Personalization of Therapy for MDS: The Role of Biology, Risk … · 2014. 9. 10. · EZH2 TK...
Transcript of Personalization of Therapy for MDS: The Role of Biology, Risk … · 2014. 9. 10. · EZH2 TK...
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Personalization of Therapy for MDS: The Role of Biology, Risk Stratification, and Evolving TherapiesGuillermo Garcia-Manero, MDThe University of Texas MD Anderson Cancer Center
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Age‐adjusted incidence rates of MDS (2001‐2003)
Characteristic (Rate) Count %Total 3.27 24 798Year of diagnosis200120022003
3.13.293.45
7 8878 5088 403
31.834.333.9
SexMaleFemale
4.432.53
13 51811 280
54.545.5
Age (years)<4040-4950-5960-6970-79≥80
0.140.621.957.14
20.0535.49
592728
1 7273 9318 5639 257
2.537
1634.537.3
Rollison D et al. Blood 2008;112:45‐52 (Rate per 105; age‐adjusted for 2000 US population)
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Diagnosis of MDS is based on morphology
Courtesy of Dr. Carlos Bueso‐Ramos
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Discordance between referral diagnoses and final diagnoses at MDACC. (A) By French-American-British.
Naqvi K et al. Blood 2011;118:4690-4693
©2011 by American Society of Hematology
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Cause of death in lower risk MDS
0
10
20
30
40
50
60
Transf. Infectious Cardiac Bleed Others
Dayyani. Cancer 2010;116:2174‐9
%
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What are the major needs in MDS?(problems that limit significant cure rate)
• Identification of poor prognosis “lower risk” patients– By default sparing patients with no need of therapy– Concept of early intervention
• Development of new targeted therapies for patients with lower risk MDS
• Development of new therapies for patients with higher risk MDS
• Understanding mechanisms of resistance to epigenetic modulators in MDS (critical)
• Understanding mechanisms of transformation to AML• Incorporation of alloSCT in MDS• Minimizing risk of relapse post alloSCT in MDS
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Why do we need prognostic models?• Predict survival without therapy
• Therefore decide on who needs therapy• Shorter the survival associated with increased need of therapy
• Predict survival with therapy• Example: SCT
• Predict survival in the context of the patient• Comorbidities
• Molecularly adapted therapy– Early intervention– Targeted approaches
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Prognostic models• IPSS• WPSS• Global MDACC model• MDACC lower risk model• Impact of comorbidities• New “revised IPSS”
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Survival by MDS model within IPSS Risk IPSS-low IPSS-int-1
IPSS-int-2 IPSS-high
Kantarjian Cancer 2008;113:1351-61
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Comorbidities in MDS. ResultsComorbidities by ACE-27None (0)Mild (1)Moderate (2)Severe (3)
N/(%)137 (23)254 (42)127 (21)82 (14)
Comorbidities by System
050
100150200250300350 328
9740
1
168
351
48 1453
17 32
Naqvi et al. JCO 2011
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Comorbidities in MDS. Multivariate Survival Model with Risk Score
Prognostic factor
Coefficient Score
Age >65 0.582 2
Comorbidityscore
(ACE -27)
Mild or moderate
0.301 1
Severe 0.782 3
IPSS Int 2 0.512 2High 0.769 3
*Score points were obtained by dividing estimated coefficients by 0.3
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Comorbidities in MDS. Survival by Risk ScoreSurvival Proposed
risk groupScore No pts (%) Median(mos)
5-yr %
0 45 (8) 60 53 Low (score: 0-1)1 71 (12) 39 38
2 52 (9) 26 19 Intermediate(score : 2-4)3 180 (30) 23 22
4 56 (9) 15 245 109 (18) 9 8 High
(score:5-8)6 62 (10) 7 27-8 20 (3) 7 0
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1999-2003: Survival by % Blasts
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Weighting of Cytogenetics in Relation to BM blast counts in IPSS
0 10 20 30 40 50 60
Months
Cum
ulat
ive
inci
denc
e fu
nctio
n fo
r AM
L
00.
10.
20.
3
IPSS cytogenetic subgroupsgoodintermediatepoor
p(Gray-test) = 0.132
B
0 10 20 30 40 50 60
Months
Cum
ulat
ive
inci
denc
e fu
nctio
n fo
r AM
L
00.
10.
20.
