Engineering Lipid Nanoparticles for sIRNA Delivery to Silence Identified Targest in Cancer Cells

RNA interference (RNAi) is a potentially powerful tool that can specifically target the expression of virtually any protein without the expensive and time-consuming drug development studies. Despite the initial excitement and extensive efforts, the potential impact of RNAi approaches is yet to be fully realized in clinical settings. This is mainly due to the challenges in delivering RNA structures effectively. This dissertation focuses on the development and optimization of an LNP platform designed for siRNA delivery, addressing critical challenges such as cellular uptake, cytotoxicity, and gene silencing efficiency. While the scope of this work is limited to LNPs, it lays the foundation for the future development of a lipid-polymer nanoparticle (LPNP) system. Chapter 1 provides a comprehensive overview of the breast cancer treatment landscape, discussing established therapies like hormone therapy and HER family receptor inhibitors, as well as emerging and experimental strategies such as immune checkpoint inhibitors and kinase inhibitors. This chapter establishes the foundation for understanding RNAi’s potential to address the therapeutic gaps in breast cancer. Chapter 2 focuses on the development and optimization of an LNP platform to deliver siRNA efficiently to breast cancer cells. The LNP platform serves as a versatile foundation, capable ofincorporating additional components for enhanced delivery efficiency. This chapter highlights the platform's refinement, achieving effective gene silencing, and sets the stage for future development of an advanced lipid-polymer nanoparticle (LPNP) system. Chapter 3 investigates mechanisms of resistance to enzalutamide in castration-resistant prostate cancer (CRPC). By using gradual and shock resistance induction models, specific molecular targets associated with resistance are identified. These targets provide opportunities for RNAibased therapeutic interventions in prostate cancer. Chapter 4 explores prostate cancer using tissue microarray (TMA) analysis to identify ...