Low Mammographic Density Research Articles

Very low mammographic breast density predicts poorer outcome in patients with invasive breast cancer.

To examine the prognostic value of mammographic breast density (MBD) and mammographic features and their relationship with established prognostic factors in patients with invasive breast cancer. Mammographic characteristics of 270 patients were analyzed. MBD was classified according to percentile density (<5%, 5-10%, 10-25%, 25-50%, 50-75%, >75%) and further categorized into very low density (VLD; <10%), low density (LOD; <25%) and mixed density (MID; >25%). Mammographic features were compared with established prognostic factors and patient outcomes while correcting for possible confounders. MBD was inversely associated with tumour grade (p = 0.019). Patients with LOD breasts had worse prognoses compared to those with MID breasts (disease-free survival 74.7% vs. 84.8%, p = 0.048; overall survival 75.3% vs. 90.2%, p = 0.003). Patients with VLD breasts showed the strongest significance compared to the remaining patients, even after adjusting for age, body mass index, and menopausal status. No other mammographic feature was prognostically significant. In Cox regression analysis, VLD proved to be an independent, poor prognostic feature (hazard ratio = 3.275; p < 0.001). In patients with newly diagnosed breast cancer, very low MBD proved to be an independent prognostic feature, associated with higher tumour grade and predicted worse survival even after correcting for possible confounders. • Percentile mammographic breast density was associated with patient prognosis. • Very low density proved to be an independent poor prognostic factor. • Only patients with densities <10% displayed this difference in survival. • Mammographic breast density was inversely associated with histological tumour grade.

Risk factors and tumor characteristics of interval cancers by mammographic density.

To compare tumor characteristics and risk factors of interval breast cancers and screen-detected breast cancers, taking mammographic density into account. Women diagnosed with invasive breast cancer from 2001 to 2008 in Stockholm, Sweden, with data on tumor characteristics (n = 4,091), risk factors, and mammographic density (n = 1,957) were included. Logistic regression was used to compare interval breast cancers with screen-detected breast cancers, overall and by highest and lowest quartiles of percent mammographic density. Compared with screen-detected breast cancers, interval breast cancers in nondense breasts (≤ 20% mammographic density) were significantly more likely to exhibit lymph node involvement (odds ratio [OR], 3.55; 95% CI, 1.74 to 7.13) and to be estrogen receptor negative (OR, 4.05; 95% CI, 2.24 to 7.25), human epidermal growth factor receptor 2 positive (OR, 5.17; 95% CI, 1.64 to 17.01), progesterone receptor negative (OR, 2.63; 95% CI, 1.58 to 4.38), and triple negative (OR, 5.33; 95% CI, 1.21 to 22.46). In contrast, interval breast cancers in dense breasts (> 40.9% mammographic density) were less aggressive than interval breast cancers in nondense breasts (overall difference, P = .008) and were phenotypically more similar to screen-detected breast cancers. Risk factors differentially associated with interval breast cancer relative to screen-detected breast cancer after adjusting for age and mammographic density were family history of breast cancer (OR, 1.32; 95% CI, 1.02 to 1.70), current use of hormone replacement therapy (HRT; OR, 1.84; 95% CI, 1.38 to 2.44), and body mass index more than 25 kg/m(2) (OR, 0.49; 95% CI, 0.29 to 0.82). Interval breast cancers in women with low mammographic density have the most aggressive phenotype. The effect of HRT on interval breast cancer risk is not fully explained by mammographic density. Family history is associated with interval breast cancers, possibly indicating disparate genetic background of screen-detected breast cancers and interval breast cancers.

Stress signaling from human mammary epithelial cells contributes to phenotypes of mammographic density.

