Correspondence Shustik, J., Quinn, M., Connors, J.M., Gascoyne, R.D., Skinnider, B. & Sehn, L.H. (2011) Follicular nonHodgkin lymphoma grades 3A and 3B have a similar outcome and appear incurable with anthracyclinebased therapy. Annals of Oncology, 22, 1164–1169. Swerdlow, S.H., Campo, E., Harris, N.L., Jaffe, E., Pileri, S.A., Stein, H., Thiele, J. & Vardiman,
J.W. (2008) WHO Classification of Tumours of Haematopoetic and Lymphoid Tissues. IARC, Lyon. Vaidyanathan, G. & Czuczman, M.S. (2014) Follicular lymphoma grade 3: review and updates. Clinical Lymphoma, Myeloma & Leukemia, 14, 431–435.
Wahlin, B.E., Yri, O.E., Kimby, E., Holte, H., Delabie, J., Smeland, E.B., Sundstr€ om, C., Christensson, B. & Sander, B. (2012) Clinical significance of the WHO grades of follicular lymphoma in a population-based cohort of 505 patients with long follow-up times. British Journal of Haematology, 156, 225–233.
Global hypomethylation in myeloma is associated with poor prognosis
Multiple myeloma is a malignancy of plasma cells, which transforms from monoclonal gammopathy of uncertain significance (MGUS) at a rate of around 1%/year (Kyle et al, 2002). Epigenetic mechanisms play a role in this progression, with methylation studies demonstrating two distinct patterns: (i) Global hypomethylation in the transition towards an increasingly aggressive phenotype: normal plasma cells/ MGUS/asymptomatic myeloma/symptomatic myeloma. These changes occur predominantly outside CpG islands (Salhia et al, 2010; Walker et al, 2011; Heuck et al, 2013). (ii) Distinct patterns of hypermethylation occurring within subgroups of symptomatic myeloma, with changes occurring more commonly within CpG islands. These patterns of hypermethylation can distinguish cytogenetic subtypes (Walker et al, 2011) and have been linked to clinical outcomes (Kaiser et al, 2013). Myeloma may also be classified according to cyclin D-type dysregulation. Amongst nonhyperdiploid cases, those with IGH translocations t(4;14) or t(14;16) express higher levels of cyclin-D2, while those with t(11;14) translocations express elevated cyclin-D1 (Bergsagel & Kuehl, 2005). Cyclin-D2 dysregulated myeloma cases tend to progress with more proliferative disease and poorer outcomes than cyclin-D1, but the underlying biological processes remain unclear. To investigate the role of methylation in both cyclin dysregulation and myeloma prognosis more generally, we performed global methylation analysis on primary patient plasma cells, matched for cyclin types D1 and D2. Primary bone marrow samples were collected from eight t(11;14) cyclin-D1 patients, and eight cyclin-D2 patients [four t(4;14) and four t(14;16)]. Plasma cells were isolated using magnetic-activated CD138 MicroBeads (Miltenyi Biotec, Bisley, UK). DNA was extracted using DNeasy (Qiagen, Manchester, UK), bisulfite-converted with the EZ-DNA Methylation Kit (Zymo, Cambridge, UK), and processed on Illumina Infinium human methylation27 arrays. Differentially methylated probes were identified using the R package Limma (http:// www.bioconductor.org/packages/release/bioc/html/limma.html). Methylation variable positions (MVPs) that exhibited a false discovery rate (FDR) adjusted P-value < 001 and a ª 2015 John Wiley & Sons Ltd British Journal of Haematology, 2016, 172, 461–486
methylation difference (Δb) of 30% were considered significant. Survival analyses for progression-free survival (PFS) and overall survival (OS) were calculated from the date of sampling and analysed by Kaplan–Meier and log-rank methods. P-values < 005 were considered significant. Unsupervised hierarchical clustering based on global methylation data separated the samples into two groups (‘Group 1’ and ‘Group 2’) unrelated to cyclin D-type. These two epigenetically distinct groups were well matched in terms of baseline characteristics, with no obvious differences in prognostic features. Although samples were taken at varying time points from initial presentation, the time from diagnosis to sampling did not vary significantly between the two groups (Table I). Table I. Patient and disease characteristics of myeloma cases in Groups 1 and 2, derived from unsupervised analysis of methylation data.
N Median age at diagnosis, years (range) Male:female Immunoglobulin Isotype: IgG/IgA/IgD/IgM/light chain Cyclin translocation t(11;14) t(4;14) t(14;16) Other cytogenetic features tp53 1q+ 1p 13q Months from diagnosis to sampling (range) Median progression-free survival (months) Median overall survival (months)
Group 1
Group 2
P value
6 64 (51–78)
10 61 (45–73)
066
5:1 2/1/2/1/0
6:4 4/1/2/0/3
3 2 1
5 2 3
0 1 0 1 275 (0–60)
1 2 0 4 215 (0–83)
078
244
72
034
617
119
006
473
Correspondence
(A)
(B)
Group 1
Group 2
% Survival
100
Progression-free survival P = 0·34
50
0
0
20
40
60
80
Time (months)
Overall survival P = 0·06
(C)
Colour key
% Survival
100
50
0 0·2 0·6 Value
0
20
Supervised analysis of the methylation differences between the groups revealed 448 MVPs (corresponding to 403 unique genes) that exhibited a difference in methylation at an FDRadjusted P-value threshold of
J.W. (2008) WHO Classification of Tumours of Haematopoetic and Lymphoid Tissues. IARC, Lyon. Vaidyanathan, G. & Czuczman, M.S. (2014) Follicular lymphoma grade 3: review and updates. Clinical Lymphoma, Myeloma & Leukemia, 14, 431–435.
