Mammographic density and hormone receptor expression in breast cancer: the Multiethnic Cohort Study

Deep learning identification of stiffness markers in breast cancer

While essential to our understanding of solid tumor progression, the study of cell and tissue mechanics has yet to find traction in the clinic. Determining tissue stiffness, a mechanical property known to promote a malignant phenotype in vitro and in vivo, is not part of the standard algorithm for the diagnosis and treatment of breast cancer. Instead, clinicians routinely use mammograms to identify malignant lesions and radiographically dense breast tissue is associated with an increased risk of developing cancer. Whether breast density is related to tumor tissue stiffness, and what cellular and non-cellular components of the tumor contribute the most to its stiffness are not well understood. Through training of a deep learning network and mechanical measurements of fresh patient tissue, we create a bridge in understanding between clinical and mechanical markers. The automatic identification of cellular and extracellular features from hematoxylin and eosin (H&E)-stained slides reveals that global and local breast tissue stiffness best correlate with the percentage of straight collagen. Importantly, the percentage of dense breast tissue does not directly correlate with tissue stiffness or straight collagen content.

Prediagnostic circulating metabolites in female breast cancer cases with low and high mammographic breast density

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case-case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case-case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. ¹H NMR metabolomic spectra were available for 87 complete case-case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the "phenylalanine, tyrosine and tryptophan pathway" emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case-case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.

The impact of selected risk factors among breast cancer molecular subtypes: a case-only study

PURPOSE

Breast cancer (BC) risk factors have been differentially associated with BC subtypes, but quantification is still undefined. Therefore, we compared selected risk factors with BC subtypes, using a case-case approach.

METHODS

We retrieved 1321 invasive female BCs from the Piedmont Cancer Registry. Through record linkage of clinical records, we obtained data on estrogen (Er) and progesterone (Pr) receptors, Ki67 and HER2+ status, BC family history, breast imaging reporting and data system (BI-RADS) density, reproductive risk factors and education. We defined BC subtypes as follows : luminal A (Er+ and/or Pr+ , HER2- , low Ki67), luminal BH- (Er+ and/or Pr + , HER2- , Ki67 high), luminal BH+ (Er+ and/or Pr + , HER2+), HER2+ (Er - , Pr - , HER2+), ) and triple negative (Er - , Pr - , HER2-). Using a multinomial regression model, we estimated the odds ratios (ORs) for selected BC risk factors considering luminal A as reference.

RESULTS

For triple negative, the OR for BC family history was 1.83 (95% confidence interval (CI) 1.13-2.97). Compared to BI-RADS 1, for triple negative, the OR for BI-RADS 2 was 0.56 (95% CI 0.27-1.14) and for BI-RADS 3-4 was 0.37 (95% CI 0.15-0.88); for luminal BH +, the OR for BI-RADS 2 was 2.36 (95% CI 1.08-5.11). For triple negative, the OR for high education was 1.78 (95% CI 1.03-3.07), and for late menarche, the OR was 1.69 (95% CI 1.02-2.81). For luminal BH + , the OR for parous women was 0.56 (95% CI 0.34-0.92).

CONCLUSIONS

This study supported BC etiologic heterogeneity across subtypes, particularly for triple negative.

Is mammographic density a marker of breast cancer phenotypes?

PURPOSE

To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location.

METHODS

MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features.

RESULTS

Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics.

CONCLUSION

MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

Mammographic density parameters and breast cancer tumor characteristics among postmenopausal women

Purpose

Mammographic density is an important breast cancer risk factor, although it is not clear whether the association differs across breast cancer tumor subtypes. We examined the association between indicators of mammographic density and breast cancer risk by tumor subtype among postmenopausal women by investigating heterogeneity across tumor characteristics.

Methods

Mammographic density measures were determined for 477 breast cancer cases and 588 controls, all postmenopausal, in Vancouver, British Columbia, using digitized screening mammograms and Cumulus software. Mammographic dense (DA), non-dense (NDA), and percent dense (PDA) areas were treated as continuous covariates and categorized into quartiles according to the distribution in controls. For cases only, tests for heterogeneity between tumor subtypes were assessed by multinomial logistic regression. Associations between mammographic density and breast cancer risk were modeled for each subtype separately through unconditional logistic regression.

Results

Heterogeneity was apparent for the association of PDA with tumor size (p-heterogeneity=0.04). Risk did not differ across the other assessed tumor characteristics (p-heterogeneity values >0.05).

