BMC Cancer 2009, 9:182 http://www.biomedcentral.com/1471-2407/9/182 Table 3: Marker expression and mammographic density stratified by total breast size Marker ERα ERβ PR HER2/neu Ki-67 PCNA % density† Dense area# Number % density Dense area Number % density Dense area Number % density Dense area Number % density Dense area Number % density Dense area Number Small total breast area Large total breast area Category* Category 1 41.3 29.5 63 41.3 28.9 50 39.0 28.8 45 41.7 30.3 55 38.2 25.4 30 41.0 29.4 43 2 38.0 29.1 16 39.5 29.7 29 43.3 29.8 36 39.8 28.6 24 42.6 31.8 49 39.9 28.8 38 P-value 0.55 0.92 0.71 0.82 0.36 0.78 0.71 0.65 0.35 0.07 0.81 0.86 1 30.7 34.6 59 29.9 34.1 60 27.1 28.3 32 30.4 35.2 49 29.7 35.8 35 29.9 33.7 52 2 33.7 39.7 19 36.3 41.2 18 33.3 40.0 45 33.5 37.6 28 30.9 34.5 41 33.9 40.5 25 P-value 0.61 0.53 0.24 0.34 0.19 0.05 0.51 0.71 0.81 0.85 0.43 0.32 * Categories for ERα, ERβ, HER2/neu and PCNA; category 1 <10% staining, category 2 ≥ 10% staining. Categories for PR and Ki-67; category 1 = no staining, category 2 = any staining † Mean percent breast density # Mean dense area in cm2 Mean values and p-values calculated using general linear models adjusted for age at mammogram, BMI, ethnicity, HT use at mammogram, menopausal status, parity, age at first live birth, age at menarche and family history of breast cancer. (ERα = estrogen receptor alpha; ERβ = estrogen receptor beta; PR = progesterone receptor; HER2/neu = Human Epidermal growth factor receptor2; PCNA = Proliferating Cell Nuclear Antigen; BMI = body mass index) the higher PR expression in women with large breasts as compared to women with small breasts may reflect responsiveness to estrogen [29]. Despite the non-signifi- cant results, these observations may indicate that higher ER expression in combination with high tissue levels of estrogens influence breast density. This epidemiologic investigation took advantage of the TMA approach that allows assessment of marker expres- sion in a large number of pathologic samples under simi- lar staining conditions [34,42]. Another benefit of TMAs was that multiple markers could be analyzed using sec- tions of the TMA block without exhausting the material. However, a disadvantage of the method is the loss of sam- ples during immunostaining due to lack of adhesion to glass slides and cross-sectional variation in the amount of epithelial tissue. The use of cores with a larger diameter may alleviate that problem. Alternatively, immunohisto- chemistry could be performed on full sections, if they are available. Another issue with TMAs is that consecutive sec- tions may reveal different types of tissue for the same core due to heterogeneity with tissue depth. As shown before, benign tissue samples were more affected than malignant cores [42,43]. Since a maximum of 4 benign core sections per woman was placed, information on a substantial number of women was obtained. Despite identifying benign specimens for only 159 out of 279 subjects due to the difficulties with benign tissue in the tumor blocks, lit- tle evidence for selection bias was detected (Table 1). Obviously benign biopsies would be the preferred source of material for this type of research because benign tissue adjacent to tumor tissue may be different from benign tis- sue in the other breast or in breast tissue of women with- out cancer. Unfortunately, that type of tissue is not easy to obtain. The amount of material available from stereotactic biopsies is often too small for TMA preparation and women with benign biopsies cannot be identified through tumor registries. Although breast reduction sur- gery would yield large amounts of tissue, women under- going that procedure represent a selected subgroup with Page 6 of 8 (page number not for citation purposes)