In colon tumors, the transcription of many genes becomes deregulated by poorly defined epigenetic mechanisms that have been studied mainly in established cell lines. In this study, we used frozen human colon tissues to analyze patterns of histone modification and DNA cytosine methylation in cancer and matched normal mucosa specimens. DNA methylation is strongly targeted to bivalent H3K4me3- and H3K27me3-associated promoters, which lose both histone marks and acquire DNA methylation. However, we found that loss of the Polycomb mark H3K27me3 from bivalent promoters was accompanied often by activation of genes associated with cancer progression, including numerous stem cell regulators, oncogenes, and proliferation-associated genes. Indeed, we found many of these same genes were also activated in patients with ulcerative colitis where chronic inflammation predisposes them to colon cancer. Based on our findings, we propose that a loss of Polycomb repression at bivalent genes combined with an ensuing selection for tumor-driving events plays a major role in cancer progression. Cancer Res; 74(13); 3617–29. ©2014 AACR.

Tumorigenesis is a complex process that is driven by a number of genetic and epigenetic alterations, which often result in aberrant gene expression (1–3). Mutations are generally considered to be the primary drivers of tumorigenesis (4, 5). However, dysregulation of epigenetic regulatory mechanisms also contributes to malignant transformation. Methylation of cytosine at CpG sequences in DNA leading to the formation of 5-methylcytosine (5mC) is one of the most stable and most widely studied epigenetic modifications (6). In most human tumors, widespread hypermethylation of CpG-rich sequences (CpG islands) is observed along with genome-wide DNA hypomethylation (1, 7–14). DNA hypermethylation in cancer is not a random event; it commonly affects specific gene classes and is seen most frequently at targets of the Polycomb repression complex (15–18) including numerous homeobox genes (19, 20). However, many of the genes marked by Polycomb in normal tissues and cell types, for example embryonic stem cells, are expressed at very low levels in these cells (21, 22). The acquisition of the more permanent silencing mark, 5mC, at the promoters of Polycomb target genes does not fundamentally change their expression levels although plasticity of expression will be reduced. For these reasons, it has remained unclear whether methylation of Polycomb target genes plays an essential role in tumor promotion and is in fact a tumor-driving event (23).

Recently, genome sequencing has identified a high frequency of mutations in epigenetic regulatory factors or chromatin structural elements in human malignancies (24, 25). However, technical limitations have made it difficult to directly examine chromatin changes in normal and malignant tissues, with most studies being limited to in vitro cell culture models. To determine the role of histone modifications in targeting DNA methylation and in altering gene expression patterns in human primary tumors, we have conducted the first comprehensive analysis of frozen tissues from patients with colorectal cancer focusing on two histone methylation marks, the activating histone H3 lysine 4 trimethylation (H3K4me3) and the repressive histone H3 lysine 27 trimethylation (H3K27me3), which are thought to be critical for gene regulation. We found that genes carrying both histone modifications (bivalent genes) in normal tissue are characterized by substantial variability and undergo reorganization of these modifications in colorectal cancer, leading to activation of cancer-promoting genes as one important outcome that can confer tumor-driving properties onto an emerging malignant cell population.

Human tissue samples

Human Duke's stage II colon cancers and matching normal mucosa were obtained from the Cooperative Human Tissue Network (CHTN).

Gene expression analysis

Total RNA from patient samples was purified by using the mirVana Kit (Ambion; Life Technologies). For whole genome expression analysis, GeneChip Human Gene 2.0 ST arrays (Affymetrix) were used. Validation of gene expression changes by real-time reverse transcription-PCR was performed as described previously (18). All expression data were normalized to GAPDH in the same sample.

Analysis of 5mC patterns

For analysis of genomic 5mC patterns, the methylated CpG island recovery assay (MIRA) was used as described previously (26). After genome amplification, the methylated DNA fraction was hybridized versus input DNA on human CpG island/promoter microarrays (NimbleGen). The observed MIRA patterns for single CpG islands were validated by combined bisulfite restriction analysis (COBRA) as described previously (18). Primer sequences are available upon request.

Chromatin immunoprecipitation

For chromatin immunoprecipitation (ChIP), frozen tissues were crushed with a plastic pestle in ice-cold phosphate-buffered saline (PBS) and fixed for 10 minutes at room temperature in 1% formaldehyde. ChIP and genome amplification protocols were performed as described previously (26). The following antibodies were used: anti-H3K4me3 (39159; Active Motif), and anti-H3K27me3 (07-449; Millipore). For obtaining the H3K4me3 profile, H3K4me3 antibodies were preblocked with an H3K9me3 peptide (Abcam) to remove minor cross-reactivity of this antibody. After genome amplification, immunoprecipitated DNA was hybridized versus input DNA on human CpG island/promoter microarrays (NimbleGen).

For sequential ChIP (ReChIP), the first immunoprecipitation was performed as described above except for the elution step, which was performed with SDS lysis buffer (1% SDS, 10 mmol/L EDTA, 50 mmol/L Tris-HCl, pH 8.1, 1× cOmplete Protease Inhibitor Cocktail; Roche Applied Science) for 10 minutes at 68°C on a shaker at 1,000 rpm. After removal of beads, the samples were diluted with 1:10 ChIP dilution buffer (0.01% SDS, 1.1% Triton X-100, 1.2 mmol/L EDTA, 16.7 mmol/L Tris-HCl, pH 8.1, 167 mmol/L NaCl, 22 μg/mL BSA, 1× cOmplete Protease Inhibitor Cocktail) and incubated with protein A/G PLUS-agarose (sc-2003; Santa Cruz Biotechnology), preblocked with BSA and herring sperm DNA, for 30 minutes at 4°C. After removal of beads, chromatin was incubated with anti-H3K4me3 (39159; Active Motif), anti-H3K27me3 (17-622; Millipore), or IgG (17-622, Millipore) antibodies overnight at 4°C followed by further incubation with protein A/G PLUS-agarose. Beads were washed once with low-salt immune complex wash buffer (0.1% SDS, 1% Triton X-100, 2 mmol/L EDTA, 20 mmol/L Tris-HCl, pH 8.1, 150 mmol/L NaCl, 1× cOmplete Protease Inhibitor Cocktail) and twice with high salt immune complex wash buffer (0.1% SDS, 1% Triton X-100, 2 mmol/L EDTA, 20 mmol/L Tris-HCl, pH 8.1, 500 mmol/L NaCl, 1× cOmplete Protease Inhibitor Cocktail). Chromatin was eluted with SDS lysis buffer for 10 minutes at 68°C on a shaker at 1,000 rpm and crosslinks were reversed in presence of 300 mmol/L NaCl at 65°C overnight. Primer sequences for qPCR of individual genes are available upon request. Analysis was done with tissues from patient no. 14. Results are for triplicate experiments (±SD).

Bioinformatics analysis

All analysis was performed using R statistical language, except for gene ontology analysis, which was performed using DAVID annotation tools and Ingenuity Pathway Analysis. The heat maps were generated with Cluster v3.0 and Java Treeview v2.0. Refseq genes were downloaded from the UCSC hg18 annotation database. Promoter was defined as −1.4 to +0.6 kb relative to the transcription start site (TSS). For heat maps with epigenetic marks, only genes with gene body length greater than 2 kb were included. Genes that were differentially expressed during colorectal cancer formation were identified as those with a log2-fold change >1. Probes were considered positive if their normalized log2 ratios were above 1.5-fold. Peaks in each sample were defined as four or more consecutive positive probes with either one or no gaps. A promoter was defined as bivalent if it contained overlapping H3K4me3 and H3K27me3 peaks at expanded promoter areas (−2.4 kb < TSS < 0.6 kb). For heat-map analysis, genes were assumed activated in all tumors and bivalent in mucosa if those genes had a promoter bivalent status in at least 3 of 4 normal colon samples and tumor-associated gene activation of log2 ≥ 0.4 in four patient sample pairs.

