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Nuovi markers bio-molecolari nelle Sindromi Linfoproliferative

La Leucemia Acuta Linfoblastica

Genova, 11 Novembre 2014 Alterazioni molecolari in onco-ematologia:

dalla diagnosi allo studio della Malattia Residua Minima (MRD)

Estimated frequency of specific genotypes in childhood ALL

Hyperdiploid >50, 25,0%

TEL-AML1, 20,0%

E2A-PBX1, 4,0% MLL-AF4, 2,0%

BCR-ABL1, 2,0% BCR-ABL1-like; 9.0% CRLF2, 4,0%

IKZF1, 12,0%

ERG, 3,0%

dic(9;20), 2,0% iAMP21, 2,0%

E2A-HLF, 0,5% Hypodiploid; 0.5% Other MLL-R, 4,0%

Other BCP-ALL, 4,5%

TAL1, 7,0%

TLX3, 2,3% LYL1, 1,4%

TLX1, 3,0% MLL-ENL, 3,0%

ETP; 2.0% Others T-ALL; 1.7%

Modified from Pui et al, Blood. 2012;120:1165

BCP-ALL

Molecular genetic subsets of ALL are age-dependent

<1 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Annual incidence rate of childhood ALL

per 106 population

t(9;22) or BCR/ABL: 33% (SE 9%), N= 27 t(4;11) or MLL/AF4: 30% (SE 10%), N= 23

t(1;19) or E2A/PBX1: 5-J.-EFS 93% (SE 6%), N= 15 t(12;21) orTEL/AML1: 95% (SE 3%), N= 44 >50 chromosomes (hyperdipl.): 86% (SE 3%), N=198 normal karyotype: 78% (SE 3%), N=244

years 0 1 2 3 4 5 6 7 8 9 10 11 12

Prognosis of ALL according to genetics ALL-BFM 90

ALL Study (year) 70 76 79 81 83 86 90 95 2000 2009

WBC x x x

Total leukemic cell mass (RF) x x x x

Age x x x Sex x CNS x x x x Thymic tumor x x x

Immunophenotype (T vs non-T) sP sP x x x x

No CR to phase Ia x x x x x x x

Prednisone response day 8 x x x x x

MRD x x

t(9;22) BCR-ABL x x x EsPhALL

t(4;11) MLL-AF4 x x x t(12;21) ETV6-RUNX1 x Ploidy x

Childhood ALL trials: criteria for risk group stratification

Childhood ALL: The Treatment Dilemma

Treatment intensity (number of drugs combined, dose intensity)

Status at the end of the 1990's

The questions:

•  How to identify those children (20-25%) who ultimately relapse with disease that is highly refractory to current therapy.

•  How to identify those children (25%, or more?) who are likely „over-treated“ and may well be cured using less intensive regimens resulting in fewer toxicities and long term side effects.

Improved overall survival in childhood acute lymphoblastic leukemia

Hunger SP, Pediatr Blood Cancer 2005;45(7):876–80

MRD as “surrogate” marker to assess heterogeneity in response to treatment

MRD detection in Acute Lymphoblastic Leukemia:

Fusion transcripts resulting from chromosomal translocations Immunoglobulin (IG) and T cell Receptor (TR) gene rearrangements Multiparametric Flow cytometry

Variability of the V(D)J region of IG/TR gene rearrangements as patient and clone-specific target for MRD detection

VH 5 ' 3 ' JH

VH primer ASO primer/probe

Junctional (“N”) regions

JH primer

Patient Marker Junction Junctional sequence Sensitivity

AC15 Vd2-Dd3 -20 / 9 /-13 TGAAGGGTCTT TCGGGCCCC CACAGTGCTAC 4AN40 Vd2-Dd3 -5 /14 / 0 TGAAGGGTCTTACTACTGTGCCTGTG CACCTGACGTACTT ACTGGGGGATACGCACAGTGCTAC 4AX21 Vd2-Dd3 -1 / 2 / 0 TGAAGGGTCTTACTACTGTGCCTGTGACAC GA ACTGGGGGATACGCACAGTGCTAC 4AA34 Vd2-Dd3 -3 /14 / 0 TGAAGGGTCTTACTACTGTGCCTGTGAC CTTTCACCCTTTTT ACTGGGGGATACGCACAGTGCTAC 5

Initial semi-quantitative ‘dot blot’ analysis by 32P-labelled ASO probes

Germline fluorescent probe

Forward junctional primer

Reverse primer

R Q V N J

MRD detection by monitoring Ig/TcR rerrangements

10-1 10-2 10-3 10-4 PB undil

Advanced RQ-PCR MRD detection in childhood ALL in the AIEOP-BFM 2000 study

•  Germline TaqMan probes;

•  Design of specific primers for each patient specific target;

•  Sensitivity testing of all the primers/probe combinations; •  Sensitivity testing by modifying annealing temperature;

•  MRD detection experiment;

•  Parallel albumin analysis on each sample;

•  Final data calculation (normalization).

It strongly depends on the therapeutic time point assessed:

•  Early time points •  the applicability of MRD could be higher as much as earlier is

the prognostic time point.

