Effect of estrogen receptor α binding on functional DNA methylation in breast cancer

Abstract

Epigenetic modifications introduce an additional layer of regulation that drastically expands the instructional capability of the human genome. The regulatory consequences of DNA methylation is context dependent; it can induce, enhance, and suppress gene expression, or have no effect on gene regulation. Therefore, it is essential to account for the genomic location of its occurrence and the protein factors it associates with to improve our understanding of its function and effects. Here, we use ENCODE ChIP-seq and DNase I hypersensitivity data, along with large-scale breast cancer genomic data from The Cancer Genome Atlas (TCGA) to computationally dissect the intricacies of DNA methylation in regulation of cancer transcriptomes. In particular, we identified a relationship between estrogen receptor α (ERα) activity and DNA methylation patterning in breast cancer. We found compelling evidence that methylation status of DNA sequences at ERα binding sites is tightly coupled with ERα activity. Furthermore, we predicted several transcription factors including FOXA1, GATA1, and SUZ12 to be associated with breast cancer by examining the methylation status of their binding sites in breast cancer. Lastly, we determine that methylated CpGs highly correlated with gene expression are enriched in regions 1kb or more downstream of TSSs, suggesting more significant regulatory roles for CpGs distal to gene TSSs. Our study provides novel insights into the role of ERα in breast cancers.

Keywords: ChIP-seq; DNase I hypersensitivity; breast cancer; differential gene expression; differential methylation; estrogen receptor α; transcription factor.

Figure 1. The schematic diagram of our analysis. We combined DNA methylation and gene expression data in breast cancer samples from TCGA, and TF binding and DNase I hypersensitivity data from ENCODE. We identified the CpG sites with differential methylation levels between ER+ and ER- breast cancer samples, and examined the correlation of their methylation levels with expression of associated genes. Blue double arrows denote comparative analysis of regions of interest to outside regions.

Figure 2. Correlation between CpG methylation and ESR1 expression levels. (A) An example- correlation between methylation level of cg03387103 (corresponding to LETM1) and ESR1 expression level in all breast cancer samples. (B) CpGs in ER binding peaks have larger negative correlations with ESR1 expression in their methylation levels. (C) Fraction of CpGs highly correlated with ESR1 expression. There is a higher fraction of anti-correlated CpGs in ERα binding sites compared with non-ERα binding sites at ± 0.4 SCC cutoff. (D) CpGs in ER binding peaks have higher average methylation levels in ER- than ER+ samples. Each point is a CpG. SCC: Spearman correlation coefficient.

Figure 3. Distribution of CpGs with differential methylation levels between ER+ and ER- breast samples. (A) Examples- CpG may have higher methylation in ER+ (cg05846044) or ER- (cg05859267). (B) Relationship between differential methylation and CpG position relative to transcription start site (from –1500 upstream to 4500 downstream of TSS). (C) Distribution of CpGs with significant (P < 1e-6) differential methylation between ER+ and ER- samples. (D) Fraction of CpGs with significant differential methylation levels at different positions. The fraction is the ratio of the number of significant CpGs to the total number of CpGs in a DNA window. CpGs with significantly higher methylation levels in ER+ (red) and in ER- (green) samples are examined separately. The relative frequency of significantly differentially methylated CpGs increases as the distance from TSS increases.

Figure 4. CpGs in ER binding sites tend to have lower methylation levels in ER+ breast samples. (A) The fraction of CpGs with significant differential methylation levels between ER+ and ER- samples. Note that CpGs in ER binding regions tend to have higher methylation levels in ER- samples, while CpGs not in ER binding regions tend to have higher methylation levels in ER+ samples. Four different thresholds are used to determine differential methylated CpGs. (B) Distribution of t-scores (ER+ vs. ER-) of methylation levels for CpGs. Genes are divided into 3 classes based on their expression levels in ER+ vs. ER- samples: ER+ > ER- (red), ER+ < ER- (green), and ER+ = ER- (white). Distributions of CpGs associated with the three gene classes are shown separately. (C) CpGs in ER binding regions tend to have lower methylation levels in ER+ samples (lower t-scores) compared with thosenot in ER binding regions, which is the case for CpGs associated with all three gene classes.

Figure 5. Relationship between differential methylation of CpGs and TF binding. (A) Binding of some TFs is correlated with reduced methylation level of CpGs in ER+ relative to ER- samples, while binding of others (SUZ12 and CTBP2) is correlated with increased methylation level. (B) CpGs proximal to ER binding center are more likely to have lower methylation levels in ER+ (smaller t-scores for ER+ vs. ER- comparison). (C) CpGs proximal to SUZ12 binding center are more likely to have higher methylation levels in ER+ (larger t-scores for ER+ vs. ER- comparison).

Figure 6. Correlation of CpG methylation level with expression level of the associated genes. (A) Methylation level of cg06228260 is positively correlated with its associated gene PTPRN2. (B) Methylation level of cg01586506 is negatively correlated with its associated gene SOX10. (C) Relationship between methylation-expression correlation and CpG position relative to transcription start site (from –1500 upstream to 4500 downstream of TSS). (D) Distribution of CpGs with strong correlations in methylation with expression level of the associated genes. Positive correlation (red, r > 0.4) and negative correlation (green, r < –0.4) are examined separately. (E) Fraction of CpGs strongly correlated with expression of the associated genes at different positions. (F) CpGs in ER binding regions tend to have negative correlation in their methylation with expression of their associated genes.

Figure 7. Comparison of CpGs in and not in DNase hypersensitive sites. (A) CpGs in DHS and non-DHS exhibit no significant difference in differential methylation between ER+ and ER- breast cancer samples. (B) CpGs in DHS tend to have negative correlation in their methylation level with the expression of their associated genes.