ArticleBreast cancer research : BCR2021
Accelerated aging in normal breast tissue of women with breast cancer.
Article in Breast cancer research : BCR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Can DNA Methylation in Peritumoral and Contralateral Breast Tissue Predict Recurrence or Second Breast Cancers?Current issues in molecular biology · 2026Article
- Single-cell profiling reveals distinct populations of tumor-associated macrophages and metastatic tumor cells in breast cancer brain metastasis.Cell death & disease · 2026Article
- Environmental endocrine disruptors: rethinking the origins of early-onset ERNature reviews. Cancer · 2025Article
- Article
- DNA methylation patterns in breast cancer, paired benign tissue from ipsilateral and contralateral breast, and healthy controls.Breast cancer research : BCR · 2025Article
- Selective Estrogen Receptor Modulators' (SERMs) Influence onInternational journal of molecular sciences · 2024Article
- Natural Compounds for Preventing Age-Related Diseases and Cancers.International journal of molecular sciences · 2024Review
- Review
- Comprehensive single cell aging atlas of mammary tissues reveals shared epigenomic and transcriptomic signatures of aging and cancer.bioRxiv : the preprint server for biology · 2023Article
- Article
- DNA methylation entropy as a measure of stem cell replication and aging.Genome biology · 2023Article
- Epigenome-Wide Study Identifies Epigenetic Outliers in Normal Mucosa of Patients with Colorectal Cancer.Cancer prevention research (Philadelphia, Pa.) · 2022Article
- Article
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundDNA 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.
methodsWe generated whole-genome DNA methylation profiles (GSE160233) on purified epithelial cells and used publicly available Infinium HumanMethylation 450K array datasets (TCGA, GSE88883, GSE69914, GSE101961, and GSE74214) for discovery and validation.
resultsWe 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 DNA methylation datasets. We also found that there were significantly more outlier samples in normal-adjacent to cancer (24/139, 17.3%) than in normal samples (15/228, 5.2%). Additionally, we found significant differences between the 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, we found that the epigenome of the outliers in the pre-malignant tissue was as severely altered as in cancer.
conclusionsA subset of patients with breast cancer has severely altered epigenomes which are characterized by accelerated aging in their normal-appearing tissue. In the future, these DNA methylation sites should be studied further such as in cell-free DNA to determine their potential use as biomarkers for early detection of malignant transformation and preventive intervention in breast cancer.
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