3
Bone marrow blast count<5%5-10%11-20%21-30%
p(Gray-test) < .001
D
Figure 1 A-DOverall survival and cumulative risk of AML-transformation in IPSS cytogenetic and FAB bone marrow blast count subgroups (univariate analysis; pts. treated with supportive care exclusively)
0 50 100 150 200 2500.0
0.2
0.4
0.6
0.8
1.0
goodintermediatepoor
A
IPSS cytogenetic subgroup
p (log-rank) <0.0001
Months
Cum
ulat
ive
surv
ival
0 50 100 150 200 2500.0
0.2
0.4
0.6
0.8
1.0
<5%5-10%11-20%21-30%
CBone marrow blast count
p (log-rank) <0.0001
Months
Cum
ulat
ive
surv
ival
Category OS(months)
OS (HR)
Poor (IPSS)
7.5 3.2
Complex(non 5/7)
7.4 3.0
Complex(5/7)
5.6 5.4
Blasts(21-30%)
7.4 3.2
Schanz J et al. J Clin Oncol. 2012;30:820-829.
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New Cytogenetic Scoring System in MDS
Schanz J et al. J Clin Oncol. 2012;30:820-829.
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chr 7 abn alone7%
chr 7 abn + other abn13%
Tri X alone2%
Tri Y alone2%XXYY
2%
Tri 8 alone13%
Tri 8 + Tri 52%
Tri 9 alone2%
Tri 11 alone2%
Tri 13 alone2%Tri 14 or Add 14q32
alone%
Add 18q232%
Add 19p13.3
2%
Tri 214%
5p del alone4%
Y del alone2%
Del 1p34.1p36.22%
del 3q21q274%
del9q12q224%
del12p11p134%
del 13q12q222%
del14q22q312%
del17q22q242%
t(2;9)(p14p21)2%
t(3;18)(p21q21.3)2% t(6;9)
4%
Complex abn exclud 7 abn
7%
Other abn5%
Cytogenetic acquisition in MDS
Jabbour. ASH 2011 abstract 3802
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0 20 40 60 80 100 120
Time (Months)
0.0
0.2
0.4
0.6
0.8
1.0
Prob
abilit
y of
Ove
rall
Surv
ival
Non-CACA
Jabbour. ASH 2011 abstract 3802
Effect of cytogenetic acquisition in MDS
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Diploid
Diploid
Abnormal
LR MDS
LR MDS
AML
AML
ACA
ACA
Diploid
Abnormal
Abnormal
Diploid
Abnormal
7 months
8 months11 months
6 months
A)
B)
Early identificationpatients at risk
Early identificationpatients at risk
Intervention
Intervention
Hypothesis #5: identification of drivers of transformation
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NRASFL
T3 MLL NF1CSF
R1KIT
CDKN2BTP
53CDKN2A RB1
EV11
IRF1
RUNX1CEB
PAWT1NPM
1
0
10
20
30
40
50Pe
rcen
t
Bernasconi. BJH 2008
Molecular lesions in MDS
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UPD chromosome 7 in MDS
Heinrichs. Leukemia 2010
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Point Mutations in MDSAssociations With Clinical Features
Independent Predictors of Overall Survival
Bejar et al. N Engl J Med. 2011;364:2496-2506.
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DNA Sequencing454 sequencingRUNX1TP53TET2NPM1
Laura Macconaill & Charlie Hatton Omar Abdel‐Wahab & Ross Levine
Sanger sequencingASXL1EZH2KDM6A (UTX)
Björn Nilsson
CDKN2APTENCBL
IDH1IDH2ETV6
Bejar et al. N Engl J Med. 2011;364:2496-2506.
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Somatic mutations in 18 genes were identified.
51% of samples had at least one mutation ...
... including 52% of cases with a normal karyotype.
Mutation Frequency
Bejar et al. N Engl J Med. 2011;364:2496-2506.
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TP53
TET2
ASXL1
RUNX1
NRAS/KRAS/BRAF
CBL
JAK2
EZH2
IDH1/IDH2
ETV6
NPM1
5q‐ alone
Complex
‐7/7q‐ alone or +1 abnormality
Normal and –Y alone
+8 alone
Other
‐20q alone
Unknown
Karyotype
20.5%
14.4%
8.7%
5.0%
2.3%
3.0%
6.4%
3.4%
2.7%
7.5%
1.8%
Mutation Frequency and Distribution
Bernd Boidol & Bennett Caughey Bejar et al. N Engl J Med. 2011;364:2496-2506.
