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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

Basal level expression and DNA methylation for most of the genes in MT1 gene cluster show lower expression and higher methylation in breast cancer cell lines. (A) RT-qPCR gene expression and (B) averaged methylation profiles of MT1 genes in cell lines representing ERα + (MCF7 and BT474) and ERα − (BT20 and MDAMB231) subsets compared to normal (HMEC used for PCR and average of normal samples for DNA methylation) revealing lower levels of expression and higher levels of DNA methylation in cell lines compared to normal.
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Fig5: Basal level expression and DNA methylation for most of the genes in MT1 gene cluster show lower expression and higher methylation in breast cancer cell lines. (A) RT-qPCR gene expression and (B) averaged methylation profiles of MT1 genes in cell lines representing ERα + (MCF7 and BT474) and ERα − (BT20 and MDAMB231) subsets compared to normal (HMEC used for PCR and average of normal samples for DNA methylation) revealing lower levels of expression and higher levels of DNA methylation in cell lines compared to normal.

Mentions: Next, we performed quantitative reverse transcription PCR (RT-qPCR) to examine the gene expression level for the MT1 gene cluster in selected breast cell lines, including one normal cell line, human mammary epithelial cells (HMEC), two ERα + cell lines, MCF7, BT474, and two ERα − cell lines, BT20 and MDA-MB231. Although there are publicly available gene expression data in 61 breast cancer cell lines [33], the cell lines we used for profiling methylation are not completely overlapping with them, and some of the genes in our study were not in the profiling. As shown in Figure 5A, overall, all genes showed lower expression in four breast cancer cell lines than in the HMEC cell line, except MT1F and MT1X, where MT1F has lower in HMEC than in MCF7 and MDA-MB231 cells, and MT1X has a similar level in MDA-MB231 cells. Meanwhile, there are no clear differences for each individual gene in two ERα − vs. two ERα + breast cancer cell lines. This may be due to the cell model not fully recapitulating the molecular characteristics of the primary tumors. We also found that there are no detectable expression levels for MT1B in all cell lines. This is consistent with the TCGA data showing no expression for this gene in all patients and normal samples. By examining the methylation levels in these cell lines (Figure 5B), we found that all genes showed higher methylation in breast cancer cell lines than normal tissue while we did not find a clear differential pattern between ERα + and ERα − cell lines. These validations further support our earlier observation that the correlation of lower expression with hypermethylation for this gene cluster is independent of the status of ERα in the breast tumors.Figure 5


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)

Basal level expression and DNA methylation for most of the genes in MT1 gene cluster show lower expression and higher methylation in breast cancer cell lines. (A) RT-qPCR gene expression and (B) averaged methylation profiles of MT1 genes in cell lines representing ERα + (MCF7 and BT474) and ERα − (BT20 and MDAMB231) subsets compared to normal (HMEC used for PCR and average of normal samples for DNA methylation) revealing lower levels of expression and higher levels of DNA methylation in cell lines compared to normal.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig5: Basal level expression and DNA methylation for most of the genes in MT1 gene cluster show lower expression and higher methylation in breast cancer cell lines. (A) RT-qPCR gene expression and (B) averaged methylation profiles of MT1 genes in cell lines representing ERα + (MCF7 and BT474) and ERα − (BT20 and MDAMB231) subsets compared to normal (HMEC used for PCR and average of normal samples for DNA methylation) revealing lower levels of expression and higher levels of DNA methylation in cell lines compared to normal.
Mentions: Next, we performed quantitative reverse transcription PCR (RT-qPCR) to examine the gene expression level for the MT1 gene cluster in selected breast cell lines, including one normal cell line, human mammary epithelial cells (HMEC), two ERα + cell lines, MCF7, BT474, and two ERα − cell lines, BT20 and MDA-MB231. Although there are publicly available gene expression data in 61 breast cancer cell lines [33], the cell lines we used for profiling methylation are not completely overlapping with them, and some of the genes in our study were not in the profiling. As shown in Figure 5A, overall, all genes showed lower expression in four breast cancer cell lines than in the HMEC cell line, except MT1F and MT1X, where MT1F has lower in HMEC than in MCF7 and MDA-MB231 cells, and MT1X has a similar level in MDA-MB231 cells. Meanwhile, there are no clear differences for each individual gene in two ERα − vs. two ERα + breast cancer cell lines. This may be due to the cell model not fully recapitulating the molecular characteristics of the primary tumors. We also found that there are no detectable expression levels for MT1B in all cell lines. This is consistent with the TCGA data showing no expression for this gene in all patients and normal samples. By examining the methylation levels in these cell lines (Figure 5B), we found that all genes showed higher methylation in breast cancer cell lines than normal tissue while we did not find a clear differential pattern between ERα + and ERα − cell lines. These validations further support our earlier observation that the correlation of lower expression with hypermethylation for this gene cluster is independent of the status of ERα in the breast tumors.Figure 5

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