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A pre-neoplastic epigenetic field defect in HCV-infected liver at transcription factor binding sites and polycomb targets

View Article: PubMed Central - PubMed

ABSTRACT

The predisposition of patients with Hepatitis C virus (HCV) infection to hepatocellular carcinoma (HCC) involves components of viral infection, inflammation and time. The development of multifocal, genetically distinct tumors is suggestive of a field defect affecting the entire liver. The molecular susceptibility mediating such a field defect is not understood. One potential mediator of long-term cellular reprogramming is heritable (epigenetic) regulation of transcription, exemplified by DNA methylation. We studied epigenetic and transcriptional changes in HCV-infected livers in comparison with control, uninfected livers and HCC, allowing us to identify pre-neoplastic epigenetic and transcriptional events.

We find the HCV-infected liver to have a pattern of acquisition of DNA methylation targeted to candidate enhancers active in liver cells, enriched for the binding sites of the FOXA1, FOXA2 and HNF4A transcription factors. These enhancers can be subdivided into those proximal to genes implicated in liver cancer or to genes involved in stem cell development, the latter distinguished by increased CG dinucleotide density and polycomb-mediated repression, manifested by the additional acquisition of histone H3 lysine 27 trimethylation (H3K27me3). Transcriptional studies on our samples showed that the increased DNA methylation at enhancers was associated with decreased local gene expression, results validated in independent samples from The Cancer Genome Atlas (TCGA). Pharmacological depletion of H3K27me3 using the EZH2 inhibitor GSK343 in HepG2 cells suppressed cell growth and also revealed that local acquired DNA methylation was not dependent upon the presence of polycomb-mediated repression.

The results support a model of HCV infection influencing the binding of transcription factors to cognate sites in the genome, with consequent local acquisition of DNA methylation, and the added repressive influence of polycomb at a subset of CG-dense cis-regulatory sequences. These epigenetic events occur before neoplastic transformation, resulting in what may be a pharmacologically-reversible epigenetic field defect in HCV-infected liver.

No MeSH data available.


Related in: MedlinePlus

Analysis of gene expression data from the samples tested for DNA methylation changes. In (a) we again use k-means clustering to identify subsets of genes with distinctive progression of expression patterns during disease progression. Groups III and IV represent genes increasing their expression while groups V and VI show a decrease in expression levels. The significantly differentially expressed genes in a comparison of malignant and control samples (b) are mostly accounted for by genes in groups IV and VI. We associated a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene's transcription start site and showed increased DNA methylation in control versus malignant samples, finding a total of 622 genes fitting these criteria. When we tested to see whether these 622 include genes with significantly altered levels of expression, we showed that these genes with increased DNA methylation were significantly enriched for overlap with genes with decreased expression (p=0.002) but not increased expression (c). In (d) we show the results of analysis of matched HCC and infected liver samples from HCV+ individuals, using data from The Cancer Genome Atlas (TCGA). We tested DNA methylation data from TCGA at candidate enhancers where we had identified increased DNA methylation and found the studies from TCGA to reveal a significant increase of DNA methylation in their samples also. We also compared the genes where we had found significant changes in levels of expression, showing the genes with decreased expression also to have significantly lower levels in TCGA samples, but no significant changes in the levels of expression of genes that we had found to be up-regulated with disease progression.
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Figure 5: Analysis of gene expression data from the samples tested for DNA methylation changes. In (a) we again use k-means clustering to identify subsets of genes with distinctive progression of expression patterns during disease progression. Groups III and IV represent genes increasing their expression while groups V and VI show a decrease in expression levels. The significantly differentially expressed genes in a comparison of malignant and control samples (b) are mostly accounted for by genes in groups IV and VI. We associated a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene's transcription start site and showed increased DNA methylation in control versus malignant samples, finding a total of 622 genes fitting these criteria. When we tested to see whether these 622 include genes with significantly altered levels of expression, we showed that these genes with increased DNA methylation were significantly enriched for overlap with genes with decreased expression (p=0.002) but not increased expression (c). In (d) we show the results of analysis of matched HCC and infected liver samples from HCV+ individuals, using data from The Cancer Genome Atlas (TCGA). We tested DNA methylation data from TCGA at candidate enhancers where we had identified increased DNA methylation and found the studies from TCGA to reveal a significant increase of DNA methylation in their samples also. We also compared the genes where we had found significant changes in levels of expression, showing the genes with decreased expression also to have significantly lower levels in TCGA samples, but no significant changes in the levels of expression of genes that we had found to be up-regulated with disease progression.

