Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing

Feature selection followed by a novel residuals-based normalization that includes variance stabilization simplifies and improves single-cell gene expression analysis

Normalization is a crucial step in the analysis of single-cell RNA-sequencing (scRNA-seq) counts data. Its principal objectives are reduction of systematic biases primarily introduced through technical sources and transformation of counts to make them more amenable for the application of established statistical frameworks. In the standard workflows, normalization is followed by feature selection to identify highly variable genes (HVGs) that capture most of the biologically meaningful variation across the cells. Here, we make the case for a revised workflow by proposing a simple feature selection method and showing that we can perform feature selection before normalization by relying on observed counts. We highlight that the feature selection step can be used to not only select HVGs but to also identify stable genes. We further propose a novel variance stabilization transformation inclusive residuals-based normalization method that in fact relies on the stable genes to inform the reduction of systematic biases. We demonstrate significant improvements in downstream clustering analyses through the application of our proposed methods on biological truth-known as well as simulated counts datasets. We have implemented this novel workflow for analyzing high-throughput scRNA-seq data in an R package called Piccolo.

Expansion of mammary intraepithelial lymphocytes and intestinal inputs shape T cell dynamics in lactogenesis

Pregnancy brings about profound changes to the mammary gland in preparation for lactation. Changes in immunocyte populations that accompany this rapid remodeling are incompletely understood. We comprehensively analyzed mammary T cells through all parous stages, revealing a marked increase in CD4+ and CD8+ T effector cells in late pregnancy and lactation. T cell expansion was partly dependent on microbial signals and included an increase in TCRαβ+CD8αα+ cells with strong cytotoxic markers, located in the epithelium, that resemble intraepithelial lymphocytes of mucosal tissues. This relationship was substantiated by demonstrating T cell migration from gut to mammary gland in late pregnancy, by TCR clonotypes shared by intestine and mammary tissue in the same mouse, including intriguing gut TCR families. Putative counterparts of CD8αα+ IELs were found in human milk. Mammary T cells are thus poised to manage the transition from a non-mucosal tissue to a mucosal barrier during lactogenesis.

Archetypal clustering reveals physiological mechanisms linking milk yield and fertility in dairy cattle

Fertility in dairy cattle has declined as an unintended consequence of single-trait selection for high milk yield. The unfavorable genetic correlation between milk yield and fertility is now well documented; however, the underlying physiological mechanisms are still uncertain. To understand the relationship between these traits, we developed a method that clusters variants with similar patterns of effects and, after the integration of gene expression data, identifies the genes through which they are likely to act. Biological processes that are enriched in the genes of each cluster were then identified. We identified several clusters with unique patterns of effects. One of the clusters included variants associated with increased milk yield and decreased fertility, where the "archetypal" variant (i.e., the one with the largest effect) was associated with the GC gene, whereas others were associated with TRIM32, LRRK2, and U6-associated snRNA. These genes have been linked to transcription and alternative splicing, suggesting that these processes are likely contributors to the unfavorable relationship between the 2 traits. Another cluster, with archetypal variant near DGAT1 and including variants associated with CDH2, BTRC, SFRP2, ZFHX3, and SLITRK5, appeared to affect milk yield but have little effect on fertility. These genes have been linked to insulin, adipose tissue, and energy metabolism. A third cluster with archetypal variant near ZNF613 and including variants associated with ROBO1, EFNA5, PALLD, GPC6, and PTPRT were associated with fertility but not milk yield. These genes have been linked to GnRH neuronal migration, embryonic development, or ovarian function. The use of archetypal clustering to group variants with similar patterns of effects may assist in identifying the biological processes underlying correlated traits. The method is hypothesis generating and requires experimental confirmation. However, we have uncovered several novel mechanisms potentially affecting milk production and fertility such as GnRH neuronal migration. We anticipate our method to be a starting point for experimental research into novel pathways, which have been previously unexplored within the context of dairy production.

Targeting Tumor Heterogeneity by Breaking a Stem Cell and Epithelial Niche Interaction Loop

Tumor heterogeneity, the presence of multiple distinct subpopulations of cancer cells between patients or among the same tumors, poses a major challenge to current targeted therapies. The way these different subpopulations interact among themselves and the stromal niche environment, and how such interactions affect cancer stem cell behavior has remained largely unknown. Here, it is shown that an FGF-BMP7-INHBA signaling positive feedback loop integrates interactions among different cell populations, including mammary gland stem cells, luminal epithelial and stromal fibroblast niche components not only in organ regeneration but also, with certain modifications, in cancer progression. The reciprocal dependence of basal stem cells and luminal epithelium is based on basal-derived BMP7 and luminal-derived INHBA, which promote their respective expansion, and is regulated by stromal-epithelial FGF signaling. Targeting this interaction loop, for example, by reducing the function of one or more of its components, inhibits organ regeneration and breast cancer progression. The results have profound implications for overcoming drug resistance because of tumor heterogeneity in future targeted therapies.

Clustering single-cell RNA sequencing data via iterative smoothing and self-supervised discriminative embedding

Single-cell transcriptome sequencing (scRNA-seq) is a high-throughput technique used to study gene expression at the single-cell level. Clustering analysis is a commonly used method in scRNA-seq data analysis, helping researchers identify cell types and uncover interactions between cells. However, the choice of a robust similarity metric in the clustering procedure is still an open challenge due to the complex underlying structures of the data and the inherent noise in data acquisition. Here, we propose a deep clustering method for scRNA-seq data called scRISE (scRNA-seq Iterative Smoothing and self-supervised discriminative Embedding model) to resolve this challenge. The model consists of two main modules: an iterative smoothing module based on graph autoencoders designed to denoise the data and refine the pairwise similarity in turn to gradually incorporate cell structural features and enrich the data information; and a self-supervised discriminative embedding module with adaptive similarity threshold for partitioning samples into correct clusters. Our approach has shown improved quality of data representation and clustering on seventeen scRNA-seq datasets against a number of state-of-the-art deep learning clustering methods. Furthermore, utilizing the scRISE method in biological analysis against the HNSCC dataset has unveiled 62 informative genes, highlighting their potential roles as therapeutic targets and biomarkers.

Transcriptomic Analysis of Pubertal and Adult Virgin Mouse Mammary Epithelial and Stromal Cell Populations

Conflicting data exist as to how mammary epithelial cell proliferation changes during the reproductive cycle. To study the effect of endogenous hormone fluctuations on gene expression in the mouse mammary gland, we performed bulk RNAseq analyses of epithelial and stromal cell populations that were isolated either during puberty or at different stages of the adult virgin estrous cycle. Our data confirm prior findings that proliferative changes do not occur in every mouse in every cycle. We also show that during the estrous cycle the main gene expression changes occur in adipocytes and fibroblasts. Finally, we present a comprehensive overview of the Wnt gene expression landscape in different mammary gland cell types in pubertal and adult mice. This work contributes to understanding the effects of physiological hormone fluctuations and locally produced signaling molecules on gene expression changes in the mammary gland during the reproductive cycle and should be a useful resource for future studies investigating gene expression patterns in different cell types across different developmental timepoints.

scVIC: deep generative modeling of heterogeneity for scRNA-seq data

Motivation

Single-cell RNA sequencing (scRNA-seq) has become a valuable tool for studying cellular heterogeneity. However, the analysis of scRNA-seq data is challenging because of inherent noise and technical variability. Existing methods often struggle to simultaneously explore heterogeneity across cells, handle dropout events, and account for batch effects. These drawbacks call for a robust and comprehensive method that can address these challenges and provide accurate insights into heterogeneity at the single-cell level.

