Supplementary information to the manuscript by Ammerpohl et
al entitled: "Array-based DNA methylation analysis in classical
Hodgkin lymphoma reveals new insights into the mechanisms
underlying silencing of B cell-specific genes"
1. Materials and methods
1.1. Controls, primary cases and cell lines
1.2. DNA methylation microarray
1.3. Microarray data analysis
1.4. Bisulfite pyrosequencing
1.5. Gene ontology analysis of differentially methylated genes
1.6. Gene expression analysis
1.7. Enrichment for PcG-marks and promoter classes in different
methylation groups.
1.8. EZH2 mutation screening
2. Supplementary results
2.1. Quality, reproducibility and technical validation of the
microarray data
2.2. Hierarchical cluster analysis
2.3. Additional gene expression analysis
2.4. Mutation analysis of EZH2 in cHL
2.5. Supplementary references
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1. Materials and methods
1.1. Controls, primary cases and cell lines
We analyzed a total of 25 B cell lymphoma samples by DNA methylation
microarrays. These included the five cHL cell lines L-1236, L-428, KM-H2,
HDLM-2 (German Collection of Microorganisms and Cell Cultures) and U-HO1
(1) (kindly provided by Andreas Bräuninger, University Hospital Münster,
Germany), and 20 gcdBCL. The latter included the BL cell line Raji (BioChain
Institute, CA, USA) and the FL cell line RL (kindly provided by Charles W.
Caldwell, University of Missouri, USA) as well as 18 primary lymphomas defined
by transcriptional and genomic profiling (2) (six molecular BL (mBL), seven
germinal center B cell (GCB) DLBCL, and five activated B cell (ABC) DLBCL).
As normal B cell (NBC) controls, we used the NA06999 lymphoblastoid cell line
(Coriell Institute for Medical Research, Camden, NJ, USA), tonsillar centroblasts
(CD77+) and tonsillar germinal center B cells (CD19+, CD20high, CD38+). We
also used in vitro methylated DNA (M.SssI methyltransferase, New England
Biolabs, MA, USA) and whole genome amplified DNA (REPLI-g MiniKit, Qiagen,
Hilden, Germany) as positive and negative technical controls for the microarray
analyses (3), respectively.
Part of the cases studied herein have been published before. Genomic and
transcriptional profiling of the 18 gcdBCL primary cases included in the study
has been published in Hummel et al. (2). A partial analysis of DNA methylation
data from these cases as well as from the NA06999 lymphoblastoid cell line and
tonsilar germinal center B-cells (CD19+, CD20high, CD38+) has been published
in Martin-Subero et al. (4). The PLAGL1 primers used for bisulfite
pyrosequencing have been published in Martin-Subero et al. (5)
The primary lymphomas studied herein belong to the network project “Molecular
Mechanisms in Malignant Lymphomas (MMML)”, for which central and local
ethics approval was obtained.
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1.2. DNA methylation microarray
We used the Infinium Assay from Illumina (San Diego, CA) for genome-wide
DNA methylation analyses. The panel is developed to quantify the DNA
methylation status of 27,578 CpG sites located within the proximal promoter
regions (1 kb upstream and 500 bp downstream of transcription start sites) of
14,475 well-annotated genes from the consensus coding sequence project as
well as known cancer genes and microRNAs (3). Briefly, genomic DNA is
converted by sodium bisulfite treatment and whole-genome amplified using the
manufacturer’s instructions. Each CpG locus is represented by two bead types:
one for the unmethylated (U) site and another for the methylated (M) site. After
hybridization and single-base extension using labelled nucleotides, the intensity
of the U and M beads is measured with a microarray reader. The methylation
status of a CpG is determined by the beta-value calculation, which is the ratio of
the fluorescent signals between the M bead to the total locus fluorescence
intensity.
1.3. Microarray data analysis
Before analyzing the methylation data (so called beta values, which range from
0 for unmethylated to 1 for completely methylated), we excluded possible
sources of biological and technical biases that could alter the results. As the X
chromosome shows differential methylation in men and women and
chromosome Y is only present in males, we excluded all 1,092 CpGs on
chromosomes X and Y to avoid a gender-specific bias. Additionally, we selected
exclusively high quality CpGs by filtering out 2,174 CpGs with bad detection p
values (p>0.01) in at least one sample. Using these strict criteria, a total of
24,312 high-quality CpGs (13,088 genes) entered further statistical analyses
(raw data shown as supplementary information).
As 7 of the 28 studied samples were analyzed in duplicate, we measured the
reproducibility of the Infinium microarray by performing scatter plots and
calculating the coefficients of determination.
Unsupervised hierarchical clustering was performed using the Cluster Analysis
tool of the BeadStudio software (version 3.2). A differential methylation analysis
was performed with the R statistical software (http://www.R-project.org). Using
previously reported criteria for DNA methylation analyses with Illumina arrays
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(4), a given CpG was classified as differentially methylated between cases and
controls if the difference between mean beta values was at least 0.25 in the two
compared groups, and the false discovery rate (FDR) of a Wilcoxon test for
independent samples was below 0.05.
