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Part 1: Targeting Cancer Pathways

Tumor Resistance

October 22, 2014

Sponsored by:

Brought to you by the Science/AAAS Custom Publishing Office

Participating Experts

Michael B. Yaffe, M.D., Ph.D.

MIT

Cambridge, MA

Jeffrey Engelman, M.D., Ph.D.

Harvard Medical School

Boston, MA

Michael Deininger, M.D., Ph.D.

University of Utah

Salt Lake City, UT

October 22, 2014

Sponsored by:

Webinar Series


Tumor Resistance

FASEB - 2014

Dynamic Re-Wiring of Signaling Networks as Mechanisms for

Improving Combination Therapy for Cancer

Michael B. Yaffe

Koch Institute for Integrative Cancer Biology

Depts of Biology & Biological Engineering

Broad Institute & MIT

Dept. of Surgery, Beth Israel Deaconess Med Ctr,


FASEB - 2014

Dynamic Re-Wiring of Signaling Networks as Mechanisms for

Improving Combination Therapy for Cancer

Michael B. Yaffe

Koch Institute for Integrative Cancer Biology

Depts of Biology & Biological Engineering

Broad Institute & MIT

Dept. of Surgery, Beth Israel Deaconess Med Ctr,


Protein kinases

Growth Factor receptors

DNA Damage

RNA-Binding Proteins

cytokines

Signaling networks

Signaling and Systems Biology are the ‘Missing Data’ that links Genotype

to Phenotype…Mutational spectra to tumor responses…..

Yaffe MB Science Signaling 2013

Why Use Systems Biology of Signaling to Treat Cancer?

1. Targeted monotherapies for cancer, including EGFR inhibitors, B-Raf inhibitors, and ALK inhibitors do not cure the disease. They target signaling molecules and result in impressive remission of the disease, but ultimately the disease recurs in nearly all patients as the tumors develop resistance. 2. Most forms of combination chemotherapy for cancer are not synergistic. Instead, most common drug combinations function by targeting heterogeneity with the tumor cell population – they represent ‘de-personalized’ medicine. However, these combinations have the advantage of non-overlapping toxicities.

3. Systems Biology is the key to (1) identifying new nodes in clinically relevant pathways; (2) designing and optimizing effective synergistic combination therapies; (3) Predicting patients who will respond to a drug, at least initially; (4) developing approaches to minimize development of chemo-resistance.

TWO KEY CONCEPTS: SYNTHETIC LETHALITY and DYNAMIC NETWORK RE-WIRING.

Static Versus Dynamic Network Rewiring

Dynamic network re-wiring is bad for molecularly targeted therapies alone

Wagle et al., J. Clin. Oncol. 2011

Static Versus Dynamic Network Rewiring

Dynamic network re-wiring is bad for molecularly targeted therapies alone

But it can be beneficial for combination chemotherapy

using molecularly targeted drugs PLUS DNA damaging cytotoxic agents…

Targeted therapies

Conventional DNA-damaging chemotherapy

Mike Lee

Combination Drug Screen in Breast Cancer

EGFR over-expression

(30% overall; 45-75% TNBC)

“TRIPLE-NEGATIVE” =

No ER expression

No PR expression

No HER2 amplification

Luminal

(A and B)

48 – 78 %

HER2

10-30%

TNBC

15-20%

Combination Drug Screen for Triple Negative Breast Cancer

Erlotinib (EGFR)

Gefitinib (EGFR)

Lapatinib (EGFR/HER2)

MM-121 (ErbB3)

PD98059 (MEK)

BMS-345541 (NF-kB)

Rapamycin (mTOR)

NVP-BEZ235 (PI3K/mTOR)

Wortmannin (PIKKs)

IR

Camptothecin

CDDP

Etoposide

Doxorubicin

Temozolomide

Taxol

Erlotinib (EGFR)

Gefitinib (EGFR)

Lapatinib (EGFR/HER2)

MM-121 (ErbB3)

PD98059 (MEK)

BMS-345541 (NF-kB)

Rapamycin (mTOR)

NVP-BEZ235 (PI3K/mTOR)

Wortmannin (PIKKs)

IR

Camptothecin

CDDP

Etoposide

Doxorubicin

Temozolomide

Taxol

Drug1

Drug2 Time course

Start End

a

Signaling inhibitors DNA Damage

Apoptotic Response at 8 hours after doxorubicin treatment

Efficacy of EGFR Inhibition in BT-20 TNBC Cells

Depends on Timing of Drug Delivery

Subtype Dependent Responses to Treatment

Luminal

(A and B)

48 – 78 %

HER2

7-12%

TNBC

15-20% %

Ap

op

totic C

ells

40

BT-20 MDA-MB-453

(TNBC) (HER2 OE)

MCF7 Hs578Bst

(Luminal) (Normal) 45

20

5

% A

po

pto

tic C

ells

DMSO ERL DOX D/E E D D E DMSO ERL DOX D/E E D D E

DMSO ERL DOX D/E E D D E DMSO ERL DOX D/E E D D E

0 0

0 0

6

0

-6

0 25

(2097 DEGs)

BT-20 (TNBC)

24 hours Erlotinib

Lo

g2 (

Mea

n D

iff. E

xpre

ss.)

