Next Generation Sequencing and targeted genotyping as tools
for personalized medicine in lymphoma
February 2017, the 10th
23d BHS Meeting
Fabrice Jardin, MD-PhD,
Department of Clinical Hematology and INSERM U1245,
Centre Henri Becquerel, Rouen, France
UMR 918
B-cell lymphoma biology : milestones
Translocations
GEPABC / GCB / PMBL
NGSRecurrent mutations
Epigenomics, miRNA
1985-1995 2000 2009
IgH- BCL2/BCL6/MYC
The post R-CHOP era ?
Translocations
GEPABC / GCB / PMBL
NGSRecurrent mutations
Epigenomics, miRNA
1985-1995 2000 2009
CHOP R-CHOP R-CHOPPlus…..
1970 1998 2014
Chemotherapy Immunochemotherapy Precision therapy
Principles of NGS
Sonication
Selection/capture
Amplification
Sequencing
You get a lot of pieces of Puzzle (Reads)….
…..That you have to order and compare
Comparaison / Alignement to Genome reference
Human genome reference 19 (Hg19)
Hg19
Alignement
Calling
Identification of a Variant / reference
Hg19
Variant analyse
SNP or true Acquired mutation ?Synonymous ?Functional impact ?(false-sens, non-sens, frameshift…)
Data base resourcesdb SNP , COSMIC…
Algorithms: SIFT, CADD, Polyphen…
??
Hg19
reads
unmutated
mutated
= VAFVariant allele Frequency
« deep sequencing »
Projet 5000 K, Lawrence et al, Nature 2014
Whole exome sequencing data in diffuse large B-cell lymphoma> 500 published WES
Exome sequencing : saturation data ?
Lymphomes – BiologieLDGCB
missense mutations
Copy gain
frameshift/ stop mutations
Copy loss
1001 exomes
sequences
NF-kB (n = 454) Récepteur de cellule B (n = 166)
Signal GPCR (n = 194)
PIM1/MYC (n = 212)
Apoptose (n = 389)
Cycle cellulaire (n = 208)
PRC2 (n = 123)SWI/SNF (n = 263)
JAK/STAT (n = 241)
PI3K (n = 188)
HAT (n = 160)
Interféron (n = 176)
Méthylation de l’histone lysine (n = 241)
Épissure (n = 84) RAS sig (n = 116)
13
Pattern ofAcquired genomic alteration
ASH 2016 - Dave S et al., abstr. 1087
1001 genomes in DLBCL
Lymphomes – BiologieLDGCB
14
MYC
SRGAP3
ZFAT
NF1
HRAS
BTG1
KLHL14
CDKN2A
CREBBP
PTPRD
NHSL1
EZH2
MYD88
ARID5B
CD70
0,03125 0,25000 2,00000
All LDGCB
ABC LDGCB
GCBLDGCB
subtypesFavorable Unfavorable
HR
0,0625 1 4,0HR
Functional combinations
ABC & KLHL14
BCL2 élevé & SPTBN1
ABC & CDKN2A
BCL2 élevé & MLL2 & TP53
MYC élevé & BTG2
ABC & CREBBP
GCB & EZH2
GCB & MYD88
GCB & ARID5B
GCB & CD70
Favorable Unfavoralble
ASH 2016 - Dave S et al., abstr. 1087
• Next Generation Sequencing (NGS)
• New insights into DLBCL genomic characterization
• Recurrent Single Nucleotide Variants (SNVs)
• Actionable targets
• Need for a clinically relevant consensus gene panel
• More definite identification of molecular subtypes
• Routine clinical disease management
• Reach goal of precision therapy in DLBCL
• Lymphopanel development dedicated to DLBCL
• Inclusion of 34 genes
• Based on literature data and study of R/R patients (Mareschal et al, GCC 2015)
The role of next-generation sequencing in understanding the genomic basis of diffuse large B cell lymphoma and advancing targeted therapies.
EZH2
Y E S ICG
TP53, CDKN2A/CDKN2B, BCL2, MFHAS1, MYC, GNA13,
PRDM1, XPO1
Apoptosis
KMT2D, EZH2, CREBBP, EP300, ME2FB
Epigenetic regulation
MYD88, CARD11, TNFAIP3, PIM1
NFkB
ITPKB, CD79A/B, IRF4ID3, TCF3, FOXO1
BCR
CD58, TNFSR14, B2M, CIITA
Immunity
NOTCH1, NOTCH2
NOTCH
BRAF
MAP Kinases
STAT6, SOCS1
JAK/STAT
n = 34 genes, 80 Kb
Lymphopanel 1.0
MLL2,28%
BCL2, 25%
TP53, 23%
MYD88, 16%
CREBBP, 16%
B2M, PIM1, MEF2B, 14%
SOCS1, TFNAIP3, CARD11, 11%
COSMID data base, 2014, top 50
* * * * * * * * * * * * * * * * *
* Included in the lymphopanel
DLBCLGene panel
TP53, MYD88(?), FOXO1, TNFAIP3
(?)
EZH2, MLL2(?), CREBBP (?),
CARD11, MYD88, CD79A/B
XPO1, ID3, TCF3EZH2, MYD88,
GNA13, CARD11, IRF4
• Cohort of 215 patients
– de novo DLBCL, included in LYSA prospective clinical
trials
– GEP (Affymetrix): 83 GCB, 81 ABC, 18 PMBL, 33 other
• Sequenced with Ion Torrent Personal Genome Machine ®
• Variant analysis using lab-developed pipeline– GenerateReports tool (P-J Viailly)
Dubois et al. CCR 2016
Dubois et al. Clinical Cancer Research 2016
N = 215Programme LNH 03B
Classification COO affyCGHIHC
Lymphopanel 1.0 : COO discriminant +++
Confirmation of subtype-enriched mutations
Lim et al. CCR 2016
Pronostic relevance of the lymphopanel
Dubois et al. Clinical Cancer Research 2016
TNFAIP3 GNA13
The role of next-generation sequencing in understanding the genomic basis of diffuse large B cell lymphoma : putative impact on targeted therapies.
Dubois et al. CCR 2016
Three emblematicmutations as example
• EZH2 (Y641N)
• MYD88 (L265P)
• XPO1 (E571K)
SET
EZH2
EEDRBP48
SUZ12
PRC2
Transcriptionof PRC2-related target genes
OFF
me
K27
me
K27
me
K27
me me
me
DZNep
Histone tail
EI1, GSK343, GSK126
SAH-EZH2
Targeting the EZH2 / PRC2 pathway
Bohers et al. Leukemia and lymphoma 2014, Jardin et al. Discovery Medicine 2014
EZH2 inhibitors
S . Dubois et al Oncotarget 2015
Transcriptionof PRC2-related target genes
OFF
me
K27
me
K27
me
K27
me me
meHistone tail
EZH2
H3K27 m2 H3K27 m3EZH2
Targeting the EZH2 / PRC2 pathway
SET
EZH2
EEDRBP48
SUZ12
PRC2
transcription
OFF
me
K27
me
K27
me
K27
meme
meHistone tail
Tazemetostat
-125
-75
-25
25
75
125
non-GCB
non-GCB
non-GCB
non-GCB
Und. GCB Und. non-GCB
GCB non-GCB
225
275
RP RPRP RP RP RP RP RC
RC
DLBCL MZLFL
DLBCL FL MZL
RC+RP5/10 (50%) 3/5 (60 %) 1/1
9/16 (56 %)
Patients (n = 16)
(Ribrag et al. abstract # 473, ASH 2015)
Targeting the EZH2 / PRC2 pathway
Ngo et al. Nature 2011
MYD88 mutations in DLBCL
Bohers et al. Leukemia and lymphoma 2015
MYD88 mutations in DLBCL
Jung-Woo et al. Human Pathol 2013
MYD88 expression and MYD88 mutations: clinical relevance
• correlation with age , Non-GCB• Cytoplasmic staining + 38%; • No correlation with mutation status
MYD88 protein expression
MYD88 mutations
Rovira et al. CCR 2016, Dubois et al CCR 2016, Fernandez, Rodriguez al. Leukemia 2014
• correlation with age, Non-GCB/ABC• Prognostic relevance ?• Extra-nodal (testis)• High IPI
Wilson el al . Nature genetics 2015
Ibrutinib sensibility regarding MYD88 mutational status
Resistance
Sensibility
BCR
CD
79
A
CD
79
B
SYK
BLNKPLCγ2
BTK
PI3K
IP3 DAG
PKC
Ibrutinib
AKT
mTOR
IKK Comple
x
CARD11
TNFAIP3
LYN
TLR
MYD88
ID3
TCF3 PTEN
NFkB pathwayactivation
ITPKB
R
R
S
SR
(60)
(Dubois et al. CCR 2016)
Dubois et al. CCR 2016
Clinical parameter
Total (n= 357) MYD88 WT (n= 265) MYD88 L265P (n= 58) MYD88 non-L265P (n= 34)
Gender M/F, n 178/177 125/138 34/24 19/15
Age (years), median (range) 63 (17-93) 61 (17-90) 76 (44-90)*** 66 (37-93)
Subtype, n (%)
ABC 155 (43%) 93 (35%) 48 (83%)*** 14 (41%)
GCB 127 (36%) 109 (41%) 4 (7%)** 14 (41%)
PMBL 18 (5%) 18 (7%) 0 0
Other 36 (10%) 29 (11%) 2 (3%) 5 (15%)
NA 21 (6%) 16 (6%) 4 (7%) 1 (3%)
Adverse prognost ic factors, n (%)
