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Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.

Jadhav RR, Ye Z, Huang RL, Liu J, Hsu PY, Huang YW, Rangel LB, Lai HC, Roa JC, Kirma NB, Huang TH, Jin VX - Clin Epigenetics (2015)

Bottom Line: Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes.Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer.Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Medicine/Institute of Biotechnology, University of Texas Health Science Center at San Antonio, STRF, Room 225, 7703 Floyd Curl Drive, San Antonio, 78229 TX USA.

ABSTRACT

Background: Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines.

Results: Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα-) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17β-estradiol (E2) and demethylating agent 5-aza-2'-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer.

Conclusions: Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.

No MeSH data available.


Related in: MedlinePlus

Lower expression and higher methylation of MT1 gene cluster for ERα + compared to ERα − and normal patient samples is observed in TCGA RNA-seq and our MBD-seq cohort, respectively. (A) A heat map showing RNA-seq expression data from TCGA for all the genes in identified clusters along with fold change comparisons (left) with normal vs. tumor and ERα − vs. ERα + samples. (B) A boxplot showing the significant difference in average gene expressions in each subset compared to normal for all the genes in MT1 gene cluster. (C) A boxplot showing significant difference in average MT1 cluster gene methylation for each subset compared to normal samples in our MDB-seq cohort.
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Fig3: Lower expression and higher methylation of MT1 gene cluster for ERα + compared to ERα − and normal patient samples is observed in TCGA RNA-seq and our MBD-seq cohort, respectively. (A) A heat map showing RNA-seq expression data from TCGA for all the genes in identified clusters along with fold change comparisons (left) with normal vs. tumor and ERα − vs. ERα + samples. (B) A boxplot showing the significant difference in average gene expressions in each subset compared to normal for all the genes in MT1 gene cluster. (C) A boxplot showing significant difference in average MT1 cluster gene methylation for each subset compared to normal samples in our MDB-seq cohort.

Mentions: Next, we utilized the publicly available TCGA breast cancer cohort, including 106 normal tissue and 988 primary tumor samples, and examined the expression values measured by RNA-seq data for these hypermethylated gene clusters. Interestingly, we found five gene clusters, ZNF, PCDH, MT1, HOXD, and HOXA, which showed reduced expression in cancer patients compared to normal tissues. However, the other two clusters, HOXC and HIST1, surprisingly showed increased expression levels (Figure 3A). Although this latter observation is inconsistent with a traditional view that the promoter hypermethylated genes in tumors are usually positively correlated with lower expression, this supported a newly established concept that the methylated status of other gene regions, such as intragenic and 3′TTS, may also play a role in determining the overall expression as demonstrated by many studies [30-32]. Nevertheless, for the first time, our findings provide a correlation between methylation status and gene expression level at a gene cluster scale. A further detailed examination of the MT1 gene cluster revealed that the ERα + tumor samples have a much lower gene expression level than ERα negative (ERα−) tumor samples while both display significantly lower gene expression level than normal tissue samples (Figure 3B). However, their methylation levels showed a decrease in an order of ERα + tumor, ERα − tumor, and normal samples (Figure 3C). This positive correlation prompted us to ask if the epigenetic repression of this gene cluster is associated with the status of ERα level (positive vs. negative) in the breast tumors. To this end, we re-examined K-M survival analysis based on the status of ERα level and found that both ERα + and ERα − patients show poor outcomes for the hypermethylated MT1 genes (Figure 4A). A Cox proportional hazard regression model further confirmed that the hazard ratios show statistical significance for methylation, age, and grading but not for ERα status (Figure 4B). Most of the individual genes in the cluster also showed a significant negative correlation between DNA methylation and gene expression in both ERα + and ERα − patient samples (Additional file 1: Figure S10). This data supported a notion that DNA methylation is an important factor contributing to gene repression regardless of the estrogen receptor (ER) status in breast tumors.Figure 3


Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.

Jadhav RR, Ye Z, Huang RL, Liu J, Hsu PY, Huang YW, Rangel LB, Lai HC, Roa JC, Kirma NB, Huang TH, Jin VX - Clin Epigenetics (2015)

Lower expression and higher methylation of MT1 gene cluster for ERα + compared to ERα − and normal patient samples is observed in TCGA RNA-seq and our MBD-seq cohort, respectively. (A) A heat map showing RNA-seq expression data from TCGA for all the genes in identified clusters along with fold change comparisons (left) with normal vs. tumor and ERα − vs. ERα + samples. (B) A boxplot showing the significant difference in average gene expressions in each subset compared to normal for all the genes in MT1 gene cluster. (C) A boxplot showing significant difference in average MT1 cluster gene methylation for each subset compared to normal samples in our MDB-seq cohort.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4355986&req=5

