A Clinical Correlation study of DNA Methyltransferases Alterations in Breast Cancer and Evaluation of DNA Methyltransferases as a Therapeutic Target in Cell and Animal Models

Project: A - Government Institutionb - National Science and Technology Council

Project Details


Background and significance: Breast cancer is the most common non-cutaneous cancer diagnosed in women in the United States and is second only to lung cancer as the leading cause of cancer-related mortality. Cancer is caused by the accumulation of both genetic and epigenetic changes. Methylation of CpG islands, which are about 1-2 kb in length in or near the promoter and first exon regions of genes, is considered to be one of the major epigenetic aberrations that causes tumor suppressor genes (TSGs) inactivation in tumor development. DNMTs are the enzymes which are responsible for DNA methylation through transfer of methyl group to cytosine residue of CpGs. A previous study found that the mRNA expression of DNMT3B was highly up-regulated in breast cancer. Therefore, whether DNMT1, 3A and 3B protein also over-expressed in breast cancer are worth to investigate. In our preliminary study, the protein expression of DNMT1 (4/7, 57.1%) and DNMT3B (7/10, 70%) was indeed over-expressed in breast cancer using immunohistochemistry and encourage the search for inhibitors of DNMTs as anticancer treatments. We therefore hypothesized that DNMT may be a good target for breast cancer therapy. Blocking 5’-cytosine-methyltransferase (DNMT) could potentially reverse the process of epigenetic silencing and reactivate tumor suppressor genes (TSGs). Pharmacologic inhibitors of DNA methylation thus provide an attractive and rational approach to reversal of epigenetic silencing of TSGs, with the hope that they will induce promoters de-methylation and reactivation of TSGs genes in tumor cells, restore activity of TSGs in critical cellular pathways and sensitizes breast cancer cells to endocrine therapy. Study design: The mRNA and protein expression levels of DNA methyltransferase genes (DNMTs) will first be examined by real-time PCR and immunohistochemistry in 150 breast cancer patients. And we will further to analyze the correlation of the DNMTs expression with the clinicopathological parameters, prognosis and metastasis state in breast cancer. To develop novel DNMTs inhibitors, in vitro and in vivo inhibition of DNA methylation assay will be serially examined. High potential DNMT inhibitor will be further treated in the breast cancer and normal cells to demonstrate whether novel inhibitors enable to induce cancer cytoxicity, inhibit metastasis, activate apoptosis or promote differentiation. Identification of drug induced demethylation and TSGs re-expression also will be further performed in the cells. In vivo antitumor activity and toxicity of novel DNMT inhibitors will also be evaluated in xenograft model. Preliminary results: Immunohistochemistry indicated that the protein expression of DNMT1 (4/7, 57.1%) and DNMT3B (7/10, 70%) was overexpressed in breast cancer. The DNMT1 enzyme activity assays showed that several phenolics compounds could inhibit the methylation effect of DNMT1, especially for compound P6 (P= 0.0006). P6 compound can inhibit 92.5% activity of DNMT1. In addition, P6 showed higher inhibitory effect to DNMT1 enzyme than EGCG in vitro. We also found ubiquinone derivatives (LTH0909-1) and sesquiterpene derivatives (WJ-3) also could suppress DNMT1 activity. We further indicated that LTH0909-1 could inhibit DNMT1 enzyme in a dose dependent manner. The demethylation effect by LTH0909-1 at the promoters of tumor suppressor genes, RARβ, was found when treated with LTH0909-1 in MDA-MB-231 breast cancer cell line for 3 days. LTH0909-1 also dramatically induced gene expressions of Tumor suppressor genes RARβ and Endocrine therapy sensitive gene ESR1 in MDA-MB-231 breast cancer cell line.
Effective start/end date8/1/137/31/14


  • breast cancer
  • DNMT
  • tumor suppressor gene
  • natural compound


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.