MEMP PhD Thesis Defense: Eva Cai

Engineering Layered Lipid Nanoparticles for Synergistic siRNA Delivery

Despite advances in cancer therapeutics and improvements in survival rates for solid tumors, the overall survival for high-grade serous ovarian cancer (HGSOC) has not improved significantly over the last 50 years. It is thus critical to develop novel, effective, and safe therapeutics. Given that many phenotypes of HGSOC are associated with underlying genetic alterations, RNA interference (RNAi) has emerged as a promising therapeutic strategy to regulate gene expression and ultimately disrupt tumor growth. Specifically, small interfering RNA (siRNA) has high specificity, high efficiency, and low toxicity in gene silencing. However, siRNAs need to efficiently enter the intracellular environment to achieve gene silencing, a process that can be facilitated by a delivery vehicle. In addition, given the metastatic nature of HGSOC in the peritoneal cavity, it is crucial that therapeutics reach the target cell types of interest while avoiding healthy tissues. Targeted delivery of nucleic acids remains a challenge in drug development and drug delivery, and improving delivery specificity may enable efficacy at lower therapeutic doses while reducing potential side effects. The goal of this thesis is to develop layered lipid nanoparticles (LLNP) delivering synergistic siRNAs as a therapeutic strategy for HGSOC. We first identify and validate synergistic biological pathways that have therapeutic impact when downregulated with siRNAs in HGSOC. We then engineer an LLNP platform that leverages the layer-by-layer electrostatic assembly approach to improve siRNA delivery specificity to tumor cells over healthy cells. We also further optimize the LNP composition using iterative design of experiments, analyzing various design parameters that impact transfection and encapsulation efficiency. Finally, we demonstrate that the synergistic siRNA LLNP is effective in suppressing tumor growth and extending survival in an orthotopic HGSOC model. Taken together, we demonstrate the utility of LLNPs as a modular platform for the targeted delivery of therapeutic nucleic acids, both in HGSOC and potentially in other clinical applications.

Thesis Supervisor:
Paula Hammond, PhD
Institute Professor and Dean for the School of Engineering, MIT

Thesis Committee Chair:
Sangeeta Bhatia, MD, PhD
John J. and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science, MIT

Thesis Readers:
Sarah Hill, MD, PhD
Assistant Professor of Medicine, Harvard Medical School
Physician Scientist, Department of Medical Oncology at Dana-Farber Cancer Institute

Daniel Anderson, PhD
Professor, Chemical Engineering and Institute for Medical Engineering and Science, MIT
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Eva Cai is inviting you to a scheduled Zoom meeting

Topic: Eva Cai MEMP PhD Thesis Defense
Time: Tuesday, June 23, 2026, 10:00 AM Eastern Time (US and Canada)

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