A human breast atlas integrating single-cell proteomics and transcriptomics

•Multimodal single-cell analyses identify breast epithelial and stromal subtypes•Spatially distinct epithelial subsets are linked with age, parity, and BRCA2 status•Alveolar cells with poor transcriptional lineage fidelity accumulate with age•Subtypes of the three major epithelial lineages are maintained in organoid cultures 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. 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. Breast cancer is heterogeneous, comprising distinct subtypes with unique therapeutic vulnerabilities possibly rooted in their distinct cells of origin (Visvader, and Stingl, 2014Visvader J.E. Stingl J. Mammary stem cells and the differentiation hierarchy: current status and perspectives.Genes Dev. 2014; 28: 1143-1158Crossref PubMed Scopus (349) Google Scholar). However, investigation of early tumor formation and progression has been limited by an underdeveloped, occasionally conflicting annotation of mammary lineages. Existing annotations are often defined by a small number of markers that inadequately capture mammary intra-lineage heterogeneity. Many questions remain regarding the diversity of the mammary cellular landscape and how it changes in relation to cancer risk factors, such as age, parity, and germline mutations in breast cancer predisposition genes such as BRCA1/2. Thus, there is a pressing need to define breast cell types/states more comprehensively at high resolution from a broad spectrum of samples. The mammary gland is composed of an epithelial bilayer and a supportive stroma (Inman et al., 2015Inman J.L. Robertson C. Mott J.D. Bissell M.J. Mammary gland development: cell fate specification, stem cells and the microenvironment.Development. 2015; 142: 1028-1042Crossref PubMed Scopus (239) Google Scholar; Polyak, and Kalluri, 2010Polyak K. Kalluri R. The role of the microenvironment in mammary gland development and cancer.Cold Spring Harb. Perspect. Biol. 2010; 2: a003244Crossref PubMed Google Scholar). Within the epithelium, basal/myoepithelial (BA) cells contract to help express milk during lactation and provide structural support to two luminal populations: alveolar (AV) and hormone-sensing (HS) cells. AV cells give rise to milk-producing cells during lactation, whereas HS cells integrate endocrine signals to control mammary growth and differentiation. AV and HS cells have historically been termed luminal progenitors and mature luminal cells, respectively, based on in vitro assays (Fu et al., 2020Fu N.Y. Nolan E. Lindeman G.J. Visvader J.E. Stem cells and the differentiation hierarchy in mammary gland development.Physiol. Rev. 2020; 100: 489-523Crossref PubMed Scopus (67) Google Scholar; Shackleton et al., 2006Shackleton M. Vaillant F. Simpson K.J. Stingl J. Smyth G.K. Asselin-Labat M.L. Wu L. Lindeman G.J. Visvader J.E. Generation of a functional mammary gland from a single stem cell.Nature. 2006; 439: 84-88Crossref PubMed Scopus (1569) Google Scholar; Stingl et al., 2006Stingl J. Eirew P. Ricketson I. Shackleton M. Vaillant F. Choi D. Li H.I. Eaves C.J. Purification and unique properties of mammary epithelial stem cells.Nature. 