Wahlin, B.E., Yri, O.E., Kimby, E., Holte, H., Delabie, J., Smeland, E.B., Sundstr€ om, C., Christensson, B. & Sander, B. (2012) Clinical significance of the WHO grades of follicular lymphoma in a population-based cohort of 505 patients with long follow-up times. British Journal of Haematology, 156, 225–233.
Global hypomethylation in myeloma is associated with poor prognosis
Multiple myeloma is a malignancy of plasma cells, which transforms from monoclonal gammopathy of uncertain significance (MGUS) at a rate of around 1%/year (Kyle et al, 2002). Epigenetic mechanisms play a role in this progression, with methylation studies demonstrating two distinct patterns: (i) Global hypomethylation in the transition towards an increasingly aggressive phenotype: normal plasma cells/ MGUS/asymptomatic myeloma/symptomatic myeloma. These changes occur predominantly outside CpG islands (Salhia et al, 2010; Walker et al, 2011; Heuck et al, 2013). (ii) Distinct patterns of hypermethylation occurring within subgroups of symptomatic myeloma, with changes occurring more commonly within CpG islands. These patterns of hypermethylation can distinguish cytogenetic subtypes (Walker et al, 2011) and have been linked to clinical outcomes (Kaiser et al, 2013). Myeloma may also be classified according to cyclin D-type dysregulation. Amongst nonhyperdiploid cases, those with IGH translocations t(4;14) or t(14;16) express higher levels of cyclin-D2, while those with t(11;14) translocations express elevated cyclin-D1 (Bergsagel & Kuehl, 2005). Cyclin-D2 dysregulated myeloma cases tend to progress with more proliferative disease and poorer outcomes than cyclin-D1, but the underlying biological processes remain unclear. To investigate the role of methylation in both cyclin dysregulation and myeloma prognosis more generally, we performed global methylation analysis on primary patient plasma cells, matched for cyclin types D1 and D2. Primary bone marrow samples were collected from eight t(11;14) cyclin-D1 patients, and eight cyclin-D2 patients [four t(4;14) and four t(14;16)]. Plasma cells were isolated using magnetic-activated CD138 MicroBeads (Miltenyi Biotec, Bisley, UK). DNA was extracted using DNeasy (Qiagen, Manchester, UK), bisulfite-converted with the EZ-DNA Methylation Kit (Zymo, Cambridge, UK), and processed on Illumina Infinium human methylation27 arrays. Differentially methylated probes were identified using the R package Limma (http:// www.bioconductor.org/packages/release/bioc/html/limma.html). Methylation variable positions (MVPs) that exhibited a false discovery rate (FDR) adjusted P-value < 001 and a ª 2015 John Wiley & Sons Ltd British Journal of Haematology, 2016, 172, 461–486
methylation difference (Δb) of 30% were considered significant. Survival analyses for progression-free survival (PFS) and overall survival (OS) were calculated from the date of sampling and analysed by Kaplan–Meier and log-rank methods. P-values < 005 were considered significant. Unsupervised hierarchical clustering based on global methylation data separated the samples into two groups (‘Group 1’ and ‘Group 2’) unrelated to cyclin D-type. These two epigenetically distinct groups were well matched in terms of baseline characteristics, with no obvious differences in prognostic features. Although samples were taken at varying time points from initial presentation, the time from diagnosis to sampling did not vary significantly between the two groups (Table I). Table I. Patient and disease characteristics of myeloma cases in Groups 1 and 2, derived from unsupervised analysis of methylation data.
N Median age at diagnosis, years (range) Male:female Immunoglobulin Isotype: IgG/IgA/IgD/IgM/light chain Cyclin translocation t(11;14) t(4;14) t(14;16) Other cytogenetic features tp53 1q+ 1p 13q Months from diagnosis to sampling (range) Median progression-free survival (months) Median overall survival (months)
Group 1
Group 2
P value
6 64 (51–78)
10 61 (45–73)
066
5:1 2/1/2/1/0
6:4 4/1/2/0/3
3 2 1
5 2 3
0 1 0 1 275 (0–60)
1 2 0 4 215 (0–83)
078
244
72
034
617
119
006
473
Correspondence
(A)
(B)
Group 1
Group 2
% Survival
100
Progression-free survival P = 0·34
50
0
0
20
40
60
80
Time (months)
Overall survival P = 0·06
(C)
Colour key
% Survival
100
50
0 0·2 0·6 Value
0
20
Supervised analysis of the methylation differences between the groups revealed 448 MVPs (corresponding to 403 unique genes) that exhibited a difference in methylation at an FDRadjusted P-value threshold of
