Breast Tissue Composition and Immunophenotype and Its Relationship with Mammographic Density in Women at High Risk of Breast Cancer

Baseline breast tissue characteristics determine the effect of tamoxifen on mammographic density change

Tamoxifen prevents recurrence of breast cancer and is also approved for preventive, risk-reducing, therapy. Tamoxifen alters the breast tissue composition and decreases the mammographic density. We aimed to test if baseline breast tissue composition influences tamoxifen-associated density change. This biopsy-based study included 83 participants randomised to 6 months daily intake of placebo, 20, 10, 5, 2.5, or 1 mg tamoxifen. The study is nested within the double-blinded tamoxifen dose-determination trial Karolinska Mammography Project for Risk Prediction of Breast Cancer Intervention (KARISMA) Study. Ultrasound-guided core-needle breast biopsies were collected at baseline before starting treatment. Biopsies were quantified for epithelial, stromal, and adipose distributions, and epithelial and stromal expression of proliferation marker Ki67, oestrogen receptor (ER) and progesterone receptor (PR). Mammographic density was measured using STRATUS. We found that greater mammographic density at baseline was positively associated with stromal area and inversely associated with adipose area and stromal expression of ER. Premenopausal women had greater mammographic density and epithelial tissue, and expressed more epithelial Ki67, PR, and stromal PR, compared to postmenopausal women. In women treated with tamoxifen (1-20 mg), greater density decrease was associated with higher baseline density, epithelial Ki67, and stromal PR. Women who responded to tamoxifen with a density decrease had on average 17% higher baseline density and a 2.2-fold higher PR expression compared to non-responders. Our results indicate that features in the normal breast tissue before tamoxifen exposure influences the tamoxifen-associated density decrease, and that the age-associated difference in density change may be related to age-dependant differences in expression of Ki67 and PR.

Increased matrix stiffness enhances pro-tumorigenic traits in a physiologically relevant breast tissue- monocyte 3D model

High mammographic density, associated with increased tissue stiffness, is a strong risk factor for breast cancer per se. In postmenopausal women there is no differences in the occurrence of ductal carcinoma in situ (DCIS) depending on breast density. Preliminary data suggest that dense breast tissue is associated with a pro-inflammatory microenvironment including infiltrating monocytes. However, the underlying mechanism(s) remains largely unknown. A major roadblock to understanding this risk factor is the lack of relevant in vitro models. A biologically relevant 3D model with tunable stiffness was developed by cross-linking hyaluronic acid. Breast cancer cells were cultured with and without freshly isolated human monocytes. In a unique clinical setting, extracellular proteins were sampled using microdialysis in situ from women with various breast densities. We show that tissue stiffness resembling high mammographic density increases the attachment of monocytes to the cancer cells, increase the expression of adhesion molecules and epithelia-mesenchymal-transition proteins in estrogen receptor (ER) positive breast cancer. Increased tissue stiffness results in increased secretion of similar pro-tumorigenic proteins as those found in human dense breast tissue including inflammatory cytokines, proteases, and growth factors. ER negative breast cancer cells were mostly unaffected suggesting that diverse cancer cell phenotypes may respond differently to tissue stiffness. We introduce a biological relevant model with tunable stiffness that resembles the densities found in normal breast tissue in women. The model will be key for further mechanistic studies. Additionally, our data revealed several pro-tumorigenic pathways that may be exploited for prevention and therapy against breast cancer. STATEMENT OF SIGNIFICANCE: Women with mammographic high-density breasts have a 4-6-fold higher risk of breast cancer than low-density breasts. Biological mechanisms behind this increase are not fully understood and no preventive therapeutics are available. One major reason being a lack of suitable experimental models. Having such models available would greatly enhance the discovery of relevant targets for breast cancer prevention. We present a biologically relevant 3D-model for studies of human dense breasts, providing a platform for investigating both biophysical and biochemical properties that may affect cancer progression. This model will have a major scientific impact on studies for identification of novel targets for breast cancer prevention.

Breast density is strongly associated with multiparametric magnetic resonance imaging biomarkers and pro-tumorigenic proteins in situ

BACKGROUND

High mammographic density is an independent risk factor for breast cancer by poorly understood molecular mechanisms. Women with dense breasts often undergo conventional magnetic resonance imaging (MRI) despite its limited specificity, which may be increased by diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) and contrast. How these modalities are affected by breast density per se and their association with the local microenvironment are undetermined.

