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Fluorescent Metastatic Mouse Models of Pancreatic Cancer for Drug Discovery

  • Michael Bouvet
  • Robert M. Hoffman
Chapter

Abstract

Here we describe our cumulative experience with the development and preclinical application of imageable, clinically-relevant, metastatic orthotopic mouse models of pancreatic cancer. These models utilize the human pancreatic cancer cell lines which have been genetically engineered to selectively express high levels of green fluorescent protein (GFP) or red fluorescent protein (RFP). Fluorescent tumors are established subcutaneously in nude mice, and tumor fragments are then surgically transplanted onto the pancreas. Locoregional tumor growth and distant metastasis of these orthotopic implants occurs spontaneously and rapidly throughout the abdomen in a manner consistent with clinical human disease. Highly specific, high-resolution, real-time quantitative imaging of tumor growth and metastasis may be achieved in vivo without the need for contrast agents, invasive techniques, or expensive imaging equipment. We have shown a high correlation between florescent optical imaging and magnetic resonance imaging in these models. Transplantation of RFP-expressing tumor fragments onto the pancreas of GFP-expressing transgenic mice may be used to facilitate visualization of tumor–host interaction between the pancreatic cancer cells and host-derived stroma and vasculature. Such in vivo models have enabled us to serially visualize and acquire images of the progression of pancreatic cancer in the live animal, and to demonstrate the real-time antitumor and antimetastatic effects of novel therapeutic strategies on pancreatic malignancy. These fluorescent models are therefore powerful and reliable tools with which to investigate metastatic human pancreatic cancer and novel therapeutic strategies directed against it.

Keywords

Pancreatic Cancer Green Fluorescent Protein Nude Mouse Human Pancreatic Cancer Human Pancreatic Cancer Cell Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of SurgeryUniversity of California San Diego, Moores Cancer CenterLa JollaUSA

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