• A Correction to this article was published on 30 April 2018


Changes in DNA methylation in cancer have been heralded as promising targets for the development of powerful diagnostic, prognostic, and predictive biomarkers. Despite the existence of more than 14,000 scientific publications describing DNA methylation-based biomarkers and their clinical associations in cancer, only 14 of these biomarkers have been translated into a commercially available clinical test. Methodological and experimental obstacles are both major causes of this disparity, but the genomic location of a DNA methylation-based biomarker is an intrinsic and essential property that also has an important and often overlooked role. Here, we examine the importance of the location of DNA methylation for the development of cancer biomarkers, and take a detailed look at the genomic location and other relevant characteristics of the various biomarkers with commercially available tests. We also emphasize the value of publicly available databases for the development of DNA methylation-based biomarkers and the importance of accurate reporting of the full methodological details of research findings.

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The work of the authors is supported financially by the Maag Lever Darm Stichting (MLDS, grant FP13-15), the Universiteitsfonds Limburg/SWOL, and an SU2C- DCS International Translational Cancer Research Dream Team Grant (Stand Up To Cancer (SU2C)-AACR- DT1415, MEDOCC). SU2C is a programme of the Entertainment Industry Foundation administered by the American Association for Cancer Research.

Author information


  1. Department of Pathology, GROW — School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, Netherlands

    • Alexander Koch
    • , Zheng Feng
    • , Muriel X. Draht
    • , Veerle Melotte
    • , Kim M. Smits
    • , Leander Van Neste
    •  & Manon van Engeland
  2. Division of Medical Oncology, Department of Internal Medicine, GROW — School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, Netherlands

    • Sophie C. Joosten
    • , Tim C. de Ruijter
    • , Kim M. Smits
    •  & Jurgen Veeck
  3. Lung Cancer Program, University of Pittsburgh Cancer Institute, The Hillman Cancer Center, Pittsburgh, PA, USA

    • James G. Herman
  4. BioBix: Laboratory of Bioinformatics and Computational Genomics, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium

    • Wim Van Criekinge
  5. Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium

    • Tim De Meyer


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A.K., S.C.J., and M.v.E. researched data for the article, all authors made a substantial contribution to discussion of content, A.K., S.C.J., and M.v.E. wrote the manuscript, and all authors reviewed and/or edited the manuscript before submission.

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M.v.E. receives research funding from MDxHealth. W.V.C. is a consultant of MDxHealth. The other authors declare no competing interests.

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Correspondence to Manon van Engeland.

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