New Model May Predict Breast Cancer Patients’ Response Before Chemotherapy

New Model May Predict Breast Cancer Patients’ Response Before Chemotherapy
Researchers are developing a model to predict which patients with triple negative breast cancer will respond to chemotherapy before the start of the treatment, according to a study recently presented at the San Antonio Breast Cancer Symposium. If validated, the tool would allow patients to know beforehand whether chemotherapy will be effective in their case and, if not, spare them potentially harmful side effects. Breast cancer treatments usually target a specific protein that is particularly active in these cancer cells – either estrogen receptor, progesterone receptor, or the Her2 protein. But triple negative breast cancer cells do not express any of these proteins and therefore has no targeted treatment, which is why it is particularly aggressive. Women with this disease have higher response rates to chemotherapy, however, as treatments are designed to broadly attack dividing cells. According to Katherine Hoadley, PhD, first author of the study, the model developed by her team was moderately successful at predicting which patients with triple negative breast cancer will respond to chemotherapy, but more work is necessary to improve its accuracy. To develop their model, researchers analyzed the profiles of gene expression in breast cancer samples from 389 patients before treatment as well as data on how each patient responded to chemotherapy. They started by analyzing gene expression profiles in some of the samples (training samples) to identify which genes were associated with a successful response to chemotherapy and built the predictive ability of the model. They then validated the model in the remaining samples, showing that the model was able to predict which samples belonged to patients who showed
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