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Kristen Stevenson & Donna Neuberg
Survival Curves II
Bejar et al. N Engl J Med. 2011;364:2496-2506.
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Multivariate Model
Kristen Stevenson & Donna Neuberg
HR (95% CI) p‐value
Age
≥55 yrs vs. <55 yrs 1.81 (1.20‐2.73) 0.004
IPSS Risk Group
Int1 vs. Low 2.29 (1.69‐3.11) <0.001
Int2 vs. Low 3.45 (2.42‐4.91) <0.001
High vs. Low 5.85 (3.63‐9.40) <0.001
Mutational Status ‐ Present vs. Absent
TP53Mutation 2.48 (1.60‐3.84) <0.001
EZH2Mutation 2.13 (1.36‐3.33) <0.001
ETV6Mutation 2.04 (1.08‐3.86) 0.029
RUNX1Mutation 1.47 (1.01‐2.15) 0.047
ASXL1Mutation 1.38 (1.00‐1.89) 0.049
137/439 (31.2%) samples carry one or more prognostic mutations
LowInt1
Int2High
IPSS Risk Groups
Bejar et al. N Engl J Med. 2011;364:2496-2506.
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Molecular genetic landscape (2010)RUNX1 20%
poor prognosisMDS-EV1 n/a ~5% cases over-expressedTP53 10% poor prognosis, therapy related MDSRAS 15% potential treatment targets in downstream
pathway membersJAK2 5% most often seen in RARS-T
potential treatment with JAK2 inhibitorsTET2 12-26% seen in various myeloid malignancies
potential link to DNA methylation and treatment with hypomethylating agents
ASXL-1 11-18% potential treatment targets in histone modifying enzymes and ATRA
EZH2 6% seen in various myeloid and solid tumor malignanciespotential treatment targets in histone modifying enzyme
Cortesy Ross Levine. MSKCC
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Identification of poor prognosis “lower risk” patients with MDS
Bejar et al. J Clin Oncol 2012 (e‐pub).
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Mutation Distribution in the LR‐PSS
SF3B1
SRSF2
TET2
TP53
RUNX1
ASXL1
EZH2
TK Pathway
ETV6
IDH1/IDH2
NPM1
U2AF1
DNMT3A
SF3B1
SRSF2
TET2
TP53
RUNX1
ASXL1
EZH2
TK Pathway
ETV6
IDH1/IDH2
NPM1
U2AF1
DNMT3A
Category 1 Category 3
TK Pathway Genes = NRAS, KRAS, BRAF, CBL, JAK2
46% 90%
Bejar et al. J Clin Oncol 2012 (e‐pub).
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U2AF1 Normal (n=242)Mutated (n=46)
p = 0.026
SRSF2 Normal (n=246)Mutated (n=42)
p = 0.016
SF3B1 Normal (n=226)Mutated (n=62)
p = 0.11
Overall Survival in Lower Risk MDSLower Risk MDS Set (n=288)
Kristen Stevenson & Donna Neuberg
DNMT3A Normal (n=252)Mutated (n=36)
p = 0.89
Mutated Genes with Shorter OS NRAS p < 0.001
EZH2 p < 0.001
RUNX1 p < 0.001
ASXL1 p < 0.001
SRSF2 p = 0.016
U2AF1 p = 0.026
TP53 p = 0.054
Bejar et al. J Clin Oncol 2012 (e‐pub).