Results

In this study, we introduce scVIC, an algorithm designed to account for variational inference, while simultaneously handling biological heterogeneity and batch effects at the single-cell level. scVIC explicitly models both biological heterogeneity and technical variability to learn cellular heterogeneity in a manner free from dropout events and the bias of batch effects. By leveraging variational inference, we provide a robust framework for inferring the parameters of scVIC. To test the performance of scVIC, we employed both simulated and biological scRNA-seq datasets, either including, or not, batch effects. scVIC was found to outperform other approaches because of its superior clustering ability and circumvention of the batch effects problem.

Availability and implementation

The code of scVIC and replication for this study are available at https://github.com/HiBearME/scVIC/tree/v1.0.

Cyclical heat stress during lactation influences the microstructure of the bovine mammary gland

This study aimed to evaluate the impact of heat stress on mammary epithelial cell (MEC) losses into milk, secretory mammary tissue structure, and mammary epithelial cell activity. Sixteen multiparous Holstein cows (632 ± 12 kg BW) approximately 100 d in milk housed in climate-controlled rooms were paired by body weight and randomly allocated to one of 2 treatments, heat stress (HS) or pair feeding thermoneutral (PFTN) using 2 cohorts. Each cohort was subjected to 2 periods of 4 d each. In period 1, both treatments had ad libitum access to a common total mixed ration and were exposed to a controlled daily temperature-humidity index (THI) of 64. In period 2, HS cows were exposed to controlled cyclical heat stress (THI: 74 to 80), while PFTN cows remained at 64 THI and daily dry matter intake was matched to HS. Cows were milked twice daily, and milk yield was recorded at each milking. Individual milk samples on the last day of each period were used to quantify MEC losses by flow cytometry using butyrophilin as a cell surface marker. On the final day of period 2, individual bovine mammary tissue samples were obtained for histomorphology analysis, assessment of protein abundance, and evaluation of gene expression of targets associated with cellular capacity for milk and milk component synthesis, heat response, cellular proliferation, and autophagy. Statistical analysis was performed using the GLIMMIX procedure of SAS. Milk yield was reduced by 4.3 kg by HS (n = 7) compared with PFTN (n = 8). Independent of treatment, MEC in milk averaged 174 cells/mL (2.9% of total cells). There was no difference between HS vs. PFTN cows for MEC shed or concentration in milk. Alveolar area was reduced 25% by HS, and HS had 4.1 more alveoli than PFTN. Total number of nucleated MEC per area were greater in HS (389 ± 1.05) compared with PFTN (321 ± 1.05); however, cell number per alveolus was similar between groups (25 ± 1.5 vs. 26 ± 1.4). There were no differences in relative fold expression for GLUT1, GLUT8, CSN2, CSN3, LALBA, FASN, HSPA5, and HSPA8 in HS compared with PFTN. Immunoblotting analyses showed a decrease abundance for phosphorylated STAT5 and S6K1, and an increase in LC3 II in HS compared with PFTN. These results suggest that even if milk yield differences and histological changes occur in the bovine mammary gland after 4 d of heat exposure, MEC loss into milk, nucleated MEC number per alveolus, and gene expression of nutrient transport, milk component synthesis, and heat stress related targets are unaffected. In contrast, the abundance of proteins related to protein synthesis and cell survival decreased significantly, while an upregulation of proteins associated with autophagy in HS compared with PFTN.

FGD5 in basal cells induces CXCL14 secretion that initiates a feedback loop to promote murine mammary epithelial growth and differentiation

The interactions of environmental compartments with epithelial cells are essential for mammary gland development and homeostasis. Currently, the direct crosstalk between the endothelial niche and mammary epithelial cells remains poorly understood. Here, we show that faciogenital dysplasia 5 (FGD5) is enriched in mammary basal cells (BCs) and mediates critical interactions between basal and endothelial cells (ECs) in the mammary gland. Conditional deletion of Fgd5 reduced, whereas conditional knockin of Fgd5 increased, the engraftment and expansion of BCs, regulating ductal morphogenesis in the mammary gland. Mechanistically, murine mammary BC-expressed FGD5 inhibited the transcriptional activity of activating transcription factor 3 (ATF3), leading to subsequent transcriptional activation and secretion of CXCL14. Furthermore, activation of CXCL14/CXCR4/ERK signaling in primary murine mammary stromal ECs enhanced the expression of HIF-1α-regulated hedgehog ligands, which initiated a positive feedback loop to promote the function of BCs. Collectively, these findings identify functionally important interactions between BCs and the endothelial niche that occur through the FGD5/CXCL14/hedgehog axis.

scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

In droplet-based single-cell and single-nucleus RNA-seq assays, systematic contamination of ambient RNA molecules biases the quantification of gene expression levels. Existing methods correct the contamination for all genes globally. However, there lacks specific evaluation of correction efficacy for varying contamination levels. Here, we show that DecontX and CellBender under-correct highly contaminating genes, while SoupX and scAR over-correct lowly/non-contaminating genes. Here, we develop scCDC as the first method to detect the contamination-causing genes and only correct expression levels of these genes, some of which are cell-type markers. Compared with existing decontamination methods, scCDC excels in decontaminating highly contaminating genes while avoiding over-correction of other genes.

ABCD4 is associated with mammary gland development in mammals

BACKGROUND

Mammary gland development is a critical process in mammals, crucial for their reproductive success and offspring nourishment. However, the functional roles of key candidate genes associated with teat number, including ABCD4, VRTN, PROX2, and DLST, in this developmental process remain elusive. To address this gap in knowledge, we conducted an in-depth investigation into the dynamic expression patterns, functional implications, and regulatory networks of these candidate genes during mouse mammary gland development.

RESULTS

In this study, the spatial and temporal patterns of key genes were characterized in mammary gland development. Using time-series single-cell data, we uncovered differences in the expression of A bcd4, Vrtn, Prox2, and Dlst in cell population of the mammary gland during embryonic and adult stages, while Vrtn was not detected in any cells. We found that only overexpression and knockdown of Abcd4 could inhibit proliferation and promote apoptosis of HC11 mammary epithelial cells, whereas Prox2 and Dlst had no significant effect on these cells. Using RNA-seq and qPCR, further analysis revealed that Abcd4 can induce widespread changes in the expression levels of genes involved in mammary gland development, such as Igfbp3, Ccl5, Tlr2, and Prlr, which were primarily associated with the MAPK, JAK-STAT, and PI3K-AKT pathways by functional enrichment.

