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.

乳房是一个动态器官，其对生理和病理生理条件的反应会改变其疾病易感性，但这些临床变量对细胞状态的具体影响仍未得到充分说明。我们通过整合单细胞 RNA-seq、质谱流式细胞术和循环免疫荧光，呈现了一个统一的、高分辨率的乳腺图谱，涵盖了无数种状态。我们定义了肺泡、激素感应和基底上皮细胞谱系中的细胞亚型，描述了几种亚型与癌症风险因素（包括年龄、胎次和BRCA2）的关联种系突变。特别感兴趣的是称为基底管腔 (BL) 细胞的肺泡细胞亚群，其表现出较差的转录谱系保真度，随着年龄的增长而积累，并携带与基底样乳腺癌相关的基因特征。我们进一步利用中等耗竭方法来识别调节类器官中细胞亚型比例的分子因素。总之，这些数据是阐明不同乳腺细胞状态的丰富资源。