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Senescent cells harbour features of the cancer epigenome

Nature Cell Biology volume 15, pages 1495–1506 (2013)Cite this article

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Abstract

Altered DNA methylation and associated destabilization of genome integrity and function is a hallmark of cancer. Replicative senescence is a tumour suppressor process that imposes a limit on the proliferative potential of normal cells that all cancer cells must bypass. Here we show by whole-genome single-nucleotide bisulfite sequencing that replicative senescent human cells exhibit widespread DNA hypomethylation and focal hypermethylation. Hypomethylation occurs preferentially at gene-poor, late-replicating, lamin-associated domains and is linked to mislocalization of the maintenance DNA methyltransferase (DNMT1) in cells approaching senescence. Low-level gains of methylation are enriched in CpG islands, including at genes whose methylation and silencing is thought to promote cancer. Gains and losses of methylation in replicative senescence are thus qualitatively similar to those in cancer, and this ‘reprogrammed’ methylation landscape is largely retained when cells bypass senescence. Consequently, the DNA methylome of senescent cells might promote malignancy, if these cells escape the proliferative barrier.

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Figure 1: Senescent cells exhibit overall hypomethylation and focal hypermethylation.
Figure 2: Promoter proximal methylation of transcriptionally repressed cell cycle genes.
Figure 3: DNA hypomethylation occurs before cell cycle exit and is associated with mislocalization of DNMT1.
Figure 4: Hypomethylation and expression of late-replicating satellite sequences in senescent cells.
Figure 5: Hypomethylation occurs at gene-poor, late-replicating and lamin-associated domains whereas hypermethylation occurs at gene-rich, early-replicating regions and CpG islands.
Figure 6: Methylation changes in senescence resemble those in cancer.
Figure 7: Altered methylation is retained in cells that bypass senescence.
Figure 8: The altered epigenome of senescent cells might promote age-associated increase in incidence of human cancers.

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Acknowledgements

Thanks to S. Pepper in the CRUK microarray facility and to S. Hansen for assistance with DNA replication timing data. Thanks to Beijing Genome Institute for bisulfite sequencing. Work in the laboratory of P.D.A. was funded by NIA Program Project P01 AG031862 and CRUK Program A10250. S.L.B.’s laboratory was funded by NIA Program Project P01 AG031862. R.R.M.’s laboratory was funded by the MRC and the BBSRC. P.D.A. thanks P. Cairns for critical formative discussions.

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Author notes

  1. Hazel A. Cruickshanks & Taranjit Singh Rai

    Present address: Present addresses: MRC Human Genetics Unit at the Institute of Genetics and Molecular Medicine at the University of Edinburgh, Crewe Road, Edinburgh, EH4 2XU, UK; (H.A.C.); Institute of Biomedical and Environmental Health Research, University of the West of Scotland, Paisley, PA1 2BE, UK (T.S.R.),

  2. Hazel A. Cruickshanks and Tony McBryan: These authors contributed equally to this work

Authors and Affiliations

  1. Institute of Cancer Sciences, University of Glasgow and Beatson Institute for Cancer Research, Glasgow, G61 1BD, UK

    Hazel A. Cruickshanks, Tony McBryan, David M. Nelson, John van Tuyn, Taranjit Singh Rai, Claire Brock, Mark E. Drotar & Peter D. Adams

  2. Center for Pharmacogenomics, Washington University School of Medicine, St Louis, Missouri 63110, USA

    Nathan D. VanderKraats & John R. Edwards

  3. Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA

    Parisha P. Shah, Greg Donahue & Shelley L. Berger

  4. MRC Human Genetics Unit at the Institute of Genetics and Molecular Medicine at the University of Edinburgh, Crewe Road, Edinburgh, EH4 2XU, UK

    Donncha S. Dunican & Richard R. Meehan

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  1. Hazel A. Cruickshanks
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Contributions

H.A.C. carried out the bulk of the experiments. D.M.N., P.P.S., J.v.T., T.S.R., C.B., M.E.D. and D.S.D. carried out further experiments. T.M. carried out the bulk of the data analysis. N.D.V. and G.D. carried out further data analyses. H.A.C. and T.M. provided substantial and critical intellectual input. R.R.M., J.R.E. and S.L.B. provided further intellectual input. P.D.A., H.A.C. and T.M. conceived the project and wrote the manuscript.

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Integrated supplementary information

Supplementary Figure 1 Confirmation of senescence in IMR-90 cells.

(A) Growth curve of IMR-90 cells grown in 3% O2 shows proliferation ceased at population doubling (PD) 88. Scale bar = 30 μm. (B) Senescence-Associated β-galactosidase staining in proliferating (prolif), PD28 and senescent (sen), PD88. (C) Quantitation of senescence-associated β-galactosidase (SA β-gal) positive cells. (D) Immunofluorescence of proliferating and senescent cells with a marker of cell proliferation, cyclin A and 4’, 6-diamidino-2-phenylindole (DAPI). Scale bar = 5 μm. (E) Quantitation of cyclin A positive cells. (F) Staining of proliferating and senescent cells with DAPI shows senescent cells displaying senescence associated heterochromatin foci (SAHF). Scale bar = 5 μm. (G) Quantitation of SAHF positive cells. (H) Immunofluorescence of PML and HIRA in proliferating and senescent cells shows co-localization of these 2 proteins, a known marker of senescence in the senescent population. (I) Quantitation of cells with HIRA and PML co-localization. In panels (C), (E), (G) and (I), data was obtained from at least 100 cells scored from a single sample, representative of at least 10 independent samples.

Supplementary Figure 2 Altered gene expression in senescence.

(A) Heatmap showing hierarchical clustering of gene expression in proliferating and senescent cells. Significant changed probes of fold change > = 1.5 and BH-fdr(tt) < = 0.05. (B) Gene set enrichment analysis of downregulated genes with normalized enrichment score (NES) and family wise-error rate (FWER) p-value (C) Gene set enrichment plot of cell cycle process in senescence, top part shows the enrichment value for each gene in this class and the bottom part, the ranked list metric of these genes. (D) Heatmap showing hierarchical clustering of expression of genes in gene set “inflammatory response” (http://www.broadinstitute.org/gsea/msigdb/cards/INFLAMMATORY{_}RESPONSE.html) in proliferating and senescent cells. Significant changed probes of fold change > = 1.5 and BH-fdr(tt) < = 0.05.

Supplementary Figure 3 Concordance of replicates and methylation changes across all chromosomes.

(A) Overlayed percentage methylated basecall plots of proliferating (blue) and senescent (orange) for each replicate pair. Chromosome 1 (chr 1) is shown as a representative region. (B) Difference p plots of all chromosomes (chr).

Supplementary Figure 4 Methylation changes relative to gene expression.

(A)–(C) Relative level of gene expression in proliferating cells against the difference in methylation between proliferating and senescent cells (Sen-Prolif). Methylation was scored at promoters, gene bodies and promoters containing CpG islands defined in UCSC, as indicated. (D)–(F) Ln fold change of gene expression between proliferating and senescent cells (positive values, increased expression in senescence; negative values, decreased expression in senescence) against the difference in methylation between proliferating and senescent cells (Sen-Prolif). Methylation was scored at promoters, gene bodies and promoters containing CpG islands, as indicated. (G) Same analysis as in F, but only for genes expressed above the median level of expression in proliferating cells.

Supplementary Figure 5 Promoters of repressed cell cycle genes are methylated in senescence.

Plots of differential methylation versus position up and downstream of TSS (−5kb to +5kb) for selected genes. Y-axis is a differential methylation score that ranges from −1 to 1, denoting complete hypomethylation and hypermethylation, respectively. The full list of genes is in Supplementary Dataset 3. In each plot, the vertical line marks the TSS. Fold change (log2) gene expression of each gene is indicated in green. For each gene, data from all 3 replicates is shown.

Supplementary Figure 6 Knock down of DNMT1 triggers cell senescence, expression of satellite 2 RNA and senescence-associated chromatin changes; and overlap of hypomethylated DMRs in senescence and cancer.

