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Cornering kinases
Dana-Farber's William Sellers, MD, and Matthew Meyerson, MD, PhD, have set a goal for themselves and their collaborators that might modestly be described as gargantuan: locating every harmful error, or mutation, in every one of a class of genes associated with cancer. The job involves analyzing hundreds, eventually thousands, of tumor cell samples to pinpoint abnormalities in specific genes —— a task that requires literally millions of scans of cells' DNA.
Scientific data produced at Dana-Farber, like breaking news, is a hot commodity.
Illustration by David Cutler
And that is only the first part of the challenge. "The information we're generating is very difficult to display and use in a traditional way," Sellers explains. "There was a need for a computer program that would organize the data so it could be easily visualized —— where the mutations we were looking for would be clear."
Sellers and Meyerson's project focuses on a class of enzymes known as kinases, which direct the flow of signals inside and outside of cells. Mutations in kinases, particularly in the 94 types known as tyrosine kinases, are found in many forms of cancer.
The data-handling job was assigned to Meng Wang and Charlie Hatton, Dana-Farber programming experts based at the Eli and Edythe L. Broad Institute, a collaboration of the Massachusetts Institute of Technology, Harvard University and affiliated hospitals such as Dana-Farber, and the Whitehead Institute for Biomedical Research.
Wang and Hatton grouped the genes for tyrosine kinases into families and used commercial software to highlight the sections of DNA that family members have in common. They then "layered in" the ability to show where mutations have been found.
The result: a program where relevant information is as easy to pick out as a striped shirt in a rack of plaids. "Mutations that occur in the same region of several genes are more likely to be involved in cancer," says Hatton, who developed the design of the system while Wang wrote the software. "This system helps researchers find them."
For now, the program is available only to the DFCI team and their collaborators. Later this year, however, researchers plan to make it accessible online as Sellers and Meyerson publish their findings. "We'll be adding additional capabilities as well as different categories of kinases," Hatton remarks. "The goal is to build a broad repository of data that is rich and valuable enough for other investigators to use."
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