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Researchers Develop Strategy To Predict Mutations Involved In Cancer Drug Resistance

Date:
March 21, 2003
Source:
Whitehead Institute For Biomedical Research
Summary:
Researchers have devised a way to identify genetic mutations that will cause resistance to targeted anti-cancer drugs, even before patients are treated – a finding that will aid scientists involved in drug development and allow physicians to monitor patients for resistance problems before they occur.

CAMBRIDGE, MA – Researchers have devised a way to identify genetic mutations that will cause resistance to targeted anti-cancer drugs, even before patients are treated – a finding that will aid scientists involved in drug development and allow physicians to monitor patients for resistance problems before they occur.

Scientists at Whitehead Institute for Biomedical Research developed the screen to identify mutations that cause patients with chronic myeloid leukemia, or CML, to become resistant to Gleevec, a "magic bullet" cancer-fighting drug that targets the protein produced by BCR/ABL, the gene that causes this rare form of leukemia.

"In the leukemia cells of a CML patient, BCR/ABL is constantly mutating," said George Daley, leader of the research team that developed the screening strategy. "Cells carrying certain mutations can resist the drug and continue to grow while the remainder of leukemia cells are suppressed. We have found a way to discover those mutations experimentally."

In studies reported March 21 in the journal Cell, the scientists used recombinant DNA methods to randomly mutate the BCR/ABL gene to mimic potential variations that might be found in CML patients. The mutated genes were then transferred into millions of mouse blood cells and exposed to Gleevec. While most cells succumbed to the drug, some of the cells with specific variations thrived.

"We looked for those cells that continued to grow, extracted them and sequenced their genes," said Mohammad Azam, a postdoctoral researcher at Whitehead and lead author of this new study, which was supported by the National Institutes of Health. That examination revealed 15 mutations researchers elsewhere had previously linked to Gleevec resistance in CML patients – plus 97 more. As research on the mutations continues and more patients are surveyed, more of these mutations are likely to be found.

With the catalogue of mutations in hand, Daley said, physicians could one day examine patients who've relapsed because of resistance to Gleevec and pinpoint which of the 112 mutations is causing problems, or better still, detect the presence of a mutation before the patient relapses. "Doctors could monitor the patient's leukemia at the molecular level for signs of impending resistance," he said, "and decide when it is best to switch medications."

The screening technique could also be used by pharmaceutical scientists involved in drug development, Daley said. Scientists can detect the location of the variations that cause drug resistance to first-generation compounds and design new drugs that remain effective despite those mutations. Physicians could then prescribe a combination of drugs that complement one another, much like the drug cocktails given to patients with HIV or antibiotic-resistant bacterial infections.

Scientists have been anxious to figure out how cells resist drugs such as Gleevec, one of a new class of what some call "magic bullet" chemotherapy drugs that seek out and bind only to cancer cells. Although CML is rare – there are about 5,000 cases in the U.S. each year – it is caused by a gene scientists have studied extensively, Daley said, and is a good model for other cancers.

"We understand this leukemia with molecular precision, so its significance outweighs its incidence," Daley said. "Everything that we're learning about Gleevec and BCR/ABL will be a recurring theme for every new target-directed agent being developed against cancer."

Gleevec binds to a specific pocket within the BCR/ABL kinase domain – the part of the protein that regulates enzyme function. All mutations previously found in CML patients who relapsed while on Gleevec therapy have been found within that domain, most around the drug binding pocket.

But once the Whitehead researchers analyzed the gene sequence results from their study, it was clear that many of the mutations lay in other parts of the protein, some at great distances from the drug-binding pocket and thought to have no direct involvement with drug binding.

As part of this project, Daley and Azam worked with Robert Latek, a senior bioinformatics scientist at Whitehead, to map the 112 mutations the team isolated on a 3-D computer model of BCR/ABL.

The model not only casts a vivid image of the location of the mutations, Latek noted, it also begins to illustrate how the different parts of the protein interact with one another to influence gene function. Such information was difficult to visualize before the age of computer modeling.

"We're not just randomly guessing what will bind to a particular protein of interest," he said. "By creating a 3-dimensional structural model, we're able to look at the actual site that we want the drug to bind to and design a drug customized for that binding site."


Story Source:

The above story is based on materials provided by Whitehead Institute For Biomedical Research. Note: Materials may be edited for content and length.


Cite This Page:

Whitehead Institute For Biomedical Research. "Researchers Develop Strategy To Predict Mutations Involved In Cancer Drug Resistance." ScienceDaily. ScienceDaily, 21 March 2003. <www.sciencedaily.com/releases/2003/03/030321075411.htm>.
Whitehead Institute For Biomedical Research. (2003, March 21). Researchers Develop Strategy To Predict Mutations Involved In Cancer Drug Resistance. ScienceDaily. Retrieved July 25, 2014 from www.sciencedaily.com/releases/2003/03/030321075411.htm
Whitehead Institute For Biomedical Research. "Researchers Develop Strategy To Predict Mutations Involved In Cancer Drug Resistance." ScienceDaily. www.sciencedaily.com/releases/2003/03/030321075411.htm (accessed July 25, 2014).

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