Time-resolved single-cell analysis of Brca1 associated mammary tumourigenesis reveals aberrant differentiation of luminal progenitors

Top-Down Proteomics Analysis of Picogram-Level Complex Samples Using Spray-Capillary-Based Capillary Electrophoresis-Mass Spectrometry

Proteomics analysis of mass-limited samples has become increasingly important for understanding biological systems in physiologically relevant contexts such as patient samples, multicellular organoids, spheroids, and single cells. However, relatively low sensitivity in top-down proteomics methods makes their application to mass-limited samples challenging. Capillary electrophoresis (CE) has emerged as an ideal separation method for mass-limited samples due to its high separation resolution, ultralow detection limit, and minimal sample volume requirements. Recently, we developed "spray-capillary", an electrospray ionization (ESI)-assisted device, that is capable of quantitative ultralow-volume sampling (e.g., pL-nL level). Here, we developed a spray-capillary-CE-MS platform for ultrasensitive top-down proteomics analysis of intact proteins in mass-limited complex biological samples. Specifically, to improve the sensitivity of the spray-capillary platform, we incorporated a polyethylenimine (PEI)-coated capillary and optimized the spray-capillary inner diameter. Under optimized conditions, we successfully detected over 200 proteoforms from 50 pg of E. coli lysate. To our knowledge, the spray-capillary CE-MS platform developed here represents one of the most sensitive detection methods for top-down proteomics. Furthermore, in a proof-of-principle experiment, we detected 261 ± 65 and 174 ± 45 intact proteoforms from fewer than 50 HeLa and OVCAR-8 cells, respectively, by coupling nanodroplet-based sample preparation with our optimized CE-MS platform. Overall, our results demonstrate the capability of the modified spray-capillary CE-MS platform to perform top-down proteomics analysis on picogram amounts of samples. This advancement presents the possibility of meaningful top-down proteomics analysis of mass-limited samples down to the level of single mammalian cells.

Epithelial IL-2 is critical for NK cell-mediated cancer immunosurveillance in mammary glands

Interleukin 2 (IL-2) is the first identified cytokine and its interaction with receptors has been known to shape the immune responses in many lymphoid or non-lymphoid tissues for more than four decades. Active T cells are the primary cellular source for IL-2 production and epithelial cells have never been considered the major cellular source of IL-2 under physiological conditions. It is, however, tempting to speculate that epithelial cells could potentially express IL-2 that regulates the intricate interactions between epithelial cells and lymphocytes. Datamining our recently published single-cell RNAseq in the mouse mammary gland identified IL-2 expression in mammary epithelial cells, which is induced by prolactin via the STAT5 signaling pathway. Furthermore, epithelial IL-2 plays a crucial role in maintaining the physiological functions of natural killer (NK) cells within the mammary glands. IL-2 deletion in the mammary epithelial cells leads to a significant reduction in the number and function of NK cells, which in turn results in defective immunosurveillance, expansion of luminal epithelial cells, and tumor development. Interestingly, T cells in the mammary glands are not changed, indicating the specific regulation of NK cells by epithelial IL-2 production. In agreement, we also found that human epithelial cells express IL-2 and NK cells express the highest level of IL2RB among all the immune cells. Here, we provide the first evidence that epithelial cells produce IL-2, which is critical for maintaining the physiological functions of NK cells in immunosurveillance.

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.

Biological basis of extensive pleiotropy between blood traits and cancer risk

BACKGROUND

The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations.

METHODS

Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis.

RESULTS

The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis.

CONCLUSIONS

This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Cancer as a Disease of Development Gone Awry

In the 160 years since Rudolf Virchow first postulated that neoplasia arises by the same law that regulates embryonic development, scientists have come to recognize the striking overlap between the molecular and cellular programs used by cancers and embryos. Advances in cancer biology and molecular techniques have further highlighted the similarities between carcinogenesis and embryogenesis, where cellular growth, differentiation, motility, and intercellular cross talk are mediated by common drivers and regulatory networks. This review highlights the many connections linking cancer biology and developmental biology to provide a deeper understanding of how a tissue's developmental history may both enable and constrain cancer cell evolution.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer

