The application of methylation specific electrophoresis (MSE) to DNA methylation analysis of the 5' CpG island of mucin in cancer cells

Methylation of CpG sites in genomic DNA plays an important role in gene regulation and especially in gene silencing. We have reported mechanisms of epigenetic regulation for expression of mucins, which are markers of malignancy potential and early detection of human neoplasms. Epigenetic changes in promoter regions appear to be the first step in expression of mucins. Thus, detection of promoter methylation status is important for early diagnosis of cancer, monitoring of tumor behavior, and evaluating the response of tumors to targeted therapy. However, conventional analytical methods for DNA methylation require a large amount of DNA and have low sensitivity. Here, we report a modified version of the bisulfite-DGGE (denaturing gradient gel electrophoresis) using a nested PCR approach. We designated this method as methylation specific electrophoresis (MSE). The MSE method is comprised of the following steps: (a) bisulfite treatment of genomic DNA, (b) amplification of the target DNA by a nested PCR approach and (c) applying to DGGE. To examine whether the MSE method is able to analyze DNA methylation of mucin genes in various samples, we apply it to DNA obtained from state cell lines, ethanol-fixed colonic crypts and human pancreatic juices. The MSE method greatly decreases the amount of input DNA. The lower detection limit for distinguishing different methylation status is < 0.1% and the detectable minimum amount of DNA is 20 pg, which can be obtained from only a few cells. We also show that MSE can be used for analysis of challenging samples such as human isolated colonic crypts or human pancreatic juices, from which only a small amount of DNA can be extracted. The MSE method can provide a qualitative information of methylated sequence profile. The MSE method allows sensitive and specific analysis of the DNA methylation pattern of almost any block of multiple CpG sites. The MSE method can be applied to analysis of DNA methylation status in many different clinical samples, and this may facilitate identification of new risk markers