Conclusion

These findings do not provide strong evidence that mammographic density parameters differentially affect specific breast cancer tumor characteristics.

A review of the influence of mammographic density on breast cancer clinical and pathological phenotype

PURPOSE

It is well established that high mammographic density (MD), when adjusted for age and body mass index, is one of the strongest known risk factors for breast cancer (BC), and also associates with higher incidence of interval cancers in screening due to the masking of early mammographic abnormalities. Increasing research is being undertaken to determine the underlying histological and biochemical determinants of MD and their consequences for BC pathogenesis, anticipating that improved mechanistic insights may lead to novel preventative or treatment interventions. At the same time, technological advances in digital and contrast mammography are such that the validity of well-established relationships needs to be re-examined in this context.

METHODS

With attention to old versus new technologies, we conducted a literature review to summarise the relationships between clinicopathologic features of BC and the density of the surrounding breast tissue on mammography, including the associations with BC biological features inclusive of subtype, and implications for the clinical disease course encompassing relapse, progression, treatment response and survival.

RESULTS AND CONCLUSIONS

There is reasonable evidence to support positive relationships between high MD (HMD) and tumour size, lymph node positivity and local relapse in the absence of radiotherapy, but not between HMD and LVI, regional relapse or distant metastasis. Conflicting data exist for associations of HMD with tumour location, grade, intrinsic subtype, receptor status, second primary incidence and survival, which need further confirmatory studies. We did not identify any relationships that did not hold up when data involving newer imaging techniques were employed in analysis.

Association between mammographic density and tumor marker-defined breast cancer subtypes: a case-control study

High mammographic density (MD) is the most important risk factor for breast cancer. This study aimed to clarify the relationship between MD and breast cancer subtypes defined by tumor markers. We enrolled 642 women with breast cancer (69% premenopausal) and 1241 controls matched for age and menopausal status. Absolute mammographic dense area (ADA), percent mammographic dense area (PDA), and nondense area were assessed using a computer-assisted thresholding technique. We classified breast cancer cases into four subtypes using information on tumor marker expression such as estrogen receptor (ER), progesterone receptor (PR), and Cerb2 receptor (HER2); luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-overexpressing (ER-, PR-, and HER2+), and triple-negative (ER-, PR-, and HER2-). Analysis was carried out using a conditional logistic regression model with adjustment for covariates. ADA and PDA were associated positively with the risk of breast cancer overall. Both ADA and PDA tended to have a positive association with breast cancer with any ER, any PR, or HER2-, but not for HER2+. The risk of luminal A breast cancer increased significantly 1.11 times (95% confidence interval: 1.01-1.23) for ADA and 1.12 times (95% confidence interval: 1.01-1.24) for PDA, estimated per 1 SD of the age and BMI-adjusted MD. However, the risk of breast cancer with luminal B, HER2-overexpressing, and triple-negative subtypes did not differ (P>0.10). Differential associations between MD measures and breast cancer by tumor marker status or tumor marker-defined subtypes were not detected. These findings suggested that the association between MD and breast cancer subtype may be because of other causal pathways.

Breast density and breast cancer-specific survival by detection mode

Background

Breast density is known to affect breast cancer risk and screening sensitivity, but it may also be associated with breast cancer survival. The interpretation of results from previous studies on breast density and survival is complicated by the association between detection mode and survival. Here, we studied the effect of breast density on breast cancer-specific survival for different detection modes (screen-detected, interval ≤ 24 or > 24 months, non-participant).

Methods

Data from the Nijmegen (Dutch) breast cancer screening programme were used. Women diagnosed with invasive breast cancer between 1975 and 2011 were included. Breast density was assessed visually, based on a dichotomized Wolfe scale: ‘fatty breasts’ (≤25%) and ‘dense breasts’ (> 25%). Cox proportional hazard regression was used to obtain hazard ratios (HR).

Results

We identified 2742 eligible women, with a breast pattern available for 2233 women. A diagnosis of interval cancer (HR 2.06, 95% CI 1.62–2.61) led to a significantly increased risk of breast cancer death compared with screen-detected cancer. No significant cause-specific survival difference between women with dense and fatty breasts was observed (HR 0.94, 95% CI 0.77–1.15). The hazard was only higher for women with dense breasts among interval cancers ≤24 m (HR 1.07, 95% CI 0.74–1.56). The hazard appeared to be lower for women with dense breasts than for women with fatty breasts among screen-detected (HR 0.77, 95% CI 0.53–1.11) and interval cancers > 24 m (HR 0.80, 95% CI 0.53–1.20). None of the effects were statistically significant.

