using mouse models of acute lymphoblastic leukemia...
TRANSCRIPT
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Using Mouse Models of Acute Lymphoblastic Leukemia to Test Novel Therapies
David T. Teachey, MD
Tumor Models Boston 2017
July 20, 2017
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Disclosures for
David T. Teachey
Employee N/A
Consultant N/A
Major Stockholder N/A
Speakers Bureau N/A
Honoraria/Grant Funding Novartis (Institution)
Scientific Advisory Board Amgen
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Hunger S P et al. JCO 2012;30:1663-1669
©2012 by American Society of Clinical Oncology
ALL OS: COG studies
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Dismal Outcome for 2nd+ Relapse of ALL
Resimuller et al. JPHO 2013
10 year EFS
Leukemia is the #2 cause of pediatric cancer mortality: NOVEL THERAPIES ARE NEEDED
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How to tackle the problem?
• Intensify therapy for high risk disease
• Reduce therapy for low risk disease
• Introduce targeted therapies
• Addressing clonal evolution in chemoresistance
• Incorporate immunotherapies
• Modify therapy based on
host polymorphisms that
can affect drug metabolism
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NSG Xenograft Model of ALL
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Spectral Unmixing of Click Beetle Green (CBG) and Click Beetle Red (CBR) Luciferase
CBG Leukemia only
EMpeak 540 nm
CBR T-cells only EMpeak 640 nm
Barrett
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CHOP ALL Xenografts
• > 400 patients – 75% 1o engraftment – 66% >85% replacement bm and
spleen (usable samples) – 100%: 2o engraftment – Start with 1 million
lymphoblasts – Gain 10-960 million/mouse
• Cytotoxics – DEX, VCR, PRED, ASNase, ARA-C,
DOX, VP-16, MTX, MITO
• Biologic agents – Sirolimus, Temsirolimus – Bortezomib, Ruxolitinib – R04929097, MLN8237 – ENZ3042, CEP-701 – Dasatinib, AT9283, Trametinib – Triptolide, iCRT and many more
• Immunotherapies – moABs – CAR T – BITEs – DARTs
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Targeted Therapies
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Somatic Alterations Are Associated With Prognosis and Have Therapeutic Implications
Pui CH, et al. Blood. 2012;120(6):1165-1174. Schultz KR, et al. J Clin Oncol. 2009;27(31):5175-5181.
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Ph-like ALL
Roberts, et. al. NEJM 2014
12.6% 3.9%/7.4% 50% 12.6% 4.3% 9%
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Targeting JAK pathway in vivo
0.0E+00
1.0E+08
2.0E+08
3.0E+08
4.0E+08
5.0E+08
6.0E+08
7.0E+08
BC
R-J
AK
2
0
1000
2000
3000
4000
5000
6000
Vehicle
Ruxolitinib
Maude, et. al. Blood 2012
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Ruxolitinib for Ph-like ALL
USI JAK2 mut CRLF2r Other kinase lesion Rux activity
PALKTY QGinsR683 P2RY8 Yes
