Tumour evolution inferred by single-cell sequencing


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 common1,2,3, 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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Figure 1: Comparison of SK-BR-3 single cells to millions.
Figure 2: Analysis of 100 single cells from a polygenomic breast tumour.
Figure 3: Analysis of 100 single cells from a monogenomic breast tumour and its liver metastasis.
Figure 4: Genetically diverse pseudodiploid cells in the diploid fractions of tumours.

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Sequence Read Archive

Data deposits

All data has been deposited into the NCBI Sequence Read Archive under accession number SRA018951.105.


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We thank M. Ronemus, T. Spencer, A. Leotta, J. Meth, M. Kramer, L. Gelley, E. Ghiban. We also thank P. Blake and N. Navin at Sophic Systems Alliance. This work was supported by the NCI T32 Fellowship to N.N., and grants to M.W. and J.H. from the Department of the Army (W81XWH04-1-0477), the Breast Cancer Research Foundation, and the Simons Foundation. M.W. is an American Cancer Society Research Professor.

Author information

N.N. designed and performed experiments and analysis, and wrote the manuscript. J.K., A.K., L.M., D.L. and P.A. developed analysis programs. J.T., L.R., K.C., J.M., D.E. and A.S. performed experiments. W.R.M. designed experiments. J.H. and M.W. designed experiments, performed analysis and wrote manuscript.

Correspondence to Michael Wigler.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-8 with legends and Supplementary Methods. (PDF 4792 kb)

Supplementary Table 1

This table shows a summary of 100 Single Cells in the Polygenomic Tumor T10. (XLS 42 kb)

Supplementary Table 2

This table shows a summary of 100 Single Cells in T16P and T16M Metastatic Tumor Pair. (XLS 45 kb)

Supplementary Table 3

This table shows LOH and Copy Number in Tumor Subpopulations. (XLS 28 kb)

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Navin, N., Kendall, J., Troge, J. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011). https://doi.org/10.1038/nature09807

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