Mentions: As the acquisition of DNA methylation at enhancers is potentially associated with altered gene expression38,42, RNA-seq was therefore performed on the same samples on which DNA methylation studies had been performed. K-means clustering was used in the analysis of these data, with the optimal number of groups found to be approximately 6, allowing patterns of gene expression changes in infected and malignant samples to be compared with the controls (Figure S1). In Figure 5a it is apparent that most genes (groups I and II) do not change levels of expression in infected or malignant cells (n=13,507), but that there are also groups of genes with early (group IV, n=1,720) and progressive (group III, n=4,621) patterns of increased gene expression, and further genes that progressively decrease expression levels by substantial (pattern VI, n=890) or lesser extents (pattern V, n=4,375) (Figure 5a). Overall, more genes were represented by patterns with increased rather than decreased gene expression. A PCA found potential covariates modifying gene expression, allowing subsequent polytomous regression to control for sequencing batch (Figure S6). In all, 309 genes were identified to have significantly decreasing expression and only 193 genes with increased expression levels (Figure 5b, Tables S2-S3). The 309 genes with significantly decreased expression were tested for proximity to the enhancers found to have increased DNA methylation. A conservative approach was used, linking a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene’s transcription start site, finding a total of 644 genes fitting these criteria. A significant association was found linking enhancers with increased DNA methylation and genes with decreased expression levels (hypergeometric test p=0.002), with no significant association found for the genes with increased expression levels (hypergeometric test p=0.763) (Figure 5c). While influencing only a small proportion of genes, the increased DNA methylation at candidate enhancers is significantly associated with local transcriptional repression.


A pre-neoplastic epigenetic field defect in HCV-infected liver at transcription factor binding sites and polycomb targets
Analysis of gene expression data from the samples tested for DNA methylation changes. In (a) we again use k-means clustering to identify subsets of genes with distinctive progression of expression patterns during disease progression. Groups III and IV represent genes increasing their expression while groups V and VI show a decrease in expression levels. The significantly differentially expressed genes in a comparison of malignant and control samples (b) are mostly accounted for by genes in groups IV and VI. We associated a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene's transcription start site and showed increased DNA methylation in control versus malignant samples, finding a total of 622 genes fitting these criteria. When we tested to see whether these 622 include genes with significantly altered levels of expression, we showed that these genes with increased DNA methylation were significantly enriched for overlap with genes with decreased expression (p=0.002) but not increased expression (c). In (d) we show the results of analysis of matched HCC and infected liver samples from HCV+ individuals, using data from The Cancer Genome Atlas (TCGA). We tested DNA methylation data from TCGA at candidate enhancers where we had identified increased DNA methylation and found the studies from TCGA to reveal a significant increase of DNA methylation in their samples also. We also compared the genes where we had found significant changes in levels of expression, showing the genes with decreased expression also to have significantly lower levels in TCGA samples, but no significant changes in the levels of expression of genes that we had found to be up-regulated with disease progression.
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Related In: Results  -  Collection