•  Late time points •  the persistence of residual blasts beyond 4 to 6 months or the

re-emergence of residual disease, even at the level of 1x10-4, predicts clinical relapse. However, the clinical usefulness of late MRD determination is limited.

Clinical impact of MRD

I-BFM-SG ALL-MRD-Study: Update Outcome by MRD detection levels at w5 (tp 1) and w12 (tp 2)

MRD at tp. 1+2 neg.: 0.98, SE=.02 (N= 55, 1 event) MRD pos but < 10-3 at tp. 2: 0.76, SE=.06 (N= 55, 14 events) MRD at tp. 1+2 >=10-3: 0.16, SE=.08 (N= 19, 16 events)

p: 1-2: .0003; 1-3: .0001; 2-3: .0001 mrd

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4 5 6 7 8 9 10 11

Basis for risk stratification in trial ALL-BFM 2000

Low risk group

Intermediate risk group

High risk group

MR - 1

MR - 2

H R 1'

H R 2'

H R 3'

BM sampling

* presymptomatic cranial irradiation (18[24] Gy for CNS pos. pts only) # selected indications for allo-BMT (in all strata of HR) ° SR: 2 molecular marker with a sensitivity of =<10-4 available (obligatory)

MRD Timepoints

1 2 (3) (4) (5)

SR°: •  no HR criteria •  MRD neg. at tps. 1+2

HR: MRD level at tp. 2 >=10-3 HR:

PRED-PR t(9;22) t(4;11) NR d33

12 Gy* only T-ALL

SR - 2

SR - 1

B M T#

III 12 Gy* only T-ALL

30/7/2000

MR: •  no HR criteria •  no SR-criteria

III III III

II 18Gy*

II AIEOP

104 W. 52 + IA-D: Protocol I, Phase A with DEXA IA-P: Protocol I, Phase A with PRED

10 weeks interim maintenance with 6-MP / MTX

H R 1'

H R 2'

H R 3'

HR - 1

HR - 2

H R 1'

H R 2'

H R 3'

6-MP/MTX 4 Wks.

MRD as surrogate marker for risk-based

patient stratification

AIEOP-BFM ALL 2000 protocol

MR: n = 1495

n=1495

MRD-MR n = 1708 (51%)

HR: n = 270

MRD-HR n = 270 (8%)

MRD classification feasible n = 3265 (77%)

Final risk group assignment in AIEOP-BFM ALL 2000 with and without MRD results (n=4239)

MRD classification not feasible n = 974 (23%)

SR: n = 1241

n=1241

MRD-SR n = 1287 (40%)

n=213 n=46

n = 424

n = 843 n = 131

n = 2338 n = 660 Final clinical risk groups (all eligible pts = 4239)

29% 55% 16%

AIEOP-BFM ALL 2000 protocol: Outcome results

311 deaths 89.4%(0.7)5 yrs Prob.

SURVIVAL524 events 79.4%(1.1)

5 yrs Prob.

AIEOP-BFM 2000

4239 patients

CORS/Hannover - Apr 2006

YEARS FROM DIAGNOSIS0 1 2 3 4 5

1241N. pts

50N. events

91.4%(1.5)5 yrs EFS

SR 20002338

N. pts

N. events

78.8%(1.6)

5 yrs EFS

MR 2000660

N. pts

N. events

59.5%(3.2)

5 yrs EFS

HR 2000

AIEOP-BFM 2000by final risk

4239 patients

by Final Risk n=4239

All BCP and T-ALL n=4239

1290N. pts

52N. events

91.5%(1.5)5 yrs EFS

SR1705

N. pts

N. events

75.7%(2.3)

5 yrs EFS

N. pts

N. events

36.8%(6.6)

5 yrs EFS

AIEOP-BFM 2000by MRD

3265 patients

by MRD n=3265

Definition of risk groups in ALL-BFM 95: SR: PRED-GR; WBC <20,000, and age 2-5y MR: PRED-GR; WBC >= 20,000, or age <1y, or >= 6y HR: PRED-PR, or induction failure, or Ph+ ALL

2552 15% 53% 32% All

215 (100%) 61% 29% 9% HR

1306 (100%) 16% 55% 29% MR

1031 (100%) 5% 55% 40% SR MRD risk criteria

ALL 2000

All HR MR SR

ALL-BFM 95 risk criteria

MRD risk groups of ALL-AIEOP BFM 2000 in comparison to risk groups according to ALL-BFM 95 criteria

(eligible patients classifiable by MRD)

Relapses in BCP-ALL by MRD risk groups AIEOP-BFM ALL 2000

1348 61 6.0%(0.8) 7.2%(1.2)1647 266 21.0%(1.2) 22.3%(1.4)189 60 34.9%(3.8) 38.5%(5.0)

SRIRHR

N.pts N. rel. 5-yrs CI 7-yrs CI

p-value<0.001

Years from diagnosis0 1 2 3 4 5 6 7

Conter V et al Blood 2010; 115: 3206

Relapses in T-ALL by MRD risk groups AIEOP-BFM ALL 2000

75 5 7.6%(3.3)292 51 17.6%(2.2)97 36 37.7%(5.0)