Telomere malfunction and other types of DNA damage induce an activin A-dependent stress response in mortal nontumorigenic human mammary epithelial cells that subsequently induces desmoplastic-like phenotypes in neighboring fibroblasts. Some characteristics of this fibroblast/stromal response, such as reduced adipocytes and increased extracellular matrix content, are observed not only in tumor tissues but also in disease-free breast tissues at high risk for developing cancer, especially high mammographic density tissues. We found that these phenotypes are induced by repression of the fatty acid translocase CD36, which is seen in desmoplastic and disease-free high mammographic density tissues. In this study, we show that epithelial cells from high mammographic density tissues have more DNA damage signaling, shorter telomeres, increased activin A secretion and an altered DNA damage response compared with epithelial cells from low mammographic density tissues. Strikingly, both telomere malfunction and activin A expression in epithelial cells can repress CD36 expression in adjacent fibroblasts. These results provide new insights into how high mammographic density arises and why it is associated with breast cancer risk, with implications for the definition of novel invention targets (e.g., activin A and CD36) to prevent breast cancer.

How Mammographic Breast Density Affects Radiologists' Visual Search Patterns

To determine the impact of mammographic breast density on the visual search process of radiologists when reading digital mammograms. Institutional review board approval was obtained. A set of 149 craniocaudal digital mammograms were read by seven radiologists, and observer search patterns were recorded. Total time examining each case, time to first hit the lesion, dwell time, and number of hits per area were calculated. The nonparametric Mann-Whitney U test was used for statistical evaluation. In both low- and high-mammographic density cases, significant increases were observed in the time to first hit lesions when they were located outside, compared to overlying fibroglandular dense tissue (P = .001). Significantly longer dwell time (P = .003) and greater number of fixations (P = .0003) were observed when the lesions were situated within--rather than outside--the dense fibroglandular tissue. Increased mammographic breast density changes radiologists' visual search patterns. Dense areas of the parenchyma attracted greater visual attention in both high- and low-mammographic density cases, resulting in faster detection of lesions overlying the fibroglandular dense tissue, along with longer dwell times and greater number of fixations, as compared to lesions located outside the dense fibroglandular regions.

Mammographic Density and Cancer Detection: Does Digital Imaging Challenge our Current Understanding?

To investigate the impact of breast density on the performance of radiologists when mammograms are digitally acquired and displayed. A total of 150 craniocaudal digital mammograms including 75 cases with cancer were examined by 14 radiologists divided into two groups: those who read more (six) and less (eight) than 2000 mammograms per year. Cases were classified as low or high mammographic density. For both types of cases, detection of cancers within and outside the dense fibroglandular tissue was investigated. The performance of radiologist was measured using jack-knife free-response receiver operating characteristic (JAFROC) figure of merit (FOM). Radiologists with over 2000 annual reads had significantly higher JAFROC FOM (P = .03) for high (0.76) mammographic density compared to low (0.70) mammographic density cases. When lesions overlaid the fibroglandular tissue, cases with high mammographic density compared to low mammographic density displayed increased location sensitivity for all radiologists (P = .03) and for those radiologists reading more than 2000 mammograms annually (P = .04), whereas JAFROC FOMs increased for all radiologists (P = .05). No significant changes were observed when the lesion was outside the fibroglandular region. Increased mammographic density improves the performance of experienced radiologists when using digital mammograms. This finding, which does not align with those previously reported for film screen systems, may be because of windowing/leveling opportunities available with digital images.

Dynamic changes in high and low mammographic density human breast tissues maintained in murine tissue engineering chambers during various murine peripartum states and over time

Mammographic density (MD) is a strong heritable risk factor for breast cancer, and may decrease with increasing parity. However, the biomolecular basis for MD-associated breast cancer remains unclear, and systemic hormonal effects on MD-associated risk is poorly understood. This study assessed the effect of murine peripartum states on high and low MD tissue maintained in a xenograft model of human MD. Method High and low MD human breast tissues were precisely sampled under radiographic guidance from prophylactic mastectomy specimens of women. The high and low MD tissues were maintained in separate vascularised biochambers in nulliparous or pregnant SCID mice for 4weeks, or mice undergoing postpartum involution or lactation for three additional weeks. High and low MD biochamber material was harvested for histologic and radiographic comparisons during various murine peripartum states. High and low MD biochamber tissues in nulliparous mice were harvested at different timepoints for histologic and radiographic comparisons. Results High MD biochamber tissues had decreased stromal (p=0.0027), increased adipose (p=0.0003) and a trend to increased glandular tissue areas (p=0.076) after murine postpartum involution. Stromal areas decreased (p=0.042), while glandular (p=0.001) and adipose areas (p=0.009) increased in high MD biochamber tissues during lactation. A difference in radiographic density was observed in high (p=0.0021) or low MD biochamber tissues (p=0.004) between nulliparous, pregnant and involution groups. No differences in tissue composition were observed in high or low MD biochamber tissues maintained for different durations, although radiographic density increased over time. Conclusion High MD biochamber tissues had measurable histologic changes after postpartum involution or lactation. Alterations in radiographic density occurred in biochamber tissues between different peripartum states and over time. These findings demonstrate the dynamic nature of the human MD xenograft model, providing a platform for studying the biomolecular basis of MD-associated cancer risk.

