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.

Author notes

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Asterisk with author names denotes non-ASH members.

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