SRIRHR

N.pts N. rel. 7-yrs CI

p-value: overall<0.001; SR vs MR=0.02; MR vs HR<0.001

Years from diagnosis0 1 2 3 4 5 6 7

Schrappe et al. Blood 2011; 118: 2077

401N. pts

13N. events

93.5%(1.9)5 yrs EFS

N. pts

N. events

67.5%(8.2)

5 yrs EFS

N. pts

N. events

58.3%(18.6)

5 yrs EFS

AIEOP-BFM 2000TEL/AML pos - by MRD

673 patients

MRD-SR 1.0, SE=.00 (N= 6, no event)MRD-MR .50, SE=.15 (N=16, 6 events)MRD-HR .23, SE=.12 (N=18, 11 events)

Log-Rank p = .016

0.00.10.20.30.40.50.60.70.80.91.0

0 1 2 3 4

Pts enrolledSep/Jul 00–Oct 04(Status April 05)

AIEOP + ALL-BFM 2000, EFS MRD Risk Groups, BCR/ABL pos

MRD results in genetically defined subgroups

BCR/ABL pos BCP-ALL (Pre-TKI)

t(12;21) n=673 pts

Summary of MRD results in childhood ALL

•  The long term EFS results of the retrospective MRD study confirmed the prognostic value of MRD monitoring at two early time points.

•  The cooperative AIEOP-BFM ALL2000 protocol was the first large multicentric trial using early MRD monitoring as a major prognostic factor for risk stratification in childhood ALL.

–  feasibility of early MRD monitoring in a large proportion of patients (~80%)

–  MRD confirmed its high prognostic value in all the biological subgroups of patients.

–  Definition of a large SR group with excellent outcome

•  MRD-SR MRD negative at TP 1 and TP 2 with at least one, preferably more than one PCR-MRD marker with a sensitivity of at least 10-4

•  MRD-MR MRD positive at TP 1 and/or TP 2 and MRD at TP 2 <10-3 with at least one PCR-MRD marker

‚Slow early responders‘ (SER) MRD >10-3 at TP 1 and still positive at TP 2 by PCR-MRD

•  MRD-HR PCR-MRD >10-3 at TP 2 FCM-MRD >10% at d15 Hypodiploidy <44

•  PCR-MRD not stratified : FCM-MRD at d15: <0,1% SR

>0,1% and <10% MR

AIEOP-BFM ALL 2009: new MRD Risk Criteria

MRD stratification PCR : 94.0% FCM : 5.6% Overall: 99.6%

N=1290, 52 events

AIEOP-BFM ALL2000 Outcome by number of markers

Pts enrolled Sep/Jul 00–Sept 05 (Status April 06)

0.0 0.1

0.2 0.3

0.4 0.5 0.6 0.7

0.8 0.9 1.0

0 1 2 3 4 5 6

.91, SE=.01

MRD-SR 2000 (at least 2 sensitive markers,

TP1 + TP2 negative)

.96, SE=.01

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4 5 6

N=300, 11 events

MRD-MR 2000 (only 1 sensitive marker,

TP1 + TP2 negative)

Outcome of Childhood ALL by Flow Cytometric Measurement of Residual Disease on Day 15 Bone Marrow

Basso G. JCO 2009

TP1 LOW+, TP2 NEG 0.83, SE=0.03 (N=305, 38 events) TP1 LOW+, TP2 POS 0.79, SE=0.05 (N= 97, 16 events) TP1 HIGH+, TP2 NEG 0.73, SE=0.05 (N=106, 28 events) TP1 HIGH+, TP2 POS 0.40, SE=0.07 (N= 89, 40 events)

Log-Rank p = <.0001

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4 5 6 7 8

AIEOP + ALL-BFM 2000 EFS (6 years) BCP-ALL, non-HR

Patient enrollment AIEOP: 09/00 – 07/06 BFM: 07/00 – 06/06 (Status June 08)

SER, slow early responers

DI >1.6 .86, SE=.05 (N=59, 8 events) DI >1.16-<1.6 .87, SE=.01 (N=769, 99 events) DI >.81 -<1.16 .77, SE=.01 (N=3405, 680 events) DI <.81 .49, SE=.10 (N=24, 12 events)

ALL-BFM 90-2000 Age > 1 year EFS (5 years) DNA index

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

DNA Index<0.8 or < 44 chromosomes

DNA Index ≥1.16 or >50 chromosomes

IB M IAD

T/non-‐HR

pB#/non-‐HR M

AIEOP-BFM ALL 2009 pCRT 12 Gy if age > 2 yrs* / in selected subgroups no CRT + 6x IT MTX

Immunology unknown or pB-‐ALL + TEL/AML1 neg + FCM-‐MRD d15 >0.1%

TEL/AML1 pos and/or FCM-‐MRD d15 <0.1%

Prot. IA with 2 DNR doses (day 8 and 15)

Prot. IA with 4 DNR doses (day 8, 15, 22 and 29)

