ArticlePLoS computational biology2016
A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett's Esophagus.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
30 citing papers in PubMed.
- The biology and therapeutic implications of heterogeneity in Barrett oesophagus and oesophageal adenocarcinoma.Nature reviews. Clinical oncology · 2026Review
- Aging-Related Mechanisms Underlying Carcinogenesis: Therapeutic Opportunities.Aging and disease · 2025Review
- An improved epigenetic counter to track mitotic age in normal and precancerous tissues.Nature communications · 2024Article
- Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma.Nature communications · 2023Article
- CNETML: maximum likelihood inference of phylogeny from copy number profiles of multiple samples.Genome biology · 2023Article
- Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study.Scientific reports · 2023Article
- Increased PXR and Suppressed T-Cell Signaling Are Associated With Malignant Degeneration of Barrett's Esophagus.Gastro hep advances · 2023Article
- DNA Methylation, Aging, and Cancer Risk: A Mini-Review.Frontiers in bioinformatics · 2022Review
- Evolution and progression of Barrett's oesophagus to oesophageal cancer.Nature reviews. Cancer · 2021Review
- Optimal Timing for Cancer Screening and Adaptive Surveillance Using Mathematical Modeling.Cancer research · 2021Article
- Within-patient phylogenetic reconstruction reveals early events in Barrett's Esophagus.Evolutionary applications · 2021Article
- Epigenetic Alterations in the Gastrointestinal Tract: Current and Emerging Use for Biomarkers of Cancer.Gastroenterology · 2021Review
- Barrett's Esophagus and Esophageal Adenocarcinoma Biomarkers.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Article
- Inferring Tumor Proliferative Organization from Phylogenetic Tree Measures in a Computational Model.Systematic biology · 2020Article
- A comparison of epigenetic mitotic-like clocks for cancer risk prediction.Genome medicine · 2020Article
- Epigenetic Aging: More Than Just a Clock When It Comes to Cancer.Cancer research · 2020Review
- Implications of Epigenetic Drift in Colorectal Neoplasia.Cancer research · 2019Article
- Molecular Evolution of Metaplasia to Adenocarcinoma in the Esophagus.Digestive diseases and sciences · 2018Review
- Models of epigenetic age capture patterns of DNA methylation in glioma associated with molecular subtype, survival, and recurrence.Neuro-oncology · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Biomarkers that drift differentially with age between normal and premalignant tissues, such as Barrett's esophagus (BE), have the potential to improve the assessment of a patient's cancer risk by providing quantitative information about how long a patient has lived with the precursor (i.e., dwell time). In the case of BE, which is a metaplastic precursor to esophageal adenocarcinoma (EAC), such biomarkers would be particularly useful because EAC risk may change with BE dwell time and it is generally not known how long a patient has lived with BE when a patient is first diagnosed with this condition. In this study we first describe a statistical analysis of DNA methylation data (both cross-sectional and longitudinal) derived from tissue samples from 50 BE patients to identify and validate a set of 67 CpG dinucleotides in 51 CpG islands that undergo age-related methylomic drift. Next, we describe how this information can be used to estimate a patient's BE dwell time. We introduce a Bayesian model that incorporates longitudinal methylomic drift rates, patient age, and methylation data from individually paired BE and normal squamous tissue samples to estimate patient-specific BE onset times. Our application of the model to 30 sporadic BE patients' methylomic profiles first exposes a wide heterogeneity in patient-specific BE onset times. Furthermore, independent application of this method to a cohort of 22 familial BE (FBE) patients reveals significantly earlier mean BE onset times. Our analysis supports the conjecture that differential methylomic drift occurs in BE (relative to normal squamous tissue) and hence allows quantitative estimation of the time that a BE patient has lived with BE.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.