Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Abstract

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Experimental process for sequencing of CTCs.
Figure 2: Census-based variant calling from WES of CTCs from patient CRPC_36.
Figure 3: Comparison of mutation pattern across CTCs, primary cores and metastasized tumor from patient CRPC_36.

Similar content being viewed by others

References

  1. Garraway, L.A. Genomics-driven oncology: framework for an emerging paradigm. J. Clin. Oncol. 31, 1806–1814 (2013).

    Article  PubMed  Google Scholar 

  2. International Cancer Genome Consortium. et al. International network of cancer genome projects. Nature 464, 993–998 (2010); erratum 465, 966 (2010).

  3. Dawson, S.-J. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199–1209 (2013).

    Article  CAS  PubMed  Google Scholar 

  4. Cristofanilli, M. et al. Circulating tumor cells: a novel prognostic factor for newly diagnosed metastatic breast cancer. J. Clin. Oncol. 23, 1420–1430 (2005).

    Article  PubMed  Google Scholar 

  5. Zhang, L. et al. The identification and characterization of breast cancer CTCs competent for brain metastasis. Sci. Transl. Med. 5, 180ra48 (2013).

    Article  PubMed  Google Scholar 

  6. Yu, M. et al. Circulating tumor cells: approaches to isolation and characterization. J. Cell Biol. 192, 373–382 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Cohen, S.J. et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. J. Clin. Oncol. 26, 3213–3221 (2008).

    Article  PubMed  Google Scholar 

  8. Maheswaran, S. et al. Detection of mutations in EGFR in circulating lung-cancer cells. N. Engl. J. Med. 359, 366–377 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Heitzer, E. et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing. Cancer Res. 73, 2965–2975 (2013).

    Article  CAS  PubMed  Google Scholar 

  10. Ni, X. et al. Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients. Proc. Natl. Acad. Sci. USA 110, 21083–21088 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yu, M. et al. RNA sequencing of pancreatic circulating tumour cells implicates WNT signalling in metastasis. Nature 487, 510–513 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Allard, W.J. et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clin. Cancer Res. 10, 6897–6904 (2004).

    Article  PubMed  Google Scholar 

  13. Swennenhuis, J.F. et al. Efficiency of whole genome amplification of single circulating tumor cells enriched by CellSearch and sorted by FACS. Genome Med. 5, 106 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Hou, Y. et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148, 873–885 (2012).

    CAS  PubMed  Google Scholar 

  15. Zong, C. et al. Genome-wide detection of single-nucleotide and copy-number variations of a single human cell. Science 338, 1622–1626 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Cann, G.M. et al. mRNA-Seq of single prostate cancer circulating tumor cells reveals recapitulation of gene expression and pathways found in prostate cancer. PLoS ONE 7, e49144 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. El Gammal, A.T. et al. Chromosome 8p deletions and 8q gains are associated with tumor progression and poor prognosis in prostate cancer. Clin. Cancer Res. 16, 56–64 (2010).

    Article  CAS  PubMed  Google Scholar 

  18. Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Grasso, C.S. et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature 487, 239–243 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Beltran, H. et al. New strategies in prostate cancer: translating genomics into the clinic. Clin. Cancer Res. 19, 517–523 (2013).

    Article  CAS  PubMed  Google Scholar 

  21. Ross, R.W. et al. Predictors of prostate cancer tissue acquisition by an undirected core bone marrow biopsy in metastatic castration-resistant prostate cancer—a Cancer and Leukemia Group B study. Clin. Cancer Res. 11, 8109–8113 (2005).

    Article  CAS  PubMed  Google Scholar 

  22. Robbins, C.M. et al. Copy number and targeted mutational analysis reveals novel somatic events in metastatic prostate tumors. Genome Res. 21, 47–55 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Nickerson, M.L. et al. Somatic alterations contributing to metastasis of a castration-resistant prostate cancer. Hum. Mutat. 34, 1231–1241 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Chapman, P.B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 364, 2507–2516 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Heinrich, M.C. et al. Kinase mutations and imatinib response in patients with metastatic gastrointestinal stromal tumor. J. Clin. Oncol. 21, 4342–4349 (2003).

    Article  CAS  PubMed  Google Scholar 

  27. Lindberg, J. et al. Exome sequencing of prostate cancer supports the hypothesis of independent tumour origins. Eur. Urol. 63, 347–353 (2013).

    Article  CAS  PubMed  Google Scholar 

  28. Gole, J. et al. Massively parallel polymerase cloning and genome sequencing of single cells using nanoliter microwells. Nat. Biotechnol. 31, 1126–1132 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Murtaza, M. et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).