# or immunophenotype unknown * in paSents with CNS disease (CNS 3) tCRT with 12 Gy/18 Gy (dose age-‐adapted))

PEG-‐L-‐ASP 2500 IU/m2 every 2 weeks, over 20 weeks in total

PEG-‐L-‐ASP 4 x 2500 IU/m2 over 4 weeks

53 104 w 12 1 22 31 43 20 10

T-‐ALL

pB-‐ALL#

HR 1‘

HR 2‘

HR 3‘ III III III

pCRT 12 Gy if age > 2 yrs* / in selected subgroups no CRT + 6x IT MTX

„NRd33 only“ FCM d15 >10%

„MRD-‐MR SER“ „MRD-‐HR only“

DNX-‐FLA + SCT

IA’ IA

European Study Group on MRD detection in ALL (ex ‘ESG-MRD-ALL’; 57 laboratories in 23 countries)

− Standardization − Guidelines − Quality Control Rounds − Education − Developments

EuroClonality NGS consortium

A. Langerak / J. van Dongen (Rdam)

P. Groenen (Nijmegen)

M. Brüggemann / C. Pott (Kiel)

M. Hummel (Berlin)

M. Catherwood (Belfast)

F. Davi (Paris)

E. Macintyre (Paris)

R. Garcia Sanz (Salamanca)

K. Stamatopoulos (Thessaloniki)

N. Darzentas (Brno)

G. Cazzaniga (Monza) J.Hancock (Bristol) J.Trka (Prague) M.Ladetto (Turin)

M. Lefranc / V. Giudicelli (Montpellier) Coordination : A.W. Langerak

3. RQ-PCR design and sensitivity testing

4. MRD analysis of follow-up samples

2. MRD PCR target identification

1. DNA preparation

a. PCR-heteroduplex analysis

b. Sequencing of clonal rearrangements

c. Sequence interpretation

d. Selection of MRD-PCR targets

a. BM sampling at diagnosis (≥ 5ml)

b. MNC-density gradient separation (1x107 cells)

c. Genomic DNA extraction (≥ 10µg)

a. Design of allele-specific oligonucleotide primers

b. RQ-PCR analysis of dilution series of diagnostic sample

c. RQ-PCR data interpretation

a. RQ-PCR analysis of follow-up samples (control gene)

b. RQ-PCR analysis of follow-up samples (Ig/TCR targets)

d. Calculation of MRD level

( 2-3 days )

( 1-2 weeks )

3. RQ-PCR design and sensitivity testing

4. MRD analysis of follow-up samples

2. MRD PCR target identification

1. DNA preparation

a. PCR-heteroduplex analysis

b. Sequencing of clonal rearrangements

c. Sequence interpretation

d. Selection of MRD-PCR targets

a. BM sampling at diagnosis (≥ 5ml)

b. MNC-density gradient separation (1x107 cells)

c. Genomic DNA extraction (≥ 10µg)

a. Design of allele-specific oligonucleotide primers

b. RQ-PCR analysis of dilution series of diagnostic sample

a. RQ-PCR analysis of follow-up samples (control gene)

b. RQ-PCR analysis of follow-up samples (Ig/TCR targets)

d. Calculation of MRD level

( 2-3 days )

( 1-2 weeks )

Flow diagram of RQ-PCR MRD diagnostics :

IG/TR sequencing

Bioinformatic analysis (data interpretation and

calculation of MRD levels)

Adult- ALL , Raff et al., Blood 2007

Early detection of relapse

Pediatric- ALL , Paganin et al., JCO 2014

Early detection of relapse

Major points still to be addressed: •  treatment context;

•  prospective validation;

• multivariate analysis.

How to integrate new novel genetic markers with MRD-defined subgroups?

Gene Expression Profiling SNParrays (copy number analysis)

Next Generation Sequencing

Novel genomic alterations with prognostic or therapeutic relevance

Gene/Subgroup Alteration Frequency Function Prognostic or therapeutic relevance

PAX5 Focal deletions, translocations, sequence mutations 30% of BCP-ALL Transcription factor required for B-

lymphoid development not related to outcome

IKZF1 Focal deletions or sequence mutations

15% of pediatric BCP-ALL cases Transcription factor required for

lymphoid development poor outcome 70-80% BCR-ABL1 ALL 35% of high-risk BCR-

ABL1negative ALL

JAK1/2

Pseudokinase and kinase domain mutations 20%-35% Down syndrome ALL

Constitutive JAK-STAT activation May be responsive to JAK inhibitors

10% high-riskBCR-ABL1negative ALL

CRLF2 IGH@-CRLF2 or P2RY8-CRLF2, resulting in overexpression

5%-15% pediatric and adult BCP-ALL, Associated with mutant JAK in up

to 50% of cases poor outcome >50% Down syndrome-ALL,

15% pediatric high-risk ALL Associated with IKZF1 alteration and JAK mutations

IL7RA Small ins/del and sequence mutations

10% pediatric T-ALL; <1% in BCP-ALL

Constitutive activation of the IL7 receptor; associated to CRLF2 rearrangements in BCP-ALL.