Basal-like breast cancer (BLBC) is highly aggressive, and often characterized by BRCA1 and p53 deficiency. Although conventional mouse models enabled the investigation of BLBC at malignant stages, its initiation and pre-malignant progression remain understudied. Here, we leveraged a mouse genetic system known as mosaic analysis with double markers (MADM) to study BLBC initiation by generating rare GFP+Brca1, p53-deficient mammary cells alongside RFP+ wild-type sibling cells. After confirming the close resemblance of mammary tumors arising in this model to human BLBC at both transcriptomic and genomic levels, we focused our studies on the pre-malignant progression of BLBC. Initiated GFP+ mutant cells showed a stepwise pre-malignant progression trajectory from focal expansion to hyper-alveolarization and then to micro-invasion. Furthermore, despite morphological similarities to alveoli, hyper-alveolarized structures actually originate from ductal cells based on twin-spot analysis of GFP-RFP sibling cells. Finally, luminal-to-basal transition occurred exclusively in cells that have progressed to micro-invasive lesions. Our MADM model provides excellent spatiotemporal resolution to illuminate the pre-malignant progression of BLBC, and should enable future studies on early detection and prevention for this cancer.

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.

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.

sccomp: Robust differential composition and variability analysis for single-cell data

Cellular omics such as single-cell genomics, proteomics, and microbiomics allow the characterization of tissue and microbial community composition, which can be compared between conditions to identify biological drivers. This strategy has been critical to revealing markers of disease progression, such as cancer and pathogen infection. A dedicated statistical method for differential variability analysis is lacking for cellular omics data, and existing methods for differential composition analysis do not model some compositional data properties, suggesting there is room to improve model performance. Here, we introduce sccomp, a method for differential composition and variability analyses that jointly models data count distribution, compositionality, group-specific variability, and proportion mean-variability association, being aware of outliers. sccomp provides a comprehensive analysis framework that offers realistic data simulation and cross-study knowledge transfer. Here, we demonstrate that mean-variability association is ubiquitous across technologies, highlighting the inadequacy of the very popular Dirichlet-multinomial distribution. We show that sccomp accurately fits experimental data, significantly improving performance over state-of-the-art algorithms. Using sccomp, we identified differential constraints and composition in the microenvironment of primary breast cancer.

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.

A genetic mosaic mouse model illuminates the pre-malignant progression of basal-like breast cancer

Basal-like breast cancer is an aggressive breast cancer subtype, often characterized by a deficiency in BRCA1 function and concomitant loss of p53 . While conventional mouse models enable the investigation of its malignant stages, one that reveals its initiation and pre-malignant progression is lacking. Here, we leveraged a mouse genetic system known as M osaic A nalysis with D ouble M arkers (MADM) to generate rare GFP-labeled Brca1 , p53 -deficient cells alongside RFP+ wildtype sibling cells in the mammary gland. The mosaicism resembles the sporadic initiation of human cancer and enables spatially resolved analysis of mutant cells in comparison to paired wildtype sibling cells. Mammary tumors arising in the model show transcriptomic and genomic characteristics similar to human basal-like breast cancer. Analysis of GFP+ mutant cells at interval time points before malignancy revealed a stepwise progression of lesions from focal expansion to hyper-alveolarization and then to micro-invasion. These stereotyped morphologies indicate the pre-malignant stage irrespective of the time point at which it is observed. Paired analysis of GFP-RFP siblings during focal expansion suggested that hyper-alveolarized structures originate from ductal rather than alveolar cells, despite their morphological similarities to alveoli. Evidence for luminal-to-basal transition at the pre-malignant stages was restricted to cells that had escaped hyper-alveoli and progressed to micro-invasive lesions. Our MADM-based mouse model presents a useful tool for studying the pre-malignancy of basal-like breast cancer.

Summary statement

A mouse model recapitulates the process of human basal-like breast tumorigenesis initiated from sporadic Brca1, p53 -deficient cells, empowering spatially-resolved analysis of mutant cells during pre-malignant progression.

