CCL2-driven inflammation increases mammary gland stromal density and cancer susceptibility in a transgenic mouse model

Sun, Xuan; Glynn, Danielle J.; Hodson, Leigh J.; Huo, Cecilia W.; Britt, Kara; Thompson, Erik W.; Woolford, Lucy; Evdokiou, Andreas; Pollard, Jeffrey W.; Robertson, Sarah A.; Ingman, Wendy V.

doi:10.1186/s13058-016-0796-z

Cited by 67 publications

(63 citation statements)

References 65 publications

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“…A). Although 2D imaging can be sufficient to demonstrate broad changes in branching morphogenesis and alveolar budding across the oestrous cycle, as has been shown previously , here we highlight the importance of deep imaging analyses that do not depend critically on the plane of section and where the relationship between buds and branches is much more visually apparent. We noted also the precise orientation and high density of the long, thin basal myoepithelial cells that run in parallel to the direction of ductal elongation (Fig.…”

Section: Resultssupporting

confidence: 54%

Dynamic architectural interplay between leucocytes and mammary epithelial cells

et al. 2019

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The adult mammary gland undergoes dynamic changes during puberty and the postnatal developmental cycle. The mammary epithelium is composed of a bilayer of outer basal, or myoepithelial, cells and inner luminal cells, the latter lineage giving rise to the milk-producing alveolar cells during pregnancy. These luminal alveolar cells undergo Stat3-mediated programmed cell death following the cessation of lactation. It is established that immune cells in the microenvironment of the gland have a role to play both in the ductal outgrowth during puberty and in the removal of dead cells and remodelling of the stroma during the process of postlactational regression. However, most studies have focussed on the role of the stromal immune cell compartment or have quantified immune cell populations in tissue extracts. Our recent development of protocols for deep imaging of the mammary gland in three dimensions (3D) has enabled the architectural relationship between immune cells and the epithelium to be examined in detail, and we have discovered a surprisingly dynamic relationship between the basal epithelium and leucocytes. Furthermore, we have observed morphological changes in the myoepithelial cells, as involution progresses, which were not revealed by previous work in 2D tissue sections and whole tissue. This dynamic architecture suggests a role for myoepithelial cells in the orderly progression of involution. We conclude that deep imaging of mammary gland and other tissues is essential for analysing complex interactions between cellular compartments.Abbreviations 2D, two dimensions; 3D, three dimensions; CD, cluster of differentiation; DAPI, 4 0 ,6-diamidino-2-phenylindole; DCIS, ductal carcinoma in situ; DCs, dendritic cells; DNA, deoxyribonucleic acid; GPI, glycosylphosphatidylinositol; H&E, haematoxylin and eosin; IgA, immunoglobulin A; K5, keratin 5; LIF, leukaemia inhibitory factor; MHCII, major histocompatibility complex class II; MIP, maximum intensity projection; MMPs, matrix metalloproteinases; NF-jB, nuclear factor kappa-light-chain-enhancer of activated B cells; SEMA, semaphorin; SMA, smooth muscle actin isoform a-actin; Stat, signal transducer and activator of transcription; TEBs, terminal end buds; Th, T helper; VEGF, vascular endothelial growth factor.

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Section: Resultssupporting

confidence: 54%

Dynamic architectural interplay between leucocytes and mammary epithelial cells

et al. 2019

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“…The biologic reasons why regions on a mammogram appear to be highly dense is not well understood and difficult to resolve, not the least because a mammogram is a two-dimensional picture of a three-dimensional object. Although it is beyond the scope of this study to speculate on what those processes might be, an increasing amount of work is being published on potential biologic mechanisms (27). Third, these new breast cancer risk factors are among the strongest yet in terms of differentiating the women who will from those who will not get breast cancer from a population perspective versus from an individual perspective.…”

Section: Discussionmentioning

confidence: 99%

Breast Cancer Risk Associations with Digital Mammographic Density by Pixel Brightness Threshold and Mammographic System