CONCLUSIONS

These findings revealed ABCD4 as a candidate gene pivotal for regulating mammary gland development and lactation during pregnancy by influencing PRLR expression.

Ehf controls mammary alveolar lineage differentiation and is a putative suppressor of breast tumorigenesis

The transcription factor EHF is highly expressed in the lactating mammary gland, but its role in mammary development and tumorigenesis is not fully understood. Utilizing a mouse model of Ehf deletion, herein, we demonstrate that loss of Ehf impairs mammary lobuloalveolar differentiation at late pregnancy, indicated by significantly reduced levels of milk genes and milk lipids, fewer differentiated alveolar cells, and an accumulation of alveolar progenitor cells. Further, deletion of Ehf increased proliferative capacity and attenuated prolactin-induced alveolar differentiation in mammary organoids. Ehf deletion also increased tumor incidence in the MMTV-PyMT mammary tumor model and increased the proliferative capacity of mammary tumor organoids, while low EHF expression was associated with higher tumor grade and poorer outcome in luminal A and basal human breast cancers. Collectively, these findings establish EHF as a non-redundant regulator of mammary alveolar differentiation and a putative suppressor of mammary tumorigenesis.

Feature selection followed by a novel residuals-based normalization simplifies and improves single-cell gene expression analysis

Normalization is a crucial step in the analysis of single-cell RNA-sequencing (scRNA-seq) counts data. Its principal objectives are to reduce the systematic biases primarily introduced through technical sources and to transform the data to make it more amenable for application of established statistical frameworks. In the standard workflows, normalization is followed by feature selection to identify highly variable genes (HVGs) that capture most of the biologically meaningful variation across the cells. Here, we make the case for a revised workflow by proposing a simple feature selection method and showing that we can perform feature selection before normalization by relying on observed counts. We highlight that the feature selection step can be used to not only select HVGs but to also identify stable genes. We further propose a novel variance stabilization transformation inclusive residuals-based normalization method that in fact relies on the stable genes to inform the reduction of systematic biases. We demonstrate significant improvements in downstream clustering analyses through the application of our proposed methods on biological truth-known as well as simulated counts datasets. We have implemented this novel workflow for analyzing high-throughput scRNA-seq data in an R package called Piccolo.

TRPS1 maintains luminal progenitors in the mammary gland by repressing SRF/MRTF activity

The transcription factor TRPS1 is a context-dependent oncogene in breast cancer. In the mammary gland, TRPS1 activity is restricted to the luminal population and is critical during puberty and pregnancy. Its function in the resting state remains however unclear. To evaluate whether it could be a target for cancer therapy, we investigated TRPS1 function in the healthy adult mammary gland using a conditional ubiquitous depletion mouse model where long-term depletion does not affect fitness. Using transcriptomic approaches, flow cytometry and functional assays, we show that TRPS1 activity is essential to maintain a functional luminal progenitor compartment. This requires the repression of both YAP/TAZ and SRF/MRTF activities. TRPS1 represses SRF/MRTF activity indirectly by modulating RhoA activity. Our work uncovers a hitherto undisclosed function of TRPS1 in luminal progenitors intrinsically linked to mechanotransduction in the mammary gland. It may also provide new insights into the oncogenic functions of TRPS1 as luminal progenitors are likely the cells of origin of many breast cancers.

Protein Dynamic Landscape during Mouse Mammary Gland Development from Virgin to Pregnant, Lactating, and Involuting Stages

The mammary gland undergoes significant physiological changes as it undergoes a transition from virgin to pregnancy, lactation, and involution. However, the dynamic role of proteins in regulating these processes during mouse mammary gland development has not been thoroughly explored. In this study, we collected mouse mammary gland tissues from mature virgins aged 8-10 weeks (V), day 16 of pregnancy (P16d), day 12 of lactation (L12d), day 1 of forced weaning (FW 1d), and day 3 of forced weaning (FW 3d) stages for analysis using DIA-based quantitative proteomics technology. A total of 3,312 proteins were identified, of which 843 were DAPs that were categorized into nine clusters based on their abundance changes across developmental stages. Notably, DAPs in cluster 2, which peaked at the L12d stage, were primarily associated with mammary gland development and lactation. The protein-protein interaction network revealed that the epidermal growth factor (EGF) was central to this cluster. Our study provides a comprehensive overview of the mouse mammary gland development proteome and identifies some important proteins, such as EGF, Janus kinase 1 (JAK1), and signal transducer and activator of transcription 6 (STAT6) that may serve as potential targets for future research to provide guidelines for a deeper understanding of the developmental biology of mammary glands.

A single-cell atlas enables mapping of homeostatic cellular shifts in the adult human breast

Here we use single-cell RNA sequencing to compile a human breast cell atlas assembled from 55 donors that had undergone reduction mammoplasties or risk reduction mastectomies. From more than 800,000 cells we identified 41 cell subclusters across the epithelial, immune and stromal compartments. The contribution of these different clusters varied according to the natural history of the tissue. Age, parity and germline mutations, known to modulate the risk of developing breast cancer, affected the homeostatic cellular state of the breast in different ways. We found that immune cells from BRCA1 or BRCA2 carriers had a distinct gene expression signature indicative of potential immune exhaustion, which was validated by immunohistochemistry. This suggests that immune-escape mechanisms could manifest in non-cancerous tissues very early during tumor initiation. This atlas is a rich resource that can be used to inform novel approaches for early detection and prevention of breast cancer.

Mcam stabilizes luminal progenitor breast cancer phenotypes via Ck2 control and Src/Akt/Stat3 attenuation

Breast cancers are categorized into subtypes with distinctive therapeutic vulnerabilities and prognoses based on their expression of clinically targetable receptors and gene expression patterns mimicking different cell types of the normal gland. Here, we tested the role of Mcam in breast cancer cell state control and tumorigenicity in a luminal progenitor-like murine tumor cell line (Py230) that exhibits lineage and tumor subtype plasticity. Mcam knockdown Py230 cells show augmented Stat3 and Pi3K/Akt activation associated with a lineage state switch away from a hormone-sensing/luminal progenitor state toward alveolar and basal cell related phenotypes that were refractory to growth inhibition by the anti-estrogen therapeutic, tamoxifen. Inhibition of Stat3, or the upstream activator Ck2, reversed these cell state changes. Mcam binds Ck2 and acts as a regulator of Ck2 substrate utilization across multiple mammary tumor cell lines. In Py230 cells this activity manifests as increased mesenchymal morphology, migration, and Src/Fak/Mapk/Paxillin adhesion complex signaling in vitro, in contrast to Mcam's reported roles in promoting mesenchymal phenotypes. In vivo, Mcam knockdown reduced tumor growth and take rate and inhibited cell state transition to Sox10+/neural crest like cells previously been associated with tumor aggressiveness. This contrasts with human luminal breast cancers where MCAM copy number loss is highly coupled to Cyclin D amplification, increased proliferation, and the more aggressive Luminal B subtype. Together these data indicate a critical role for Mcam and its regulation of Ck2 in control of breast cancer cell state plasticity with implications for progression, evasion of targeted therapies and combination therapy design.

