The method is based on a mathematical model that determines when a cancer becomes drug-resistant during therapy. It does this by estimating the probability of finding drug-resistant mutant cells at different stages of cancer progression and examining the fate of individual mutant colonies during therapy. It then pinpoints under what circumstances these mutant cells become a problem and the therapy stops being effective.
The finding will help physicians determine when a combination of drugs will be more effective in fighting a cancer.
Researchers Natalia Komarova and Dominik Wodarz present their findings in this week's online edition of the Proceedings of the National Academy of Sciences.
The researchers applied their model to chronic myeloid leukemia, a cancer of the blood and bone marrow that is treated today with a bone marrow transplant, drug therapy, or both. The drug used for treating CML works by attacking a specific oncogene -- the gene responsible for the initiation and progression of CML. The treatment is successful during the early stages of the progression of the disease. In later stages, however, the cancer develops a resistance to the drug because the oncogene mutates. Once the drug can no longer recognize the cancer cells, the treatment fails.
Using their model, the researchers concluded that mutant cells existed before treatment began and that the drug was not effectively eliminating these cells. "This is important because a good knowledge about the origin of cancer cells' resistance to drugs is the first step towards more effectively breaking this resistance," said Komarova, assistant professor of mathematics with a joint appointment in ecology and evolutionary biology, and the first
Contact: Iqbal Pittalwala
University of California - Irvine