Breast Network

Breast Network - Overview

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. Overall design: A total of 16 breast samples were assayed (4 samples from reductive mammoplasties and 12 from prophylactic mastectomies).

A human breast atlas integrating single-cell proteomics and transcriptomics

The authors developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq.

A single-cell and single-nucleus RNA-seq toolbox for fresh and frozen human tumors.

Breast Cancer (BC) patient stratification is mainly driven by tumour receptor status and histological grading and subtyping, with about twenty percent of patients for which absence of any actionable biomarkers results in no clear therapeutic intervention to apply. Here, we evaluated the potential of single-cell transcriptomics for automated diagnosis and drug treatment of breast cancer. We transcriptionally profiled 35,276 individual cells from 32 BC cell-lines covering all main BC subtypes to yield a Breast Cancer Single Cell Atlas. We show that single cell transcriptomics can successfully detect clinically relevant BC biomarkers and that atlas can be used to automatically predict cancer subtype and composition from a patient’s tumour biopsy. We found that BC cell lines harbour a high degree of heterogeneity in the expression of clinically relevant BC biomarkers and that such heterogeneity enables cells with differential drug sensitivity to co-exist even within a genomically stable isogenic cell line. Finally, we developed a novel bioinformatics approach named DREEP (Drug Response Estimation from Expression Profiles) to automatically predict responses to more than 450 anticancer agents starting from single-cell transcriptional profiles. We validated DREEP both in-silico and in-vitro by selectively inhibiting the growth of the HER2-deficient subpopulation in the MDAMB361 cell line. Our work shows that transcriptional heterogeneity is common, dynamic and that its plasticity plays a relevant role in determining drug sensitivity. Moreover, our Breast Cancer Single Cell Atlas and DREEP approach are a unique resource for the BC research community and to advance the use of single-cell sequencing in the clinic. Overall design: Single-cell sequencing of 32 breast cancer cell-lines

A single-cell atlas of breast cancer cell lines to study tumour heterogeneity and drug response

Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for approximately 1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems. Overall design: Applying single cell chromatin accessibility assays to diverse human tissue types from four donors.

A single-cell atlas of chromatin accessibility in the human genome

Single-cell RNA sequencing (scRNA-seq) is an evolving technology used to elucidate the cellular architecture of adult organs. Previous scRNA-seq on breast tissue utilized reduction mammoplasty samples, which are often histologically abnormal. We report a rapid tissue collection/processing protocol to perform scRNA-seq of breast biopsies of healthy women and identify 23 breast epithelial cell clusters. Putative cell-of-origin signatures derived from these clusters are applied to analyze transcriptomes of ~3,000 breast cancers. Gene signatures derived from mature luminal cell clusters are enriched in ~68% of breast cancers, whereas a signature from a luminal progenitor cluster is enriched in ~20% of breast cancers. Overexpression of luminal progenitor cluster-derived signatures in HER2+, but not in other subtypes, is associated with unfavorable outcome. We identify TBX3 and PDK4 as genes co-expressed with estrogen receptor (ER) in the normal breasts, and their expression analyses in >550 breast cancers enable prognostically relevant subclassification of ER+ breast cancers.

A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells

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.

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

Unbiased whole-genome methylome was studied in the wound-edge (WE) tissue of chronic wound patients. Methylation status of proximal promoter (1Kb) was calculated using MethylCap-Seq and PrEMeR-CG data analyses. A total of 4689 differentially methylated regions (DMRs) were identified in chronic WE compared to unwounded (UW) human skin. Hypermethylation was more frequently observed (3661 DMRs) in the chronic WE compared to hypomethylation (1028 DMRs). Twenty-six hypermethylated DMRs were involved in epithelial to mesenchymal transition (EMT). Bisulfite sequencing validated hypermethylation of a predicted specific upstream regulator TP53. Whole genome RNA sequencing analysis was performed to qualify findings from methylome analysis. Hierarchical clustering analyses identified a large set of genes, the expression of which were significantly downregulated in chronic WE compared to UW skin. Analysis of the downregulated genes identified the TP53 signaling pathway, including P63, P73, FOXO3, SIRT1 and HDAC1, as being significantly silenced. Direct comparison of hypermethylation and downregulated gene expression identified four genes, ADAM17, NOTCH, TWIST1 and SMURF1, that were common to both data sets and functionally represented the EMT pathway. Single cell RNA sequencing studies identified that these effects on gene expression were limited to the keratinocyte cell compartment. Overall design: In this work, scRNA-seq analyses of human chronic WE characterized its heterogenous cellular composition as compared to unwounded skin.

Genome-Wide DNA Hypermethylation in the Wound-Edge of Chronic Wound Patients Opposes Closure by Impairing Epithelial to Mesenchymal Transition

Milk derived live mammary epithelial cells were characterized by single cell RNA sequencing. Overall design: Cells were pelleted from mid-feed milk samples prior to cryopreservation and subsequent analysis by single cell RNA sequencing.

