G. Kenneth Gray*, Carman Man-Chung Li*, Jennifer M. Rosenbluth*, Laura M. Selfors*, Nomeda Girnius, Jia-Ren Lin, Ron C.J. Schackmann, Walter L. Goh, Kaitlin Moore, Hana K. Shapiro, Shaolin Mei, Kurt D’Andrea, Katherine L. Nathanson, Peter K. Sorger, Sandro Santagata, Aviv Regev, Judy E. Garber, Deborah A. Dillon, Joan S. Brugge, A human breast atlas integrating single-cell proteomics and transcriptomics, Developmental Cell, 2022, ISSN 1534-5807, https://doi.org/10.1016/j.devcel.2022.05.003.

*co-first authors, in alphabetical order

Summary

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 scRNA-seq data are deposited here on the Single Cell Portal, while the CyTOF data are deposited on Mendeley Data at the following links:

CyTOF primary tissue raw data https://data.mendeley.com/datasets/pcftzv8w63/1

CyTOF primary tissue processed data https://data.mendeley.com/datasets/vs8m5gkyfn/1

CyTOF organoid data https://data.mendeley.com/datasets/f2v94hj7jm/1