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Other molecular alterations in MDS• Aberrant DNA methylation CpG islands
• NUP98-HOXD13: transplantable animal model
• EVI1: role in erythropoiesis (GATA-1, PU.1)
• SPARC, c-CBL, RUNX-1, Tet-2
• miRNA (5q-)
• Disrupted mesenchymal stem cell differentiation
Boumber Cancer Res 2007;67:1997-2005. Chung PNAS 2008;105:140088-93. Pellagatti, PNAS 2007;104:11406-11. Dunbar, Cancer Res 2008;68:10349-57. Delhommeau NEJM 2009;360:2289-301.Laricchia-Robbio Cancer Res 2009, in press. Lopez-Villar Leukemia 2009, in press
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MDS
Low-risk(IPSS low, INT-1)
(BM blasts < 10%)
High-risk(IPSS INT-2, high)(BM blasts > 10%)
• Iron chelation• Growth factors
(Epo + G-CSF)• MTI (5-AZA/decitabine)• Lenalidomide (5q-)• Immunemodulation• Clinical trial
Age < 60• Intensive
chemotherapy• MTI (5-AZA/decitabine)• Clinical trial
Age ≥ 60• MTI (5-AZA/decitabine)• Clinical trial• Intensive
chemotherapy1
1Consider in younger patients with diploid cytogenetics
2Consider earlier in younger patients
Failure/ Progression
Allo SCT
Proposed treatment algorithm for patients with MDS
Any age
Atallah. Cancer Inv. 2008;26:208-16
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Low dose decitabine in LR MDS: Study Design
Study Arms• Arm A: DAC 20 mg/m2 SC Q DAY x 3 every 28 days• Arm B: DAC 20 mg/m2 SC Q WEEK x 3 every 28 days
Statistical Methods• First 40 patients 1:1 randomization• Then adaptive randomization procedure for a maximum of
80 patients• Modified intent-to-treat-analysis• Expected overall response rate of 20% for each arm• Continuous data monitoring• Overall improvement included: CR, marrow CR, PR or HI
by IWG 2006• An arm will considered superior if the posterior probability
was 0.95 and inferior if it was 0.1 • A maximum of N=80 patients to be treated
Garcia-Manero. Blood 2009;114:54:54 (abstract 119)
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Low dose DAC in LR MDS: Transfusion Independence Rate
Arm A(Daily)N(%)
Arm B(Weekly)
N (%)RBC TransfusionIndependence 20 (62.5) 15 (68.2)
Platelet Transfusion Independence 22 (68.8) 18 (81.8)
RBC/PLT Transfusion Independence
20 (62.5) 13 (59.1)
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Phase 1 Oral Aza Study
• MDS or AML• ECOG PS 0-2• Prior Aza/Dec
allowed
Treat to Progression
• Cycle 1: SC Aza 75 mg/m2 x 7 days• Cycle 2 and beyond: PO Aza x 7 days• 3 + 3 design• 28-day cycles
• PK Cycles 1, 2 and 7• PD every Cycle• End of Cycle 7:
– Assessment of response– Crossover to SC permitted for non-
responders• Intrasubject dose escalation permitted
Garcia-Manero. JCO 2011
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Phase 1 Oral Aza Study Response to Therapy (N=41)
DispositionMDS
(N=29)N (%)
CMML (N=4) N (%)
AML (N=8)N (%)
Ongoing 8 (28) 2 (50) 2 (25)Terminated 21 (72) 2 (50) 6 (75)
Median duration of oral therapy,
# of cycles, (range) 6.0 (1–23+) 7.0 (3–17+) 4.5 (1– 14+)
Cycle 7 Response Assessment* 13 (45) 2 (50) 2 (25)CR / PR / HI 4 (31) 1 (50) 0 (0)SD 8 (61) 1 (50) 2 (100)†
Progression 1 (8) 0 (0) 0 (0)
* IWG 2003 or 2006†Subjects did not meet criteria for progression or response by IWG 2003
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Duration on Study of MDS Subjects (N=29)
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Extrapolated Cumulative AZA Exposure per Cycle*
*Percentage of exposure as compared to SC azacitidine.
0
2000
4000
6000
8000
10000
SC-75 mg/m2
qd×7d (n = 44)Oral-480 mg
qd×7d (n = 15)Oral-300 mg
qd×14d (n = 13)Oral-300 mg
qd×21d (n = 13)
Mea
n cu
mul
ativ
e ex
posu
re
(AU
C) p
er c
ycle
(ng*
hr/m
L)
100%
58%
36% 38%
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LK08-02-11_1.ppt
A Decision Analysis of RIC Allogeneic HSCT for Older Patients
with De-Novo MDS: Early Transplantation Offers Survival
Benefit in Higher-Risk MDS
CIBMTR Study #LK08-02
COI Disclosures per ASH
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Datasets Natural History Cohorts (Low/Int-1 IPSS): BSC: IMRAW (Greenberg), Pavia (Cazzola, Malcovati) ESA: GFM (Park), Nordic (Hellstrom-Lindberg,
Jadersten)
Hypomethylating Agent Cohorts (Int-2/High IPSS): AZA-001 (Fenaux, Beach, Gale) GFM Compassionate use Azacytidine (Itzykson, Ades) MDACC Decitabine (Garcia-Manero)
RIC HSCT Cohorts (All IPSS risk): CIBMTR-MDS DFCI-MDS FHCRC-MDS (Deeg)
LK08-02-11_7.ppt
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Monte Carlo – Low/int-1 IPSSSurvival Estimates
LK08-02-11_15.ppt
Test of Equality over Strata
Test p
Log‐Rank <.0001
Wilcoxon <.0001
‐2Log(LR) <.0001
RIC HSCT
Non-transplant
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Pleiotropic effectson Progenitors and AML blasts
Dual Inhibition of p38 and Tie2 by ARRY-614 Blocks Myelosuppression in Bone Marrow
Ang-1 Ang-2
• Major regulator of the cellular pathways which sense stress (Cuadrado et al. Biochem. J. 2010. 429: 403.)