Single Cell RNA Sequencing of Human Milk-Derived Cells Reveals Sub-Populations of Mammary Epithelial Cells with Molecular Signatures of Progenitor and Mature States: a Novel, Non-invasive Framework for Investigating Human Lactation Physiology

During tumour growth cancer cells are subject to and selected by microenvironmental stress. The selection of such cells allows for continued growth and survival, during hypoxia, acidosis, nutritional deprivation, drug treatment and radiation. However, there is great microenvironmental heterogeneity in every tumour. Must studies of gene regulation in vitro investigate whole cell populations, often by western blotting or mRNA expression. Thus, the individual variability of gene induction that could lead to selection, and basal cell molecular variability on which the selection operates, basic Darwinian principles, are not defined. We previously showed that two distinct populations can often be induced in epithelial tumour cell lines under hypoxia, identified by induction of Carbonic Anhydrase 9 [CA9].Here, we investigated the heterogeneity of breast cancer cells, and the relationship to the CA9 positive population in hypoxia, by using single cell sequencing analysis. Overall design: Examination of the MCF7 breast cancer cell line using single cell transcriptomics (smartseq2)

Single cell sequencing identifies novel sub-populations of breast cancer cells selected under hypoxia

Knowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We profiled 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph nodes, using single-cell RNA-seq. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous phenotypic expansions specific to the tumor microenvironment. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer. Our results have important implications for characterizing tumor-infiltrating immune cells.

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.

Single-nucleus analysis allows robust cell-type classification and
helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Using samples from 92 women of
several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells and macrophages. In addition to the known cell
identity genes FOXA1 (luminal hormone sensing), EHF and ELF5 (LASP), TP63 and KRT14 (basal-myoepithelial), epithelial subtypes displayed
several uncharacterized markers and inferred gene regulatory networks.
By integrating breast epithelial cell gene expression signatures with
spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed
genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.

Single-nucleus chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry

Understanding gene function and regulation in homeostasis and disease requires knowledge of the cellular and tissue contexts in which genes are expressed. Here, we applied four single-nucleus RNA sequencing methods to eight diverse, archived, frozen tissue types from 16 donors and 25 samples, generating a cross-tissue atlas of 209,126 nuclei profiles, which we integrated across tissues, donors, and laboratory methods with a conditional variational autoencoder. Using the resulting cross-tissue atlas, we highlight shared and tissue-specific features of tissue-resident cell populations; identify cell types that might contribute to neuromuscular, metabolic, and immune components of monogenic diseases and the biological processes involved in their pathology; and determine cell types and gene modules that might underlie disease mechanisms for complex traits analyzed by genome-wide association studies.

Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function.

We have created a compendium of single cell transcriptome data from the model
organism Mus musculus comprising more than 100,000 cells from 20 organs and
tissues. These data represent a new resource for cell biology, revealing gene
expression in poorly characterized cell populations and allowing for direct and
controlled comparison of gene expression in cell types shared between tissues, such
as T-lymphocytes and endothelial cells from distinct anatomical locations. Two
distinct technical approaches were used for most tissues: one approach, microfluidic
droplet-based 3’-end counting, enabled the survey of thousands of cells at relatively
low coverage, while the other, FACS-based full length transcript analysis, enabled
characterization of cell types with high sensitivity and coverage. The cumulative
data provide the foundation for an atlas of transcriptomic cell biology.

Tabula Muris: Transcriptomic characterization of 20 organs and tissues from Mus musculus at single cell resolution

In recent years there has been tremendous progress towards deep molecular characterization of cell types using single cell transcriptome sequencing. Here we report a single cell transcriptomic atlas comprising nearly 500,000 cells from 24 different human tissues and organs. In several instances multiple organs were analyzed from the same donor. Analyzing organs from the same individual controls for genetic background, age, environment, and epigenetic effects, and enables a detailed comparison of cell types that are shared between tissues. This resource provides a rich molecular characterization of more than 400 cell types, their distribution across tissues, and detailed information about tissue specific variation in gene expression. We have used the fact that multiple tissues came from the same donor to study the clonal distribution of T cells between tissues, to understand the tissue specific mutation rate in B cells, and to analyze the cell cycle state and proliferative potential of shared cell types across tissues. Finally, we have also used this data to characterize cell type specific RNA splicing and how such splicing varies across tissues within an individual.

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans

Rhabdomyosarcoma (RMS) is the most soft tissue sarcoma of childhood and histologically mimics developing skeletal muscle. To better understand RMS, we performed single-cell RNA-seq of one embryonal subtype RMS (ERMS) and one alveolar subtype RMS (ARMS). We expanded our observations by performing single-nucleus RNA-seq of 18 patient tumors (12 ERMS, 6 ARMS). All 18 of these tumors were used to generate orthotopic patient-derived xenografts, and we performed single-cell RNA-seq of all 18 O-PDXs to compare heterogeneity between the original tumor and the patient-derived model. 15 of the O-PDXs underwent lentiviral barcoding, and lineage could be tracked using a separate dial-out PCR step during the single-cell RNA-seq workflow. We performed single-cell RNA-seq of an ex vivo organoid, showing that we can preserve heterogeneity in this model. We expanded our study to the epigenetic level by using single-cell ATAC-sequencing of 7 O-PDXs. Finally, we longitudinally tracked shifts in heterogeneity in an O-PDX model treated with chemotherapy. Overall design: We performed single-cell RNA-seq from 2 patient RMS tumors, 18 O-PDXs, and 1 organoid. Additionally, we performed single-nucleus RNA-seq from 18 patient RMS tumors and single-cell ATAC-seq from 7 O-PDXs. We also provide dialout PCR data from 15 RMS O-PDX that were used for lentiviral barcode experiments to track clonal lineages within O-PDXs.

The myogenesis program drives clonal selection and drug resistance in rhabdomyosarcoma

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.

Breast Network

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Breast Network atlases are still under development.

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