Sensitive digital quantification of DNA methylation in clinical samples (original) (raw)

Nature Biotechnology volume 27, pages 858–863 (2009)Cite this article

Abstract

Analysis of abnormally methylated genes is increasingly important in basic research and in the development of cancer biomarkers1,2. We have developed methyl-BEAMing technology to enable absolute quantification of the number of methylated molecules in a sample. Individual DNA fragments are amplified and analyzed either by flow cytometry3 or next-generation sequencing. We demonstrate enumeration of as few as one methylated molecule in ∼5,000 unmethylated molecules in DNA from plasma or fecal samples. Using methylated vimentin as a biomarker in plasma samples, methyl-BEAMing detected 59% of cancer cases. In early-stage colorectal cancers, this sensitivity was four times more than that obtained by assaying serum-carcinoembryonic antigen (CEA). With stool samples, methyl-BEAMing detected 41% of cancers and 45% of advanced adenomas. In addition to diagnostic and prognostic applications, this digital quantification of rare methylation events should be applicable to preclinical assessment of new epigenetic biomarkers and quantitative analyses in epigenetic research.

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References

  1. Sidransky, D. Emerging molecular markers of cancer. Nat. Rev. Cancer 2, 210–219 (2002).
    Article CAS Google Scholar
  2. Fleischhacker, M. & Schmidt, B. Circulating nucleic acids (CNAs) and cancer–a survey. Biochim. Biophys. Acta 1775, 181–232 (2007).
    CAS PubMed Google Scholar
  3. Dressman, D., Yan, H., Traverso, G., Kinzler, K.W. & Vogelstein, B. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc. Natl. Acad. Sci. USA 100, 8817–8822 (2003).
    Article CAS Google Scholar
  4. Feinberg, A.P. & Tycko, B. The history of cancer epigenetics. Nat. Rev. Cancer 4, 143–153 (2004).
    Article CAS Google Scholar
  5. Jones, P.A. & Baylin, S.B. The epigenomics of cancer. Cell 128, 683–692 (2007).
    Article CAS Google Scholar
  6. Laird, P.W. The power and the promise of DNA methylation markers. Nat. Rev. Cancer 3, 253–266 (2003).
    Article CAS Google Scholar
  7. Diehl, F. et al. Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proc. Natl. Acad. Sci. USA 102, 16368–16373 (2005).
    Article CAS Google Scholar
  8. Diehl, F. et al. Analysis of mutations in DNA isolated from plasma and stool of colorectal cancer patients. Gastroenterology 135, 489–498 (2008).
    Article CAS Google Scholar
  9. Bailey, V.J. et al. MS-qFRET: a quantum dot-based method for analysis of DNA methylation. Genome Res. 19, 1455–1461 (2009).
    Article CAS Google Scholar
  10. Hayatsu, H. The bisulfite genomic sequencing used in the analysis of epigenetic states, a technique in the emerging environmental genotoxicology research. Mutat. Res. 659, 77–82 (2008).
    Article CAS Google Scholar
  11. Herman, J.G., Graff, J.R., Myohanen, S., Nelkin, B.D. & Baylin, S.B. Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands. Proc. Natl. Acad. Sci. USA 93, 9821–9826 (1996).
    Article CAS Google Scholar
  12. Xiong, Z. & Laird, P.W. COBRA: a sensitive and quantitative DNA methylation assay. Nucleic Acids Res. 25, 2532–2534 (1997).
    Article CAS Google Scholar
  13. Gonzalgo, M.L. & Jones, P.A. Rapid quantitation of methylation differences at specific sites using methylation-sensitive single nucleotide primer extension (Ms-SNuPE). Nucleic Acids Res. 25, 2529–2531 (1997).
    Article CAS Google Scholar
  14. Lo, Y.M. et al. Quantitative analysis of aberrant p16 methylation using real-time quantitative methylation-specific polymerase chain reaction. Cancer Res. 59, 3899–3903 (1999).
