Molecular basis of Chronic Myelo-Monocytic

Leukemia

Madrid, April 5th, 2013

Overview

• Disease definition & causes of death

• Genetic mutations

• Frequence

• Clonal architecture

• GM-CSF hypersensitivity

• Abnormal gene expression w/o mutation

• Prognostic significance of gene mutation / deregulation

• Impact on current disease management

CMMLa disease defined by one positive

criteria

Clonal (oligoclonal?) disease of the HSC with monocytosis

- Monocytosis (> 1 G/L) that persists for at least 3 months

- NOT a CML Lack of Philadelphia chromosome Ph1 or BCR-ABL- NOT a MLN-Eo Lack of PDGFR/FGFR rearrangement and eosinophilia - NOT an AML Blood and bone marrow blast cells < 20%

- In most cases : cell dysplasia, at least one cell line

Tefferi A, Vardiman JW. Leukemia. 2008;22:14-22.

Persistant monocytosis > 1 G/L

Why do these patients die?

The best recognizedprognostic factor is blast cell count

Diagnostic feature

Peripheral blood blasts

Bone marrow blasts

CMML1

< 5%

< 10%

CMML2

5-19%

10-19%

Patients die in < 3 years from

Progression to AML (< 25%)Consequences of cytopenias

a-defensins HNP1-3

CD14-/CD24+Immature granulocytes

CD14+/CD24-Monocytes

Lymphocytes

Macrophages

CSF1

« Monocytes » include a fraction of dysplastic granulocytes

endowed with immunosuppressive properties

Droin N et al, Blood. 2010;115:78-88

Persistant monocytosis > 1 G/L

Why do these patients die?

Progression to acute leukemia

Consequences of cytopenias

Immune system deregulation

Molecular abnormalities in CMML cells

1 - Non specific cytogenetic abnormalities* 30-40 %

2 - Gene mutations (5-20 / patient) 100 % > 30 recurrently mutated genes

3 - Deregulated expression of genes (down, up) 100 %

* Such E et al, Haematologica. 2011;96:375-83

Gene tested (n) mutated (n,%)

ASXL1 312 125 (40%)TET2 262 151 (58%)SRSF2 220 101 (46%)RUNX1 263 39 (15%)

NRAS 263 29 (11%)

CBL 264 27 (10%)

JAK2 263 21 (8%)KRAS 263 20 (8%)ZRSF2 189 15 (8%)

IDH2 229 13 (6%)

SF3B1 220 13 (6%)

U2AF35 220 11 (5%)

EZH2 173 8 (5%)

FLT3 264 8 (3%)

DNMT3A 227 5 (2%)NPM1 260 3 (1%)IDH1 229 1 (<1%)

KIT 228 1 (<1%)

TP53 202 2 (1%)

Gene mutationsThe 3 most frequently

mutated genes are

TET2

SRSF2

ASXL1

Studied in sorted peripheral blood

monocytes Itzykson R et al, J Clin Oncol, 2013, in press

Damm F et al, Leukemia, 2013, in press

TET2

SRSF2

ASXL1

TET2 mutations associate with SRSF2 mutations

2 CMML groups ?

TET2 +/- SRSF2

ASXL1

Itzykson R et al, J Clin Oncol, 2013, in press

Gene mutations in CMML

Three frequently mutated genes

TET2 +/- SRSF2

&

ASXL1

120 3624 48 60

0%20

%40

%10

0%60

%80

%

5147

4236

3123

1914

84

1At risk Time (months)

Ove

rall

Surv

ival

(%)

0-1

2

3

≥4

Number of mutated genes

5124

3613

175

9 2 1

MonthsC

umul

ativ

e P

roba

bilit

y of

Sur

viva

l

0 6 12 18 24 30 36 42 48 54 60

0.0

0.2

0.4

0.6

0.8

1.0

120 3624 48 60

0%20

%40

%10

0%60

%80

%

5147

4236

3123

1914

84

1At risk Time (months)

Ove

rall

Surv

ival

(%)

