Engineering researchers at Columbia University have developed a new model to help predict how a breast cancer will grow. The researchers won the Sage Bionetworks/DREAM Breast Cancer Prognosis Challenge for the work.
The research was published in the April 17, 2013 issue of the journal Science Translational Medicine. Read the abstract of “Development of a Prognostic Model for Breast Cancer Survival in an Open Challenge Environment.”
Right now, there are three tests – Oncotype DX, MammaPrint, and Mammostrat – that analyze certain genes to figure out if a breast cancer is likely to come back (recurrence). The results of these tests, combined with other characteristics of the cancer, can help women and their doctors make more informed decisions about whether or not to use chemotherapy or other treatments after surgery for early-stage breast cancer to reduce the risk of recurrence.
This new model uses what the scientists call “attractor metagenes” – groups of genes that they found behaved similarly in several types of cancer, including breast cancer. The model analyzes the activity of the attractor metagenes in a breast cancer sample.
To test the model’s accuracy, it was used it to analyze genetic and clinical information from 2,000 women diagnosed with breast cancer. The model’s prognosis predictions were compared to the women’s outcomes. The Columbia University researchers’ model was more accurate than the other 1,700 models submitted by about 350 researchers from more than 35 countries.
While the winning model isn’t being used in an available test just yet, these results are exciting. The engineering researchers hope to work with medical researchers to develop tests incorporating the attractor metagenes that will offer women and their doctors more and better information on how a breast cancer is likely to behave and respond to treatment.
Stay tuned to Breastcancer.org Research News for the latest information on tests to predict a breast cancer’s prognosis.