A paper in the April issue of Genes and Development describes two new mouse models for aculte myeloid leukemia (AML). These models show promise for elucidating the mechanisms of specific cancers and for predicting how patients will respond to treatment.
One of the most confounding aspects of cancer is the genetic instability that is a hallmark of the uncontrolled cells. Because of this genetic instability the same cancer can have completely different genetic mutations in two different patients and it is the specific mutations that will determine whether or not a treatment is effective. A good example of this is AML, which can be the end result of different mutations in white blood cells. Most patients with AML recieve the same standard treatment of chemotherapy followed by either bone marrow transplant or additional rounds of chemotherapy, but this treatment is only effective in one fourth of patients. Most patients with AML die within months of diagnosis.
To understand this phenomenon researchers at the Lowe lab in Cold Spring Harbor engineered two mouse models of AML. One which combined mutations in the genes N-Ras and AML1/ETO and another that combined N-Ras and the gene MLL. These are common combinations seen in populations of patients with AML.
Just like in human cases, mice expressing the AML1/ETO containing combination responded to treatment. Mice expressing MLL/N-ras did not respond to chemotherapy and succumbed to the leukemia. The MLL expressing version of the cancer is similarly associateed with a dismal prognosis in humans. The researchers found that mice expressing the MLL oncogene were unable to activate the p53 pathway. When they knocked down p53 in AML/ETO mice the leukemia became unresponsive to treatment and the mice died.
Not only did the model correctly mimic what is seen in real cases but it also allowed investigation into the mechanism responsible. Use of specifically tailored mouse models may provide the key to bridging the gap between what scientists have learned about cancer and how that knowledge is used.
To read the paper click here
