DNA Demethylation By Activation-Induced Cytidine Deaminase in B Cell Lymphoma

DNA methylation and demethylation at cytosine residues are epigenetic modifications that regulate gene expression associated with early cell development, somatic cell differentiation, cellular reprogramming and malignant transformation. While the process of DNA methylation and maintenance by DNA methyltransferases is well described, the nature of DNA demethylation remains poorly understood. The current model of DNA demethylation proposes modification of 5-methylcytosine followed by DNA repair-dependent cytosine substitution. Although there is debate on the extent of its involvement in DNA demethylation, activation-induced cytidine deaminase (AID) has recently emerged as an enzyme that is capable of deaminating 5-methylcytosine to thymine, creating a T:G mismatch which can be repaired back to cytosine through DNA repair pathways. AID is expressed at low levels in many tissue types but is most highly expressed in germinal center B cells where it deaminates cytidine to uracil during somatic hypermutation and class switch recombination of the immunoglobulin genes. In addition to this critical role in immune diversification, aberrant targeting of AID contributes to oncogenic point mutations and chromosome translocations associated with B cell malignancies. Thus, to explore a role for AID in DNA demethylation in B cell lymphoma, we performed genome-wide methylation profiling in BL2 and AID-deficient (AID-/-) BL2 cell lines (Burkitt lymphoma that can be induced to express high levels of AID). Using Illumina’s Infinium II DNA Methylation assay combined with the Infinium Human Methylation 450 Bead Chip, we analyzed over 450,000 methylation (CpG) sites at single nucleotide resolution in each line. BL2 AID-/- cells had a median average beta value (ratio of the methylated probe intensity to overall intensity) of 0.76 compared with 0.73 in AID-expressing BL2 cells (P < 0.00001), indicating a significant reduction in global methylation in the presence of AID. Using a delta average beta value of ≥ 0.3 (high stringency cut-off whereby a difference of 0.3 or more defines a CpG site as hypomethylated), we identified 5883 CpG sites in 3347 genes that were hypomethylated in BL2 versus BL2 AID-/- cells. Using the Illumina HumanHT-12 v4 Expression BeadChip and Genome Studio software, we then integrated gene expression and methylation profiles from both lines to generate a list of genes that met the following criteria: 1) contained at least 4 methylation sites within the first 1500 bases downstream of the primary transcriptional start site (TSS 1500; AID is most active in this region during somatic hypermutation); 2) average beta value increased by >0.1 in the TSS 1500 region in BL2 compared with BL2 AID-/- cells; and 3) down-regulated by >50% in BL2 compared with BL2 AID-/- cells. This analysis identified 31 candidate genes targeted for AID-dependent demethylation with consequent changes in gene expression. Interestingly, 15 of these genes have been reported to be bound by AID in association with stalled RNA polymerase II in activated mouse B cells. After validating methylation status in a subset of genes (APOBEC3B, BIN1, DEM1, GRN, GNPDA1) through bisulfite sequencing, we selected DEM1 for further analysis. DEM1 encodes an exonuclease involved in DNA repair and contains 16 CpG sites within its TSS1500, with only one site >50% methylated in BL2 cells compared with 8 of 16 in BL2 AID-/- cells. To assess a direct role for AID in DEM1 methylation status, a retroviral construct (AIDΔL189-L198ER) driving tamoxifen-inducible expression of a C-terminal deletion mutant of AID (increases time spent in the nucleus) was introduced into BL2 AID-/- cells. BL2, BL2 AID-/-, and BL2 AIDΔL189-L198ER cells were cultured continuously for 21 days in the presence of tamoxifen, 100 nM. Bisulfite sequencing of DEM1 TSS 1500 did not demonstrate any significant changes in methylation at day 7. However, at day 21, 13 of the 16 DEM1 TSS 1500 methylation sites in BL2 AIDΔL189-L198ER cells were found to have an increase in the ratio of unmethylated to methylated clones ~10-25% above that of BL2 AID-/- cells. By qPCR, this correlated with a 1.75-fold increase in DEM1 gene expression to levels that were equivalent to that seen in BL2 cells (P = 0.003). Although further investigations are needed, this data supports the notion that AID is able to regulate target gene expression in B cell malignancy through active DNA demethylation. Disclosures No relevant conflicts of interest to declare.

