How do Nanoparticles Target Cancer? An In Vivo Experimental/Mathematical Study

描述(申请人提供)：根据世界卫生组织的数据，今年(2010年)，癌症将成为世界上最大的杀手。纳米技术可能是通过革命性地改变癌症诊断和治疗来扭转这一趋势所需的游戏规则改变者。尤其是可注射的靶向纳米颗粒(NPs)在寻找、成像和消灭癌症方面具有巨大的潜力。然而，尽管现有的NPs种类繁多，但交付可能仍然是实现其临床前景的最大障碍。 目前，在选择纳米粒作为更好的生物医学载体时，关键的是没有考虑到不同类型的纳米粒靶向肿瘤的能力。这是因为目前对系统注射的纳米粒子在微观尺度上的动态行为知之甚少。我们在活着的小鼠身上对几种NP类型(具有不同的物理性质，如量子点和纳米管)进行了初步的显微镜实验，这些类型在我们测试的NP类型中显示出截然不同的靶向特征。因此，这项建议的一个主要目标是通过实验观察和数学模型发展对NP在活体受试者中的行为的基本了解，从而指导最终用于静脉注射的NPs的临床成像和治疗。该提案最终旨在了解不同大小和形状的NPs在活体受试者肿瘤中的靶向行为。对NP靶向的详细机制洞察可以产生一个系统，用于针对每一种应用(即通过定制的纳米结构实现药物的个性化)对这些试剂进行智能经验设计。此外，还可以预测用所选的NPs进行成像或治疗的最佳时间。因此，这可以使医生有能力选择适当的成像/治疗剂和时间点，这将提高疗效并导致更早发现癌症，增加治疗效果，并减少基于NP的毒性。 为了了解纳米颗粒在肿瘤中的行为，该方案描述了如何使用活体显微镜来探索肿瘤组织内和周围的主动、被动和非特异性纳米颗粒相互作用，包括靶向肿瘤血管内皮细胞、外渗和靶向肿瘤细胞表面。然而，仅靠活体显微镜并不足以解释纳米颗粒在活体动物中的行为。由于在选择不适合特定应用的纳米粒子上损失了大量的时间、精力和金钱，生物医学纳米技术界迫切需要使用先进的定量模型来严格理解观察到的现象。这项建议描述了数学模型的发展，该模型真实地模拟纳米颗粒与肿瘤血管的结合，预先验证选择进入临床前模型的纳米颗粒。与活体实验密切相关的数学建模将有力地相互告知和指导。这将产生一个通用的框架，根据该框架选择合适的诊断/治疗纳米颗粒的大小和形状，以便在实验室并最终在临床上进行测试。因此，这将更快地导致癌症靶向纳米颗粒的卓越临床应用。

DESCRIPTION (provided by applicant): This year (2010), cancer will become the world's biggest killer according to the World Health Organization. Nanotechnology is likely the game-changer needed to reverse this trend by revolutionizing cancer diagnosis and therapy. Injectable, targeted nanoparticles (NPs) in particular have enormous potential to seek, image, and destroy cancer. Yet despite the enormous diversity of NPs available, delivery remains perhaps the biggest obstacle to the realization of their clinical promise. The current paradigm in the selection of NPs as superior biomedical delivery vehicles critically does not account for the ability of different NP types to target tumor. This is because there currently exists very little understanding about the dynamic behavior of systemically injected NPs on the microscale. We have performed preliminary microscopy experiments on several NP types (with varied physical properties, such as quantum dots and nanotubes) in living mice that display broadly different targeting characteristics across the NP types we have tested. A chief objective of this proposal is therefore to guide selection of NPs for eventual use in intravenous delivery for clinical imaging and therapy by developing a fundamental understanding of NP behavior in living subjects via experimental observation and mathematical models. The proposal ultimately aims to understand the targeting behavior of NPs of diverse size and shape in the tumor of living subjects. Detailed mechanistic insight of NP targeting could yield a system for the intelligent empirical design of these agents for each application (i.e., personalization of medicine via customized nanostructures). Moreover, the optimal times for imaging or therapy with the selected NPs could be predicted. This could thus arm physicians with the ability to select the appropriate imaging/therapeutic agent and time-point, which would increase efficacy and lead to earlier cancer detection, increased therapeutic efficacy, and decreased NP-based toxicity. To understand nanoparticle behavior in tumors, this proposal delineates how intravital microscopy will be used to explore active, passive, and non-specific nanoparticle interactions within and around tumor tissue, including targeting to tumor blood vessel endothelium, extravasation, and targeting to tumor cell surfaces. However, intravital microscopy alone will not be sufficient to explain nanoparticle behavior in living animals. Because much time, effort, and money is forfeit on choosing nanoparticles inappropriate for a given application, an urgent need exists in the biomedical nanotechnology community to rigorously understand observed phenomena using advanced quantitative models. This proposal describes the development of mathematical models that realistically simulate nanoparticle binding to tumor blood vessels, pre-validating the nanoparticles chosen to enter pre-clinical models. Mathematical modeling in intimate association with intravital experiments will robustly inform and guide one another. This will result in a generalized framework by which to choose the appropriate size and shape of diagnostic/therapeutic nanoparticles to test in the lab and eventually in the clinic. This will thus much more rapidly lead to superior clinical applications for cancer-targeted nanoparticles.