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. 2012;7(1):e29686.
doi: 10.1371/journal.pone.0029686. Epub 2012 Jan 3.

Reproducibility and concordance of differential DNA methylation and gene expression in cancer

Chen Yao  1 , Hongdong Li, Xiaopei Shen, Zheng He, Lang He, Zheng Guo
Affiliations

Reproducibility and concordance of differential DNA methylation and gene expression in cancer

Chen Yao et al. PLoS One. 2012.

Abstract

Background: Hundreds of genes with differential DNA methylation of promoters have been identified for various cancers. However, the reproducibility of differential DNA methylation discoveries for cancer and the relationship between DNA methylation and aberrant gene expression have not been systematically analysed.

Methodology/principal findings: Using array data for seven types of cancers, we first evaluated the effects of experimental batches on differential DNA methylation detection. Second, we compared the directions of DNA methylation changes detected from different datasets for the same cancer. Third, we evaluated the concordance between methylation and gene expression changes. Finally, we compared DNA methylation changes in different cancers. For a given cancer, the directions of methylation and expression changes detected from different datasets, excluding potential batch effects, were highly consistent. In different cancers, DNA hypermethylation was highly inversely correlated with the down-regulation of gene expression, whereas hypomethylation was only weakly correlated with the up-regulation of genes. Finally, we found that genes commonly hypomethylated in different cancers primarily performed functions associated with chronic inflammation, such as 'keratinization', 'chemotaxis' and 'immune response'.

Conclusions: Batch effects could greatly affect the discovery of DNA methylation biomarkers. For a particular cancer, both differential DNA methylation and gene expression can be reproducibly detected from different studies with no batch effects. While DNA hypermethylation is significantly linked to gene down-regulation, hypomethylation is only weakly correlated with gene up-regulation and is likely to be linked to chronic inflammation.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Batch effects on tumour samples for nine cancer types.
(a) different batches and different laboratories; (b) the same laboratory but different batches; (c) the same batch but different laboratories; (d) Hierarchical clustering the tumour samples of ovarian serous cystadenocarcinoma in batch 9 and batch 12. For a cancer type denoted in the x-axis in graph a, b or c, a box plot in the y-axis represents the percentage of probes significantly susceptible to different batch conditions. The percentage takes value ranging from 0 (no susceptible probe) to 1 (100% susceptible probes). Each box stretches from the lower hinge (defined as the 25th percentile) to the upper hinge (the 75th percentile) and the median is shown as a line across the box.
Figure 2
Figure 2. Batch effects on DM genes of six cancer types.
For each cancer type denoted in the x-axis, a box plot in the y-axis represents the consistency score defined as the proportion of DM genes with consistent methylation states among all overlapping DM gene commonly detected in both of the two groups (see ‘Methods’ section). The consistency score takes value ranging from 0 (no consistent states) to 1 (100% consistent states). Each box stretches from the lower hinge (defined as the 25th percentile) to the upper hinge (the 75th percentile) and the median is shown as a line across the box.
See this image and copyright information in PMC

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