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利用单细胞转录组分析研究癌症发生的进化视角。

Investigating evolutionary perspective of carcinogenesis with single-cell transcriptome analysis.

作者信息

Zhang Xi, Zhang Cheng, Li Zhongjun, Zhong Jiangjian, Weiner Leslie P, Zhong Jiang F

机构信息

Department of Pathology, University of Southern California, Keck School of Medicine, Los Angeles, CA 90033, USA; 2Z-Genetic Medicine LLC, Temple City, CA 91780, USA.

出版信息

Chin J Cancer. 2013 Dec;32(12):636-9. doi: 10.5732/cjc.012.10291. Epub 2013 May 27.

Abstract

We developed phase-switch microfluidic devices for molecular profiling of a large number of single cells. Whole genome microarrays and RNA-sequencing are commonly used to determine the expression levels of genes in cell lysates (a physical mix of millions of cells) for inferring gene functions. However, cellular heterogeneity becomes an inherent noise in the measurement of gene expression. The unique molecular characteristics of individual cells, as well as the temporal and quantitative information of gene expression in cells, are lost when averaged among all cells in cell lysates. Our single-cell technology overcomes this limitation and enables us to obtain a large number of single-cell transcriptomes from a population of cells. A collection of single-cell molecular profiles allows us to study carcinogenesis from an evolutionary perspective by treating cancer as a diverse population of cells with abnormal molecular characteristics. Because a cancer cell population contains cells at various stages of development toward drug resistance, clustering similar single-cell molecular profiles could reveal how drug-resistant sub-clones evolve during cancer treatment. Here, we discuss how single-cell transcriptome analysis technology could enable the study of carcinogenesis from an evolutionary perspective and the development of drug-resistance in leukemia. The single-cell transcriptome analysis reported here could have a direct and significant impact on current cancer treatments and future personalized cancer therapies.

摘要

我们开发了用于大量单细胞分子谱分析的相切换微流控装置。全基因组微阵列和RNA测序通常用于确定细胞裂解物(数百万个细胞的物理混合物)中基因的表达水平,以推断基因功能。然而,细胞异质性成为基因表达测量中固有的噪声。当在细胞裂解物中的所有细胞之间进行平均时,单个细胞的独特分子特征以及细胞中基因表达的时间和定量信息就会丢失。我们的单细胞技术克服了这一限制,使我们能够从一群细胞中获得大量的单细胞转录组。单细胞分子谱的集合使我们能够通过将癌症视为具有异常分子特征的多样化细胞群体,从进化的角度研究致癌作用。由于癌细胞群体包含处于耐药性发展各个阶段的细胞,对相似的单细胞分子谱进行聚类可以揭示耐药亚克隆在癌症治疗过程中是如何进化的。在这里,我们讨论单细胞转录组分析技术如何能够从进化的角度研究致癌作用以及白血病中耐药性的发展。本文报道的单细胞转录组分析可能会对当前的癌症治疗和未来的个性化癌症治疗产生直接而重大的影响。

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