Affymetrix microarray data were processed by Expression Console v 2.0 with default settings. Transcription profiles of unique genes were obtained by averaging the transcriptional levels of all different transcript isoforms of the same gene according to Affymetrix's annotation. Genes with log2 intensity <5 in more than 10% of biopsies were considered uninformative and were removed. Affymetrix expression array data were used to generate heat maps as described previously (27). All array data were deposited in the GEO database (accession number GSE47076).

Chromatin mapping studies with frozen tissue

Previous correlative studies, mostly performed with cultured cells (e.g., embryonic stem cells), indicated that the Polycomb-associated chromatin modification, H3K27me3, predisposes sequences toward DNA hypermethylation in cancer (15–17, 20). To study aberrations of chromatin and DNA methylation in primary tumors, we directly profiled H3K4me3, H3K27me3, and DNA methylation in 4 archived frozen colorectal tumors with diagnosed Duke's stage II and 4 matching normal mucosa samples, using human promoter and CpG island microarrays containing ∼28,000 CpG islands and ∼20,000 promoters.

We used the methylated-CpG island recovery assay (MIRA; ref. 19) to comprehensively identify DNA methylation changes in the analyzed tissues. By using an established bioinformatics approach (28), we identified between 484 and 2,098 tumor-associated hypermethylated DNA regions in the four tumors (tumor #6: 2,098 regions, tumor #8: 1,552 regions, tumor #12: 484 regions, and tumor #14: 1,676 regions). We validated the aberrant methylation patterns by COBRA for several differentially methylated regions located in the TMEFF2, LIFR, CDKN2A, WNT5A, and MLH1 promoters (Supplementary Fig. S1). In total, we analyzed 11 regions by bisulfite-based methods and observed that the two approaches yielded excellent correlation for all regions examined.

To judge the quality of ChIP conducted on the frozen tissues, we performed several bioinformatics comparisons of our ChIP data with DNA methylation and gene expression data obtained with the presumably more stable DNA or RNA material obtained from the same samples. As shown in Supplementary Fig. S2, ChIP patterns from frozen tissues are very reproducible between samples and provide remarkable consistency among independent ChIP analyses within the same tissue (R = 0.89, P < 0.0001; Supplementary Fig. S2A). Our data revealed the well-established negative correlation (R = −0.6, P < 0.0001) between 5mC and H3K4me3 at CpG islands (Fig. 1A: refs. 29 and 30). Furthermore, changes of H3K4me3 at promoters occurring between tumors and matching normal tissues were strongly linked to transcriptional changes analyzed at the RNA level (Fig. 1C). Genes gaining H3K4me3 at promoters were frequently activated in tumors and genes, which lost H3K4me3, were repressed. Genome-wide, DNA methylation changes at promoters also showed a strong negative correlation with H3K4me3 changes between tumors and matching normal tissues (Fig. 1B). Taken together, these data confirmed the reliability of our chromatin mapping approach using frozen tissue specimens.

Figure 1.

Verification of chromatin mapping with frozen tissues. A, DNA methylation analysis and H3K4me3 histone mapping was conducted with normal (N) and tumor (T) samples from patients #6 (top) and #8 (bottom). An inverse correlation between 5mC and H3K4me3 signal is observed for each sample. B, changes in 5mC signal between tumor (T) and normal (N) samples are plotted versus changes in H3K4me3 signal for patients #6 and #8. An inverse correlation is observed. Analysis was performed for promoters overlapping with CpG islands. The Pearson correlations between 5mC and H3K4me3 datasets are indicated. C, a heat-map analysis of changes (T vs. N) in H3K4me3, 5mC, and gene expression levels is shown for four patient sample pairs. H3K4me3 changes positively correlate with changes in gene expression but negatively correlate with changes in 5mC. Promoters of genes longer than 2 kb were sorted by cancer-associated H3K4me3 changes. Each row represents a gene promoter. Red indicates a gain and green represents a loss.

Figure 1.

Verification of chromatin mapping with frozen tissues. A, DNA methylation analysis and H3K4me3 histone mapping was conducted with normal (N) and tumor (T) samples from patients #6 (top) and #8 (bottom). An inverse correlation between 5mC and H3K4me3 signal is observed for each sample. B, changes in 5mC signal between tumor (T) and normal (N) samples are plotted versus changes in H3K4me3 signal for patients #6 and #8. An inverse correlation is observed. Analysis was performed for promoters overlapping with CpG islands. The Pearson correlations between 5mC and H3K4me3 datasets are indicated. C, a heat-map analysis of changes (T vs. N) in H3K4me3, 5mC, and gene expression levels is shown for four patient sample pairs. H3K4me3 changes positively correlate with changes in gene expression but negatively correlate with changes in 5mC. Promoters of genes longer than 2 kb were sorted by cancer-associated H3K4me3 changes. Each row represents a gene promoter. Red indicates a gain and green represents a loss.

Close modal

Variability of H3K27me3

Analysis of H3K27me3-marked genomic regions showed many similarities between tumor and nonmalignant matching specimens (e.g., Supplementary Figs. S2D and S3A). However, in contrast to the generally more invariant H3K4me3 patterns, we observed a substantial degree of instability of the H3K27me3 mark when comparing normal and tumor samples (Fig. 2A and B and Supplementary Fig. S3). The Pearson correlation coefficients of H3K27me3 when comparing between tumors and matching normal mucosa were significantly reduced (∼0.75) in comparison to the Pearson correlation coefficients for H3K4me3 when comparing between matching tumor and normal samples (∼0.91; Supplementary Fig. S3A). Inspection of H3K27me3 patterns revealed that the H3K27me3 mark was frequently lost along larger genomic areas such as the HOX and histone gene clusters in tumors (Fig. 2B and Supplementary Fig. S3B), similar as has been reported recently by Bert and colleagues (10). However, these long-range areas of H3K27me3 loss represented only a relatively small fraction of all sequences that lost H3K27me3.

Figure 2.

Frequent variability of the Polycomb mark H3K27me3 in colon tumors. A, representative snapshots showing loss of H3K27me3 at the HOXB13 locus in 3 of 4 analyzed tumors (T) compared with matching normal mucosa (N) samples. The snapshots indicate log2 ratios of signal of IP versus input. Transcriptional start sites and transcript directions are shown. B, loss of H3K27me3 in tumors is linked to aberrant DNA methylation or accumulation of H3K4me3 at promoters. Representative snapshots of the HOXC cluster from patient #6 are shown. The colored circles mark changes of H3K4me3 or 5mC levels in tumor (T) versus normal (N) samples. Transcriptional start sites and transcript directions are shown. C, sorting of the genome by cancer-associated H3K27me3 changes at promoters. Each row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss. For analysis, we used genes larger than 2 kb and with positive values of H3K27me3 in at least one of the tissues (T or N). D, loss of H3K27me3 in tumors is frequently associated either with a gain of H3K4me3 and gene activation or with aberrant DNA methylation and gene silencing. The top 15% of genes with greatest loss of H3K27me3 from the sorting in C were sorted by H3K4me3 changes. Each row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss of the respective mark.