PAMDRM GPinsR683 IGH@ No
PAKHZT R687Q IGH@ Yes (Partial)
PAMDKS R683G IGH@ Yes (Partial)
PALLSD R683G IGH@ Yes
PAKRSL R683G IGH@ Yes
PAKMZM I682F IGH@ No
PALNTB P933R IGH@ Yes
PALJCF JAK1 L624_R629>W P2RY8 Yes (Partial)
PAKSWW JAK1 V658F IGH@ Yes
PAKMVD JAK1 S646F Yes (Partial)
PALTWS IGH@ Yes
PAKKXB IGH@ FLT3 N609ins23aa No
PAKYEP BCR-JAK2 Yes
PALJDL IL7R, SH2B3 Yes
PAKKCA EBF1-PDGFRB No
PAKVKK NUP214-ABL1 Yes (Partial)
PAKTAL STRN3-JAK2 Yes
PANSFD ETV6-ABL1 no
PAPDFU SSBP2-CSF1R no
Engrafted >35 samples
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EXPERIMENTAL DESIGN SCHEMA AALL08B1
Risk Assessment & LDA testing
NCI HR B-precursor ALL and SR B-
precursor ALL (CNS3, Testicular disease, Steroid pre-treated)
AALL1131 (Study Entry)
Patients receive 3-drug Induction on AALL0932 –
Post Induction risk assessment determined as HR-ALL or VHR-ALL
4-Drug Induction
(< 10 years-DEX for 14 days) (≥10 years-PRED for 28 days)
VHR-ALL1
Randomization
Control Arm Exp Arm 1
Consolidation 3 (Day 1-28) MBFM
Consolidation (Day 29-57)
MBFM
Consolidation (Day 29-57) CPM/ETOP
Evaluation (MRD Flow) 4
Interim Maintenance I (MBFM-IMHDM)
Delayed Intensification (Day 1-28)
Delayed Intensification
(Day 29-57) MBFM
Delayed Intensification
(Day 29-57) CPM/ETOP
Interim Maintenance II (MBFM- CMTX)
Maintenance5#(MBFM)
HR-ALL1
Randomization
Consolidation 3
MBFM (+ ITT)
Consolidation 3
MBFM (+ IT MTX)
Interim Maintenance
MBFM-IMHDM
(+ IT MTX)
Interim Maintenance
MBFM-IMHDM
(+ ITT)
Delayed
Intensification
MBFM (+ IT MTX)
Delayed Intensification
MBFM (+ ITT)
Maintenance5
MBFM
(+ ITT)
Maintenance5
MBFM
(+ IT MTX)
Maintenance
+ dasatinib
Delayed Intensification
MBFM
+ dasatinib
Interim Maintenance I
MBFM-IMHDM
+ dasatinib
BM Evaluation (MRD Flow)
Consolidation
MBFM
+ dasatinib
Dasatinib Arm
Interim Maintenance II
MBFM-CMTX
+ dasatinib
Ph-Like
with drug
targetable
kinase
mutation
Ph-Like
dasatinib
sensitive
kinase
mutation
Ph-Like
ruxolitinib
sensitive
kinase
mutation
AALL1521
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ETP ALL
• AALL1231 Clinical Trial – 1200 patient randomized trial aBFM
vs bortezomib plus aBFM – Proteomics, RNAseq, Xenografts on
~40% of patients – >150 samples injected into mice – >80 have engrafted; 15% ETP
• DNM2, JAK3 • PTPN11 • GATA3, JAK1, SH2B3 • FLT3 • EZH2, NOTCH1, RUNX1, SH2B3 • Biallelic TRGD, EED, PRC2_SETD2 • CDKN2SA, RB1, GATA3, JAK1, PTEN
Coustan-Smith et al, Lancet Oncology 2009 Woord, et. al., ASH 2015
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Targeting JAK/STAT in ETP ETP 12 Absolute Blast Count x 10 in Spleen
Control RuxDay 0 Day 7 Day 14 Day 21 Day 28
500
100
ETP 12 Absolute Blast Count Peripheral Blood
500
1,500
6
300
2,500Ruxolitinib
Control
p <0.01 p <0.01
ETP 13 Absolute Blast Count x 10 in Spleen
Control RuxDay 0 Day 7 Day 14 Day 21 Day 28
250
50
ETP 13 Absolute Blast Count Peripheral Blood
400
1,000
