Association of mammographic density measures and breast cancer "intrinsic" molecular subtypes

Association and Prediction Utilizing Craniocaudal and Mediolateral Oblique View Digital Mammography and Long-Term Breast Cancer Risk

Mammographic percentage of volumetric density is an important risk factor for breast cancer. Epidemiology studies historically used film images often limited to craniocaudal (CC) views to estimate area-based breast density. More recent studies using digital mammography images typically use the averaged density between craniocaudal (CC) and mediolateral oblique (MLO) view mammography for 5- and 10-year risk prediction. The performance in using either and both mammogram views has not been well-investigated. We use 3,804 full-field digital mammograms from the Joanne Knight Breast Health Cohort (294 incident cases and 657 controls), to quantity the association between volumetric percentage of density extracted from either and both mammography views and to assess the 5 and 10-year breast cancer risk prediction performance. Our results show that the association between percent volumetric density from CC, MLO, and the average between the two, retain essentially the same association with breast cancer risk. The 5- and 10-year risk prediction also shows similar prediction accuracy. Thus, one view is sufficient to assess association and predict future risk of breast cancer over a 5 or 10-year interval.

PREVENTION RELEVANCE

Expanding use of digital mammography and repeated screening provides opportunities for risk assessment. To use these images for risk estimates and guide risk management in real time requires efficient processing. Evaluating the contribution of different views to prediction performance can guide future applications for risk management in routine care.

Longitudinal Analysis of Change in Mammographic Density in Each Breast and Its Association With Breast Cancer Risk

Importance

Although breast density is an established risk factor for breast cancer, longitudinal changes in breast density have not been extensively studied to determine whether this factor is associated with breast cancer risk.

Objective

To prospectively evaluate the association between change in mammographic density in each breast over time and risk of subsequent breast cancer.

Design, Setting, and Participants

This nested case-control cohort study was sampled from the Joanne Knight Breast Health Cohort of 10 481 women free from cancer at entry and observed from November 3, 2008, to October 31, 2020, with routine screening mammograms every 1 to 2 years, providing a measure of breast density. Breast cancer screening was provided for a diverse population of women in the St Louis region. A total of 289 case patients with pathology-confirmed breast cancer were identified, and approximately 2 control participants were sampled for each case according to age at entry and year of enrollment, yielding 658 controls with a total number of 8710 craniocaudal-view mammograms for analysis.

Exposures

Exposures included screening mammograms with volumetric percentage of density, change in volumetric breast density over time, and breast biopsy pathology-confirmed cancer. Breast cancer risk factors were collected via questionnaire at enrollment.

Main Outcomes and Measures

Longitudinal changes over time in each woman's volumetric breast density by case and control status.

Results

The mean (SD) age of the 947 participants was 56.67 (8.71) years at entry; 141 were Black (14.9%), 763 were White (80.6%), 20 were of other race or ethnicity (2.1%), and 23 did not report this information (2.4%). The mean (SD) interval was 2.0 (1.5) years from last mammogram to date of subsequent breast cancer diagnosis (10th percentile, 1.0 year; 90th percentile, 3.9 years). Breast density decreased over time in both cases and controls. However, there was a significantly slower decrease in rate of decline in density in the breast that developed breast cancer compared with the decline in controls (estimate = 0.027; 95% CI, 0.001-0.053; P = .04).

Conclusions and Relevance

This study found that the rate of change in breast density was associated with the risk of subsequent breast cancer. Incorporation of longitudinal changes into existing models could optimize risk stratification and guide more personalized risk management.

Mammographic Breast Density: Current Assessment Methods, Clinical Implications, and Future Directions

Mammographic breast density is widely accepted as an independent risk factor for the development of breast cancer. In addition, because dense breast tissue may mask breast malignancies, breast density is inversely related to the sensitivity of screening mammography. Given the risks associated with breast density, as well as ongoing efforts to stratify individual risk and personalize breast cancer screening and prevention, numerous studies have sought to better understand the factors that impact breast density, and to develop and implement reproducible, quantitative methods to assess mammographic density. Breast density assessments have been incorporated into risk assessment models to improve risk stratification. Recently, novel techniques for analyzing mammographic parenchymal complexity, or texture, have been explored as potential means of refining mammographic tissue-based risk assessment beyond breast density.

Cellular reprogramming, chemoresistance, and dietary interventions in breast cancer

Breast cancer (BC) diagnosis has been associated with significant risk factors, including family history, late menopause, obesity, poor eating habits, and alcoholism. Despite the advances in the last decades regarding cancer treatment, some obstacles still hinder the effectiveness of therapy. For example, chemotherapy resistance is common in locally advanced or metastatic cancer, reducing treatment options and contributing to mortality. In this review, we provide an overview of BC metabolic changes, including the impact of restrictive diets associated with chemoresistance, the therapeutic potential of the diet on tumor progression, pathways related to metabolic health in oncology, and perspectives on the future in the area of oncological nutrition.

Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications

Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.

The breast tissue microbiome, stroma, immune cells and breast cancer

BACKGROUND

Stromal and immune cell composition alterations in benign breast tissue associate with future cancer risk. Pilot data suggest the innate microbiome of normal breast tissue differs between women with and without breast cancer. Microbiome alterations might explain tissue microenvironment variations associated with disease status.

