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Genomic profiling of Breast Tumors might
determine prognosis, treatment
Newswise — Combining a breast cancer
patient's clinical characteristics with a
genomic profile of her tumor may provide
important information for predicting an
individual patient’s prognosis and
accurately guiding treatment options,
according to a new study led by researchers
in the Duke Comprehensive Cancer Center (DCCC)
and Duke’s Institute for Genome Sciences &
Policy (IGSP).
“Our goal is to treat patients on a more
individualized basis, matching the right
drugs with the right patients,” said Anil
Potti, M.D., an oncologist and researcher in
the DCCC and the IGSP.
“The combination of these two methods, one
of which uses the clinical description of
patient’s breast cancer and the other which
looks at gene expression at a molecular
level in a patient’s tumor, may allow us to
do that with unprecedented accuracy.
"This
represents a robust approach to
personalizing treatment strategies in
patients suffering from breast cancer.”
The findings appear in the April 2, 2008
issue of the Journal of the American
Medical Association. The study was
funded by the Jimmy V Foundation, the
American Cancer Society and the Emilene
Brown Research Fund.
Researchers looked at almost 1000 breast
tumor samples, and corresponding patient
data, and applied existing technology -- a
computerized system called Adjuvant! -- to
assess clinical characteristics and make
predictions of recurrence based on them.
By then comparing gene expression in these
tumor samples, the researchers were able to
see specific genomic patterns among patients
with aggressive cancers, and those whose
cancers were less likely to recur.
“We knew from previous studies that
Adjuvant! tends to overestimate disease
recurrence in younger patients,” Potti said.
“We hypothesized that genomic profiling
could be a complementary tool that would
more precisely define clinical outcomes, and
could also help to aid in selecting the
right drug for a given patient.”
By using the clinical and genomic tools
together and cross-comparing data, the
researchers were able to not only say that a
particular patient has a ‘high’ risk of
recurrence, but they could be more specific;
for instance, they could predict that a
particular patient was 90 percent likely to
see her cancer recur, Potti said.
“This is important because with this data,
we might decide to treat this person more
aggressively even than someone else who is
considered ‘high risk’ but may have only a
60 percent likelihood of recurrence,” he
said.
“Moreover, we can identify specific options
for chemotherapy in such patients as well,
by correlating gene expression in a tumor
with its response, or non-response, to
certain chemotherapies.”
The findings have already been put into
practice as part of several clinical trials
at Duke for cancer patients.
A tumor’s genomic make-up is being used to
dictate the choice between a traditional
chemotherapy regimen and an alternate drug
that is more likely to benefit an individual
patient.
One such trial involving almost 300 patients
with breast cancer is expected to start at
Duke this spring.
Other researchers involved with this study
include Chaitanya Acharya, David Hsu, Carey
Anders, Ariel Anguiano, Kelly Salter, Kelli
Walters, Bradford Perez, Richard Redman,
Sascha Tuchman, Cynthia Moylan, Sayan
Mukherjee, William Barry, Holly Dressman,
Geoffrey Ginsburg, Katherine Garman, Gary
Lyman Kelly Marcom, and Joseph Nevins.
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