next generation sequencing and targeted genotyping as ... · february 2017, the 10th 23d bhs...

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.


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


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)


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)


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%)


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


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


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 / 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


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

next generation sequencing and targeted genotyping as ... · february 2017, the 10th 23d bhs...

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