A Cancer rainbow mouse for simultaneous assessment of multiple oncogenes Genetically engineered mouse models of cancer hold significant promise for studying the basic cellular and molecular mechanisms underlying tumor formation and then evaluating prospective therapies. However, several factors have limited the success of current models and development of next-generation technologies. First, the conceptualization, engineering, and generation of a new mouse strain is outside the scope of most laboratories. These projects encounter high rates of failure and continue to carry significant risk for even the most seasoned and prestigious research programs. Second, establishing roles for tumor driver genes in vivo in important cellular behaviors such as differentiation, proliferation, and migration often requires extensive compound breeding, making these experiments expensive and time consuming. Third, deep-sequencing continues to identify new tumor driver genes at a rate in which the utilization of a one driver gene per mouse paradigm is unable to keep pace. Therefore to meet these demanding needs, we have developed the Cancer rainbow (Crainbow) mouse platform to generate user-defined, reliable, and multiplexed models of tumorigenesis in a single genetically tractable system. In our R21 IMAT funded project, we have demonstrated in vivo proof-of-principle for this technology and are now beyond the initial phases of this project. With this system we are able to stochastically express multiple tumor driver genes in a diversity of tissues and cell-types and simultaneously monitor their effects at a single cell level using spectrally resolvable fluorescent protein reporters. The objective of this R33 proposal is to perform extensive and rigorous testing of our emerging technology to ensure its reliability and accessibility for the scientific community. To achieve this objective, our specific aims will 1) Optimize Crainbow Generation and Expression, 2) Validate Crainbow technology In Vivo, and 3) Validate Quantitative Multiplex Analysis of Driver Gene Activity In Vivo. We expect the Crainbow platform to transform cancer research by enabling all investigators to reliably build mouse models of cancer on-demand and with minimal inherent risk. The flexible and forward-thinking design of Crainbow will also enable robust delivery of genome-editing tools to provide multiplexing of endogenously edited driver genes with cellular and temporally precise resolution. Through multiplex driver gene analysis and enabling of a decentralized user-base, the Crainbow platform will enable synergistic modeling of a diversity of cancers and provide future models for testing personalized therapeutic intervention.

Public Health Relevance

The Crainbow platform will decentralize mouse engineering thereby transforming mouse model development into a user-defined commodity accessible by most standard cancer research laboratories. Crainbow's unique ability to study multiple driver genes with cellular resolution and in a single mouse will transform lists of candidate drivers into validated molecular and cellular targets. When fully validated and implemented by the scientific community, Crainbow will enable the discovery of new forms of cancer prevention, diagnosis, and treatment.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Exploratory/Developmental Grants Phase II (R33)
Project #
5R33CA191198-02
Application #
9011511
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Li, Jerry
Project Start
2015-02-09
Project End
2018-01-31
Budget Start
2016-02-01
Budget End
2017-01-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Duke University
Department
Anatomy/Cell Biology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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Jean-Charles, P-Y; Snyder, J C; Shenoy, S K (2016) Chapter One - Ubiquitination and Deubiquitination of G Protein-Coupled Receptors. Prog Mol Biol Transl Sci 141:1-55
Snyder, Joshua C; Pack, Thomas F; Rochelle, Lauren K et al. (2015) A rapid and affordable screening platform for membrane protein trafficking. BMC Biol 13:107