Correlation of an epigenetic mitotic clock with cancer risk

Yang et al. Genome Biology (2016) 17:205 DOI 10.1186/s13059-016-1064-3 RESEARCH Open Access Correlation of an epigenetic mitotic clock with cancer risk Zhen Yang1†, Andrew Wong2, Diana Kuh2, Dirk S. Paul3, Vardhman K. Rakyan4, R. David Leslie4, Shijie C. Zheng1, Martin Widschwendter5, Stephan Beck3 and Andrew E. Teschendorff1,5,6*† Abstract Background: 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. Results: 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. Conclusions: 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. Keywords: DNA methylation, Epigenetic clock, Cancer, Mitotic, Stem cells, Ageing Background Estimating the relative rate of stem cell divisions of a given tissue type between individuals may allow their stratification according to their prospective risk of cancer [1, 2]. It is therefore of interest to construct molecular mitotic-like clocks, which may provide an approximate estimate of the relative stem cell division rate of a tissue in an individual [3–5]. While telomere shortening represents a mitotic clock [6] and has been associated with increased cancer risk [7], these associations have, however, been largely inconsistent and only * Correspondence: ; † Equal contributors 1 CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, 320 Yue Yang Road, Shanghai 200031, China 5 Department of Women’s Cancer, University College London, 74 Huntley Street, London WC1E 6AU, UK Full list of author information is available at the end of the article obtained in surrogate tissues such as blood [8]. A recently identified mutational clock-like signature [5] may also approximate a mitotic clock but has not yet been applied to cancer risk prediction. Errors in the maintenance of DNA methylation (DNAm) arising during cell division may accumulate in the stem cell population of a tissue in line with the stem cell division rate and chronological age and have been proposed as molecular marks for a mitotic clock [3, 4, 9]. In addition, an increased rate of mitosis in the stem cell pool, possibly associated with cancer risk factors such as inflammation or viral infection, has been suggested to fuel epigenetic cellular heterogeneity and to lead to an increased epigenetic clonal mosaicism which may predispose the tissue to future neoplastic transformation [10–15]. Indeed, clonal genetic and copy number variation mosaicism has already been associated with the future risk of hematological cancers [16–19], and DNAm variability © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Yang et al. Genome Biology (2016) 17:205 in normal cervical cells has been shown to predict the prospective risk of cervical cancer [15]. Given that many cancer risk factors have been associated with DNAm changes in normal cells [12, 15, 20–22], and preferentially at the same sites that undergo DNAm changes with age in healthy tissue [23, 24], we posited that a DNAm based mitotic-like clock could serve as a tool to predict cancer risk. Here we report substantial progress towards the construction of such an epigenetic mitotic-like clock. Using a novel approach, based on an underlying mathematical model, we build a DNAm-based age-correlative model called “epiTOC” (Epigenetic Timer Of Cancer). A key feature underlying the construction of epiTOC is the focus on Polycomb group target (PCGT) promoter CpGs which are unmethylated in many different fetal tissue types, thus allowing us to define a proper ground state from which to then assess deviations in DNAm in aged tissue. By correlating the tick rate predictions of this model to the rate of stem cell divisions in normal tissue, as well as to an mRNA expression-based mitotic index in cancer tissue, we demonstrate that our model approximates a mitotic-like clock. Importantly, unlike Horvath’s epigenetic clock [25], the tick rate of epiTOC is universally accelerated in cancer, in preinvasive lesions, in normal epithelial cells at risk of neoplastic transformation, and in normal epithelial cells exposed to smoke carcinogens. Results Construction of the epiTOC model By virtue of it being a highly accurate multi-tissue age predictor, Horvath’s clock cannot be a mitotic clock [14, 25]. Thus, in order to construct an age-correlative model which also reflects a mitotic clock-like process, we devised an alternative strategy, integrating mathematical modeling with previous biological knowledge (“Methods”). We reasoned that using only one tissue type from a large cohort of healthy individuals and focusing on CpG sites which, based on previous biological knowledge [26, 27], would more likely capture mitotic effects, relevant CpGs could be identified by correlation with chronological age (“Methods”; Fig. 1a). Specifically, we focused on CpGs satisfying the following criteria (justification in “Methods”): (1) CpGs that are constitutively unmethylated in fetal tissue encompassing many different tissue types [27]; (2) CpGs that map to gene promoters marked by the PRC2 polycomb repressive complex (also known as Polycomb g (...truncated)