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.
Highlights
Altered DNA methylation is common in cancer and often considered an early event in tumorigenesis
To estimate the contribution of each functional class of variables in explaining total variation in DNA methylation, we pooled all variables in the same functional category and averaged across their importance and usage scores separately (Supplementary Fig. 4a,b). Results from both Random Forest and Elastic Net algorithms identified a considerable contribution from the variables within the SGOC metabolic network relative to other classes of variables (‘other SGOC enzymes’ was the second highest scoring among all classes, closely following ‘transcription factors’ according to both methods. ‘methionine cycle enzymes’ was the third and fourth according to Random Forest and Elastic Net, respectively) (Fig. 2a,b)
Given the contribution of the methionine cycle and its biochemical link to DNA methylation, we further explored the variables within the met cycle class compared with all other variables in their ability to predict DNA methylation (Fig. 2c)
Summary
Altered DNA methylation is common in cancer and often considered an early event in tumorigenesis. 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. This study represents a comprehensive analysis of the determinants of methylation and demonstrates the surprisingly large interaction between metabolism and DNA methylation variation. In addition to hypo- and hypermethylation, cancer cells exhibit increased variability in DNA methylation across large portions of the genome compared with their corresponding normal tissues[8,9]. We found a surprisingly large contribution for the expression of the methionine cycle and related SGOC network genes in explaining DNA methylation and identified numerous contexts, where this interaction may contribute to cancer pathology
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