Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk

The Untapped Opportunities of Addressing Lifecourse Growth in Mammographic Breast Density and Breast Cancer Prevention in Non-Hispanic Black Women

This commentary discusses the importance of adiposity and lifecourse growth with mammographic breast density (MBD) in non-Hispanic Black (NHB) women. Although high MBD is a well-established risk factor for breast cancer, the determinants of MBD in NHB women remain understudied. Although adiposity at the time of mammography is most strongly associated with MBD, adiposity as early as ages 10 and 18 years is also independently associated with MBD. The commentary emphasizes the need for future research to identify biological mechanisms underlying the associations of adulthood adiposity and lifecourse growth with MBD in NHB women and how these can be translated to breast cancer prevention. Additionally, it highlights the need for more studies looking at lifecourse growth and microscopic breast tissue characteristics such as terminal duct lobular unit involution and epithelial-to-stromal proportions. See related article by Bigham et al., p. 1640.

Associations between quantitative measures of mammographic density and terminal ductal lobular unit involution in Chinese breast cancer patients

BACKGROUND

Higher mammographic density (MD), a radiological measure of the proportion of fibroglandular tissue in the breast, and lower terminal duct lobular unit (TDLU) involution, a histological measure of the amount of epithelial tissue in the breast, are independent breast cancer risk factors. Previous studies among predominantly white women have associated reduced TDLU involution with higher MD.

METHODS

In this cohort of 611 invasive breast cancer patients (ages 23-91 years [58.4% ≥ 50 years]) from China, where breast cancer incidence rates are lower and the prevalence of dense breasts is higher compared with Western countries, we examined the associations between TDLU involution assessed in tumor-adjacent normal breast tissue and quantitative MD assessed in the contralateral breast obtained from the VolparaDensity software. Associations were estimated using generalized linear models with MD measures as the outcome variables (log-transformed), TDLU measures as explanatory variables (categorized into quartiles or tertiles), and adjusted for age, body mass index, parity, age at menarche and breast cancer subtype.

RESULTS

We found that, among all women, percent dense volume (PDV) was positively associated with TDLU count (highest tertile vs. zero: Expbeta = 1.28, 95% confidence interval [CI] 1.08-1.51, ptrend =  < .0001), TDLU span (highest vs. lowest tertile: Expbeta = 1.23, 95% CI 1.11-1.37, ptrend =  < .0001) and acini count/TDLU (highest vs. lowest tertile: Expbeta = 1.22, 95% CI 1.09-1.37, ptrend = 0.0005), while non-dense volume (NDV) was inversely associated with these measures. Similar trend was observed for absolute dense volume (ADV) after the adjustment of total breast volume, although the associations for ADV were in general weaker than those for PDV. The MD-TDLU associations were generally more pronounced among breast cancer patients ≥ 50 years and those with luminal A tumors compared with patients < 50 years and with luminal B tumors.

CONCLUSIONS

Our findings based on quantitative MD and TDLU involution measures among Chinese breast cancer patients are largely consistent with those reported in Western populations and may provide additional insights into the complexity of the relationship, which varies by age, and possibly breast cancer subtype.

Temporal changes in mammographic breast density and breast cancer risk among women with benign breast disease

INTRODUCTION

Benign breast disease (BBD) and high mammographic breast density (MBD) are prevalent and independent risk factors for invasive breast cancer. It has been suggested that temporal changes in MBD may impact future invasive breast cancer risk, but this has not been studied among women with BBD.

METHODS

We undertook a nested case-control study within a cohort of 15,395 women with BBD in Kaiser Permanente Northwest (KPNW; 1970-2012, followed through mid-2015). Cases (n = 261) developed invasive breast cancer > 1 year after BBD diagnosis, whereas controls (n = 249) did not have breast cancer by the case diagnosis date. Cases and controls were individually matched on BBD diagnosis age and plan membership duration. Standardized %MBD change (per 2 years), categorized as stable/any increase (≥ 0%), minimal decrease of less than 5% or a decrease greater than or equal to 5%, was determined from baseline and follow-up mammograms. Associations between MBD change and breast cancer risk were examined using adjusted unconditional logistic regression.

RESULTS

Overall, 64.5% (n = 329) of BBD patients had non-proliferative and 35.5% (n = 181) had proliferative disease with/without atypia. Women with an MBD decrease (≤ - 5%) were less likely to develop breast cancer (Odds Ratio (OR) 0.64; 95% Confidence Interval (CI) 0.38, 1.07) compared with women with minimal decreases. Associations were stronger among women ≥ 50 years at BBD diagnosis (OR 0.48; 95% CI 0.25, 0.92) and with proliferative BBD (OR 0.32; 95% CI 0.11, 0.99).

DISCUSSION

Assessment of temporal MBD changes may inform risk monitoring among women with BBD, and strategies to actively reduce MBD may help decrease future breast cancer risk.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Host, reproductive, and lifestyle factors in relation to quantitative histologic metrics of the normal breast

BACKGROUND

Emerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast.

METHODS

The study participants were 4108 healthy women ages 18-75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008-2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models.

RESULTS

With increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP [β (95% Confidence Interval (CI)) = -0.28 (- 0.43, - 0.13); P < 0.001] with ESP peaks at 30-40 years and 60-70 years among pre- and postmenopausal women, respectively. Pregnancy [β (95%CI) vs nulligravid = 0.19 (0.08, 0.30); P < 0.001] and increasing number of live births (P-trend < 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP [β (95%CI) vs no breastfeeding = -0.15 (- 0.29, - 0.01); P = 0.036]. A positive family history of breast cancer (FHBC) [β (95%CI) vs no FHBC = 0.14 (0.02-0.26); P = 0.02], being overweight or obese [β (95%CI) vs normal weight = 0.18 (0.06-0.30); P = 0.004 and 0.32 (0.21-0.44); P < 0.001, respectively], and Black race [β (95%CI) vs White = 0.12 (- 0.005, 0.25); P = 0.06] were positively associated with ESP.

CONCLUSION

Our findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.

Outdoor air pollution and histologic composition of normal breast tissue

BACKGROUND

Biologic pathways underlying the association between outdoor air pollution and breast cancer risk are poorly understood. Breast tissue composition may reflect cumulative exposure to breast cancer risk factors and has been associated with breast cancer risk among patients with benign breast disease. Herein, we evaluated whether fine particulate matter (PM2.5) was associated with the histologic composition of normal breast tissue.

METHODS

Machine-learning algorithms were applied to digitized hematoxylin and eosin-stained biopsies of normal breast tissue to quantify the epithelium, stroma, adipose and total tissue area from 3,977 individuals aged 18-75 years from a primarily Midwestern United States population who donated breast tissue samples to the Susan G. Komen Tissue Bank (2009-2019). Annual levels of PM2.5 were assigned to each woman's residential address based on year of tissue donation. We applied predictive k-means to assign participants to clusters with similar PM2.5 chemical composition and used linear regression to examine the cross-sectional associations between a 5-μg/m3 increase in PM2.5 and square root-transformed proportions of epithelium, stroma, adipose, and epithelium-to-stroma proportion [ESP], overall and by PM2.5 cluster.

RESULTS

Higher residential PM2.5 was associated with lower proportion of breast stromal tissue [β = -0.93, 95% confidence interval: (-1.52, -0.33)], but was not related to the proportion of epithelium [β = -0.11 (-0.34, 0.11)]. Although PM2.5 was not associated with ESP overall [β = 0.24 (-0.16, 0.64)], the association significantly differed by PM2.5 chemical composition (p-interaction = 0.04), with a positive association evident only among an urban, Midwestern cluster with higher concentrations of nitrate (NO3-) and ammonium (NH4+) [β = 0.49 (0.03, 0.95)].

CONCLUSIONS

Our findings are consistent with a possible role of PM2.5 in breast cancer etiology and suggest that changes in breast tissue composition may be a potential pathway by which outdoor air pollution impacts breast cancer risk. This study further underscores the importance of considering heterogeneity in PM2.5 composition and its impact on breast carcinogenesis.