Conclusions

Detection mode is strongly associated with breast cancer death. No clear association is apparent between breast density and breast cancer death, regardless of detection mode.

The Effect of Neoadjuvant Chemotherapy on Hormone Receptor Status, HER2/neu and Prolactin in Breast Cancer

Aims and Background

Histological and immunohistochemical findings may vary in cases of breast cancer. Possible changes in tumor markers between biopsies performed before and after neoadjuvant chemotherapy are controversial and pose a challenge when a clinical decision is needed. The objectives of the present study were: (i) to compare the immunohistochemical expression of estrogen, progesterone and prolactin receptors and HER-2/neu in breast cancer before and after neoadjuvant chemotherapy; and (ii) to correlate the expression of these tumor markers with partial tumor response to neoadjuvant chemotherapy.

Methods and Study Design

Immunohistochemical staining for breast tumor markers was performed in 90 cases of breast cancer. Statistical analysis was carried out using Fisher's exact test, McNemar's test, Spearman's correlation and the Kappa index with linear weighting (κ).

Results

Agreement between markers before and after neoadjuvant chemotherapy was fair to moderate (κ = 0.37–0.51). The immunohistochemical expression of HER-2/neu and prolactin receptors showed a significant, albeit weak correlation before and after neoadjuvant chemotherapy (HER-2/neu, rho = 0.34; P = 0.0009; κ = 0.35 [95% CI, 0.19–0.51]). Prolactin status changed in 28/90 cases (P = 0.001; McNemar's test), whereas no changes were found in estrogen or progesterone receptors. No association was found between tumor marker expression and tumor response.

Conclusions

It seems prudent to reevaluate immunohistochemical markers such as HER-2/neu after neoadjuvant chemotherapy, since the findings will guide the strategy for implementation of adjuvant systemic treatment. No correlation was found between the tumor markers analyzed in the present study and partial tumor response to neoadjuvant chemotherapy.

Breast density: why all the fuss?

The term "breast density" or mammographic density (MD) denotes those components of breast parenchyma visualised at mammography that are denser than adipose tissue. MD is composed of a mixture of epithelial and stromal components, notably collagen, in variable proportions. MD is most commonly assessed in clinical practice with the time-honoured method of visual estimation of area-based percent density (PMD) on a mammogram, with categorisation into quartiles. The computerised semi-automated thresholding method, Cumulus, also yielding area-based percent density, is widely used for research purposes; however, the advent of fully automated volumetric methods developed as a consequence of the widespread use of digital mammography (DM) and yielding both absolute and percent dense volumes, has resulted in an explosion of interest in MD recently. Broadly, the importance of MD is twofold: firstly, the presence of marked MD significantly reduces mammographic sensitivity for breast cancer, even with state-of-the-art DM. Recognition of this led to the formation of a powerful lobby group ('Are You Dense') in the US, as a consequence of which 32 states have legislated for mandatory disclosure of MD to women undergoing mammography. Secondly, it is now widely accepted that MD is in itself a risk factor for breast cancer, with a four-to sixfold increased relative risk in women with PMD in the highest quintile compared to those with PMD in the lowest quintile. Consequently, major research efforts are underway to assess whether use of MD could provide a major step forward towards risk-adapted, personalised breast cancer prevention, imaging, and treatment.

Tumor characteristics and family history in relation to mammographic density and breast cancer: The French E3N cohort

BACKGROUND

Mammographic density is a known heritable risk factor for breast cancer, but reports how tumor characteristics and family history may modify this association are inconsistent.

METHODS

Dense and total breast areas were assessed using Cumulus™ from pre-diagnostic mammograms for 820 invasive breast cancer cases and 820 matched controls nested within the French E3N cohort study. To allow comparisons across models, percent mammographic density (PMD) was standardized to the distribution of the controls. Odds ratios (OR) and 95% confidence intervals (CI) of breast cancer risk for mammographic density were estimated by conditional logistic regression while adjusting for age and body mass index. Heterogeneity according to tumor characteristic and family history was assessed using stratified analyses.

RESULTS

Overall, the OR per 1 SD for PMD was 1.50 (95% CI, 1.33-1.69). No evidence for significant heterogeneity by tumor size, lymph node status, grade, and hormone receptor status (estrogen, progesterone, and HER2) was detected. However, the association of PMD was stronger for women reporting a family history of breast cancer (OR_1SD=2.25; 95% CI, 1.67-3.04) than in women reporting none (OR_1SD=1.41; 95% CI, 1.24-1.60; p_{heterogeneity}=0.002). Similarly, effect modification by FHBC was observed using categories of PMD (p_{heterogeneity}=0.02) with respective ORs of 15.16 (95% CI, 4.23-54.28) vs. 3.14 (95% CI, 1.89-5.22) for ≥50% vs. <10% PMD.

