Using Mouse Models of Acute Lymphoblastic Leukemia to Test Novel Therapies

David T. Teachey, MD

Tumor Models Boston 2017

July 20, 2017

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

Hunger S P et al. JCO 2012;30:1663-1669

©2012 by American Society of Clinical Oncology

ALL OS: COG studies

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

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

NSG Xenograft Model of ALL

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

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

Targeted Therapies

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.

Ph-like ALL

Roberts, et. al. NEJM 2014

12.6% 3.9%/7.4% 50% 12.6% 4.3% 9%

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

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

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

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

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

Clonal Evolution

• 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%)

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

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

Immunotherapies

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

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

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

Preclinical Models to Test Efficacy

19-z Saline

Day 7 Day 10

72 hours after single T cell infusion

19-z Saline

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

Compare Different Co-stimulatory Domains

Milone, et. al. Molecular Therapy 2009

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

Epitope Matters

Haso, et. al. Blood 2013

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

Overcoming CD19 escape

Ruella, et. al. JCI 2016

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

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

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

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

●●

●

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●

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●

●●●●●●●●●●●●●●●

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●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ●●●●●●●●●●●●●●

●

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

CRS Prediction

sgp130+IFNg+IL1RA IFNg + IL13 + MIP1a

Combined cohort Pediatric cohort

CRS: Different CARs

Turtle, et.al, JCI 2017

Davilla, et.al., Science Trans Med 2014

Tocilizumab and CRS after CTL019

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

MCL NSG model of CRS

Ruella, et. al. Leukemia 2017

Immunotherapy for B-ALL

B-ALL

• Naked Monoclonals • Rituximab

• Epratuzumab

• Conjugated Monoclonals • Inotuzumab

• Moxetumomab

• BiTEs • Blinatumomab

• CARs

T-ALL

• UM…..

CD5 CAR T cells

Mamonkin, et al, Blood 2015 CD5 quickly down-regulated in normal T cells

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

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