Abstract
The ability to accurately measure aberrant DNA methylation levels is integral to the understanding of DNA methylation biology. It is well-established that in cancer, the largest, and thus, most biologically important absolute gains of DNA methylation levels occur at CpG sites with low native levels while the largest losses occur at CpG sites with high native levels. Conventional wisdom assumes that the observed association between the degree of the alterations and the native levels are largely due to the limitations of change within the DNA methylation scale. Here, we present evidence that this association is largely caused by alterations occurring as a global rate of change relative to the native level. We show that DNA methylation alterations can be accurately compared by calculating the rate of change relative to the native level. Most importantly, this approach enables the identification of more biologically significant DNA methylation alterations.
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Data availability
3BKO and 3ABDKO cell line data was downloaded from the Gene Expression Omnibus (GEO) database (GSE51815. and GSE68344). The TCGA tumor DNA methylation data, mutational data, RNA sequencing data and clinical data were downloaded from the Firebrowse site (http://firebrowse.org).
Code availability
The OutlierMeth package is on GitHub (https://github.com/bdowns4/OutlierMeth)38 and the custom code used for the analyses in this study is available upon reasonable request. The R version 4.2.3 was used for the analysis in this manuscript.
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Acknowledgements
The authors would like to thank Dr. Claudia Mercado Rodriguez, Dr. Harharan Easwaran, Dr. Leslie Cope, and Dr. Christopher Umbricht for their generous advice for the preparation of this manuscript. We would also like to thank all of the students of the Tza-Huei Wang lab for their support.
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B.D. conceived the idea for this work. B.D. completed the bioinformatic analysis. J.H., J.P., H.L., T.W., T.R.P., K.H., and T.H. wrote, designed and contributed to the interpretation of the data and the preparation of the manuscript.
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Downs, B.M., Hu, J., Park, J.S. et al. An unbiased approach to measure aberrant DNA methylation alterations. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71089-5
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DOI: https://doi.org/10.1038/s41467-026-71089-5