6
150
1,600 Ruxolitinib
Control
p <0.01
p <0.01
ETP 14 Absolute Blast Count x 10 in Spleen
Control RuxDay 0 Day 7 Day 14 Day 28
300
100
ETP 14 Absolute Blast Count Peripheral Blood
500
2,500
6
2001,500
Ruxolitinib
Control
p <0.01p <0.01
Maude, et. al. Blood 2015
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Clonal Evolution
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• Ma, et. al. Nat Commun. 2015
Clonal Evolution
Sometimes, evolution stinks
Frequently mutated pathways at relapse Ras signaling (65%) JAK-STAT signaling (25%) Epigenetic modification (65%) Cell cycle regulation (60%) B-cell development (85%) Nucleoside metabolism (45%)
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0.0 0.5 1.0 1.5 2.0 2.50
20000
40000
60000
80000
Matched Relapsed Sample
Trametinib
Control
P=0.005
Weeks
Ab
solu
te b
last
co
un
t p
er µ
L
0.0 0.5 1.0 1.5 2.0 2.50
10000
20000
30000
Matched Diagnosis Sample
Trametinib
Control
P=NS
Weeks
Ab
solu
te b
last
co
un
t p
er µ
L
MEK inhibition in relapsed ALL
Jones, et. al., Blood 2015
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NT5C2 activating mutations • Mutations NT5C2
– ~19% relapsed T-ALL (Tzoneva, et al Nat Med 2013)
– ~20% early relapse B-ALL (Meyer, et al Nat Gen 2013)
– Resistance to nucleoside analogues: 6MP and 6TG
0
200000
400000
600000
800000
1000000
1200000
SPN Diagnosis vs Relapse Blood
R-Veh
R-6MP
R-Cyt
D-Veh
D-6MP
D-Cyt
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Immunotherapies
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CAR T cell Engineering
Lentiviral vector
T cell
CD19
Native TCR
Tumor cell
CTL019 cell
Dead tumor cell
Anti-CD19 CAR construct
• T cells collected from patient
• Lentiviral vector introduces gene encoding CAR
• CAR links extracellular antibody to intracellular T cell signaling domains
• T cells expanded ex vivo
• Reinfused come in contact with antigen engage CAR cytotoxic response and in vivo proliferation
• Persistent CTL019 cells may allow long-term disease control
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93CAR T cells effective in r/r ALL
• 60 r/r Pediatric ALL patients – 93% CR rate (56/60)
– 12 mo RFS: 60%; 12 mo OS: 79%
– 24 mo RFS: 53%; 24 mo OS: 61%
– 98% of pts have CTL019 detectable in CSF
>200 patients with CLL, ALL, NHL, MM have received CTL019
Grupp/Maude
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1.0E+06
1.0E+07
1.0E+08
1.0E+09
1.0E+10
1.0E+11
1 2 3 5 6 7 13 16 21Days
Time Course of Nalm-6 Expansion and Distribution Using Bioluminescence
Barrett
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Preclinical Models to Test Efficacy
19-z Saline
Day 7 Day 10
72 hours after single T cell infusion
19-z Saline
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5.0E+05
2.1E+07
4.1E+07
6.1E+07
8.1E+07
1.0E+08
1.2E+08
1.4E+08
1.6E+08
1.8E+08
2 hours 24 hours 48 hours 72 hours
Photo
ns/s
econd/c