prognosis not known; may be responsive to JAK/STAT

inhibitors

SH2B3 Deletion and sequence mutations very rare in BCP-ALL, associated to BCR-ABL1-like

negative regulator of JAK2 signaling

May be responsive to JAK inhibitors

CREBBP Focal deletion and sequence mutations

20% of relapsed BCP-ALL; commonly acquired at relapse

Mutations result in impaired histone acetylation and

transcriptional regulation

Associated with glucocorticoid resistance

TP53 Deletions and sequence mutations

3% of BCP-ALL, commonly acquired at relapse

Loss of function or dominant negative poor outcome

BCR-ABL1-like GEP/CNA similar to BCR-ABL1 10% of BCP-ALL Activating cytokine receptor and kinase signaling

May be responsive to TKI or to JAK inhibitors

ETP T-ALL/myeloid immature immunophenotype 6-12% of T-ALL stem cell disease May be responsive to high-dose

cytarabine or epigenetic therapy

Adapted from ref.1. BCP-ALL= B-cell precursor Acute Lymphoblastic Leukemia, GEP=Gene Expression Profile; CNA=Copy Number Abnormalities; TKI=Tyrosine Kinase Inhibitor.

Mullighan C, Nature 2008;453:110

Mullighan C, N Engl J Med 2009;360:470

Impact of Ikaros deletions in childhood ALL

Validation Cohort, BCP, Ph- ALL (N=237) Validation Cohort, BCP ALL (N=258) Original Cohort (N=221)

DCOG protocol. Waanders E, Leukemia 2011;25:254

MRD / IKZF1 based stratification in non-HR

MRD-IR by IKZF1 status

MRD-LR/IR and IKZF1 wt

MRD-LR/IR and IKZF1 del

IKZF1 wt

IKZF1 mut

DCOG-ALL-11 treatment protocol

M IA,IB IV MP/MTX

M MP/MTX+Dex/VCR

M HR1 MP/MTX

Risk group stratification: - MRD - prednisone response - CR day 33 - t(4;11)

HR2 HR3 HR1 HR2 HR3

Down/TELAML1: no anthr

IKZFdel: anthracycl

Other: anthracycl

MP/MTX+Dex/VCR

MP/MTX+Dex/VCR MP/MTX

Courtesy of Rob Pieters, DCOG

Treatment adapted on genomic lesions

Palmi C, Haematologica 2013;98:1226

overall

Intermediate Risk

n % n %SR 109 30,6% 8 2,2%IR 222 62,4% 42 11,8%HR 25 7,0% 4 1,1%

No YesIKZF1 deletionsFinal

stratification

Relapses in IKZF1 deleted: 0/8 SR vs 10/42 IR (23.8%) and 3/4 HR

EFS and CIR by CRLF2 expression in BCP-ALL Intermediate risk patients

P=0.04 P<0.0001

P=0.24(solo rel) P=0.03(solo rel)

214N. pts

39N. rel.

17.6%(2.6)5 yrs Cum. Incidence

N. pts

N. rel.

61.1%(12.9)

5 yrs Cum. Incidence

pB AIEOP 2000Intermediate Risk - by CRLF2 deletion

229 patients

CORS - Nov 2010

. Incid

10N. pts

1N. events

90%(9.5)5 yrs EFS

N. pts

N. events

37.5%(16.1)

5 yrs EFS

pB AIEOP 2000CRLF2>=20 - by CRLF2 deletion

20 patients

CORS - Nov 2010

A new genomic subgroup : ‘Ph-like ALL’

Prognostic impact of Ph-like ALL

Mullighan C et al 2009; Loh M et al Blood 2013;121: 485-488

Den Boer ML et al 2009;

Cazzaniga G, ASH 2013 n. 353, Monday 9, 11:30 AM

p-value<0.001

0 1 2 3 4 5

BCP-ALL Total

Ph-like clustering

Case No. 235 11 (4.7%)

Age (mean) 5.7 10.3

WBC count 35,389 157,506

4-year EFS 83.20% 66.70%

Kiyokawa N, ASH 2013 n. 352, Monday 9, 11:15 AM

Kinase alterations in US Ph-like (detectable by multiplex RT-PCR)

Adapted from Mullighan, ASH 2013

Gene Drug n° of partners n° of cases partner genes

ABL1 Dasatinib 6 13 ETV6, NUP214, RCSD1, ZMIZ1, RANBP2, SNX2

ABL2 Dasatinib 3 7 RCSD1, ZC3HAV1, PAG1

CSF1R Dasatinib 1 4 SSBP2

PDGFRB Dasatinib 3 8 EBF1, ZEB2, TNIPI

CRLF2 JAK2 inhibitor 2 IGH, P2RY8

JAK2 JAK2 inhibitor 10 19 BCR, ETV6, PAX5, SSBP2, EBF1, others

EPOR JAK2 inhibitor 2 9 IGH, IGK

EBF1-PDGFRB (Ph-like) responds to TKI

Weston BW et al, J Clin Oncol. 2013;31:e413-6

Lengline E et al, Haematologica. 2013;98:e146-8

Conclusions

•  Childhood ALL has become a paradigm of success in modern oncology. Still treatment failure rate is 15-20%.

•  Response (MRD) oriented risk stratification cannot yet be fully replaced by genetic markers at time of diagnosis.

•  New risk groups are being defined but their characterization is still not standardized.

•  Need to minimize long-term health complications in the large population of leukemia survivors.