2006; 439: 993-997Crossref PubMed Scopus (1227) Google Scholar). However, recent post-natal lineage tracing in murine glands show these two cell types are not hierarchically organized but rather are independent (Blaas et al., 2016Blaas L. Pucci F. Messal H.A. Andersson A.B. Josue Ruiz E. Gerling M. Douagi I. Spencer-Dene B. Musch A. Mitter R. et al.Lgr6 labels a rare population of mammary gland progenitor cells that are able to originate luminal mammary tumours.Nat. Cell Biol. 2016; 18: 1346-1356Crossref PubMed Scopus (51) Google Scholar; Davis et al., 2016Davis F.M. Lloyd-Lewis B. Harris O.B. Kozar S. Winton D.J. Muresan L. Watson C.J. Single-cell lineage tracing in the mammary gland reveals stochastic clonal dispersion of stem/progenitor cell progeny.Nat. Commun. 2016; 7: 13053Crossref PubMed Google Scholar; Elias et al., 2017Elias S. Morgan M.A. Bikoff E.K. Robertson E.J. Long-lived unipotent Blimp1-positive luminal stem cells drive mammary gland organogenesis throughout adult life.Nat. Commun. 2017; 8: 1714Crossref PubMed Scopus (21) Google Scholar; Lilja et al., 2018Lilja A.M. Rodilla V. Huyghe M. Hannezo E. Landragin C. Renaud O. Leroy O. Rulands S. Simons B.D. Fre S. Clonal analysis of Notch1-expressing cells reveals the existence of unipotent stem cells that retain long-term plasticity in the embryonic mammary gland.Nat. Cell Biol. 2018; 20: 677-687Crossref PubMed Scopus (72) Google Scholar; Rios et al., 2014Rios A.C. Fu N.Y. Lindeman G.J. Visvader J.E. In situ identification of bipotent stem cells in the mammary gland.Nature. 2014; 506: 322-327Crossref PubMed Scopus (366) Google Scholar; Rodilla et al., 2015Rodilla V. Dasti A. Huyghe M. Lafkas D. Laurent C. Reyal F. Fre S. Luminal progenitors restrict their lineage potential during mammary gland development.PLoS Biol. 2015; 13: e1002069Crossref PubMed Google Scholar; Van Keymeulen et al., 2017Van Keymeulen A. Fioramonti M. Centonze A. Bouvencourt G. Achouri Y. Blanpain C. Lineage-restricted mammary stem cells sustain the development, homeostasis, and regeneration of the estrogen receptor positive lineage.Cell Rep. 2017; 20: 1525-1532Abstract Full Text Full Text PDF PubMed Google Scholar; Wang et al., 2017Wang C. Christin J.R. Oktay M.H. Guo W. Lineage-biased stem cells maintain estrogen-receptor-positive and -negative mouse mammary luminal lineages.Cell Rep. 2017; 18: 2825-2835Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar). These mammary epithelial cell (MEC) lineages undergo dramatic alterations in morphology and function throughout a human life, including in puberty, pregnancy, and menopause (Fu et al., 2020Fu N.Y. Nolan E. Lindeman G.J. Visvader J.E. Stem cells and the differentiation hierarchy in mammary gland development.Physiol. Rev. 2020; 100: 489-523Crossref PubMed Scopus (67) Google Scholar; LaBarge et al., 2016LaBarge M.A. Mora-Blanco E.L. Samson S. Miyano M. Breast cancer beyond the age of mutation.Gerontology. 2016; 62: 434-442Crossref PubMed Scopus (28) Google Scholar; Slepicka et al., 202 1Slepicka P.F. Somasundara A.V.H. Dos Santos C.O. The molecular basis of mammary gland development and epithelial differentiation.Semin. Cell Dev. Biol. 2021; 114: 93-112Crossref PubMed Scopus (10) Google Scholar). Many physiological/genetic variables and cancer risk factors influence MEC composition. Depending on cohorts analyzed and methods employed, previous studies have reported various alterations in MEC proportions and properties associated with aging, parity, and germline BRCA1/2 mutations (Benz, 2008Benz C.C. Impact of aging on the biology of breast cancer.Crit. Rev. Oncol. Hematol. 