Figure 2.

Frequent variability of the Polycomb mark H3K27me3 in colon tumors. A, representative snapshots showing loss of H3K27me3 at the HOXB13 locus in 3 of 4 analyzed tumors (T) compared with matching normal mucosa (N) samples. The snapshots indicate log2 ratios of signal of IP versus input. Transcriptional start sites and transcript directions are shown. B, loss of H3K27me3 in tumors is linked to aberrant DNA methylation or accumulation of H3K4me3 at promoters. Representative snapshots of the HOXC cluster from patient #6 are shown. The colored circles mark changes of H3K4me3 or 5mC levels in tumor (T) versus normal (N) samples. Transcriptional start sites and transcript directions are shown. C, sorting of the genome by cancer-associated H3K27me3 changes at promoters. Each row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss. For analysis, we used genes larger than 2 kb and with positive values of H3K27me3 in at least one of the tissues (T or N). D, loss of H3K27me3 in tumors is frequently associated either with a gain of H3K4me3 and gene activation or with aberrant DNA methylation and gene silencing. The top 15% of genes with greatest loss of H3K27me3 from the sorting in C were sorted by H3K4me3 changes. Each row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss of the respective mark.

Close modal

Quite surprisingly, a detailed examination of the chromatin profiles also revealed that loss of the H3K27me3 mark over larger sequence blocks can be alternatively associated with accumulation of aberrant DNA methylation at some promoters or with accumulation of the H3K4me3 mark at other (even nearby) promoters (Fig. 2B and Supplementary Fig. S3B). Moreover, even a switch between transcriptional isoforms can occur in tumors when alternative routes between H3K4me3 and 5mC deposition are used upon H3K27me3 loss. For example, a loss of H3K27me3 at the HOXC cluster in sample #6 is associated with aberrant DNA methylation at the short HOXC9 isoform promoter, at the HOXC10 promoter and at the HOXC4 short isoform (transcript variant 2) promoter. The same genomic locus shows accumulation of H3K4me3 at the HOXC5 promoter (transcript variant 1), HOXC6 promoter (transcript variant 1), HOTAIR long isoform (transcript variant 1) promoter, the HOXC4 long isoform (transcript variant 1) promoter, and at the long HOXC9 isoform promoter (Fig. 2B). Thus, a loss of H3K27me3 at distinct promoters can be involved in H3K4me3 accumulation or aberrant DNA methylation and can have a major impact on transcript isoform usage in colorectal tumors. To evaluate if these observations apply to the cancer epigenome as a whole, and to determine whether alterations of the H3K27me3 patterns reflect transcriptional changes, we used the heat-map approach for promoter regions and sorted genes by H3K27me3 changes (Fig. 2C and D). We examined the 15% of genes that showed the greatest loss of H3K27me3 at promoters, and we additionally sorted these genes by H3K4me3 changes (Fig. 2C and D). We found that H3K4me3 alterations within this group of genes negatively correlated with accumulation of aberrant DNA methylation at promoters. At the same time, accumulation of H3K4me3 at promoters, which lost H3K27me3 in tumors, was frequently associated with gene activation (Fig. 2D). Thus, at a genome-wide level, we confirmed the two different correlates of H3K27me3 loss in colorectal cancer, gain of 5mC, or gene activation.

Bivalent chromatin in embryonic stem cells and colonic mucosa

Bivalent (H3K4me3 and H3K27me3 containing) chromatin status is a key regulatory mechanism during embryonic stem (ES) cell maintenance and differentiation (31, 32). We first asked to what extent bivalent promoter status is retained in human colonic mucosa versus ES cells. We found that the number of bivalent promoters varies between 3,414 and 3,967 within the normal colonic mucosal samples (Supplementary Fig. S4A). Approximately 50% to 60% of these bivalent promoters in normal colon are also bivalent in ES cells, whereas 40% to 50% of bivalent promoters are specific for colon. Gene ontology analysis using DAVID (http://david.abcc.ncifcrf.gov/) showed that the gene group retaining the bivalent state from ES cells to colon is more enriched with developmental genes in comparison to the gene groups that have lost the bivalent state during development, and those, which perhaps obtained it de novo in the colon (Supplementary Fig. S4B). Previously, aberrant DNA methylation in cancer has been linked to the bivalent state of promoters (15). To further assess this correlation, we compared the bivalent promoter state in normal tissue to aberrant methylation in matching tumors (Supplementary Fig. S5A) and observed that genes with bivalent promoters comprise the vast majority of promoters with cancer-associated DNA methylation. Strikingly, the presence of H3K27me3 at promoters in normal colon epithelial tissue was associated with 90% of all hypermethylated sites (Supplementary Fig. S5B) and approximately 70% of aberrantly methylated promoters had a bivalent state in normal colon tissue (Supplementary Fig. S5A).

Because the simultaneous presence of H3K4me3 and H3K27me3 at promoters might reflect different cell populations, we examined chromatin state at several candidate genes by sequential immunoprecipitation (Fig. 3A and Supplementary Fig. S4C). These experiments confirmed presence of both histone marks on the same immunoprecipitated DNA fragments in normal mucosa.

Figure 3.

Patterns of instability of bivalent promoters in colorectal cancer. A, ChIP and ReChIP of the FOXQ1 promoter for matched tumor and normal samples. Standard ChIP with anti-H3K4me3 and anti-H3K27me3 antibodies is shown in the left panel and sequential ChIP with both antibody combinations is shown in the right panel. B, clustering analysis of epigenetic changes at bivalent promoters in colon tumors. Analysis was done for promoters with bivalent status in all analyzed normal tissue samples. Each vertical row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss. C, transcriptional changes of bivalent promoters, which undergo similar epigenetic changes during colorectal cancer progression. The box-plots represent transcriptional levels for three groups of genes with bivalent promoter status in all analyzed normal tissues: genes with a gain H3K27me3 at promoters in tumors, genes that lose H3K27me3 at promoters and acquire cancer-associated DNA methylation, and genes that lose H3K27me3 and gain H3K4me3 at promoters. The data are merged for four patient samples. D, activation or repression of genes with bivalent promoters in normal mucosa. The graph indicates the fraction of bivalent genes, which become activated or repressed at least 2-fold in tumor versus matching mucosa.

Figure 3.

Patterns of instability of bivalent promoters in colorectal cancer. A, ChIP and ReChIP of the FOXQ1 promoter for matched tumor and normal samples. Standard ChIP with anti-H3K4me3 and anti-H3K27me3 antibodies is shown in the left panel and sequential ChIP with both antibody combinations is shown in the right panel. B, clustering analysis of epigenetic changes at bivalent promoters in colon tumors. Analysis was done for promoters with bivalent status in all analyzed normal tissue samples. Each vertical row represents a gene promoter. Values for each epigenetic mark were calculated as a mean of signal intensity log2 ratio for probes located at promoters. Red indicates a gain, and green represents a loss. C, transcriptional changes of bivalent promoters, which undergo similar epigenetic changes during colorectal cancer progression. The box-plots represent transcriptional levels for three groups of genes with bivalent promoter status in all analyzed normal tissues: genes with a gain H3K27me3 at promoters in tumors, genes that lose H3K27me3 at promoters and acquire cancer-associated DNA methylation, and genes that lose H3K27me3 and gain H3K4me3 at promoters. The data are merged for four patient samples. D, activation or repression of genes with bivalent promoters in normal mucosa. The graph indicates the fraction of bivalent genes, which become activated or repressed at least 2-fold in tumor versus matching mucosa.

