Tumour evolution inferred by single-cell sequencing

Navin, N. E., Kendall, J. T., Troge, J. E., Andrews, P., Rodgers,  L., McIndoo, J., Cook, K., Stepansky,  A., Levy, D., Esposito, D., Muthuswamy, L., Krasnitz, A., McCombie, W. R., Hicks, J. B., Wigler, M. H. (2011) Tumour evolution inferred by single-cell sequencing. Nature, 472 (7341). pp. 90-94. ISSN 00280836 (ISSN)

URL: http://www.ncbi.nlm.nih.gov/pubmed/21399628
DOI: 10.1038/nature09807

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 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.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > annotation > sequence annotation
bioinformatics > genomics and proteomics > analysis and processing > Sequence Data Processing
Investigative techniques and equipment > assays
diseases & disorders > cancer > cancer types > breast cancer
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > copy number variants
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene amplification
CSHL Authors:
Communities: CSHL Cancer Center Shared Resources > DNA Sequencing Service
CSHL Cancer Center Shared Resources > Flow Cytometry Service
CSHL Cancer Center Shared Resources > Instrumentation Service
CSHL Cancer Center Shared Resources > Microscopy Service
CSHL labs > Hicks lab
CSHL labs > Krasnitz lab
CSHL labs > McCombie lab
CSHL labs > Wigler lab
CSHL Cancer Center Program > Cancer Genetics
Depositing User: CSHL Librarian
Date Deposited: 05 Apr 2012 16:24
Last Modified: 26 Jan 2017 20:28
PMCID: PMC4504184
Related URLs:
URI: http://repository.cshl.edu/id/eprint/26034

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