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Macrophages are diverse immune cells that reside in all tissues. Although macrophages have been implicated in mammary-gland function, their diversity has not been fully addressed. By exploiting high-resolution three-dimensional imaging and flow cytometry, we identified a unique population of tissue-resident ductal macrophages that form a contiguous network between the luminal and basal layers of the epithelial tree throughout postnatal development. Ductal macrophages are long lived and constantly survey the epithelium through dendrite movement, revealed via advanced intravital imaging. Although initially originating from embryonic precursors, ductal macrophages derive from circulating monocytes as they expand during puberty. Moreover, they undergo proliferation in pregnancy to maintain complete coverage of the epithelium in lactation, when they are poised to phagocytose milk-producing cells post-lactation and facilitate remodelling. Interestingly, ductal macrophages strongly resemble mammary tumour macrophages and form a network that pervades the tumour. Thus, the mammary epithelium programs specialized resident macrophages in both physiological and tumorigenic contexts.Dawson et al. characterize a macrophage population associated with mammary ducts that are long lived, derive from embryonic precursors and have multiple roles in pregnancy, lactation, involution and cancer.

Despite rapid advances in our knowledge of the cellular heterogeneity and molecular regulation of the mammary gland, how these relate to 3D cellular organization remains unclear. In addition to hormonal regulation, mammary gland development and function is directed by para- and juxtacrine signaling among diverse cell-types, particularly the immune and mesenchymal populations. Precise mapping of the cellular landscape of the breast will help to decipher this complex coordination. Imaging of thin tissue sections has provided foundational information about cell positioning in the mammary gland and now technological advances in tissue clearing and subcellular-resolution 3D imaging are painting a more complete picture. In particular, confocal, light-sheet and multiphoton microscopy applied to intact tissue can fully capture cell morphology, position and interactions, and have the power to identify spatially rare events. This review will summarize our current understanding of mammary gland cellular organization as revealed by microscopy. We focus on the mouse mammary gland and cover a broad range of immune and stromal cell types at major developmental stages and give insights into important tissue niches and cellular interactions.

Background Heterogeneity within the mouse mammary epithelium and potential lineage relationships have been recently explored by single-cell RNA profiling. To further understand how cellular diversity changes during mammary ontogeny, we profiled single cells from nine different developmental stages spanning late embryogenesis, early postnatal, prepuberty, adult, mid-pregnancy, late-pregnancy, and post-involution, as well as the transcriptomes of micro-dissected terminal end buds (TEBs) and subtending ducts during puberty. Methods The single cell transcriptomes of 132,599 mammary epithelial cells from 9 different developmental stages were determined on the 10x Genomics Chromium platform, and integrative analyses were performed to compare specific time points. Results The mammary rudiment at E18.5 closely aligned with the basal lineage, while prepubertal epithelial cells exhibited lineage segregation but to a less differentiated state than their adult counterparts. Comparison of micro-dissected TEBs versus ducts showed that luminal cells within TEBs harbored intermediate expression profiles. Ductal basal cells exhibited increased chromatin accessibility of luminal genes compared to their TEB counterparts suggesting that lineage-specific chromatin is established within the subtending ducts during puberty. An integrative analysis of five stages spanning the pregnancy cycle revealed distinct stage-specific profiles and the presence of cycling basal, mixed-lineage, and 'late' alveolar intermediates in pregnancy. Moreover, a number of intermediates were uncovered along the basal-luminal progenitor cell axis, suggesting a continuum of alveolar-restricted progenitor states. Conclusions This extended single cell transcriptome atlas of mouse mammary epithelial cells provides the most complete coverage for mammary epithelial cells during morphogenesis to date. Together with chromatin accessibility analysis of TEB structures, it represents a valuable framework for understanding developmental decisions within the mouse mammary gland.

Multiphoton intravital imaging is essential for understanding cellular behavior and function in vivo. The adipose-rich environment of the mammary gland poses a unique challenge to in vivo microscopy due to light scattering that impedes high-resolution imaging. Here we provide a protocol for high-quality, six-color 3D intravital imaging of regions across the entire mouse mammary gland and associated tissues for several hours while maintaining tissue access for microdissection and labeling. An incision at the ventral midline and along the right hind leg creates a skin flap that is then secured to a raised platform skin side down. This allows for fluorescence-guided microdissection of connective tissue to provide unimpeded imaging of mammary ducts. A sealed imaging chamber over the skin flap creates a stable environment while maintaining access to large tissue regions for imaging with an upright microscope. We provide a strategy for imaging single cells and the tissue microenvironment utilizing multicolor Confetti lineage-tracing and additional dyes using custom-designed filters and sequential excitation with dual multiphoton lasers. Furthermore, we describe a strategy for simultaneous imaging and photomanipulation of single cells using the Olympus SIM scanner and provide steps for 3D video processing, visualization and high-dimensional analysis of single-cell behavior. We then provide steps for multiplexing intravital imaging with fixation, immunostaining, tissue clearing and 3D confocal imaging to associate cell behavior with protein expression. The skin-flap surgery and chamber preparation take 1.5 h, followed by up to 12 h of imaging. Applications range from basic filming in 1 d to 5 d for multiplexing and complex analysis. We present a protocol for long-term intravital imaging of mouse mammary tissue while maintaining tissue access using a skin flap and an imaging chamber. Strategies are provided for single-cell imaging, photomanipulation and multiplexed analysis.

Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental, and dynamic single-cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data from mouse models. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.

Distinct transcriptional states are maintained through organization of chromatin, resulting from the sum of numerous repressive and active histone modifications, into tightly packaged heterochromatin versus more accessible euchromatin. Polycomb repressive complex 2 (PRC2) is the main mammalian complex responsible for histone 3 lysine 27 trimethylation (H3K27me3) and is integral to chromatin organization. Using in vitro and in vivo studies, we show that deletion of Suz12, a core component of all PRC2 complexes, results in loss of H3K27me3 and H3K27 dimethylation (H3K27me2), completely blocks normal mammary gland development, and profoundly curtails progenitor activity in 3D organoid cultures. Through the application of mammary organoids to bypass the severe phenotype associated with Suz12 loss in vivo, we have explored gene expression and chromatin structure in wild-type and Suz12-deleted basal-derived organoids. Analysis of organoids led to the identification of lineage-specific changes in gene expression and chromatin structure, inferring cell type-specific PRC2-mediated gene silencing of the chromatin state. These expression changes were accompanied by cell cycle arrest but not lineage infidelity. Together, these data indicate that canonical PRC2 function is essential for development of the mammary gland through the repression of alternate transcription programs and maintenance of chromatin states.

Breast cancer is a heterogeneous disease that comprises multiple histological and molecular subtypes. To gain insight into mutations that drive breast tumorigenesis, we describe a pipeline for the identification and validation of tumor suppressor genes. Based on an in vivo genome‐wide CRISPR/Cas9 screen in Trp53+/– heterozygous mice, we identified tumor suppressor genes that included the scaffold protein Axin1, the protein kinase A regulatory subunit gene Prkar1a, as well as the proof‐of‐concept genes Pten, Nf1, and Trp53 itself. Ex vivo editing of primary mammary epithelial organoids was performed to further interrogate the roles of Axin1 and Prkar1a. Increased proliferation and profound changes in mammary organoid morphology were observed for Axin1/Trp53 and Prkar1a/Trp53 double mutants compared to Pten/Trp53 double mutants. Furthermore, direct in vivo genome editing via intraductal injection of lentiviruses engineered to express dual short‐guide RNAs revealed that mutagenesis of Trp53 and either Prkar1a, Axin1, or Pten markedly accelerated tumor development compared to Trp53‐only mutants. This proof‐of‐principle study highlights the application of in vivo CRISPR/Cas9 editing for uncovering cooperativity between defects in tumor suppressor genes that elicit mammary tumorigenesis. TP53 mutations occur frequently in breast cancer. Here, we describe a framework to identify novel tumor suppressor genes that cooperate with loss of Trp53 in mammary tumorigenesis using an in vivo genome‐wide CRISPR/Cas9 screen. Hits were validated through genetic editing of mammary epithelial organoids in vitro and direct editing of ductal cells in vivo using engineered lentiviruses.

Mutant isocitrate dehydrogenase 1 ( IDH1 ) is common in gliomas, and produces D-2-hydroxyglutarate (D-2-HG). The full effects of IDH1 mutations on glioma biology and tumor microenvironment are unknown. We analyzed a discovery cohort of 169 World Health Organization (WHO) grade II–IV gliomas, followed by a validation cohort of 148 cases, for IDH1 mutations, intratumoral microthrombi, and venous thromboemboli (VTE). 430 gliomas from The Cancer Genome Atlas were analyzed for mRNAs associated with coagulation, and 95 gliomas in a tissue microarray were assessed for tissue factor (TF) protein. In vitro and in vivo assays evaluated platelet aggregation and clotting time in the presence of mutant IDH1 or D-2-HG. VTE occurred in 26–30 % of patients with wild-type IDH1 gliomas, but not in patients with mutant IDH1 gliomas (0 %). IDH1 mutation status was the most powerful predictive marker for VTE, independent of variables such as GBM diagnosis and prolonged hospital stay. Microthrombi were far less common within mutant IDH1 gliomas regardless of WHO grade (85–90 % in wild-type versus 2–6 % in mutant), and were an independent predictor of IDH1 wild-type status. Among all 35 coagulation-associated genes, F3 mRNA, encoding TF, showed the strongest inverse relationship with IDH1 mutations. Mutant IDH1 gliomas had F3 gene promoter hypermethylation, with lower TF protein expression. D-2-HG rapidly inhibited platelet aggregation and blood clotting via a novel calcium-dependent, methylation-independent mechanism. Mutant IDH1 glioma engraftment in mice significantly prolonged bleeding time. Our data suggest that mutant IDH1 has potent antithrombotic activity within gliomas and throughout the peripheral circulation. These findings have implications for the pathologic evaluation of gliomas, the effect of altered isocitrate metabolism on tumor microenvironment, and risk assessment of glioma patients for VTE.

Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental, and dynamic single-cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data from mouse models. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.

Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering essential insights into cancer progression. This technique allows for the observation of single-cell behaviors within their natural 3D tissue environments, shedding light on how genetic and microenvironmental changes influence the complex dynamics of tumors. IVM generates highly complex datasets that often exceed the analytical capacity of traditional uni-parametric approaches, which can neglect single-cell heterogeneous in vivo behavior and limit insights into microenvironmental influences on cellular behavior. To overcome these limitations, we present BEHAV3D Tumor Profiler (BEHAV3D-TP), a computational framework that enables unbiased single-cell classification based on a range of morphological, environmental and dynamic single cell features. BEHAV3D-TP integrates with widely used 2D and 3D image processing pipelines, enabling researchers without advanced computational expertise to profile cancer and healthy cell dynamics in IVM data. Here, we apply BEHAV3D-TP to study diffuse midline glioma (DMG), a highly aggressive pediatric brain tumor characterized by invasive progression. By extending BEHAV3D-TP to incorporate tumor microenvironment (TME) data from IVM or fixed correlative imaging, we demonstrate that distinct migratory behaviors of DMG cells are associated with specific TME components, including tumor-associated macrophages and vasculature. BEHAV3D-TP enhances the accessibility of computational tools for analyzing the complex behaviors of cancer cells and their interactions with the TME in IVM data.