July 28, 2009 — Expression of the phosphatase and tensin homolog (PTEN) protein might help predict which breast cancer patients will be resistant to treatment with trastuzumab (Herceptin, Genentech), according to a new study published in the August 15 issue of Cancer Research.
The research uses computers to mathematically model biologic pathways that test the efficacy of a therapy. This method, known as systems biology, is relatively new and not yet clinically applicable, but has been hailed as a "great step forward" in the effort to determine which breast cancer patients will benefit from anti-HER2 therapy.
Trastuzumab "has benefited thousands of women with HER2-positive breast cancer, but only a third to half of patients treated with this agent respond," said lead author Dana Faratian, MD, a clinical lecturer in pathology at the University of Edinburgh in the United Kingdom, in a press statement. "We need to know which patients will [and which patients] won't respond to treatment, and this research is a step toward realizing that aim."
The key to using computational power to evaluate the efficacy of a targeted cancer therapy lies in the fact that pathways can be translated relatively easily into mathematical models, suggest Dr. Faratian and his coauthors.
This study "is a major step forward because, as revolutionary as [trastuzumab] has been, there are many patients who fail. This helps us understand why, and it would not have been possible without the new mathematical techniques," said Sofia Merajver, MD, PhD, scientific director of the Breast Oncology Program at the University of Michigan Comprehensive Cancer Center in Ann Arbor. She is a senior editorial board member of Cancer Research and was not involved in the study.
First Success of Systems Biology in Oncology
"The use of therapies targeted against the products of cellular oncogenes in signaling pathways lends itself to this approach because these pathways can readily be modeled using ordinary differential equations," Dr. Faratian and colleagues explain.
The investigators used 56 differential equations to build a model and analyze the change in concentrations of 56 separate biologic entities, including proteins. They found that quantitative PTEN protein expression was the key determinant of resistance to the anti-HER2 therapy, both in the math model and in vitro.
Furthermore, this quantitative PTEN protein expression was more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6 - 5.5; P < .0001) than other pathway components taken in isolation and when 122 breast cancers treated with trastuzumab were tested by multivariate analysis.
Dr. Faratian suggested that these mathematical techniques have not been embraced by clinicians. "Systems biology is much hyped, but there are relatively few success stories where it has been applied to clinical problems, and it has been viewed with a degree of skepticism by clinicians because of this," he told Medscape Oncology. "This is the first time it has been successfully applied to the problem of therapeutic resistance in cancer, and it provides a framework in which it can be used as a tool in clinical decision-making."
Dr. Faratian also said that systems biology is a "long way off" from being used in the clinic, but that it has other utility in drug development. "For helping decisions on which markers should be measured in large clinical trials, the approach can provide essential and valuable information. For example, systems-biology models were used, [in a US Food and Drug Administration] application that saw the heart drug ranolazine enter the clinic, as part of the evidence on its safety profile."
The study authors received grant support from Breakthrough Breast Cancer, the Breast Cancer Campaign, the Scottish Funding Council (Strategic Research Development Grant), and the Biotechnology and Biological Sciences Research Council.
Cancer Res. 2009;69(16). DOI: 10.1158/0008-5472.CAN-09-0777.
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