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Disease Progression Model Of Pancreatic Cancer Developed By Penn Researchers

Date:
May 19, 2005
Source:
University of Pennsylvania School of Medicine
Summary:
Building on previous work, researchers at the University of Pennsylvania School of Medicine have developed an animal model of pancreatic cancer that closely mimics disease progression in humans. From this, they hope to develop new treatments for this deadly disease. Advanced pancreatic cancer is among the most lethal of cancers, with a one-year survival rate after chemotherapy of only 17 to 28 percent of patients.

Philadelphia, PA -- Building on previous work, researchers at the University of Pennsylvania School of Medicine have developed an animal model of pancreatic cancer that closely mimics disease progression in humans. From this, they hope to develop new treatments for this deadly disease. Advanced pancreatic cancer is among the most lethal of cancers, with a one-year survival rate after chemotherapy of only 17 to 28 percent of patients, according to the National Cancer Institute.

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Sunil R. Hingorani, MD, PhD, and David A. Tuveson, MD, PhD, both in the Departments of Medicine and Cancer Biology, and colleagues, engineered mice to express two mutant genes commonly associated with pancreatic cancer: Kras, an oncogene, and p53, a well-studied tumor suppressor. The investigators linked physiological, cellular, and genomic changes due to mutations in Kras and p53 in the mice to changes similar to that observed in pancreatic cancer patients. They report their findings in the May issue of Cancer Cell.

The disease that develops in the Kras and p53 mutant mouse model demonstrates distinct similarities to human pancreatic cancer at multiple levels. "In terms of clinical presentation, metastatic burden, and histological changes in tissue, this model appears to closely mimic the human disease," says Hingorani.

Clinical symptoms in the mutant mice mirrored those displayed in pancreatic cancer patients, such as abdominal swelling and muscle loss. Similarly, the progression of pancreatic cancer metastases paralleled that seen in the human disease. "In this model, pancreatic cancer metastasizes to the liver, lungs, diaphragm, and adrenal glands, all the same places that human pancreatic cancer metastasizes," says Tuveson.

The frequency of metastases to these various organ sites was also highly similar to that seen in humans. In human patients, 60 to 80 percent develop metastases to the liver; and 50 to 60 percent develop metastases to the lungs. In the genetically modified animals, 63 percent displayed liver metastases, and 45 percent displayed lung metastases -- further emphasizing the accuracy of this model in mimicking human pancreatic cancer.

To understand the progression of pancreatic cancer, Hingorani and colleagues studied cell lines derived from primary tumor and metastasized cells. From this, the researchers established the occurrence of genomic instability in the mouse model. Genomic instability -- continuous formation of mutated chromosomes -- leads to widespread genetic changes throughout the affected cells. Genomic instability is seen in many human epithelial cancers, including pancreatic cancer, and is thought to be a driving force in the transition from local tumor growth to metastases of cancers. According to Hingorani, "This model may prove useful to understanding human pancreatic and other epithelial cancers because the key event of genomic instability that has been very difficult to model in the mouse appears to be recapitulated here."

In the pancreatic tumors and metastases from the mouse model, the investigators characterized other molecules implicated in pancreatic cancer. Often, the expression of molecules such as growth factors and their receptors will offer possible targets for treatment. The researchers were surprised to discover a high degree of heterogeneity in expression among these key molecules across the specimens. After ruling out the likelihood that this variability resulted from additional acquired mutations in known key tumor suppressor pathways, Hingorani suggests, "there may actually be unique genetic routes to pancreatic cancer, such that not all pancreatic cancers are equivalent."

The development of the first animal model for pancreatic cancer that fully imitates the progression of the human condition will likely open many new doors in understanding this debilitating disease. "With a model that can generate the full spectrum of disease, from preinvasive to invasive and metastastic lesions, we can begin to tease out the events that are linked to the progression of pancreatic cancer," explains Hingorani. "In trying to understand what events are required to create and support invasive and metastatic disease, we hope to translate our findings into better therapies," states Hingorani.

The study was funded in part by the National Institutes of Health, the National Cancer Institute, the National Pancreas Foundation, and an AACR-PanCAN Career Development Award. Study co-authors are Lifu Wang, Chelsea Combs, Therese B. Deramaudt, and Anil K. Rustgi from Penn, as well as Asha S. Multani and Sandy Chang, from M.D. Anderson Cancer Center, and Ralph H. Hruban from Johns Hopkins University.



Story Source:

The above story is based on materials provided by University of Pennsylvania School of Medicine. Note: Materials may be edited for content and length.


Cite This Page:

University of Pennsylvania School of Medicine. "Disease Progression Model Of Pancreatic Cancer Developed By Penn Researchers." ScienceDaily. ScienceDaily, 19 May 2005. <www.sciencedaily.com/releases/2005/05/050519142409.htm>.
University of Pennsylvania School of Medicine. (2005, May 19). Disease Progression Model Of Pancreatic Cancer Developed By Penn Researchers. ScienceDaily. Retrieved December 21, 2014 from www.sciencedaily.com/releases/2005/05/050519142409.htm
University of Pennsylvania School of Medicine. "Disease Progression Model Of Pancreatic Cancer Developed By Penn Researchers." ScienceDaily. www.sciencedaily.com/releases/2005/05/050519142409.htm (accessed December 21, 2014).

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