UNS: Collaborative Research: Unique binding geometries: Engineering & Modeling of Sticky Patches on Lipid Nanoparticles for Effective Targeting of Otherwise Untargetable cells

PI: Sofou, Stavroula / Kevrekidis, Yannis G.提案号：1510015 / 1510149该提案旨在探索和理解携带药物的纳米颗粒的行为，当它们接近癌细胞时，其表面会被重组并形成“粘片”。这些新的结合几何形状有可能显著扩大治疗药物靶向的癌细胞类型。该项目将这种靶向方法与单分子光学测量和数学建模相结合，以了解其机制，并为优化颗粒的设计提供信息。基于在选择性靶向和使用载药纳米颗粒治疗癌细胞方面有希望的初步结果，研究人员将探索和理解载药脂质纳米颗粒的行为，其表面相分离形成肿瘤细胞近端“粘片”。潜在的假设是，靶向成功取决于这些斑块上结合配体的密集浓度，并且这些新型结合几何形状的运输和结合动力学显著延长了结合时间，从而导致内化。这些假设将通过四个具体目标来解决，其中包括：1)使用集体测量，评估有效细胞结合（关联）的动力学，粘性脂质纳米颗粒的解离和内化过程；2)使用单分子光学跟踪技术，评估纳米颗粒-受体复合物的寿命，导致复合物细胞内化的纳米颗粒相关受体的数量，以及每个细胞相关纳米颗粒的潜在共定位受体；3)开发、实施和使用实验信息的通用计算工具来测试机制假设，评估所使用纳米颗粒的物理和化学属性的相对重要性，并最终帮助设计纳米颗粒，以便以最佳/选择性地靶向其他无法靶向的癌症；4)利用数学模型对粘质纳米颗粒进行优化设计，并对其体外效果进行评价。该方法为纳米颗粒引入了一种新的几何结构，使其能够结合其他无法靶向的癌细胞，并有可能最终改善晚期癌症患者的生活质量，延长他们的预期寿命。通过这项活动，研究人员将交叉训练一名博士研究生（罗格斯大学）专注于物理化学和异质脂膜的自组装，另一名博士研究生（普林斯顿大学）专注于多尺度建模和实验生物物理光学。与牛津应用数学学院的国际合作将涉及第三名博士生，他将多次访问普林斯顿/罗格斯大学与pi进行互动。研究者将此研究整合到他们对本科生的指导、课程开发和本科课程的扩展中。除了开发和传播突出这项研究的教育材料外，还将支持已经实施的高中学生外展计划。该奖项由化学、生物工程、环境和运输系统部门的生物医学工程项目共同资助；通过数学科学创新孵化器计划获得数学科学；由数学和物理科学理事会通过多学科活动办公室提供。

PI: Sofou, Stavroula / Kevrekidis, Yannis G. Proposal Number: 1510015 / 1510149This proposal aims to explore and understand the behavior of drug-carrying nanoparticles whose surface becomes reorganized and forms "sticky patches" when they get close to cancer cells. These new binding geometries have the potential to significantly expand the types of cancer cells that can be targeted with therapeutic agents. The project combines this targeting approach with single molecule optical measurements and mathematical modeling, to understand the mechanisms, and inform the design of optimized particles.Based on promising initial results in selectively targeting and treating cancer cells using drug-carrying nanoparticles, the investigators will explore and understand the behavior of drug-carrying lipid nanoparticles whose surface phase-separates to form "sticky patches" proximally to tumor cells. The underlying hypotheses are that the targeting success lies in the dense concentration of the binding ligands on these patches, and that the transport and binding kinetics of these novel binding geometries give significantly longer binding times resulting in internalization. These hypotheses will be addressed through four specific aims, which include: 1) Using collective measurements, evaluation of the kinetics of effective cell binding (association), dissociation and internalization processes of sticky lipid nanoparticles; 2) Using single molecule optical tracking techniques, evaluation of the lifetime of the nanoparticle-receptor(s) complex, of the number of nanoparticle-associated receptors that lead to cellular internalization of the complex, and of potential co-localization of receptors for each cell-associated nanoparticle; 3) Development, implementation and use of an experimentally informed general computational tool to test the mechanistic hypotheses, to evaluate the relative importance of the physical and chemical attributes of the nanoparticles used, and ultimately to help design them so as to optimally/selectively target otherwise untargetable cancers; and 4) Utilization of the mathematical model to optimize the design of sticky lipid nanoparticles, and to evaluate their efficacy in vitro. The proposed approach introduces an new geometry for nanoparticles to bind otherwise untargetable cancer cells, and has the potential to ultimately improve the quality of life of patients with advanced cancer and extend their life expectancy. Through this activity the investigators will cross-train one Ph.D. student (at Rutgers) with focus on physical chemistry and self-assembly of heterogeneous lipid membranes, and a second Ph.D. student (at Princeton) with focus on multiscale modeling and experimental biophysics optics. An international collaboration with Applied Mathematics in Oxford will involve a third PhD student, who will repeatedly visit Princeton/Rutgers to interact with the PIs. The investigators will integrate this research in their mentoring of undergraduate students, curriculum development and expansion of undergraduate programs. High school student outreach programs already in place will be supported, in addition to the development and dissemination of educational materials highlighting this research. This award is co-funded by the Biomedical Engineering Program in the Chemical, Bioengineering, Environmental and Transport Systems Division; by Mathematical Sciences through the Mathematical Sciences Innovation Incubator Program; and by the Directorate of Mathematical and Physical Sciences through the Office of Multidisciplinary Activities.