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Disease progression model of pancreatic cancer developed by Penn researchers

imals, 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 l
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Source:University of Pennsylvania


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