Associations of breast cancer etiologic factors with stromal microenvironment of primary invasive breast cancers in the Ghana Breast Health Study

Background

Emerging data suggest that beyond the neoplastic parenchyma, the stromal microenvironment (SME) impacts tumor biology, including aggressiveness, metastatic potential, and response to treatment. However, the epidemiological determinants of SME biology remain poorly understood, more so among women of African ancestry who are disproportionately affected by aggressive breast cancer phenotypes.

Methods

Within the Ghana Breast Health Study, a population-based case-control study in Ghana, we applied high-accuracy machine-learning algorithms to characterize biologically-relevant SME phenotypes, including tumor-stroma ratio (TSR (%); a metric of connective tissue stroma to tumor ratio) and tumor-associated stromal cellular density (Ta-SCD (%); a tissue biomarker that is reminiscent of chronic inflammation and wound repair response in breast cancer), on digitized H&E-stained sections from 792 breast cancer patients aged 17-84 years. Kruskal-Wallis tests and multivariable linear regression models were used to test associations between established breast cancer risk factors, tumor characteristics, and SME phenotypes.

Results

Decreasing TSR and increasing Ta-SCD were strongly associated with aggressive, mostly high grade tumors (p-value < 0.001). Several etiologic factors were associated with Ta-SCD, but not TSR. Compared with nulliparous women [mean (standard deviation) = 28.9% (7.1%)], parous women [mean (standard deviation) = 31.3% (7.6%)] had statistically significantly higher levels of Ta-SCD (p-value = 0.01). Similarly, women with a positive family history of breast cancer [FHBC; mean (standard deviation) = 33.0% (7.5%)] had higher levels of Ta-SCD than those with no FHBC [mean (standard deviation) = 30.9% (7.6%); p-value = 0.01]. Conversely, increasing body size was associated with decreasing Ta-SCD [mean (standard deviation) = 32.0% (7.4%), 31.3% (7.3%), and 29.0% (8.0%) for slight, moderate, and large body sizes, respectively, p-value = 0.005]. These associations persisted and remained statistically significantly associated with Ta-SCD in mutually-adjusted multivariable linear regression models (p-value < 0.05). With the exception of body size, which was differentially associated with Ta-SCD by grade levels (p-heterogeneity = 0.04), associations between risk factors and Ta-SCD were not modified by tumor characteristics.

Conclusions

Our findings raise the possibility that epidemiological factors may act via the SME to impact both risk and biology of breast cancers in this population, underscoring the need for more population-based research into the role of SME in multi-state breast carcinogenesis.

Proceedings of the fifth international Molecular Pathological Epidemiology (MPE) meeting

Cancer heterogeneities hold the key to a deeper understanding of cancer etiology and progression and the discovery of more precise cancer therapy. Modern pathological and molecular technologies offer a powerful set of tools to profile tumor heterogeneities at multiple levels in large patient populations, from DNA to RNA, protein and epigenetics, and from tumor tissues to tumor microenvironment and liquid biopsy. When coupled with well-validated epidemiologic methodology and well-characterized epidemiologic resources, the rich tumor pathological and molecular tumor information provide new research opportunities at an unprecedented breadth and depth. This is the research space where Molecular Pathological Epidemiology (MPE) emerged over a decade ago and has been thriving since then. As a truly multidisciplinary field, MPE embraces collaborations from diverse fields including epidemiology, pathology, immunology, genetics, biostatistics, bioinformatics, and data science. Since first convened in 2013, the International MPE Meeting series has grown into a dynamic and dedicated platform for experts from these disciplines to communicate novel findings, discuss new research opportunities and challenges, build professional networks, and educate the next-generation scientists. Herein, we share the proceedings of the Fifth International MPE meeting, held virtually online, on May 24 and 25, 2021. The meeting consisted of 21 presentations organized into the three main themes, which were recent integrative MPE studies, novel cancer profiling technologies, and new statistical and data science approaches. Looking forward to the near future, the meeting attendees anticipated continuous expansion and fruition of MPE research in many research fronts, particularly immune-epidemiology, mutational signatures, liquid biopsy, and health disparities.

Mammary collagen architecture and its association with mammographic density and lesion severity among women undergoing image-guided breast biopsy

Background

Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established.

Methods

Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm²)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section.

Results

Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p < 0.001) and with local percent mammographic density volume at both the biopsy target (p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p < 0.05).

Conclusions

Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01482-z.