• Over-activated, leading to inappropriate production of myelosuppressive cytokines (Navas et al. Blood. 2006. 108: 4170.)
• Dysregulated, may be a survival factor for the AML blast (Keith et al. BJH. 2007. 137: 206.) (Wakabayashi et al. Hematol. J. 2004. 5: 353.)
• Increased signaling associated with poor prognosis (Cheng et al. BJC. 2011. 105: 975.)
p38 MAPK in MDS Tie2 in MDS – Emerging Target
p38
Stress/Inflammatory Stimuli (Cytokines, Hypoxia, FasL)
TNF-α, IL-6, ChemokinesDecreased RBC, WBC,
platelets
Apoptosis
Komrokji R. ASH 2011.
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Prior Therapies
AZA=azacitidine, ESA=erythropoiesis stimulating agents, DEC=decitabine, LEN=lenalidomide, GCSF=granulocyte colony stimulating factor, HDACi=histone deacetylase inhibitor
80%
58%
42%
22%
49%
40%
24%
16%13%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%Pe
rcen
t of P
atie
nts
(N=4
5)
HMAs Other
• Median number of prior therapies (range): 3 (0 – 9)• 80% received treatment with ≥ 1 HMA
Komrokji R. ASH 2011.
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0%
10%
20%
30%
40%
50%
400 (n=15) 600 (n=10) 900 (n=3) 1200 (n=16)
HI R
ate
Total Daily Dose (mg)
Trend for Increased HI by DoseIWG 2006 HI by Total Daily Dose
• 38% HI at highest dose (1200 mg daily)• 67% bi-lineage responses
Bi-lineage
Uni-lineage
38 %33 %
30 %
20 %
Komrokji R. ASH 2011.
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HI Responses• Overall, durable HI observed in 13 of 44 evaluable patients (30%)
• 5 bi-lineage responses
1Includes one each: Pseudodiploid Clone, T(1:8)(Q21;Q22), Del (7), Pseudo Hyperdiploid Clone del (20q), del 5q, and Trisomy 8
• Responder (n = 13) baseline characteristics• All ≥ 1 prior HMA• 12 IPSS Int-1• 11 2-3 cytopenias• 6 abnormal cytogenetics1
N patients HI-E HI-P HI-N Total HIn = 41 n = 25 n = 16 N = 44
Total (%) 8 (20) 5 (20) 5 (31) 13 (30)
Median duration, weeks (range) 32 (9-80) 16 (8-67) 21 (14-26)5 of 7 platelet transfusion-dependent patients became transfusion independent (TI) for a median duration of 20 weeks (range 15 – 31)3 of 28 RBC transfusion-dependent patients became TI for a median duration of 21 weeks (range 11 – 72)
Komrokji R. ASH 2011.