CONCLUSIONS

The stronger association between mammographic density and breast cancer risk with a family history supports the hypothesis of shared genetic factors responsible for familial aggregation of breast cancer and the heritable component of mammographic density.

Background Parenchymal Enhancement and Fibroglandular Tissue Proportion on Breast MRI: Correlation with Hormone Receptor Expression and Molecular Subtypes of Breast Cancer

OBJECTIVE

To assess the relationship between background parenchymal enhancement (BPE) and fibroglandular tissue (FGT) proportion on breast magnetic resonance imaging (MRI) and hormone receptor expression and molecular subtypes in invasive breast cancer.

MATERIALS AND METHODS

This retrospective study enrolled 75 breast cancer patients who underwent breast MRI before treatment. T1-weighted images were reviewed to determine the FGT proportion, and contrast-enhanced fat-suppressed T1-weighted images were reviewed to determine BPE. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2-neu (HER2) status, and molecular subtypes of the tumors were compared with the BPE and FGT proportions.

RESULTS

Women with high BPE tended to have increased rate of ER and PR positive tumors (p=0.018 and p=0.013). FGT proportion was associated with ER positivity (p=0.009), but no significant differences between FGT proportion and PR positivity were found (p=0.256). There was no significant difference between HER2 status and any of the imaging features (p=0.453 and p=0.922). For premenopausal women, both FGT proportion and BPE were associated with molecular subtypes (p=0.025 and p=0.042). FGT proportion was also associated with BPE (p<0.001).

CONCLUSION

In women with invasive breast cancer, both high FGT containing breasts and high BPE breasts tended to have ER positive tumors.

Risk Factors That Increase Risk of Estrogen Receptor-Positive and -Negative Breast Cancer

Background

Risk factors may differentially influence development of estrogen receptor (ER)-positive vs -negative breast cancer. We examined associations with strong, prevalent risk factors by ER subtype.

Methods

Of 1 279 443 women age 35 to 74 years participating in the Breast Cancer Surveillance Consortium, 14 969 developed ER-positive and 3617 developed ER-negative invasive breast cancer. We calculated hazard ratios (HRs) using Cox regression and compared ER subtype hazard ratios at representative ages or by menopausal status using Wald tests. All statistical tests were two-sided.

Results

For women age 40 years, compared with no prior biopsy, ER-positive vs ER-negative HRs were 1.53 (95% CI = 1.30 to 1.81) vs 1.26 (95% CI = 0.90 to 1.76) for nonproliferative disease, 1.63 (95% CI = 1.23 to 2.17) vs 1.41 (95% CI = 0.78 to 2.57) for proliferative disease without atypia, and 4.47 (95% CI = 2.88 to 6.96) vs 0.20 (95% CI = 0.02 to 2.51) for proliferative disease with atypia. Benign disease proliferation risk was stronger for ER-positive than ER-negative cancer for women age 35 years (Wald P = .04), age 40 years (Wald P = .04), and age 50 years (Wald P = .06). Among pre/perimenopausal women, body mass index (BMI) had a stronger association with ER-negative than ER-positive cancer (obese II/III vs. normal weight: HR = 1.52, 95% CI = 1.19 to 1.94; vs 1.21, 95% CI = 1.08 to 1.36). Increasing BMI similarly increased ER-positive and ER-negative cancer risk among postmenopausal hormone users (Wald P = .15) and nonusers (Wald P = .08). Associations with ER subtype varied by race/ethnicity across all ages (P < .001) and by family history of breast cancer and breast density for specific ages.

Conclusions

Strength of risk factor associations differed by ER subtype. Separate risk models for ER subtypes may improve identification of women for targeted prevention strategies.

Estrogen and progesterone receptors in breast cancer

Breast cancer is the most common cancer in women worldwide. The majority of breast cancers show overexpression of estrogen receptors (ERs) and progesterone receptors (PRs). The development of drugs to target these hormone receptors, such as tamoxifen, has brought about significant improvement in survival for women with hormone receptor-positive breast cancers. Since information about ER and PR is vital for patient management, quality assurance is important to ensure accurate testing. In recent guidelines, the recommended definition of ER and PR positivity is 1% or more of cells that stain positive. Semiquantitative assessment of ER and PR is important for prognosis and, hence, management. Even with the development of genomic tests, hormone receptor status remains the most significant predictive and prognostic biomarker.

