450K-Array Analysis of Chronic Lymphocytic Leukemia Cells Reveals

ORIGINAL ARTICLE 450K-array analysis of chronic lymphocytic leukemia cells reveals global DNA methylation to be relatively stable over time and similar in resting and proliferative compartments

N Cahill1,2, A-C Bergh3, M Kanduri1,4,HGo¨ ransson-Kultima5, L Mansouri1, A Isaksson4, F Ryan2, KE Smedby6, G Juliusson7, C Sundstro¨m1, A Rose´n3 and R Rosenquist1

In chronic lymphocytic leukemia (CLL), the microenvironment influences gene expression patterns; however, knowledge is limited regarding the extent to which methylation changes with time and exposure to specific microenvironments. Using high-resolution 450K arrays, we provide the most comprehensive DNA methylation study of CLL to date, analyzing paired diagnostic/follow-up samples from IGHV-mutated/untreated and IGHV-unmutated/treated patients (n ¼ 36) and patient-matched peripheral blood and lymph node samples (n ¼ 20). On an unprecedented scale, we revealed 2239 differentially methylated CpG sites between IGHV- mutated and unmutated patients, with the majority of sites positioned outside annotated CpG islands. Intriguingly, CLL prognostic genes (for example, CLLU1, LPL, ZAP70 and NOTCH1), epigenetic regulator (for example, HDAC9, HDAC4 and DNMT3B), B-cell signaling (for example, IBTK) and numerous TGF-b and NF-kB/TNF pathway genes were alternatively methylated between subgroups. Contrary, DNA methylation over time was deemed rather stable with few recurrent changes noted within subgroups. Although a larger number of non-recurrent changes were identified among IGHV-unmutated relative to mutated cases over time, these equated to a low global change. Similarly, few changes were identified between compartment cases. Altogether, we reveal CLL subgroups to display unique methylation profiles and unveil methylation as relatively stable over time and similar within different CLL compartments, implying aberrant methylation as an early leukemogenic event.

Leukemia (2013) 27, 150–158; doi:10.1038/leu.2012.245 Keywords: chronic lymphocytic leukemia; DNA methylation; 450K array; prognostic subgroups; compartments

INTRODUCTION Although aberrant DNA methylation events are often suggested Aberrant DNA hypermethylation driven gene silencing of tumor as early pathogenic events, little is known regarding DNA suppressor genes is today recognized as a key event in cancer methylation changes over time, particularly for CLL. In addition, pathogenesis.1,2 So far, investigations focusing on CpG sites at knowledge concerning the extent to which the microenvironment single gene promoters and CpG islands in chronic lymphocytic shapes the tumor epigenetic profile is limited. It is well known that 15 leukemia (CLL) have revealed a number of aberrantly methylated the microenvironment is key to CLL pathobiology, where proliferat- genes of biological and clinical importance, for example, DAPK1 ion centers in lymphoid tissue are hubs of cell proliferation allowing 16 ZAP70, TWIST2, HOXA4, SFRP4 and ID4.3–8 More recently, the up to 1% of the clone to proliferate daily. Recently, gene expression advent of microarray allowing global methylation screening has profiling of lymph node (LN)-derived CLL cells also identified high revealed a number of functionally diverse aberrantly methylated expression of genes involved in B-cell receptor (BCR) signaling and genes and pathways in CLL.9–12 Using 27K DNA methylation proliferation relative to cells from the resting peripheral blood (PB) 17 microarrays, we previously recognized a differential methyla- compartment. tion pattern distinguishing favorable prognostic IGHV-mutated Given that we previously identified IGHV-M and IGHV-UM CLL to (IGHV-M) from poor-prognostic IGHV-unmutated (IGHV-UM) CLL have differential methylation profiles and in light of the patients.11 Interestingly, we identified several tumor suppressor contribution of time and microenvironment to gene expres- 11,17 genes (for example, ABI3 and WISP3)13,14 differentially methylated sion, we sought to determine DNA methylation changes between these subgroups and noted a number of proliferation- occurring over time and changes attributed to alternative related genes to remain unmethylated and potentially expressed microenvironments. To gain insights into these issues, we here within the unfavourable as IGHV-UM subgroup. Furthermore, DNA applied 450K DNA methylation arrays (including 4450 000 CpG methylation interrogation by arrays has also identified a number of sites) on diagnostic and follow-up samples from treated IGHV-UM differentially methylated genes to segregate according to CD38 and untreated IGHV-M CLL patients as well as from patient- expression status in CLL.10 matched PB and LN samples. On a larger scale than previously

1Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden; 2Department of Biological Sciences, Institute of Technology, Dublin, Ireland; 3Division of Cell Biology, Department of Clinical and Experimental Medicine, Linko¨ping, Sweden; 4Department of Clinical Genetics and Transfusion Medicine, Institute of Biomedicine, Sahlgrenska University Hospital, Gothenburg, Sweden; 5Department of Medical Sciences, Cancer Pharmacology and Informatics, Uppsala University, Uppsala, Sweden; 6Clinical Epidemiology Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden and 7Department of Laboratory Medicine, Stem Cell Center, Hematology and Transplantation, Lund University, Lund, Sweden. Correspondence: Professor R Rosenquist, Rudbeck Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Dag Hammarskjo¨ lds va¨g 20, Uppsala 751-85, Sweden. E-mail: [email protected] Received 8 August 2012; accepted 17 August 2012; accepted article preview online 27 August 2012; advance online publication, 18 September 2012 DNA methylation over time and within different compartments of CLL N Cahill et al 151 published,11 we identified a large number of differentially controls were included for comparison purposes. Ingenuity pathway methylated CpG sites between prognostic subgroups, and, for analysis (IPA) software was utilized for gene ontology and pathway analysis the first time revealed that the methylation patterns were stable to delineate the differentially methylated genes between the CLL over time and between compartments. subgroups (http://www.ingenuity.com). To identify methylation differences between paired diagnostic and follow-up samples and matched samples from different compartments, MATERIALS AND METHODS data were pre-processed in the same way as above; however, a paired t-test was adopted to define recurrent changes. Recurrent changes over Patients and controls time were identified using a filter of 40.2 in average beta difference To assess the global DNA methylation profiles in different prognostic between the diagnostic and follow-up samples. To identify non-recurrent subgroups of CLL, PB samples collected at diagnosis from nine IGHV-M and differences that ordinarily would be masked by transformation and nine IGHV-UM patients were included for analysis. Approximately 5–8 years averaging of the DNA methylation data, an intra-individual sample paired later (median 6.8 years), a follow-up PB sample from the same IGHV-M and analyses on non-transformed data was performed on the over time and IGHV-UM patients was obtained to study DNA methylation over time. compartment samples using a cutoff of X0.40 in beta difference. Between first and second sampling points, all IGHV-M patients had remained untreated, while all IGHV-UM patients had subsequently been treated. The median age of this cohort at diagnosis was 63 years (range, Pyrosequencing 47–73 years) and consisted of 7 males and 11 females. All samples were To validate the array, DNA methylation quantitation of the exact CpG site obtained from the Swedish division of the Scandinavian population-based targeted by the array was measured via pyrosequencing analysis. CpG case–control study called SCALE (Scandinavian Lymphoma Etiology).18 To sites covering three genes (HDAC4, HDAC9 and CLLU1) were chosen for determine the DNA methylation profiles of CLL cells derived from different validation using samples originally run on the array (primers are available compartments, a separate set of 20 CLL samples encompassing 10 patient- upon request). To determine the DNA methylation status of the matched PB and LN samples were obtained from Biobanks at Uppsala and differentially methylated LPL gene not only at the single CpG site targeted Linko¨ping University hospitals. The median age for these patients was 58 by the array, pyrosequencing of multiple sites across the CpG island (five years and the ratio of males to females was 4:1. Eight of the ten CLL sites) and gene promoter (two sites) were also chosen for analysis. This patients were untreated at sampling. Three patient-matched PB and LN latter analysis was conducted on a set of independent non-sorted patient paired cases were simultaneously retrieved, six were collected within samples that were previously not run on the array. Test samples were 1 month (range, 2–4 weeks) and 1 pair was sampled a year apart. bisulfite converted using the EZ DNA methylation kit (Zymo Research, All CLL samples were diagnosed according to recently revised criteria, Orange, CA, USA), PCR amplified and denatured according to standard showing a typical CLL immunophenotype.19 Normal B cells isolated form protocols (Qiagen, Venlo, Netherlands). Quantitative methylation analysis three individuals aged 51, 65 and 66 years were included as controls and was then performed on the PyroMark Q24 instrument (Qiagen). Epitect one whole-genome amplified DNA sample was included as a negative fully converted and unconverted DNA controls were included for analysis control. Informed consent was collected according to the Helsinki (Qiagen). Declaration and ethical approval was granted by ethical review committees at Uppsala and Linko¨ping Universities. Molecular and clinical data for all patients are summarized in Supplementary Table 1A and B. RESULTS A comparison of global DNA methylation between IGHV mutated B-cell enrichment and CLL cell sorting and unmutated CLL All 36 PB CLL samples collected to study DNA methylation over time Genome-wide DNA methylation profiles were compared between originally contained 470% tumor cells. To enrich for tumor cells, all newly diagnosed IGHV-M (n ¼ 9) and IGHV-UM (n ¼ 9) CLL patients. samples were subjected to negative depletion according to standard Using stringent selection criteria (as described in Materials and protocols devised by the Stem cell technologies B cell enrichment kit methods), a total of 2239 sites were deemed as differentially (Stem Cell, Grenoble, France). Tumor cell purity was then assessed by FACS analysis of CD5 and CD19 cell surface markers. A purity of X94% (mean methylated between these subgroups (Figure 1). A spatial view of 96%) was obtained for all samples. Normal B-cell controls were enriched in these sites mapped across the genome (chromosomes 1–22) the same manner. In contrast, the 20 patient-matched PB and LN samples revealed no bias in the distribution across all chromosomes collected to study DNA methylation within different CLL compartments (Supplementary Figure 1). A regional analysis of these sites in were CD5/CD19 sorted by flow cytometry. relation to CpG islands revealed the majority of sites to be positioned outside of known annotated CpG islands. More 450K methylation analysis specifically, B7% were located in CpG islands (149/2239 sites), High quality DNA was bisulfite converted using the EZ DNA Methylation 22% in shores (492/2239 sites), 13% in shelves (297/2239 sites) gold Kit (Zymo Research, Irvine, CA, USA) according to manufacturer’s and 58% (1301/2239 sites) lay in non-annotated regions in relation instructions. Converted DNA was then hybridized to the HumanMethyla- to the CpG island. Hence, of the available annotated regions, tion450 Analysis BeadChip and processed following the Illumina Infinium B16% were located in islands, 52% in shores and 32% in shelves. 450K Methylation array assay procedure (Illumina, San Diego, CA, USA). Investigations into the position of these differentially methylated Hybridization fluorescent signals were read by the Illumina BeadStation GX sites across the gene structure noted a large proportion of them to scanner. A beta value, a quantitative measure of DNA methylation was be situated within the gene body (Supplementary Figure 2). then assigned via the bead studio software (Illumina). This value was IPA ontology analysis of the 1826 differentially methylated calculated from the ratio of fluorescent signals from the methylated alleles to the sum of the signals from the methylated and unmethylated alleles. genes identified by the array demonstrated a number of enriched Upon transformation of the data, beta values ranged from 0 (completely physiological and molecular functionalities as described in Table 1. unmethylated) to 1.3 (completely methylated) over the different CpG sites Most of the genes contained within these functions have not been studied. implicated in CLL previously. However, many of these were Bioinformatic analysis was conducted using the Illumina methylation identified as members of recognized signaling pathways, whereas analyzer (IMA) package. Raw data were quantile normalized and arcsin others were known to have roles in other cancers. A summary of transformed. To determine differential methylation patterns between the methylation status of a selection of these genes and the IGHV-M and IGHV-UM CLL patients at diagnosis, an empirical Bayes position of their targeted CpG sites is given in Table 2 and moderated t-test was employed using the limma package. P-values were Supplementary Table 2. For comparison purposes, the methylation adjusted using the Benjamini and Hochberg method20 and a P-value of status of these select genes within the normal B-cell controls is p0.05 was applied as a cutoff. A further filter of X0.40 in average beta difference between the diagnostic IGHV-M/UM sample sets was used to additionally provided in Table 2. ensure that only recurrent CpG sites with a large methylation difference A focused search for genes clinically associated with CLL were obtained. Results were visualized by means of a heat-map using the revealed a number of well-known CLL prognostication genes. genesis program (http://genome.tugraz.at) and three normal B-cell Interestingly, we identified the differential methylation profiles of

& 2013 Macmillan Publishers Limited Leukemia (2013) 150 – 158 DNA methylation over time and within different compartments of CLL N Cahill et al 152