    Article  CAS  PubMed  Google Scholar 

  30. Barbieri, C.E. et al. Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat. Genet. 44, 685–689 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Oh, W.K. et al. Development of an integrated prostate cancer research information system. Clin. Genitourin. Cancer 5, 61–66 (2006).

    Article  PubMed  Google Scholar 

  32. Love, J.C. et al. A microengraving method for rapid selection of single cells producing antigen-specific antibodies. Nat. Biotechnol. 24, 703–707 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Fisher, S. et al. A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries. Genome Biol. 12, R1 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Stransky, N. et al. The mutational landscape of head and neck squamous cell carcinoma. Science 333, 1157–1160 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  36. DePristo, M.A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lawrence, M.S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Shalek, A.K. et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498, 236–240 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ramsköld, D. et al. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nat. Biotechnol. 30, 777–782 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Li, B. & Dewey, C. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Trapnell, C. et al. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

J.G.L. was supported by a Conquer Cancer Foundation Young Investigator Award, US National Institutes of Health grant 5P50CA100707-10 (DF/HCC SPORE) and the Wong Family Award. V.A.A. was supported in part by a graduate fellowship from the National Science Foundation. A.D.C. is supported by the Prostate Cancer Foundation Young Investigator Award and the Department of Defense Physician Scientist Training Award. J.C.L. is a Camille Dreyfus Teacher-Scholar. We acknowledge the Arthur and Linda Gelb Center for Translational Research for the acquisition and annotation of clinical samples and A. Abbott and A. Van Den Abbeele from the Dana-Farber Cancer Institute (DFCI) Department of Imaging for positron-emission tomography (PET) images. We also acknowledge P.K. Brastianos (Department of Medical Oncology, DFCI) and I. Dunn (Department of Neurosurgery, Brigham and Women's Hospital) for contributing samples for CTC analysis, D. Peck for help with technology development, O. Voznesensky and S. Balk for purification of DNA from the metastatic tumor for sequencing, C. Whittaker and S.S. Levine for advice on sequencing and analysis and the Broad Genomics Platform for the development of new sequencing approaches used here. This work was also supported in part by the Koch Institute Support (core) grant P30-CA14051 from the National Cancer Institute, and we thank the Koch Institute Swanson Biotechnology Center for technical support, specifically the BioMicroCenter. This work was also supported in part by Janssen Pharmaceuticals, Inc. and the Klarman Family Foundation. We would like to thank Illumina for providing the MagSweeper. The authors dedicate this paper to the memory of Officer Sean Collier, for his caring service to the MIT community and for his sacrifice.

Author information

Authors and Affiliations

Authors

Contributions

J.G.L. and V.A.A. designed and performed experiments, analyzed data and wrote the manuscript. K.C. and M.R. developed computational methods, analyzed data and wrote the manuscript. A.D.C. provided clinical samples and patient data and analyzed clinical data. P.C.-G., N. Tahirova and S.K. performed experiments for isolating CTCs. J.M.F. developed single-cell sequencing methods and designed experiments. C.-Z.Z. analyzed data and applied the autocorrelation methods. A.K.S., R.S., J.J.T. and D.L. performed single-cell RNA sequencing and data analysis. N. Tallapragada developed code for determining CTCs to recover from nanowells. B.B. performed early technology development. C.S. and D.A. performed sample and data management and gave conceptual advice. A. Lowe and A. Ly performed experiments comparing our process to the Veridex CellSearch System. E.M.V.A. analyzed sequencing data. M.N., G.-S.M.L., T.L. and M.S.C. coordinated and acquired clinical samples. R.T.L. reviewed pathology slides and guided selection of clinical samples. B.W. performed data visualization. T.E.C. provided samples and validated methods for isolating CTCs. M.-E.T., M.L., A.R., M.M., W.C.H. and P.W.K. supervised experiments and sample and data collection and edited the manuscript. T.R.G., G.G., J.S.B. and J.C.L. designed the experimental strategy, supervised the analysis and wrote the manuscript. All authors discussed the results and implications and reviewed the manuscript.

Corresponding authors

Correspondence to Gad Getz, Jesse S Boehm or J Christopher Love.

Ethics declarations

Competing interests

J.C.L. is a founder and shareholder of Enumeral Biomedical Corp., holding a license for a patent on the specific design of the nanowells used in this study.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Table 1 (PDF 3083 kb)

Supplementary Table 2

Sequencing metrics (XLSX 42 kb)

Supplementary Table 3

List of SSNVs called in patient CRPC_36 (XLSX 96 kb)

Supplementary Table 4

List of SSNVs called in patient CRPC_10 (XLSX 27 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lohr, J., Adalsteinsson, V., Cibulskis, K. et al. Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer. Nat Biotechnol 32, 479–484 (2014). https://doi.org/10.1038/nbt.2892

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.2892

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer