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Hybrid Stem Cell States: Insights Into the Relationship Between Mammary Development and Breast Cancer Using Single-Cell Transcriptomics

机译:杂交干细胞状态:使用单细胞转录组学识别乳腺癌患者乳腺癌与乳腺癌关系的见解

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摘要

Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M). Hybrid E/M cells in particular have been implicated in breast cancer metastasis and poor prognosis. Mounting evidence also suggests that stem cell phenotypes change throughout the life course, for example, through embryonic development and pregnancy. The goal of this study was to use single cell RNA-sequencing to quantify cell state distributions of the normal mammary (NM) gland throughout developmental stages and when perturbed into a stem-like state in vitro using conditional reprogramming (CR). Using machine learning based dataset alignment, we integrate multiple mammary gland single cell RNA-seq datasets from human and mouse, along with bulk RNA-seq data from breast tumors in the Cancer Genome Atlas (TCGA), to interrogate hybrid stem cell states in the normal mammary gland and cancer. CR of human mammary cells induces an expanded stem cell state, characterized by increased expression of embryonic stem cell associated genes. Alignment to a mouse single-cell transcriptome atlas spanning mammary gland development from in utero to adulthood revealed that NM cells align to adult mouse cells and CR cells align across the pseudotime trajectory with a stem-like population aligning to the embryonic mouse cells. Three hybrid populations emerge after CR that are rare in NM: KRT18+/KRT14+ (hybrid luminal/basal), EPCAM+/VIM+ (hybrid E/M), and a quadruple positive population, expressing all four markers. Pseudotime analysis and alignment to the mouse developmental trajectory revealed that E/M hybrids are the most developmentally immature. Analyses of single cell mouse mammary RNA-seq throughout pregnancy show that during gestation, there is an enrichment of hybrid E/M cells, suggesting that these cells play an important role in mammary morphogenesis during lactation. Finally, pseudotime analysis and alignment of TCGA breast cancer expression data revealed that breast cancer subtypes express distinct developmental signatures, with basal tumors representing the most “developmentally immature” phenotype. These results highlight phenotypic plasticity of normal mammary stem cells and provide insight into the relationship between hybrid cell populations, stemness, and cancer.
机译:干细胞和癌细胞之间的相似性在乳腺发生中具有含有乳腺干细胞的乳腺干细胞。最近的证据表明,在多个表型状态存在正常乳腺干细胞:上皮细胞,间充质和上皮混合/间质(E / M)。特别是杂交E / m细胞涉及乳腺癌转移和预后差。安装证据还表明干细胞表型在整个寿命过程中发生变化,例如,通过胚胎发育和妊娠。本研究的目的是使用单细胞RNA测序在整个发育阶段中量化正常乳腺(NM)腺体的细胞状态分布,并且当使用条件重编程(CR)在体外扰乱到干燥的状态时。采用基于机器学习的数据集对准,我们将多个乳腺单细胞RNA-SEQ数据集与人和小鼠集成,以及来自癌症基因组Atlas(TCGA)的乳腺肿瘤的批量RNA-SEQ数据,以询问杂交干细胞状态正常乳腺和癌症。人乳腺细胞的Cr诱导扩增的干细胞状态,其特征征通过增加胚胎干细胞相关基因的表达。对一对小鼠单细胞转录瘤地图集的对齐培养乳腺从子宫到成年的发展显示,NM细胞与成年小鼠细胞对齐,并且CR细胞与副腔轨迹对齐,其与胚胎小鼠细胞对齐的干燥群。在NM中罕见的CR罕见的杂交种群中出现:KRT18 + / KRT14 +(杂交腔/基础),EPCAM + / Vim +(杂交E / M)和四重阳性群,表达所有四个标记。对小鼠发育轨迹的假尺分析和对准显示E / M杂种是最不成熟的。单细胞小鼠乳腺RNA-seq的分析的整个孕期表明,妊娠期间,有混合动力E / M细胞的富集,表明这些细胞在哺乳期间发挥乳腺形态发生中起重要作用。最后,TCGA乳腺癌表达数据的假息分析和对准显示,乳腺癌亚型表达明显的发育签名,基底肿瘤代表最“发育不成熟”的表型。这些结果突出了正常乳腺干细胞的表型可塑性,并对杂交细胞群,茎秆和癌症之间的关系提供了洞察力。

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