Global Methylation Array Analysis of Multiple Myeloma Samples Indicate An Alteration of Epigenetics During the Transition From MGUS to Myeloma and An Increased Frequency of Gene Methylation in t(4;14) Myeloma.

Abstract 121 The methylation status of genes in myeloma can change as the disease progresses and as such identifying genes deregulated by methylation that mediate disease aetiology and progression may offer epigenetically relevant therapeutic targets. We have analyzed 153 presenting myeloma samples for methylation differences using the Illumina Infinium humanmethylation27 array, which interrogates 27,578 highly informative CpG sites per sample at the single-nucleotide resolution using bisulfite converted DNA. Data are presented as an average beta-score where 1.0 is fully methylated and 0 is fully unmethylated. Samples were analyzed using Illumina GenomeStudio and the custom differential methylation algorithm. Initially, we compared global methylation of genes between MGUS, myeloma (n=153) and relapsed myeloma (n=18) in order to determine the effect of clinical stage on the general methylation state of the genome. There were 267 probesets showing an increase in methylation between presenting and relapsed myeloma. However, the largest changes in DNA methylation were between MGUS and myeloma with 4209 probesets showing a decrease in methylation and 879 probesets showing an increase in methylation as the pre-malignant stage progresses to myeloma. In order to address the potential for differential methylation between cytogenetic subtypes of myeloma we compared the translocation groups (t(4;14) n=14; t(11;14) n=32; t(14;16) n=7; t(14;20) n=3) and samples with no split IgH locus (n=66). When average beta-scores for each translocation are compared using a 1.5 fold-change cut-off we identified 8.7% of probes differentially methylated in t(4;14), 5.1% in t(14;20), 3.3% in t(14;16), and 2% in t(11;14), indicating that the t(4;14) translocation has the largest effect on genome methylation, and in addition there are significant methylation effects associated with deregulation of the MAF transcription factors. The t(4;14) translocation in myeloma results in the over-expression of two genes, MMSET and FGFR3, of which MMSET has histone methyltransferase properties and it has been shown that methylation of chromatin is associated with DNA methylation at CpG islands resulting in transcriptional repression. In this analysis the t(4;14) samples had a greater than 1.5-fold increase in methylation in 2410 probesets, corresponding to 1685 unique genes, when compared with non-translocation samples. On average the remaining translocation groups had only 746 probes with differential methylation, and with the exception of the t(14;20) group most were hypomethylated. Identifying the genes affected by these methylation changes is important. The gene with the largest fold-change in methylation in t(4;14) samples was APC. Clinically relevant changes in methylation may be characterised by associated changes in gene expression and when methylation and expression array data from the same samples are compared there are 23 genes with decreased expression and increased methylation in t(4;14) samples compared with non-translocation samples. These include potential tumor suppressor genes GLTSCR2 and NME4, as well as SEPTIN9. We also looked for differential methylation between common cytogenetic subgroups including hyperdiploidy (HRD n=64 vs. normal n=67), 1q+ (n=44 vs. n=83), del(1p32.3) (n=20 vs. n=104), del(13q) (n=66 vs. n=68), del(16q) (n=36 vs. n=96), and del(17p) (n=8 vs. n=126) but were unable to show that any gross differences in global methylation between samples with and without the abnormality. However, there were a limited number of genes that had a greater than 1.5-fold change in methylation between the analysis groups, indicating that there are genes of potential interest. We are also mapping the methylation of genes within these regions of copy number change. In summary, we have identified that the major influences on epigenetics occur at the transition between MGUS and myeloma. t(4;14) myeloma, characterised by deregulation of MMSET, along with the translocations that deregulate the transcription factor MAF have a higher frequency of genome methylation than the cases lacking these events. These analyses enable us to identify targets which may be sensitive to modulation by epigenetic therapies in vivo. Disclosures: No relevant conflicts of interest to declare.

