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New strategies to predict the potential of a breast tumour to spread are presented in an article in Molecular Systems Biology. These findings could help early identification of patients who are at high risk of developing metastasis and may also be important for better targeted therapy.
Early diagnosis is essential in decreasing breast cancer mortality but it is difficult to predict which tumours found will go on to spread and form metastases. When metastasis risk is thought to be high, aggressive chemotherapy is systematically deployed. This type of treatment has serious side effects and significantly impacts on the patient?s quality of life. Despite saving lives the lack of precision means a significant number of women are being over-treated when local surgery and radiotherapy would suffice. One of the major challenges in predicting metastatic potential is to find sets of molecular markers that carry sufficient information on the disease state to enable an accurate classification. Trey Ideker and colleagues combine data on gene expression with an extensive map of cellular biochemical interactions to take into account the "wiring diagram" of a human cell and re-group seemingly disparate alterations in gene expression into more coherent pathways. Using data from two large scale studies on breast cancer metastasis, the authors show that this integrative strategy does not only improve accuracy and reproducibility of the prediction but, importantly, also provide valuable biological insight into the biochemical and molecular mechanisms that underly metastasis. This type of approach is anticipated to extend well beyond the example of breast cancer metastasis and cancer classification and will open new avenues in the ways human diseases are understood, diagnosed and treated. Author contact: Trey Ideker (University of California San Diego, USA
E-mail: trey@bioeng.ucsd.edu Free full article available online. (C) Molecular Systems Biology press release.
Message posted by: Trevor M. D'Souza
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