METHODS

Healthy postmenopausal women attending mammography screen with extremely dense or entirely fatty breasts underwent multiparametric MRI for analyses of lean tissue fraction (LTF), ADC and perfusion dynamics. Microdialysis was used for extracellular proteomics in situ.

RESULTS

Significantly increased LTF and ADC and delayed perfusion were detected in dense breasts. In total, 270 proteins were quantified, whereof 124 related to inflammation, angiogenesis, and cellular growth were significantly upregulated in dense breasts. Most of these correlated significantly with LTF, ADC and the perfusion data.

CONCLUSIONS

ADC and perfusion characteristics depend on breast density, which should be considered during the implementation of thresholds for malignant lesions. Dense and nondense breasts are two essentially different biological entities, with a pro-tumorigenic microenvironment in dense breasts. Our data reveal several novel pathways that may be explored for breast cancer prevention strategies.

Artificial intelligence scale-invariant feature transform algorithm-based system to improve the calculation accuracy of Ki-67 index in invasive breast cancer: a multicenter retrospective study

BACKGROUND

Ki-67 is a key indicator of the proliferation activity of tumors. However, no standardized criterion has been established for Ki-67 index calculation. Scale-invariant feature transform (SIFT) algorithm can identify the robust invariant features to rotation, translation, scaling and linear intensity changes for matching and registration in computer vision. Thus, this study aimed to develop a SIFT-based computer-aided system for Ki-67 calculation in breast cancer.

METHODS

Hematoxylin and eosin (HE)-stained and Ki-67-stained slides were scanned and whole slide images (WSIs) were obtained. The regions of breast cancer (BC) tissues and non-BC tissues were labeled by experienced pathologists. All the labeled WSIs were randomly divided into the training set, verification set, and test set according to a fixed ratio of 7:2:1. The algorithm for identification of cancerous regions was developed by a ResNet network. The registration process between paired consecutive HE-stained WSIs and Ki-67-stained WSIs was based on a pyramid model using the feature matching method of SIFT. After registration, we counted the nuclear-stained Ki-67-positive cells in each identified invasive cancerous region using color deconvolution. To assess the accuracy, the AI-assisted result for each slice was compared with the manual diagnosis result of pathologists. If the difference of the two positive rate values is not greater than 10%, it was a consistent result; otherwise, it was an inconsistent result.

RESULTS

The accuracy of the AI-based algorithm in identifying breast cancer tissues in HE-stained slides was 93%, with an area under the curve (AUC) of 0.98. After registration, we succeeded in identifying Ki-67-positive cells among cancerous cells across the entire WSIs and calculated the Ki-67 index, with an accuracy rate of 91.5%, compared to the gold standard pathological reports. Using this system, it took about 1 hour to complete the evaluation of all the tested 771 pairs of HE- and Ki-67-stained slides. Each Ki-67 result took less than 2 seconds.

CONCLUSIONS

Using a pyramid model and the SIFT feature matching method, we developed an AI-based automatic cancer identification and Ki-67 index calculation system, which could improve the accuracy of Ki-67 index calculation and make the data repeatable among different hospitals and centers.

Mechanotransduction at the Plasma Membrane-Cytoskeleton Interface

Mechanical cues are crucial for survival, adaptation, and normal homeostasis in virtually every cell type. The transduction of mechanical messages into intracellular biochemical messages is termed mechanotransduction. While significant advances in biochemical signaling have been made in the last few decades, the role of mechanotransduction in physiological and pathological processes has been largely overlooked until recently. In this review, the role of interactions between the cytoskeleton and cell-cell/cell-matrix adhesions in transducing mechanical signals is discussed. In addition, mechanosensors that reside in the cell membrane and the transduction of mechanical signals to the nucleus are discussed. Finally, we describe two examples in which mechanotransduction plays a significant role in normal physiology and disease development. The first example is the role of mechanotransduction in the proliferation and metastasis of cancerous cells. In this system, the role of mechanotransduction in cellular processes, including proliferation, differentiation, and motility, is described. In the second example, the role of mechanotransduction in a mechanically active organ, the gastrointestinal tract, is described. In the gut, mechanotransduction contributes to normal physiology and the development of motility disorders.