Close modal

Chromatin changes at bivalent promoters

We next evaluated all epigenetic changes that target bivalent promoters in colorectal cancer. We generated a heat map containing information for H3K27me3, H3K4me3, and 5mC changes occurring at promoters with bivalent status in all analyzed normal colonic mucosa samples (Fig. 3B and Supplementary Table S1). We found that the majority of bivalent promoters undergo H3K27me3 changes at least in 1 of 4 analyzed tumors, pointing to a high instability or variability of bivalent promoters in colorectal cancer. Detailed analysis revealed that some genes such as DMRTA2 and HOXD11 lose H3K27me3 in tumors in comparison to normal tissue and may undergo either gene activation associated with accumulation of H3K4me3 or repression associated with aberrant DNA methylation in different individual patients (Supplementary Fig. S3C). This fact may indicate a random nature of the consequences of Polycomb loss at promoters, at least for certain genes. Clustering analysis indicated a large group of promoters characterized by a loss of H3K27me3, loss of H3K4me3, and gain of 5mC in all tumors (Fig. 3B; promoter groups marked by blue bars; Supplementary Fig. S5C). Furthermore, we observed a group of genes, which are characterized by a loss of H3K4me3 in all tumors and accumulation of 5mC in some tumors but accumulation of H3K27me3 in other tumors (Fig. 3B; promoter groups marked with black bars) providing alternative routes toward gene silencing (33). Both types of alterations, accumulation of H3K27me3 or of 5mC, are indeed characterized by gene repression (Fig. 3C). This observation suggests that the variability of chromatin at bivalent promoters can lead to two opposite outcomes, a gain or a loss of H3K27me3, and may result in gene repression according to both scenarios if 5mC is gained in the latter. A majority of promoters with aberrant DNA methylation in tumors was associated with a loss of H3K27me3 (Supplementary Fig. S5D). This phenomenon, which has been referred to as “Polycomb switching” (34), was true for promoters with and without bivalent state (Supplementary Fig. S5C and S5D).

Gene activation at bivalent promoters in cancer

Our study identified a novel and distinct group of promoters where a loss of H3K27me3 is associated with accumulation or retention of H3K4me3 in tumors but generally little or no change in DNA methylation levels (Fig. 3B; promoter group marked by a green bar). These promoters were associated with strong gene activation (Fig. 3C). Analysis of the transcriptome of bivalent promoters revealed a very high transcriptional instability of bivalent genes in tumors. Approximately 26% to 46% of bivalent promoters were affected by transcriptional alterations (at least 2-fold) in each tumor (Fig. 3D). We found that 15% to 20% of the bivalent genes undergo transcriptional activation in tumors (Fig. 3D).

To further elucidate the potential functional impact of bivalent promoter activation on colorectal cancer progression, we performed a detailed analysis of genes that are bivalent or nonbivalent in colonic mucosa and become activated at least 2-fold in at least two out of four analyzed tumors (Supplementary Table S2). Nonbivalent genes activated in tumors were enriched for genes important in mitotic progression including mitotic kinases, mitotic cyclins and kinesins, and checkpoint proteins (Supplementary Fig. S6A and Table S2). The activated bivalent genes were strongly associated with the colonic transcriptome and transcriptional activity in colorectal cancer (Fig. 4A). Importantly, this group of genes was strongly enriched with genes involved in transcriptional regulation and associated with early development (Supplementary Fig. S6B and Table S2). The genes that become repressed in tumors and carry a bivalent status in mucosa were strongly linked to brain development (Supplementary Fig. S6C), whereas repressed nonbivalent genes did not show any functional categories with major enrichment (data not shown). Significantly, the nonbivalent genes did not show any enrichment for transcription factors (Supplementary Table S2), neither for activation nor for repression gene groups, suggesting that the enrichment of mitotic proteins in the nonbivalent group could be downstream of crucial regulators (e.g., cyclin D) encoded by the activated bivalent genes. According to Ingenuity pathway analysis (www.ingenuity.com), the group of genes, which become activated in cancer and are bivalent in mucosa, was strongly enriched with genes associated with cancer as a disease (Fig. 4B) and with important aspects of the transformed phenotype (Supplementary Table S3). For example, one of the main regulators of the epithelial to mesenchymal transition (EMT), SNAI2 was activated together with a loss of bivalent status in tumor tissues (Supplementary Table S3). This group of genes contains many genes encoding transcription factors and genes associated with cellular growth and proliferation such as the oncogene cyclin D1 (CCND1), ribonucleotide reductase (RRM2), and MKi67, genes associated with cell adhesion and invasion including claudin1 (CLDN1) and EPCAM and other genes strongly implicated in cancer such as COX2/PTGS2 and the MET oncogene (Fig. 4D, Table 1, Supplementary Table S3, and Fig. S6D).

Figure 4.

Gene activation associated with bivalent promoters in colon tumors affects cancer-promoting and stem cell genes. A, genes that become activated in colorectal cancer and carry bivalent promoter status in matching mucosa are strongly linked to colon and colorectal tumor transcriptomes. The top 10 transcriptomes are indicated. Analysis was done for genes, which are at least 2-fold activated in at least 2 of 4 tumors and are bivalent in matching mucosa. We performed data analysis by using the Unigene tissue specificity database (http://www.ncbi.nlm.nih.gov/unigene) incorporated into DAVID (http://david.abcc.ncifcrf.gov/). B, top 5 diseases and disorders (www.ingenuity.com) associated with genes activated at least 2-fold in 2 of 4 tumors and having bivalent promoter status in matching mucosa. The numbers of genes in each subgroup are indicated. C, activation of LGR5 in colorectal cancer. Transcript levels of LGR5 in colon tumors and matching mucosa were validated by qRT-PCR with further normalization to GAPDH. D, loss of H3K27me3 affects stem cell marker genes and genes strongly linked to colorectal cancer. Representative snapshots for patient #8 displaying epigenetic changes associated with gene activation in colon tumors are shown. E, bivalent genes are activated in adenomas. The heat map displays transcriptional changes in colorectal adenomas for bivalent genes, which are activated in colorectal tumors and are also activated at least 2-fold in at least one third of the adenomas. Expression data for 32 human adenomas and matching mucosa were obtained from GEO dataset GDS2947. For clustering analysis, we used only genes with bivalent state in at least 3 of 4 mucosa tissues and activated in all four analyzed colorectal cancers. Gene symbols are indicated.

Figure 4.

Gene activation associated with bivalent promoters in colon tumors affects cancer-promoting and stem cell genes. A, genes that become activated in colorectal cancer and carry bivalent promoter status in matching mucosa are strongly linked to colon and colorectal tumor transcriptomes. The top 10 transcriptomes are indicated. Analysis was done for genes, which are at least 2-fold activated in at least 2 of 4 tumors and are bivalent in matching mucosa. We performed data analysis by using the Unigene tissue specificity database (http://www.ncbi.nlm.nih.gov/unigene) incorporated into DAVID (http://david.abcc.ncifcrf.gov/). B, top 5 diseases and disorders (www.ingenuity.com) associated with genes activated at least 2-fold in 2 of 4 tumors and having bivalent promoter status in matching mucosa. The numbers of genes in each subgroup are indicated. C, activation of LGR5 in colorectal cancer. Transcript levels of LGR5 in colon tumors and matching mucosa were validated by qRT-PCR with further normalization to GAPDH. D, loss of H3K27me3 affects stem cell marker genes and genes strongly linked to colorectal cancer. Representative snapshots for patient #8 displaying epigenetic changes associated with gene activation in colon tumors are shown. E, bivalent genes are activated in adenomas. The heat map displays transcriptional changes in colorectal adenomas for bivalent genes, which are activated in colorectal tumors and are also activated at least 2-fold in at least one third of the adenomas. Expression data for 32 human adenomas and matching mucosa were obtained from GEO dataset GDS2947. For clustering analysis, we used only genes with bivalent state in at least 3 of 4 mucosa tissues and activated in all four analyzed colorectal cancers. Gene symbols are indicated.

