delivery systems for the active targeting of pancreatic cancer
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Updated: Jan 20, 2026

Targeting Drugs to Larval Zebrafish Macrophages by Injecting Drug-Loaded Liposomes
Published on: February 18, 2020
Yerin Jang1, Jaehee Jang1, Jaewoo Son2
1School of Integrative Engineering, Chung-Ang University, Seoul, 06974, Republic of Korea.
Abstract:
Pancreatic cancer is among the most fatal malignancies worldwide. The aggressive nature of this disease, coupled with late-stage diagnosis and limited therapeutic options, highlights the urgent need for innovative treatment approaches. Targeted therapy has emerged as a promising strategy to enhance therapeutic efficacy while minimizing systemic toxicity. Liposomes, as versatile nanoparticles, have shown significant potential to contribute to the develpment of drug delivery system. These lipid-based vesicles encapsulate chemotherapeutic drugs, shield them from degradation, and promote greater accumulation within tumor cites. Furthermore, liposomes can be surface-modifed with various ligands to improve their specificity and cellular uptake. Research on liposome-based targeted chemotherapy for pancreatic cancer has explored useful ligand-based strategies to enhance drug delivery to pancreatic cancer cells. In this review, liposome-based targeted strategies for pancreatic cancer are classified by ligand type, including antibodies, aptamers, carbohydrates, proteins and peptides, and integrates case studies to demonstrate how different targeting approaches translate into improved cellular uptake, therapeutic efficacy, and antitumor effects. In addition, emerging formulations such as dual-targeting liposomes are described, highlighting their potential to further strengthen treatment performance. The review summarizes the current research landscape of liposome-based targeted drug delivery systems for pancreatic cancer, providing insights into promising biomarkers and ligand-mediated targeting strategies. It further discusses broader opportunities for target exploration and liposomal design optimization, as well as future research directions aimed at overcoming existing limitations and improving therapeutic outcomes.
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