Preneoplastic stromal cells promote BRCA1-mediated breast tumorigenesis

Women with germline BRCA1 mutations (BRCA1+/mut) have increased risk for hereditary breast cancer. Cancer initiation in BRCA1+/mut is associated with premalignant changes in breast epithelium; however, the role of the epithelium-associated stromal niche during BRCA1-driven tumor initiation remains unclear. Here we show that the premalignant stromal niche promotes epithelial proliferation and mutant BRCA1-driven tumorigenesis in trans. Using single-cell RNA sequencing analysis of human preneoplastic BRCA1+/mut and noncarrier breast tissues, we show distinct changes in epithelial homeostasis including increased proliferation and expansion of basal-luminal intermediate progenitor cells. Additionally, BRCA1+/mut stromal cells show increased expression of pro-proliferative paracrine signals. In particular, we identify pre-cancer-associated fibroblasts (pre-CAFs) that produce protumorigenic factors including matrix metalloproteinase 3 (MMP3), which promotes BRCA1-driven tumorigenesis in vivo. Together, our findings demonstrate that precancerous stroma in BRCA1+/mut may elevate breast cancer risk through the promotion of epithelial proliferation and an accumulation of luminal progenitor cells with altered differentiation.

The evolving tumor microenvironment: From cancer initiation to metastatic outgrowth

Cancers represent complex ecosystems comprising tumor cells and a multitude of non-cancerous cells, embedded in an altered extracellular matrix. The tumor microenvironment (TME) includes diverse immune cell types, cancer-associated fibroblasts, endothelial cells, pericytes, and various additional tissue-resident cell types. These host cells were once considered bystanders of tumorigenesis but are now known to play critical roles in the pathogenesis of cancer. The cellular composition and functional state of the TME can differ extensively depending on the organ in which the tumor arises, the intrinsic features of cancer cells, the tumor stage, and patient characteristics. Here, we review the importance of the TME in each stage of cancer progression, from tumor initiation, progression, invasion, and intravasation to metastatic dissemination and outgrowth. Understanding the complex interplay between tumor cell-intrinsic, cell-extrinsic, and systemic mediators of disease progression is critical for the rational development of effective anti-cancer treatments.

Loss of Epigenetic Regulation Disrupts Lineage Integrity, Induces Aberrant Alveogenesis, and Promotes Breast Cancer

Systematically investigating the scores of genes mutated in cancer and discerning disease drivers from inconsequential bystanders is a prerequisite for precision medicine but remains challenging. Here, we developed a somatic CRISPR/Cas9 mutagenesis screen to study 215 recurrent "long-tail" breast cancer genes, which revealed epigenetic regulation as a major tumor-suppressive mechanism. We report that components of the BAP1 and COMPASS-like complexes, including KMT2C/D, KDM6A, BAP1, and ASXL1/2 ("EpiDrivers"), cooperate with PIK3CAH1047R to transform mouse and human breast epithelial cells. Mechanistically, we find that activation of PIK3CAH1047R and concomitant EpiDriver loss triggered an alveolar-like lineage conversion of basal mammary epithelial cells and accelerated formation of luminal-like tumors, suggesting a basal origin for luminal tumors. EpiDriver mutations are found in ∼39% of human breast cancers, and ∼50% of ductal carcinoma in situ express casein, suggesting that lineage infidelity and alveogenic mimicry may significantly contribute to early steps of breast cancer etiology.

SIGNIFICANCE

Infrequently mutated genes comprise most of the mutational burden in breast tumors but are poorly understood. In vivo CRISPR screening identified functional tumor suppressors that converged on epigenetic regulation. Loss of epigenetic regulators accelerated tumorigenesis and revealed lineage infidelity and aberrant expression of alveogenesis genes as potential early events in tumorigenesis. This article is highlighted in the In This Issue feature, p. 2711.

Separation methods in single-cell proteomics: RPLC or CE?

Cellular heterogeneity is commonly investigated using single-cell genomics and transcriptomics to investigate biological questions such as disease mechanism, therapeutic screening, and genomic and transcriptomic diversity between cellular populations and subpopulations at the cellular level. Single-cell mass spectrometry (MS)-based proteomics enables the high-throughput examination of protein expression at the single-cell level with wide applicability, and with spatial and temporal resolution, applicable to the study of cellular development, disease, effect of treatment, etc. The study of single-cell proteomics has lagged behind genomics and transcriptomics largely because proteins from single-cell samples cannot be amplified as DNA and RNA can using well established techniques such as PCR. Therefore, analytical methods must be robust, reproducible, and sensitive enough to detect the very small amount of protein within a single cell. To this end, nearly every step of the proteomics process has been extensively altered and improved to facilitate the proteomics analysis of single cells including cell counting and sorting, lysis, protein digestion, sample cleanup, separation, MS data acquisition, and data analysis. Here, we have reviewed recent advances in single-cell protein separation using nano reversed phase liquid chromatography (nRPLC) and capillary electrophoresis (CE) to inform application driven selection of separation techniques in the laboratory setting.