–0.5 1:1 0.5 Mutated 2 Neg Con 1 Con 3 Mutated 1 Mutated 9 Unmutated 9 Con 2 Mutated 4 Mutated 5 Mutated 6 Mutated 7 Mutated 8 Unmutated 1 Unmutated 2 Unmutated 3 Unmutated 4 Unmutated 5 Unmutated 6 Unmutated 7 Unmutated 8 Mutated 3

Figure 1. Heat map demonstrating supervised hierarchical clustering of methylated and unmethylated genes between IGHV-mutated and unmutated CLL subgroups. Three normal healthy B cell control samples (Con 1–3) and one negative whole-genome ampliﬁed control (Neg) were included for comparison purposes. A gradient color scale ranging between green (completely unmethylated) to red (completely methylated) is shown.

key CLL prognosticator genes, such as ZAP70, LPL and CLLU1.4,21–23 example, IBTK) and epigenetic regulator genes (for example, More specifically, higher DNA methylation of the CLLU1 gene was HDAC4, HDAC9 and DNMT3B) as differentially methylated (Table 2; present in IGHV-M CLL and normal B-cell controls relative to the Supplementary Table 2).26–31 Interestingly, this array study could IGHV-UM cases. Similarly, higher DNA methylation of the LPL gene, also reiterate the preferential methylation of tumor suppressor within the transcription start site TSS1500/shore and gene body/ genes ABI3(ref.13) in IGHV-UM and WISP3(ref. 14) in IGHV-M subgroups shore regions, was evidenced in IGHV-M and normal B cells as seen in our earlier 27K-array study11 (Table 2; Supplementary compared with IGHV-UM CLL. In line with previous data,4 IGHV-M Table 2). Moreover, we reconfirmed CD80 and CD86, the B cell cases were also found to have higher DNA methylation of the co-stimulating molecules,32 to be hypermethylated in IGHV-UM ZAP70 gene compared with IGHV-UM CLL (Table 2; Supplementary relative to IGHV-M cases.11 Table 2). Interestingly, we found NOTCH1, a newly identified One of the enriched canonical pathways highlighted through mutated gene in CLL24,25 to have higher methylation within the IPA analysis was the ‘molecular mechanisms of cancer pathway’. gene body/shore region of IGHV-M patients and healthy Superimposing our data set onto this pathway, differentially individuals relative to IGHV-UM cases. methylated genes were sorted into pathways known to be An investigation of genes of possible biological importance in involved in cancer. Following a literature review of these CLL unveiled a number of proliferation and apoptosis-associated pathways, only genes from the more established genes/pathways genes (for example, LEF-1 and TCF3) BCR signaling genes (for previously implicated in CLL were further investigated. Nine key

Leukemia (2013) 150 – 158 & 2013 Macmillan Publishers Limited DNA methylation over time and within different compartments of CLL N Cahill et al 153

Table 1. IPA functional categories for the differentially methylated genes

P-value

Molecular and cellular functions Cell development 2.33E À 11–2.98E À 03 Cellular function and maintenance 1.14E À 10–2.46E À 03 Gene expression 4.17E À 10–2.52E À 03 Cellular movement 1.39E À 08–2.63E À 03 Cellular growth and proliferation 4.18E À 08–2.76E À 03

Physiological system development and function Hematological system development and function 1.16E À 12–2.98E À 03 Hematopoiesis 1.16E À 12–2.42E À 03 Lymphoid tissue structure and development 7.65E À 10–2.98E À 03 Tissue development 1.25E À 09–2.98E À 03 Cell-mediated immune response 2.02E À 09–1.98E À 03 Abbreviation: IPA, ingenuity pathway analysis. Functionalities were determined relative to the Ingenuity knowledge database using a Benjamini-Hochberg adjusted Fisher’s test, at a significance level of adjusted Po0.05. genes belonging to the TGF-b pathway and thirteen components of differentially methylated sites in IGHV-UM patients (89.1–98.2%) of the NF-kB/TNF pathway were identified. The methylation status had an absolute beta difference in the range of 0.40–0.59. of the CpG site(s) and the gene region interrogated by the array Approximately half of the sites showed a decrease and the for the various genes contained within these pathways categor- remaining half an increase in methylation over time. ized according to the IGHV mutational status are described in Table 3 and Supplementary Table 3. DNA methylation in patient-matched CLL cells from alternative compartments A comparison of genome-wide DNA methylation over time On analyzing the patient-matched CLL material derived from the On searching for recurrent methylation changes using strict LN and PB using the same stringent criteria as described above criteria (P ¼ 0.05 and an average beta difference of 40.20), no (P ¼ 0.05 and an average beta difference of 40.20), no recurrent recurrent differentially methylated sites were noted over time differences in DNA methylation could be detected. Using solely a within the IGHV-M subgroup. Under the same criteria, only six cutoff of P ¼ 0.05 and no filter in an average beta difference, only a recurrent sites covering five genes (LNX1, OTP, PDGFRA, HOXA11A single small recurrent change (0.08 in average beta difference) and LOC400927) were found to be differentially methylated over covering the MICALL2 gene was noted. Of note, the R2 values time in the IGHV-UM cases. reported for patient-matched compartment samples (498%) To identify smaller recurrent changes over time, we solely were analogous to the technical replicate values reported by employed a cutoff of P ¼ 0.05 and omitted the use of a further Illumina. filter in average beta difference. Only four sites with small changes Intra-individual analysis using a cutoff of X0.40 revealed (range, 0.04–0.06 mean beta difference) in methylation were between 4 and 78 non-recurrent CpG sites to be differentially observed in the IGHV-M cases. The magnitude of these small methylated between patient-matched PB and LN samples. In changes was larger within the unmutated subgroup, here 43 sites global terms, this translated into a 0–0.02% global change. Given presented with small changes. Of the aforementioned sites, 70% the lack of change determined under such strict criteria, a less changed by an average beta difference in the range of 0.05–0.10 strict cutoff of X0.30 was applied. Under this criterion, 16–277 and the remainder in the range of X0.10 to p0.20. Within the non-recurrent CpG sites were found to be differentially methy- IGHV-M and IGHV-UM subgroups studied, approximately half of lated, translating into a 0–0.06% global change The majority of these small DNA methylation changes were shown to increase these non-recurrent differentially methylated sites (50–89.8%) and the remaining half to decrease over time. were found to have an absolute beta difference in the range of To estimate the likelihood that these small methylation changes 0.30–0.39. represent technical array changes, R2 values for the paired over time IGHV-M and IGHV-UM samples were compared with the R2 value obtained by Illumina for their technical replicates. R2 values Array validation for the IGHV-M paired samples were shown to be in the same Two epigenetic regulator genes, HDAC4, HDAC9 and the CLL range (499%) as the technical replicates quoted by Illumina prognostic gene CLLU1 found to be differentially methylated were (o98%); however, R2 values for the IGHV-UM pairs (94–98%) were validated by bisulfite pyrosequencing (Figures 2a and c).23,29,30 not entirely within the range quoted by Illumina for their technical Additionally, pyrosequencing analysis established IGHV-M cases to replicates. Hence, these small changes could not be deemed as have higher DNA methylation across the multiple CpG sites being truly biological or technical in nature. spanning the CpG island (five sites) and promoter (two sites) of To identify changes masked by transformation and averaging, the CLL prognostic gene LPL compared with IGHV-UM cases.22 In intra-individual patient analyses were applied. Analysis revealed general, IGHV-M cases were more heterogeneous in terms of DNA IGHV-UM patients to have higher number of differentially methylation across the latter sites between patients compared methylated sites (X0.40) compared with IGHV-M patients with IGHV-UM patients (Figure 2a). To demonstrate the possible Po0.001. More specifically, the total number of sites shown to functional link between DNA methylation and gene expression, differ over time within the IGHV-UM patients ranged from 125 to previously published RQ-PCR gene expression results33 from two 3243, equating to a global change of 0.03–0.67% (median, 0.27%). of our highly methylated CLL prognostic genes CLLU1 and LPL In contrast, the total number of sites differing over time within the were correlated with the methylation levels, revealing a lower IGHV-M cases ranged from 9 to 38, equating to 0–0.01% genome- gene expression in hypermethylated IGHV-M cases relative to their wide change. Defined by a beta difference of X0.40, the majority less methylated IGHV-UM counterparts (Figure 2b).

