Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 10 (1), 2188

Chromatin Dysregulation and DNA Methylation at Transcription Start Sites Associated With Transcriptional Repression in Cancers

Affiliations

Chromatin Dysregulation and DNA Methylation at Transcription Start Sites Associated With Transcriptional Repression in Cancers

Mizuo Ando et al. Nat Commun.

Erratum in

Abstract

Although promoter-associated CpG islands have been established as targets of DNA methylation changes in cancer, previous studies suggest that epigenetic dysregulation outside the promoter region may be more closely associated with transcriptional changes. Here we examine DNA methylation, chromatin marks, and transcriptional alterations to define the relationship between transcriptional modulation and spatial changes in chromatin structure. Using human papillomavirus-related oropharyngeal carcinoma as a model, we show aberrant enrichment of repressive H3K9me3 at the transcriptional start site (TSS) with methylation-associated, tumor-specific gene silencing. Further analysis identifies a hypermethylated subtype which shows a functional convergence on MYC targets and association with CREBBP/EP300 mutation. The tumor-specific shift to transcriptional repression associated with DNA methylation at TSSs was confirmed in multiple tumor types. Our data may show a common underlying epigenetic dysregulation in cancer associated with broad enrichment of repressive chromatin marks and aberrant DNA hypermethylation at TSSs in combination with MYC network activation.

