Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA343785 | ENA |
REPOSITORIES: ENA
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Project description: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.
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Project description:The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 480,000 CpGs in a total of 407 samples, including 50 normal samples from healthy women, 42 matched normal-adjacent breast cancer pairs (84 samples), 263 unmatched breast cancers, 7 normal samples from BRCA1 carriers and 4 BRCA1 breast cancers. Bisulphite converted DNA from the 407 samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
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