A Single-Cell Transcriptome of Bovine Milk Somatic Cells

The production of milk by dairy cows far exceeds the nutritional needs of the calf and is vital for the economical use of dairy cattle. High milk yield is a unique production trait that can be effectively enhanced through traditional selection methods. The process of lactation in cows serves as an excellent model for studying the biological aspects of lactation with the aim of exploring the mechanistic base of this complex trait at the cellular level. In this study, we analyzed the milk transcriptome at the single-cell level by conducting scRNA-seq analysis on milk samples from two Holstein Friesian cows at mid-lactation (75 and 93 days) using the 10× Chromium platform. Cells were pelleted and fat was removed from milk by centrifugation. The cell suspension from each cow was loaded on separate channels, resulting in the recovery of 9313 and 14,544 cells. Library samples were loaded onto two lanes of the NovaSeq 6000 (Illumina) instrument. After filtering at the cell and gene levels, a total of 7988 and 13,973 cells remained, respectively. We were able to reconstruct different cell types (milk-producing cells, progenitor cells, macrophages, monocytes, dendritic cells, T cells, B cells, mast cells, and neutrophils) in bovine milk. Our findings provide a valuable resource for identifying regulatory elements associated with various functions of the mammary gland such as lactation, tissue renewal, native immunity, protein and fat synthesis, and hormonal response.

Single-Cell Transcription Mapping of Murine and Human Mammary Organoids Responses to Female Hormones

During female adolescence and pregnancy, rising levels of hormones result in a cyclic source of signals that control the development of mammary tissue. While such alterations are well understood from a whole-gland perspective, the alterations that such hormones bring to organoid cultures derived from mammary glands have yet to be fully mapped. This is of special importance given that organoids are considered suitable systems to understand cross species breast development. Here we utilized single-cell transcriptional profiling to delineate responses of murine and human normal breast organoid systems to female hormones across evolutionary distinct species. Collectively, our study represents a molecular atlas of epithelial dynamics in response to estrogen and pregnancy hormones.

PAPAS promotes differentiation of mammary epithelial cells and suppresses breast carcinogenesis

Extensive remodeling of the female mammary epithelium during development and pregnancy has been linked to cancer susceptibility. The faithful response of mammary epithelial cells (MECs) to hormone signaling is key to avoiding breast cancer development. Here, we show that lactogenic differentiation of murine MECs requires silencing of genes encoding ribosomal RNA (rRNA) by the antisense transcript PAPAS. Accordingly, knockdown of PAPAS derepresses rRNA genes, attenuates the response to lactogenic hormones, and induces malignant transformation. Restoring PAPAS levels in breast cancer cells reduces tumorigenicity and lung invasion and activates many interferon-regulated genes previously linked to metastasis suppression. Mechanistically, PAPAS transcription depends on R-loop formation at the 3' end of rRNA genes, which is repressed by RNase H1 and replication protein A (RPA) overexpression in breast cancer cells. Depletion of PAPAS and upregulation of RNase H1 and RPA in human breast cancer underpin the clinical relevance of our findings.

Tristetraprolin promotes survival of mammary progenitor cells by restraining TNFα levels

Tristetraprolin (TTP) is an RNA binding protein that destabilizes mRNAs of factors involved in proliferation, invasiveness, and inflammation. Disruption of the gene that codes for TTP (Zfp36) led to severe arthritis, autoimmunity, cachexia and dermatitis in mice. It has been shown that these phenotypes were mostly due to excessive TNFα levels in the affected tissues. We have previously reported that TTP expression is required for lactation maintenance. Our results indicated that conditional MG TTP-KO female mice displayed early involution due to the untimely induction of pro-inflammatory pathways led mostly by TNFα overexpression. Here we show that reducing TTP levels not only affects the fully differentiated mammary gland, but also harms morphogenesis of this tissue by impairing the progenitor cell population. We found that Zfp36 expression is linked to mammary stemness in human and mice. In addition, diminishing TTP expression and activity induced apoptosis of stem-like mouse mammary cells, reduced its ability to form mammospheres in culture and to develop into complete glands when implanted into cleared mammary fat pads in vivo. Our results show that survival of the stem-like cells is compromised by increased levels of inflammatory cytokines and stimulation of signaling cascades involving NFκB, STAT3 and MAPK-p38 activation. Moreover, TNFα overexpression and the consequent p38 phosphorylation would be the leading cause of progenitor cell death upon TTP expression restriction. Taken together, our results reveal the relevance of TTP for the maintenance of the mammary progenitor cell compartment by maintaining local TNFα levels at bay.

Fatty acid amide hydrolase drives adult mammary gland development by promoting luminal cell differentiation

Mammary gland development occurs primarily in adulthood, undergoing extensive expansion during puberty followed by cycles of functional specialization and regression with every round of pregnancy/lactation/involution. This process is ultimately driven by the coordinated proliferation and differentiation of mammary epithelial cells. However, the endogenous molecular factors regulating these developmental dynamics are still poorly defined. Endocannabinoid signaling is known to determine cell fate-related events during the development of different organs in the central nervous system and the periphery. Here, we report that the endocannabinoid-degrading enzyme fatty acid amide hydrolase (FAAH) plays a pivotal role in adult mammary gland development. Specifically, it is required for luminal lineage specification in the mammary gland, and it promotes hormone-driven secretory differentiation of mammary epithelial cells by controlling the endogenous levels of anandamide and the subsequent activation of cannabinoid CB1 receptors. Together, our findings shed light on the role of the endocannabinoid system in breast development and point to FAAH as a therapeutic target in milk-production deficits.

Signaling Pathway Alterations Driven by BRCA1 and BRCA2 Germline Mutations are Sufficient to Initiate Breast Tumorigenesis by the PIK3CAH1047R Oncogene

Single-cell transcriptomics studies have begun to identify breast epithelial cell and stromal cell specific transcriptome differences between BRCA1/2 mutation carriers and non-carriers. We generated a single-cell transcriptome atlas of breast tissues from BRCA1, BRCA2 mutation carriers and compared this single-cell atlas of mutation carriers with our previously described single-cell breast atlas of healthy non-carriers. We observed that BRCA1 but not BRCA2 mutations altered the ratio between basal (basal-myoepithelial), luminal progenitor (luminal adaptive secretory precursor, LASP), and mature luminal (luminal hormone sensing) cells in breast tissues. A unique subcluster of cells within LASP cells is underrepresented in case of BRCA1 and BRCA2 mutation carriers compared with non-carriers. Both BRCA1 and BRCA2 mutations specifically altered transcriptomes in epithelial cells which are an integral part of NFκB, LARP1, and MYC signaling. Signaling pathway alterations in epithelial cells unique to BRCA1 mutations included STAT3, BRD4, SMARCA4, HIF2A/EPAS1, and Inhibin A signaling. BRCA2 mutations were associated with upregulation of IL6, PDK1, FOXO3, and TNFSF11 signaling. These signaling pathway alterations are sufficient to alter sensitivity of BRCA1/BRCA2-mutant breast epithelial cells to transformation as epithelial cells from BRCA1 mutation carriers overexpressing hTERT + PIK3CAH1047R generated adenocarcinomas, whereas similarly modified mutant BRCA2 cells generated basal carcinomas in NSG mice. Thus, our studies provide a high-resolution transcriptome atlas of breast epithelial cells of BRCA1 and BRCA2 mutation carriers and reveal their susceptibility to PIK3CA mutation-driven transformation.

