Unknown

Dataset Information

Tumour evolution inferred by single-cell sequencing.


ABSTRACT: 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 sin

SUBMITTER: Navin N 

PROVIDER: S-EPMC4504184 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature