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Correlation of an epigenetic mitotic clock with cancer risk.

ABSTRACT: Variation 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.Here, 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.Unlike 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.

SUBMITTER: Yang Z

PROVIDER: S-EPMC5046977 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Correlation of an epigenetic mitotic clock with cancer risk.

Yang Zhen Z Wong Andrew A Kuh Diana D Paul Dirk S DS Rakyan Vardhman K VK Leslie R David RD Zheng Shijie C SC Widschwendter Martin M Beck Stephan S Teschendorff Andrew E AE

Genome biology 20161003 1

<h4>Background</h4>Variation 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.<h4>Results</h4>H ...[more]

PMID: 27716309

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Project description:BackgroundDNA methylation changes that accrue in the stem cell pool of an adult tissue in line with the cumulative number of cell divisions may contribute to the observed variation in cancer risk among tissues and individuals. Thus, the construction of epigenetic "mitotic" clocks that can measure the lifetime number of stem cell divisions is of paramount interest.MethodsBuilding upon a dynamic model of DNA methylation gain in unmethylated CpG-rich regions, we here derive a novel mitotic clock ("epiTOC2") that can directly estimate the cumulative number of stem cell divisions in a tissue. We compare epiTOC2 to a different mitotic model, based on hypomethylation at solo-WCGW sites ("HypoClock"), in terms of their ability to measure mitotic age of normal adult tissues and predict cancer risk.ResultsUsing epiTOC2, we estimate the intrinsic stem cell division rate for different normal tissue types, demonstrating excellent agreement (Pearson correlation?=?0.92, R2?=?0.85, P?=?3e-6) with those derived from experiment. In contrast, HypoClock's estimates do not (Pearson correlation?=?0.30, R2?=?0.09, P?=?0.29). We validate these results in independent datasets profiling normal adult tissue types. While both epiTOC2 and HypoClock correctly predict an increased mitotic rate in cancer, epiTOC2 is more robust and significantly better at discriminating preneoplastic lesions characterized by chronic inflammation, a major driver of tissue turnover and cancer risk. Our data suggest that DNA methylation loss at solo-WCGWs is significant only when cells are under high replicative stress and that epiTOC2 is a better mitotic age and cancer risk prediction model for normal adult tissues.ConclusionsThese results have profound implications for our understanding of epigenetic clocks and for developing cancer risk prediction or early detection assays. We propose that measurement of DNAm at the 163 epiTOC2 CpGs in adult pre-neoplastic lesions, and potentially in serum cell-free DNA, could provide the basis for building feasible pre-diagnostic or cancer risk assays. epiTOC2 is freely available from https://doi.org/10.5281/zenodo.2632938.

Project description:BackgroundAgeing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue.MethodsTo address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle.ResultsThe newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies.ConclusionsWe have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes.

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Correlation of an epigenetic mitotic clock with cancer risk.

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Correlation of an epigenetic mitotic clock with cancer risk.

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