Aberrant DNA methylation of CpG islands, CpG island shores and first exons is 
known to play a key role in the altered gene expression patterns in all human 
cancers. To date, a systematic study on the effect of DNA methylation on gene 
expression using high resolution data has not been reported. In this study, we 
conducted an integrated analysis of MethylCap-sequencing data and Affymetrix 
gene expression microarray data for 30 breast cancer cell lines representing 
different breast tumor phenotypes. As well-developed methods for the integrated 
analysis do not currently exist, we created a series of four different analysis 
methods. On the computational side, our goal is to develop methylome data 
analysis protocols for the integrated analysis of DNA methylation and gene 
expression data on the genome scale. On the cancer biology side, we present 
comprehensive genome-wide methylome analysis results for differentially 
methylated regions and their potential effect on gene expression in 30 breast 
cancer cell lines representing three molecular phenotypes, luminal, basal A and 
basal B. Our integrated analysis demonstrates that methylation status of 
different genomic regions may play a key role in establishing transcriptional 
patterns in molecular subtypes of human breast cancer.