SIGNIFICANCE

This study provides a single-cell atlas of breast tissues of BRCA1/2 mutation carriers and demonstrates that aberrant signaling due to BRCA1/2 mutations is sufficient to initiate breast cancer by mutant PIK3CA.

Mechanosensitive hormone signaling promotes mammary progenitor expansion and breast cancer risk

Tissue stem-progenitor cell frequency has been implicated in tumor risk and progression, but tissue-specific factors linking these associations remain ill-defined. We observed that stiff breast tissue from women with high mammographic density, who exhibit increased lifetime risk for breast cancer, associates with abundant stem-progenitor epithelial cells. Using genetically engineered mouse models of elevated integrin mechanosignaling and collagen density, syngeneic manipulations, and spheroid models, we determined that a stiff matrix and high mechanosignaling increase mammary epithelial stem-progenitor cell frequency and enhance tumor initiation in vivo. Augmented tissue mechanics expand stemness by potentiating extracellular signal-related kinase (ERK) activity to foster progesterone receptor-dependent RANK signaling. Consistently, we detected elevated phosphorylated ERK and progesterone receptors and increased levels of RANK signaling in stiff breast tissue from women with high mammographic density. The findings link fibrosis and mechanosignaling to stem-progenitor cell frequency and breast cancer risk and causally implicate epidermal growth factor receptor-ERK-dependent hormone signaling in this phenotype.

scMAE: a masked autoencoder for single-cell RNA-seq clustering

MOTIVATION

Single-cell RNA sequencing has emerged as a powerful technology for studying gene expression at the individual cell level. Clustering individual cells into distinct subpopulations is fundamental in scRNA-seq data analysis, facilitating the identification of cell types and exploration of cellular heterogeneity. Despite the recent development of many deep learning-based single-cell clustering methods, few have effectively exploited the correlations among genes, resulting in suboptimal clustering outcomes.

RESULTS

Here, we propose a novel masked autoencoder-based method, scMAE, for cell clustering. scMAE perturbs gene expression and employs a masked autoencoder to reconstruct the original data, learning robust and informative cell representations. The masked autoencoder introduces a masking predictor, which captures relationships among genes by predicting whether gene expression values are masked. By integrating this masking mechanism, scMAE effectively captures latent structures and dependencies in the data, enhancing clustering performance. We conducted extensive comparative experiments using various clustering evaluation metrics on 15 scRNA-seq datasets from different sequencing platforms. Experimental results indicate that scMAE outperforms other state-of-the-art methods on these datasets. In addition, scMAE accurately identifies rare cell types, which are challenging to detect due to their low abundance. Furthermore, biological analyses confirm the biological significance of the identified cell subpopulations.

AVAILABILITY AND IMPLEMENTATION

The source code of scMAE is available at: https://zenodo.org/records/10465991.

Mcam inhibits macrophage-mediated development of mammary gland through non-canonical Wnt signaling

While canonical Wnt signaling is well recognized for its crucial regulatory functions in cell fate decisions, the role of non-canonical Wnt signaling in adult stem cells remains elusive and contradictory. Here, we identified Mcam, a potential member of the non-canonical Wnt signaling, as an important negative regulator of mammary gland epithelial cells (MECs) by genome-scale CRISPR-Cas9 knockout (GeCKO) library screening. Loss of Mcam increases the clonogenicity and regenerative capacity of MECs, and promotes the proliferation, differentiation, and ductal morphogenesis of mammary epithelial in knockout mice. Mechanically, Mcam knockout recruits and polarizes macrophages through the Il4-Stat6 axis, thereby promoting secretion of the non-canonical Wnt ligand Wnt5a and its binding to the non-canonical Wnt signaling receptor Ryk to induce the above phenotypes. These findings reveal Mcam roles in mammary gland development by orchestrating communications between MECs and macrophages via a Wnt5a/Ryk axis, providing evidences for non-canonical Wnt signaling in mammary development.

Redox and metabolic reprogramming in breast cancer and cancer-associated adipose tissue

Redox and metabolic processes are tightly coupled in both physiological and pathological conditions. In cancer, their integration occurs at multiple levels and is characterized by synchronized reprogramming both in the tumor tissue and its specific but heterogeneous microenvironment. In breast cancer, the principal microenvironment is the cancer-associated adipose tissue (CAAT). Understanding how the redox-metabolic reprogramming becomes coordinated in human breast cancer is imperative both for cancer prevention and for the establishment of new therapeutic approaches. This review aims to provide an overview of the current knowledge of the redox profiles and regulation of intermediary metabolism in breast cancer while considering the tumor and CAAT of breast cancer as a unique Warburg's pseudo-organ. As cancer is now recognized as a systemic metabolic disease, we have paid particular attention to the cell-specific redox-metabolic reprogramming and the roles of estrogen receptors and circadian rhythms, as well as their crosstalk in the development, growth, progression, and prognosis of breast cancer.

Notch1 cortical signaling regulates epithelial architecture and cell-cell adhesion

Notch receptors control tissue morphogenic processes that involve coordinated changes in cell architecture and gene expression, but how a single receptor can produce these diverse biological outputs is unclear. Here, we employ a 3D model of a human ductal epithelium to reveal tissue morphogenic defects result from loss of Notch1, but not Notch1 transcriptional signaling. Instead, defects in duct morphogenesis are driven by dysregulated epithelial cell architecture and mitogenic signaling which result from the loss of a transcription-independent, Notch1 cortical signaling mechanism that ultimately functions to stabilize adherens junctions and cortical actin. We identify that Notch1 localization and cortical signaling are tied to apical-basal cell restructuring and discover that a Notch1-FAM83H interaction underlies control of epithelial adherens junctions and cortical actin. Together, these results offer new insights into Notch1 signaling and regulation and advance a paradigm in which transcriptional and cell adhesive programs might be coordinated by a single receptor.