Dissecting cell fate dynamics in pediatric glioblastoma through the lens of complex systems and cellular cybernetics

Cancers are complex dynamic ecosystems. Reductionist approaches to science are inadequate in characterizing their self-organized patterns and collective emergent behaviors. Since current approaches to single-cell analysis in cancer systems rely primarily on single time-point multiomics, many of the temporal features and causal adaptive behaviors in cancer dynamics are vastly ignored. As such, tools and concepts from the interdisciplinary paradigm of complex systems theory are introduced herein to decode the cellular cybernetics of cancer differentiation dynamics and behavioral patterns. An intuition for the attractors and complex networks underlying cancer processes such as cell fate decision-making, multiscale pattern formation systems, and epigenetic state-transitions is developed. The applications of complex systems physics in paving targeted therapies and causal pattern discovery in precision oncology are discussed. Pediatric high-grade gliomas are discussed as a model-system to demonstrate that cancers are complex adaptive systems, in which the emergence and selection of heterogeneous cellular states and phenotypic plasticity are driven by complex multiscale network dynamics. In specific, pediatric glioblastoma (GBM) is used as a proof-of-concept model to illustrate the applications of the complex systems framework in understanding GBM cell fate decisions and decoding their adaptive cellular dynamics. The scope of these tools in forecasting cancer cell fate dynamics in the emerging field of computational oncology and patient-centered systems medicine is highlighted.

A Review of Mathematical and Computational Methods in Cancer Dynamics

Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks. Understanding the cybernetics of cancer requires the integration of information dynamics across multidimensional spatiotemporal scales, including genetic, transcriptional, metabolic, proteomic, epigenetic, and multi-cellular networks. However, the time-series analysis of these complex networks remains vastly absent in cancer research. With longitudinal screening and time-series analysis of cellular dynamics, universally observed causal patterns pertaining to dynamical systems, may self-organize in the signaling or gene expression state-space of cancer triggering processes. A class of these patterns, strange attractors, may be mathematical biomarkers of cancer progression. The emergence of intracellular chaos and chaotic cell population dynamics remains a new paradigm in systems medicine. As such, chaotic and complex dynamics are discussed as mathematical hallmarks of cancer cell fate dynamics herein. Given the assumption that time-resolved single-cell datasets are made available, a survey of interdisciplinary tools and algorithms from complexity theory, are hereby reviewed to investigate critical phenomena and chaotic dynamics in cancer ecosystems. To conclude, the perspective cultivates an intuition for computational systems oncology in terms of nonlinear dynamics, information theory, inverse problems, and complexity. We highlight the limitations we see in the area of statistical machine learning but the opportunity at combining it with the symbolic computational power offered by the mathematical tools explored.

A human breast atlas integrating single-cell proteomics and transcriptomics

The breast is a dynamic organ whose response to physiological and pathophysiological conditions alters its disease susceptibility, yet the specific effects of these clinical variables on cell state remain poorly annotated. We present a unified, high-resolution breast atlas by integrating single-cell RNA-seq, mass cytometry, and cyclic immunofluorescence, encompassing a myriad of states. We define cell subtypes within the alveolar, hormone-sensing, and basal epithelial lineages, delineating associations of several subtypes with cancer risk factors, including age, parity, and BRCA2 germline mutation. Of particular interest is a subset of alveolar cells termed basal-luminal (BL) cells, which exhibit poor transcriptional lineage fidelity, accumulate with age, and carry a gene signature associated with basal-like breast cancer. We further utilize a medium-depletion approach to identify molecular factors regulating cell-subtype proportion in organoids. Together, these data are a rich resource to elucidate diverse mammary cell states.

