Hartmann, L

Abstract Abstract #5008 Background: Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features, such as the terminal duct lobular unit (TDLU), may help to stratify women into different risk levels as breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. Regression, however, does not occur in all women.
 Materials and Methods: We have quantified the extent of lobule regression on a benign breast biopsy in 85 breast cancer cases and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini/lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women.
 Results: There is a step-wise increase in breast cancer risk with increasing numbers of acini/lobule (p=0.0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association.
 
 Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (p=0.03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c-statistic was 0.60 (95% CI; 0.50-0.70); the acinar count c-statistic was 0.65 (95% CI; 0.54-0.75). Combining acinar count and lobular area, the c-statistic was 0.68 (95% GI; 0.58-0.78). Adding the Gail model to these did not improve the c-statistic.
 
 Discussion: Novel, tissue-based features that reflect the status of a woman's normal breast lobules are strongly associated with breast cancer risk. These features appear to provide more accurate risk assessment than the currently used Gail model. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 5008.

Abstract Abstract #4037 Background: Mammographic breast density is a strong and consistent risk factor for breast cancer. Women with dense tissue in over 60 to 75% of the breast are at 4 to 6 times greater risk than women with little or no density. However, the biology of breast density is not well understood and studies at the tissue level are limited. We present the first report of a tissue-based study of breast density, sampling mammographically dense and non-dense areas of the breast of healthy women with the goal of examining histologic correlates.
 Materials and Methods: Healthy women volunteers aged 40 to 85 years, with no breast symptoms, normal screening mammogram within 6 months, and no personal history of breast cancer were considered eligible. Women with breast-related symptoms, those on endocrine therapy, or with bleeding tendencies were excluded from participation. Sixty consecutive eligible women were enrolled in the study- results are based on the first 34 participants. Eligible women underwent an ultrasound-guided, core-needle breast biopsy of mammographically dense and non-dense areas of the breast, performed by a single experienced radiologist. Quantitative assessment of breast tissue from dense and non-dense areas was performed for epithelium, stroma, and fat. In addition, we assessed the difference in the extent of lobular involution (complete, partial and none) between dense and non-dense areas. We used means and SD to describe distributions in each tissue type. Signed rank test was used to assess within woman differences between dense and non-dense tissue.
 Results: The mean age of the participants was 50.1 years (range 40 to 79 years). The histological findings are outlined below.
 
 Dense tissue is comprised of increased stroma and epithelium and decreased fat, consistent with prior reports on breast density. The finding of 'no involution' was greater in dense tissue compared to non-dense tissue (24% versus 8.8%); non-dense tissue had greater proportion of complete involution compared to dense tissue (82.5% versus 35.2%).
 Discussion: This report is the first to quantify histology in tissue sampled from dense and non-dense regions of the healthy breast. We find a dramatic difference in tissue composition between dense and non-dense tissue in the breast. Future studies using this tissue to assess molecular markers will further help to characterize pathways through which density may increase breast cancer risk. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4037.