Olga Modlich and colleagues, from the University of Düsseldorf and Bayer HealthCare AG in Germany, analysed samples of breast tissue from five healthy individuals and tumour tissue from fifty-six breast cancer patients treated with preoperative systemic chemotherapy (PST) with a combination of the anti-cancer drugs epirubicin and cyclophosphamide. The genes present in the samples were analysed using a DNA microarray - a collection of microscopic DNA spots attached to a solid surface used to measure the expression levels of large numbers of genes simultaneously.
From the DNA microarray analysis the authors were able to identify a total of fifty-seven 'predictor' genes active in tumours: thirty-one genes associated with a favourable response and twenty-six genes associated with a poor response. The authors then tested the ability of these genes to predict the response of twenty-seven breast cancer patients, who were then treated with PST.
The predictor genes could be used to correctly predict the outcome of PST in all cases of partial remission and nearly 75% of cases of complete remission of primary tumours. According to the authors the use of microarray technology to identify genes that can predict response to chemotherapy could represent a powerful tool to identify patients for whom PST is the most appropriate, and would be the most successful form of treatment.
Currently, decisions about whether to use chemotherapy as a breast cancer treatment are based on factors such as patients' age and type and size of tumour. These factors do not provide sufficient information to tailor treatment to the individual patient. Nearly all breast cancer patients receive standard chemotherapy treatment, despite the potential for a poor response to therapy, adverse side effects and excess healthcare costs. According to the authors "the identification of molecular markers predictive of patients' responsiveness to treatment is becoming a central focus of research". The ability to predict a patient's response to chemotherapy for breast cancer would be of benefit to doctors and patients, shifting the focus away from a standard treatment for all patients and towards treatment based on predictions made from patients' genetic background.
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