0-1

2

3

≥4

Number of mutated genes

5124

3613

175

9 2 1

MonthsC

umul

ativ

e P

roba

bilit

y of

Sur

viva

l

0 6 12 18 24 30 36 42 48 54 60

0.0

0.2

0.4

0.6

0.8

1.0

1 2 3 4 5 6 7

0%

20%

40%

60%

Number of mutated genes

% o

f pat

ient

s

0 1 2 3 4 5 6

8

43 47

51

19

4 1

The number of mutations in a survey of 19 candidate genes affects the prognostic

~70% cases

Single cell analysis of the mutations

in 4 bone marrow cell compartments

19 genes sequenced on sorted CD14+ blood cells

and

HSC/MPP/CMP/GMP sorted

Seeded at 1 cell per well

Cultured for 12 days with cytokines

Colonies picked up

In each colony, mutation specific PCR

Early clonal dominance specifies CMML

among myeloid neoplasms

0

20

40

60

80

100

# 53

7#

500

# 42

8#

497

# 65

4#

536

# 53

1#

518

# 50

7#

501

# 46

2#

524

# 74

3#

514

# 73

1#

662

# 51

6#

550

# 63

2#

495

# 49

8#

586

# 64

4#

759

# 73

6#

658

63 61 9 102

22 46 16 160

20 67 46 48 67 37 119

95 51 49 56 72 10 49 32 93 70 28

HSC : CD34+/CD38-/CD90+

Black 0 mutationYellow 1 mutationOrange 2 mutationsRed 3 mutations

Clonal architecture in CMML (1/3)

TET2 SRSF2 KRAS

• Early clonal dominance in HSC• Linear acquisition of mutations, starting with epigenetic and splice genes• Growth advantage to the more mutated cells with differentiation

Itzykson R et al, Blood. 2013 Jan 14.

Clonal architecture in CMML (2/3)Growth advantage to the more mutated cells

with differentiation

KRAS homozygous

KRAS wildtype

Exome sequencing in blood leukemic cells (16 variants :14 SNP, 2 indels)Single cell analysis in CD34+ cells

Linear accumulation of mutations

with some branching

through HR

TET2 heterozygousU2AF35BFSP2TRAPPC6BCTTNBP2MYLK

TET2 homozygousU2AF35BFSP2TRAPPC6BCTTNBP2MYLKKRAS heterozygousASAP1ADCY10ATP2C2CEP63HECW2SIPA1L2SMOC2

TET2 homozygousU2AF35BFSP2TRAPPC6BCTTNBP2MYLKKRAS heterozygousASAP1ADCY10ATP2C2CEP63HECW2SIPA1L2SMOC2SH2B3CTCF

Clone 1N =10

Clone 2N = 1

Clone 3N = 73

Clone 4N = 7

Clone 5N = 9

TET2 homozygousU2AF35BFSP2TRAPPC6BCTTNBP2MYLKKRAS homozygousASAP1ADCY10ATP2C2CEP63HECW2SIPA1L2SMOC2SH2B3CTCF

Clonal architecture in CMML (3/3)

Clonal architecture in CMML

Early clonal dominance

Mostly linear acquisition of mutations

Some branching due to mitotic recombinations

Growth advantage to the most mutated cells

Limited effect of current therapeutic approaches

13 TET2mut chronic myeloid malignancies

(8 JAK2V617F MPN, 5 MDS)

CD34+/CD38- P=0.006 CD34+/CD38+ P=0.08

Early dominance of TET2 mutations may participate to the differentiation bias

Early dominance of TET2 mutations may participate to the differentiation bias

Sh:SCR

Sh:TET2

Sh:SCR

Sh:TET2

CD34+/CD38- CD34+/CD38+

ns*4.0

3.0

2.0

1.0

0.0(CD

33+)

GPA

- / G

PA+

Cord Blood CD34+

Proposed model to distinguish CMML from other chronic myeloid neoplasms

CD34+/CD38- CD34+/CD38+

TET2 genemutation

Other chronic myeloid neoplasms

CMML

CD34-

Clon

al E

xpan

sion

Myeloid Differentiation

Additional mutations?

Different HSC of origin?

Stochastic?

The mutated gene SF3B1 and ring sideroblasts

The altered pathway Signaling genes and proliferative forms of CMML

The allele burden JAK2 in ET versus PV

The early / late amplificationTET2 and monocytosis

Four parameters that affect the phenotype

in chronic myeloid diseases

JMML is a RAS diseaseHypersensitivity of progenenitorsto GM-CSF

Germline 10% Neurofibromatosis (NF1) Noonan syndrome (PTPN11, CBL)

Somatic 90% Inactivating homozygous mutations in PTPN11, NF1, CBLActivating mutations in NRAS, or KRAS

Usually only one mutation / patient by WGS

Loh ML. Br J Haematol. 2011;152:677-87.

