Waldenström macroglobulinemia (WM) DNA methylation analysis Collaboration INSERM U1170 (O. Bernard) Bioinformatics Ohio State (C. Oakes) GH Pitié-Salpêtrière, UMRS 1138 (F. Nguyen-Khac) Damien Roos-Weil FILO Nancy 2020
Waldenström macroglobulinemia (WM)
DNA methylation analysis
Collaboration
INSERM U1170 (O. Bernard)
Bioinformatics Ohio State (C. Oakes)
GH Pitié-Salpêtrière, UMRS 1138 (F. Nguyen-Khac)
Damien Roos-Weil
FILO Nancy 2020
Waldenström’s macroglobulinemia (WM)
Küppers, 2005
Origin ? Clinical heterogeneity ?
- Clonal mixture of lymphoid and plasma cells
- IgM secretion, unable to undergo CSR
- mutated IGHV
- CD22low+, CD23+, CD25+, CD27+, CD38low+, SmIgM+
Morel 2008
Treon 2012 and 2015
DNA methylation (in B-cell malignancies)
• DNA methylation (5mC) : CpG dinucleotides
• DNA methyltransferases (DNMT, writers), 5mC binding proteins (readers), 5mC demethylation (TET, erasers)
• Promoter DNA methylation inversely correlated with gene expression
• Global DNA hypomethylation (depth correlated to increasing maturation)
• Focal changes in promoters and regulatory regionsOakes Blood 2018
DNA methylation dynamics during B-cell maturation
Oakes Nat Genet 2016
• High degree of epigenetic change during B-cell maturation
• Activity of a limited group of transcriptions factors
DNA methylation analysis in CLL
Oakes Nat Genet 2016
Waldenström macroglobulinemia (WM)
DNA methylation analysis
Collaboration C. Oakes (Ohio state)
Bone marrow WM samples : cell-sorted B-cells on CD19+, monotypic light chain+
Methylation : 35 (T. Zenz team, Heidelberg)
. NGS : 35 including 11 WES and 24 targeted NGS (Gustave Roussy)
. RNA seq : 24 (P. Vyash team, Oxford)
DNA methylation profile of WM ? Differents patterns ?
Specific epigenetic events in WM ?
Correlation with distinct clinical and biological characteristics ?
Principal component 1 (33%)
Pri
nc
ipa
l c
om
po
ne
nt
2 (
5%
)
Illumina EPIC/850K arrays
Principal component analysis (PCA) of the top 1% most-variable CpGs
PCAUnsupervised clustering
35 WM patients (14+21)
All MYD88 mutated (VAF > 30%)
Global DNA methylation analysis
Principal component 1 (38%)
Pri
ncip
al c
om
po
nen
t 2
(1
1%
)
PCA
RNA sequencing analysis
24 WM patients (11+14)
All MYD88 mutated (VAF > 30%)
top hit = gene set comparing IgM memory B cells to plasma cells
7 of the top 10 most enriched gene sets
GSEA
2 groups, B-cell maturation
Memory B-cell (MBC)-like, Plasma-Cell (PC)-like
MBC = memory B cells ; PC = plasma cell
19 genes
0
20
40
60
80
100
120
140
160
180
200
MBC PC
0
50
100
150
200
250
300
350
400
WM MBC-like
WM PC-like
0
20
40
60
80
100
120
140
160
180
200
MBC PC
0
50
100
150
200
250
WM MBC-like
WM PC-like
0
10
20
30
40
50
60
70
80
90
100
MBC PC
0
50
100
150
200
250
300
350
WM MBC-like
WM PC-like
0
2000
4000
6000
8000
10000
12000
14000
MBC PC
0
10000
20000
30000
40000
50000
60000
WM MBC-like
WM PC-like
0
5
10
15
20
25
MBC PC
0
5
10
15
20
25
30
35
40
45
WM MBC-like
WM PC-like
0
200
400
600
800
1000
1200
MBC PC
0
100
200
300
400
500
600
WM MBC-like
WM PC-like
0
20
40
60
80
100
120
140
160
MBC PC
0
10
20
30
40
50
60
70
WM MBC-like
WM PC-like
0
10
20
30
40
50
60
MBC PC
0
2
4
6
8
10
12
14
16
18
WM MBC-like
WM PC-like
0
50
100
150
200
250
300
350
400
450
MBC PC
0
200
400
600
800
1000
1200
1400
WM MBC-like
WM PC-like
IRF8 BLK SPIB BACH2 XBP1 BLIMP1 CD138 IGHM CD20
MBC
PC
WM, MBC-like
WM, PC-like
C
16 differentially expressed
10 concordant
MBC (n=5), PC (n=7)
Association with normal MBC and PC subsets
Exp
ress
ion
WM
PC
-lik
e/M
BC
-lik
e (
log
10
)
Expression normal
PC/MBC (log10)
ncs = non-classed switched ; cs = class-switched
1,000 most-variable CpGs
Comparison of DNA methylation patterns between WM and normal cells
MBC-like and PC-like WM subtypes reminiscent of other B-cell malignancies
tSNE analysis
Most variable CpGs
Among WM and normal B-cells
Tumor-specific epigenetic events ?
Concordant hypomethylated CpGs
- 75% MBC-like and PC-like
- 40% MBC-like and HP-CLL
- 85% PC-like and MM
Tumor-specific epigenetic events ? Association with chromatin states ?
Distinct biological features of MBC-like and PC-like subtypes
Distinct biological features of MBC-like and PC-like subtypes
MBC-like
• more splenomegaly (5/14 vs. 1/21, P = .02)
• more thrombocytopenia (7/14 vs. 0/21, P = .0001)
DNA analysis of WM patients
Perspectives
- Correlation with clinical outcomes ?
- Larger cohorts
- DNA methylation probe set ? CD38 ? Cytologic features ?
- DNA methylation profile comparison with splenic marginal zone lymphoma ?
- Model the impact of CXCR4 mutations (in association with MYD88 LP) or others
genetic events on human and murine B-cell (PC vs. MBC) differentiation ?
Acknowledgments
Olivier Bernard
Véronique Della Valle
Hussein Ghamlouch
Camille Decaudin
Marine Armand
Florence Nguyen-Khac
Véronique Leblond
Magali Le Garff-Tavernier
Nabih Azar
Karim Maloum, Catherine Settegrana
U1170, Gustave Roussy, Villejuif
Oxford (RNAseq)
Pitié-Salpêtrière, Paris
Paresh Vyas
Marlen Metzner
Ohio State and Heidelberg (DNA methylation)
Chris Oakes
Brian Giacopelli
Thorsten Zenz
Junyan Lu