m2
mock
meso-41BB-zeta
19-41BB-zeta
19-28-41BB-zeta
20-28-stop
19-41BB-zeta/20-28-stop
Saline
p/s/c
m2/sr
Mock
Meso-41BB-z
19-41BB-z
19-28-41BB-z
20-28-*stop
19-41BB-z + 20-28-*stop
Saline
Compare T cell Migration & Expansion
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Compare Different Co-stimulatory Domains
Milone, et. al. Molecular Therapy 2009
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Compare cell culturing methods
CD3/CD28 beads vs OKT3 and IL2 CD3/CD28 bead stimulated cells Proliferated earlier More effective Longer telomeres Central memory phenotype Effective against re-challenge
Barrett, et. al. Cytotherapy 2014
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Epitope Matters
Haso, et. al. Blood 2013
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1.00E+00
1.00E+01
1.00E+02
1.00E+03
1.00E+04
1.00E+05
1.00E+06
1.00E+07
1.00E+08
1.00E+09
1.00E+10
1.00E+11
1.00E+12
Day 5 Day 8 Day 14 Day 18 Day 21 Day 27 Day 34
saline
19-41bb-zeta
*
* * * *
Saline
19-41BB-z
Day 5 8
A
B
C
mRNA Transfected CAR+ T cells Effective
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Overcoming CD19 escape
Ruella, et. al. JCI 2016
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Toxicity
• Cytokine Release Syndrome (CRS) – Correlates with T cell proliferation and efficacy
– Severity related to disease burden
– Reversed with novel approach – cytokine blockade
• Tumor Lysis Syndrome – Not a prominent feature, but may be with high WBC
• Neurotoxicity – Seen in several CD19 immunotherapy trials: NCI,
CHOP/UPENN, MSKCC, Blinatumomab – In our experience - generally untreated, fully resolves
• Chronic B cell aplasia requiring IgG replacement
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Cytokine profile: 30 days
10
50100
5001000
500010000
GCSFpk35
0−3 4−5
p<0.001 125
102050
100200500
GMCSFpk35
0−3 4−5
p<0.0015
10
50100
5001000
500010000
IFGpk35
0−3 4−5
p<1e−05 20
50
100
200
IFNApk35
0−3 4−5
p<0.001 51020
50100200
50010002000
IL10pk35
0−3 4−5
p=0.001
50100200500
100020005000
100002000050000
IL1RApk35
0−3 4−5
p=0.0012
5
10
20
50
100
200
IL4pk35
0−3 4−5
p<0.001 1
100
10000
IL6pk35
0−3 4−5
p<1e−07 10
50100
5001000
500010000
IL8pk35
0−3 4−5
p<1e−07 5e+011e+02
5e+021e+03
5e+031e+04
5e+041e+05
IP10pk35
0−3 4−5
p<1e−06
5e+021e+032e+03
5e+031e+042e+04
5e+041e+052e+05
MCP1pk35
0−3 4−5
p<1e−05 10
50100
5001000
500010000
MIGpk35
0−3 4−5
p<1e−05 50100200
50010002000
5000
MIP1Bpk35
0−3 4−5
p<0.00120
50
100
200
500
1000
MIP1apk35
0−3 4−5
p<1e−04 12
51020
50100
TNFApk35
0−3 4−5
p<1e−04
0.51.02.0
5.010.020.0
50.0100.0
VEGFpk35
0−3 4−5
p<1e−04
2e+05
3e+05
4e+05
5e+05
sgp130pk35
0−3 4−5
p<0.001100
200
500
sIL_1RIpk35
0−3 4−5
p<1e−045e+031e+042e+04
5e+041e+052e+05
5e+05
sIL_1RIIpk35
0−3 4−5
p<1e−055e+021e+032e+03
5e+031e+042e+04
5e+041e+052e+05
IL2RApk35
0−3 4−5
p<1e−07
2e+04
5e+04
1e+05
2e+05
sIL_6Rpk35
0−3 4−5
p<1e−05 50
100
200
