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Mathematical Modeling Can Predict Herceptin Response

Technique identifies PTEN protein expression as biomarker for stratifying breast cancer patients

WEDNESDAY, July 29 (HealthDay News) -- A new mathematical modeling technique may help identify breast cancer patients who are most likely to respond to Herceptin, according to a study published online July 28 in Cancer Research.

Dana Faratian, M.D., of the University of Edinburgh in the United Kingdom, and colleagues created a mathematical modeling technique that used 56 differential equations to analyze 56 different pathway components in 122 breast cancers treated with Herceptin.

The researchers found that quantitative expression of PTEN -- a protein that acts as a tumor suppressor gene -- was more predictive of Herceptin response than any other pathway component in isolation or when tested by multivariate analysis (relative risk, 3.0).

"For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies," the authors conclude.

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