High mammographic density in women of Ashkenazi Jewish descent

Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era

Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.

Breast Arterial Calcification Rates in a Diverse, Urban Group of Screening Mammography Patients

PURPOSE

Breast arterial calcifications (BAC), detected by digital mammography are a potential marker of coronary artery disease (CAD). Past BAC research has been limited by having primarily racially and ethnically homogeneous samples, samples at higher risk for CAD, and neglecting to explore the influence of women's health factors. The purpose of this study was to evaluate the prevalence of, and factors associated with, BAC in an ethnically and racially diverse group.

METHODS

We conducted a retrospective chart review on 17,237 screening mammography patients. Mammography results and patient responses to a demographic and medical history questionnaire were abstracted. Logistic regression was used.

RESULTS

BAC prevalence was 12.3%. Age was a significant risk factor, with the odds of BAC approximately doubling every decade. Age-adjusted analyses showed: 1) higher BAC prevalence among Hispanic, Black, and Ashkenazi women; 2) lower BAC prevalence among nulliparous and pre-menopausal women, those with dense breasts and breast implants, and those currently using HRT; and 3) no association between BAC prevalence and BMI or age at menarche.

CONCLUSIONS

BAC prevalence differs according to age, ethnicity, race, women's health, and breast-specific factors. Communication of BAC information in clinical settings could potentially prompt women to engage in preventive care.

Changes in mammographic density over time in breast cancer cases and women at high risk for breast cancer

High mammographic breast density is one of the strongest intermediate markers of breast cancer risk, and decreases in density over time have been associated with decreases in breast cancer risk. Using repeated measures of mammographic density in a cohort of high-risk women, the Women at Risk (WAR) cohort at Columbia University Medical Center (N = 2670), we examined whether changes in prediagnostic mammographic density differed among 85 prospectively-ascertained breast cancer cases and 85 age-matched controls, using a nested case–control design. Median age at first mammogram was 51 years (range, 29–77 years), with a median of 4 years between first and second prediagnostic mammogram (range, 1–15 years). Using linear regression with change in percent density as the outcome, we found that in women who did not go on to be diagnosed with breast cancer, change in percent density decreased as time between first and second mammogram increased (β = −1.62% per year, p = 0.004). However, in women who did go on to be diagnosed with breast cancer, there was no overall change in percent density associated with time between first and second mammogram (β = 0.29% per year, p = 0.61); the change over time was statistically significantly different between cases versus controls (p <0.009). If replicated in larger cohorts, these results suggest that within-individual changes in mammographic density as measured by percent density may be a useful biomarker of breast cancer risk.