Pathogenic BRCA1 variants disrupt PLK1-regulation of mitotic spindle orientation

Preneoplastic mammary tissues from human female BRCA1 mutation carriers, or Brca1-mutant mice, display unexplained abnormalities in luminal differentiation. We now study the division characteristics of human mammary cells purified from female BRCA1 mutation carriers or non-carrier donors. We show primary BRCA1 mutant/+ cells exhibit defective BRCA1 localization, high radiosensitivity and an accelerated entry into cell division, but fail to orient their cell division axis. We also analyse 15 genetically-edited BRCA1 mutant/+ human mammary cell-lines and find that cells carrying pathogenic BRCA1 mutations acquire an analogous defect in their division axis accompanied by deficient expression of features of mature luminal cells. Importantly, these alterations are independent of accumulated DNA damage, and specifically dependent on elevated PLK1 activity induced by reduced BRCA1 function. This essential PLK1-mediated role of BRCA1 in controlling the cell division axis provides insight into the phenotypes expressed during BRCA1 tumorigenesis.

Modification of BRCA1-associated breast cancer risk by HMMR overexpression

Breast cancer risk for carriers of BRCA1 pathological variants is modified by genetic factors. Genetic variation in HMMR may contribute to this effect. However, the impact of risk modifiers on cancer biology remains undetermined and the biological basis of increased risk is poorly understood. Here, we depict an interplay of molecular, cellular, and tissue microenvironment alterations that increase BRCA1-associated breast cancer risk. Analysis of genome-wide association results suggests that diverse biological processes, including links to BRCA1-HMMR profiles, influence risk. HMMR overexpression in mouse mammary epithelium increases Brca1-mutant tumorigenesis by modulating the cancer cell phenotype and tumor microenvironment. Elevated HMMR activates AURKA and reduces ARPC2 localization in the mitotic cell cortex, which is correlated with micronucleation and activation of cGAS-STING and non-canonical NF-κB signaling. The initial tumorigenic events are genomic instability, epithelial-to-mesenchymal transition, and tissue infiltration of tumor-associated macrophages. The findings reveal a biological foundation for increased risk of BRCA1-associated breast cancer.

BRCA1 and Breast Cancer: Molecular Mechanisms and Therapeutic Strategies

Breast cancer susceptibility gene 1 (BRCA1) is a tumor suppressor gene, which is mainly involved in the repair of DNA damage, cell cycle regulation, maintenance of genome stability, and other important physiological processes. Mutations or defects in the BRCA1 gene significantly increase the risk of breast, ovarian, prostate, and other cancers in carriers. In this review, we summarized the molecular functions and regulation of BRCA1 and discussed recent insights into the detection and treatment of BRCA1 mutated breast cancer.

Gpr125 is a unifying hallmark of multiple mammary progenitors coupled to tumor latency

Gpr125 is an orphan G-protein coupled receptor, with homology to cell adhesion and axonal guidance factors, that is implicated in planar polarity and control of cell movements. By lineage tracing we demonstrate that Gpr125 is a highly specific marker of bipotent mammary stem cells in the embryo and of multiple long-lived unipotent basal mammary progenitors in perinatal and postnatal glands. Nipple-proximal Gpr125+ cells express a transcriptomic profile indicative of chemo-repulsion and cell movement, whereas Gpr125+ cells concentrated at invasive ductal tips display a hybrid epithelial-mesenchymal phenotype and are equipped to bind chemokine and growth factors and secrete a promigratory matrix. Gpr125 progenitors acquire bipotency in the context of transplantation and cancer and are greatly expanded and massed at the pushing margins of short latency MMTV-Wnt1 tumors. High Gpr125 expression identifies patients with particularly poor outcome within the basal breast cancer subtype highlighting its potential utility as a factor to stratify risk.

Gpr125 has emerged as a specific marker of mammary stem cells and basal progenitors. Here they show that Gpr125 cells congregate at ductal tips during morphogenesis and amass at tumor margins, and that high Gpr125 predicts early tumor onset and poor outcome in basal breast cancer.