In CMML, hypersensitivity of GM-CSF is inconstant

CONTROLCMML

0

20

40

60

80

Num

ber

of c

olon

ies

Serum-free + SCFGM-CSF 10 ng/mL

Mutation in a signaling geneNRAS, JAK2, CBL

6/7 cases

3/13 cases

Itzykson R et al, unpublished

GM-CSF hypersensitivity

Heterogeneous (contrary to JMML)

Mostly linked to mutations in signaling genes

Peripheral blood

0

1

2

3

4 CtrlD/D

1-13 14-26 27-39 ≥40

Mon

ocyt

es (k

/mm

3 )

Weeks

n=11n=23

n=12n=23

n=12n=20

n=9n=9

*

**

Gr1-FITC

Mac

1-A

lexa

647

Ctrl D/D

44% 1%3% 51%

Ctrl D/D

1 cm

Spleen

In the mouse, deletion of tif1g in myeloid cells (Transcription Intermediary Factor 1 g)

induces a CMML phenotype

Aucagne R et al, J Clin Invest. 2011;121:2361-70

TIF1g gene promoter is methylated in 35-40% of CMML

35%of patients

-139GGGAGGAYGT TYGTGYGTA YGTGYGYGTGT YGTAAT YGTTT TT TTTTAAA YGYGYGA YGYG-139GGGAGGACGTCCGTGCGTACGTGCGCGTGCCGCAACCGCCCTCCTTCAAACGCGCGACGCG unconverted

non methylatedmethylated

Control TIF1g low TIF1g norm

al expression (Subset # 1) (Part of subset # 2)

Aucagne R et al, J Clin Invest. 2011;121:2361-70

Cycles0

20

40

60

80

100

120

5 7 15

Tif1g

mR

NA

leve

l

0

CtrlDec.

170 TIF1g

HSC7072

Befo

re tr

eatm

ent

Afte

r 5 cy

cles

GTGTG70TTTTTG

-92AAATGTGTGATGTGAGGGTGGGGGCGCCGCGTGCGTGTGTG C C C C

T60TTGTTGGC

-92AAATGTGTGATGTGAGGGTGGGGGTGTTGTGTGTGTGTGTG

Bef

ore

deci

tabi

neA

fter

deci

tabi

ne

TIF1g expression increase in CD14+ cellsas a biomarker of HMA efficacy

Aucagne R et al, J Clin Invest. 2011;121:2361-70

Months

Cum

ulat

ive

Pro

babi

lity

of S

urvi

val

0 6 12 18 24 30

0.0

0.2

0.4

0.6

0.8

1.0

17 15 11 7 2 0

18 14 11 9 3 1

low TIF1ghigh TIF1g

Low TIF1g

Normal TIF1g

1.0

0.8

0.6

0.4

0.2

0.0 0 6 12 18 24 30

Months

Cum

ulati

ve p

roba

blili

ty o

f sur

viva

l

TIF1g expression level does not predict decitabine efficacy

0

50

100

150

200

250

300

mRN

A ex

pres

sion

(rel

ative

)

Cont

rol

Subs

et #

1

Subs

et #

2

Braun et al, Blood. 2011;118:3824-31.

Months

Cum

ulat

ive

Pro

babi

lity

of S

urvi

val

0 6 12 18 24 30

0.0

0.2

0.4

0.6

0.8

1.0

17 16 13 12 5 0

18 13 9 4 1

low MYBhigh MYB

Months

Cum

ulat

ive

Pro

babi

lity

of S

urvi

val

0 6 12 18 24 30

0.0

0.2

0.4

0.6

0.8

1.0

16 15 14 10 2 0

19 14 8 6 3 1

low CJUNhigh CJUN

P = 0.06

Cum

ulati

ve p

roba

blili

ty o

f sur

viva

l 1.0

0.8

0.6

0.4

0.2

0.0

Low

High

CJUN 1.0

0.8

0.6

0.4

0.2

0.0

CMYB

Low

HighP = 0.01

0 6 12 18 24 30 0 6 12 18 24 30 Months Months

Elevated CJUN and CMYB levels are negative prognostic factors

Braun et al, Blood. 2011;118:3824-31.