Mammographic density and breast cancer in women from high risk families

Introduction

Mammographic density (MD) is one of the strongest determinants of sporadic breast cancer (BC). In this study, we compared MD in BRCA1/2 mutation carriers and non-carriers from BRCA1/2 mutation-positive families and investigated the association between MD and BC among BRCA1/2 mutation carriers per type of mutation and tumor subtype.

Methods

The study was carried out in 1039 female members of BRCA1 and BRCA2 mutation-positive families followed at 16 Spanish Genetic Counseling Units. Participants’ density was scored retrospectively from available mammograms by a single blinded radiologist using a 5-category scale (<10 %, 10-25 %, 25-50 %, 50-75 %, >75 %). In BC cases, we selected mammograms taken prior to diagnosis or from the contralateral breast, whereas, in non-cases, the last screening mammogram was evaluated. MD distribution in carriers and non-carriers was compared using ordinal logistic models, and the association between MD and BC in BRCA1/2 mutation carriers was studied using logistic regression. Huber-White robust estimators of variance were used to take into account correlations between family members. A similar multinomial model was used to explore this association by BC subtype.

Results

We identified and scored mammograms from 341 BRCA1, 350 BRCA2 mutation carriers and 229 non-carriers. Compared to non-carriers, MD was significantly lower among BRCA2 mutation carriers (odds ratio (OR) =0.71; P-value=0.04), but not among BRCA1 carriers (OR=0.84; P-value=0.33). MD was associated with subsequent development BC (OR per category of MD=1.45; 95 % confidence interval=1.18-1.78, P-value<0.001), with no significant differences between BRCA1 and BRCA2 mutation carriers (P-value=0.48). Finally, no statistically significant differences were observed in the association of MD with specific BC subtypes.

Conclusions

Our study, the largest to date on this issue, confirms that MD is an independent risk factor for all BC subtypes in either BRCA1 and BRCA2 mutation carriers, and should be considered a phenotype risk marker in this context.

Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics

BACKGROUND

Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes.

METHODS

Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression.

RESULTS

DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; P(trend) <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; P(trend) <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (P(trend) < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER(+) versus ER(-) tumors (P(het) = 0.02), while NDA was more strongly associated with decreased risk of ER(-) versus ER(+) tumors (P(het) = 0.03).

CONCLUSIONS

DA and NDA have differential associations with ER(+) versus ER(-) tumors that vary by age.

IMPACT

DA and NDA are important to consider when developing age- and subtype-specific risk models.

Association between mammographic density and basal-like and luminal A breast cancer subtypes

Introduction

Mammographic density is a strong risk factor for breast cancer overall, but few studies have examined the association between mammographic density and specific subtypes of breast cancer, especially aggressive basal-like breast cancers. Because basal-like breast cancers are less frequently screen-detected, it is important to understand how mammographic density relates to risk of basal-like breast cancer.

Methods

We estimated associations between mammographic density and breast cancer risk according to breast cancer subtype. Cases and controls were participants in the Carolina Breast Cancer Study (CBCS) who also had mammograms recorded in the Carolina Mammography Registry (CMR). A total of 491 cases had mammograms within five years prior to and one year after diagnosis and 528 controls had screening or diagnostic mammograms close to the dates of selection into CBCS. Mammographic density was reported to the CMR using Breast Imaging Reporting and Data System categories. The expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 1 and 2 (HER1 and HER2), and cytokeratin 5/6 (CK5/6) were assessed by immunohistochemistry and dichotomized as positive or negative, with ER+ and/or PR+, and HER2- tumors classified as luminal A and ER-, PR-, HER2-, HER1+ and/or CK5/6+ tumors classified as basal-like breast cancer. Triple negative tumors were defined as negative for ER, PR and HER2. Of the 491 cases 175 were missing information on subtypes; the remaining cases included 181 luminal A, 17 luminal B, 48 basal-like, 29 ER-/PR-/HER2+, and 41 unclassified subtypes. Odds ratios comparing each subtype to all controls and case-case odds ratios comparing mammographic density distributions in basal-like to luminal A breast cancers were estimated using logistic regression.