Close modal
Table 1.

Bivalent genes activated in colorectal cancer

GeneClassificationActivationWnt-pathway targetActivation in UC
LGR5a Leucine-rich repeat containing G protein–coupled receptor 5 Crypt stem cell marker Colon cancer stem cells, crypt stem cells Yes  
SOX9a SRY (sex determining region Y)-box 9 Crypt stem cell marker, transcription factor Crypt stem cells, colon cancer Yes  
ASCL2, aAchaete-scute complex homolog 2 Crypt stem cell marker, transcription factor Crypt stem cells, colon cancer Yes  
CD133 (PROM1), Prominin1 Stem cell marker Colon cancer stem cells, crypt stem cells   
FOXQ1, aForkhead box Q1 Transcription factor Colorectal cancer Yes Yes 
COX2 (PTGS2), prostaglandin-endoperoxide synthase 2 Inflammation and cancer-associated cyclooxygenase-2 Colon cancer Yes Yes 
MET, Met proto-oncogene (hepatocyte growth factor receptor) Oncogene, hepatocyte growth factor receptor Colon cancer, cancer stem cells, stem cells  Yes 
CCND1, cyclin D1 Cyclin, oncogene Colon cancer   
CLDN1, aClaudin1 Tight junction molecule Colon cancer Yes Yes 
EPCAM, epithelial cell adhesion molecule Adhesion molecule Colon cancer, cancer stem cells   
MKI67, antigen identified by monoclonal antibody Ki67 General proliferation marker Proliferating cells  Yes 
GeneClassificationActivationWnt-pathway targetActivation in UC
LGR5a Leucine-rich repeat containing G protein–coupled receptor 5 Crypt stem cell marker Colon cancer stem cells, crypt stem cells Yes  
SOX9a SRY (sex determining region Y)-box 9 Crypt stem cell marker, transcription factor Crypt stem cells, colon cancer Yes  
ASCL2, aAchaete-scute complex homolog 2 Crypt stem cell marker, transcription factor Crypt stem cells, colon cancer Yes  
CD133 (PROM1), Prominin1 Stem cell marker Colon cancer stem cells, crypt stem cells   
FOXQ1, aForkhead box Q1 Transcription factor Colorectal cancer Yes Yes 
COX2 (PTGS2), prostaglandin-endoperoxide synthase 2 Inflammation and cancer-associated cyclooxygenase-2 Colon cancer Yes Yes 
MET, Met proto-oncogene (hepatocyte growth factor receptor) Oncogene, hepatocyte growth factor receptor Colon cancer, cancer stem cells, stem cells  Yes 
CCND1, cyclin D1 Cyclin, oncogene Colon cancer   
CLDN1, aClaudin1 Tight junction molecule Colon cancer Yes Yes 
EPCAM, epithelial cell adhesion molecule Adhesion molecule Colon cancer, cancer stem cells   
MKI67, antigen identified by monoclonal antibody Ki67 General proliferation marker Proliferating cells  Yes 

aActivated in all four tumors.

Three crypt stem cell markers, ASCL2, LGR5, and SOX9 (35–37) belong to the group of most frequently activated genes (in all tumors) with bivalent promoters in normal colonic epithelium (Fig. 4C and D, Table 1, and Supplementary Table S3). This fact was also confirmed for LGR5 in 11 sample pairs by qRT-PCR (Fig. 4C). Analysis of transcription factor binding sites by DAVID for bivalent tumor-activated genes showed enrichment for SOX9 and FOXQ1 binding sites (Supplementary Fig. S6E). Interestingly, the genes coding for both transcription factors were activated because of loss of H3K27me3 in all tumors. In addition, two other intestinal stem cell signature genes, OLFM4 and EPHB3 were activated together with a loss of the H3K27me3 mark in colorectal cancer (Fig. 4D). It is remarkable that the well-known proliferation marker, MKI67 (Ki67) and cancer stem cell markers such as Prominin 1 (CD133) and ALCAM (CD166) also became activated together with a loss of bivalent state in tumors (Table 1 and Supplementary Table S3). These data suggest that loss of the bivalent state accompanied by activation of critical cell cycle drivers and tumor-promoting genes is a general and pervasive mechanism in colorectal cancer.

To evaluate the possibility that the apparent loss of H3K27me3 in tumors reflects an intestinal stem cell origin and presence of H3K27me3 in mucosa reflects a differentiation process in which this mark is acquired at promoters of stem cell genes, we determined if cancer-associated transcriptional changes in tumors carry primarily a gene expression signature indicative of cells at the crypt base where such stem cells reside. We used previously published expression profiling of human crypt top versus bottom samples (38). From 3,157 crypt bottom-specific genes, of which 306 genes carry a bivalent status in normal mucosa, we found only 26 crypt bottom genes including LGR5, ASCL2, MKi67, and CLDN1 to be activated in all tumors and bivalent in mucosa. At the same time, very few genes (10) of 2,865 crypt top-specific genes, of which 251 genes carry bivalent character in mucosa, were repressed in all tumors and were bivalent in mucosa (Supplementary Fig. S6F). These data clearly suggest that the tumors we analyzed do not express a predominant stem cell–like phenotype. Analysis of genes, which are not associated with crypt top or bottom according to Kosinski and colleagues (38), have bivalent status in mucosa and are activated in all tumors, revealed a strong association of these genes with cancer and epithelial neoplasia (Supplementary Table S4). This fact suggests that this group of genes may play an important role in cancer development.

We then tested if activation of bivalent genes may occur at an early stage of colorectal cancer progression. Based on publically available gene expression profiles of 32 human adenomas and matching mucosa (39), we evaluated if bivalent genes, which become activated in all tumors, undergo transcriptional changes in colorectal adenomas. Bivalent genes were activated slightly preferentially over nonbivalent genes in adenomas (18% vs. 15%). However, the majority (54%) of bivalent genes activated in stage II colorectal cancer were also activated in adenoma. Among the activated genes were stem cell markers including LGR5, SOX9, and ASCL2 and proliferation-associated genes such as MKI67 and RRM2 (Fig. 4E).