CMML: deregulated gene expression

Down

P15/INK4b – 50%

TIF1 g – 40%

miR-150

Up

cJUN

cMYB

Prognostic impactNo prognostic impact

wildtype

mutated

120 3624 48 60120 3624 48 60

Ove

rall

Surv

ival

(%)

100

80

60

40

20

0

187125

13468

8429

5010

196

51

187125

13468

8429

5010

196

51

187125

12656

7723

479

186

51

187125

12656

7723

479

186

51

120 3624 48 60120 3624 48 60

AM

L-fr

ee S

urvi

val (

%)

100

80

60

40

20

0

wildtype

mutated

Univariate analysisASXL1 : P < 0.0001

alsoSRSF2 : P = 0.03CBL : P = 0.003 IDH2 : P = 0.03

ASXL1 mutations have a negative prognostic impact

Itzykson R et al, J Clin Oncol, 2013, in press

120 3624 48 60

0%20

%40

%10

0%60

%80

%

5657

4630

2815

127

33

At risk Time (months)

Ove

rall

Surv

ival

(%)

Validation set (MLL)

52 24 8 2

low int high

Months

Cum

ulat

ive

Pro

babi

lity

of S

urvi

val

0 6 12 18 24 30 36 42 48 54 60

0.0

0.2

0.4

0.6

0.8

1.0

11 1

120 3624 48 60

0%20

%40

%10

0%60

%80

%

132106

10066

6736

4315

187

42

At risk Time (months)

Ove

rall

Surv

ival

(%)

low int high

Training set (GFM)

74 36 10 2

Months

Cum

ulat

ive

Pro

babi

lity

of S

urvi

val

0 6 12 18 24 30 36 42 48 54 60

0.0

0.2

0.4

0.6

0.8

1.0

A simplified prognostic score that includes ASXL1 mutations

Training (GFM) : 312 Validation (MLL) :165

Low

Int

High

Low

Int

High

Hyperleucocytosis (>15)Age (>65)

AnemiaThrombocytopenia (<100)

ASXL1 mutation

Low < 4Intermediate 4-8

High >8

Absence00000

Presence32222

Itzykson R et al, J Clin Oncol, 2013, in press

To refine the diagnosis

BCR-ABLPDGFR/FGFR

KIT

To capture prognostic informations

ASXL1

Molecular characterization of CMMLin clinical practice

Which molecular analyses ?

Monocytes > 1 G/L

Yes (MLN-Eo)Imatinib

Eliminate BCR-ABL

OthersASXL1, Complex

Karyotype

EosinophiliaPDGFR / FGFR

Mast cellsKIT

Yes (SM)TKI?

YesHSCT?

Which therapeutic proposal?

Leucocyte count

< 13 G/L > 13 G/L

0 ou 1 > 1

Poor prognostic

factors

HSCTHMA

HydroxyureaBest supportive

care

IPSS

Yes No

HSCTHMA

1 - CMML : a disease of the HSC in which gene mutations accumulate, mostly linearly, and the most mutated cells

accumulate with differentiation.

2 - High number of genetic abnormalities with mutations inTET2, SRSF2 and ASXL1 being the most prominent.

3 - Mutations in signaling genes and early clonal dominance of TET2 mutations favor GM amplification.

4 – Treatment of poor prognostic CMML: ABMT (rarely feasible) and hypomethylating agents

5 – Molecular informations may better guide the therapeutic choice in coming years, with ASXL1 mutations affecting

outcome

Gustave Roussy, Villejuif, France

Raphael Itzykson

Nathalie Droin

Hana Raslova

Margot MorabitoFrançois DelhommeauPhilippe RameauCédric OréarGuillaume Meurice

William VainchenkerOlivier Bernard

Marseille, France

Daniel BirnbaumVéronique Gelsi-Boyer

Groupe Francophone des Myélodysplasies

P. FenauxAnd all GFM clinical teams

Lille, FranceAline Renneville

Claude Preudhomme

Cochin, FranceOlivier Kosmider

Michaela Fontenay

Southampton, GBClaire Hidalgo-Curtis

Nicholas Cross

Dresden, Munich, Germany Uwe Platzbecker

Thorsten HaferlachSuzanne Schnittger

red blood cell

Haematopoietic stem cell

Lympho-myeloid progenitor cell

lymphoid progenitor cellMEP

BFU-E

CFU-E

CFU-MK

CFU-GM

CFU-MCFU-G

platelet granulocyteT cell B cell NK

erythro

MGK

CFU-BCFU-T

monocyte