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Integrative modelling of tumour DNA methylation quantifies the contribution of metabolism

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  • Mahya Mehrmohamadi

    (Duke Cancer Institute, Duke University School of Medicine
    Duke Molecular Physiology Institute, Duke University School of Medicine
    Duke University School of Medicine
    Field of Genetics, Genomics and Development, Cornell University)

  • Lucas K. Mentch

    (Cornell University)

  • Andrew G. Clark

    (Field of Genetics, Genomics and Development, Cornell University
    Cornell University)

  • Jason W. Locasale

    (Duke Cancer Institute, Duke University School of Medicine
    Duke Molecular Physiology Institute, Duke University School of Medicine
    Duke University School of Medicine)

Abstract

Altered DNA methylation is common in cancer and often considered an early event in tumorigenesis. However, the sources of heterogeneity of DNA methylation among tumours remain poorly defined. Here we capitalize on the availability of multi-platform data on thousands of human tumours to build integrative models of DNA methylation. We quantify the contribution of clinical and molecular factors in explaining intertumoral variability in DNA methylation. We show that the levels of a set of metabolic genes involved in the methionine cycle is predictive of several features of DNA methylation in tumours, including the methylation of cancer genes. Finally, we demonstrate that patients whose DNA methylation can be predicted from the methionine cycle exhibited improved survival over cases where this regulation is disrupted. This study represents a comprehensive analysis of the determinants of methylation and demonstrates the surprisingly large interaction between metabolism and DNA methylation variation. Together, our results quantify links between tumour metabolism and epigenetics and outline clinical implications.

Suggested Citation

  • Mahya Mehrmohamadi & Lucas K. Mentch & Andrew G. Clark & Jason W. Locasale, 2016. "Integrative modelling of tumour DNA methylation quantifies the contribution of metabolism," Nature Communications, Nature, vol. 7(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms13666
    DOI: 10.1038/ncomms13666
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