A human breast atlas integrating single-cell proteomics and transcriptomics.

A human breast atlas integrating single-cell proteomics and transcriptomics.
复制标题

整合单细胞蛋白质组学和转录组学的人类乳房图集。

DOI:
10.1016/j.devcel.2022.05.003
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发表时间:
2022-06-06
期刊:
影响因子:
11.8
通讯作者:
Brugge, Joan S.
Brugge, Joan S.
中科院分区:
生物学1区
文献类型:
--
作者:
Gray, G. Kenneth;Li, Carman Man-Chung;Rosenbluth, Jennifer M.;Selfors, Laura M.;Girnius, Nomeda;Lin, Jia-Ren;Schackmann, Ron C. J.;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.

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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不清楚。我们通过整合单细胞 RNA-seq、质谱流式细胞仪和循环免疫荧光技术,提供了一个统一的、高分辨率的乳腺图谱,涵盖了多种状态。我们定义了肺泡、激素感应和基底上皮谱系内的细胞亚型,描绘了几种亚型与癌症危险因素(包括年龄、胎次和 BRCA2 种系突变)的关联。特别令人感兴趣的是肺泡细胞的一个子集,称为基底腔(BL)细胞,其转录谱系保真度较差,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。我们进一步利用介质消耗方法来识别调节类器官中细胞亚型比例的分子因子。这些数据共同构成了阐明不同乳腺细胞状态的丰富资源。格雷、李、罗森布鲁斯、塞尔福斯等人。生成乳腺组织和类器官的多维图谱。研究发现不同的上皮亚型与年龄、胎次和 BRCA2 突变有关。称为基底腔细胞的肺泡亚群表现出较差的转录谱系保真度和与侵袭性基底样乳腺癌相关的基因表达特征。
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 exhibits poor transcriptional lineage fidelity, accumulates with age, and carries 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. Gray, Li, Rosenbluth, Selfors et al. generate a multi-dimensional atlas of breast tissues and organoids. Distinct epithelial subtypes are found to be associated with age, parity, and BRCA2 mutation. An alveolar subset termed basal-luminal cells display poor transcriptional lineage fidelity and gene expression signatures associated with aggressive basal-like breast cancers.
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