•  Need for new drugs, new statistical methods, and transnational collaborations across large and well-characterized patient populations.

Acknowledgments Lilia Corral Simona Songia Tiziana Villa Eugenia Mella Valentina Carrino Giuseppe Gaipa Oscar Maglia Simona Sala Laura Levati Vincenzo Rossi Andrea Biondi Valentino Conter Giuseppe Masera Daniela Silvestri Maria Grazia Valsecchi Fondazione Tettamanti

Emanuela Giarin

Maddalena Paganin Katia Polato

Barbara Buldini

Barbara Michelotto

Giuseppe Basso

Clinica Ped. Univ. Padova

Grants by Fondazione Cariplo, AIRC and Comitato M.L.Verga

BFM Germany BFM Austria BFM Suisse

AIEOP Center

•  Immunophenotyping •  Cytomorphology (diagnosis) •  Evaluation of response (d8) •  Preparation of DNA (d0, d33, w12) •  Banking of Cells and DNA •  MRD of local patients

Padova (centralized)

If material is insufficient: phone call for repuncture

Molecular genetics: •  Translocations (RNA) •  MRD:

•  Identification of MRD targets •  Testing of specifity and sensitivity

•  MRD quantification of follow up time points

•  Interpretation of results

•  DNA of diagnosis •  DNA of follow up time points

Genetics and MRD result for final risk group assignment

Flow diagram of diagnostic management

Definition of MRD in AIEOP-BFM ALL 2000

•  SR: MRD negative on day 33 (post-induction,TP1), and at day 78 (before "Prot. M" = TP2), if measured with at least 2 markers with a sensitivity of at least 10-4.

•  MR: no "SR-MRD" or "HR-MRD" criteria are met.

•  HR: MRD at time point 2 (d 78) is positive at ≥10-3.

How to integrate MRD in the design of the new childhood ALL

treatment protocol ?

1) FCM-MRD @d15 >10% ! HR 2) Stratification of patients who are not stratifiable by

PCR-MRD (and without classical HR criteria):

FCM-MRD @d15 <0,1% ! SR >0,1% and <10% ! MR

-> Stratification in >95% of patients

Role of FCM-MRD d15 for the stratification in AIEOP-BFM 2009

How to integrate MRD in the design of the new ALL treatment protocol ?

•  MRD detection, currently the best available individual

risk assessment method, was available for stratification in almost all patients (combined use of PCR and FCM)

•  R1: Treatment reduction for low-risk pts but controlled by MRD

•  R2: Targeted and monitored intensification for all pts with intermediate relapse risk

•  R3: Early targeted and monitored intensification in high risk pts

Perspectives

•  MRD is generally used in ALL to guide post induction or post consolidation therapy.

•  Whilst it is unlikely that MRD studies could be completely replaced by novel risk factors, the combined use of MRD evaluation and the newly available genomic information on leukaemia presenting features, like Ikaros or CRLF2 gene deletions will further improve risk assignment of ALL patients.

•  However, clinically relevant improvements in ALL treatment can only result if MRD-based stratification is paralleled by the finding of the appropriate therapeutic strategy.

Monitoraggio molecolare della malattia minima residua nelle leucemie acute pediatriche:

standards o ricerca ?

Prerequisites of a reliable technique to detect MRD

a. Sensitivity of at least 10-4, although it depends on the clinical question;

b. Specificity, to prevent false-positive results c. being quantifiable within a large dynamic range; d. stability over-time of leukaemia-specific markers, to prevent false-

negative results, particularly in long-term studies; e. reproducibility between laboratories (essential for multicenter

trials); f. careful standardization and quality control checks; g. rapid availability of results (in time for clinical usefulness)

Problems and pitfalls of MRD-PCR detection via Ig/TCR genes

1.  Time consuming, labor intensive and expensive •  Target identification, selection and testing: 3-4 weeks •  RQ-PCR analysis of follow-up samples:1-2 weeks

2. Extensive knowledge and experience needed: •  Structure of Ig/TCR genes and rearrangement processes •  Ig/TCR gene rearrangement patterns in ALL (precursor-B-

ALL ↔ T-ALL; children ↔ adults)

3. International comparability of MRD-PCR results •  Between MRD-PCR centers of same treatment protocol •  Between treatment protocols

→ Standardization, guidelines and quality control

European Study Group on MRD detection in ALL (EuroMRD)

AIMS of ESG-MRD-ALL (initial focus on PCR analysis of Ig/TCR genes): 1. Quality Control Program: 2 times per year: - February / March

- August / September

2. Educational meetings, including evaluation of quality control rounds: 2 times per year: - April / May - October / November

3. Standardization of MRD techniques - standardization techniques within each treatment protocol - guidelines for interpretation of RQ-PCR results

4. Collaborative development and clinical evaluation of new MRD strategies and new MRD techniques

Basis for accreditation of laboratory diagnostics

EuroMRD collaborative history

Start IG/TcR analysis in I-

Quality Control within the EuroMRD-ALL

Positive 1.00E-05 1.00E-04 1.00E-03 1.00E-02

QR: 5x10-4

RQ-PCR analysis of a follow-up sample using provided primers/probe set

→ MRD level differs less than 2-fold between various laboratories

MRD-PCR laboratories 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

QR 21 Task 1: QR, S, MRD1 and MRD2

case 1 case 2 case 3 case 4 case 5 case 6 case 7 case 8 case 9 case 10

QRSMRD 1MRD 2

Inter-laboratory concordance on QR, sensitivity, MRD1 and MRD2

Subclonal architecture in ALL

Linear

Moderate Complex

Anderson, Nature 2011 Notta, Nature 2011

Darwinian clonal evolution of a cancer

Evolutionary speciation, from Charles Darwin's

(1837) Greaves, M. Cancer stem cells: back to Darwin? Semin. Cancer Biol. 20, 65–70 (2010).