Stiff stroma increases breast cancer risk by inducing the oncogene ZNF217

Women with dense breasts have an increased lifetime risk of malignancy that has been attributed to a higher epithelial density. Quantitative proteomics, collagen analysis, and mechanical measurements in normal tissue revealed that stroma in the high-density breast contains more oriented, fibrillar collagen that is stiffer and correlates with higher epithelial cell density. microRNA (miR) profiling of breast tissue identified miR-203 as a matrix stiffness-repressed transcript that is downregulated by collagen density and reduced in the breast epithelium of women with high mammographic density. Culture studies demonstrated that ZNF217 mediates a matrix stiffness- and collagen density-induced increase in Akt activity and mammary epithelial cell proliferation. Manipulation of the epithelium in a mouse model of mammographic density supported a causal relationship between stromal stiffness, reduced miR-203, higher levels of the murine homolog Zfp217, and increased Akt activity and mammary epithelial proliferation. ZNF217 was also increased in the normal breast epithelium of women with high mammographic density, correlated positively with epithelial proliferation and density, and inversely with miR-203. The findings identify ZNF217 as a potential target toward which preexisting therapies, such as the Akt inhibitor triciribine, could be used as a chemopreventive agent to reduce cancer risk in women with high mammographic density.

Postmenopausal Dense Breasts Maintain Premenopausal Levels of GH and Insulin-like Growth Factor Binding Proteins in Vivo

CONTEXT

Dense breast tissue is associated with 4 to 6 times higher risk of breast cancer by poorly understood mechanisms. No preventive therapy for this high-risk group is available. After menopause, breast density decreases due to involution of the mammary gland. In dense breast tissue, this process is haltered by undetermined biological actions. Growth hormone (GH) and insulin-like binding proteins (IGFBPs) play major roles in normal mammary gland development, but their roles in maintaining breast density are unknown.

OBJECTIVE

To reveal in vivo levels of GH, IGFBPs, and other pro-tumorigenic proteins in the extracellular microenvironment in breast cancer, in normal breast tissue with various breast density in postmenopausal women, and premenopausal breasts. We also sought to determine possible correlations between these determinants.

SETTING AND DESIGN

Microdialysis was used to collect extracellular in vivo proteins intratumorally from breast cancers before surgery and from normal human breast tissue from premenopausal women and postmenopausal women with mammographic dense or nondense breasts.

RESULTS

Estrogen receptor positive breast cancers exhibited increased extracellular GH (P < .01). Dense breasts of postmenopausal women exhibited similar levels of GH as premenopausal breasts and significantly higher levels than in nondense breasts (P < .001). Similar results were found for IGFBP-1, -2, -3, and -7 (P < .01) and for IGFBP-6 (P <.05). Strong positive correlations were revealed between GH and IGFBPs and pro-tumorigenic matrix metalloproteinases, urokinase-type plasminogen activator, Interleukin 6, Interleukin 8, and vascular endothelial growth factor in normal breast tissue.

CONCLUSIONS

GH pathways may be targetable for cancer prevention therapeutics in postmenopausal women with dense breast tissue.

Breast Density in a Contemporary Cohort of Women With Ductal Carcinoma In Situ (DCIS)

BACKGROUND

Mammographic breast density (MBD) is an independent risk factor for breast cancer. Information regarding the relationship of MBD and breast cancer biology in women with ductal carcinoma in situ (DCIS) is currently lacking. This study aimed to examine the clinicopathologic characteristics of DCIS in women stratified by MBD.

METHODS

A retrospective review was performed to identify women with pure DCIS who underwent preoperative mammography between 2010 and 2018. Clinicopathologic and demographic data were collected. For the purpose of analysis, MBD was categorized as "non-dense" (Breast Imaging-Reporting and Data System [BI-RADS] density categories A and B) or "dense" (BI-RADS C and D) according to its identification in radiology reports.

RESULTS

Of 3227 patients with a breast cancer diagnosis enrolled in the institutional Breast Cancer Database during the study period, 658 (20%) had pure DCIS. Of these 658 patients, 42% had non-dense breasts, and 58% had dense breasts. Most lesions were non-palpable (92%) and detected by mammography (84%). Patients with dense breasts were more likely to be younger at the time of diagnosis (p < 0.001), premenopausal (p < 0.001), and Asian (p = 0.018), and to have higher-grade disease (p = 0.006; Table 2). Family history, BRCA status, parity, mammogram frequency, palpability, method of presentation, lesion size, hormone receptor status, comedo histology, and recurrence did not differ significantly between the two groups (Table 1). The median follow-up period was 7.1 years.

