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Changes in correlation between promoter methylation and gene expression in cancer.

Moarii M, Boeva V, Vert JP, Reyal F - BMC Genomics (2015)

Bottom Line: Methylation of high-density CpG regions known as CpG Islands (CGIs) has been widely described as a mechanism associated with gene expression regulation.However, this hypermethylation is not accompanied by a decrease in expression of the corresponding genes, which are already lowly expressed in the normal genes.It may instead modify how the expression of a few specific genes, particularly transcription factors, are associated with DNA methylation variations in a tissue-dependent manner.

View Article: PubMed Central - PubMed

Affiliation: CBIO-Centre for Computational Biology, Mines Paristech, PSL-Research University, 35 Rue Saint-Honore, Fontainebleau, F-77300, France. matahi.moarii@mines-paristech.fr.

ABSTRACT

Background: Methylation of high-density CpG regions known as CpG Islands (CGIs) has been widely described as a mechanism associated with gene expression regulation. Aberrant promoter methylation is considered a hallmark of cancer involved in silencing of tumor suppressor genes and activation of oncogenes. However, recent studies have also challenged the simple model of gene expression control by promoter methylation in cancer, and the precise mechanism of and role played by changes in DNA methylation in carcinogenesis remains elusive.

Results: Using a large dataset of 672 matched cancerous and healthy methylomes, gene expression, and copy number profiles accross 3 types of tissues from The Cancer Genome Atlas (TCGA), we perform a detailed meta-analysis to clarify the interplay between promoter methylation and gene expression in normal and cancer samples. On the one hand, we recover the existence of a CpG island methylator phenotype (CIMP) with prognostic value in a subset of breast, colon and lung cancer samples, where a common subset of promoter CGIs hypomethylated in normal samples become hypermethylated. However, this hypermethylation is not accompanied by a decrease in expression of the corresponding genes, which are already lowly expressed in the normal genes. On the other hand, we identify tissue-specific sets of genes, different between normal and cancer samples, whose inter-individual variation in expression is significantly correlated with the variation in methylation of the 3' flanking regions of the promoter CGIs. These subsets of genes are not the same in the different tissues, nor between normal and cancerous samples, but transcription factors are over-represented in all subsets.

Conclusion: Our results suggest that epigenetic reprogramming in cancer does not contribute to cancer development via direct inhibition of gene expression through promoter hypermethylation. It may instead modify how the expression of a few specific genes, particularly transcription factors, are associated with DNA methylation variations in a tissue-dependent manner.

No MeSH data available.


Related in: MedlinePlus

Distribution of gene expression in different clusters for in breast tissues. Gene expression distribution for genes based on the cluster assignment of their associated CGI + SS. Panel a Gene expression distribution in normal breast tissues shows a slight repression for genes associated with cluster 2 (hyper-methylated CGI + SS profiles). “Ref” represents the genome-wide gene expression distribution Panel b Gene expression profiles in cancerous breast tissues shows high repression for genes associated with cluster 3 and specifically cluster “3up” (hemi-methylated CGI + SS profiles). Panel c Gene expression profiles in both normal and cancerous breast tissues using the cluster assignement in cancerous tissues shows that genes associated with cluster “3up” in cancerous tissues define a cluster of genes already repressed in normal tissues
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Fig4: Distribution of gene expression in different clusters for in breast tissues. Gene expression distribution for genes based on the cluster assignment of their associated CGI + SS. Panel a Gene expression distribution in normal breast tissues shows a slight repression for genes associated with cluster 2 (hyper-methylated CGI + SS profiles). “Ref” represents the genome-wide gene expression distribution Panel b Gene expression profiles in cancerous breast tissues shows high repression for genes associated with cluster 3 and specifically cluster “3up” (hemi-methylated CGI + SS profiles). Panel c Gene expression profiles in both normal and cancerous breast tissues using the cluster assignement in cancerous tissues shows that genes associated with cluster “3up” in cancerous tissues define a cluster of genes already repressed in normal tissues

Mentions: CGI methylation is often associated with gene expression silencing. We therefore assess whether the CGI + SS clusters defined above, corresponding roughly to lowly methylated (clusters 1), highly methylated (cluster 2) or partially methylated in cancer (cluster 3) CGI + SS, are associated with different mean levels of gene expression. In normal breast tissues, we indeed observe that genes near hypo-methylated islands in cluster 1 are slightly but significantly less expressed than genes near an hyper-methylated islands in cluster 2 (Fig. 4a, PBreast=0.02). There is however no significant difference between the two clusters in normal lung tissues (Additional file 7a, PLung=0.39), and we could not test the hypothesis on normal colon tissues since we have none with both methylation and expression data (Table 1). In cancerous samples, we observe that genes near a CGI + SS in the cancer-specific cluster 3 have a significantly lower expression than other genes (Fig. 4b, Additional files 7b and 8, PBreast,PLung,PColon< 10−16), particularly for the genes near a CGI + SS in the “3up” cluster. As genes in the “3up” cluster are hypo-methylated in normal tissues, this could suggest that their cancer-specific methylation is a way to repress their expression in cancer. However, a closer look at the expression of these genes in normal tissues (Fig. 4c, Additional file 7c) shows that they are already lowly expressed in normal tissues. This suggests that instead of activating CGI methylation to silence to genes, cancer cells instead activates CGI methylation of hypo-methylated genes which are already lowly expressed in normal tissues.Fig. 4


Changes in correlation between promoter methylation and gene expression in cancer.