Changes in clonal architecture in ALL

Clonal relationship of diagnosis and relapse samples in ALL

Mullighan, C. G. et al. Science 322, 1377–1380 (2008).

Perspectives : Clinical use of MRD

1.  Identification of subgroup of patients with different kinetic of early tumor reduction

2.  Identification of patients with different outcome within genetically homogeneous subgroups

3.  Identification of impending relapse

4.  ‘Molecular relapse’ ?

Prospective MRD monitoring in chilhood ALL for molecular relapse detection ?

•  Systematic controls for MRD on all patients have relatively low chances (in children) to identify “MRD relapses”

•  MRD monitoring may be quite stressful (for patients/families and labs)

•  HR subgroups could be more suitable for a strategy of MRD monitoring

•  A second sample for confirmation of MRD positivity should be required

MRD as surrogate marker for early assessment of novel therapies?

"  The pressure to accelerate approval of novel drugs or the attempt to shorten the time to trial results has generated a growing interest on the use of end-points on activity (response) as surrogate end-points for efficacy (survival or event free survival).

" However, deciding that efficacy of treatment can be assessed in terms of molecular response requires that MRD levels are properly validated as a surrogate end-point.

An end-‐point for acSvity is not necessarily a surrogate for efficacy

AcSvity or Efficacy

MRD as surrogate end point

‘… It has to be pointed out that surrogate markers cannot serve as final proof of clinical efficacy or long term benefit. If they are intended to be the basis for regulatory review and approval then, unless they are properly validated, there should be a predetermined plan to supplement such studies with further evidence to support clinical benefit, safety and risk/benefit assessment.’ EmeaCHMP/EWP/83561/2005

MRD EFS-‐Survival

early response or clinical outcome

Conclusions ‘standards or research’?

"  ‘Standard’ •  Indepenent prognostic value at end-induction •  Standarized method •  Quality control rounds

"  ‘Research’ •  MRD depends on treatment and time points -> no clear value

outside clinical protocols •  Clonal background and evolution •  Combination of MRD and new genetic biomarkers •  Validation as a surrogate marker of efficacy •  Future use of next generation sequencing (development and

validation) •  Biology of different response (MRD) ?

Molecular MRD monitoring

in chilhood AML

(…) AML is lagging behind acute lymphoblastic leukemia with respect to the implementation of MRD criteria for guidance during therapy. AML is particularly disadvantaged compared with ALL in that approximately half of AML patients lack a molecular target suitable for MRD monitoring.

Elisabeth Paietta. Minimal residual disease in acute myeloid leukemia: coming of age. ASH 2012 - Eucational

Molecular targets for MRD quantification in AML

#  Fusion transcripts - t(8;21)(q22;q22) / AML1-ETO - inv(16) or t(16;16)(p13q22) / CBFβ-MYH11 15% of cases RNA, non-linear correlation with cells Pre-leukemia/SC monitoring

#  Mutations (allele specific primers)

ex. NPM1, FLT3-ITD low mutation rate in chilren unstable targets

#  Overexpression

ex. WT1, EVI1, PRAME

WT1 expression monitoring in chilhoo AML

•  Various methodologies to quantify WT1 expression •  Aim: To standardize WT1 mRNA quantitation the

European Study Group on WT1 Expression in Childhood AML was established including centers from Germany, Italy and Czech Republic

WT1 Quality controls

Leukemia 2009, 23 (8), 1472-1479 - Standardization of WT1 mRNA quantitation

WT1 expression in AML and healthy BM

2 log 20%

Acknowledgments Lilia Corral Simona Songia Tiziana Villa Eugenia Mella Valentina Carrino Giuseppe Gaipa Oscar Maglia Simona Sala Laura Levati Vincenzo Rossi Andrea Biondi Valentino Conter Giuseppe Masera Daniela Silvestri Maria Grazia Valsecchi Fondazione Tettamanti

Emanuela Giarin

Maddalena Paganin Katia Polato

Barbara Buldini

Barbara Michelotto

Giuseppe Basso

Clinica Ped. Univ. Padova

Grants by Fondazione Cariplo, AIRC and Comitato M.L.Verga

BFM Germany BFM Austria BFM Suisse

Surrogacy requires that the effect of the intervention on the ‘candidate’surrogate predicts its effect on

true clinical outcome

Prentice’s definition

Treatment Surrogate Clinical

Surrogate endpoint needs to be validated It is treatment (class) specific

“Surrogate scenario”

