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Tracking the evolution of cancer methylomes

Nature Genetics volume 44, pages 1173–1174 (2012)Cite this article

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Cellular transformation in cancer has long been associated with aberrant DNA methylation, most notably, hypermethylation of promoter sequences. A new study uses a clever approach of selective high-resolution profiling to follow DNA methylation over a time course of cellular transformation and challenges the notion that hypermethylation in cancer arises in an orchestrated fashion.

In mammals, methylation of cytosines is an epigenetic mark found primarily at CpG dinucleotides and is associated with transcriptional repression. Aberrations in the normal genomic patterns of DNA methylation were first associated with cancer 30 years ago1. This opened a field of research that led to clinical applications that use methylation as a biomarker in diagnosis2. However, the order of events leading to an aberrant epigenome remains unclear. One hypothesis is that selection favors methylation and silencing at the promoters of genes important for normal cell homeostasis2. Recent technical advances in sequencing technologies allowed the generation of a complete map of the genomic regions susceptible to methylation changes in a particular cancer type3, and large initiatives are geared up to provide complete maps for an even wider spectrum of tumors4. Although these maps will further enhance our knowledge of epigenetic aberrations in cancer, they provide limited information on the sequence of events that lead to the diseased state. Such deeper understanding of the events that generate epigenetic abnormalities is likely a prerequisite of a correct understanding of the functional consequences of methylation changes and the development of models that describe how aberrant methylation occurs. Such time-course data should answer the questions of when changes arise during transformation and if these changes occur in a stochastic or deterministic fashion. More specifically, these data should determine whether changes accumulate continuously or in bursts and assess the methylation heterogeneity within a population of either normal or transformed cells. On page 1207 of this issue, Amos Tanay and colleagues report an original approach that combines the use of an in vitro evolution system that mimics cancer progression with deep-coverage methylation profiling5. Their results suggest that a stochastic series of subtle methylation changes in cancer evolution leads to deterministic methylation profiles.

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Figure 1: The ability to detect polymorphic methylation patterns depends on the depth of coverage with which a particular region is sequenced.

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  1. Arnaud R. Krebs and Dirk Schübeler are at the Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.,

    Arnaud R Krebs & Dirk Schübeler

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  1. Arnaud R Krebs
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  2. Dirk Schübeler
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Correspondence to Dirk Schübeler.

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The authors declare no competing financial interests.

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Krebs, A., Schübeler, D. Tracking the evolution of cancer methylomes. Nat Genet 44, 1173–1174 (2012). https://doi.org/10.1038/ng.2451

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