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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

Gene clusters hypermethylated in breast cancer and associated with poor survival. (A) Heat maps showing averaged DNA methylation in the different gene cluster loci (left panel). (B) Kaplan-Meier survival curves indicating candidate cluster gene hypermethylation are associated with decreased survival (right panel).
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Fig2: Gene clusters hypermethylated in breast cancer and associated with poor survival. (A) Heat maps showing averaged DNA methylation in the different gene cluster loci (left panel). (B) Kaplan-Meier survival curves indicating candidate cluster gene hypermethylation are associated with decreased survival (right panel).

Mentions: Recent studies including ours [11-13] found that DNA methylation patterns span long stretches of chromosome regions that mostly consist of gene clusters in different types of cancer. We therefore examined hypermethylated levels of more than 60 unique gene clusters in our breast cohort (77 tumor vs. 10 normal), where hypermethylation in the breast tumors was defined in relative terms to DNA methylation in normal breast tissue, and then performed survival analysis to determine their significance. Survival analysis, represented by Kaplan-Meier curves, was conducted using the third quartile as the cutoff value to dichotomize patients into high- and low-methylation groups (Figure 2A). We found that methylation levels of 38 of these unique gene clusters were significantly correlated with OS, showing that these gene clusters’ hypermethylated levels were a high risk factor and positively correlated with a poor survival (Figure 2B) (Additional file 2). We further selected seven gene clusters from these which have been reported in the literature to have biological functions and protein domains associated with estrogen interactions and/or cancer development for further investigation [23-28]. Our analyses also determined that most but not all of the hypermethylated genes in a particular gene cluster were able to be included in stratifying patients with a statistical significance, implying that these excluded few genes in the cluster may exhibit a more distinct functional role. For example, 9 of 11 metallothionein-1 (MT1) genes (MT1A, B, E, G, H, L, and X), including two hypothetical genes MT1DP and MT1IP, were able to predict a poor survival with a P = 0.004. MT1F and MT1M, which are not in the list, exert anti-oncogenic effects (see last section in Results).Figure 2


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)

Gene clusters hypermethylated in breast cancer and associated with poor survival. (A) Heat maps showing averaged DNA methylation in the different gene cluster loci (left panel). (B) Kaplan-Meier survival curves indicating candidate cluster gene hypermethylation are associated with decreased survival (right panel).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Fig2: Gene clusters hypermethylated in breast cancer and associated with poor survival. (A) Heat maps showing averaged DNA methylation in the different gene cluster loci (left panel). (B) Kaplan-Meier survival curves indicating candidate cluster gene hypermethylation are associated with decreased survival (right panel).
Mentions: Recent studies including ours [11-13] found that DNA methylation patterns span long stretches of chromosome regions that mostly consist of gene clusters in different types of cancer. We therefore examined hypermethylated levels of more than 60 unique gene clusters in our breast cohort (77 tumor vs. 10 normal), where hypermethylation in the breast tumors was defined in relative terms to DNA methylation in normal breast tissue, and then performed survival analysis to determine their significance. Survival analysis, represented by Kaplan-Meier curves, was conducted using the third quartile as the cutoff value to dichotomize patients into high- and low-methylation groups (Figure 2A). We found that methylation levels of 38 of these unique gene clusters were significantly correlated with OS, showing that these gene clusters’ hypermethylated levels were a high risk factor and positively correlated with a poor survival (Figure 2B) (Additional file 2). We further selected seven gene clusters from these which have been reported in the literature to have biological functions and protein domains associated with estrogen interactions and/or cancer development for further investigation [23-28]. Our analyses also determined that most but not all of the hypermethylated genes in a particular gene cluster were able to be included in stratifying patients with a statistical significance, implying that these excluded few genes in the cluster may exhibit a more distinct functional role. For example, 9 of 11 metallothionein-1 (MT1) genes (MT1A, B, E, G, H, L, and X), including two hypothetical genes MT1DP and MT1IP, were able to predict a poor survival with a P = 0.004. MT1F and MT1M, which are not in the list, exert anti-oncogenic effects (see last section in Results).Figure 2

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