2008; 66: 65-74Crossref PubMed Scopus (118) Google Scholar; Britt et al., 2007Britt K. Ashworth A. Smalley M. Pregnancy and the risk of breast cancer.Endocr. Relat. Cancer. 2007; 14: 907-933Crossref PubMed Scopus (179) Google Scholar; Choudhury et al., 2013Choudhury S. Almendro V. Merino V.F. Wu Z. Maruyama R. Su Y. Martins F.C. Fackler M.J. Bessarabova M. Kowalczyk A. et al.Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics.Cell Stem Cell. 2013; 13: 117-130Abstract Full Text Full Text PDF PubMed Scopus (64) Google Scholar; Ding et al., 2019Ding L. Su Y. Fassl A. Hinohara K. Qiu X. Harper N.W. Huh S.J. Bloushtain-Qimron N. Jovanović B. Ekram M. et al.Perturbed myoepithelial cell differentiation in BRCA mutation carriers and in ductal carcinoma in situ.Nat. Commun. 2019; 10: 4182Crossref PubMed Scopus (21) Google Scholar; Garbe et al., 2012Garbe J.C. Pepin F. Pelissier F.A. Sputova K. Fridriksdottir A.J. Guo D.E. Villadsen R. Park M. Petersen O.W. Borowsky A.D. et al.Accumulation of multipotent progenitors with a basal differentiation bias during aging of human mammary epithelia.Cancer Res. 2012; 72: 3687-3701Crossref PubMed Scopus (68) Google Scholar; Honeth et al., 2015Honeth G. Schiavinotto T. Vaggi F. Marlow R. Kanno T. Shinomiya I. Lombardi S. Buchupalli B. Graham R. Gazinska P. et al.Models of breast morphogenesis based on localization of stem cells in the developing mammary lobule.Stem Cell Rep. 2015; 4: 699-711Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Karaayvaz-Yildirim et al., 2020Karaayvaz-Yildirim M. Silberman R.E. Langenbucher A. Saladi S.V. Ross K.N. Zarcaro E. Desmond A. Yildirim M. Vivekanandan V. Ravichandran H. et al.Aneuploidy and a deregulated DNA damage response suggest haploinsufficiency in breast tissues of BRCA2 mutation carriers.Sci. Adv. 2020; 6: eaay2611Crossref PubMed Scopus (9) Google Scholar; King et al., 2004King T.A. Gemignani M.L. Li W. Giri D.D. Panageas K.S. Bogomolniy F. Arroyo C. Olvera N. Robson M.E. Offit K. et al.Increased progesterone receptor expression in benign epithelium of BRCA1-related breast cancers.Cancer Res. 2004; 64: 5051-5053Crossref PubMed Scopus (0) Google Scholar; Lim et al., 2009Lim E. Vaillant F. Wu D. Forrest N.C. Pal B. Hart A.H. Asselin-Labat M.L. Gyorki D.E. Ward T. Partanen A. et al.Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers.Nat. Med. 2009; 15: 907-913Crossref PubMed Scopus (998) Google Scholar; Mote et al., 2004Mote P.A. Leary J.A. Avery K.A. Sandelin K. Chenevix-Trench G. Kirk J.A. Clarke C.L. kConFab InvestigatorsGerm-line mutations in BRCA1 or BRCA2 in the normal breast are associated with altered expression of estrogen-responsive proteins and the predominance of progesterone receptor A.Genes Chromosomes Cancer. 2004; 39: 236-248Crossref PubMed Scopus (0) Google Scholar; Nolan et al., 2016Nolan E. Vaillant F. Branstetter D. Pal B. Giner G. Whitehead L. Lok S.W. Mann G.B. Rohrbach K. et al.Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab)RANK ligand as a potential target for breast cancer prevention in BRCA1-mutation carriers.Nat. Med. 2016; 22: 933-939Crossref PubMed Scopus (174) Google Scholar; Pal et al., 2021Pal B. Chen Y. Vaillant F. Capaldo B.D. Joyce R. Song X. Bryant V.L. Penington J.S. Di Stefano L. Tubau Ribera N. et al.A single-cell RNA expression atlas of normal, preneoplastic and tumorigenic states in the human breast.EMBO J. 2021; 40: e107333Crossref PubMed Scopus (18) Google Scholar; Pelissier Vatter et al., 2018Pelissier Vatter F.A. Schapiro D. Chang H. Borowsky A.D. Lee J.K. Parvin B. Stampfer M.R. LaBarge M.A. Bodenmiller B. Lorens J.B. High-dimensional phenotyping identifies age-emergent cells in human mammary epithelia.Cell Rep. 2018; 23: 1205-1219Abstract Full Text Full Text PDF PubMed Scopus (22) Google Scholar; Proia et al., 2011Proia T.A. Keller P.J. Gupta P.B. Klebba I. Jones A.D. Sedic M. Gilmore H. Tung N. Naber S.P. Schnitt S. et al.Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate.Cell Stem Cell. 2011; 8: 149-163Abstract Full Text Full Text PDF PubMed Scopus (263) Google Scholar; Russo et al., 1992Russo J. Rivera R. Russo I.H. Influence of age and parity on the development of the human breast.Breast Cancer Res. Treat. 1992; 23: 211-218Crossref PubMed Scopus (183) Google Scholar; Shalabi et al., 2021Shalabi S.F. Miyano M. Sayaman R.W. Lopez J.C. Jokela T.A. Todhunter M.E. Hinz S. Garbe J.C. Stampfer M.R. Kessenbrock K. et al.Evidence for accelerated aging in mammary epithelia of women carrying germline BRCA1 or BRCA2 mutations.Nat. Aging. 2021; 1: 838-849Crossref PubMed Google Scholar). These studies have provided somewhat fragmented views of the mammary cell landscape; a systematic, high-resolution taxonomy of the breast can provide a framework for large-scale studies to delineate the effects of risk factors on cancer development. Recent advances in single-cell technologies like single-cell RNA sequencing (scRNA-seq) and mass cytometry (cytometry by time-of-flight; CyTOF) have enabled a more comprehensive evaluation of mammary cell diversity (Bach et al., 2017Bach K. Pensa S. Grzelak M. Hadfield J. Adams D.J. Marioni J.C. Khaled W.T. Differentiation dynamics of mammary epithelial cells revealed by single-cell RNA sequencing.Nat. Commun. 2017; 8: 2128Crossref PubMed Scopus (0) Google Scholar; Bhat-Nakshatri et al., 2021Bhat-Nakshatri P. Gao H. Sheng L. McGuire P.C. Xuei X. Wan J. Liu Y. Althouse S.K. Colter A. Sandusky G. et al.A single-cell atlas of the healthy breast tissues reveals clinically relevant clusters of breast epithelial cells.Cell Rep. Med. 2021; 2: 100219Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Colacino et al., 2018Colacino J.A. Azizi E. Brooks M.D. Harouaka R. Fouladdel S. McDermott S.P. Lee M. Hill D. Madden J. Boerner J. et al.Heterogeneity of human breast stem and progenitor cells as revealed by transcriptional profiling.Stem Cell Rep. 2018; 10: 1596-1609Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Giraddi et al., 2018Giraddi R.R. Chung C.Y. Heinz R.E. Balcioglu O. Novotny M. Trejo C.L. Dravis C. Hagos B.M. Mehrabad E.M. Rodewald L.W. et al.Single-cell transcriptomes distinguish stem cell state changes and lineage specification programs in early mammary gland development.Cell Rep. 2018; 24: 1653-1666.e7Abstract Full Text Full Text PDF PubMed Scopus (71) Google Scholar; Henry et al., 2021Henry S. Trousdell M.C. Cyrill S.L. Zhao Y. Feigman M.J. Bouhuis J.M. Aylard D.A. Siepel A. Dos Santos C.O. Characterization of gene expression signatures for the identification of cellular heterogeneity in the developing mammary gland.J. Mammary Gland Biol. Neoplasia. 