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Singling out the real breast cancer among the lumps
Date:10/25/2011

kers specific for different subtypes would improve the odds of getting the diagnosis right.

To explore this idea, Zangar and his colleagues at PNNL and Duke University picked 23 candidate biomarkers and measured them using tests similar to the ones found in clinics. The team compared proteins in blood from four groups of women about 20 women in each of the four subtypes of breast cancer to women with benign lumps that had previously been identified as false positives. Then, Zangar's team homed in on a handful of biomarkers for each subtype that could best distinguish between the most true positives and the least false positives.

The biomarker panel for each subtype was significantly better at distinguishing between breast cancer and benign lumps than mammograms or single biomarkers. The statistical test the team used rates performance from 0.5 to 1.0 -- with 0.5 indicating the biomarker panel predicts cancer randomly and 1.0 means it's perfect. Mammograms and the best single biomarkers rank around 0.8. But for two of the most common breast cancer subtypes, the biomarker panels ranked above 0.95 and reached 0.99 depending on which proteins were included in the panel.

"Perhaps researchers haven't found good biomarkers because they've been treating the different subtypes as a single disease, but they actually represent unique diseases that are associated with different biomarkers," said Zangar. "We're hopeful these results can be repeated because these assays would markedly improve our ability to detect breast cancer early on, when treatment is more effective, less costly and less harsh."

In addition, the study hints about the underlying biology of breast cancer. Four of the biomarkers are proteins involved in normal breast development that turn on and off at different times during growth. The fact that these proteins show up in different ways, depending on the subtype of breast cancer, might provide clues about what goes wrong wh
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Contact: Mary Beckman
mary.beckman@pnnl.gov
509-375-3688
DOE/Pacific Northwest National Laboratory
Source:Eurekalert  

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