1.4. Bisulfite pyrosequencing
Genomic DNA was bisulfite converted using the EpiTect Bisulfite Conversion Kit
(Qiagen, Hilden, Germany), according to manufacturer’s instructions. Bisulfite
pyrosequencing was performed according to standard protocols and evaluated
with the analysis software Pyro Q-CpG 1.0.9 (Biotage, Uppsala, Sweden),
which was also used to quantify the percentage of methylated cytosines at the
analyzed CpG sites. PCR and primer sequences are shown in Table S1.
1.5. Gene ontology analysis of differentially methylated genes
The Gene Ontology enRIchment anaLysis and visuaLizAtion tool (GOrilla,
http://cbl-gorilla.cs.technion.ac.il) was used to determine the enrichment of
individual ontology terms and create gene ontology maps in the groups of
differentially methylated genes as compared with the 13,088 genes studied with
the Infinium array (6).
1.6. Gene expression analysis
Normalized Affymetrix U95A gene expression data from normal B cells, cHL cell
lines as well as gcdBCL cell lines and primary cases were obtained from the
supplementary material of a publication by Küppers and coworkers (7). We
analyzed the percentage of absent and present detection calls for genes
differentially methylated in cHL and/or gcdBCL.
1.7. Enrichment for PcG-marks and promoter classes in different
methylation groups.
Proportions of PRC2 targets in genes commonly or differentially methylated in
cHL and gcdBCL were compared with the proportion of PRC2 targets in all
genes included in the Infinium Illumina Array using Fisher’s exact test. ChIPSeq genome-wide maps of EZH2 and 3mK27H3 genes in ESCs and normal
germinal center B cells (centroblasts) was obtained from Ku et al. (8) and
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Velichutina et al. (9), respectively. To analyze whether promoter regions of the
methylation groups showed different CpG compositions, we classified them into
promoters with high (HCP), intermediate (ICP) and low (LCP) CpG content
according to a previously published study (10).
1.8. EZH2 mutation screening
Genomic DNA from five cHL cell lines (L-1236, L-428, KM-H2, HDLM-2 and UHO1) was used for screening of mutations in the coding region of EZH2.
Sequencing was performed using previously published primers (11, 12)
according to conventional methods using an ABI PRISM® 310 Genetic Analyzer
capillary sequencer (Applied Biosystems, Darmstadt, Germany).
2. Supplementary results
2.1. Quality, reproducibility and technical validation of the microarray data
After filtering sex chromosome-specific and low quality CpGs as outlined in the
methods section, a total of 24,312 autosomal CpGs from 13,088 genes entered
the statistical analyses. The mean coefficient of determination between
replicates (seven samples) was 0.987 (ranging from 0.984 to 0.991) (Figure S1)
demonstrating the high reproducibility of the assay.
To technically validate the results by an independent method, we compared the
DNA methylation level of 14 different CpGs (11 genes) present in the Infinium
array to the levels measured by bisulfite pyrosequencing in the five cHL cell
lines and the Raji cell line (Primers are shown in Table S1). These comparisons
indicated that DNA methylation levels detected with both methods are highly
correlated (Spearman correlation coefficient = 0.86, p<0.001, Figure S2).
2.2. Hierarchical cluster analysis
A hierarchical cluster analysis of the methylation values of the 24,312 CpGs
entering the evaluation is shown in Figure S3. This analysis shows that the
positive and negative technical controls are fully methylated and fully
unmethylated, respectively, and cluster separately. Normal B cells (NBCs) show
DNA methylation profiles clearly different from most lymphoma samples.
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Classical HL and gcdBCL cell lines along with one primary case show the
highest number of hypermethylated genes of all samples studied. This finding
suggests either that lymphoma cell lines are developed from primary cases with
highly altered DNA methylomes and/or that some epigenetic changes are
acquired in vitro. Within lymphoma subtypes, cHL and gcbBCL (FL and BL) cell
lines cluster separately, suggesting the presence of specific DNA methylation
patterns associated to these entities.
2.3. Additional gene expression analysis
As shown in figure 2 of the manuscript, genes Hmet-cHL showed a higher
percentage of absent calls (i.e. not expressed) in cHL (62%) than in NBCs
(32%) and gcdBCL (40%). As the link between hypermethylation and silencing
in cHL might be affected by the fact that the group of gcdBCLs is made out of
different lymphoma entities, we studied BL and DLBCL separately. In particular,
we took those genes silenced only in cHL as compared to gcdBCLs and we
calculated the percentage of absent calls in cHL, BL and DLBCL. As shown in
figure S4, these genes are mostly silenced both in BL and DLBCL. This result
further supports the finding that genes silenced in cHL target the B cell program,
which is expressed in BL and DLBCL.
2.4. Mutation analysis of EZH2 in cHL
As the Tyr641 EZH2 mutation, which enhances EZH2 activity (13), has been
recurrently detected in gcdBCLs (14), we screened the same five cHL cell lines
used for DNA methylation profiling for EZH2 mutations. Indeed, we could
identify a heterozygous mutation A>C in the cell line L428 leading to a tyrosine
to serine alteration at codon 641 (Tyr641) (Figure S8).
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2.5. Supplementary references
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6.
7.
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9.
10.
11.
12.
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