2021; 26: 43-66Crossref PubMed Scopus (5) Google Scholar; Hu et al., 2021Hu L. Su L. Cheng H. Mo C. Ouyang T. Li J. Wang T. Fan Z. Fan T. Lin B. et al.Single-cell RNA sequencing reveals the cellular origin and evolution of breast cancer in BRCA1 mutation carriers.Cancer Res. 2021; 81: 2600-2611Crossref PubMed Scopus (5) Google Scholar; Kanaya et al., 2019Kanaya N. Chang G. Wu X. Saeki K. Bernal L. Shim H.J. Wang J. Warden C. Yamamoto T. Li J. et al.Single-cell RNA-sequencing analysis of estrogen- and endocrine-disrupting chemical-induced reorganization of mouse mammary gland.Commun. Biol. 2019; 2: 406Crossref PubMed Scopus (5) Google Scholar; Knapp et al., 2017Knapp D.J.H.F. Kannan N. Pellacani D. Eaves C.J. Mass cytometric analysis reveals viable activated caspase-3+ luminal progenitors in the normal adult human mammary gland.Cell Rep. 2017; 21: 1116-1126Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Li et al., 2020Li C.M. Shapiro H. Tsiobikas C. Selfors L.M. Chen H. Rosenbluth J. Moore K. Gupta K.P. Gray G.K. Oren Y. et al.Aging-associated alterations in mammary epithelia and stroma revealed by single-cell RNA sequencing.Cell Rep. 2020; 33: 108566Abstract Full Text Full Text PDF PubMed Google Scholar; Mahendralingam et al., 2021Mahendralingam M.J. Kim H. McCloskey C.W. Aliar K. Casey A.E. Tharmapalan P. Pellacani D. Ignatchenko V. Garcia-Valero M. Palomero L. et al.Mammary epithelial cells have lineage-rooted metabolic identities.Nat. Metab. 2021; 3: 665-681Crossref PubMed Scopus (7) Google Scholar; Nguyen et al., 2018Nguyen Q.H. Pervolarakis N. Blake K. Ma D. Davis R.T. James N. Phung A.T. Willey E. Kumar R. Jabart E. et al.Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity.Nat. Commun. 2018; 9: 2028Crossref PubMed Scopus (132) Google Scholar; Pal et al., 2021Pal B. Chen Y. Vaillant F. Capaldo B.D. Joyce R. Song X. Bryant V.L. Penington J.S. Di Stefano L. Tubau Ribera N. et al.A single-cell RNA expression atlas of normal, preneoplastic and tumorigenic states in the human breast.EMBO J. 2021; 40: e107333Crossref PubMed Scopus (18) Google Scholar, Pal et al., 2017Pal B. Chen Y. Vaillant F. Jamieson P. Gordon L. Rios A.C. Wilcox S. Fu N. Liu K.H. Jackling F.C. et al.Construction of developmental lineage relationships in the mouse mammary gland by single-cell RNA profiling.Nat. Commun. 2017; 8: 1627Crossref PubMed Scopus (99) Google Scholar; Pelissier Vatter et al., 2018Pelissier Vatter F.A. Schapiro D. Chang H. Borowsky A.D. Lee J.K. Parvin B. Stampfer M.R. LaBarge M.A. Bodenmiller B. Lorens J.B. High-dimensional phenotyping identifies age-emergent cells in human mammary epithelia.Cell Rep. 2018; 23: 1205-1219Abstract Full Text Full Text PDF PubMed Scopus (22) Google Scholar; Rosenbluth et al., 2020Rosenbluth J.M. Schackmann R.C.J. Gray G.K. Selfors L.M. Li C.M. Boedicker M. Kuiken H.J. Richardson A. Brock J. Garber J. et al.Organoid cultures from normal and cancer-prone human breast tissues preserve complex epithelial lineages.Nat. Commun. 2020; 11: 1711Crossref PubMed Scopus (66) Google Scholar; Scheele et al., 2017Scheele C.L. Hannezo E. Muraro M.J. Zomer A. Langedijk N.S. van Oudenaarden A. Simons B.D. van Rheenen J. Identity and dynamics of mammary stem cells during branching morphogenesis.Nature. 2017; 542: 313-317Crossref PubMed Scopus (113) Google Scholar; Twigger et al., 2022Twigger A.J. Engelbrecht L.K. Bach K. Schultz-Pernice I. Pensa S. Stenning J. Petricca S. Scheel C.H. Khaled W.T. Transcriptional changes in the mammary gland during lactation revealed by single cell sequencing of cells from human milk.Nat. Commun. 