Abstract 1362: Dyslipidemia, excess weight and high mammographic density are associated with high levels of daily estrogen and progesterone. .

Abstract Background: Dyslipidemia, excess weight, and high mammographic density have independently been associated with breast cancer development. However, little is known regarding the combined effect of dyslipidemia, excess weight and mammographic density on cyclic variation in estrogen and progesterone. Material and Methods: 202 premenopausal women (25-35 years) participated in the Norwegian EBBA-I study including clinical examinations, and fasting blood sampling. Computer-assisted percent mammographic density (Madena) was obtained from digitized mammograms taken at day 7-12 of menstrual cycle. Daily saliva samples were collected across an entire menstrual cycle, and concentrations of 17β-estradiol and progesterone were measured at the Reproductive Ecology Laboratory, Harvard University, USA. Uni and multivariable linear and logistic regression models were used to study the combined association of high-density lipoprotein cholesterol (HDL-C), body mass index (BMI) and mammographic density with daily concentrations of 17β-estradiol and progesterone. Results: Among women with mean age of 30.7 years, mean percent mammographic density 29.8 %, mean BMI 24.4 kg/m2, mean total cholesterol 4.45 mmol/l, and mean HDL-C 1.54 mmol/l, we observed overall mean salivary 17β-estradiol 16.2 pmol/l and progesterone 129.3 pmol/l. We used median split and women characterized by lower than median HDL-C (≤ 1.51 mmol/l), higher than median BMI (&amp;gt; 23.6 kg/m2), and higher than median percent mammographic density (&amp;gt; 28.5 %) (unfavorable profile), had higher concentrations of both 17β-estradiol (p = 0.005) and progesterone (p = 0.016) across the entire menstrual cycle, compared with women characterized by higher HDL-C(&amp;gt; 1.51 mmol/l), lower BMI (≤ 23.6 kg/m2) and lower percent mammographic density (≤ 28.5 %) (favorable profile). Comparing the profiles, women with an unfavorable profile had 46 % higher overall mean 17β-estradiol (17β-estradiol; 22.2 versus 15.9 pmol/l) and 48% higher overall mean progesterone (progesterone; 187.5 versus 126.1pmol/l). These factors also showed strong associations with differences in AUC (area under curve) of these sex steroid hormones across the entire menstrual cycle, reflecting cumulative exposure. Women characterized by unfavorable profile had 48 % higher AUC estradiol compared with women having favorable profile (AUCe, 387, 95 % confidence interval (CI) 244 - 531 versus 262, 95% CI 244 - 281). Furthermore, women with unfavorable profile had 47 % higher AUC progesterone than women with favorable profile (AUCp, 1929, 95 % CI 1125 - 2733 versus 1309, 95% CI 1211 -1408). Conclusion: A combination of low HDL-C, excess weight, and high percent mammographic density, was strongly associated with higher daily levels of 17β-estradiol and progesterone, and could in part explain the association of these factors with increased risk of breast cancer development. Citation Format: Vidar G. Flote, Hanne Frydenberg, Giske Ursin, Anita Iversen, Morten W. Fagerland, Peter T. Ellison, Erik A. Wist, Thore Egeland, Anne-Sofie Furberg, Inger Thune. Dyslipidemia, excess weight and high mammographic density are associated with high levels of daily estrogen and progesterone. . [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1362. doi:10.1158/1538-7445.AM2013-1362

Abstract P3-01-01: Insulin, Insulin-like Growth Factor-1 and cycling estrogen predict premenopausal mammographic density.