    CAS PubMed Google Scholar
  15. Eads, C.A. et al. MethyLight: a high-throughput assay to measure DNA methylation. Nucleic Acids Res. 28, E32 (2000).
    Article CAS Google Scholar
  16. Vogelstein, B. & Kinzler, K.W. Digital PCR. Proc. Natl. Acad. Sci. USA 96, 9236–9241 (1999).
    Article CAS Google Scholar
  17. Grunau, C., Clark, S.J. & Rosenthal, A. Bisulfite genomic sequencing: systematic investigation of critical experimental parameters. Nucleic Acids Res. 29, E65 (2001).
    Article CAS Google Scholar
  18. Okamoto, A. Chemical approach toward efficient DNA methylation analysis. Org. Biomol. Chem. 7, 21–26 (2009).
    Article CAS Google Scholar
  19. Zou, H. et al. Highly methylated genes in colorectal neoplasia: implications for screening. Cancer Epidemiol. Biomarkers Prev. 16, 2686–2696 (2007).
    Article CAS Google Scholar
  20. Chen, W.D. et al. Detection in fecal DNA of colon cancer-specific methylation of the nonexpressed vimentin gene. J. Natl. Cancer Inst. 97, 1124–1132 (2005).
    Article CAS Google Scholar
  21. Jahr, S. et al. DNA fragments in the blood plasma of cancer patients: quantitations and evidence for their origin from apoptotic and necrotic cells. Cancer Res. 61, 1659–1665 (2001).
    CAS PubMed Google Scholar
  22. Diehl, F. et al. Circulating mutant DNA to assess tumor dynamics. Nat. Med. 14, 985–990 (2008).
    Article CAS Google Scholar
  23. Hundt, S., Haug, U. & Brenner, H. Comparative evaluation of immunochemical fecal occult blood tests for colorectal adenoma detection. Ann. Intern. Med. 150, 162–169 (2009).
    Article Google Scholar
  24. Lieberman, D.A. Screening for colorectal cancer. Clin. Cornerstone 4, 1–10 (2002).
    Article Google Scholar
  25. Kahi, C.J., Rex, D.K. & Imperiale, T.F. Screening, surveillance, and primary prevention for colorectal cancer: a review of the recent literature. Gastroenterology 135, 380–399 (2008).
    Article Google Scholar
  26. Humphrey, L.L., Helfand, M., Chan, B.K. & Woolf, S.H. Breast cancer screening: a summary of the evidence for the US Preventive Services Task Force. Ann. Intern. Med. 137, 347–360 (2002).
    Article Google Scholar
  27. Kent Moore, J., Smith, J.A., Whitney, D.H., Durkee, K.H. & Shuber, A.P. An electrophoretic capture method for efficient recovery of rare sequences from heterogeneous DNA. Biotechniques 44, 363–374 (2008).
    Article CAS Google Scholar
  28. Rago, C. et al. Serial assessment of human tumor burdens in mice by the analysis of circulating DNA. Cancer Res. 67, 9364–9370 (2007).
    Article CAS Google Scholar
  29. Warnecke, P.M. et al. Detection and measurement of PCR bias in quantitative methylation analysis of bisulphite-treated DNA. Nucleic Acids Res. 25, 4422–4426 (1997).
    Article CAS Google Scholar
  30. Diehl, F. et al. BEAMing: single-molecule PCR on microparticles in water-in-oil emulsions. Nat. Methods 3, 551–559 (2006).
    Article CAS Google Scholar

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Acknowledgements

We thank B. Berger for helpful discussions; D. Edelstein for the help with plasma collection; and M. Whalen and L. Kasturi for expert technical assistance. This work was supported by the Virginia and D.K. Ludwig Fund for Cancer Research; the Miracle Foundation; the Edelstein Fund; the US National Colorectal Cancer Research Alliance; The US National Institutes of Health grants CA43460,CA62924 and CA120237; The Danish Cancer Society; The Danish Research Council; and The Institute of Experimental Clinical Research, Aarhus University.