Results

Mammographic density was associated with increased risk of both luminal A and basal-like breast cancers, although estimates were imprecise. The magnitude of the odds ratio associated with mammographic density was not substantially different between basal-like and luminal A cancers in case–control analyses and case-case analyses (case-case OR = 1.08 (95% confidence interval: 0.30, 3.84)).

Conclusions

These results suggest that risk estimates associated with mammographic density are not distinct for separate breast cancer subtypes (basal-like/triple negative vs. luminal A breast cancers). Studies with a larger number of basal-like breast cancers are needed to confirm our findings.

High volumetric breast density predicts risk for breast cancer in postmenopausal, but not premenopausal, Korean Women

PURPOSE

We investigated the association between mammographic breast density and breast cancer risk in Korean women according to menopausal status and breast cancer subtypes.

METHODS

We enrolled 677 patients diagnosed with breast cancer and 1,307 healthy controls who participated in screening mammography at the National Cancer Center. Breast density was estimated using volumetric breast composition measurement.

RESULTS

Of the total population, 1,156 (58.3 %) women were postmenopausal. The risk of breast cancer increased progressively with the increment of volumetric density grade (VDG) in postmenopausal women (p < 0.001). High breast density (VDG 4) was significantly associated with breast cancer compared with low breast density (VDG 1/2) regardless of body mass index. However, the association with parity and history of hormone replacement therapy (HRT) was only found in those with ≥2 children and those not receiving HRT. Breast density was positively associated with breast cancer risk regardless of histologic grade, tumor size, lymph node involvement, Ki67 index, and hormone receptor status. The association was more prominent in human epidermal growth factor receptor 2 (HER2)-positive tumors (VDG 1/2 vs. VDG 4 for HER2 normal, odds ratio [OR] 2.21, 95 % confidence interval [CI] 1.28-3.83, p < 0.001; for HER2 positive, OR 8.63, 95 % CI 3.26-22.83, p = 0.001; P heterogeneity = 0.030). However, no significant association was found between breast density and breast cancer risk in premenopausal women except for those with large-sized tumors (>2 cm) and a Ki67 index >15 %.

CONCLUSION

High volumetric breast density is significantly associated with the risk of breast cancer in postmenopausal women; however, these relationships were not found in premenopausal women.

Mammographic density-a review on the current understanding of its association with breast cancer

There has been considerable recent interest in the genetic, biological and epidemiological basis of mammographic density (MD), and the search for causative links between MD and breast cancer (BC) risk. This report will critically review the current literature on MD and summarize the current evidence for its association with BC. Keywords 'mammographic dens*', 'dense mammary tissue' or 'percent dens*' were used to search the existing literature in English on PubMed and Medline. All reports were critically analyzed. The data were assigned to one of the following aspects of MD: general association with BC, its relationship with the breast hormonal milieu, the cellular basis of MD, the generic variations of MD, and its significance in the clinical setting. MD adjusted for age, and BMI is associated with increased risk of BC diagnosis, advanced tumour stage at diagnosis and increased risk of both local recurrence and second primary cancers. The MD measures that predict BC risk have high heritability, and to date several genetic markers associated with BC risk have been found to also be associated with these MD risk predictors. Change in MD could be a predictor of the extent of chemoprevention with tamoxifen. Although the biological and genetic pathways that determine and perhaps modulate MD remain largely unresolved, significant inroads are being made into the understanding of MD, which may lead to benefits in clinical screening, assessment and treatment strategies. This review provides a timely update on the current understanding of MD's association with BC risk.

Tumor phenotype and breast density in distinct categories of interval cancer: results of population-based mammography screening in Spain

INTRODUCTION

Interval cancers are tumors arising after a negative screening episode and before the next screening invitation. They can be classified into true interval cancers, false-negatives, minimal-sign cancers, and occult tumors based on mammographic findings in screening and diagnostic mammograms. This study aimed to describe tumor-related characteristics and the association of breast density and tumor phenotype within four interval cancer categories.

METHODS

We included 2,245 invasive tumors (1,297 screening-detected and 948 interval cancers) diagnosed from 2000 to 2009 among 645,764 women aged 45 to 69 who underwent biennial screening in Spain. Interval cancers were classified by a semi-informed retrospective review into true interval cancers (n = 455), false-negatives (n = 224), minimal-sign (n = 166), and occult tumors (n = 103). Breast density was evaluated using Boyd's scale and was conflated into: <25%; 25 to 50%; 50 to 75%; >75%. Tumor-related information was obtained from cancer registries and clinical records. Tumor phenotype was defined as follows: luminal A: ER+/HER2- or PR+/HER2-; luminal B: ER+/HER2+ or PR+/HER2+; HER2: ER-/PR-/HER2+; triple-negative: ER-/PR-/HER2-. The association of tumor phenotype and breast density was assessed using a multinomial logistic regression model. Adjusted odds ratios (OR) and 95% confidence intervals (95% CI) were calculated. All statistical tests were two-sided.

RESULTS

Forty-eight percent of interval cancers were true interval cancers and 23.6% false-negatives. True interval cancers were associated with HER2 and triple-negative phenotypes (OR = 1.91 (95% CI:1.22-2.96), OR = 2.07 (95% CI:1.42-3.01), respectively) and extremely dense breasts (>75%) (OR = 1.67 (95% CI:1.08-2.56)). However, among true interval cancers a higher proportion of triple-negative tumors was observed in predominantly fatty breasts (<25%) than in denser breasts (28.7%, 21.4%, 11.3% and 14.3%, respectively; <0.001). False-negatives and occult tumors had similar phenotypic characteristics to screening-detected cancers, extreme breast density being strongly associated with occult tumors (OR = 6.23 (95% CI:2.65-14.66)). Minimal-sign cancers were biologically close to true interval cancers but showed no association with breast density.

CONCLUSIONS

Our findings revealed that both the distribution of tumor phenotype and breast density play specific and independent roles in each category of interval cancer. Further research is needed to understand the biological basis of the overrepresentation of triple-negative phenotype among predominantly fatty breasts in true interval cancers.

Mammographic density and risk of breast cancer by age and tumor characteristics

Introduction

Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models.

Methods

Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (<55, 55–64, and ≥65 years).

Results

MD was positively associated with risk of invasive tumors across all ages, with a two-fold increased risk for high (>51%) versus average density (11-25%). Women ages <55 years with high MD had stronger increased risk of ductal carcinoma in situ (DCIS) compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.02). Among all ages, MD had a stronger association with large (>2.1 cm) versus small tumors and positive versus negative lymph node status (P’s < 0.01). For women ages <55 years, there was a stronger association of MD with ER-negative breast cancer than ER-positive tumors compared to women ages 55–64 and ≥65 years (P_{age-interaction} = 0.04). MD was positively associated with both HER2-negative and HER2-positive tumors within each age group.

Conclusion

MD is strongly associated with all breast cancer subtypes, but particularly tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages <55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women.

Mammographic Density and Prediction of Nodal Status in Breast Cancer Patients

Aim: Nodal status remains one of the most important prognostic factors in breast cancer. The cellular and molecular reasons for the spread of tumor cells to the lymph nodes are not well understood and there are only few predictors in addition to tumor size and multifocality that give an insight into additional mechanisms of lymphatic spread. Aim of our study was therefore to investigate whether breast characteristics such as mammographic density (MD) add to the predictive value of the presence of lymph node metastases in patients with primary breast cancer. Methods: In this retrospective study we analyzed primary, metastasis-free breast cancer patients from one breast center for whom data on MD and staging information were available. A total of 1831 patients were included into this study. MD was assessed as percentage MD (PMD) using a semiautomated method and two readers for every patient. Multiple logistic regression analyses with nodal status as outcome were used to investigate the predictive value of PMD in addition to age, tumor size, Ki-67, estrogen receptor (ER), progesterone receptor (PR), grading, histology, and multi-focality. Results: Multifocality, tumor size, Ki-67 and grading were relevant predictors for nodal status. Adding PMD to a prediction model which included these factors did not significantly improve the prediction of nodal status (p = 0.24, likelihood ratio test). Conclusion: Nodal status could be predicted quite well with the factors multifocality, tumor size, Ki-67 and grading. PMD does not seem to play a role in the lymphatic spread of tumor cells. It could be concluded that the amount of extracellular matrix and stromal cell content of the breast which is reflected by MD does not influence the probability of malignant breast cells spreading from the primary tumor to the lymph nodes.

Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study

INTRODUCTION

It is not clear whether high mammographic density (MD) is equally associated with all subtypes of breast cancer (BC). We investigated the association between MD and subsequent BC, considering invasiveness, means of detection, pathologic subtype, and the time elapsed since mammographic exploration and BC diagnosis.