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Azacitidine survival studyAZA 75 mg/m2/d x 7 d q28 d
CCRRandomization
BSC was included with each armTx continued until unacceptable toxicity or AML transformation or disease progression
• Best Supportive Care (BSC) only• Low Dose Ara-C (LDAC,
20 mg/m2/d x 14 d q28-42 d)• Std Chemo (7 + 3)
Screening/CentralPathology Review
Investigator CCRTx Selection
Fenaux et al. Lancet Oncology 2010
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Overall Survival: Azacitidine vs CCR ITT Population
Log-Rank p=0.0001HR = 0.58 [95% CI: 0.43, 0.77]Deaths: AZA = 82, CCR = 113
0 5 10 15 20 25 30 35 40Time (months) from Randomization
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Prop
ortio
n Su
rviv
ing
CCRAZA
Difference: 9.4 months
24.4 months
15 months
50.8%
26.2%
Fenaux et al. Lancet Oncology 2010
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Hazard Ratio and 95% CI for Overall SurvivalITT Subgroups Total - Event / N
Cytopenias: 0/1 20 / 53
WHO: RAEB-1 15 / 31
0.125 0.250 0.500 1 2 4
Favors Azacitidine Favors CCR
≥ 65 150 / 258
Female 61 / 107FAB: RAEB 95 / 207
RAEB-T 80 / 123
RAEB-2 102 / 193IPSS: INT-2 71 / 146
High 98 / 167Cytogenetics: Good 80 / 167
Intermediate 38 / 76Poor 67 / 100
2/3 167 / 290
Karyotype: -7/del (7q) 42 / 57
≥ 21% to < 31% 58 / 99
AGE: < 65 45 / 100
LDH: ≤ 240 U/I 97 / 208
RAEB & RAEB-T: AGE ≥ 65 138 / 240
> 240 U/I 94 / 145
ITT 195 / 358
≥ 75 50 / 87
≥ 11% to < 21% 98 / 192
Male 134 / 251
BM Blasts: ≥ 5% to < 11% 34 / 61
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Update on AZA-001 study• Subset analysis of pts ≥ 75 years in AZA-001• 87 of 358 (24%) in that category in AZA-001• OS not reached for 5-aza treated vs 10.8 months
for BSC (HR 0.48, 0.26-0.89, p=0.01)• OS at 2 years 55% 5-aza vs 15% BSC• Subset analysis WHO AML in AZA-001• 113 of 358 WHO AML (blasts 20-30%)• Median age 70; 24% abnormal CG• Median N of cycles 8 (1-39)• OS at 2 years 50% vs 16% p=0.0007• No differences in CR
Seymour. Blood 2008;112:1241 (abstract 3629)
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Fenaux P. JCO 2010; 28:562
Overall Survival: Azacitidine (n=55) or Conventional Care Regimens (CCR,n=58)
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Outcome in MDS post hypomethylating failure
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Synergistic apoptotic effect of the combination of decitabine with VPA
Yang H, et al. Leuk Res 2005;29:739-748
05
101520253035404550
Control VPA DAC DAC + VPA% Apoptosis
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VPA(mg/kg) N CR CRp BM OR
N (%)Courses to response
50 40 10 3 6 19 (47) 1(1-3)
62.5 7 1 0 0 1 (14) 2
75 6 1 0 1 2 (33) 1
Total 53 12 3 7 22 (42) 1 (1-3)
Untreated 33 11 3 3 17 (52) 1 (1-3)
Previously Treated 20 1 0 4 5 (25) 1(1-2)
5-AZA + VPA + ATRA in Leukemia: Responses
Soriano. Blood 2007; 110:2302-2308
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5-AZA + VPA + ATRA in Leukemia: Overall survival
Soriano. Blood 2007;110:2302-2308
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TET2 and response to 5-azacitidine• TET genes transform 5mC to 5(OH)mC
• Mutations may result in passive hypomethylation
• N=103 patients: median age 72 (43 to 91)
• Standard 5-aza in France
• Median N of cycles 7 (1 to 39)
• TET2 MUT in 21 pts (17%)
• RR 11/17 (65%) in MUT vs 26/86 (30%) in WT (p=0.01)
• OS 15.3 months in MUT vs 16.2 in WT (NS)Itzykson. ASH 2010 abst 439
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Len + Aza Phase 2: Response Results
• ORR (n=36): 26/36 (72%)– 15 CR (42%)– 10 HI (28%)– 1 BM CR (3%)
• Median CR duration: 16+ months (range, 3-36+)
• Median OS among CR pts: 27+ months (range, 7-55+)
Sekeres et al. Blood 2011;118:607a
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North American Intergroup Randomized Phase 2 MDS Proposal (S1117)
AZAN=80
