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Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
A novel method to quantify local CpG methylation density by regional methylation elongation assay on microarray.
Dingdong Zhang1, Yan Wang, Yunfei Bai
1State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China. zdd_7597@seu.edu.cn
BMC Genomics
|February 2, 2008
Summary
This study introduces a new microarray method for quantifying DNA methylation density, crucial for gene silencing. The regional methylation elongation assay on microarray (RMEAM) offers a high-throughput, accurate analysis of methylation patterns.
Area of Science:
- Epigenetics
- Molecular Biology
- Cancer Genomics
Background:
- DNA methylation analysis is vital for clinical diagnostics and therapeutics.
- Current methods often analyze limited CpG sites, overlooking regional methylation density.
- Methylation density, rather than single CpG sites, is critical for gene silencing.
Purpose of the Study:
- To develop a novel, quantitative method for analyzing CpG methylation density.
- To overcome limitations of existing site-specific methylation analysis techniques.
- To assess the methylation density of key genes in colorectal cancer.
Main Methods:
- Developed a microarray-based hybridization technique incorporating Cy5-dCTP into Cy3-labeled DNA.
- Utilized Taq DNA Polymerase for quantitative analysis of methylation.
- Quantification achieved by measuring the Cy5/Cy3 signal ratio, proportional to methylation density.
- Introduced the regional methylation elongation assay on microarray (RMEAM).
Main Results:
- RMEAM enables precise quantification of regional methylation density.
- The method demonstrated high throughput potential.
- Applied RMEAM to determine methylation density in the promoter regions of MLH1, TERT, and MGMT in colorectal carcinoma patients.
Conclusions:
- RMEAM provides quantitative analysis of regional methylation density, representing all allelic methylation patterns.
- The technique is simple, rapid, specific, and high-throughput.
- This method is valuable for studying epigenetic alterations in diseases like cancer.

