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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

DNA hypermethylation in breast cancer samples relative to normal breast tissue in promoter and non-promoter CpG islands. Methyl capture sequencing (MBD-seq) was used to generate DNA methylation profiles of the genomes of breast tumors (n = 77) and normal breast tissue (n = 10). (A) Pie charts demonstrate differential methylation in promoter, intragenic, and intergenic CGIs as well as non-CGI promoter regions (left panel). Methylation of core and shore regions is also demonstrated under each corresponding CGI type (left panel). DNA hypermethylation in core and shore regions are shown for breast tumors compared to normal tissue (right panel). (B) Example loci showing promoter CGI, intragenic, intergenic, and non-CGI promoter regions. Dashed squares highlight regions corresponding to breast cancer hypermethylation.
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Fig1: DNA hypermethylation in breast cancer samples relative to normal breast tissue in promoter and non-promoter CpG islands. Methyl capture sequencing (MBD-seq) was used to generate DNA methylation profiles of the genomes of breast tumors (n = 77) and normal breast tissue (n = 10). (A) Pie charts demonstrate differential methylation in promoter, intragenic, and intergenic CGIs as well as non-CGI promoter regions (left panel). Methylation of core and shore regions is also demonstrated under each corresponding CGI type (left panel). DNA hypermethylation in core and shore regions are shown for breast tumors compared to normal tissue (right panel). (B) Example loci showing promoter CGI, intragenic, intergenic, and non-CGI promoter regions. Dashed squares highlight regions corresponding to breast cancer hypermethylation.

Mentions: We conducted MBD-seq to investigate methylation patterns on a genome-wide scale for a cohort of breast cancer patients (n = 77), Integrative Cancer Biology Program (ICBP) breast cancer cell lines (n = 38), and normal mammary tissue (n = 10). Over 20 million unique reads were analyzed for all samples, a coverage expected to provide sufficient sequence depth for methylation mapping of the whole genome (Additional file 1: Figure S1). Differential methylation between breast tumor and normal control samples (Additional file 1: Table S3) was observed in promoter CpG islands (CGIs) (19.5% of 13,081 promoter CGIs analyzed; P < 0.05), as well as intragenic CGIs (55.2% of 6,959 intragenic CGIs analyzed; P < 0.01), intergenic CGIs (28.1% of 4,847 intergenic CGIs analyzed; P < 0.01), and non-CGI promoters (1.8% of 5,454 non-CGI promoters; P < 0.01) (Figure 1A, left panel). DNA hypermethylation in breast tumors compared to normal control occurred predominantly in CGI cores at transcription start site (TSS) regions and also in regions flanking CGIs, or so-called CpG shores (Figure 1A, right panel). This distinct type of methylation pattern was first reported in colon cancer [22]. Examples of loci exhibiting hypermethylation in breast tumor samples relative to normal tissue in promoter CGIs (CIDEA), intragenic CGIs (RASGEF1A), intergenic CGIs (FOXB1), and non-CGI promoters (COL11A1) are presented in Figure 1B (hypermethylated regions are outlined by dashed squares) and in Additional file 1: Figure S2.Figure 1


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)

DNA hypermethylation in breast cancer samples relative to normal breast tissue in promoter and non-promoter CpG islands. Methyl capture sequencing (MBD-seq) was used to generate DNA methylation profiles of the genomes of breast tumors (n = 77) and normal breast tissue (n = 10). (A) Pie charts demonstrate differential methylation in promoter, intragenic, and intergenic CGIs as well as non-CGI promoter regions (left panel). Methylation of core and shore regions is also demonstrated under each corresponding CGI type (left panel). DNA hypermethylation in core and shore regions are shown for breast tumors compared to normal tissue (right panel). (B) Example loci showing promoter CGI, intragenic, intergenic, and non-CGI promoter regions. Dashed squares highlight regions corresponding to breast cancer hypermethylation.
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Related In: Results  -  Collection

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Fig1: DNA hypermethylation in breast cancer samples relative to normal breast tissue in promoter and non-promoter CpG islands. Methyl capture sequencing (MBD-seq) was used to generate DNA methylation profiles of the genomes of breast tumors (n = 77) and normal breast tissue (n = 10). (A) Pie charts demonstrate differential methylation in promoter, intragenic, and intergenic CGIs as well as non-CGI promoter regions (left panel). Methylation of core and shore regions is also demonstrated under each corresponding CGI type (left panel). DNA hypermethylation in core and shore regions are shown for breast tumors compared to normal tissue (right panel). (B) Example loci showing promoter CGI, intragenic, intergenic, and non-CGI promoter regions. Dashed squares highlight regions corresponding to breast cancer hypermethylation.
Mentions: We conducted MBD-seq to investigate methylation patterns on a genome-wide scale for a cohort of breast cancer patients (n = 77), Integrative Cancer Biology Program (ICBP) breast cancer cell lines (n = 38), and normal mammary tissue (n = 10). Over 20 million unique reads were analyzed for all samples, a coverage expected to provide sufficient sequence depth for methylation mapping of the whole genome (Additional file 1: Figure S1). Differential methylation between breast tumor and normal control samples (Additional file 1: Table S3) was observed in promoter CpG islands (CGIs) (19.5% of 13,081 promoter CGIs analyzed; P < 0.05), as well as intragenic CGIs (55.2% of 6,959 intragenic CGIs analyzed; P < 0.01), intergenic CGIs (28.1% of 4,847 intergenic CGIs analyzed; P < 0.01), and non-CGI promoters (1.8% of 5,454 non-CGI promoters; P < 0.01) (Figure 1A, left panel). DNA hypermethylation in breast tumors compared to normal control occurred predominantly in CGI cores at transcription start site (TSS) regions and also in regions flanking CGIs, or so-called CpG shores (Figure 1A, right panel). This distinct type of methylation pattern was first reported in colon cancer [22]. Examples of loci exhibiting hypermethylation in breast tumor samples relative to normal tissue in promoter CGIs (CIDEA), intragenic CGIs (RASGEF1A), intergenic CGIs (FOXB1), and non-CGI promoters (COL11A1) are presented in Figure 1B (hypermethylated regions are outlined by dashed squares) and in Additional file 1: Figure S2.Figure 1

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