Molecular complexity of mammary glands development: a review of lactogenic differentiation in epithelial cells

The mammary gland is a dynamic organ with various physiological processes like cellular proliferation, differentiation, and apoptosis during the pregnancy-lactation-involution cycle. It is essential to understand the molecular changes during the lactogenic differentiation of mammary epithelial cells (MECs, the milk-synthesizing cells). The MECs are organized as luminal milk-secreting cells and basal myoepithelial cells (responsible for milk ejection by contraction) that form the alveoli. The branching morphogenesis and lactogenic differentiation of the MECs prepare the gland for lactation. This process is governed by many molecular mediators including hormones, growth factors, cytokines, miRNAs, regulatory proteins, etc. Interestingly, various signalling pathways guide lactation and understanding these molecular transitions from pregnancy to lactation will help researchers design further research. Manipulation of genes responsible for milk synthesis and secretion will promote augmentation of milk yield in dairy animals. Identifying protein signatures of lactation will help develop strategies for persistent lactation and shortening the dry period in farm animals. The present review article discusses in details the physiological and molecular changes occurring during lactogenic differentiation of MECs and the associated hormones, regulatory proteins, miRNAs, and signalling pathways. An in-depth knowledge of the molecular events will aid in developing engineered cellular models for studies related to mammary gland diseases of humans and animals.

Cellular Plasticity in Mammary Gland Development and Breast Cancer

Cellular plasticity is a phenomenon where cells adopt different identities during development and tissue homeostasis as a response to physiological and pathological conditions. This review provides a general introduction to processes by which cells change their identity as well as the current definition of cellular plasticity in the field of mammary gland biology. Following a synopsis of the evolving model of the hierarchical development of mammary epithelial cell lineages, we discuss changes in cell identity during normal mammary gland development with particular emphasis on the effect of the gestation cycle on the emergence of new cellular states. Next, we summarize known mechanisms that promote the plasticity of epithelial lineages in the normal mammary gland and highlight the importance of the microenvironment and extracellular matrix. A discourse of cellular reprogramming during the early stages of mammary tumorigenesis that follows focuses on the origin of basal-like breast cancers from luminal progenitors and oncogenic signaling networks that orchestrate diverse developmental trajectories of transforming epithelial cells. In addition to the epithelial-to-mesenchymal transition, we highlight events of cellular reprogramming during breast cancer progression in the context of intrinsic molecular subtype switching and the genesis of the claudin-low breast cancer subtype, which represents the far end of the spectrum of epithelial cell plasticity. In the final section, we will discuss recent advances in the design of genetically engineered models to gain insight into the dynamic processes that promote cellular plasticity during mammary gland development and tumorigenesis in vivo.

FXYD3 functionally demarcates an ancestral breast cancer stem cell subpopulation with features of drug-tolerant persisters

The heterogeneity of cancer stem cells (CSCs) within tumors presents a challenge in therapeutic targeting. To decipher the cellular plasticity that fuels phenotypic heterogeneity, we undertook single-cell transcriptomics analysis in triple-negative breast cancer (TNBC) to identify subpopulations in CSCs. We found a subpopulation of CSCs with ancestral features that is marked by FXYD domain-containing ion transport regulator 3 (FXYD3), a component of the Na+/K+ pump. Accordingly, FXYD3+ CSCs evolve and proliferate, while displaying traits of alveolar progenitors that are normally induced during pregnancy. Clinically, FXYD3+ CSCs were persistent during neoadjuvant chemotherapy, hence linking them to drug-tolerant persisters (DTPs) and identifying them as crucial therapeutic targets. Importantly, FXYD3+ CSCs were sensitive to senolytic Na+/K+ pump inhibitors, such as cardiac glycosides. Together, our data indicate that FXYD3+ CSCs with ancestral features are drivers of plasticity and chemoresistance in TNBC. Targeting the Na+/K+ pump could be an effective strategy to eliminate CSCs with ancestral and DTP features that could improve TNBC prognosis.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Single-cell and spatial analyses reveal a tradeoff between murine mammary proliferation and lineage programs associated with endocrine cues

Although distinct epithelial cell types have been distinguished in glandular tissues such as the mammary gland, the extent of heterogeneity within each cell type and the degree of endocrine control of this diversity across development are incompletely understood. By combining mass cytometry and cyclic immunofluorescence, we define a rich array of murine mammary epithelial cell subtypes associated with puberty, the estrous cycle, and sex. These subtypes are differentially proliferative and spatially segregate distinctly in adult versus pubescent glands. Further, we identify systematic suppression of lineage programs at the protein and RNA levels as a common feature of mammary epithelial expansion during puberty, the estrous cycle, and gestation and uncover a pervasive enrichment of ribosomal protein genes in luminal cells elicited specifically during progesterone-dominant expansionary periods. Collectively, these data expand our knowledge of murine mammary epithelial heterogeneity and connect endocrine-driven epithelial expansion with lineage suppression.

Comprehensive single cell aging atlas of mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer

Aging is the greatest risk factor for breast cancer; however, how age-related cellular and molecular events impact cancer initiation is unknown. We investigate how aging rewires transcriptomic and epigenomic programs of mouse mammary glands at single cell resolution, yielding a comprehensive resource for aging and cancer biology. Aged epithelial cells exhibit epigenetic and transcriptional changes in metabolic, pro-inflammatory, or cancer-associated genes. Aged stromal cells downregulate fibroblast marker genes and upregulate markers of senescence and cancer-associated fibroblasts. Among immune cells, distinct T cell subsets (Gzmk+, memory CD4+, γδ) and M2-like macrophages expand with age. Spatial transcriptomics reveal co-localization of aged immune and epithelial cells in situ. Lastly, transcriptional signatures of aging mammary cells are found in human breast tumors, suggesting mechanistic links between aging and cancer. Together, these data uncover that epithelial, immune, and stromal cells shift in proportions and cell identity, potentially impacting cell plasticity, aged microenvironment, and neoplasia risk.

Kindlin-2 in myoepithelium controls luminal progenitor commitment to alveoli in mouse mammary gland

Myoepithelium plays an important role in mammary gland development, but less is known about the molecular mechanism underlying how myoepithelium controls acinus differentiation during gestation. Herein, we found that loss of Kindlin-2 in myoepithelial cells impaired mammary morphogenesis, alveologenesis, and lactation. Using five genetically modified mouse lines combined with single-cell RNA sequencing, we found a Kindlin-2-Stat3-Dll1 signaling cascade in myoepithelial cells that inactivates Notch signaling in luminal cells and consequently drives luminal progenitor commitment to alveolar cells identity. Single-cell profiling revealed that Kindlin-2 loss significantly reduces the proportion of matured alveolar cells. Mechanistically, Kindlin-2 depletion in myoepithelial cells promotes Stat3 activation and upregulates Dll1, which activates the Notch pathway in luminal cells and inhibits luminal progenitor differentiation and maturation during gestation. Inhibition of Notch1 with tangeretin allowed luminal progenitors to regain commitment ability in the pregnant mice with Kindlin-2 depletion in myoepithelium. Taken together, we demonstrated that Kindlin-2 is essential to myoepithelium-controlled luminal progenitors to alveoli transition during gestation.

