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NF1 Research Provides Breakthrough in Understanding Cancer Drug Resistance

By September 4, 2009December 18th, 2023Awareness, Science & Research

Why do tumor cells become resistant to drug therapies? Why do some cancer patients respond to drugs and others do not? Even with what seems to be a really ‘good drug’, resistance is recognized as a major problem. Light is shed on this issue in a paper* in the September 2 issue of Nature from studies of leukemias that utilize mice with Nf1 gene inactivation. The paper is authored by Children’s Tumor Foundation’s NF Preclinical Consortium researchers Dr. Jennifer Lauchle, Dr. Ernesto Diaz-Flores (also a former Foundation Young Investigator Awardee) and Dr. Kevin Shannon (UCSF) along with colleagues at UCSF and other institutions including NCI, University of Texas Southwestern and Pfizer Inc.

Leukemia is a fairly rare complication of NF1, but Nf1 gene mutations appear to play a key role in certain leukemias which makes leukemia a useful study model for finding effective drug therapies for NF1 as well as more broadly for other tumor disorders and cancer. In the Nature paper Lauchle et al. created mouse models of leukemia based on Nf1 gene deficiency leukemia, and also based on the addition of ‘cooperating mutations’. In these mice as leukemia developed the cells were genetically labeled and could be tracked.

These mice were then treated with drugs that inhibit MEK, a drug target that is hyperactive in NF1 and other tumors and is a candidate target for therapy. By treating and studying the different mouse models the team found that drug resistance developed because specific cell clones grow and become established prior to the time of drug treatment. The team also identified some candidate ‘drug resistance genes’ that included increased levels of gene RasGRP1 levels and reduced levels of p38 kinase activity in cells resistant to MEK inhibitors.

This novel approach provides a strategy for understanding how drug resistance develops and for unraveling the genes involved, and hopefully paves the way to understanding, potentially predicting and treating tumors as effectively as possible.

 

* Lauchle et al., Nature Sept 2: http://www.nature.com/nature/journal/vaop/ncurrent/full/nature08279.html