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Figure 5: Analysis of gene expression data from the samples tested for DNA methylation changes. In (a) we again use k-means clustering to identify subsets of genes with distinctive progression of expression patterns during disease progression. Groups III and IV represent genes increasing their expression while groups V and VI show a decrease in expression levels. The significantly differentially expressed genes in a comparison of malignant and control samples (b) are mostly accounted for by genes in groups IV and VI. We associated a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene's transcription start site and showed increased DNA methylation in control versus malignant samples, finding a total of 622 genes fitting these criteria. When we tested to see whether these 622 include genes with significantly altered levels of expression, we showed that these genes with increased DNA methylation were significantly enriched for overlap with genes with decreased expression (p=0.002) but not increased expression (c). In (d) we show the results of analysis of matched HCC and infected liver samples from HCV+ individuals, using data from The Cancer Genome Atlas (TCGA). We tested DNA methylation data from TCGA at candidate enhancers where we had identified increased DNA methylation and found the studies from TCGA to reveal a significant increase of DNA methylation in their samples also. We also compared the genes where we had found significant changes in levels of expression, showing the genes with decreased expression also to have significantly lower levels in TCGA samples, but no significant changes in the levels of expression of genes that we had found to be up-regulated with disease progression.
Mentions: As the acquisition of DNA methylation at enhancers is potentially associated with altered gene expression38,42, RNA-seq was therefore performed on the same samples on which DNA methylation studies had been performed. K-means clustering was used in the analysis of these data, with the optimal number of groups found to be approximately 6, allowing patterns of gene expression changes in infected and malignant samples to be compared with the controls (Figure S1). In Figure 5a it is apparent that most genes (groups I and II) do not change levels of expression in infected or malignant cells (n=13,507), but that there are also groups of genes with early (group IV, n=1,720) and progressive (group III, n=4,621) patterns of increased gene expression, and further genes that progressively decrease expression levels by substantial (pattern VI, n=890) or lesser extents (pattern V, n=4,375) (Figure 5a). Overall, more genes were represented by patterns with increased rather than decreased gene expression. A PCA found potential covariates modifying gene expression, allowing subsequent polytomous regression to control for sequencing batch (Figure S6). In all, 309 genes were identified to have significantly decreasing expression and only 193 genes with increased expression levels (Figure 5b, Tables S2-S3). The 309 genes with significantly decreased expression were tested for proximity to the enhancers found to have increased DNA methylation. A conservative approach was used, linking a candidate enhancer (H3K4me1 positive, H3K4me3 negative) to a gene if the chromatin state was within 5 kb of the gene’s transcription start site, finding a total of 644 genes fitting these criteria. A significant association was found linking enhancers with increased DNA methylation and genes with decreased expression levels (hypergeometric test p=0.002), with no significant association found for the genes with increased expression levels (hypergeometric test p=0.763) (Figure 5c). While influencing only a small proportion of genes, the increased DNA methylation at candidate enhancers is significantly associated with local transcriptional repression.

View Article: PubMed Central - PubMed

ABSTRACT

The predisposition of patients with Hepatitis C virus (HCV) infection to hepatocellular carcinoma (HCC) involves components of viral infection, inflammation and time. The development of multifocal, genetically distinct tumors is suggestive of a field defect affecting the entire liver. The molecular susceptibility mediating such a field defect is not understood. One potential mediator of long-term cellular reprogramming is heritable (epigenetic) regulation of transcription, exemplified by DNA methylation. We studied epigenetic and transcriptional changes in HCV-infected livers in comparison with control, uninfected livers and HCC, allowing us to identify pre-neoplastic epigenetic and transcriptional events.

We find the HCV-infected liver to have a pattern of acquisition of DNA methylation targeted to candidate enhancers active in liver cells, enriched for the binding sites of the FOXA1, FOXA2 and HNF4A transcription factors. These enhancers can be subdivided into those proximal to genes implicated in liver cancer or to genes involved in stem cell development, the latter distinguished by increased CG dinucleotide density and polycomb-mediated repression, manifested by the additional acquisition of histone H3 lysine 27 trimethylation (H3K27me3). Transcriptional studies on our samples showed that the increased DNA methylation at enhancers was associated with decreased local gene expression, results validated in independent samples from The Cancer Genome Atlas (TCGA). Pharmacological depletion of H3K27me3 using the EZH2 inhibitor GSK343 in HepG2 cells suppressed cell growth and also revealed that local acquired DNA methylation was not dependent upon the presence of polycomb-mediated repression.

The results support a model of HCV infection influencing the binding of transcription factors to cognate sites in the genome, with consequent local acquisition of DNA methylation, and the added repressive influence of polycomb at a subset of CG-dense cis-regulatory sequences. These epigenetic events occur before neoplastic transformation, resulting in what may be a pharmacologically-reversible epigenetic field defect in HCV-infected liver.

No MeSH data available.


Related in: MedlinePlus