Transcriptional alterations of bivalent genes in inflamed mucosa

Chronic inflammation is a strong risk factor for cancer development (40). Similar to colon cancer, chronic inflammation of the digestive tract is associated with aberrant DNA methylation (41, 42), which frequently coincides with a loss of the Polycomb mark, H3K27me3 (18). We determined if activation of H3K27me3-marked genes occurs during inflammation and if these activated genes play a role in cancer. We used publically available expression profiles for 15 inflamed mucosal samples from patients with ulcerative colitis (UC), 7 unaffected mucosal tissues from patients with UC and 13 human colon biopsies from noninflamed controls obtained from GEO dataset GSE38713 (43). Analysis of expression profiles for genes with bivalent status in mucosa revealed that almost 20% of bivalent genes already undergo transcriptional changes during inflammation (Fig. 5A and Supplementary Table S1). Bivalent genes were not activated preferentially over nonbivalent genes (11% vs. 10%, respectively). Remarkably, patterns of activation and repression of bivalent genes strongly divided biopsies with and without inflammation (Fig. 5B). According to ingenuity pathway analysis, these activated bivalent genes are strongly linked to cancer (Fig. 5C and Supplementary Fig. S6G) and are associated with functions associated with cancer development such as cellular movement, cell death and survival, and proliferation (Supplementary Fig. S6H). Moreover, approximately 40% of genes (31/80) that are activated in all colorectal tumors and have bivalent status in adjacent mucosa are activated in inflamed tissues from patients with UC (Fig. 5D). Among these genes, we found FOXQ1, CLDN1, LEF1, and MKI67. However, in contrast to adenoma, expression of stem cell markers including SOX9, LGR5, and ASCL2 was not activated in inflamed tissues. These data provide additional evidence for bivalent gene activation in differentiated mucosa, in the absence of overt tumor formation, and demonstrates that the phenomenon of bivalent promoter activation occurs already during chronic inflammation, a condition strongly correlated with cancer predisposition.

Figure 5.

Activation of genes with bivalent promoters in UC. A, transcriptional changes in UC for genes with bivalent promoter status in mucosa. Expression profiles for 13 human colon biopsies from noninflamed controls, 15 inflamed mucosa samples from patients with UC, and 7 unaffected mucosa tissues from patients with UC were obtained from GEO dataset GSE38713. Bivalent genes were divided into three groups: genes that become activated at least 2-fold in at least one third of inflamed tissues versus noninflamed controls, genes that became repressed at least 2-fold, and genes that were not activated or repressed. B, differentially expressed bivalent genes in inflamed tissues from patients with UC. Clustering analysis was performed for bivalent genes, which underwent at least 2-fold transcriptional activation or repression in at least one third of inflamed tissues from patients with UC versus noninflamed controls. For this analysis, we used genes with bivalent state in at least 3 of 4 mucosal tissues. C, top 5 diseases and disorders (www.ingenuity.com) associated with genes activated at least 2-fold in inflamed biopsies versus noninflamed controls and having bivalent promoter status in all four analyzed mucosal tissues. The numbers of genes in each subgroup are indicated. D, bivalent genes, which become activated in colorectal cancer and are activated also in inflamed tissues from patients with UC. Clustering analysis is shown for bivalent genes, which underwent at least 2-fold transcriptional changes in at least one third of inflamed UC tissues and were activated in all tumors. Clustering analysis was done for genes that carry a bivalent promoter status in 3 of 4 mucosal samples.

Figure 5.

Activation of genes with bivalent promoters in UC. A, transcriptional changes in UC for genes with bivalent promoter status in mucosa. Expression profiles for 13 human colon biopsies from noninflamed controls, 15 inflamed mucosa samples from patients with UC, and 7 unaffected mucosa tissues from patients with UC were obtained from GEO dataset GSE38713. Bivalent genes were divided into three groups: genes that become activated at least 2-fold in at least one third of inflamed tissues versus noninflamed controls, genes that became repressed at least 2-fold, and genes that were not activated or repressed. B, differentially expressed bivalent genes in inflamed tissues from patients with UC. Clustering analysis was performed for bivalent genes, which underwent at least 2-fold transcriptional activation or repression in at least one third of inflamed tissues from patients with UC versus noninflamed controls. For this analysis, we used genes with bivalent state in at least 3 of 4 mucosal tissues. C, top 5 diseases and disorders (www.ingenuity.com) associated with genes activated at least 2-fold in inflamed biopsies versus noninflamed controls and having bivalent promoter status in all four analyzed mucosal tissues. The numbers of genes in each subgroup are indicated. D, bivalent genes, which become activated in colorectal cancer and are activated also in inflamed tissues from patients with UC. Clustering analysis is shown for bivalent genes, which underwent at least 2-fold transcriptional changes in at least one third of inflamed UC tissues and were activated in all tumors. Clustering analysis was done for genes that carry a bivalent promoter status in 3 of 4 mucosal samples.

Close modal

Our data suggest that loss of the bivalent (H3K4me3 and H3K27me3) chromatin state at promoters is accompanied by either gain of 5mC (when both marks are lost) or by gene activation (when H3K27me3 is lost; Fig. 6). The latter event, as we demonstrate here for the first time, is likely to be a critical step in cancer pathogenesis responsible for the activation of crucial genes leading to progression to malignancy and metastasis. Among the activated bivalent genes were several key components of the WNT signaling pathway including LGR5, CD133, LEF1, TCF7, WNT2, and WNT3. This pathway is commonly found to have a high level of constitutive activity in colorectal cancer. Also, many cell-cycle drivers and proliferation-associated genes were found in this category, including cyclin D, MKi67, RRM2, ETV4, and FGF19 along with many transcription factor genes such as SOX9, TP73, MYB, FOXA2, ETV4, and TEAD4, a transcription factor negatively regulated by the Hippo tumor suppressor pathway (Supplementary Table S3). It is easily understandable that selection for activation of these sets of genes would provide a growth advantage to the tumor cell population. However, the DNA methylation pathway, if operative at bivalent promoters after loss of H3K27me3, may not immediately provide such a selective advantage because the affected genes are already expressed at a very low level while in the bivalent state in normal cells.

Figure 6.

Fate of bivalent promoters in colorectal cancer. The model depicts the state of promoters containing H3K4me3 (green) and H3K27me3 (red) in normal colonic mucosa and how this state has resolved in cancer cells. The disappearance of the H3K27me3 mark can be associated with DNA methylation and permanent repression of genes (bottom) or, alternatively, with activation of growth-promoting genes (top).

Figure 6.

Fate of bivalent promoters in colorectal cancer. The model depicts the state of promoters containing H3K4me3 (green) and H3K27me3 (red) in normal colonic mucosa and how this state has resolved in cancer cells. The disappearance of the H3K27me3 mark can be associated with DNA methylation and permanent repression of genes (bottom) or, alternatively, with activation of growth-promoting genes (top).

Close modal

Two nonexclusive models of colorectal cancer initiation have been discussed. According to mouse models, it has been suggested that Lgr5+ cells from the crypt bottom comprise the tumor-initiating cell population (44). Other models favor a “top-down” model, in which dysplastic cells can originate in the upper areas of crypts (45, 46). The latter model invokes a dedifferentiation process in which the cells re-acquire stem cell–like properties. Our data are consistent with a model in which colorectal cancer can arise from differentiated epithelial cells in which the bivalent chromatin state resolves into active or inactive forms. It is likely that the instability of bivalent genes is a mechanism that predisposes the colonic epithelium to cancer by being operative already during inflammatory processes. Elevated NF-κB signaling, as found in chronic inflammation, has been shown to enhance Wnt activation and to induce dedifferentiation of non-stem cells in the colon that acquire tumor-initiating capacity (45). Inflammation has been linked to methylation of Polycomb-marked genes in the intestinal epithelium of mice (18). We show here that activation of cancer-relevant genes occurs at bivalent promoters in inflamed differentiated mucosa from patients with UC.

Besides inflammation, aging is a major risk factor for cancer. Similar to inflammatory conditions, the aging process has been associated with DNA hypermethylation of Polycomb target genes (47, 48). If the loss of the Polycomb mark underlies both DNA methylation silencing and the activation of bivalent genes in cancer cells, a mechanistic connection between inflammation, aging, and cancer can be proposed, in which gene activation because of H3K27me3 loss may easily be a dominant driving force for the malignant change.