CONCLUSION

Women with pure DCIS and higher MBD are more likely to be younger at the time of diagnosis, premenopausal, and Asian, and to present with higher-grade disease. Further research on the relationship of age, MBD, and tumor biology in DCIS is warranted.

Mammographic density: a potential monitoring biomarker for adjuvant and preventative breast cancer endocrine therapies

Increased mammographic density (MD) has been shown beyond doubt to be a marker for increased breast cancer risk, though the underpinning pathobiology is yet to be fully elucidated. Estrogenic activity exerts a strong influence over MD, which consequently has been observed to change predictably in response to tamoxifen anti-estrogen therapy, although results for other selective estrogen receptor modulators and aromatase inhibitors are less consistent. In both primary and secondary prevention settings, tamoxifen-associated MD changes correlate with successful modulation of risk or outcome, particularly among pre-menopausal women; an observation that supports the potential use of MD change as a surrogate marker where short-term MD changes reflect longer-term anti-estrogen efficacy. Here we summarize endocrine therapy-induced MD changes and attendant outcomes and discuss both the need for outcome surrogates in such therapy, as well as make a case for MD as such a monitoring marker. We then discuss the process and steps required to validate and introduce MD into practice as a predictor or surrogate for endocrine therapy efficacy in preventive and adjuvant breast cancer treatment settings.

MMTV-NeuT/ATTAC mice: a new model for studying the stromal tumor microenvironment

One of the central challenges in cancer prevention is the identification of factors in the tumor microenvironment (TME) that increase susceptibility to tumorigenesis. One such factor is stromal fibrosis, a histopathologic negative prognostic criterion for invasive breast cancer. Since the stromal composition of the breast is largely adipose and fibroblast tissue, it is important to understand how alterations in these tissues affect cancer progression. To address this question, a novel transgenic animal model was developed by crossing MMTV-NeuT mice containing a constitutively active ErbB2 gene into the FAT-ATTAC (fat apoptosis through targeted activation of caspase 8) background, which expresses an inducible caspase 8 fusion protein targeted to mammary adipose tissue. Upon caspase 8 activation, lipoatrophy of the mammary gland results in stromal fibrosis and acceleration of mammary tumor development with an increase in tumor multiplicity. Fibrosis was accompanied by an increase in collagen deposition, α-smooth muscle actin and CD31 expression in the tumor stroma as well as an increase in PD-L1-positive tumor cells, and infiltration by regulatory T cells, myeloid-derived suppressor cells and tumor-associated macrophages. Gene expression and signal transduction profiling indicated upregulation of pathways associated with cytokine signaling, inflammation and proliferation. This model should be useful for evaluating new therapies that target desmoplasia in the TME associated with invasive cancer.

Equal Pro-inflammatory Profiles of CCLs, CXCLs, and Matrix Metalloproteinases in the Extracellular Microenvironment In Vivo in Human Dense Breast Tissue and Breast Cancer

The inflammatory microenvironment affects breast cancer progression. Proteins that govern the inflammatory response are secreted into the extracellular space, but this compartment still needs to be characterized in human breast tissues in vivo. Dense breast tissue is a major risk factor for breast cancer by yet unknown mechanisms and no non-toxic prevention for these patients exists. Here, we used the minimal invasive technique of microdialysis for sampling of extracellular proteins in live tissues in situ in breast cancers of women before surgery and in healthy women having dense or non-dense breast tissue on mammography. Proteins were profiled using a proximity extension assay. Out of the 32 proteins assessed, 26 exhibited similar profiles in breast cancers and dense breast tissues; CCL-4, -7, -8, -11, -15, -16, -22, -23, and -25, CXCL-5, -8, -9, -16 as well as sIL-6R, IL-18, vascular endothelial growth factor, TGF-α, fibroblast growth factor 19, matrix metalloproteinase (MMP)-1, -2, -3, and urokinase-type plasminogen activator were all increased, whereas CCL-3, CX3CL1, hepatocyte growth factor, and MMP-9 were unaltered in the two tissues. CCL-19 and -24, CXCL-1 and -10, and IL-6 were increased in dense breast tissue only, whereas IL-18BP was increased in breast cancer only. Our results provide novel insights in the inflammatory microenvironment in human breast cancer in situ and define potential novel therapeutic targets. Additionally, we show previously unrecognized similarities of the pro-inflammatory microenvironment in dense breast tissue and breast cancer in vivo suggesting that anti-inflammatory breast cancer prevention trials for women with dense breast tissue may be feasible.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.

