deCODE Discovers Fourth Major Set of Common Genetic Variants Linked to Risk of Estrogen Receptor-Positive Bre...(breast cancers appear to confer risk exc...)

Date:4/27/2008

breast cancers, appear to confer risk exclusively of ER+ tumors. deCODE is applying these variants as the basis for a DNA-based reference laboratory risk-assessment test the company plans to launch in the coming months. Such a test will allow for the identification of women who may benefit from regular screening with standard as well as new, high-resolution technologies. The American Cancer Society now recommends that women who are at a 20-50% above- average risk of breast cancer should consider undergoing annual magnetic- resonance imaging (MRI) scans as well as mammograms.

"Within the past two years we have identified specific sequence variants that underlie much of the inherited risk of the common forms of breast cancer, the most frequently diagnosed cancer in women. And we have now reached a long awaited tipping point in this progress: the ability to identify, through a simple genetic test, a large proportion of women who are at a clinically- meaningful risk of the disease. The rationale for such testing is all the more compelling in ER+ cancers, since drugs such as tamoxifen have been shown to be successful in preventing as well as treating these cancers, and other drugs now in development may prove to be safe as long-term prophylactic therapy as well. deCODE's pioneering work in this field has also demonstrated that ER+ and ER- breast cancer appear to have distinct genetic bases, a phenomenon which may open the way to a better understanding of the nature, treatment and prevention of breast cancer in general. One of the most pressing next steps in this research is to analyze these results in large cohorts of women of non- European descent," said Kari Stefansson, CEO of deCODE.

deCODE made today's discovery through the analysis of genotypic data from a total of nearly 40,000 patients and control subjects from five countries. The deCODE team analyzed both genome-wide data on some 300,000 SNPs, supplemented by data on a much smaller number of SNPs on
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