2022; 13: 562Crossref PubMed Scopus (1) Google Scholar; Wuidart et al., 2018Wuidart A. Sifrim A. Fioramonti M. Matsumura S. Brisebarre A. Brown D. Centonze A. Dannau A. Dubois C. Van Keymeulen A. et al.Early lineage segregation of multipotent embryonic mammary gland progenitors.Nat. Cell Biol. 2018; 20: 666-676Crossref PubMed Scopus (82) Google Scholar). However, a comprehensive atlas of breast cell types has not yet been constructed due to high inter-individual variability, highlighting a need for broader studies to capture full intra-lineage cell diversity. In particular, a multi-omic approach may reveal nonsynonymous levels of heterogeneity (Chung et al., 2019Chung C.Y. Ma Z. Dravis C. Preissl S. Poirion O. Luna G. Hou X. Giraddi R.R. Ren B. Wahl G.M. Single-cell chromatin analysis of mammary gland development reveals cell-state transcriptional regulators and lineage relationships.Cell Rep. 2019; 29: 495-510.e6Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar; Ding et al., 2020Ding J. Adiconis X. Simmons S.K. Kowalczyk M.S. Hession C.C. Marjanovic N.D. Hughes T.K. Wadsworth M.H. Burks T. Nguyen L.T. et al.Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.Nat. Biotechnol. 2020; 38: 737-746Crossref PubMed Scopus (203) Google Scholar; Hao et al., 2021Hao Y. Hao S. Andersen-Nissen E. Mauck 3rd, W.M. Zheng S. Butler A. Lee M.J. Wilk A.J. Darby C. Zager M. et al.Integrated analysis of multimodal single-cell data.Cell. 2021; 184: 3573-3587.e29Abstract Full Text Full Text PDF PubMed Scopus (560) Google Scholar). Here, we report a high-resolution breast cell taxonomy generated by integrating scRNA-seq (n = 16), CyTOF (n = 38), and cyclic immunofluorescence (CyCIF; n = 53). We analyzed samples from reductive mammoplasties and prophylactic mastectomies encompassing a broad spectrum of ages, parities, and germline BRCA1/2 mutation statuses. Organoid modulation experiments uncovered potential molecular regulation of several MEC subtypes, thus demonstrating a feasible approach to illuminate targetable changes in high-risk individuals’ breasts. Collectively, this multi-omic, single-cell approach yields a breast atlas of cell lineages and intra-lineage subtypes, uncovers altered MEC subtypes associated with cancer risk factors, and enables signaling pathway interrogation in cell subtypes in vitro. This multifaceted approach may serve as a template for studying premalignant changes in the breast and other tissues. To generate a high-resolution portrait of breast cell types, scRNA-seq and CyTOF were utilized to provide complementary views of cell diversity at the mRNA and protein levels (Figure 1A). The scRNA-seq was performed on 52,681 cells from 16 breast tissues, including tissues from noncarriers (n = 3) and carriers of germline mutations in BRCA1 (n = 6), BRCA2 (n = 6), or RAD51C (n = 1), spanning a range of ages (25–65) and parities (Table S1). Cells were analyzed by unsupervised graph-based clustering and visualized using Uniform Manifold Approximation and Projection (UMAPs) (see STAR Methods) (Figure S1A). MECs and stromal cells were distinguished by EPCAM expression (Figure 1B). Clusters were annotated as specific cell types based on canonical marker expression of the three established MEC lineages (AV, HS, and BA) and three stromal populations (fibroblasts, vascular/lymphatic cells, and immune cells) (Figures 1B and 1C). All cell types were detected in each sample, although their proportions varied substantially (Figure S1B). Gene expression signatures were generated for each cell type, which can serve as a benchmark for future cell-type identification and isolation (Figure 1D; Table