Stromal characteristics may hold the key to mammographic density: the evidence to date

There is strong epidemiological data indicating a role for increased mammographic density (MD) in predisposing to breast cancer, however, the biological mechanisms underlying this phenomenon are less well understood. Recently, studies of human breast tissues have started to characterise the features of mammographically dense breasts, and a number of in-vitro and in-vivo studies have explored the potential mechanisms through which dense breast tissue may exert this tumourigenic risk. This article aims to review both the pathological and biological evidence implicating a key role for the breast stromal compartment in MD, how this may be modified and the clinical significance of these findings. The epidemiological context will be briefly discussed but will not be covered in detail.

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.

Correlation of Breast Ultrasound Classifications with Breast Cancer in Chinese Women

The aim of this study was to identify potential links between ultrasonographic breast parenchymal patterns and the risk of breast cancer in Chinese women. The population of Chinese women at high risk for breast cancer was explored using the ultrasonographic classification. Ultrasonographic parenchymal patterns were classified into four types: heterogeneous type, ductal type, mixed type and fibrous type. A total of 5879 Chinese women underwent breast ultrasound examination from May 2010 to April 2014. Of the 5879 women, 256 women had pathology-confirmed breast cancer. Among the remaining 5623 women, 512 randomly selected, age-matched women were recruited into the present study. The correlation between ultrasonographic type and breast cancer revealed that the odds ratio (OR) was highest for the heterogeneous type (odds ratio = 4.11, 95% confidence interval: 2.01-8.41, p < 0.001), followed by the fibrous type (odds ratio = 2.05, 95% confidence interval: 1.51-2.78, p < 0.001). The odds ratios of the ductal and mixed types were both less than 1 (p < 0.05). This study indicates that the heterogeneous and fibrous types in the ultrasonographic classification are associated with an increased risk of breast cancer and, therefore, can be used as a marker of breast cancer risk in the female population of China.

Mammographically dense human breast tissue stimulates MCF10DCIS.com progression to invasive lesions and metastasis

Background

High mammographic density (HMD) not only confers a significantly increased risk of breast cancer (BC) but also is associated with BCs of more advanced stages. However, it is unclear whether BC progression and metastasis are stimulated by HMD. We investigated whether patient-derived HMD breast tissue could stimulate the progression of MCF10DCIS.com cells compared with patient-matched low mammographic density (LMD) tissue.

Methods

Sterile breast specimens were obtained immediately after prophylactic mastectomy from high-risk women (n = 10). HMD and LMD regions of each specimen were resected under radiological guidance. Human MCF10DCIS.com cells, a model of ductal carcinoma in situ (DCIS), were implanted into silicone biochambers in the groins of severe combined immunodeficiency mice, either alone or with matched LMD or HMD tissue (1:1), and maintained for 6 weeks. We assessed biochamber weight as a measure of primary tumour growth, histological grade of the biochamber material, circulating tumour cells and metastatic burden by luciferase and histology. All statistical tests were two-sided.

Results

HMD breast tissue led to increased primary tumour take, increased biochamber weight and increased proportions of high-grade DCIS and grade 3 invasive BCs compared with LMD. This correlated with an increased metastatic burden in the mice co-implanted with HMD tissue.

Conclusions

Our study is the first to explore the direct effect of HMD and LMD human breast tissue on the progression and dissemination of BC cells in vivo. The results suggest that HMD status should be a consideration in decision-making for management of patients with DCIS lesions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-016-0767-4) contains supplementary material, which is available to authorized users.

Dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment in vivo

Inflammation is one of the hallmarks of carcinogenesis. High mammographic density has been associated with increased risk of breast cancer but the mechanisms behind are poorly understood. We evaluated whether breasts with different mammographic densities exhibited differences in the inflammatory microenvironment. Postmenopausal women attending the mammography-screening program were assessed having extreme dense, n = 20, or entirely fatty breasts (nondense), n = 19, on their regular mammograms. Thereafter, the women were invited for magnetic resonance imaging (MRI), microdialysis for the collection of extracellular molecules in situ and a core tissue biopsy for research purposes. On the MRI, lean tissue fraction (LTF) was calculated for a continuous measurement of breast density. LTF confirmed the selection from the mammograms and gave a continuous measurement of breast density. Microdialysis revealed significantly increased extracellular in vivo levels of IL-6, IL-8, vascular endothelial growth factor, and CCL5 in dense breast tissue as compared with nondense breasts. Moreover, the ratio IL-1Ra/IL-1β was decreased in dense breasts. No differences were found in levels of IL-1β, IL-1Ra, CCL2, leptin, adiponectin, or leptin:adiponectin ratio between the two breast tissue types. Significant positive correlations between LTF and the pro-inflammatory cytokines as well as between the cytokines were detected. Stainings of the core biopsies exhibited increased levels of immune cells in dense breast tissue. Our data show that dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment and, if confirmed in a larger cohort, suggests novel targets for prevention therapies for women with dense breast tissue.

Amount of stroma is associated with mammographic density and stromal expression of oestrogen receptor in normal breast tissues

Following female sex and age, mammographic density is considered one of the strongest risk factors for breast cancer. Despite the association between mammographic density and breast cancer risk, little is known about the underlying histology and biological basis of breast density. To better understand the mechanisms behind mammographic density we assessed morphology, proliferation and hormone receptor status in relation to mammographic density in breast tissues from healthy women. Tissues were obtained from 2012-2013 by ultrasound-guided core needle biopsy from 160 women as part of the Karma (Karolinska mammography project for risk prediction for breast cancer) project. Mammograms were collected through routine mammography screening and mammographic density was calculated using STRATUS. The histological composition, epithelial and stromal proliferation status and hormone receptor status were assessed through immunohistochemical staining. Higher mammographic density was significantly associated with a greater proportion of stromal and epithelial tissue and a lower proportion of adipose tissue. Epithelial expression levels of Ki-67, oestrogen receptor (ER) and progesterone receptor (PR) were not associated with mammographic density. Epithelial Ki-67 was associated with a greater proportion of epithelial tissue, and epithelial PR was associated with a greater proportion of stromal and a lower proportion of adipose tissue. Epithelial ER was not associated with any tissues. In contrast, expression of ER in the stroma was significantly associated with a greater proportion of stroma, and negatively associated with the amount of adipose tissue. High mammographic density is associated with higher amount of stroma and epithelium and less amount of fat, but is not associated with a change in epithelial proliferation or receptor status. Increased expressions of both epithelial PR and stromal ER are associated with a greater proportion of stroma, suggesting hormonal involvement in regulating breast tissue composition.

Neutrophils drive accelerated tumor progression in the collagen-dense mammary tumor microenvironment

Background

High mammographic density has been correlated with a 4-fold to 6-fold increased risk of developing breast cancer, and is associated with increased stromal deposition of extracellular matrix proteins, including collagen I. The molecular and cellular mechanisms responsible for high breast tissue density are not completely understood.

Methods

We previously described accelerated tumor formation and metastases in a transgenic mouse model of collagen-dense mammary tumors (type I collagen-α1 (Col1α1)^tm1Jae and mouse mammary tumor virus - polyoma virus middle T antigen (MMTV-PyVT)) compared to wild-type mice. Using ELISA cytokine arrays and multi-color flow cytometry analysis, we studied cytokine signals and the non-malignant, immune cells in the collagen-dense tumor microenvironment that may promote accelerated tumor progression and metastasis.

Results

Collagen-dense tumors did not show any alteration in immune cell populations at late stages. The cytokine signals in the mammary tumor microenvironment were clearly different between wild-type and collagen-dense tumors. Cytokines associated with neutrophil signaling, such as granulocyte monocyte-colony stimulated factor (GM-CSF), were increased in collagen-dense tumors. Depleting neutrophils with anti-Ly6G (1A8) significantly reduced the number of tumors, and blocked metastasis in over 80 % of mice with collagen-dense tumors, but did not impact tumor growth or metastasis in wild-type mice.

Conclusion

Our study suggests that tumor progression in a collagen-dense microenvironment is mechanistically different, with pro-tumor neutrophils, compared to a non-dense microenvironment.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-016-0703-7) contains supplementary material, which is available to authorized users.