METHODS

BC cases occurring in the population of women who attended screening from 1997 through 2004 in Navarre, a Spanish region with a fully consolidated screening program, were identified via record linkage with the Navarre Cancer Registry (n = 1,172). Information was extracted from the records of their first attendance at screening in that period. For each case, we randomly selected four controls, matched by screening round, year of birth, and place of residence. Cases were classified according to invasiveness (ductal carcinoma in situ (DCIS) versus invasive tumors), pathologic subtype (considering hormonal receptors and HER2), and type of diagnosis (screen-detected versus interval cases). MD was evaluated by a single, experienced radiologist by using a semiquantitative scale. Data on BC risk factors were obtained by the screening program in the corresponding round. The association between MD and tumor subtype was assessed by using conditional logistic regression.

RESULTS

MD was clearly associated with subsequent BC. The odds ratio (OR) for the highest MD category (MD >75%) compared with the reference category (MD <10%) was similar for DCIS (OR = 3.47; 95% CI = 1.46 to 8.27) and invasive tumors (OR = 2.95; 95% CI = 2.01 to 4.35). The excess risk was particularly high for interval cases (OR = 7.72; 95% CI = 4.02 to 14.81) in comparison with screened detected tumors (OR = 2.17; 95% CI = 1.40 to 3.36). Sensitivity analyses excluding interval cases diagnosed in the first year after MD assessment or immediately after an early recall to screening yielded similar results. No differences were seen regarding pathologic subtypes. The excess risk associated with MD persisted for at least 7 to 8 years after mammographic exploration.

CONCLUSIONS

Our results confirm that MD is an important risk factor for all types of breast cancer. High breast density strongly increases the risk of developing an interval tumor, and this excess risk is not completely explained by a possible masking effect.

Is mammographic density differentially associated with breast cancer according to receptor status? A meta-analysis

Mammographic density (MD) is a strong marker of breast cancer risk, but it is debated whether the association holds, and is of a similar magnitude, for different subtypes of breast cancer defined by receptor status or gene expression profiles. A literature search conducted in June 2012 was used to identify all studies that had investigated the association of MD with subtype-specific breast cancer, independent of age. 7 cohort/case-control and 12 case-only studies were included, comprising a total of >24,000 breast cancer cases. Random effects meta-analysis models were used to combine relative risks (RR) of MD with subtype-specific breast cancer for case-control studies, and in case-only studies to combine relative risk ratios (RRR) of receptor positive versus negative breast tumors. In case-control/cohort studies, relative to women in the lowest density category, women in the highest density category had 3.1-fold (95 % confidence interval [CI] 2.2, 4.2) and 3.2-fold (1.7, 5.9) increased risk of estrogen receptor positive (ER+) and ER- breast cancer, respectively. In case-only analyses, RRRs of breast tumors being ER+ versus ER- were 1.13 (95 % CI 0.89, 1.42) for medium versus minimal MD. MD remained associated with screen-detected ER+ tumors, despite the expectation of this association to be attenuated due to masking bias and overdiagnoses of ER+ tumors. In eight contributing studies, the association of MD did not differ by HER2 status. This combined evidence strengthens the importance of MD as a strong marker of overall and of subtype-specific risk, and confirms its value in overall breast cancer risk assessment and monitoring for both research and clinical purposes.

Breast density, body mass index, and risk of tumor marker-defined subtypes of breast cancer

PURPOSE

Breast density and body mass index (BMI) are correlated attributes and are both potentially modifiable risk factors for breast cancer. However, relationships between these factors and risk of molecularly-defined subtypes of breast cancer have not been established.

METHODS

We used breast density and BMI data collected by the Breast Cancer Surveillance Consortium from 1,054,466 women ages 40 to 84 years receiving mammography, including 13,797 women subsequently diagnosed with breast cancer. Cases were classified into three groups on the basis of expression of the estrogen receptor (ER), progesterone receptor (PR), and HER2:1) ER-positive (ER+, n = 10,026), 2) HER2-expressing (ER-negative/PR-negative/HER2-positive, n = 308), or triple-negative (ER-negative/PR-negative/HER2-negative, n = 705). Using Cox regression, we evaluated subtype-specific associations with breast density and BMI.

RESULTS

Breast density was similarly positively associated with risk of all subtypes, especially among women ages 40 to 64 years. BMI was positively associated with risks of ER+ and triple-negative breast cancer in women ages 50 to 84 who were not users of hormone therapy.

CONCLUSIONS

Breast density is positively associated with breast cancer risk, regardless of disease subtype. Associations with BMI appear to vary more by breast cancer subtype. Additional studies are needed to confirm and further characterize risk factors for HER2-expressing and triple-negative breast cancer.

Mammographic density and breast cancer risk: current understanding and future prospects

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.