Fig3: Lower expression and higher methylation of MT1 gene cluster for ERα + compared to ERα − and normal patient samples is observed in TCGA RNA-seq and our MBD-seq cohort, respectively. (A) A heat map showing RNA-seq expression data from TCGA for all the genes in identified clusters along with fold change comparisons (left) with normal vs. tumor and ERα − vs. ERα + samples. (B) A boxplot showing the significant difference in average gene expressions in each subset compared to normal for all the genes in MT1 gene cluster. (C) A boxplot showing significant difference in average MT1 cluster gene methylation for each subset compared to normal samples in our MDB-seq cohort.
Mentions: Next, we utilized the publicly available TCGA breast cancer cohort, including 106 normal tissue and 988 primary tumor samples, and examined the expression values measured by RNA-seq data for these hypermethylated gene clusters. Interestingly, we found five gene clusters, ZNF, PCDH, MT1, HOXD, and HOXA, which showed reduced expression in cancer patients compared to normal tissues. However, the other two clusters, HOXC and HIST1, surprisingly showed increased expression levels (Figure 3A). Although this latter observation is inconsistent with a traditional view that the promoter hypermethylated genes in tumors are usually positively correlated with lower expression, this supported a newly established concept that the methylated status of other gene regions, such as intragenic and 3′TTS, may also play a role in determining the overall expression as demonstrated by many studies [30-32]. Nevertheless, for the first time, our findings provide a correlation between methylation status and gene expression level at a gene cluster scale. A further detailed examination of the MT1 gene cluster revealed that the ERα + tumor samples have a much lower gene expression level than ERα negative (ERα−) tumor samples while both display significantly lower gene expression level than normal tissue samples (Figure 3B). However, their methylation levels showed a decrease in an order of ERα + tumor, ERα − tumor, and normal samples (Figure 3C). This positive correlation prompted us to ask if the epigenetic repression of this gene cluster is associated with the status of ERα level (positive vs. negative) in the breast tumors. To this end, we re-examined K-M survival analysis based on the status of ERα level and found that both ERα + and ERα − patients show poor outcomes for the hypermethylated MT1 genes (Figure 4A). A Cox proportional hazard regression model further confirmed that the hazard ratios show statistical significance for methylation, age, and grading but not for ERα status (Figure 4B). Most of the individual genes in the cluster also showed a significant negative correlation between DNA methylation and gene expression in both ERα + and ERα − patient samples (Additional file 1: Figure S10). This data supported a notion that DNA methylation is an important factor contributing to gene repression regardless of the estrogen receptor (ER) status in breast tumors.Figure 3

Bottom Line: Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes.Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer.Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Medicine/Institute of Biotechnology, University of Texas Health Science Center at San Antonio, STRF, Room 225, 7703 Floyd Curl Drive, San Antonio, 78229 TX USA.

ABSTRACT

Background: Recent genome-wide analysis has shown that DNA methylation spans long stretches of chromosome regions consisting of clusters of contiguous CpG islands or gene families. Hypermethylation of various gene clusters has been reported in many types of cancer. In this study, we conducted methyl-binding domain capture (MBDCap) sequencing (MBD-seq) analysis on a breast cancer cohort consisting of 77 patients and 10 normal controls, as well as a panel of 38 breast cancer cell lines.

Results: Bioinformatics analysis determined seven gene clusters with a significant difference in overall survival (OS) and further revealed a distinct feature that the conservation of a large gene cluster (approximately 70 kb) metallothionein-1 (MT1) among 45 species is much lower than the average of all RefSeq genes. Furthermore, we found that DNA methylation is an important epigenetic regulator contributing to gene repression of MT1 gene cluster in both ERα positive (ERα+) and ERα negative (ERα-) breast tumors. In silico analysis revealed much lower gene expression of this cluster in The Cancer Genome Atlas (TCGA) cohort for ERα + tumors. To further investigate the role of estrogen, we conducted 17β-estradiol (E2) and demethylating agent 5-aza-2'-deoxycytidine (DAC) treatment in various breast cancer cell types. Cell proliferation and invasion assays suggested MT1F and MT1M may play an anti-oncogenic role in breast cancer.

Conclusions: Our data suggests that DNA methylation in large contiguous gene clusters can be potential prognostic markers of breast cancer. Further investigation of these clusters revealed that estrogen mediates epigenetic repression of MT1 cluster in ERα + breast cancer cell lines. In all, our studies identify thousands of breast tumor hypermethylated regions for the first time, in particular, discovering seven large contiguous hypermethylated gene clusters.

No MeSH data available.


Related in: MedlinePlus