Lise Lotte Hansen

Quantitative comparison of DNA methylation assays for biomarker development and clinical applications

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

DOI

  • Christoph Bock, Max Planck Institute for Informatics
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  • Florian Halbritter, Austrian Academy of Sciences
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  • Francisco J. Carmona, L'Hospitalet de Llobregat
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  • Sascha Tierling, Saarland University
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  • Paul Datlinger, Austrian Academy of Sciences
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  • Yassen Assenov, German Cancer Research Center, Heidelberg
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  • María Berdasco, L'Hospitalet de Llobregat
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  • Anke K. Bergmann, University Hospital Schleswig-Holstein
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  • Keith Booher, Zymo Research Corporation
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  • Florence Busato, CEA-Institut de Génomique
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  • Mihaela Campan, University of Southern California
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  • Christina Dahl, Kræftens Bekæmpelse
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  • Christina M. Dahmcke, Kræftens Bekæmpelse
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  • Dinh Diep, University of California, San Diego
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  • Agustín F. Fernández, Nanomaterials and Nanotechnology Research Center (CINN-CSIC)
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  • Clarissa Gerhauser, German Cancer Research Center, Heidelberg
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  • Andrea Haake, Christian-Albrechts-Universität zu Kiel
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  • Katharina Heilmann, German Cancer Research Center, Heidelberg
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  • Thomas Holcomb, Oncology Biomarker Development
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  • Dianna Hussmann
  • Mitsuteru Ito, Cambridge University
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  • Ruth Kläver, Qiagen GmbH
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  • Martin Kreutz, Qiagen GmbH
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  • Marta Kulis, Universitat Autònoma Barcelona
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  • Virginia Lopez, Nanomaterials and Nanotechnology Research Center (CINN-CSIC)
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  • Shalima S. Nair, University of New South Wales (UNSW) Australia
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  • Dirk S. Paul, UCL
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  • Nongluk Plongthongkum, University of California, San Diego
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  • Wenjia Qu, Garvan Institute of Medical Research
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  • Ana C. Queirós, Universitat Autònoma Barcelona
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  • Frank Reinicke, Qiagen GmbH
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  • Guido Sauter, University Medical Center Hamburg-Eppendorf
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  • Thorsten Schlomm, University Medical Center Hamburg-Eppendorf
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  • Aaron Statham, Garvan Institute of Medical Research
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  • Clare Stirzaker, University of New South Wales (UNSW) Australia
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  • Ruslan Strogantsev, Cambridge University
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  • Rocío G. Urdinguio, Nanomaterials and Nanotechnology Research Center (CINN-CSIC)
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  • Kimberly Walter, Oncology Biomarker Development
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  • Dieter Weichenhan, German Cancer Research Center, Heidelberg
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  • Daniel J. Weisenberger, University of Southern California
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  • Stephan Beck, UCL
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  • Susan J. Clark, University of New South Wales (UNSW) Australia
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  • Manel Esteller, Theoretical and Computational Neuroscience Group, Center of Brain and Cognition, Universitat Pompeu Fabra, 08018 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain.
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  • Anne C. Ferguson-Smith, Cambridge University
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  • Mario F. Fraga, Nanomaterials and Nanotechnology Research Center (CINN-CSIC)
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  • Per Guldberg, Kræftens Bekæmpelse
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  • Lise Lotte Hansen
  • Peter W. Laird, Van Andel Research Institute
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  • José I. Martín-Subero, Universitat Autònoma Barcelona
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  • Anders O H Nygren, Agena Bioscience
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  • Ralf Peist, Qiagen GmbH
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  • Christoph Plass, German Cancer Research Center, Heidelberg
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  • David S. Shames, Oncology Biomarker Development
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  • Reiner Siebert, University Hospital of Ulm
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  • Xueguang Sun, Zymo Research Corporation
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  • Jörg Tost, CEA-Institut de Génomique
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  • Jörn Walter, Saarland University
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  • Kun Zhang, University of California, San Diego

DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.

Original languageEnglish
JournalNature Biotechnology
Volume34
Issue7
Pages (from-to)726-737
Number of pages12
ISSN1087-0156
DOIs
Publication statusPublished - 1 Jul 2016

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