Abstract Background: Mammographic density, a strong biomarker for breast cancer risk, represents epithelial and stromal proliferation. Insulin and insulin-like growth factor (IGF)-1 are suggested to influence cellular proliferation, while estrogen is a key factor in breast cancer development. However, whether the effects of these hormones among premenopausal women are mediated through mammographic density is less known. Material and Methods: Fasting serum insulin, IGF-1, and IGF binding protein (IGFBP)-3 were assessed among 202 healthy premenopausal women (Norwegian Energy Balance and Breast cancer Aspects study-I (EBBA-I). Daily salivary levels of 17β-estradiol throughout an entire menstrual cycle were measured at the reproductive Ecology Laboratory, Harvard University, USA. Computer-assisted mammographic density (Madena) was obtained from digitized mammograms taken at day 7–12 of the menstrual cycle. Uni- and multivariable regression models were used to study the associations between hormones and premenopausal percent mammographic density. Results: Among women with a mean age of 30,7 years, a mean premenopausal percent mammographic density of 29.8 % was observed. Throughout the menstrual cycle when comparing women with a high percent mammographic density (≥28.5%) to women with a low percent mammographic density (&amp;lt;28.5%), we observed insulin, IGF-1 and IGFBP-3 independently and in combination with cycling 17β-estradiol to predict premenopausal percent mammographic density. We observed among women with either serum insulin ≥89 pmol/, IGF-1 ≥24 nmol/l, IGFBP-3 ≥ 100 nmol/l, having a high (≥28.5%) versus a low (&amp;lt;28.5%) percent mammographic density was associated with an increase in overall average 17β-estradiol of 4.0 %, 10.9 % and 14.9%, respectively. Moreover, we observed a higher adjusted Odds Ratio (OR) for having a high percent mammographic density for each standard deviation (SD) increase in overall average 17β -estradiol, insulin, IGF-1 and IGFBP-3: 17β-estradiol, 1.55 (1.06–2.27); insulin, 1.62 (0.76–3.48), IGF-1, 1.90 (1.10–3.27); IGFBP-3, 1.88 (1.05–3.37) (adjusted for age, body mass index-BMI kg/m2)). Conclusion: Our study supports that insulin, IGF-1 and IGFBP-3 independently, and in combination with cycling estrogen, predicts premenopausal mammographic density. These hormones may be important biomarkers in breast cancer control and clinical practice. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P3-01-01.

Mammographic density and inter-observer variability of pathologic evaluation of core biopsies among women with mammographic abnormalities.

BackgroundAs high percentage of mammographic densities complicates the assessment of imaging findings, mammographic density may influence the histopathological evaluation of core-biopsies of the breast. We measured the influence of mammographic density on the inter-observer variability of histopathological findings of breast biopsies.MethodsHistological slides of 695 women who underwent core biopsies of the breast at University of Halle between 2006 and 2008 were evaluated in a blinded fashion by two pathologists using the five levels of the B-categorization scheme (B1-B5). To quantify mammographic density, we used a computer-based threshold method (Madena). We calculated observed and chance-corrected agreements (weighted kappa) and 95% confidence intervals (95% CI) according to four categories of mammographic density (<10%, 10<25%, 25<50%, ≥50%).ResultsThe weighted kappa decreased monotonically from 89.6% (95% CI: 85.8%, 93.3%) among women with less than 10% of mammographic density to 80.4% (95% CI: 69.9%, 90.9%) for women with more than 50% of mammographic density, respectively. Results of a kappa regression analysis showed that agreement of pathologists on clinically relevant categories (B1-B2 versus B3-B5) decreased with mammographic density.ConclusionsMammographic density is a relevant modifier of the agreement between pathologists who assess breast biopsies using the B-categorization scheme. The influence of mammographic density on the inter-observer variability can be explained to some extent by varying prevalences of histological entities across B categories that have typically different inter-observer agreement. Women with high mammographic density are at higher risk of inter-observer variability compared to women with low mammographic density and should possibly undergo a second pathology review.

Abstract 71: Relationship of mammographic density and gene expression analysis of normal breast tissue surrounding breast cancer.

Abstract Gene expression signatures of benign breast tissues surrounding breast cancers demonstrate marked heterogeneity, comparable to the diversity found in tumor tissues. Relationships between epidemiologic factors and gene expression in the breast cancer microenvironment have not been fully explored. In particular, the correspondence between high mammographic density (MD), a strong breast cancer risk factor reflecting an increased percentage of fibroglandular tissue, and gene expression is ill-defined. To evaluate how MD and breast tissue composition relate to gene expression of extratumoral microenvironment, we used data on 121 breast cancer patients aged 20-74 years from the population-based Polish Women's Breast Cancer Study. Subjects were classified into two groups based on the gene expression of normal breast tissue by the previously reported, biologically-defined extratumoral gene expression signature: Active extratumoral subtype is associated with high expression of genes related to fibrosis and wound response, while Inactive subtype has high expression of cellular adhesion genes. MD was assessed using pre-treatment digitized mammograms of unaffected breasts. Breast tissue composition was evaluated based on digital image analysis of tissue sections. Information on related breast cancer risk factors was collected using medical records and interviews. Roughly half of the patients had Active extratumoral subtype (n=59) and half had Inactive extratumoral subtype (n=62). Inactive subtype was significantly associated with higher percentage density (PD) and dense area (DA) in univariate analysis (PD: p=0.001; DA: p=0.049) and after adjusting for age and body mass index (PD: p=0.004; DA: p=0.049). Inactive/high MD group (defined as PD ≥ 25%) had significantly lower percentage of adipose tissue (mean percentage: 47% in Inactive vs. 78% in Active; 56% in high MD vs. 69% in low MD) and higher percentage of stroma (mean percentage: 42% in Inactive vs. 13% in Active; 34% in high MD vs. 21% in low MD), but no significant difference was detected in the percentage of epithelial tissue. Further analysis of published gene expression signatures suggested high MD and Inactive subtype were strongly associated with positive expression of age-related (younger) and estrogen response signatures, but decreased expression of obesity and transforming growth factor beta signatures. These results indicate that MD reflects broad transcriptional changes. Moreover, based on strong associations between the genomic phenotypes and MD, Active/Inactive subtype may be associated with breast cancer risk. Further research to better understand the molecular characteristics of normal breast genomic subtypes could identify pathways that are targetable in preventing mammographic-density associated risk. Citation Format: Xuezheng Sun, Gretchen L. Gierach, Rupninder Sandhu, Tyisha Williams, Norman Boyd, Nicole B. Johnson, Jonine D. Figueroa, Mark Sherman, Melissa A. Troester. Relationship of mammographic density and gene expression analysis of normal breast tissue surrounding breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 71.

Correlation Between Mammographic Breast Density and Expression of 17ß Hydroxysteroid Desydrogenase Type 1

INTRODUCTION: High Mammographic density is a breast cancer risk factor and it is present over one third of cases of breast cancer. The 17s-hydroxysteroid dehydrogenase (17s-HSD) enzyme has possible local effects on breast tissue by stimulating growth of breast epithelial cells and is associated with mammographic density in women in pre and perimenopause. After a review in the literature, we see the importance of the enzyme 17sHSD1 in the etiology of breast cancer by both local and peripheral steroidogenesis, which may increase breast density. OBJECTIVE: For this reason we studied the correlation between mammographic breast density and immunohistochemical expression of 17s hydroxysteroid desydrogenase type 1 (17sHSD1). Casuistic and METHODS: 48 cases were evaluated with mammographic image classified by BI-RADS® system in four categories. The pattern of density 1 and 2 (measure breast tissue until 50%) was classified like low density and the pattern 3 and 4 (measure breast tissue upper 50%) like high density. Expression of the enzymes were evaluated by tissue microarray (TMA) screened with anti-17sHSD1 monoclonal rabbit antibodies (LS-C49955, Lifespan) diluted 1/200. Specimens were assigned scores on a scale from zero to three according to intensity of staining and number of stained cells. Scores zero and one were considered negative results and scores two and three indicated positive enzyme expression. RESULTS: In relation to breast density, in absolute numbers and percentages, we found the following results in category 1, 17 patients (35.42%), category 2, 17 patients (35.42%), category 3, 6 patients (12 50%) and category 4, 8 patients (16.67%). The 17sHSD1 expression was positive in 18 (37.5%). Statistical analysis showed no significant correlation between the expression of 17sHSD1 (p = 0.00048) with breast density (p = 0.666). No significant correlation between the expression of 17sHSD1 with breast density was found to be unchanged even when the analysis of the proposed subgroups (BMI greater than or less than 25, aged 50 years or less and high and low mammographic density). CONCLUSION: The results of our studies showed that there was no positive association between mammographic breast density and the expression of the enzyme 17sHSD1.