Luminal Rank loss decreases cell fitness leading to basal cell bipotency in parous mammary glands

Rank signaling pathway regulates mammary gland homeostasis and epithelial cell differentiation. Although Rank receptor is expressed by basal cells and luminal progenitors, its role in each individual cell lineage remains unclear. By combining temporal/lineage specific Rank genetic deletion with lineage tracing techniques, we found that loss of luminal Rank reduces the luminal progenitor pool and leads to aberrant alveolar-like differentiation with high protein translation capacity in virgin mammary glands. These Rank-deleted luminal cells are unable to expand during the first pregnancy, leading to lactation failure and impairment of protein synthesis potential in the parous stage. The unfit parous Rank-deleted luminal cells in the alveoli are progressively replaced by Rank-proficient cells early during the second pregnancy, thereby restoring lactation. Transcriptomic analysis and functional assays point to the awakening of basal bipotency after pregnancy by the induction of Rank/NF-κB signaling in basal parous cell to restore lactation and tissue homeostasis.

Osteopathia striata with cranial sclerosis causing a compressive optic neuropathy

BACKGROUND

Osteopathia striata combined with cranial sclerosis (OS-CS) is an inherited skeletal dysplasia that manifests with macrocephaly, orofacial abnormalities, thickened craniofacial bones, and vertically oriented radiodensities of the long bones.

CASE REPORT

Here, we present a severe case of OS-CS in a 4-year-old girl causing optic neuropathy as shown by radiographic evidence, ophthalmic findings, and histopathology. Previous genetic testing in this patient revealed a de novo heterozygous mutation in AMER1 (c.1057C>T, p.Arg353Ter). Although the patient had a pre-existing, appropriately functioning, ventriculoperitoneal (VP) shunt, a subsequent MRI of the brain and orbits showed narrowing of the bilateral optic nerve canals secondary to osseous thickening causing bilateral optic nerve atrophy, worse on the left. The patient underwent staged bilateral orbital osteotomies, optic canal decompression, and bilateral frontal craniotomy, and at 11 months postoperatively, her vision remained stable. Conclusions: While up to 50% of the patients with OS-CS may experience hearing loss due to cranial nerve compression, we present a case of severe visual loss secondary to OS-CS-associated optic nerve compression.

Dual-GCN-based deep clustering with triplet contrast for ScRNA-seq data analysis

Single-cell RNA sequencing (ScRNA-seq) technology reveals gene expression information at the cellular level. The critical tasks in ScRNA-seq data analysis are clustering and dimensionality reduction. Recent deep clustering algorithms are used to optimize the two tasks jointly, and their variations, graph-based deep clustering algorithms, are used to capture and preserve topological information in the process. However, the existing graph-based deep clustering algorithms ignore the distribution information of nodes when constructing cell graphs which leads to incomplete information in the embedding representation; and graph convolutional networks (GCN), which are most commonly used, often suffer from over-smoothing that leads to high sample similarity in the embedding representation and then poor clustering performance. Here, the dual-GCN-based deep clustering with Triplet contrast (scDGDC) is proposed for dimensionality reduction and clustering of scRNA-seq data. Two critical components are dual-GCN-based encoder for capturing more comprehensive topological information and triplet contrast for reducing GCN over-smoothing. The two components improve the dimensionality reduction and clustering performance of scDGDC in terms of information acquisition and model optimization, respectively. The experiments on eight real ScRNA-seq datasets showed that scDGDC achieves excellent performance for both clustering and dimensionality reduction tasks and is high robustness to parameters.

Single-cell transcription mapping of murine and human mammary organoids responses to female hormones

During female adolescence and pregnancy, rising levels of hormones result in a cyclic source of signals that control the development of mammary tissue. While such alterations are well understood from a whole-gland perspective, the alterations that such hormones bring to organoid cultures derived from mammary glands have yet to be fully mapped. This is of special importance given that organoids are considered suitable systems to understand cross species breast development. Here we utilized single-cell transcriptional profiling to delineate responses of murine and human normal breast organoid systems to female hormones across evolutionary distinct species. Collectively, our study represents a molecular atlas of epithelial dynamics in response to estrogen and pregnancy hormones.

A transcriptional response to replication stress selectively expands a subset of Brca2-mutant mammary epithelial cells

Germline BRCA2 mutation carriers frequently develop luminal-like breast cancers, but it remains unclear how BRCA2 mutations affect mammary epithelial subpopulations. Here, we report that monoallelic Brca2mut/WT mammary organoids subjected to replication stress activate a transcriptional response that selectively expands Brca2mut/WT luminal cells lacking hormone receptor expression (HR-). While CyTOF analyses reveal comparable epithelial compositions among wildtype and Brca2mut/WT mammary glands, Brca2mut/WT HR- luminal cells exhibit greater organoid formation and preferentially survive and expand under replication stress. ScRNA-seq analysis corroborates the expansion of HR- luminal cells which express elevated transcript levels of Tetraspanin-8 (Tspan8) and Thrsp, plus pathways implicated in replication stress survival including Type I interferon responses. Notably, CRISPR/Cas9-mediated deletion of Tspan8 or Thrsp prevents Brca2mut/WT HR- luminal cell expansion. Our findings indicate that Brca2mut/WT cells activate a transcriptional response after replication stress that preferentially favours outgrowth of HR- luminal cells through the expression of interferon-responsive and mammary alveolar genes.

Implications of tumour heterogeneity on cancer evolution and therapy resistance: lessons from breast cancer

Tumour heterogeneity is pervasive amongst many cancers and leads to disease progression, and therapy resistance. In this review, using breast cancer as an exemplar, we focus on the recent advances in understanding the interplay between tumour cells and their microenvironment using single cell sequencing and digital spatial profiling technologies. Further, we discuss the utility of lineage tracing methodologies in pre-clinical models of breast cancer, and how these are being used to unravel new therapeutic vulnerabilities and reveal biomarkers of breast cancer progression. © 2023 The Pathological Society of Great Britain and Ireland.

Mammary duct luminal epithelium controls adipocyte thermogenic programme

Sympathetic activation during cold exposure increases adipocyte thermogenesis via the expression of mitochondrial protein uncoupling protein 1 (UCP1)1. The propensity of adipocytes to express UCP1 is under a critical influence of the adipose microenvironment and varies between sexes and among various fat depots2-7. Here we report that mammary gland ductal epithelial cells in the adipose niche regulate cold-induced adipocyte UCP1 expression in female mouse subcutaneous white adipose tissue (scWAT). Single-cell RNA sequencing shows that glandular luminal epithelium subtypes express transcripts that encode secretory factors controlling adipocyte UCP1 expression under cold conditions. We term these luminal epithelium secretory factors 'mammokines'. Using 3D visualization of whole-tissue immunofluorescence, we reveal sympathetic nerve-ductal contact points. We show that mammary ducts activated by sympathetic nerves limit adipocyte UCP1 expression via the mammokine lipocalin 2. In vivo and ex vivo ablation of mammary duct epithelium enhance the cold-induced adipocyte thermogenic gene programme in scWAT. Since the mammary duct network extends throughout most of the scWAT in female mice, females show markedly less scWAT UCP1 expression, fat oxidation, energy expenditure and subcutaneous fat mass loss compared with male mice, implicating sex-specific roles of mammokines in adipose thermogenesis. These results reveal a role of sympathetic nerve-activated glandular epithelium in adipocyte UCP1 expression and suggest that mammary duct luminal epithelium has an important role in controlling glandular adiposity.