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
DNA methylation and gene expression in HPVOPSCC and normal oropharynx. Scatter plots (left panels) separated by gene expression quartiles based on the expression levels in either tumor or normal samples (n = 3290, 3289, 3289, 3290 for Q1, Q2, Q3, Q4, respectively; Q4 is the highest expression) showing methylation ratio at 100 bp segments including genomic loci within (a) and outside (b) CpG islands in genes with promoter-associated CpG islands (CGI genes, n = 13158). CGI genes have the CpG island-containing promoter by definition, though they may have additional CpG island(s) outside of the promoter region. a Shows methylation status at each 100 bp segment with such CpG island. As CGI genes also have various methylation profiles at CpG sites outside of the island(s), i.e. shore(s) etc., such 100 bp segments are plotted in b. Thus non-overlapping 100 bp segments of an identical set of CGI genes are shown in a, b. Right panels show the mean values. TSS transcription start site
Fig. 2
Fig. 2
Association of DNA methylation at TSS with gene expression in HPVOPSCC. a Methylation-expression correlation density plots showing where DNA methylation and gene expression are significantly correlated (FDR q < 0.05), demonstrating a strong, tumor-specific association of expression with methylation at the TSS. Y-axis represents probability and the area under the curve (AUC) adds up to 1. Plots of any correlation in all genes (n = 19866) in our discovery HPVOPSCC data set, and negative correlation in genes with and without promoter-associated CpG island (CGI genes (n = 13158) and noCGI genes (n = 6708), respectively) are shown. b Significance of DNA methylation expression associations in tumor. The red line represents the observed AUC ratio (tumor/normal) at TSS ± 500 bp region. Histogram represents the null distribution as calculated by multiple permutations (n = 1000). Results of any correlation in all genes, and negative correlation in CGI genes and noCGI genes are shown. c Scatter plots of two representative genes for expression and DNA methylation levels at the most significantly correlated 500 bp window determined by MBD-seq. d Bisulfite sequencing confirmation of MBD-seq data from each two regions of two representative genes. The arrow indicates the TSS of each gene. Brown bars in the upper panel indicate binary methylation value at each 100 bp segment determined by MBD-seq. Red and blue bars show mRNA level determined by RNA-seq. Vertical lines in the lower panel represent CpG sites. Open and filled circles denote unmethylated and methylated CpG sites determined by bisulfite sequencing, respectively. Scale bars, 1 kb
Fig. 3
Fig. 3
Unsupervised hierarchical clustering based on DNA methylation-expression correlations. a Changes in DNA methylation levels of 59 genes for the discovery cohort. b, c Clustered heatmaps for methylation levels of the genes (rows) and HPVOPSCC tumor samples (columns). Identical gene set was used for the discovery cohort (b, n = 47) and the TCGA validation cohort (c, n = 54)
Fig. 4
Fig. 4
Chromatin structure correlation in normal oropharynx and PDXs. a DNA methylation profiles of the normal oropharyngeal tissue and highly/lowly methylated tumors. Mean DNA methylation value of RefSeq genes (n = 20013) determined by MBD-seq are shown. b ChIP-seq data for H3K4me3 and H3K9me3 histone marks and MBD-seq data of two representative genes (see also Fig. 2c). Genes (blue) and CpG islands (green) are presented in a forward fashion. Scale bars, 1 kb (left) and 5 kb (right). c Mean H3K4me3 and H3K9me3 levels of all genes in 10 bp windows separated by gene expression quartiles (Q4 is the highest expression). Plots for normal oropharyngeal tissue, lowly (Tumor-L), and highly (Tumor-H) methylated tumors are shown. The number of genes for Q1, Q2, Q3, Q4; n = 4366, 4373, 4358, 4382 for Normal, n = 4366, 4336, 4407, 4370 for Tumor-L, and n = 4370, 4369, 4370, 4370 for Tumor-H, respectively. d Mean H3K4me3 and H3K9me3 levels of 407 genes with significant correlation between DNA methylation and gene expression in our discovery cohort. The shaded region shows signal of 1000 randomized gene lists of the same size (n = 407) selected from the RefSeq genes, thus represents the genomic background for each window
Fig. 5
Fig. 5
Validation using TCGA cohort. Note the insufficient data in upstream region beyond −1.5 kb of TSS due to lack of HM450K probes. a, b Scatter plots (left panels) separated by gene expression quartiles based on the expression levels in either tumor or normal samples (n = 3208, 3208, 3208, 3208 for Q1, Q2, Q3, Q4, respectively; Q4 is the highest expression) showing methylation ratio at HM450K probes located within (a) and outside (b) CpG islands. Right panels show the mean values. c Methylation-expression correlation density plot showing an increase of a density peak where DNA methylation and gene expression are significantly correlated (FDR q < 0.05). Plots of any correlation in all genes (n = 19004) in the TCGA validation data set, and negative correlation in CGI genes (n = 12832) and noCGI genes (n = 6172) are shown. d Significance of DNA methylation increase in tumor. The red line represents the observed AUC ratio (tumor/normal) at TSS ± 500 bp region. Gray bars represent the null distribution as calculated by multiple permutations (n = 1000). Results are also shown for CGI genes (n = 12873) among HPV-negative head and neck squamous cell carcinoma (e, HPV(-)HNSCC), colon adenocarcinoma (f, COAD), and breast invasive carcinoma (g, BRCA) available from TCGA
Fig. 6
Fig. 6
MYC pathway associated with CREBBP/EP300 loss in highly methylated HPVOPSCC. a Single-sample gene set enrichment analysis (ssGSEA) scores ranked by their degree of association (IC) between highly and lowly methylated HPVOPSCC tumors. MYC-related motif (C3) and hallmark (H) gene sets enriched in highly methylated tumors in our discovery cohort are shown. An empirical phenotype-based permutation test procedure is used to estimate P values. Tumor-H, highly methylated HPVOPSCC. Tumor-L, lowly methylated HPVOPSCC. b MYC expression of each sample in our discovery cohort (n = 35, excluding normal samples, t-test). In boxplots, the ends of the boxes and the middle line represent the lower and upper quartiles, and medians, respectively. Whiskers extend to show the rest of the distribution, except for points that are determined to be outliers using a function of the inter-quartile range. c CREBBP/EP300 mutations show significant association with the hypermethylation phenotype Fisher’s exact test. d Suppression of MYC expression (left and center panel) and growth of UM-SCC-47 cells (right panel) by EP300 knockdown. mRNA and protein detection were performed on lysates of UM-SCC-47 cells collected at 48 h after siRNA transfection. Growth is normalized to day 0 and measured over 3 days. e Reduced histone H3K27ac at MYC locus by EP300 knockdown measured by ChIP-qPCR (upper panel). Red marks in the lower panel indicate the regions ChIP enrichment were measured. The arrow indicates the TSS of MYC gene. ChIP assays were performed on UM-SCC-47 cells collected at 48 h after siRNA transfection. f Reduced occupancy of MYC at the indicated gene promoter determined via ChIP-qPCR (left panel) and suppression of CDK2 expression (center and right panels) by EP300 knockdown in UM-SCC-47 cells. CDK4 and NPM1 as positive controls, and GCK as a negative control were used. mRNA and protein detection were performed on cell lysates collected at 48 h after siRNA transfection. g Effects of EP300 knockdown on DNA methylation (left panel) and mRNA expression (right panel) levels in ZNF470, ZNF568, and ZNF569, whose expression level had a significant negative correlation with that of MYC in the discovery cohort. All experiments in UM-SCC-47 cells were performed at least in triplicate, and data are expressed as mean ± SE. *P < 0.05 and **P < 0.01, t-test. Source data are provided as a Source Data file

Similar articles

See all similar articles

Cited by 4 PubMed Central articles

References

    1. Jones PA, Baylin SB. The epigenomics of cancer. Cell. 2007;128:683–692. doi: 10.1016/j.cell.2007.01.029. - DOI - PMC - PubMed
    1. Cedar H, Bergman Y. Linking DNA methylation and histone modification: patterns and paradigms. Nat. Rev. Genet. 2009;10:295–304. doi: 10.1038/nrg2540. - DOI - PubMed
    1. Baylin SB, Jones PA. A decade of exploring the cancer epigenome - biological and translational implications. Nat. Rev. Cancer. 2011;11:726–734. doi: 10.1038/nrc3130. - DOI - PMC - PubMed
    1. Tessarz P, Kouzarides T. Histone core modifications regulating nucleosome structure and dynamics. Nat. Rev. Mol. Cell Biol. 2014;15:703–708. doi: 10.1038/nrm3890. - DOI - PubMed
    1. Wagner JR, et al. The relationship between DNA methylation, genetic and expression inter-individual variation in untransformed human fibroblasts. Genome Biol. 2014;15:R37. doi: 10.1186/gb-2014-15-2-r37. - DOI - PMC - PubMed

Publication types

Feedback