G-Quadruplex Matters in Tissue-Specific Tumorigenesis by BRCA1 Deficiency

How and why distinct genetic alterations, such as BRCA1 mutation, promote tumorigenesis in certain tissues, but not others, remain an important issue in cancer research. The underlying mechanisms may reveal tissue-specific therapeutic vulnerabilities. Although the roles of BRCA1, such as DNA damage repair and stalled fork stabilization, obviously contribute to tumor suppression, these ubiquitously important functions cannot explain tissue-specific tumorigenesis by BRCA1 mutations. Recent advances in our understanding of the cancer genome and fundamental cellular processes on DNA, such as transcription and DNA replication, have provided new insights regarding BRCA1-associated tumorigenesis, suggesting that G-quadruplex (G4) plays a critical role. In this review, we summarize the importance of G4 structures in mutagenesis of the cancer genome and cell type-specific gene regulation, and discuss a recently revealed molecular mechanism of G4/base excision repair (BER)-mediated transcriptional activation. The latter adequately explains the correlation between the accumulation of unresolved transcriptional regulatory G4s and multi-level genomic alterations observed in BRCA1-associated tumors. In summary, tissue-specific tumorigenesis by BRCA1 deficiency can be explained by cell type-specific levels of transcriptional regulatory G4s and the role of BRCA1 in resolving it. This mechanism would provide an integrated understanding of the initiation and development of BRCA1-associated tumors.

The Role of Progesterone Receptors in Breast Cancer

The progesterone receptor (PR) modulates estrogen receptors α (ERα) action in breast cancer; it is an upregulated target gene of ER, and its expression is dependent on estrogen. PR is also a valuable prognostic biomarker in breast cancer, especially in hormone-positive breast cancer. High expression of PR is more frequently observed in tumors with a better baseline prognosis (ie, luminal A) than tumors with a poor baseline prognosis (ie, luminal B). In the following review, we present the role of PR in breast cancer, including the genomic characteristics and pathways in breast cancer, PR and endocrine therapy.

Transcriptional changes in the mammary gland during lactation revealed by single cell sequencing of cells from human milk

Under normal conditions, the most significant expansion and differentiation of the adult mammary gland occurs in response to systemic reproductive hormones during pregnancy and lactation to enable milk synthesis and secretion to sustain the offspring. However, human mammary tissue remodelling that takes place during pregnancy and lactation remains poorly understood due to the challenge of acquiring samples. We report here single-cell transcriptomic analysis of 110,744 viable breast cells isolated from human milk or non-lactating breast tissue, isolated from nine and seven donors, respectively. We found that human milk largely contains epithelial cells belonging to the luminal lineage and a repertoire of immune cells. Further transcriptomic analysis of the milk cells identified two distinct secretory cell types that shared similarities with luminal progenitors, but no populations comparable to hormone-responsive cells. Taken together, our data offers a reference map and a window into the cellular dynamics that occur during human lactation and may provide further insights on the interplay between pregnancy, lactation and breast cancer.

Human mammary tissue remodelling that takes place during pregnancy and lactation remains poorly understood. Here the authors characterize cells in human milk, identifying epithelial cells resembling luminal progenitors and immune cells, contributing insights into this process.

Parity-induced changes to mammary epithelial cells control NKT cell expansion and mammary oncogenesis

Pregnancy reprograms mammary epithelial cells (MECs) to control their responses to pregnancy hormone re-exposure and carcinoma progression. However, the influence of pregnancy on the mammary microenvironment is less clear. Here, we used single-cell RNA sequencing to profile the composition of epithelial and non-epithelial cells in mammary tissue from nulliparous and parous female mice. Our analysis indicates an expansion of γδ natural killer T-like immune cells (NKTs) following pregnancy and upregulation of immune signaling molecules in post-pregnancy MECs. We show that expansion of NKTs following pregnancy is due to elevated expression of the antigen-presenting molecule CD1d on MECs. Loss of CD1d expression on post-pregnancy MECs, or overall lack of activated NKTs, results in mammary oncogenesis. Collectively, our findings illustrate how pregnancy-induced changes modulate the communication between MECs and the immune microenvironment and establish a causal link between pregnancy, the immune microenvironment, and mammary oncogenesis.

Mammary gland development from a single cell 'omics view

Understanding the complexity and heterogeneity of mammary cell subpopulations is vital to delineate the mechanisms behind breast cancer development, progression and prevention. Increasingly sophisticated tools for investigating these cell subtypes has led to the development of a greater understanding of these cell subtypes, complex interplay of certain subtypes and their developmental potential. Of note, increasing accessibility and affordability of single cell technologies has led to a plethora of studies being published containing data from mammary cell subtypes and their differentiation potential in both mice and human data sets. Here, we review the different types of single cell technologies and how they have been used to improve our understanding of mammary gland development.