使用单细胞表观遗传和转录组分析定义乳腺癌的调控逻辑。

IF 11.1 Q1 CELL BIOLOGY
Cell genomics Pub Date : 2025-02-12 Epub Date: 2025-02-05 DOI:10.1016/j.xgen.2025.100765
Matthew J Regner, Susana Garcia-Recio, Aatish Thennavan, Kamila Wisniewska, Raul Mendez-Giraldez, Brooke Felsheim, Philip M Spanheimer, Joel S Parker, Charles M Perou, Hector L Franco
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引用次数: 0

摘要

解释驱动癌细胞转录失调的顺式调控元件对理解肿瘤生物学至关重要。在此,我们在手术切除后立即处理的人类乳腺肿瘤和健康乳腺组织中,提供了匹配的单细胞分辨率染色质可及性(通过测序[scATAC-seq]进行转座酶可及性染色质单细胞检测)和转录组(单细胞RNA测序[scRNA-seq])谱。我们确定了亚型特异性乳腺肿瘤最可能的起源细胞,并实施线性混合效应模型,以量化恶性细胞与正常细胞中调节元件和基因表达之间的关联。这些数据揭示了导致临床相关癌基因上调的细胞中癌症特异性调控元件和推定的沉默-增强转换事件。此外,我们为乳腺癌细胞系生成了匹配的scATAC-seq和scRNA-seq谱,揭示了体外和体内细胞之间保守的致癌基因表达程序。这项工作强调了非编码调控机制在致癌过程中的重要性,以及单细胞多组学定义癌细胞调控逻辑的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling.

Annotation of cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to understanding tumor biology. Herein, we present matched chromatin accessibility (single-cell assay for transposase-accessible chromatin by sequencing [scATAC-seq]) and transcriptome (single-cell RNA sequencing [scRNA-seq]) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell of origin for subtype-specific breast tumors and implement linear mixed-effects modeling to quantify associations between regulatory elements and gene expression in malignant versus normal cells. These data unveil cancer-specific regulatory elements and putative silencer-to-enhancer switching events in cells that lead to the upregulation of clinically relevant oncogenes. In addition, we generate matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing a conserved oncogenic gene expression program between in vitro and in vivo cells. This work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of cancer cells.

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