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Authors and Affiliations

  1. The Ludwig Center for Cancer Genetics and Therapeutics, Howard Hughes Medical Institute and Sidney Kimmel Cancer Center at the Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
    Meng Li, Nickolas Papadopoulos, Kerstin Schmidt, Yiping He, Frank Diehl, Victor E Velculescu, Shibin Zhou, Luis A Diaz Jr, Kenneth W Kinzler & Bert Vogelstein
  2. Department of Medicine and Ireland Cancer Center, Case Western Reserve University and Case Medical Center of University Hospitals of Cleveland and Howard Hughes Medical Institute, Cleveland, Ohio, USA
    Wei-dong Chen, Helen Moinova & Sanford D Markowitz
  3. Department of Biostatistics, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
    Steven N Goodman
  4. Department of Surgery P, Aarhus University Hospital, Aarhus, Denmark
    Niels Christian Bjerregaard & Søren Laurberg
  5. U.T.M.D. Anderson Cancer Center, Houston, Texas, USA
    Bernard Levin
  6. Indivumed, Center for Cancer Research at Israelitic Hospital, Hamburg, Germany
    Hartmut Juhl
  7. Tel Aviv University, Tel Aviv Medical Center and Sackler School of Medicine and Integrated Cancer Prevention Center, Tel Aviv, Israel
    Nadir Arber
  8. Exact Sciences Corp., Marlborough, Massachusetts, USA
    Kris Durkee

Authors

  1. Meng Li
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  2. Wei-dong Chen
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  3. Nickolas Papadopoulos
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  4. Steven N Goodman
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  5. Niels Christian Bjerregaard
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  6. Søren Laurberg
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  7. Bernard Levin
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  8. Hartmut Juhl
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  9. Nadir Arber
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  10. Helen Moinova
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  11. Kris Durkee
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  12. Kerstin Schmidt
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  13. Yiping He
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  14. Frank Diehl
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  15. Victor E Velculescu
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  16. Shibin Zhou
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  17. Luis A Diaz Jr
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  18. Kenneth W Kinzler
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  19. Sanford D Markowitz
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  20. Bert Vogelstein
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Contributions

M.L., S.D.M., S.N.G., K.W.K. and B.V. designed the project. M.L. developed the methyl-BEAMing assay and performed the experiments on plasma and fecal DNA. N.P., M.L. and Y.H. performed the Solexa sequencing experiments. H.M. performed the MSP assay. K.D. purified fecal DNA. S.N.G. provided statistical analysis. H.J., L.A.D., N.C.B., S.L., N.A. and K.S. collected clinical samples. W.-d.C., S.Z, V.E.V., F.D. and B.L. made intellectual contributions to the project. B.V., M.L. and S.D.M. wrote the manuscript.

Corresponding author

Correspondence toSanford D Markowitz.

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Competing interests

Technology for digital quantification of methylated DNA is the subject of a patent application from Johns Hopkins and Case Western Universities that include S.D.M., M.L., W.D.C., B.V. and K.W.K. as inventors. Under agreements between the Johns Hopkins University, Genzyme, Exact Sciences, Beckman, Inostics, and Invitrogen, K.W.K., B.V., M.L., and F.D. are entitled to a share of the royalties received by the University on sales of products related to BEAMing. Under agreements between Case Western University and Exact Sciences, S.D.M. and W.D.C. are entitled to a share of the royalties received on sales of products related to methylated vimentin DNA. Johns Hopkins University, K.W.K. and B.V. own stock in Genzyme and K.W.K., B.V., N.P., F.D. and L.D. own stock in Inostics, both of which are subject to certain restrictions under Johns Hopkins University policy. The terms of these arrangements are being managed by the universities in accordance with their conflict of interest policies.

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Li, M., Chen, Wd., Papadopoulos, N. et al. Sensitive digital quantification of DNA methylation in clinical samples.Nat Biotechnol 27, 858–863 (2009). https://doi.org/10.1038/nbt.1559

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