Azacitidine-Induced Changes in the MDS Methylome Are Associated with Clinical Responses

Azacitidine (AZA) has been shown to improve overall survival in patients with myelodysplastic syndrome (Silverman LR et al. J Clin Oncol2002; 20: 2429–40). AZA is postulated to work, in part, by inducing hypomethylation and thereby altering gene expression. As a correlative analysis to our phase II study of IV AZA we assessed the baseline methylome of MDS and the changes in global methylation on cycle 2 day 25 (c2d25) of treatment with AZA (75mg/m2 d1–5 of a 28 d cycle). DNA from bone marrow (BM) and peripheral blood (PB) underwent bisulfite conversion and 1500ng of DNA was hybridized to Infinium Human Methylation27 BeadArrays. Arrays were processed by the Genome Sequencing Center at Washington University. The Infinium human Methylation27 Bead Array interrogates &gt;27,000 well annotated CpG sites analyzing 14,500 promoters with single nucleotide resolution. Data was analyzed using BeadStudio version 3 and GraphPad Prism version 5. To compare the average percentages of methylated loci, we used a mixed model for repeated measurement data which allowed us to account for potential correlations among measurements taken from the same subjects. Loci were considered methylated if their average beta value was ≥0.80, hemi-methylated if their average beta value was &lt;0.80 but &gt;0.20, and unmethylated if it was ≤0.20. Loci on the X and Y chromosomes were excluded from analyses due to gender imbalances between responders and non-responders. Fifteen patients had BM and/or PB samples at baseline and/or on c2d25 and a response assessment. Median age was 69 years (range 53–82). IPSS categories were low (7%), Int-1 (27%), Int-2 (40%) and High (7%); FAB classifications were RA (26%), CMML (7%), RAEB (47%) and RAEB-t (20%). Best responses were: 2 patients with CR, 2 with a marrow CR, 1 with a PR, 8 with SD and 2 suffered PD. Patients with CR, mCR and PR were classified as responders whereas all others were classified as non-responders. For all patients the percentage of methylated loci decreased from baseline (13.4%) to c2d25 (9.9%) (p=0.0043). This effect was driven by a decrease in methylated loci in responders (15.1% to 8.9%) (p=0.0109). The decrease in methylated loci in non-responders was not statistically significant (12.4% to 10.5%) (p=0.1083). The difference in baseline methylation between responders and non-responders was not significant (p=0.1719). Baseline methylation was not associated with age (p=0.1475), IPSS (p=0.0934) or High- vs. Low-grade MDS (p=0.3575). Interestingly, the c2d25 assessment anteceded best clinical response in 4 out of 5 responders (all that achieved a mCR or CR) (81 days v. a mean of 202 days, SD 129 days to best response). Demethylation was likewise seen in the PB (18.6% to 11.7% of loci in responders and 18.8% to 13.6% of loci in non-responders) and overall there was good correlation between the mean beta values across the loci for BM and PB (r2=0.9937). But this correlation deteriorated when only methylated loci were included (r2=0.7936), demonstrating that the correlation is driven by hemi- or unmethylated loci, which compose ≥80% of loci, and suggesting that methylation in the PB is unlikely to be a good surrogate for BM methylation. Loci specific changes were considered potentially significant if average beta scores changed by ≥0.20 from baseline to c2d25. 11 loci met this criteria in responders and the changes in several of these were confirmed by t-tests (DNTT p=0.08; APOBEC2 p=0.0015, RGPD5 p=0.0138, TMSF4 p=0.0040). These differences and others between the baseline methylation status of loci in responders and non-responders will be correlated with mRNA expression levels (such as BCL2 p=0.08, HP p=0.0057, SHANK2 p=0.003). This study represents the first methylome-wide description of MDS and the changes induced by azacitidine. If validated in larger cohorts, BM methylation changes prior to cycle 3 may be able to help discriminate responders from non-responders earlier. Further studies are needed that include a larger sample size and that correlate changes in methylation status with changes in transcription and ultimately translation.