GSE160233
DREAM of purified normal human mammary epithelial cells
DNA methylation alterations have similar patterns in normal aging tissue and in cancer. In this study, we investigated breast tissue-specific age-related DNA methylation alterations and used those methylation sites to identify individuals with outlier phenotypes. Outlier phenotype is identified by unsupervised anomaly detection algorithms and is defined by individuals who have normal tissue age-dependent DNA methylation levels that vary dramatically from the population mean. To identify age-dependent DNA methylation sites, we generated DNA methylation sequencing data for 29 purified normal adjacent human breast epithelia (age range 33-82 years old) using Digital Restriction Enzyme Analysis of Methylation (DREAM). Next, we validated the age-related sites in publicly available DNA methylation (450K array) of 97 normal adjacent TCGA samples. We found that hypermethylation in normal breast tissue is the best predictor of hypermethylation in cancer. Using unsupervised anomaly detection approaches, we found that about 10% of the individuals (39 /427) were outliers for DNA methylation from 6 publicly available DNA methylation datasets (GSE88883, GSE74214, GSE101961, GSE69914(normal), GSE69914(normal-adjacent), TCGA (Firehose Legacy)). We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) then in normal samples (15/228, 5.2%). Additionally, we found significant differences between predicted ages based on DNA methylation and the chronological ages among outliers and not-outliers. Additionally, we found that accelerated outliers (older predicted age) were more frequent in normal-adjacent to cancer (14/17, 82%) compared to normal samples from individuals without cancer (3/17, 18%). Furthermore, in matched samples, the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer. Overall design: Digital restriction enzyme analysis of methylation (DREAM) was performed to determine the methylation profile of 29 purified normal adjacent human breast epithelia (age range 33-82 years old). Briefly, DREAM is a quantitative mapping of DNA methylation with high resolution on a genome-wide scale. The method is based on sequential cuts of genomic DNA with a pair of neoschizomer endonucleases (SmaI & XmaI) recognizing the same restriction site (CCCGGG) containing a CpG dinucleotide (CG). SmaI cuts first all unmethylated sites at CCC^GGG while the methylation tolerant XmaI follows by cutting the methylated sites at C^CCGGG. The enzymes thus generate distinct methylation-specific signatures at the ends of DNA fragments which are deciphered by next generation sequencing. The methylation level at individual CpG sites is calculated as the ratio of sequencing reads with the methylated signature CCGGG to the total number of reads mapping to the site.