Age > 60 years 214 (60%) 143 (54%) 46 (79%)** 25 (74%)*
Ann Arbor stage III-IV 218 (61%) 157 (59%) 37 (64%) 24 (71%)
LDH > Normal 223 (62%) 161 (61%) 39 (67%) 23 (68%)
Performance status ≥ 2 111 (31%) 52 (20%) 13 (22%) 4 (12%)
IPI, n (%)
0-2 157 (44%) 118 (45%) 21 (36%) 18 (53%)
3-5 192 (54%) 141 (53%) 34 (59%) 16 (47%)
No data 9 (3%) 6 (2%) 3 (5%) 0
Extranodal involvement at diagnosis
Stage IE 12 (3%) 10 (4%) 2 (3%) 0
Stage IIE 29 (8%) 21 (8%) 8 (14%) 0
Stage IV 167 (47%) 121 (46%) 31 (53%) 15 (44%)
Treatment, n (%)
R-chemotherapy 314 (88%) 238 (90%) 45 (78%) 31 (91%)
Chemotherapy without R 35 (10%) 23 (9%) 9 (16%) 3 (9%)
No data 8 (2%) 5 (2%) 3 (5%) 0
DLBCL at diagnosis
MYD88 mutated patients : clinical features
ABC MYD88 WT ABC MYD88 L265P ABC MYD88 non-L265P GCB MYD88 WT GCB MYD88 mutant
CD10+, n/total (%) 4/53 (8%) 4/36 (11%) 0/9 (0%) 45/75 (60%) 12/13 (92%)*
BCL6+, n/total (%) 34/50 (68%) 25/33 (76%) 6/8 (75%) 63/75 (84%) 12/12 (100%)
MUM1+, n/total (%) 46/51 (90%) 29/32 (91%) 8/8 (100%) 19/69 (28%) 3/12 (25%)
FOXP1+, n/total (%) 36/38 (95%) 15/15 (100%) 5/5 (100%) 31/53 (55%) 8/8 (100%)*
IgM+, n/total (%) 29/39 (74%) 13/15 (87%) 3/5 (60%) 16/54 (30%) 6/9 (67%)
BCL2 ≥ 50%, n/total (%) 40/48 (83%) 35/36 (97%)* 6/9 (67%) 48/72 (67%) 5/13 (38%)
MYC ≥ 40%, n/total (%) 21/33 (64%) 16/20 (80%) 2/3 (67%) 21/46 (46%) 6/8 (75%)
Double expressors, n/total (%) 17/28 (61%) 15/19 (79%) 1/3 (33%) 13/41 (32%) 2/8 (25%)
MYC ≥ 70%, n/total (%) 10/33 (30%) 12/20 (60%)* 0/3 (0%) 11/46 (24%) 2/8 (25%)
MYC rearrangement 1/38 (3%) 2/17 (12%) 0/4 (0%) 6/39 (15%) 0/8 (0%)
BCL6 rearrangement 16/38 (42%) 5/16 (31%) 2/4 (50%) 5/46 (11%) 1/8 (13%)
BCL2 rearrangement 0/39 (0%) 0/15 (0%) 0/5 (0%) 22/50 (44%) 5/8 (63%)
Dubois et al. CCR 2016
MYD88 mutated patients : clinical features
MYD88status
Relapse SNC No Relapse SNC
Mut (L265P)
9 (6) 79 (48)
wt 8 250
P = 0.02 / p = 0.03
MYD88 mutated patients and CNS relapse risk
Dubois et al. CCR 2016
11%
3%
Genetic Background related to MYD88 status
MYD88 Mutatedpatients
Ad
dit
ion
alG
en
etic
alte
rati
on
Molecular pattern predictive of Ibrutinib sensibility
Dubois et al. CCR 2016
R
R
S
Venn Diagram
N = 14
XPO1 mutations : WES of R/R DLBCL patients
* Mareschal et al. Genes Chromosomes and Cancer 2015
Tumor/ Matched Normal DNA (PBMC)
• WES: HiSeq2000 (SureSelect V5)• Gene expression profile (Affy 2.A)• CGH experiments (Agilent, 180K)
DLBCL, LNH03 GELA trial
Recurrent somatic mutations
XPO1
XPO1 / CRM1 gene
• Exportin-1 (XPO1) : member of the importin- superfamily of nuclear export receptors (karyopherins)
• mediates the translocation of RNAs and cellular regulatory proteins (p53, BRCA1, survivin, NPM, APC, …)
• The hydrophobic groove of XPO1 binds to the leucine-rich nuclear export signal (NES) domain of its cargo proteins
• XPO1 Mutations : CLL (< 5%); Cryptic XPO1-MLLT10 translocation in ALL
Dong et al. Nature 2009; Jeromin et al. Leukemia 2014; Bond et al. Blood 2014
Nucleus
Cytoplasm
XPO1
RAN-GDP
RAN-GTP XPO1
BRCA1
TP53
BRCA1
TP53
NES
NES
XPO1 mutation hot spot
Hydrophobic binding groove domain
C528
KPT Cargo NES
571
AA position 0 1071
XPO1
523 575 736
