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.

Public Health Relevance

If they can be delivered specifically to cancer, nanoparticles (innovative imaging and therapeutic agents) have the potential to revolutionize cancer diagnosis and therapy. This research proposal aims to improve our fundamental understanding of the delivery of nanoparticles to tumor sites. This profound understanding can be translated to help accelerate and improve the use of these nanoparticles to safely and more effectively manage and treat human cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Career Transition Award (K99)
Project #
1K99CA160764-01
Application #
8165828
Study Section
Subcommittee G - Education (NCI)
Program Officer
Schmidt, Michael K
Project Start
2011-07-05
Project End
2013-06-30
Budget Start
2011-07-05
Budget End
2012-06-30
Support Year
1
Fiscal Year
2011
Total Cost
$173,880
Indirect Cost
Name
Stanford University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
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Frieboes, Hermann B; Smith, Bryan R; Chuang, Yao-Li et al. (2013) An integrated computational/experimental model of lymphoma growth. PLoS Comput Biol 9:e1003008
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