Tumour evolution inferred by single-cell sequencing

生物 单细胞测序 转移 人口 遗传异质性 单细胞分析 拷贝数变化 DNA测序 肿瘤异质性 遗传学 癌症 进化生物学 基因组 细胞 基因 癌症的体细胞进化 表型 外显子组测序 社会学 人口学
作者
Nicholas Navin,Jude Kendall,Jennifer Troge,Peter M. Andrews,Linda Rodgers,Jeanne McIndoo,Kerry Cook,Asya Stepansky,Dan Levy,Diane Esposito,Lakshmi Muthuswamy,A. Krasnitz,W. Richard McCombie,James Hicks,Michael Wigler
出处
期刊:Nature [Springer Nature]
卷期号:472 (7341): 90-94 被引量:2328
标识
DOI:10.1038/nature09807
摘要

Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.
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