A human breast atlas integrating single-cell proteomics and transcriptomics
- Gray, G Kenneth;
- Li, Carman Man-Chung;
- Rosenbluth, Jennifer M;
- Selfors, Laura M;
- Girnius, Nomeda;
- Lin, Jia-Ren;
- Schackmann, Ron CJ;
- Goh, Walter L;
- Moore, Kaitlin;
- Shapiro, Hana K;
- Mei, Shaolin;
- D'Andrea, Kurt;
- Nathanson, Katherine L;
- Sorger, Peter K;
- Santagata, Sandro;
- Regev, Aviv;
- Garber, Judy E;
- Dillon, Deborah A;
- Brugge, Joan S
- et al.
Published Web Location
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202341/Abstract
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.
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