Nguyen¹,

Choi²,

Aung³

et al. 2018

Radiology

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Purpose To compare three mammographic density measures defined by different pixel intensity thresholds as predictors of breast cancer risk for two different digital mammographic systems. Materials and Methods The Korean Breast Cancer Study included 398 women with invasive breast cancer and 737 control participants matched for age at mammography (±1 year), examination date, mammographic system, and menopausal status. Mammographic density was measured by using the automated Laboratory for Individualized Breast Radiodensity Assessment (LIBRA) software and the semiautomated Cumulus software at the conventional threshold (Cumulus) and at increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were Box-Cox-transformed and adjusted for age, body mass index, and menopausal status. Conditional logistic regression was used to estimate risk associations. For calculation of measures of predictive value, the change in odds per standard deviation (OPERA) and the area under the receiver operating characteristic curve (AUC) were used. Results For dense area, with use of the direct conversion system the OPERAs were 1.72 (95% confidence interval [CI]: 1.38, 2.15) for LIBRA, 1.58 (95% CI: 1.27, 1.97) for Cumulus, 2.04 (95% CI: 1.60, 2.59) for Altocumulus, and 3.48 (95% CI: 2.45, 4.47) for Cirrocumulus (P < .001). The corresponding AUCs were 0.70, 0.69, 0.76, and 0.89, respectively. With use of the indirect conversion system, the corresponding OPERAs were 1.50 (95% CI: 1.28, 1.76), 1.36 (95% CI: 1.16, 1.59), 1.40 (95% CI: 1.19, 1.64), and 1.47 (95% CI: 1.25, 1.73) (P < .001) and the AUCs were 0.64, 0.60, 0.61, and 0.63, respectively. Conclusion It is possible that mammographic density defined by higher pixel thresholds could capture more risk-predicting information with use of a direct conversion mammographic system; the mammographically bright, rather than white, regions are etiologically important. RSNA, 2017.

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“…A variety of chemokines are found in human mammary glands and milk and are required for development and differentiation of mammary glands due to their chemotactic functions (Gouon-Evans et al, 2002;Suzuki et al, 2015). C-C motif chemokine ligand 2 (CCL2), also known as monocyte chemoattractant protein-1 (MCP1), plays a role in migration and infiltration of monocytes and macrophages, and overexpression of CCL2 appears to increase the risk of breast cancer in a transgenic mouse model (Kitamura et al, 2015;Sun et al, 2017). However, it is unclear whether the activity of CCL2 is involved in the proliferation and apoptosis of bovine mammary epithelial cells and related cell signaling pathways.…”

Section: Introductionmentioning

confidence: 99%

C-C motif chemokine ligand 2 induces proliferation and prevents lipopolysaccharide-induced inflammatory responses in bovine mammary epithelial cells

Yang

Lim

Bae

et al. 2018

Journal of Dairy Science

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C-C motif chemokine ligand 2 (CCL2) is a small chemokine which belongs to the CC-type chemokine family, and has chemoattractant activity for recruitment of monocytes to sites of inflammation. Overexpressed CCL2 binding to its receptor C-C chemokine receptor 2 increases the risk of breast cancer in humans, but its effects on proliferation of bovine mammary epithelial cells is not known. Maintaining a high level of proliferative activity in bovine mammary epithelial cells during lactation is important for improving milk yield and can benefit the dairy industry economically. In the present study, we demonstrated that CCL2 induces proliferation of MAC-T cells, a bovine mammary epithelial cell line, and stimulates progression of the cell cycle through stimulation of expression of cyclin D1. Moreover, CCL2 activates phosphoinositide 3-kinase (PI3K)/AKT [AKT, P70-S6 kinase 1 (P70S6K), ribosomal protein S6 (S6)] and mitogen activated protein kinase (MAPK) [extracellular signal-regulated kinase-1/2 (ERK1/2), c-Jun N-terminal kinase (JNK), and P38] pathways, which are involved in proliferation of MAC-T cells, as evidenced by co-treatment of MAC-T cells with pharmacological inhibitors of cell signaling transcription factors including Wortmannin, U0126, and SP600125. The CCL2 in MAC-T cells attenuates endoplasmic reticulum stress induced by tunicamycin, suggesting that CCL2 regulates intracellular synthesis of proteins and lipids and prevents activation of apoptotic pathways initiated in response to endoplasmic reticulum stress. Furthermore, CCL2 is involved in alleviating lipopolysaccharide (LPS)-induced inflammatory responses in MAC-T cells by reducing LPS-induced expression of IL8, IL6, and nuclear factor kappa B subunit 1 (NFKB1). Collectively, CCL2 is a novel target for improving the quantity and quality of milk from cows through stimulation of proliferation on mammary epithelial cells and attenuation of LPS-induced inflammatory responses.

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CCL2-driven inflammation increases mammary gland stromal density and cancer susceptibility in a transgenic mouse model

Cited by 67 publications

References 65 publications

Dynamic architectural interplay between leucocytes and mammary epithelial cells

Dynamic architectural interplay between leucocytes and mammary epithelial cells

Breast Cancer Risk Associations with Digital Mammographic Density by Pixel Brightness Threshold and Mammographic System

C-C motif chemokine ligand 2 induces proliferation and prevents lipopolysaccharide-induced inflammatory responses in bovine mammary epithelial cells

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