Evidence map›Paper›PMID 27716309›Full record

ArticleGenome biology2016

Correlation of an epigenetic mitotic clock with cancer risk.

Zhen Yang, Andrew Wong, Diana Kuh, Dirk S Paul, Vardhman K Rakyan, R David Leslie, Shijie C Zheng, Martin Widschwendter, Stephan Beck, Andrew E Teschendorff

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 208 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
208citing papers in PubMed, 2 pooled it
9.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

208 citing papers in PubMed, 2 syntheses or guidelines pooled it, 340 citations in OpenAlex.

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148 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Zhen YangCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China.
Andrew WongMRC Unit for Lifelong Health and Ageing at University College London, London, UK.
Diana KuhMRC Unit for Lifelong Health and Ageing at University College London, London, UK.
Dirk S PaulMedical Genomics, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
Vardhman K RakyanThe Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK.
R David LeslieThe Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK.
Shijie C ZhengCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China.
Martin WidschwendterDepartment of Women's Cancer, University College London, 74 Huntley Street, London, WC1E 6AU, UK.
Stephan BeckMedical Genomics, UCL Cancer Institute, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
Andrew E TeschendorffCAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai, 200031, China. a.teschendorff@ucl.ac.uk.
University College London · GBCenter for Excellence in Molecular Cell Science · CNMRC Unit for Lifelong Health and Ageing · GBQueen Mary University of London · GB

Funding

Medical Research Council G0800270Medical Research Council MC_UU_12019/1
6 · The paper itself

Abstract

backgroundVariation in cancer risk among somatic tissues has been attributed to variations in the underlying rate of stem cell division. For a given tissue type, variable cancer risk between individuals is thought to be influenced by extrinsic factors which modulate this rate of stem cell division. To date, no molecular mitotic clock has been developed to approximate the number of stem cell divisions in a tissue of an individual and which is correlated with cancer risk.

resultsHere, we integrate mathematical modeling with prior biological knowledge to construct a DNA methylation-based age-correlative model which approximates a mitotic clock in both normal and cancer tissue. By focusing on promoter CpG sites that localize to Polycomb group target genes that are unmethylated in 11 different fetal tissue types, we show that increases in DNA methylation at these sites defines a tick rate which correlates with the estimated rate of stem cell division in normal tissues. Using matched DNA methylation and RNA-seq data, we further show that it correlates with an expression-based mitotic index in cancer tissue. We demonstrate that this mitotic-like clock is universally accelerated in cancer, including pre-cancerous lesions, and that it is also accelerated in normal epithelial cells exposed to a major carcinogen.

conclusionsUnlike other epigenetic and mutational clocks or the telomere clock, the epigenetic clock proposed here provides a concrete example of a mitotic-like clock which is universally accelerated in cancer and precancerous lesions.

Indexed as

Epigenesis, GeneticAgingCpG IslandsDNA MethylationGene Expression Regulation, NeoplasticHigh-Throughput Nucleotide SequencingHumansMitosisMitotic IndexModels, TheoreticalNeoplasmsNeoplastic Stem CellsPolycomb-Group ProteinsPromoter Regions, GeneticPolycomb-Group ProteinsAgeingCancerDNA methylationEpigenetic clockMitoticStem cells

Identifiers

PMID27716309
PMCPMC5046977
OpenAlexW2529317472

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.