METHODS

Prospectively-collected sterile normal breast tissues from women with benign (n=16) or malignant (n=17) disease underwent 16SrRNA sequencing with Illumina MiSeq and Hybrid-denovo pipeline processing. Breast tissue was scored for fibrosis and fat percentages and immune cell infiltrates (lobulitis) classified as absent/mild/moderate/severe. Alpha and beta diversity were calculated on rarefied OTU data and associations analyzed with multiple linear regression and PERMANOVA.

RESULTS

Breast tissue stromal fat% was lower and fibrosis% higher in benign disease versus cancer (median 30% versus 60%, p=0.01, 70% versus 30%, p=0.002, respectively). The microbiome varied with stromal composition. Alpha diversity (Chao1) correlated with fat% (r=0.38, p=0.02) and fibrosis% (r=-0.32, p=0.05) and associated with different microbial populations as indicated by beta diversity metrics (weighted UniFrac, p=0.08, fat%, p=0.07, fibrosis%). Permutation testing with FDR control revealed taxa differences for fat% in Firmicutes, Bacilli, Bacillales, Staphylococcaceae and genus Staphylococcus, and fibrosis% in Firmicutes, Spirochaetes, Bacilli, Bacillales, Spirochaetales, Proteobacteria RF32, Sphingomonadales, Staphylococcaceae, and genera Clostridium, Staphylococcus, Spirochaetes, Actinobacteria Adlercreutzia. Moderate/severe lobulitis was more common in cancer (73%) than benign disease (13%), p=0.003, but no significant microbial associations were seen.

CONCLUSION

These data suggest a link between breast tissue stromal alterations and its microbiome, further supporting a connection between the breast tissue microenvironment and breast cancer.

Risk factors for breast cancer subtypes among Black women undergoing screening mammography

PURPOSE

Black women are more likely than non-Hispanic White women to be diagnosed with triple negative breast cancer (TNBC), an aggressive subtype with limited treatment options. The study objective was to evaluate the associations of known breast cancer risk factors, including breast density, with TNBC among Black women.

METHODS

This study included Black women who underwent screening mammography between the ages of 40-84 years at a University of Pennsylvania Health System between 2010 and 2015. Cox proportional hazard models using multiple imputation with chained equations were used to estimate hazard ratios and 95% confidence intervals for risk factors for ER/PR+/HER2- and TNBC.

RESULTS

Among 25,013 Black women, there were 330 incident breast cancers (1.3%) during a mean follow-up of 5.8 years; 218 (66.1%) ER/PR+ HER- and 61 (18.1%) TNBC. Having dense breasts (heterogeneously dense or extremely dense) vs. non-dense breasts (almost entirely fatty or scattered areas of fibroglandular density) increased risk of ER/PR+/HER2- breast cancer almost 80% (HR 1.79, 95% CI 1.32-2.43) and TNBC more than twofold (HR 2.53, 1.45-4.44). Older age was associated with an increased risk for ER/PR+/HER2- (HR 1.04, 1.03-1.06) and TNBC (HR 1.03, 1.00-1.05). Having a BMI of > 30 kg/m² was associated with an increased risk (HR 2.77, 1.05-7.30) for TNBC and an increased risk of ERPR+/HER2- breast cancer in postmenopausal but not pre-menopausal women (p-interaction = 0.016).

CONCLUSION

Our results suggest that breast density and obesity are strong risk factors for TNBC among Black women. Understanding breast cancer subtype specific risk factors among Black women can help improve risk assessment.

Relationship of established risk factors with breast cancer subtypes

Background

Breast cancer is a heterogeneous disease, divided into subtypes based on the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Subtypes have different biology and prognosis, with accumulating evidence of different risk factors. The purpose of this study was to compare breast cancer risk factors across tumor subtypes in a large, diverse mammography population.

Methods

Women aged 40–84 without a history of breast cancer with a screening mammogram at three United States health systems from 2006 to 2015 were included. Risk factor questionnaires were completed at mammogram visit, supplemented by electronic health records. Invasive tumor subtype was defined by immunohistochemistry as ER/PR+HER2−, ER/PR+HER2+, ER, and PR−HER2+, or triple‐negative breast cancer (TNBC). Cox proportional hazards models were run for each subtype. Associations of race, reproductive history, prior breast problems, family history, breast density, and body mass index (BMI) were assessed. The association of tumor subtypes with screen detection and interval cancer was assessed using logistic regression among invasive cases.

Results

The study population included 198,278 women with a median of 6.5 years of follow‐up (IQR 4.2–9.0 years). There were 4002 invasive cancers, including 3077 (77%) ER/PR+HER2−, 300 (8%) TNBC, 342 (9%) ER/PR+HER2+, and 126 (3%) ER/PR−HER2+ subtype. In multivariate models, Black women had 2.7 times higher risk of TNBC than white women (HR = 2.67, 95% CI 1.99–3.58). Breast density was associated with increased risk of all subtypes. BMI was more strongly associated with ER/PR+HER2− and HER2+ subtypes among postmenopausal women than premenopausal women. Breast density was more strongly associated with ER/PR+HER2− and TNBC among premenopausal than postmenopausal women. TNBC was more likely to be interval cancer than other subtypes.

Conclusions

These results have implications for risk assessment and understanding of the etiology of breast cancer subtypes. More research is needed to determine what factors explain the higher risk of TNBC for Black women.