Certain cancer risks can be passed down through
families, the result of tiny changes in a family's genetic
code. But not all genetic changes are deadly. To help
medical counselors and physicians identify the mutations
that pose the greatest health risks, researchers at four
institutions, including Johns Hopkins, have developed and
validated a new computer tool.
The system, described in the Feb. 16 issue of
Public Library of Science Computational Biology,
evaluates 16 "predictive features" to help answer a
critical question: Is a particular mutation a harmless
variation or a genetic glitch that could set the stage for
cancer? In blind biochemical tests involving 36 samples
containing genetic mutations whose association with breast
and ovarian cancer was unknown, the computer tool
demonstrated an accuracy rate exceeding 94 percent in
identifying protein functions that are believed to be
linked to a higher risk of cancer.
The researchers cautioned that the computer tool by
itself cannot yet predict future cancer cases. But they
believe it can be a fast and useful supplement to
traditional biochemical tests, which are far more
time-consuming, costly and labor-intensive, and do not
always yield conclusive results.
"When people are diagnosed with certain types of
cancer, other family members sometimes get genetic testing
to find out if they, too, are predisposed to this disease,"
said Rachel Karchin, an assistant professor of
at Johns Hopkins and lead author of the journal article.
"But sometimes, the standard tests find small genetic
variations that may be harmful or benign. Our computational
test may help pinpoint which one it is. We hope the system
will eventually give counselors and doctors an important
new tool to help them advise patients about whether they
need to take preventive steps to keep cancer from
Karchin, who earned a doctorate in computer science
from the University of California, 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,
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 various organisms. The last category is
important because harmful mutations tend to be eliminated
by evolutionary selection because of the damage they
inflict on their carriers.
The researchers plugged these factors into a computer
formula that identified the gene mutations most likely to
be linked with cancer. Karchin was pleased that the system
was highly successful at finding harmful mutations during
the blind tests in Monteiro's lab. She believes it has a
promising future. "Genetic counselors now base some of
their advice on family history," she said. "But family
histories are often incomplete. If we can give genetic
counselors another tool, it could be very helpful to a lot
The other co-authors of the journal paper were Sean V.
Tavtigian, of the International Agency for Research on
Cancer in Lyon, France; and Marcelo A. Carvalho, of the
Moffitt Cancer Center. The research was supported by grants
from the National Institutes of Health.