Inter-Individual Variation in Response to Estrogen in Human Breast Explants

A novel preclinical model of the normal human breast

Improved screening and treatment have decreased breast cancer mortality, although incidence continues to rise. Women at increased risk of breast cancer can be offered risk reducing treatments, such as tamoxifen, but this has not been shown to reduce breast cancer mortality. New, more efficacious, risk-reducing agents are needed. The identification of novel candidates for prevention is hampered by a lack of good preclinical models. Current patient derived in vitro and in vivo models cannot fully recapitulate the complexities of the human tissue, lacking human extracellular matrix, stroma, and immune cells, all of which are known to influence therapy response. Here we describe a normal breast explant model utilising a tuneable hydrogel which maintains epithelial proliferation, hormone receptor expression, and residency of T cells and macrophages over 7 days. Unlike other organotypic tissue cultures which are often limited by hyper-proliferation, loss of hormone signalling, and short treatment windows (< 48h), our model shows that tissue remains viable over 7 days with none of these early changes. This offers a powerful and unique opportunity to model the normal breast and study changes in response to various risk factors, such as breast density and hormone exposure. Further validation of the model, using samples from patients undergoing preventive therapies, will hopefully confirm this to be a valuable tool, allowing us to test novel agents for breast cancer risk reduction preclinically.

The role of three-dimensional in vitro models in modelling the inflammatory microenvironment associated with obesity in breast cancer

Obesity is an established risk factor for breast cancer in postmenopausal women. However, the underlying biological mechanisms of how obesity contributes to breast cancer remains unclear. The inflammatory adipose microenvironment is central to breast cancer progression and has been shown to favour breast cancer cell growth and to reduce efficacy of anti-cancer treatments. Thus, it is imperative to further our understanding of the inflammatory microenvironment seen in breast cancer patients with obesity. Three-dimensional (3D) in vitro models offer a key tool in increasing our understanding of such complex interactions within the adipose microenvironment. This review discusses some of the approaches utilised to recapitulate the breast tumour microenvironment, including various co-culture and 3D in vitro models. We consider how these model systems contribute to the understanding of breast cancer research, with particular focus on the inflammatory tumour microenvironment. This review aims to provide insight and prospective future directions on the utility of such model systems for breast cancer research.

Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution

The rise and fall of estrogen and progesterone across menstrual cycles and during pregnancy regulates breast development and modifies cancer risk. How these hormones impact each cell type in the breast remains poorly understood because they act indirectly through paracrine networks. Using single-cell analysis of premenopausal breast tissue, we reveal a network of coordinated transcriptional programs representing the tissue-level response to changing hormone levels. Our computational approach, DECIPHER-seq, leverages person-to-person variability in breast composition and cell state to uncover programs that co-vary across individuals. We use differences in cell-type proportions to infer a subset of programs that arise from direct cell-cell interactions regulated by hormones. Further, we demonstrate that prior pregnancy and obesity modify hormone responsiveness through distinct mechanisms: obesity reduces the proportion of hormone-responsive cells, whereas pregnancy dampens the direct response of these cells to hormones. Together, these results provide a comprehensive map of the cycling human breast.

Bisphenol A replacement chemicals, BPF and BPS, induce protumorigenic changes in human mammary gland organoid morphology and proteome

SignificanceBisphenol A (BPA), found in many plastic products, has weak estrogenic effects that can be harmful to human health. Thus, structurally related replacements-bisphenol S (BPS) and bisphenol F (BPF)-are coming into wider use with very few data about their biological activities. Here, we compared the effects of BPA, BPS, and BPF on human mammary organoids established from normal breast tissue. BPS disrupted organoid architecture and induced supernumerary branching. At a proteomic level, the bisphenols altered the abundance of common targets and those that were unique to each compound. The latter included proteins linked to tumor-promoting processes. These data highlighted the importance of testing the human health effects of replacements that are structurally related to chemicals of concern.

Antibody Validation for Estrogen Receptor Beta

Antibodies can cross-react with proteins other than their intended targets, and antibody-based applications can, if not properly validated, lead to flawed interpretations. When evaluating 13 anti-estrogen receptor beta (ERβ) antibodies in 2017, we concluded that only one of them was specific. Applying this antibody in immunohistochemistry of over 44 different normal human tissues and 20 types of cancers revealed ERβ expression in only a few selected tissues. This aligned with mRNA evidence but contradicted a large set of published literature. ERβ protein expression continues to be reported in tissues without clear support by mRNA expression. In this chapter, we describe how ERβ antibodies can be thoroughly validated and discuss selection of well-characterized positive and negative controls. The validation scheme presented is applicable for immunohistochemistry and Western blotting. The protocol includes evaluation of mRNA evidence, use of public databases, assessment of on- and off-target binding, and an optional step for corroboration with immunoprecipitation and mass spectrometry.

Comparison of hormone-induced mRNA and protein biomarker expression changes in breast cancer cells

PURPOSE

Protein biomarkers estrogen receptor (ER), progesterone receptor (PR), and marker of proliferation (Ki67) are routinely assessed by immunohistochemistry to guide treatment decisions for breast cancer. Now, quantification of mRNA encoding these proteins is being adopted in the clinic. However, mRNA and protein biomarkers may be differentially regulated by fluctuations in estrogen and progesterone that occur across the menstrual cycle in premenopausal breast cancer patients. This study aimed to compare how estrogen and progesterone affect mRNA and protein biomarker expression in hormone-responsive breast cancer cells.

METHODS

Hormone-responsive ZR-75-1 and T-47D human breast cancer cell lines were xenografted into the mammary fat pad of BALB/c nude mice supplemented with estrogen. Progesterone or vehicle was administered prior to dissection of tumors. Protein expression of ER, PR and Ki67 was quantified by immunohistochemistry, and mRNA encoding these proteins, ESR1, PGR and KI67, respectively, was quantified by real-time PCR. mRNA expression was also quantified in breast cancer cell lines treated with estrogen and progesterone in vitro.

RESULTS

In T-47D-xenografted tumors, estrogen and progesterone treatment reduced PGR and KI67 mRNA expression, and reduced PR and Ki67 protein positivity, compared to estrogen treatment alone. In ZR-75-1 xenografted tumors, no significant differences in protein or mRNA biomarker expression were observed. In vitro, estrogen and progesterone co-treatment significantly reduced ESR1 and PGR mRNA expression in both T-47D and ZR-75-1 cell lines.

CONCLUSIONS

Estrogen and progesterone similarly affect mRNA and protein biomarker expression in hormone-responsive breast cancer xenografts. Further research is needed to investigate concordance between protein and mRNA biomarkers in premenopausal breast cancer.