S2). Concurrently, CyTOF was performed on 38 breast tissues (Table S1; ages 19–73, including noncarriers [n = 17] or carriers of germline mutations in BRCA1 [n = 9], BRCA2 [n = 11], or RAD51C [n = 1]), using our previously reported antibody panel recognizing 40 breast development and tumorigenesis markers (Rosenbluth et al., 2020Rosenbluth J.M. Schackmann R.C.J. Gray G.K. Selfors L.M. Li C.M. Boedicker M. Kuiken H.J. Richardson A. Brock J. Garber J. et al.Organoid cultures from normal and cancer-prone human breast tissues preserve complex epithelial lineages.Nat. Commun. 2020; 11: 1711Crossref PubMed Scopus (66) Google Scholar) (Figures S1C and S1D). To identify major cell types, the expression of these markers was quantified in 10,699,281 cells and visualized by UMAP for a subset of these cells (n = 751,970) (see STAR Methods). CyTOF revealed the same cell types as scRNA-seq (Figure 1E). EPCAM marked luminal MECs, but little or no EPCAM protein was detectable in BA cells despite their expression of low levels of EPCAM mRNA (Figures 1B and 1E). Nevertheless, BA cells were clearly distinct from stromal cells based on co-expression of BA lineage markers (K14, K17, and CD10) (Figures 1F and 1G). Luminal cells were further subdivided into the AV and HS types based on the expression of key markers CD133 and ANXA8 (AV) or GATA3 and MUC1 (HS) (Figures 1F and 1G). Stromal cells were identified by canonical markers for fibroblasts (CD140B and EGFR), vascular/lymphatic cells (CD31 for endothelial cells and smooth muscle actin [SMA] for pericytes), and immune cells (CD45) (Figures 1F and 1G). Each major cell type was present in each sample, albeit in considerably variable proportions (Figure S1E). Cell-type proportions correlated between modalities for three shared samples analyzed (Figure S1F). The heterogeneity within each lineage was investigated by sub-clustering of the scRNA-seq data of each major lineage (see STAR Methods) (Figure 2A). Among stromal cells, sub-clustering identified three fibroblast, three vascular/lymphatic, and five immune subtypes whose proportions were highly heterogeneous (Figures S2A–S2D). The fibroblast subtypes (F1–F3) were distinguished by high expression of (1) hormone receptors (HRs; ESR1, androgen receptor [AR], PRLR, and LEPR) and cathepsin proteases (CTSB/D/F), (2) tubulins (TUBB2A/B and TUBB6), and (3) fibulins (FBLN2/5) and ductal branching regulator SPRY1 (Koledova et al., 2016Koledova Z. Zhang X. Streuli C. Clarke R.B. Klein O.D. Werb Z. Lu P. SPRY1 regulates mammary epithelial morphogenesis by modulating EGFR-dependent stromal paracrine signaling and ECM remodeling.Proc. Natl. Acad. Sci. USA. 2016; 113: E5731-E5740Crossref PubMed Scopus (30) Google Scholar) (Figures S2C and S2D). Vascular/lymphatic cells included lymphatic endothelial cells (LYVE1, PDPN, and PROX1), vascular endothelial cells (SOX17, PLVAP, and SELE), and pericytes/smooth muscle cells (NOTCH3, ACTA2, and RGS5) (Figures S2C and S2D) (Kalucka et al., 2020Kalucka J. de Rooij L.P.M.H. Goveia J. Rohlenova K. Dumas S.J. Meta E. Conchinha N.V. Taverna F. Teuwen L.A. Veys K. et al.Single-cell transcriptome atlas of murine endothelial cells.Cell. 2020; 180: 764-779.e20Abstract Full Text Full Text PDF PubMed Scopus (281) Google Scholar; Li et al., 2020Li C.M. Shapiro H. Tsiobikas C. Selfors L.M. Chen H. Rosenbluth J. Moore K. Gupta K.P. Gray G.K. Oren Y. et al.Aging-associated alterations in mammary epithelia and stroma