1715 18Exon 16
0%
10%
20%
30%
40%
50%
60%
70%
N = 81 N = 83 N = 33
N = 18
N = 14
N = 47N = 38
N = 19
N = 20
XPO1 mutations distribution in lymphoma subtypes
PMBL cHL
DLBCL MGZL
1% 1% 3%
39%64%
13% 16%
26%
0%
Jardin et al. Am J Hematol 2016
25%
CytoplasmNucleus
REV
GFP
XPO1/571
mChXPO1/571
mCh
KPT-330
E571G
E571K
TUMOR PLASMA
22% 9.4%
XPO1 E571K
Detection / quantification of the E571K mutation in circulating cell-free DNA by digital PCR
Digital PCR assay
Camus et al. Leukemia and lymphoma 2016
Diagnosis > Molecular residual disease (MRD)
Camus et al. Haematologica 2016
~ 25% LH are mutatedXPO1 E571K
Camus et al. Haematologica 2016
Camus et al. Haematologica 2016
Detection / quantification of the E571K mutation in circulating cell-free DNA
Lymphopanel 1.0 : Perspectives
• Successful Lymphopanel NGS using plasma-extracted circulating DNA *
• Real time Feasibility and integration in clinical trials / routine use
• Role in disease monitoring / theranostic value
• Design of Lymphopanel 2.0
* Bohers et al. Haematologica 2015; **Fontanilles et al. ASH 2015; ***Camus et al. Leukemia & lymphoma 2016
** ***
Caractérisation MolÉculaire des Lymphomes diffus à grandes cellules
B en rOutiNe
CAMELEON
Monthly Inter disciplinary Meeting dedicated to molecular characterisation of DLBCL
Mutations NFKB : MYD88, CD79B, TNFAIP3,PIM1, Epigénétique : EP300, CREBBP, Cycle/différenciation : PRDM1, MYCJAK/STAT/Immunité: SOCS1, CD58
MYC+, BCL2 + (DE) Hans : Non-GCB
55 y, DLBCL stade IV , elevated LDH, bone marrownegative> GAINED
ABC
?
83 yNasal , orbital involvement , RminiCHOP
BCL2+, MYC+ (DE)Hans = non-GCBImmunoblastesT(8;14)(q24;q32)
Mutations:-NFKB: MYD88, CD79B, PIM1-Cycle : MYC (x8)-CD58 (codon start)
CNVCDKN2A: del heterozygoteMYC del heterozygote (-8)
Score = 11.4, p(ABC) = 99.5%
!
Etude RT3
Real Time Tailored
TherapyMolecular characterization of DLBCL patients in Real Time to Tailor Therapeutic strategies
Molecular characterization of DLBCL patients in real time to tailor therapeutic strategies
RCHOP C2
RCHOP C1
RCHOP C3 + drug 1
RCHOP C3 + drug 2
RCHOP C4 + drug 1
GEP, NGS, IHC, FISH
TEP scan imaging
RCHOP C3
RCHOP C4 + drug 2
D1 D42D21
RCHOP C4
RCHOP C…
A challenge for the LYSA groupIn 2017
….
biomarkers
Multicentricdimension
Acknowledgments
• Members of the LYSA/LYSAP: Thierry Fest , Noel Milpied , Marianne Ochmann , François Lemonnier, Diane Damotte , Richard Delarue , Alexandra Traverse-Glehen , Corinne Haioun , Gilles Salles , Jean-Philippe Jais, Martin Figeac , Christiane Copie-Bergman , Thierry Jo Molina
• Members of the CALYM consortium
• Members of the U918 research unit: Elodie Bohers , Vincent Camus , Sylvain Mareschal , Sydney Dubois , Pierre-Julien Viailly , Philippe Bertrand , Catherine Maingonnat , Jean Michel Picquenot , Marie Cornic , Aspasia Stamatoullas , Christian Bastard , Hervé Tilly ,
• And Thank you for your attention …
UMR 918
BCR JAK/STAT PI3K/AKT TNF TLR
NF-Bactivation
Cell cycle, cell growth, apoptosis,glucose metabolism
Translocations, somatic mutations, cell of origin signature, microenvironnement…
Distinct pathways but cross talk and common final effects
