ArticleBMC bioinformatics2016
Stochastic epigenetic outliers can define field defects in cancer.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Individualised progesterone receptor modulator prevention strategies for triple-negative breast cancer in BRCA1 pathogenic variant carriers.NPJ breast cancer · 2026Review
- Lactylation-based machine algorithm combined with multi-omics analysis to predict prognosis in cervical cancer.Oncology letters · 2026Article
- High- versus low-dose dietary n-3 PUFA treatment produces mixed effects on DNA methylation and epigenetic fidelity in breast adipose tissue.medRxiv : the preprint server for health sciences · 2026Article
- Methylation differences between assisted reproductive technology-conceived and naturally conceived children nearEpigenetics · 2025Article
- UNet with Attention Networks: A Novel Deep Learning Approach for DNA Methylation Prediction in HeLa Cells.Genes · 2025Article
- Epigenetic signatures in surrogate tissues are able to assess cancer risk and indicate the efficacy of preventive measures.Communications medicine · 2025Article
- Potential use of DNA methylation in cervical swabs for early ovarian cancer diagnosis.Journal of ovarian research · 2025Article
- Advancing epigenetic profiling in cervical cancer: machine learning techniques for classifying DNA methylation patterns.3 Biotech · 2024Article
- An improved epigenetic counter to track mitotic age in normal and precancerous tissues.Nature communications · 2024Article
- On epigenetic stochasticity, entropy and cancer risk.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- A new approach to study stochastic epigenetic mutations in sperm methylome of Vietnam war veterans directly exposed to Agent Orange.Environmental epigenetics · 2024Article
- Efficiency of CIN2+ Detection by Thyrotropin-Releasing Hormone (TRH) Site-Specific Methylation.Viruses · 2023Article
- Article
- Assessing the risk of cervical neoplasia in the post-HPV vaccination era.International journal of cancer · 2023Review
- Epigenetics as a mediator of plasticity in cancer.Science (New York, N.Y.) · 2023Review
- Assessing Differential Variability of High-Throughput DNA Methylation Data.Current environmental health reports · 2022Review
- At age 9, the methylome of assisted reproductive technology children that underwent embryo culture in different media is not significantly different on a genome-wide scale.Human reproduction (Oxford, England) · 2022Article
- Methylome-wide analysis of IVF neonates that underwent embryo culture in different media revealed no significant differences.NPJ genomic medicine · 2022Article
- A robust mean and variance test with application to high-dimensional phenotypes.European journal of epidemiology · 2022Review
- Accelerated aging in normal breast tissue of women with breast cancer.Breast cancer research : BCR · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is growing evidence that DNA methylation alterations may contribute to carcinogenesis. Recent data also suggest that DNA methylation field defects in normal pre-neoplastic tissue represent infrequent stochastic "outlier" events. This presents a statistical challenge for standard feature selection algorithms, which assume frequent alterations in a disease phenotype. Although differential variability has emerged as a novel feature selection paradigm for the discovery of outliers, a growing concern is that these could result from technical confounders, in principle thus favouring algorithms which are robust to outliers.
resultsHere we evaluate five differential variability algorithms in over 700 DNA methylomes, including two of the largest cohorts profiling precursor cancer lesions, and demonstrate that most of the novel proposed algorithms lack the sensitivity to detect epigenetic field defects at genome-wide significance. In contrast, algorithms which recognise heterogeneous outlier DNA methylation patterns are able to identify many sites in pre-neoplastic lesions, which display progression in invasive cancer. Thus, we show that many DNA methylation outliers are not technical artefacts, but define epigenetic field defects which are selected for during cancer progression.
conclusionsGiven that cancer studies aiming to find epigenetic field defects are likely to be limited by sample size, adopting the novel feature selection paradigm advocated here will be critical to increase assay sensitivity.
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