Questions remain as to the possible mechanisms underlying the high variability of the Polycomb mark. Earlier studies showed that the H3K27 methyltransferase EZH2 is downregulated in stressed and senescing populations of cells, which coincided with decreased levels of H3K27me3 at the INK4A-ARF locus (49). However, it has often been observed that EZH2 is overexpressed in human tumors (50, 51). In our samples, we observed that EZH2 was expressed at higher levels in tumors than in normal mucosa but we did not find substantial differences in expression of the H3K27me3 demethylases KDM6A or KDM6B. It remains to be determined whether structural or functional aberrations of the Polycomb complex itself underlie the cancer-associated dysfunction of Polycomb marking at bivalent promoters or if bivalency of these loci itself predisposes them to inherent or transcription factor–driven variability and loss of the H3K27me3 mark, resulting in activation of genes with functional importance for tumor progression.

G.P. Pfeifer has ownership interest (including patents) from Active Motif. G.P. Pfeifer is a consultant/advisory board member of Zymo Research. No potential conflicts of interest were disclosed by the other authors.

Conception and design: M.A. Hahn, G.P. Pfeifer

Development of methodology: M.A. Hahn, A.X. Li, G.P. Pfeifer

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): X. Wu, D.A. Drew, D.W. Rosenberg

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M.A. Hahn, A.X. Li, X. Wu, R. Yang, G.P. Pfeifer

Writing, review, and or revision of the manuscript: M.A. Hahn, A.X. Li, X. Wu, D.A. Drew, D.W. Rosenberg, G.P. Pfeifer