Moarii M, Boeva V, Vert JP, Reyal F - BMC Genomics (2015)

Distribution of gene expression in different clusters for in breast tissues. Gene expression distribution for genes based on the cluster assignment of their associated CGI + SS. Panel a Gene expression distribution in normal breast tissues shows a slight repression for genes associated with cluster 2 (hyper-methylated CGI + SS profiles). “Ref” represents the genome-wide gene expression distribution Panel b Gene expression profiles in cancerous breast tissues shows high repression for genes associated with cluster 3 and specifically cluster “3up” (hemi-methylated CGI + SS profiles). Panel c Gene expression profiles in both normal and cancerous breast tissues using the cluster assignement in cancerous tissues shows that genes associated with cluster “3up” in cancerous tissues define a cluster of genes already repressed in normal tissues
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4625954&req=5

Fig4: Distribution of gene expression in different clusters for in breast tissues. Gene expression distribution for genes based on the cluster assignment of their associated CGI + SS. Panel a Gene expression distribution in normal breast tissues shows a slight repression for genes associated with cluster 2 (hyper-methylated CGI + SS profiles). “Ref” represents the genome-wide gene expression distribution Panel b Gene expression profiles in cancerous breast tissues shows high repression for genes associated with cluster 3 and specifically cluster “3up” (hemi-methylated CGI + SS profiles). Panel c Gene expression profiles in both normal and cancerous breast tissues using the cluster assignement in cancerous tissues shows that genes associated with cluster “3up” in cancerous tissues define a cluster of genes already repressed in normal tissues
Mentions: CGI methylation is often associated with gene expression silencing. We therefore assess whether the CGI + SS clusters defined above, corresponding roughly to lowly methylated (clusters 1), highly methylated (cluster 2) or partially methylated in cancer (cluster 3) CGI + SS, are associated with different mean levels of gene expression. In normal breast tissues, we indeed observe that genes near hypo-methylated islands in cluster 1 are slightly but significantly less expressed than genes near an hyper-methylated islands in cluster 2 (Fig. 4a, PBreast=0.02). There is however no significant difference between the two clusters in normal lung tissues (Additional file 7a, PLung=0.39), and we could not test the hypothesis on normal colon tissues since we have none with both methylation and expression data (Table 1). In cancerous samples, we observe that genes near a CGI + SS in the cancer-specific cluster 3 have a significantly lower expression than other genes (Fig. 4b, Additional files 7b and 8, PBreast,PLung,PColon< 10−16), particularly for the genes near a CGI + SS in the “3up” cluster. As genes in the “3up” cluster are hypo-methylated in normal tissues, this could suggest that their cancer-specific methylation is a way to repress their expression in cancer. However, a closer look at the expression of these genes in normal tissues (Fig. 4c, Additional file 7c) shows that they are already lowly expressed in normal tissues. This suggests that instead of activating CGI methylation to silence to genes, cancer cells instead activates CGI methylation of hypo-methylated genes which are already lowly expressed in normal tissues.Fig. 4

Bottom Line: Methylation of high-density CpG regions known as CpG Islands (CGIs) has been widely described as a mechanism associated with gene expression regulation.However, this hypermethylation is not accompanied by a decrease in expression of the corresponding genes, which are already lowly expressed in the normal genes.It may instead modify how the expression of a few specific genes, particularly transcription factors, are associated with DNA methylation variations in a tissue-dependent manner.

View Article: PubMed Central - PubMed

Affiliation: CBIO-Centre for Computational Biology, Mines Paristech, PSL-Research University, 35 Rue Saint-Honore, Fontainebleau, F-77300, France. matahi.moarii@mines-paristech.fr.

ABSTRACT

Background: Methylation of high-density CpG regions known as CpG Islands (CGIs) has been widely described as a mechanism associated with gene expression regulation. Aberrant promoter methylation is considered a hallmark of cancer involved in silencing of tumor suppressor genes and activation of oncogenes. However, recent studies have also challenged the simple model of gene expression control by promoter methylation in cancer, and the precise mechanism of and role played by changes in DNA methylation in carcinogenesis remains elusive.

Results: Using a large dataset of 672 matched cancerous and healthy methylomes, gene expression, and copy number profiles accross 3 types of tissues from The Cancer Genome Atlas (TCGA), we perform a detailed meta-analysis to clarify the interplay between promoter methylation and gene expression in normal and cancer samples. On the one hand, we recover the existence of a CpG island methylator phenotype (CIMP) with prognostic value in a subset of breast, colon and lung cancer samples, where a common subset of promoter CGIs hypomethylated in normal samples become hypermethylated. However, this hypermethylation is not accompanied by a decrease in expression of the corresponding genes, which are already lowly expressed in the normal genes. On the other hand, we identify tissue-specific sets of genes, different between normal and cancer samples, whose inter-individual variation in expression is significantly correlated with the variation in methylation of the 3' flanking regions of the promoter CGIs. These subsets of genes are not the same in the different tissues, nor between normal and cancerous samples, but transcription factors are over-represented in all subsets.

Conclusion: Our results suggest that epigenetic reprogramming in cancer does not contribute to cancer development via direct inhibition of gene expression through promoter hypermethylation. It may instead modify how the expression of a few specific genes, particularly transcription factors, are associated with DNA methylation variations in a tissue-dependent manner.

No MeSH data available.


Related in: MedlinePlus