(A) Proliferating IMR90 fibroblasts were infected with control lentivirus (EV) or lentivirus encoding independent shRNAs to DNMT1 (shDNMT1-a or shDNMT1-b), selected in puromycin and western blotted to detect DNMT1. (B) Cells from (A) were passaged until proliferation arrest. (C–G) After proliferation arrest, cells from (A) were scored by immunofluorescence for expression of cyclin A (C), expression of SA β-gal. (Scale bar = 30 μM), (D), expression of satellite 2 RNA (E), Senescence Associated Heterochromatin Foci (F) and localization of histone chaperone HIRA to PML bodies (G). For (C), (F) and (G) n = 1, but results shown with 2 independent shRNAs and similar results previously reported by others (see main text). (H) Series of graphs assessing percent overlap in total bp over whole genome of indicated features (observed) compared to overlaps calculated for random. Asterisks indicate statistical significance and a p-value of ≪0.001. Hypomethylated cancer (hypo cDMR) and senescence DMRs (hypo sDMR) greater than or equal to 100Kb, greater than or equal to 250Kb, greater than or equal to 500Kb, greater than or equal to 1Mb, greater than or equal to 2Mb, as indicated.

Supplementary Figure 7 Increased methylation of CpG islands in senescence.

Methylation of indicated CpG islands in senescence. Plot of percent methylated basecalls in proliferating (orange) and senescent cells (blue), from whole genome bisulfite sequencing data of 3 replicates of proliferating cells and 3 replicates of senescent cells. The orange and blue lines show the smoothed average percent methylated basecalls at corresponding CpGs. Individual CpGs are indicated by black ticks along the x-axis. The UCSC genes (blue bar) and CpG islands (green bar) are also shown. The transcription start sites (TSS) are indicated by vertical black arrows. Gene, chromosome and bp of CpG island are indicated top left.

Supplementary Figure 8 SV40-infected “bypass” cells proliferate and uncropped versions of Figures.

(A) Bypass cells (SV40) exhibit a low frequency of SA β-gal (<1%). (B) A large proportion of bypass cells (SV40) incorporate a EdU (DNA synthesis) after a 24hr pulse. (C) Quantitation of results from (B), compared to uninfected PD 22 proliferating cells. Error bars indicate standard deviation. Source data for panel (C) can be found in Supplemental Table 22. (D) Uncropped Figure 3c. (E) Uncropped Supplementary Figure 8a. For (D) and (E), see main figures for loading controls. Scale bar in (A) and (B) = 10 μM.

Supplementary Table 1 Sequence yield.
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Supplementary Table 2 CpG Methylation.
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Supplementary Table 3 Methylated CpG sites.
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Supplementary Table 4 Pearson Correlation Coefficients.
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Supplementary Table 5 CHG Methylation.
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Supplementary Table 6 CHH Methylation.
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Supplementary Table 7 Error rates.
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Supplementary Table 8 Individual CpG differences.
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Supplementary Table 9 Genes whose promoter methylation increases and expression decreases in senescence.
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Supplementary Table 10 Overlap of sDMRs, LADs, CpG islands, early and late replicating regions of the genome.
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Supplementary Table 11 Overlap of sDMRs with cDMRs described in Ref. 36.
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Supplementary Table 12 Overlap of sDMRs with cDMRs described in Ref. 35.
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Supplementary Table 13 Overlap of sDMRs with cDMRs described in Ref. 3.
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Supplementary Table 14 Number (no.) of CpGs call classified as methylated and unmethylated in indicated regions (CpG islands) in proliferating cells (P) and senescent cells (S).
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Supplementary Table 15 Overlap of sDMRs with bypass DMRs.
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Supplementary Table 16 Overlap of sDMR and bypass DMR intersect with cDMRs described in Ref. 36.
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Supplementary Table 17 Overlap of sDMR and bypass DMR intersect with cDMRs described in Ref. 35.
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Supplementary Table 18 Overlap of sDMR and bypass DMR intersect with cDMRs described in Ref. 3.
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Supplementary Table 19 Statistics source data.
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Supplementary Table 20 Antibodies and shRNAs used in this study.
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Cruickshanks, H., McBryan, T., Nelson, D. et al. Senescent cells harbour features of the cancer epigenome. Nat Cell Biol 15, 1495–1506 (2013). https://doi.org/10.1038/ncb2879

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