& 2013 Macmillan Publishers Limited Leukemia (2013) 150 – 158 DNA methylation over time and within different compartments of CLL N Cahill et al 154

Table 2. Functionalities and genomic positions of differentially methylated CpG sites

Gene Function/implication in cancer Normal IGHV- IGHV- Region in CpG site(s) B-cell Mutated Unmutated relation to location within controls CLL CLL CpG Island a gene structurea

BCR-related signaling genes IBTK B-cell signaling inhibitor28 Hypermeth Unmeth Hypermeth Shore TSS1500

Survival-related genes LEF1 Lymphoid enhancing binding factor Hypermeth Meth Unmeth NA Gene body Involved in WNT signaling. Pro-survival factor in CLL26 TCF3 Transcriptional regulator. Regulation of B-cell Hypermeth Unmeth Hypermeth Shore Gene body proliferation and VDJ recombination. Suspected regulator CD38 expression27

Prognostic CLL genes ZAP70 T- and B-cell signaling regulator Meth Hypermeth Unmeth NA TS1500 Upregulated in unmutated CLL21 CLLU1 CLL upregulated gene Hypermeth Hypermeth Unmeth NA Gene body Upregulated in unmutated CLL23 LPL Lipoprotein lipase Hypermeth/ Hypermeth/ Unmeth/Low Shore Gene body Upregulated in unmutated CLL22 Meth Meth meth TSS1500 NOTCH1 Transmembrane25 protein receptor Low meth Meth Unmeth Shore Gene body Mutated in CLL

Epigenetic regulating genes DNMT3B DNA methyl-transferase31 Unmeth Meth Unmeth Shore 50UTR Suspected aberrant de novo DNA HDAC4 Histone deacetylase, deactylases histones40 Hypermeth/ Unmeth Hypermeth/ Island/ Gene body Meth Meth Shore/Shelf HDAC9 Histone deacetylase, deactylases histones40 Hypermeth Unmeth Meth NA Gene Body

Tumor suppressors ABI3n Tumor suppressor13 Meth Unmeth Meth NA Gene body/ Implicated in lung metastasis TSS200 WISP3n Tumor suppressor14 Hypermeth Hypermeth Low meth/ NA TSS200/ﬁrst Expression loss in breast cancer. WNT signaling Meth exon/50UTR

Proliferation/survival-related genes CD86n B-cell co-stimulatory molecule46 Hypermeth Meth Hypermeth NA 50UTR/body CD80 B-cell co-stimulatory molecule46 Hypermeth Unmeth Hypermeth/ NA TSS1500 Meth BCL2L1 Apoptosis regulator47 Hypermeth/ Unmeth Hypermeth Shore Gene body BCL2L1 underexpressed in CLL Meth SPNn B cell development Hypermeth Hypermeth Meth Shelf TS1500 Cell trafﬁcking and lymphocyte activation48 FAS Member of TNF receptor family Hypermeth Low Meth Hypermeth Shore Gene body Regulation of programmed cell death49 MYB Proto-oncogeneRegulates miR 155 in CLL50 Meth Hypermeth Low meth Shelf NA Gene body 30UTR

Abbreviations: BCR, B-cell receptor; CLL, chronic lymphocytic leukemia. nGenes overlapping with our previous 27K methylation array study. Unmeth: p0.2 in average beta value; low meth: 0.3–0.4 in average beta value; Meth 40.4–0.6 in beta value; Hypermeth: X0.7 in average beta value. aNote the methylation status provided maybe indicative of the methylation status at more than one site for the listed gene. In some cases, the CpG site may be represented in different transcripts and therefore in different gene regions. Alternatively, a number of gene regions maybe within the same gene transcript. For more details, see Supplementary Table 2.

DISCUSSION significance of altered DNA methylation outside these regions is Genome-wide DNA methylation approaches are helping to becoming more apparent.35,37 For example, our 27K analysis dismantle the complex landscape of DNA epi-mutations and their identified DNA methylation of a CpG site positioned B1 kb away role in CLL.9–12,34,35 Using 27K arrays, we previously discovered from the promoter of the ADORA3 gene to negatively correlate to prognostically divergent IGHV-M and IGHV-UM CLL to have ADORA3 gene expression in CLL.11 Correspondingly in colon differential DNA methylation profiles.11 Here, on a significantly cancer, Irizarry et al.37 have noted that the majority of altered DNA larger scale, 450K methylation array analysis revealed IGHV-M and methylation present in CpG island shores (up to 2 kb distant from IGHV-UM subgroups to display a large number of differentially the CpG island) to functionally relate to gene expression. Similarly, methylated sites (2239 CpG cites), and, for the first time, in this study, of the CpG sites within a known annotated region in demonstrated the majority of these sites to be located outside relation to the CpG island we report a large proportion of annotated CpG islands. Traditionally, it is accepted that the differentially methylated sites to be located outside the CpG majority of functionally relevant DNA methylation occurs within islands; 52% were found in CpG island shores, 32% in shelves and the CpG islands of vital gene promoters.36 However, the a mere 16% in CpG islands. Altogether, these findings suggest

