a, Santa Cruz, joined Johns Hopkins last September as a participant in the university’s Institute for Computational Medicine. “There are some things you can do with a computer that we hope will be useful in predicting the cancer risks associated with some genetic mutations,” she said. “We’re not quite there yet, but that’s our goal.”

Karchin began working on the new computer tool as a postdoctoral fellow in the lab of Andrej Sali, a professor of biopharmaceutical sciences and pharmaceutical chemistry at the University of California, San Francisco. For the current journal article, the biochemical tests to validate the computer tool were conducted in the lab of Alvaro Monteiro at the H. Lee Moffitt Cancer Center & Research Institute in Tampa, Fla. Sali and Monteiro are co-authors of the journal article.

In their experiments, the researchers focused on inherited mutations in the BRCA1 gene. A significant number of breast and ovarian cancer cases are believed to be caused by such mutations, possibly because they disable a gene that normally suppresses cancer.

To test the computer tool, Karchin and her colleagues used it to analyze 36 “point mutants” on the BRCA1 gene, meaning locations where a single letter in a string of DNA differed from the sequence found in the general population. This mutation caused an amino acid residue change in the protein produced by the gene. “Some of these types of variations can put a woman at greater risk for developing ovarian or breast cancer,” Karchin said. “The question is: Which ones?”

To answer it, the researchers examined 16 factors in three categories. One category focused on whether the mutated genes produced proteins that performed their jobs properly. The second involved studies of the physical structure of the mutated gene. The third category was an assessment of the gene’s evolutionary history, looking at how long the changed amino acid residue position has been preserved in vari
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