AZA + LENN=80
AZA + VorinN=80
Higher-risk MDS
(IPSS >1.5 or Blasts
>5%)
Groups: SWOG, ECOG,CALGB, NCIC
Total Sample Size: 240
Primary Objective: 20%improvement of RR based on 2006 IWG Criteria
Secondary Objectives: OS,RFS, LFS
Power 81%, alpha 0.05 for each combo arm vs. AZA
Anticipated time: 2.5 years
Sekeres et al. Blood 2011;118:607a
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Monte Carlo – Int-2/High IPSSSurvival Estimates
LK08-02-11_16.ppt
Test of Equality over Strata
Test p
Log‐Rank <.0001
Wilcoxon <.0001
‐2Log(LR) <.0001
RIC HSCT
Non-transplant
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Effect of monosomy 7 in MDS/AML post alloSCT
• EBMT analysis from 1981 to 2006. N=278 patients• N=192 (70%) related• N=63 (22%) monosomy (one monosomy and at least one
other abnormality)• 5-year OS was 28% and RFS 26%• Relapse rate at 3, 12 and 60 months was 9, 29 and 39%• Non-relapse mortality was 21, 36 and 40% respectively• For patients with monosomy:
– OS 0% (HR 2.4, 95% CI 1.6 to 3.6); p=0.0001– RFS 0% (HR 2.4 95% CI 1.7 to 3.9); p=0.0001
Van Gelder. Blood 2009:114: 123 (abstract 293)
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AZA POST ALLOSCT – overall survivalMedian follow-up is 16 months
5 10 15 20 25 30 35 40 45
Months
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
Median follow-up is 16 months
Survival - patients that received AZA
DeLima Cancer 2010
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ON 01910.Na: Results in +8 MDS• ON 01910.Na new styryl sulfone; decreases
cyclin D1 levels in primary MDS• Phase I/II trial. N=15 (int-1 to AML CG +8)• Dose 800 to 1500 mg/m2 2 to 5 days every 2 to 4
weeks • No toxicity• Decrease in aneuploidy and cyclin D1• HI in 46% (7 of 15)
–4 patients with prior 5-aza: 2 responses• Potential new agent in MDS
Sloand et al. Blood 2009; 114: abst 120
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Phase 3 ON 01910 vs BSC Pivotal Trial• Randomized study (2:1) of ON 01910 vs
BSC; post AZA/DAC failures• Primary endpoint survival• ON 01910 1800 mg /m2 CI over 24 hrs
daily x 3; Qow x 8 then Qmos• Total 270: ON 01910 180 pts; BSC 90 pts
Treatment No./Eval Marrow CR (%)ON 01910 17/13 5(38)LD ara C 5/4 0
Garcia Manero. 2012
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Investigational Strategies in MDS• Clofarabine• Romiplostin (AMG531)• Vaccines (PR1)• TLK199• Farnesyltransferase inhibitors• CD33 MoAb (GO, lintuzumab)• P38 inhibitors• Sapacitabine• Homoharringtonine• HDAC inhibitors (VPA, vorinostat, MGCD0103) ±
hypomethylating agents• Intensive chemoRx
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Clofarabine in High-Risk MDS• 58 pts with MDS with ≥5% blasts or
IPSS ≥1–Median age 68y (25-89)–26% secondary MDS– IPSS karyotype poor 38%
• No prior chemohterapy(biologic/targeted Rx allowed)–60% prior hypomethylating agents
• Randomized to clofarabine (5 days/mo): 15 mg/m2 (N=37) or 30 mg/m2 (N=21)
• Ambulatory therapy 22%Jabbour et al. ASCO 2010; abst #6504
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Response to Clofarabine in HR-MDS
Dose (mg/m2)
All ptsFailed
hypomethylating agents
N% Response % 8-wk
mortality
% Response
ORR CR CRp N CR CRp15 37 41 27 17 14 22 14 530 21 29 24 5 29 13 15 0
Total 58 36 26 10 19 35 14 3• Median survival 7.4 mo• Median response duration 8.8 mo• Deaths on Study: 11 patients (19%)
Jabbour et al. ASCO 2010; abst #6504
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Sapacitabine in MDS • 39 pts; all failed AZA/DAC; all int-2 or
high risk IPSS• Randomized Rx to 3 doses of sapa: 200
mg bid x 7, 300 mg bid x 7, 400 mg bid x 6 (D1-3, D8-10)
• Median age 73 yrs; age > 70 yrs 79%• Marrow blasts > 10% 18 pts (56%)• Response: 1 CR+8 major HI = 9/39 (23%)
RR 23% at 200, 38% at 300, 8% at 400Garcia-Manero et al. Blood 114:1758, 2009
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