Leukemia (2013) 150 – 158 & 2013 Macmillan Publishers Limited DNA methylation over time and within different compartments of CLL N Cahill et al 155 Table 3. Differentially methylated genes within the TGF-b and TNF pathways

Pathway Probe ID Gene Higher methylation in Region in relation CpG site(s) location within on array mutated/unmutated CLL to CpG islanda the gene structurea

TGF-b cg20991819 TGFB2 Unmutated NA 30UTR cg00342358 TGFBR3 Mutated Shore 50UTR cg01336162 TGFBR3 Mutated Shore 50UTR cg13178170 TGFBR3 Mutated Shore Gene body cg24486867 ACVR1 Unmutated NA Gene body cg24749947 ACVR1 Mutated First exon/50UTR cg07395804 ZFYVE9 Unmutated NA Gene body cg14283454 SMAD7 Mutated Shore Gene body cg26880297 SKI Mutated Shore Gene body cg24610349 SMURF1 Unmutated NA Gene body cg25446191 SKIL Mutated Shore TSS1500/50UTR cg08348121 SKIL Unmutated 50UTR/first exon cg15723784 SMAD3 Mutated NA Gene body/30UTR cg19193595 SMAD3 Mutated NA Gene body cg22528123 SMAD3 Mutated NA Gene body/TSS200 cg24032190 SMAD3 Mutated NA 50UTR cg26430287 SMAD3 Mutated NA 50UTR TNF cg26736341 TNF Unmutated Shelf Gene body cg01360627 TNF Unmutated Shelf Gene body cg05952498 TNF Unmutated Shelf Gene body cg09637172 TNF Unmutated Shelf 30UTR cg15989608 TNF Unmutated Shelf Gene body cg20477259 TNF Unmutated Shelf Gene body cg23384708 TNF Unmutated Shelf 30UTR cg26160008 TNFRSF1A Mutated NA 50UTR/First exon cg00463840 TNFRSF8 Mutated NA Gene body/50UTR cg05036439 TNFRSF8 Unmutated NA Gene body cg07499259 TNFRSF8 Mutated Shore 50UTR/body cg10058766 TNFRSF8 Mutated NA First exon/50UTR/gene body cg18152455 TNFRSF8 Mutated NA 50UTR/gene body cg22123711 TNFRSF8 Mutated NA TSS200/gene body NA cg01767885 C1QTNF8 Unmutated Shelf TSS1500 cg20805920 DFFA Unmutated Shore TSS1500 cg11797700 PARP1 Unmutated NA 30UTR cg02319016 PAK2 Mutated Shelf 50UTR cg09319797 TNFRSF17 Mutated NA 30UTR cg18124517 TNFRSF1B Mutated NA 30UTR cg11665613 TNFRSF1B Mutated Shelf Gene body cg24886867 RIPK1 Unmutated NA TSS1500 cg10318258 RIPK3 Unmutated Shore TSS1500 cg10926554 TRAF3IP2 Mutated NA Gene body/TSS200 cg25282285 TRAF3IP2 Mutated NA Gene body/TSS200 cg26379258 TRAF3IP2 Mutated NA Gene body/TSS200 cg00590039 TRAF3IP2 Mutated NA Gene body/TSS200 cg03270395 TRAF3IP2 Mutated NA Gene body/TSS200 cg05423393 TRAF3IP2 Mutated NA Body/first exon/50UTR cg25905215 NFKB1 Unmutated NA 30UTR aNote the methylation status provided maybe indicative of the methylation status at more than one site for the listed gene and in some cases the CpG sites may be represented in different transcripts and therefore in different gene regions. Alternatively, a number of gene regions maybe within the same transcript. For more details, see Supplementary Table 3. aberrant DNA methylation to play a role in establishing the showed ZAP70 to be preferentially methylated in IGHV-M relative to variable disease course seen in prognostic subgroups of CLL and IGHV-UM CLL. Considering that gene expression correlates to DNA highlight the potential importance of non-CpG island epi- methylation status, analysis of DNA methylation marks by mutations in leukemogenesis. pyrosequencing may hence potentially offer an alternative mode When searching for differentially methylated genes of clinical of analysis for the aforementioned prognostic genes in a clinical significance in CLL, higher DNA methylation at CpG sites within setting.38 Interestingly, we also identified NOTCH1, a novel mutated the CLLU1 and LPL genes was revealed in IGHV-M versus IGHV-UM gene in CLL,24,25 to be more methylated within the gene body/ cases. In CLL, high LPL and CLLU1 expression is associated with the shore region of IGHV-M patients compared with IGHV-UM patients, presence of IGHV-UM genes and poor clinical outcome.22,23 nevertheless the functional and clinical relevance of this finding Accordingly, we could also correlate the DNA methylation status remains to be further investigated. to gene expression data for these two genes. Hence, these novel Investigation of genes of possible biological significance in CLL data clearly indicate a possible mode of direct regulation by DNA identified the IBTK gene, an inhibitor of BTK,28 a key member in methylation leading to the differential expression of these CLL BCR signaling and current target of interest for the use of small prognostic genes. In accordance with a recent study,4 we also molecule inhibitors as a novel approach to CLL treatment.39

& 2013 Macmillan Publishers Limited Leukemia (2013) 150 – 158 DNA methylation over time and within different compartments of CLL N Cahill et al 156 LPL promoter (2 site average LPL CpG island (5 site average DNA methylation level) DNA methylation level) CLLU1 100 100 100 90 90 90 p=0.002 80 p=0.03 80 80 p=0.0005 70 70 70 * 60 60 60 50 50 50 40 40 40 DNA methylation % DNA methylation 30 30 30 20 20 20 promoter DNA methylation % promoter DNA methylation

* CLLU1 10 10 10 LPL

0 % LPL CpG island DNA methylation 0 0 UM M UM M UM M n=12 n=12 n=12 n=12 n=8 n=9 IGHV mutational status IGHV mutational status IGHV mutational status