revealed by single-cell RNA sequencing.Cell Rep. 2020; 33: 108566Abstract Full Text Full Text PDF PubMed Google Scholar). Immune cells consisted of T cells (CD8+ or CD4+), myeloid cells (FCGR3A, CSF2RA, and LYVE1), plasma cells (IGKC or IGLC2/3/7), B cells, and natural killer cells (Figures S2C–S2E). These results are consistent with known breast stroma composition (Polyak, and Kalluri, 2010Polyak K. Kalluri R. The role of the microenvironment in mammary gland development and cancer.Cold Spring Harb. Perspect. Biol. 2010; 2: a003244Crossref PubMed Google Scholar). Finally, differential gene expression analyses provided systematically defined cell-subtype-specific signatures (Figure S2D; Table S2). Although the three MEC types identified via scRNA-seq are consistent with previous work (Henry et al., 2021Henry S. Trousdell M.C. Cyrill S.L. Zhao Y. Feigman M.J. Bouhuis J.M. Aylard D.A. Siepel A. Dos Santos C.O. Characterization of gene expression signatures for the identification of cellular heterogeneity in the developing mammary gland.J. Mammary Gland Biol. Neoplasia. 2021; 26: 43-66Crossref PubMed Scopus (5) Google Scholar; Nguyen et al., 2018Nguyen Q.H. Pervolarakis N. Blake K. Ma D. Davis R.T. James N. Phung A.T. Willey E. Kumar R. Jabart E. et al.Profiling human breast epithelial cells using single cell RNA sequencing identifies cell diversity.Nat. Commun. 2018; 9: 2028Crossref PubMed Scopus (132) Google Scholar), sub-clustering performed on each MEC lineage revealed less well-characterized subtypes (Figures 2B and 2C). Interestingly, two AV subtypes, termed basal-luminal (BL) and AV progenitor (AP) cells, were identified. Despite their overall AV phenotype (Figures 2A and S2F), BL cells, unlike AP cells, co-expressed intermediate levels of several BA (KRT5/14/17 and CAV1) and HS markers (MUC1, SERPINA1, and AGR2/3) (Figures 2D–2G and S2F; Table S2). Relative to AP cells, BL cells expressed high levels of the progenitor gene ALDH1A3 (Colacino et al., 2018Colacino J.A. Azizi E. Brooks M.D. Harouaka R. Fouladdel S. McDermott S.P. Lee M. Hill D. Madden J. Boerner J. et al.Heterogeneity of human breast stem and progenitor cells as revealed by transcriptional profiling.Stem Cell Rep. 2018; 10: 1596-1609Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Eirew et al., 2012Eirew P. Kannan N. Knapp D.J. Vaillant F. Emerman J.T. Lindeman G.J. Visvader J.E. Eaves C.J. Aldehyde dehydrogenase activity is a biomarker of primitive normal human mammary luminal cells.Stem Cells. 2012; 30: 344-348Crossref PubMed Scopus (63) Google Scholar; Ginestier et al., 2007Ginestier C. Hur M.H. Charafe-Jauffret E. Monville F. Dutcher J. Brown M. Jacquemier J. Viens P. Kleer C.G. Liu S. et al.ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome.Cell Stem Cell. 2007; 1: 555-567Abstract Full Text Full Text PDF PubMed Scopus (3072) Google Scholar; Shehata et al., 2012Shehata M. Teschendorff A. Sharp G. Novcic N. Russell I.A. Avril S. Prater M. Eirew P. Caldas C. Watson C.J. Stingl J. Phenotypic and functional characterisation of the luminal cell hierarchy of the mammary gland.Breast Cancer Res. 2012; 14: R134Crossref PubMed Scopus (198) Google Scholar) and low levels of the AV maturity driver ELF5 (Chakrabarti et al., 2012Chakrabarti R. Wei Y. Romano R.A. DeCoste C. Kang Y. Sinha S. Elf5 regulates mammary gland stem/progenitor cell fate by influencing notch signaling.Stem Cells. 2012; 30: 1496-1508Crossref PubMed Scopu