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新方法可从单细胞转录组中解析出人类肿瘤中的拷贝数和克隆亚结构
作者:小柯机器人 发布时间:2021/1/21 11:34:12

美国德克萨斯大学MD安德森癌症中心Nicholas E. Navin团队开发出新方法,可从单细胞转录组中解析出人类肿瘤中的拷贝数和克隆亚结构。该研究于2021年1月18日在线发表于国际一流学术期刊《自然—生物技术》。

研究人员表示,单细胞转录组学分析被广泛用于研究人类肿瘤。然而,将肿瘤微环境中的正常细胞类型与恶性细胞区分开并解析肿瘤内的克隆亚结构仍然具有挑战性。

为了解决这些挑战,研究人员开发了一种集成的贝叶斯分割方法,称为非整倍体肿瘤的拷贝数染色体核型分析(CopyKAT),这个方法能够在高通量单细胞RNA测序(scRNA-seq)数据中以平均5 Mb的基因组分辨率来估算基因组拷贝数。研究人员使用CopyKAT分析了21种肿瘤中的46,501种单细胞,包括三阴性乳腺癌、胰腺导管腺癌、间变性甲状腺癌、浸润性导管癌和胶质母细胞瘤,并准确地(98%)区分了癌细胞与正常细胞类型。

在三种乳腺肿瘤中,CopyKAT解决了克隆性亚群,这些亚群在癌症基因(例如KRAS)的表达和特征(包括上皮到间质转化、DNA修复、细胞凋亡和缺氧)方面有所不同。这些数据表明,CopyKAT可以帮助分析各种实体人类肿瘤中的scRNA-seq数据。

附:英文原文

Title: Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes

Author: Ruli Gao, Shanshan Bai, Ying C. Henderson, Yiyun Lin, Aislyn Schalck, Yun Yan, Tapsi Kumar, Min Hu, Emi Sei, Alexander Davis, Fang Wang, Simona F. Shaitelman, Jennifer Rui Wang, Ken Chen, Stacy Moulder, Stephen Y. Lai, Nicholas E. Navin

Issue&Volume: 2021-01-18

Abstract: Single-cell transcriptomic analysis is widely used to study human tumors. However, it remains challenging to distinguish normal cell types in the tumor microenvironment from malignant cells and to resolve clonal substructure within the tumor. To address these challenges, we developed an integrative Bayesian segmentation approach called copy number karyotyping of aneuploid tumors (CopyKAT) to estimate genomic copy number profiles at an average genomic resolution of 5Mb from read depth in high-throughput single-cell RNA sequencing (scRNA-seq) data. We applied CopyKAT to analyze 46,501 single cells from 21 tumors, including triple-negative breast cancer, pancreatic ductal adenocarcinoma, anaplastic thyroid cancer, invasive ductal carcinoma and glioblastoma, to accurately (98%) distinguish cancer cells from normal cell types. In three breast tumors, CopyKAT resolved clonal subpopulations that differed in the expression of cancer genes, such as KRAS, and signatures, including epithelial-to-mesenchymal transition, DNA repair, apoptosis and hypoxia. These data show that CopyKAT can aid in the analysis of scRNA-seq data in a variety of solid human tumors.

DOI: 10.1038/s41587-020-00795-2

Source: https://www.nature.com/articles/s41587-020-00795-2

期刊信息

Nature Biotechnology:《自然—生物技术》,创刊于1996年。隶属于施普林格·自然出版集团,最新IF:31.864
官方网址:https://www.nature.com/nbt/
投稿链接:https://mts-nbt.nature.com/cgi-bin/main.plex