Some cells that showed no outward irregularities were found to have DNA damage. In addition to traditional microscopic examination for outward abnormalities, the cells were subjected to DNA analysis to look for internal damage that could foreshadow the genetic Euhus said cells also could be gathered for analysis using methods such as ductal lavage, where cells are collected from milk ducts. In the cell-examination study, Euhus and his colleagues obtained cell samples from the breast through fine-needle aspiration, using a small-gauge needle to extract clusters of cells. Molecular analysis of breast cells may solve this problem. While the Gail method is accurate at assigning risk, it can't predict which women it rates as high risk actually will develop breast cancer. "Our findings suggest that it is possible to develop an individualized approach to risk assessment using breast cells obtained by various methods," Euhus said. Euhus found that the detection of small DNA deletions in breast cells from these women correlated with Gail-model risk and with precancerous changes in the cells diagnosed by routine microscopy. The Gail model is a computer model known to be an accurate predictor of women's risk of developing breast cancer. The women participating in the cell-examination study were not cancer patients however, their risk of developing breast cancer had been assigned as low, moderate or high using the Gail model. He said that while the studies were separate, both suggest new approaches for identifying women at increased risk for breast cancer. David Euhus, associate professor of surgical oncology, is the lead author on both papers. The findings are published in separate papers in today's edition of the Journal of the National Cancer Institute. DALLAS – J– Researchers at UT Southwestern Medical Center at Dallas have shown that examining breast cells' molecular makeup can provide a better way to predict breast-cancer risk and that computer-based risk-assessment tools can help identify women who would benefit from genetic testing.
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