High and low mammographic density human breast tissues maintain histological differential in murine tissue engineering chambers

Mammographic density (MD) is the area of breast tissue that appears radiologically white on mammography. Although high MD is a strong risk factor for breast cancer, independent of BRCA1/2 mutation status, the molecular basis of high MD and its associated breast cancer risk is poorly understood. MD studies will benefit from an animal model, where hormonal, gene and drug perturbations on MD can be measured in a preclinical context. High and low MD tissues were selectively sampled by stereotactic biopsy from operative specimens of high-risk women undergoing prophylactic mastectomy. The high and low MD tissues were transferred into separate vascularised biochambers in the groins of SCID mice. Chamber material was harvested after 6 weeks for histological analyses and immunohistochemistry for cytokeratins, vimentin and a human-specific mitochondrial antigen. Within-individual analysis was performed in replicate mice, eliminating confounding by age, body mass index and process-related factors, and comparisons were made to the parental human tissue. Maintenance of differential MD post-propagation was assessed radiographically. Immunohistochemical staining confirmed the preservation of human glandular and stromal components in the murine biochambers, with maintenance of radiographic MD differential. Propagated high MD regions had higher stromal (p = 0.0002) and lower adipose (p = 0.0006) composition, reflecting the findings in the original human breast tissue, although glands appeared small and non-complex in both high and low MD groups. No significant differences were observed in glandular area (p = 0.4) or count (p = 0.4) between high and low MD biochamber tissues. Human mammary glandular and stromal tissues were viably maintained in murine biochambers, with preservation of differential radiographic density and histological features. Our study provides a murine model for future studies into the biomolecular basis of MD as a risk factor for breast cancer.

Mammographic density and molecular subtypes of breast cancer

Background:Gene expression profiling has led to a subclassification of breast cancers independent of established clinical parameters, such as the Sorlie–Perou subtypes. Mammographic density (MD) is one of the strongest risk factors for breast cancer, but it is unknown if MD is associated with molecular subtypes of this carcinoma.Methods:We investigated whether MD was associated with breast cancer subtypes in 110 women with breast cancer, operated in Stockholm, Sweden, during 1994 to 1996. Subtypes were defined using expression data from HGU133A+B chips. The MD of the unaffected breast was measured using the Cumulus software. We used multinomial logistic models to investigate the relationship between MD and Sorlie–Perou subtypes.Results:Although the distribution of molecular subtypes differed in women with high vs low MD, this was statistically non-significant (P=0.249), and further analyses revealed no association between the MD and Sorlie–Perou subtypes as a whole, nor with individual subtypes.Conclusion:These findings suggest that although MD is one of the strongest risk factors for breast cancer, it does not seem to be differentially associated with breast cancer molecular subtypes. However, larger studies with more comprehensive covariate information are needed to confirm these results.

P2-10-01: Extracellular Matrix Stiffness and Mammographic Density in the Human Breast.

Abstract Introduction: Mammographic density (MD) is associated with greater risk to malignancy. MD is also correlated to high collagen content in the extra cellular matrix (ECM). Data from our group and others have highlighted the importance of mechanical cues from the ECM in breast tissue homeostasis and tumor progression to invasion [1; 2; reviewed in 3]. Whether the stiffness of the ECM could also initiate breast cancer and if so how remains unknown. Because elevated collagen levels increases ECM stiffness, we hypothesize that MD increases breast cancer risk because the ECM is stiffer. Materials and Methods: We studied breast tissues obtained through prophylactic mastectomy from women with low (BIRADS 1) versus high MD (BIRADS 4). From each surgically excised breast, samples of 0.5cm x 0.5cm x 1cm dimension were removed from the retroareolar region and from 4 peripheral quadrants. Sample sections were subjected to biophysical, morphological and biochemical analysis. Biophysical analysis included the application of Atomic Force Microscopy to obtain an extensive force map of distinct anatomical regions of the ECM associated with the intra-lobular and inter-lobular ECM. Topological analysis of ECM architecture was performed using two photons and SIM-POL imaging coupled with picrosirius staining, polarized light imaging and image quantification. Biochemical and morphological analysis consisted of immunohistochemistry for markers that detect mechano-signaling in the epithelium and stromal fibroblasts, and H&amp;E to visualize cellular and ECM organization. Results and Discussion: We found that the intra-lobular ECM associated with the terminal end-buds in the breast contained anisotropic relaxed collagen fibrils and was very compliant. By contrast, the inter-lobular ECM of the breast contained oriented collagen fibrils and was relatively stiffer. Notably, the ECM associated with the retroareolar region, which is typically detected as very dense using mammographic imaging, contained oriented collagen fibrils, and was significantly stiffer than the ECM associated with the peripheral quadrants. Intriguingly, preliminary data suggested that the ECM associated with the terminal end-buds in the upper outer quadrant showed a trend towards greater stiffness in women with high MD (BIRADS 4) than low MD (BIRADS 1). Although, it is tempting to speculate that ECM stiffness could enhance risk to malignancy, further sample analysis is now necessary. Conclusions: • In the human breast there is anatomical heterogeneity with respect to ECM organization and mechanical properties. High MD appears to reflect elevated ECM stiffness. The intra-lobular ECM is considerably stiffer in the upper outer quadrant than in the other peripheral regions of the breast. Atomic Force Microscopy is a tractable method to monitor ECM stiffness and mechanical heterogeneity in the human breast. Acknowledgements: supported by W81XWH-05-1-0330 and R01 CA138818-01A1 to VMW, 1U01 ES019458-01 to VMW and ZW, and P50 CA 58207 to JG, VW, SH and LC, U54CA143836-01 to JL and VW.

Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling

We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24-38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.

Abstract 416: Mammographic density and ECM stiffness

Abstract Breast tissue homoeostasis depends on the complex regulation of biochemical and biophysical factors present in the extra cellular matrix (ECM). Tumor tissue in mouse and human breast is characteristically stiffer than normal tissue, and changes to the ECM contribute to this phenotype. Breast density is associated with elevated collagen content, while increased deposition of collagen is known to augment ECM stiffness. Mammographic density imaging provides a qualitative description of breast density, and high mammographic density is associated with increased risk to malignancy. However, little is known about the correlation between ECM stiffness and the density in the breast image. Previously, we have used atomic force microscopy (AFM) to characterize the changes in breast tissue stiffness with cancer progression (Levental et al., Cell 2009). We hypothesized that mammographically dense breasts would be stiffer. To further understand the biophysical regulation of breast stiffness, we investigated whether mammographic density is a predictor of ECM stiffness. Towards this goal, we studied tissue samples from prophylactic mastectomies, from women with low versus high mammographic density. Tissue samples were obtained from the peripheral quadrants as well as from the retroareolar (nipple) regions, which are known to be of higher mammographic density. We performed AFM force mapping to characterize the ECM stiffness in the different regions. Our preliminary data indicate a heterogeneous pattern of stiffness within the breast. Moreover, we found that the peripheral terminal ductal lobuli have the most compliant ECM. By contrast, the stroma stiffness in the retroareolar region was 2-fold higher than in the peripheral quadrants. This work demonstrates the technical feasibility of measuring the mechanical properties as well as defined histological characteristics within the same patient specimen. The data suggest that ECM stiffness may be greater in breast tissue of high mammographic density. The correlation between mammographic density and ECM stiffness may reveal the role of collagen status in the risk to malignancy. (supported by W81XWH-05-1-0330 and R01 CA138818-01A1 to VMW, 1U01 ES019458-01 to VMW and ZW, and P50 CA 58207 to JG, VW, SH and LC.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 416. doi:10.1158/1538-7445.AM2011-416

Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue

Mammographic density (MD) adjusted for age and body mass index (BMI) is a strong heritable breast cancer risk factor; however, its biological basis remains elusive. Previous studies assessed MD-associated histology using random sampling approaches, despite evidence that high and low MD areas exist within a breast and are negatively correlated with respect to one another. We have used an image-guided approach to sample high and low MD tissues from within individual breasts to examine the relationship between histology and degree of MD. Image-guided sampling was performed using two different methodologies on mastectomy tissues (n = 12): (1) sampling of high and low MD regions within a slice guided by bright (high MD) and dark (low MD) areas in a slice X-ray film; (2) sampling of high and low MD regions within a whole breast using a stereotactically guided vacuum-assisted core biopsy technique. Pairwise analysis accounting for potential confounders (i.e. age, BMI, menopausal status, etc.) provides appropriate power for analysis despite the small sample size. High MD tissues had higher stromal (P = 0.002) and lower fat (P = 0.002) compositions, but no evidence of difference in glandular areas (P = 0.084) compared to low MD tissues from the same breast. High MD regions had higher relative gland counts (P = 0.023), and a preponderance of Type I lobules in high MD compared to low MD regions was observed in 58% of subjects (n = 7), but did not achieve significance. These findings clarify the histologic nature of high MD tissue and support hypotheses regarding the biophysical impact of dense connective tissue on mammary malignancy. They also provide important terms of reference for ongoing analyses of the underlying genetics of MD.

Expression levels of uridine 5'-diphospho-glucuronosyltransferase genes in breast tissue from healthy women are associated with mammographic density

IntroductionMammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known.MethodsGene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and a linear regression model was used to assess the independent contribution from different variables to MD.ResultsSAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified.ConclusionsThree UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest amongst young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer.

Abstract B43: Gene expression in breast tissue associated with mammographic density in healthy women

Abstract Introduction: Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, high MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of MD are virtually unknown. Methods: Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) recruited through mammographic centres and 64 newly diagnosed breast cancer patients. MD percentage was determined using a previously validated, computerized method on scanned mammograms. Unsupervised hierarchical clustering was used to investigate the presence of subgroups of samples within the normal biopsies. Significance analysis of microarrays (SAM) was performed to identify genes associated with MD. Results: Hierarchical clustering of normal biopsies on the basis of the gene expression data split the individuals into two main groups. These were not significantly associated with MD or BMI. SAM identified 24 genes differentially expressed between high and low MD in the healthy women. Several single nucleotide polymorphisms (SNPs) associated with the expression of these 24 genes were identified. Conclusions: Breast biopsies from healthy women show substantial variation in their gene-expression profiles. Twenty-four genes associated with MD and SNPs associated with their expression were identified. Several of these genes have previously been found to be linked to breast biology and oestrogen metabolism. Validation and further analysis of these genes is ongoing. Citation Information: Clin Cancer Res 2010;16(7 Suppl):B43

599 Does radiopharmaceutical molecule size change number of sentinel lymph node in breast cancer patients?

To investigate the impact of breast density on the performance of radiologists when mammograms are digitally acquired and displayed.A total of 150 craniocaudal digital mammograms including 75 cases with cancer were examined by 14 radiologists divided into two groups: those who read more (six) and less (eight) than 2000 mammograms per year. Cases were classified as low or high mammographic density. For both types of cases, detection of cancers within and outside the dense fibroglandular tissue was investigated. The performance of radiologist was measured using jack-knife free-response receiver operating characteristic (JAFROC) figure of merit (FOM).Radiologists with over 2000 annual reads had significantly higher JAFROC FOM (P = .03) for high (0.76) mammographic density compared to low (0.70) mammographic density cases. When lesions overlaid the fibroglandular tissue, cases with high mammographic density compared to low mammographic density displayed increased location sensitivity for all radiologists (P = .03) and for those radiologists reading more than 2000 mammograms annually (P = .04), whereas JAFROC FOMs increased for all radiologists (P = .05). No significant changes were observed when the lesion was outside the fibroglandular region.Increased mammographic density improves the performance of experienced radiologists when using digital mammograms. This finding, which does not align with those previously reported for film screen systems, may be because of windowing/leveling opportunities available with digital images.