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A.X. Li

Study supervision: G.P. Pfeifer

This work was supported by NIH grant CA 084469 to G.P. Pfeifer.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Jones
PA
,
Baylin
SB
. 
The epigenomics of cancer
.
Cell
2007
;
128
:
683
92
.
2.
Shen
H
,
Laird
PW
. 
Interplay between the cancer genome and epigenome
.
Cell
2013
;
153
:
38
55
.
3.
Timp
W
,
Feinberg
AP
. 
Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host
.
Nat Rev Cancer
2013
;
13
:
497
510
.
4.
Vogelstein
B
,
Papadopoulos
N
,
Velculescu
VE
,
Zhou
S
,
Diaz
LA
 Jr
,
Kinzler
KW
. 
Cancer genome landscapes
.
Science
2013
;
339
:
1546
58
.
5.
Fearon
ER
. 
Molecular genetics of colorectal cancer
.
Annu Rev Pathol
2011
;
6
:
479
507
.
6.
Suzuki
MM
,
Bird
A
. 
DNA methylation landscapes: provocative insights from epigenomics
.
Nat Rev Genet
2008
;
9
:
465
76
.
7.
Rauch
TA
,
Zhong
X
,
Wu
X
,
Wang
M
,
Kernstine
KH
,
Wang
Z
, et al
High-resolution mapping of DNA hypermethylation and hypomethylation in lung cancer
.
Proc Natl Acad Sci U S A
2008
;
105
:
252
7
.
8.
Berman
BP
,
Weisenberger
DJ
,
Aman
JF
,
Hinoue
T
,
Ramjan
Z
,
Liu
Y
, et al
Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated domains
.
Nat Genet
2012
;
44
:
40
6
.
9.
Estecio
MR
,
Issa
JP
. 
Dissecting DNA hypermethylation in cancer
.
FEBS Lett
2011
;
585
:
2078
86
.
10.
Bert
SA
,
Robinson
MD
,
Strbenac
D
,
Statham
AL
,
Song
JZ
,
Hulf
T
, et al
Regional activation of the cancer genome by long-range epigenetic remodeling
.
Cancer Cell
2013
;
23
:
9
22
.
11.
Weichenhan
D
,
Plass
C
. 
The evolving epigenome
.
Hum Mol Genet
2013
;
22
:
R1
6
.
12.
Putiri
EL
,
Robertson
KD
. 
Epigenetic mechanisms and genome stability
.
Clin Epigenetics
2011
;
2
:
299
314
.
13.
Nagarajan
RP
,
Fouse
SD
,
Bell
RJ
,
Costello
JF
. 
Methods for cancer epigenome analysis
.
Adv Exp Med Biol
2013
;
754
:
313
38
.
14.
Hughes
LA
,
Melotte
V
,
de Schrijver
J
,
de Maat
M
,
Smit
VT
,
Bovee
JV
, et al
The CpG island methylator phenotype: what's in a name?
Cancer Res
2013
;
73
:
5858
68
.
15.
Ohm
JE
,
McGarvey
KM
,
Yu
X
,
Cheng
L
,
Schuebel
KE
,
Cope
L
, et al
A stem cell-like chromatin pattern may predispose tumor suppressor genes to DNA hypermethylation and heritable silencing
.
Nat Genet
2007
;
39
:
237
42
.
16.
Schlesinger
Y
,
Straussman
R
,
Keshet
I
,
Farkash
S
,
Hecht
M
,
Zimmerman
J
, et al
Polycomb-mediated methylation on Lys27 of histone H3 pre-marks genes for de novo methylation in cancer
.
Nat Genet
2007
;
39
:
232
6
.
17.
Widschwendter
M
,
Fiegl
H
,
Egle
D
,
Mueller-Holzner
E
,
Spizzo
G
,
Marth
C
, et al
Epigenetic stem cell signature in cancer
.
Nat Genet
2007
;
39
:
157
8
.
18.
Hahn
MA
,
Hahn
T
,
Lee
DH
,
Esworthy
RS
,
Kim
BW
,
Riggs
AD
, et al
Methylation of polycomb target genes in intestinal cancer is mediated by inflammation
.
Cancer Res
2008
;
68
:
10280
9
.
19.
Rauch
T
,
Li
H
,
Wu
X
,
Pfeifer
GP
. 
Mira-assisted microarray analysis, a new technology for the determination of DNA methylation patterns, identifies frequent methylation of homeodomain-containing genes in lung cancer cells
.
Cancer Res
2006
;
66
:
7939
47
.
20.
Rauch
T
,
Wang
Z
,
Zhang
X
,
Zhong
X
,
Wu
X
,
Lau
SK
, et al
Homeobox gene methylation in lung cancer studied by genome-wide analysis with a microarray-based methylated CpG island recovery assay
.
Proc Natl Acad Sci U S A
2007
;
104
:
5527
32
.
21.
Simon
JA
,
Kingston
RE
. 
Occupying chromatin: Polycomb mechanisms for getting to genomic targets, stopping transcriptional traffic, and staying put
.
Mol Cell
2013
;
49
:
808
24
.
22.
Aloia
L
,
Di Stefano
B
,
Di Croce
L
. 
Polycomb complexes in stem cells and embryonic development
.
Development
2013
;
140
:
2525
34
.
23.
Kalari
S
,
Pfeifer
GP
. 
Identification of driver and passenger DNA methylation in cancer by epigenomic analysis
.
Adv Genet
2010
;
70
:
277
308
.
24.
You
JS
,
Jones
PA
. 
Cancer genetics and epigenetics: two sides of the same coin?
Cancer Cell
2012
;
22
:
9
20
.
25.
Suva
ML
,
Riggi
N
,
Bernstein
BE
. 
Epigenetic reprogramming in cancer
.
Science
2013
;
339
:
1567
70
.
26.
Hahn
MA
,
Qiu
R
,
Wu
X
,
Li
AX
,
Zhang
H
,
Wang
J
, et al
Dynamics of 5-hydroxymethylcytosine and chromatin marks in mammalian neurogenesis
.
Cell Rep
2013
;
3
:
291
300
.
27.
Hahn
MA
,
Wu
X
,
Li
AX
,
Hahn
T
,
Pfeifer
GP
. 
Relationship between gene body DNA methylation and intragenic H3K9me3 and H3K36me3 chromatin marks
.
PLoS ONE
2011
;
6
:
e18844
.
28.
Wu
X
,
Rauch
TA
,
Zhong
X
,
Bennett
WP
,
Latif
F
,
Krex
D
, et al
CpG island hypermethylation in human astrocytomas
.
Cancer Res
2010
;
70
:
2718
27
.
29.
Ooi
SK
,
Qiu
C
,
Bernstein
E
,
Li
K
,
Jia
D
,
Yang
Z
, et al
Dnmt3l connects unmethylated lysine 4 of histone H3 to de novo methylation of DNA
.
Nature
2007
;
448
:
714
7
.
30.
Edwards
JR
,
O'Donnell
AH
,
Rollins
RA
,
Peckham
HE
,
Lee
C
,
Milekic
MH
, et al
Chromatin and sequence features that define the fine and gross structure of genomic methylation patterns
.
Genome Res
2010
;
20
:
972
80
.
31.
Bernstein
BE
,
Mikkelsen
TS
,
Xie
X
,
Kamal
M
,
Huebert
DJ
,
Cuff
J
, et al
A bivalent chromatin structure marks key developmental genes in embryonic stem cells
.
Cell
2006
;
125
:
315
26
.
32.
Voigt
P
,
Tee
WW
,
Reinberg
D
. 
A double take on bivalent promoters
.
Genes Dev
2013
;
27
:
1318
38
.
33.
Kondo
Y
,
Shen
L
,
Cheng
AS
,
Ahmed
S
,
Boumber
Y
,
Charo
C
, et al
Gene silencing in cancer by histone H3 lysine 27 trimethylation independent of promoter DNA methylation
.
Nat Genet
2008
;
40
:
741
50
.
34.
Gal-Yam
EN
,
Egger
G
,
Iniguez
L
,
Holster
H
,
Einarsson
S
,
Zhang
X
, et al
Frequent switching of polycomb repressive marks and DNA hypermethylation in the PC3 prostate cancer cell line
.
Proc Natl Acad Sci U S A
2008
;
105
:
12979
84
.
35.
Barker
N
,
van Es
JH
,
Kuipers
J
,
Kujala
P
,
van den Born
M
,
Cozijnsen
M
, et al
Identification of stem cells in small intestine and colon by marker gene Lgr5
.
Nature
2007
;
449
:
1003
7
.
36.
van der Flier
LG
,
van Gijn
ME
,
Hatzis
P
,
Kujala
P
,
Haegebarth
A
,
Stange
DE
, et al
Transcription factor achaete scute-like 2 controls intestinal stem cell fate
.
Cell
2009
;
136
:
903
12
.
37.
Stange
DE
,
Engel
F
,
Longerich
T
,
Koo
BK
,
Koch
M
,
Delhomme
N
, et al
Expression of an ASCL2 related stem cell signature and IGF2 in colorectal cancer liver metastases with 11p15.5 gain
.
Gut
2010
;
59
:
1236
44
.
38.
Kosinski
C
,
Li
VS
,
Chan
AS
,
Zhang
J
,
Ho
C
,
Tsui
WY
, et al
Gene expression patterns of human colon tops and basal crypts and BMP antagonists as intestinal stem cell niche factors
.
Proc Natl Acad Sci U S A
2007
;
104
:
15418
23
.
39.
Sabates-Bellver
J
,
Van der Flier
LG
,
de Palo
M
,
Cattaneo
E
,
Maake
C
,
Rehrauer
H
, et al
Transcriptome profile of human colorectal adenomas
.
Mol Cancer Res
2007
;
5
:
1263
75
.
40.
Terzic
J
,
Grivennikov
S
,
Karin
E
,
Karin
M
. 
Inflammation and colon cancer
.
Gastroenterology
2010
;
138
:
2101
14 e5
.
41.
Issa
JP
,
Ahuja
N
,
Toyota
M
,
Bronner
MP
,
Brentnall
TA
. 
Accelerated age-related CpG island methylation in ulcerative colitis
.
Cancer Res
2001
;
61
:
3573
7
.
42.
Chiba
T
,
Marusawa
H
,
Ushijima
T
. 
Inflammation-associated cancer development in digestive organs: mechanisms and roles for genetic and epigenetic modulation
.
Gastroenterology
2012
;
143
:
550
63
.
43.
Planell
N
,
Lozano
JJ
,
Mora-Buch
R
,
Masamunt
MC
,
Jimeno
M
,
Ordas
I
, et al
Transcriptional analysis of the intestinal mucosa of patients with ulcerative colitis in remission reveals lasting epithelial cell alterations
.
Gut
2013
;
62
:
967
76
.
44.
Barker
N
,
Ridgway
RA
,
van Es
JH
,
van de Wetering
M
,
Begthel
H
,
van den Born
M
, et al
Crypt stem cells as the cells-of-origin of intestinal cancer
.
Nature
2009
;
457
:
608
11
.
45.
Schwitalla
S
,
Fingerle
AA
,
Cammareri
P
,
Nebelsiek
T
,
Goktuna
SI
,
Ziegler
PK
, et al
Intestinal tumorigenesis initiated by dedifferentiation and acquisition of stem-cell-like properties
.
Cell
2013
;
152
:
25
38
.
46.
Shih
IM
,
Wang
TL
,
Traverso
G
,
Romans
K
,
Hamilton
SR
,
Ben-Sasson
S
, et al
Top-down morphogenesis of colorectal tumors
.
Proc Natl Acad Sci U S A
2001
;
98
:
2640
5
.
47.
Beerman
I
,
Bock
C
,
Garrison
BS
,
Smith
ZD
,
Gu
H
,
Meissner
A
, et al
Proliferation-dependent alterations of the DNA methylation landscape underlie hematopoietic stem cell aging
.
Cell Stem Cell
2013
;
12
:
413
25
.
48.
Maegawa
S
,
Hinkal
G
,
Kim
HS
,
Shen
L
,
Zhang
L
,
Zhang
J
, et al
Widespread and tissue specific age-related DNA methylation changes in mice
.
Genome Res
2010
;
20
:
332
40
.
49.
Bracken
AP
,
Kleine-Kohlbrecher
D
,
Dietrich
N
,
Pasini
D
,
Gargiulo
G
,
Beekman
C
, et al
The polycomb group proteins bind throughout the Ink4a-Arf locus and are disassociated in senescent cells
.
Genes Dev
2007
;
21
:
525
30
.
50.
Bracken
AP
,
Pasini
D
,
Capra
M
,
Prosperini
E
,
Colli
E
,
Helin
K
. 
Ezh2 is downstream of the PRB-E2F pathway, essential for proliferation and amplified in cancer
.
EMBO J
2003
;
22
:
5323
35
.
51.
Varambally
S
,
Dhanasekaran
SM
,
Zhou
M
,
Barrette
TR
,
Kumar-Sinha
C
,
Sanda
MG
, et al
The polycomb group protein EZH2 is involved in progression of prostate cancer
.
Nature
2002
;
419
:
624
9
.