LPL gene expression CLLU1 gene expression 0.0030 0.28 * * 0.0025 0.24 p=0.1 p=0.03 0.0020 0.20 0.16 expression

expression 0.0015 0.12 0.001 0.08 LPL/B2M 0.0005 CLLU1/B2M 0.04 0 0 UM M UM M n=7 n=8 n=7 n=8 IGHV mutational status IGHV mutational status

HDAC4 HDAC9 90 100 90 80 80 * 70 p=<0.0001 70 60 p<0.0001 60 50 50 * 40 40 DNA methylation % DNA methylation DNA methylation % DNA methylation * 30 30 20 20 HDAC9 HDAC4 HDAC4 10 10 0 0 UM M UM M n=9 n=8 n=9 n=9

IGHV mutational status IGHV mutational status Figure 2. Array validation experiments. DNA methylation pyrosequencing of CLL prognostic genes LPL and CLLU1 (a) and correlation of the DNA methylation status to LPL/CLLU1 gene expression data (b). The latter analysis was conducted on unsorted DNA derived from the same patients as those run on the array. DNA methylation pyrosequencing of epigenetic regulator HDAC4 and HDAC9 genes (c). Box plots indicate the inter-quartile range (25–75%) with the smaller inner square indicating the median. Whiskers represent the minimum and maximum.

Interestingly, we found the inhibitor IBTK gene to be highly Furthermore, when searching for pathways and single gene methylated at the TSS1500/shore region of the gene in IGHV-UM components belonging to key signaling complexes important for patients. It is therefore possible that methylation of the IBTK gene CLL, survival/proliferation pathway mediators LEF1 and TCF3, known may contribute to the higher rate of BCR signaling, proliferation effectors of the Wnt pathway in regulating B-cell proliferation,26,27 and disease progression experienced by poor-prognostic IGHV-UM werefoundtobemoremethylatedamongIGHV-M patients. patients. Altogether, this novel finding pinpoints a potential Additionally, a number of genes occupying or controlled by mechanism for the regulation of BTK function in CLL cells which key canonical pathways (NF-kB/TNF and TGF-b) were denoted deserves further investigation. as differentially methylated in CLL (Table 3). For instance, the Altered histone deacetylase (HDAC) expression levels have NF-kB/TNF pathway mediators such as TNF, an autocrine growth been described in hematological malignancies.30,40 For instance, factor in CLL,5,41,42 was shown to be primarily methylated within high HDAC4 expression was noted in T cell acute lymphoblastic IGHV-UM CLL, while TNFRSF8, a receptor molecule, was deemed leukemia,40 and elevated HDAC9 was evident in CLL30 and more methylated among IGHV-M cases. In addition, we noted the childhood acute lymphoblastic leukemia40 and was indicative of downstream transcription factor NF-kB1 to be preferentially a poor prognosis. Here, we found several CpG sites within the methylated in IGHV-UM CLL. Admittedly, relating the methylation HDAC4 and HDAC9 genes to be preferentially methylated in IGHV- status of these genes to pathway function is a challenge since UM, which was also verified by pyrosequencing. Given the many genes show variable and sometimes alternative methylation potential use of HDAC inhibitors in CLL treatment,29 the finding at sites within different gene regions. Although complex, our of differential methylation of HDAC genes in specific subgroups of data support the notion that aberrant DNA methylation con- CLL may potentially lead to an altered response to such drugs, tributes to the deregulation of known pathways in CLL even though this must be studied further. pathogenesis.