500
1000
sRAGEpk35
0−3 4−5
p<0.001 1000
2000
5000
10000
20000
sTNFRIpk35
0−3 4−5
p<1e−051e+04
2e+04
5e+04
1e+05
2e+05
5e+05
sTNFRIIpk35
0−3 4−5
p<1e−08
1e−01
1e+00
1e+01
1e+02
1e+03
BFGFpk35
0−3 4−5
p=0.642 5e−011e+00
5e+001e+01
5e+011e+02
5e+021e+03
EGFpk35
0−3 4−5
p=0.942
50
100
200
Eotaxinpk35
0−3 4−5
p=0.041200
500
1000
2000
5000
10000
HGFpk35
0−3 4−5
p=0.0150
100
200
500
IL12pk35
0−3 4−5
p=0.117
2
5
10
20
50
100
IL13pk35
0−3 4−5
p=0.0235
10
50100
5001000
500010000
50000
IL15pk35
0−3 4−5
p=0.0062
5
10
20
50
100
IL17pk35
0−3 4−5
p=0.1 5e−011e+00
5e+001e+01
5e+011e+02
5e+021e+03
5e+03
IL1Bpk35
0−3 4−5
p=0.282 1
510
50100
5001000
IL2pk35
0−3 4−5
p=0.011
0.5
1.0
2.0
5.0
10.0
20.0
50.0
100.0
200.0
IL5pk35
0−3 4−5
p=0.017 0.5
1.0
2.0
5.0
10.0
20.0
50.0
100.0
200.0
IL7pk35
0−3 4−5
p=0.011 500
1000
2000
5000
10000
20000
50000
RANTESpk35
0−3 4−5
p=0.397 1
2
5
10
20
50
100
200
500
sCD30pk35
0−3 4−5
p=0.421 40000
60000
80000
100000
120000
140000
sEGFRpk35
0−3 4−5
p=0.731
200
300
400
500
600
700800900
sIL_4Rpk35
0−3 4−5
p=0.127
50
100
200
500
1000
2000
5000
10000
20000
sVEGFR1pk35
0−3 4−5
p=0.397
10000
20000
50000
sVEGFR2pk35
0−3 4−5
p=0.6992000
5000
10000
20000
sVEGFR3pk35
0−3 4−5
p=0.003
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10
50100
5001000
500010000
GCSFpk35
0−3 4−5
p<0.001 125
102050
100200500
GMCSFpk35
0−3 4−5
p<0.0015
10
50100
5001000
500010000
IFGpk35
0−3 4−5
p<1e−05 20
50
100
200
IFNApk35
0−3 4−5
p<0.001 51020
50100200
50010002000
IL10pk35
0−3 4−5
p=0.001
50100200500
100020005000
100002000050000
IL1RApk35
0−3 4−5
p=0.0012
5
10
20
50
100
200
IL4pk35
0−3 4−5
p<0.001 1
100
10000
IL6pk35
0−3 4−5
p<1e−07 10
50100
5001000
500010000
IL8pk35
0−3 4−5
p<1e−07 5e+011e+02
5e+021e+03
5e+031e+04
5e+041e+05
IP10pk35
0−3 4−5
p<1e−06
5e+021e+032e+03
5e+031e+042e+04
5e+041e+052e+05
MCP1pk35
0−3 4−5
p<1e−05 10
50100
5001000
500010000
MIGpk35
0−3 4−5
p<1e−05 50100200
50010002000
5000
MIP1Bpk35
0−3 4−5
p<0.00120
50
100
200
500
1000
MIP1apk35
0−3 4−5
p<1e−04 12
51020
50100
TNFApk35
0−3 4−5
p<1e−04
0.51.02.0
5.010.020.0
50.0100.0
VEGFpk35
0−3 4−5
p<1e−04
2e+05
3e+05
4e+05
5e+05
sgp130pk35
0−3 4−5
p<0.001100
200
500
sIL_1RIpk35
0−3 4−5
p<1e−045e+031e+042e+04
5e+041e+052e+05
5e+05
sIL_1RIIpk35
0−3 4−5
p<1e−055e+021e+032e+03
5e+031e+042e+04
5e+041e+052e+05
IL2RApk35
0−3 4−5
p<1e−07
2e+04
5e+04
1e+05
2e+05
sIL_6Rpk35
0−3 4−5
p<1e−05 50
100
200
500
1000
sRAGEpk35
0−3 4−5
p<0.001 1000
2000
5000
10000
20000
sTNFRIpk35
0−3 4−5
p<1e−051e+04
2e+04
5e+04
1e+05
2e+05
5e+05
sTNFRIIpk35
0−3 4−5
p<1e−08
Activated T cells
Activated Macrophages
Chemotactic for Macrophages Tissue Damage and Inflammation
Negative Regulators
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CRS = ?MAS/HLH
Cytokine level by CRS grade
pg/m
L
IFG
pk3
5
IL1
0p
k3
5
IL6
pk3
5
IL8
pk3
5
IP1
0p
k3
5
MC
P1
pk3
5
MIG
pk3
5
MIP
1B
pk3
5
IL2
RA
pk3
5
GM
CS
Fp
k3
5
TN
FA
pk3
5
IL1