A spatially resolved single-cell genomic atlas of the adult human breast

The adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue1-3. Although most previous studies have focused on the breast epithelial system4-6, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer.

Distinct Requirements for Adaptor Proteins NCK1 and NCK2 in Mammary Gland Development

The adaptor proteins NCK1 and NCK2 are well-established signalling nodes that regulate diverse biological processes including cell proliferation and actin dynamics in many tissue types. Here we have investigated the distribution and function of Nck1 and Nck2 in the developing mouse mammary gland. Using publicly available single-cell RNA sequencing data, we uncovered distinct expression profiles between the two paralogs. Nck1 showed widespread expression in luminal, basal, stromal and endothelial cells, while Nck2 was restricted to luminal and basal cells, with prominent enrichment in hormone-sensing luminal subtypes. Next, using mice with global knockout of Nck1 or Nck2, we assessed mammary gland development during and after puberty (5, 8 and 12 weeks of age). Mice lacking Nck1 or Nck2 displayed significant defects in ductal outgrowth and branching at 5 weeks compared to controls, and the defects persisted in Nck2 knockout mice at 8 weeks before normalizing at 12 weeks. These defects were accompanied by an increase in epithelial cell proliferation at 5 weeks and a decrease at 8 weeks in both Nck1 and Nck2 knockout mice. We also profiled expression of several key genes associated with mammary gland development at these timepoints and detected temporal changes in transcript levels of hormone receptors as well as effectors of cell proliferation and migration in Nck1 and Nck2 knockout mice, in line with the distinct phenotypes observed at 5 and 8 weeks. Together these studies reveal a requirement for NCK proteins in mammary gland morphogenesis, and suggest that deregulation of Nck expression could drive breast cancer progression and metastasis.

Imagine beyond: recent breakthroughs and next challenges in mammary gland biology and breast cancer research

On 8 December 2022 the organizing committee of the European Network for Breast Development and Cancer labs (ENBDC) held its fifth annual Think Tank meeting in Amsterdam, the Netherlands. Here, we embraced the opportunity to look back to identify the most prominent breakthroughs of the past ten years and to reflect on the main challenges that lie ahead for our field in the years to come. The outcomes of these discussions are presented in this position paper, in the hope that it will serve as a summary of the current state of affairs in mammary gland biology and breast cancer research for early career researchers and other newcomers in the field, and as inspiration for scientists and clinicians to move the field forward.

Redefining normal breast cell populations using long noncoding RNAs

Single-cell RNAseq has allowed unprecedented insight into gene expression across different cell populations in normal tissue and disease states. However, almost all studies rely on annotated gene sets to capture gene expression levels and sequencing reads that do not align to known genes are discarded. Here, we discover thousands of long noncoding RNAs (lncRNAs) expressed in human mammary epithelial cells and analyze their expression in individual cells of the normal breast. We show that lncRNA expression alone can discriminate between luminal and basal cell types and define subpopulations of both compartments. Clustering cells based on lncRNA expression identified additional basal subpopulations, compared to clustering based on annotated gene expression, suggesting that lncRNAs can provide an additional layer of information to better distinguish breast cell subpopulations. In contrast, these breast-specific lncRNAs poorly distinguish brain cell populations, highlighting the need to annotate tissue-specific lncRNAs prior to expression analyses. We also identified a panel of 100 breast lncRNAs that could discern breast cancer subtypes better than protein-coding markers. Overall, our results suggest that lncRNAs are an unexplored resource for new biomarker and therapeutic target discovery in the normal breast and breast cancer subtypes.

scQCEA: a framework for annotation and quality control report of single-cell RNA-sequencing data

BACKGROUND

Systematic description of library quality and sequencing performance of single-cell RNA sequencing (scRNA-seq) data is imperative for subsequent downstream modules, including re-pooling libraries. While several packages have been developed to visualise quality control (QC) metrics for scRNA-seq data, they do not include expression-based QC to discriminate between true variation and background noise.

RESULTS

We present scQCEA (acronym of the single-cell RNA sequencing Quality Control and Enrichment Analysis), an R package to generate reports of process optimisation metrics for comparing sets of samples and visual evaluation of quality scores. scQCEA can import data from 10X or other single-cell platforms and includes functions for generating an interactive report of QC metrics for multi-omics data. In addition, scQCEA provides automated cell type annotation on scRNA-seq data using differential gene expression patterns for expression-based quality control. We provide a repository of reference gene sets, including 2348 marker genes, which are exclusively expressed in 95 human and mouse cell types. Using scRNA-seq data from 56 gene expressions and V(D)J T cell replicates, we show how scQCEA can be applied for the visual evaluation of quality scores for sets of samples. In addition, we use the summary of QC measures from 342 human and mouse shallow-sequenced gene expression profiles to specify optimal sequencing requirements to run a cell-type enrichment analysis function.

CONCLUSIONS

The open-source R tool will allow examining biases and outliers over biological and technical measures, and objective selection of optimal cluster numbers before downstream analysis. scQCEA is available at https://isarnassiri.github.io/scQCEA/ as an R package. Full documentation, including an example, is provided on the package website.

Mammary adipocyte flow cytometry as a tool to study mammary gland biology

The mammary gland is a vital exocrine organ that has evolved in mammals to secrete milk and provide nutrition to ensure the growth and survival of the neonate The mouse mammary gland displays extraordinary plasticity each time the female undergoes pregnancy and lactation, including a sophisticated process of tertiary branching and alveologenesis to form a branched epithelial tree and subsequently milk-producing alveoli. Upon the cessation of lactation, the gland remodels back to a simple ductal architecture via highly regulated involution processes. At the cellular level, the plasticity is characterised by proliferation of mammary cell populations, differentiation and apoptosis, accompanied by major changes in cell function and morphology. The mammary epithelium requires a specific stromal environment to grow, known as the mammary fat pad. Mammary adipocytes are one of the most prominent cell types in the fat pad, but despite their vast proportion in the tissue and their crucial interaction with epithelial cells, their physiology remains largely unknown. Over the past decade, the need to understand the properties and contribution of mammary adipocytes has become more recognised. However, the development of adequate methods and protocols to study this cellular niche is still lagging, partially due to their fragile nature, the difficulty of isolating them, the lack of reliable cell surface markers and the heterogenous environment in this tissue, which differs from other adipocyte depots. Here, we describe a new rapid and simple flow cytometry protocol specifically designed for the analysis and isolation of mouse mammary adipocytes across mammary gland developmental stages.