Leukemia (2013) 150 – 158 & 2013 Macmillan Publishers Limited DNA methylation over time and within different compartments of CLL N Cahill et al 157 Currently, the extent to which DNA methylation levels change ACKNOWLEDGEMENTS with respect to time and treatment is largely undetermined This research was supported by the Nordic Cancer Union, the Swedish Cancer in cancer. Our data presented here recognized DNA methylation Society, the Swedish Research Council, and the Lion’s Cancer Research Foundation, as relatively stable over time among IGHV-M/untreated and Uppsala. Methylation profiling was performed by the SNP&SEQ Technology Platform IGHV-UM/treated CLL patients. Considering the long time period in Uppsala, which is supported by Uppsala University, Uppsala University Hospital, between the first and second sampling points (B5–8 years) and Science for Life Laboratory—Uppsala and the Swedish Research Council (Contracts given the ability of the array to interrogate 4485 000 CpG 80576801 and 70374401). sites, few to no recurrent sites differed in DNA methylation level over time, even if treatment was given between diagnosis and follow-up. The majority of the recurrent differences encountered REFERENCES during the disease course were small methylation changes 1 Herman JG. Hypermethylation of tumor suppressor genes in cancer. Semin Cancer (between 5 and 19% in average beta difference). However, these Biol 1999; 9: 359–367. could not be verified as being truly biological, since the biological 2 Herman JG, Baylin SB. Gene silencing in cancer in association with promoter replicate values were in the same range as the technical replicate hypermethylation. N Engl J Med 2003; 349: 2042–2054. values quoted by Illumina. On the other hand, the lack of 3 Raval A, Tanner SM, Byrd JC, Angerman EB, Perko JD, Chen SS et al. Down- regulation of death-associated protein kinase 1 (DAPK1) in chronic lymphocytic methylation changes may partially be explained by the hetero- leukemia. Cell 2007; 129: 879–890. geneity among the samples, which could mask such changes by 4 Corcoran M, Parker A, Orchard J, Davis Z, Wirtz M, Schmitz OJ et al. ZAP-70 the averaging and transformation of the array data. Instead, intra- methylation status is associated with ZAP-70 expression status in chronic individual analysis may reveal such DNA methylation changes. lymphocytic leukemia. Haematologica 2005; 90: 1078–1088. Using this alternative approach, a significant difference in the 5 Raval A, Lucas DM, Matkovic JJ, Bennett KL, Liyanarachchi S, Young DC et al. number of non-recurrent differentially methylated sites (X0.40) TWIST2 demonstrates differential methylation in immunoglobulin variable heavy between IGHV-UM CLL and IGHV-M patients was identified, chain mutated and unmutated chronic lymphocytic leukemia. J Clin Oncol 2005; although these differences again led to subtle changes on a 23: 3877–3885. global level (median 0.27% in IGHV-UM CLL). Akin to the scenario 6 Strathdee G, Sim A, Parker A, Oscier D, Brown R. Promoter hypermethylation where IGHV-UM patients are more likely to acquire genomic silences expression of the HoxA4 gene and correlates with IgVh mutational status alterations over time43–45 these above findings indicate that the in CLL. Leukemia 2006; 20: 1326–1329. aggressive nature of IGHV-UM CLL condones the acquisition of 7 Liu TH, Raval A, Chen SS, Matkovic JJ, Byrd JC, Plass C. CpG island methylation and expression of the secreted frizzled-related protein gene family in chronic a higher number of ‘passenger’ epi-mutations during clonal lymphocytic leukemia. Cancer Res 2006; 66: 653–658. evolution. 8 Chen SS, Claus R, Lucas DM, Yu L, Qian J, Ruppert AS et al. Silencing of the CLL cells are known to circulate between the PB and LN. inhibitor of DNA binding protein 4 (ID4) contributes to the pathogenesis of While PB CLL cells maintain in a resting state, on journeying mouse and human CLL. Blood 2011; 117: 862–871. to the LN, CLL cells interact with a pro-survival microenvironment 9 Rush LJ, Raval A, Funchain P, Johnson AJ, Smith L, Lucas DM et al. Epigenetic in proliferation centers provoking B1% of CLL to proliferate per profiling in chronic lymphocytic leukemia reveals novel methylation targets. day.16 Recently, differential expression profiles have been Cancer Res 2004; 64: 2424–2433. reported for patient-matched samples originating from the LN 10 Rahmatpanah FB, Carstens S, Hooshmand SI, Welsh EC, Sjahputera O, Taylor KH and PB in CLL.17 More specifically, genes involved in proliferation et al. Large-scale analysis of DNA methylation in chronic lymphocytic leukemia. and active BCR signaling were shown to be highly expressed Epigenomics 2009; 1: 39–61. in the LN compared with the PB. Given the reverse correlation to 11 Kanduri M, Cahill N, Goransson H, Enstrom C, Ryan F, Isaksson A et al. Differential genome-wide array-based methylation profiles in prognostic subsets of chronic gene expression, we hypothesized that DNA methylation lymphocytic leukemia. Blood 2010; 115: 296–305. may partake in the mechanism of differential gene expression 12 Tong WG, Wierda WG, Lin E, Kuang SQ, Bekele BN, Estrov Z et al. Genome-wide seen within the different compartments of CLL. In contrast DNA methylation profiling of chronic lymphocytic leukemia allows identification to our assumption, however, the global DNA methylation of epigenetically repressed molecular pathways with clinical impact. Epigenetics was rather similar in patient-matched CLL cells derived from 2010; 5: 499–508. resting and proliferative compartments, since few/no recurrent 13 Matsuda S, Yokozaki S, Yoshida H, Kitagishi Y, Shirafuji N, Okumura N. Insulin changes were noted and a limited number of non-recurrent receptor substrate protein 53 (IRSp53) as a binding partner of antimetastasis changes were detected. Overall, it appears that unlike molecule NESH, a member of Abelson interactor protein family. Ann Oncol 2008; gene expression, DNA methylation of CLL cells from different 19: 1356–1357. compartments is less influenced by microenvironmental 14 Kleer CG, Zhang Y, Pan Q, van Golen KL, Wu ZF, Livant D et al. WISP3 is a factors. novel tumor suppressor gene of inflammatory breast cancer. Oncogene 2002; 21: In conclusion, this study highlights the extensive differential 3172–3180. 15 Burger JA, Ghia P, Rosenwald A, Caligaris-Cappio F. The microenvironment in methylation profiles in IGHV-M and IGHV-UM CLL, here analyzed mature B-cell malignancies: a target for new treatment strategies. Blood 2009; on a larger scale than before. Important novel findings include the 114: 3367–3375. preferential DNA methylation of CpG sites within known CLL 16 Messmer BT, Messmer D, Allen SL, Kolitz JE, Kudalkar P, Cesar D et al. In vivo (ref. 23) 22 prognostic genes, such as CLLU1 and LPL, which for the measurements document the dynamic cellular kinetics of chronic lymphocytic first time points to a direct role of DNA methylation in regulating leukemia B cells. J Clin Invest 2005; 115: 755–764. these genes. Additionally, key components of TGF-b and NF-kB/ 17 Herishanu Y, Perez-Galan P, Liu D, Biancotto A, Pittaluga S, Vire B et al. The lymph TNF pathways and a number of proliferation-related, BCR signaling node microenvironment promotes B-cell receptor signaling, NF-kappaB activa- and epigenetic regulating genes were identified as differentially tion, and tumor proliferation in chronic lymphocytic leukemia. Blood 2011; 117: methylated in IGHV-M and IGHV-UM CLL. Finally, global DNA 563–574. methylation was deemed to be relatively stable over time and 18 Smedby KE, Hjalgrim H, Melbye M, Torrang A, Rostgaard K, Munksgaard L et al. remarkably similar within different CLL compartments, implicating Ultraviolet radiation exposure and risk of malignant lymphomas. J Natl Cancer Inst aberrant DNA methylation as early events during CLL 2005; 97: 199–209. 19 Hallek M, Cheson BD, Catovsky D, Caligaris-Cappio F, Dighiero G, Dohner H et al. development. Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines. Blood 2008; 111: 5446–5456. CONFLICT OF INTEREST 20 Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery The authors declare no conflict of interest. rate in behavior genetics research. Behav Brain Res 2001; 125: 279–284.