2p
k3
5
IL1
3p
k3
5
IL1
7p
k3
5
IL1
Bp
k3
5
IL2
pk3
5
IL4
pk3
5
IL5
pk3
5
IL7
pk3
50
50000
100000
150000
●●
●
●●
●
●●●●●●●
●
●●●●●●●●●●●●●●●
●
●
●
●
●
●
●
●●
●●
●
●
●
●
●
●
●
●
●
●
●●
●
●●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●
●
●●●
●
●
●●
●
●●
●●●●●●●●●●●●●●
●
●
●
●
●
●
●
●
●
●
●
●
●
●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●●
●
CRS grade 0−3
CRS grade 4−5
* Holm Significance
* * * * * * * * * * * *
Splenomegaly Gr 0-3: 0 of 25 pts Gr 4-5: 5 of 10 pts Hepatomegaly Gr 0-3: 0 of 25 pts Gr 4-5: 7 of 10 pts Fibrinogen <150mg/dl Gr 0-3: 2 of 15 pts Gr 4-5: 9 of 10 pts
Teachey, et.al., Cancer Discovery 2016
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CRS Prediction
sgp130+IFNg+IL1RA IFNg + IL13 + MIP1a
Combined cohort Pediatric cohort
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CRS: Different CARs
Turtle, et.al, JCI 2017
Davilla, et.al., Science Trans Med 2014
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Tocilizumab and CRS after CTL019
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Different drugs to block cytokines
• IL-1a: Anakinra
• IL2R (CD25): Basiliximab
• IL6: Siltuximab
• IL6R: Tocilizumab
• TNFa: Etanercept, Infliximab
• MCP1, MIP1b, sgp130, IFNg: Clinical trials
• Jak/Stat: Ruxolitinib, Tofacitinib, others
• BTK: Ibrutinib
• Corticosteroids
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MCL NSG model of CRS
Ruella, et. al. Leukemia 2017
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Immunotherapy for B-ALL
B-ALL
• Naked Monoclonals • Rituximab
• Epratuzumab
• Conjugated Monoclonals • Inotuzumab
• Moxetumomab
• BiTEs • Blinatumomab
• CARs
T-ALL
• UM…..
![Page 42: Using Mouse Models of Acute Lymphoblastic Leukemia …tumor-models.com/wp-content/uploads/sites/67/2017/07/David-Teachey.pdfDismal Outcome for 2nd+ Relapse of ALL ... PAKVKK NUP214-ABL1](https://reader031.vdocuments.us/reader031/viewer/2022030409/5a9277ef7f8b9a8b5d8bfc36/html5/thumbnails/42.jpg)
CD5 CAR T cells
Mamonkin, et al, Blood 2015 CD5 quickly down-regulated in normal T cells
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Daratumumab
0
25000
50000
75000
T-A
LL
cells x
10e6 in
blo
od p= 0.0112
0
50
100
150
T-A
LL
cells x
10e6 in
sp
leen p = 0.0003
Peripheral blood blasts Splenic blasts
Karen Bride
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Thanks
• Stephan Grupp • David Barrett • Stephen Hunger • Jim Whitlock • Mignon Loh • Elizabeth Raetz • William Carroll • Mini Devidas • Terzah Horton • Michelle Hermiston • Brent Wood • Patrick Zweidler-Mckay • Karen Rabin • Richard Lock • Charles Mullighan • Cheryl Willman • Richard Harvey • Peter Adamson • Malcolm Smith • Stuart Winter • Kim Dunsmore • John K. Choi • Jos Melenhorst • Simon Lacey • Pam Shaw • Sara Tasian
Teachey Lab • Shannon Maude • Tiffaney Vincent • Junior Hall • Theresa Ryan • Karen Bride • Tori Fuller • Abanoub Gab