40% 10%

% failures 4 yrs

n. of failed

Same rate of failures in responders/non responders

Modest effect on clinical outcome

Standard treatment 100 pts

YES NO

Experimental treatment 100 pts

YES NO

High ac`vity

Response

MG Valsecchi, CORS Monza

Main objective of the consortium is to develop, standardize, and validate IG / TR NGS tools for:

i.) clonality assessment; ii.) MRD analysis; iii.) repertoire analysis / somatic mutation analysis

Platform-independent assay design Scientifically independent group, no exclusive interactions with commercial partners in the field of NGS (whenever relevant and useful, collaboration will be initiated, for example for optimal dissemination of developed assays / tools)

EuroClonality-NGS consortium

EuroClonality NGS consortium

A. Langerak / J. van Dongen (Rdam)

P. Groenen (Nijmegen)

M. Brüggemann / C. Pott (Kiel)

M. Hummel (Berlin)

M. Catherwood (Belfast)

F. Davi (Paris)

E. Macintyre (Paris)

R. Garcia Sanz (Salamanca)

K. Stamatopoulos (Thessaloniki)

N. Darzentas (Brno)

G. Cazzaniga (Monza)

M. Lefranc / V. Giudicelli (Montpellier) Coordination : A.W. Langerak

Phase 1 Technical WorkPackages

1 Development of IG-TR PCR-based NGS assays (all teams)

2 Bioinformatics pipeline (N. Darzentas)

3 Capture-based NGS strategies (D Gonzalez)

Phase 2 Application WorkPackages

4 NGS-based clonality assessment (P. Groenen / M. Hummel)

5 NGS-based MRD assessment (M. Brüggemann / C. Pott)

6 NGS-based Ig repertoire analysis (F. Davi / K. Stamatopoulos)

7 NGS-based TR repertoire analysis (A. Langerak / E. Macintyre)

EuroClonality-NGS consortium

Position IGH

V-J / V-Kde

V-J / D-J

V-J / D-D/J

“FR3”

(clonality,

~200 bp

Salam.

Paris-P

Nijmegen

Rotterdam

Belfast

NOT Berlin

Paris-N

London

Paris-N Monza

London

“leader”

(repertoire) Paris-P n.a.

(phase 2?)

t.b.d.

(phase 2?)

t.b.d. NOT NOT NOT

EuroClonality-NGS – PCR-based assays

454 GS Flex, Junior (Roche) HiSeq, MiSeq (Illumina)

Ion Torrent (Life)

Platform independence

•  wet lab work • 'raw' data from the NGS machine

• data preparation, including error correction

• meta-‐analysis, e.g. IMGT/HighV-‐QUEST Nikos Darzentas Vojta Bystry Jana Silhava Bioinformatics Analysis Team -‐ BAT -‐ bat.infspire.org Central European Institute of Technology -‐ CEITEC Masaryk University -‐ MU Brno, Czech Republic

EuroClonality-NGS – Bioinformatic pipeline

basic major steps 00. everything is logged, in different formats 01. parameter choice, can be defaults, can be organised in 'scenarios' 02. reading files, counting sequences, handling data 03. if applicable: joining paired-‐end reads 04. if applicable: across-‐samples comparison and info gathering 05. primer / adapter cutting 06. quality trimming, filtering, masking 07. FASTQ to FASTA 08. dereplicating 09. error correction 10. final filtering steps 11. junction analysis, summaries, matrices, visualisations 12. wrapping up -‐ minilogging, compressing/removing files

Nikos Darzentas

error correction error corrections are attempted through a module that can be repeated as many times as requested or required there is actually an 'auto' mode that goes on (within limits) until it reaches a plateau of small number of corrections error correction decisions can be different, for many reasons: -‐ for different sequence regions, e.g. V, junction, J etc. -‐ for different receptors, i.e. IG and TR -‐ for different samples, runs, machines, protocols critically, we can learn on-‐the-‐fly from a sample or sequence region (e.g. V region in TR, which should be in germline-‐configuration) to apply in another region (e.g. junction) or other samples there can also be multiple individual factors affecting the decisions, e.g. strand biases

Nikos Darzentas

cluster 19 10 20 30 40 50 60 70 80 90 100 110 120 . | . | . | . | . | . | . | . | . | . | . | . | . gagctctgtgaccgccgcggacacggctgtgtattacTGTTCGAGCAGCTTAGGTGTGGCAGTNGCTGGTACGGGTTCGGACTACTTTGAGCAATGGagccagggaaccngggtcaccgtctcctcag g t g n g -‐ t g a n |after corrections -‐ g -‐ g t -‐ g -‐ g -‐ g -‐ t g a -‐ g

Nikos Darzentas

Exome Capture – TruSeq (Illumina) DNA $ Fragmentation ~200 bp $ Library Prep $ Hybridisation to biotin-DNA baits $ Streptavidin pull down $ Amplify/index $ Sequence

EuroClonality-NGS – Capture-based assays

BCL2 IGH

EuroClonality-NGS – Capture-based analysis

David Gonzalez ! to be extended to V(D)J rearrangements (IG-TR)

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