& 2013 Macmillan Publishers Limited Leukemia (2013) 150 – 158 DNA methylation over time and within different compartments of CLL N Cahill et al 158 21 Wiestner A, Rosenwald A, Barry TS, Wright G, Davis RE, Henrickson SE et al. ZAP-70 36 Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nat Rev expression identifies a chronic lymphocytic leukemia subtype with unmutated Genet 2002; 3: 415–428. immunoglobulin genes, inferior clinical outcome, and distinct gene expression 37 Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P et al. The human profile. Blood 2003; 101: 4944–4951. colon cancer methylome shows similar hypo- and hypermethylation at conserved 22 Mansouri M, Sevov M, Fahlgren E, Tobin G, Jondal M, Osorio L et al. Lipoprotein tissue-specific CpG island shores. Nat Genet 2009; 41: 178–186. lipase is differentially expressed in prognostic subsets of chronic lymphocytic 38 Chantepie SP, Vaur D, Grunau C, Salaun V, Briand M, Parienti JJ et al. ZAP-70 leukemia but displays invariably low catalytical activity. Leuk Res 2010; 34: intron1 DNA methylation status: determination by pyrosequencing in B chronic 301–306. lymphocytic leukemia. Leuk Res 2010; 34: 800–808. 23 Buhl AM, Jurlander J, Geisler CH, Pedersen LB, Andersen MK, Josefsson P et al. 39 Herman SE, Gordon AL, Hertlein E, Ramanunni A, Zhang X, Jaglowski S et al. CLLU1 expression levels predict time to initiation of therapy and overall survival in Bruton tyrosine kinase represents a promising therapeutic target for treatment of chronic lymphocytic leukemia. Eur J Haematol 2006; 76: 455–464. chronic lymphocytic leukemia and is effectively targeted by PCI-32765. Blood 24 Puente XS, Pinyol M, Quesada V, Conde L, Ordonez GR, Villamor N et al. Whole- 2011; 117: 6287–6296. genome sequencing identifies recurrent mutations in chronic lymphocytic 40 Moreno DA, Scrideli CA, Cortez MA, de Paula Queiroz R, Valera ET, da Silva leukaemia. Nature 2011; 475: 101–105. Silveira V et al. Differential expression of HDAC3, HDAC7 and HDAC9 is associated 25 Fabbri G, Rasi S, Rossi D, Trifonov V, Khiabanian H, Ma J et al. Analysis of the with prognosis and survival in childhood acute lymphoblastic leukaemia. Br J chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational Haematol 2010; 150: 665–673. activation. J Exp Med 2011; 208: 1389–1401. 41 Cordingley FT, Bianchi A, Hoffbrand AV, Reittie JE, Heslop HE, Vyakarnam A et al. 26 Gutierrez Jr A , Tschumper RC, Wu X, Shanafelt TD, Eckel-Passow J, Huddleston 3rd Tumour necrosis factor as an autocrine tumour growth factor for chronic B-cell PM et al. LEF-1 is a prosurvival factor in chronic lymphocytic leukemia and is malignancies. Lancet 1988; 1: 969–971. expressed in the preleukemic state of monoclonal B-cell lymphocytosis. Blood 42 Ferrajoli A, Keating MJ, Manshouri T, Giles FJ, Dey A, Estrov Z et al. The clinical 2010; 116: 2975–2983. significance of tumor necrosis factor-alpha plasma level in patients having 27 Saborit-Villarroya I, Vaisitti T, Rossi D, D’Arena G, Gaidano G, Malavasi F et al. E2A is chronic lymphocytic leukemia. Blood 2002; 100: 1215–1219. a transcriptional regulator of CD38 expression in chronic lymphocytic leukemia. 43 Shanafelt TD, Witzig TE, Fink SR, Jenkins RB, Paternoster SF, Smoley SA et al. Leukemia 2011; 25: 479–488. Prospective evaluation of clonal evolution during long-term follow-up of patients 28 Liu W, Quinto I, Chen X, Palmieri C, Rabin RL, Schwartz OM et al. Direct inhibition with untreated early-stage chronic lymphocytic leukemia. J Clin Oncol 2006; 24: of Bruton’s tyrosine kinase by IBtk, a Btk-binding protein. Nat Immunol 2001; 2: 4634–4641. 939–946. 44 Stilgenbauer S, Sander S, Bullinger L, Benner A, Leupolt E, Winkler D et al. Clonal 29 Witt O, Deubzer HE, Milde T, Oehme I. HDAC family: What are the cancer relevant evolution in chronic lymphocytic leukemia: acquisition of high-risk genomic targets? Cancer Lett 2009; 277: 8–21. aberrations associated with unmutated VH, resistance to therapy, and short 30 Wang JC, Kafeel MI, Avezbakiyev B, Chen C, Sun Y, Rathnasabapathy C et al. survival. Haematologica 2007; 92: 1242–1245. Histone deacetylase in chronic lymphocytic leukemia. Oncology 2011; 81: 45 Gunnarsson R, Staaf J, Jansson M, Ottesen AM, Goransson H, Liljedahl U et al. 325–329. Screening for copy-number alterations and loss of heterozygosity in chronic 31 Kn H, Bassal S, Tikellis C, El-Osta A. Expression analysis of the epigenetic lymphocytic leukemia--a comparative study of four differently designed, high methyltransferases and methyl-CpG binding protein families in the normal resolution microarray platforms. Genes Chromosomes Cancer 2008; 47: 697–711. B-cell and B-cell chronic lymphocytic leukemia (CLL). Cancer Biol Ther 2004; 3: 46 Lenschow DJ, Sperling AI, Cooke MP, Freeman G, Rhee L, Decker DC et al. 989–994. Differential up-regulation of the B7-1 and B7-2 costimulatory molecules after Ig 32 Chaperot L, Plumas J, Jacob MC, Bost F, Molens JP, Sotto JJ et al. Functional receptor engagement by antigen. J Immunol 1994; 153: 1990–1997. expression of CD80 and CD86 allows immunogenicity of malignant B cells from 47 Nagy B, Lundan T, Larramendy ML, Aalto Y, Zhu Y, Niini T et al. Abnormal non-Hodgkin’s lymphomas. Exp Hematol 1999; 27: 479–488. expression of apoptosis-related genes in haematological malignancies: 33 Kaderi MA, Kanduri M, Buhl AM, Sevov M, Cahill N, Gunnarsson R et al. LPL is the overexpression of MYC is poor prognostic sign in mantle cell lymphoma. Br J strongest prognostic factor in a comparative analysis of RNA-based markers in Haematol 2003; 120: 434–441. early chronic lymphocytic leukemia. Haematologica 2011; 96: 1153–1160. 48 Ban EM, LeBoeuf RD. Suppressin: an endogenous negative regulator of immune 34 Fabris S, Bollati V, Agnelli L, Morabito F, Motta V, Cutrona G et al. Biological and cell activation. Immunol Res 1994; 13: 1–9. clinical relevance of quantitative global methylation of repetitive DNA sequences 49 Osorio LM, Aguilar-Santelises M. Apoptosis in B-chronic lymphocytic leukaemia. in chronic lymphocytic leukemia. Epigenetics 2011; 6: 188–194. Med Oncol 1998; 15: 234–240. 35 Pei L, Choi JH, Liu J, Lee EJ, McCarthy B, Wilson JM et al. Genome-wide DNA 50 Vargova K, Curik N, Burda P, Basova P, Kulvait V, Pospisil V et al. MYB tran- methylation analysis reveals novel epigenetic changes in chronic lymphocytic scriptionally regulates the miR-155 host gene in chronic lymphocytic leukemia. leukemia. Epigenetics 2012; 7: 567–578. Blood 2011; 117: 3816–3825.

Supplementary Information accompanies the paper on the Leukemia website (http://www.nature.com/leu)

Leukemia (2013) 150 – 158 & 2013 Macmillan Publishers Limited