Genomic Profiling of Breast Cancers a Better Treatment Tool
Findings point to personalized therapies that help predict disease recurrence.
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(SOURCES: Duke University, news release; JAMA/Archives journals, news release, both April 1, 2008)
TUESDAY, April 1 (HealthDay News) -- Determining the genetic profile of a breast tumor, along with an assessment of a patient's clinical characteristics, can help predict prognosis and guide treatment choices, a Duke University study concludes.
"Our goal is to treat patients on a more individualized basis, matching the right drugs with the right patients," Dr. Anil Potti, an oncologist and researcher in the Duke Comprehensive Cancer Center and Duke's Institute for Genome Sciences & Policy, said in a prepared statement.
"The combination of these two methods, one of which uses the clinical description of a patient's breast cancer and the other which looks at the 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," Potti said.
The team examined almost 1,000 breast tumors and corresponding patient data and used a computerized system called Adjuvant! to assess clinical characteristics and make predictions of recurrence. The researchers then compared gene expression in the tumor samples and were able to identify specific genomic patterns among patients with aggressive cancers and those with cancers less likely to recur.
"We knew from previous studies that Adjuvant! tends to overestimate disease recurrence in younger patients. 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," Potti said.
Not only did their method identify patients at high risk for cancer recurrence, it specified the degree of that risk. For example, they could predict that a patient had a 90 percent risk of recurrence.
"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," Potti 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 study was published in the April 2 issue of the Journal of the American Medical Association.
This study "demonstrates the potential value of using microarray-based gene signatures to refine outcome predictions," Chiang-Ching Huang and Markus Bredel, of the Feinberg School of Medicine at Northwestern University in Chicago, wrote in an accompanying editorial.
"In an attempt to tailor risk estimation, these investigators shy away from pure metagene predictors but instead focus on genes with mechanistic implication in breast cancer. Because these genes represent potential targets for specific molecular therapy, this approach represents an advance in the changing landscape of oncology toward individualized patient management," they wrote.
More information
The American Cancer Society has more about breast cancer. 
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