B Score

MDA-MB-468

BT-20 HCC-1143

Hs578-T MDA-MB-231

HCC-38

BT-549 MDA-MB-436

MDA-MB-157 HCC-1500

DM

SO

E

RL

DO

X

D/E

E

D

DE

DM

SO

E

RL

DO

X

D/E

E

D

DE

DM

SO

E

RL

DO

X

D/E

E

D

DE

Apoptosis

(% at 8 hours)

Apoptosis

at 8 hours (rel. to DOX)

c-caspase-8

at 8 hours (rel. to DOX)

EG

FR

p-E

GF

R un

treat

ed

PROLIFERATION

STAT

CDK

INHIB.

BCL2

FAM.

CDK

Cyclin

EGFR HER2

DNA DAMAGE

GROWTH FACTOR RECEPTORS

IL-6R

CYTOKINE RECEPTORS

TNFR

DEATH RECEPTORS

AUTOPHAGY APOPTOSIS CELL CYCLE ARREST/DNA

REPAIR

ATM ATR

CHK2 CHK1 MK2

p38

JAK

H2A.X

HSP27

PI3K

PDK1

AKT

RAS

RAF

MEK

ERK

mTOR

S6K

S6

4EBP1

STRESS

RAC

MEKK1

JNK

p53

DUSP

CASP1

NON-APOPTOTIC

DEATH

CASP3 ATG8 ATG

5/7/12

BECN1

VPS34 VPS15

CASP8 CASP9

CASP6

DRAM

TRAF2

TRAF6

IKK

IKB

NF-KB

PUMA

DAPK

SMAC

LKB1

AMPK

XIAP

HIS H3

BRCA1 FANC

D2

53BP1

MRN

WEE1

CDC25 MYC

DNA-

PK

XRCC

ATRIP

RPA

RSK GADD

45

PLK1

9-1-1

MDC1

PKC

ABL

IL-18R

RIP1

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

-7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7

BT20

MCF7

MDA453

DMSO TAR

DOX D/T

T D D T

time

Principle Component 1

Pri

ncip

le C

om

po

ne

nt

2

cCASP8 cCASP6

pDAPK1

pH2AX

f


Pri

ncip

le C

om

po

ne

nt

2


Prin

cip

le C

om

po

ne

nt

2

c pHSP27

pJNK DAPK2

DUSP6

BIM

cCASP9 pDAPK1

-4

-3

-2

-1

0

1

2

3

4

-8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8


Pri

ncip

le C

om

po

ne

nt 2

DMSO TAR

DOX D/T

T D D T

time

BT20

b

Understanding “Dynamic Re-wiring”

Lee, MJ et al. (2012) Cell

Gene Expression Profiling Putative Response Network Collect Large Dataset of Treatment Responses

Data-driven Modeling Identify EGFR-driven Subset Confirm Utility of Treatment Strategy In vivo

DNA DAMAGE

RTK

(EGFR)

ONCOGENIC

SIGNATURE

CASP8

CASP3

CASP9

DEATH

DNA DAMAGE

ONCOGENIC

SIGNATURE

CASP8

CASP3

CASP9

DEATH

ERLOTINIB RTK

(EGFR)

Working Model

TNBC before Erlotinib treatment TNBC chronically treated with Erlotinib

Testing Time-Staggered Inhibition In Vivo

Collaboration with Paula Hammond’s Lab: Nanoparticle

Development for Time-Staggered Drug Delivery in vivo

Erlotinib Polylactic co-glycolic acid (PLGA)

Erlotinib

Stephen Morton, Mike Lee

Doxil®

Small Molecule Inhibitor

Hydrophilic Cytotox

Liposomal Delivery Vehicles

Doxorubicin Erlotinib

Doxil®

Small Molecule Inhibitor

Hydrophilic Cytotox

Liposomal Delivery Vehicles

Doxorubicin Erlotinib

0 25 50 75 100 125 1500

20

40

60

80

100

Dox - conjugate

Tar

%

Rele

ase

Erlotinib

Liposomal Formulation

Mean dh (nm)

PDI ζ-Potential (mV)

Cytotox:Inhibitor Mass Loading Ratio

DFP 156 0.1 -20 N/A

DEFP 151 0.16 -20 3:2

Folate/PEG Decorated Combo Liposomes

Combination Erl-Dox Nanoparticles in vivo

Erlotinib

Doxorubicin + Erlotinib

Doxorubicin

Dynamic Network Rewiring through Time-Staggered

EGFR Inhibition also kills NSCLC tumors

A549

0 10 20 300.1

1

10

DEFPDFPuntreated

days

Fo

ld L

um

ine

sc

en

ce

Sig

na

l

[No

rma

lize

d t

o p

re-i

nje

cti

on

]

BT-20

0 10 20 300.01

0.1

1

10

DFPDEFP

untreated

days

Fo

ld L

um

ine

sc

en

ce

Sig

na

l

[No

rma

lize

d t

o p

re-i

nje

cti

on

]

Dynamic Network Rewiring through Time-Staggered

EGFR Inhibition also kills NSCLC tumors

0

4

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

popto

sis

Rel. A

ctivity

DMSO LAP DOX D/L L--D D--L0

10

20

30

40

50

0

4

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

po

pto

sis

Rel. A

ctivity

DMSO ERL DOX D/E E--D D--E0

10

20

30

40

50

! "

! #! ! $"

! #! %"

! #! %$"

! #! &"

%" &" ' " ( " $" ) " *" +"DMSO LAP DOX L/D L--D D--L

5

15

25

35

45

0

2

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

pop

tosis

Rel. A

ctivity

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! #! ! $"

! #! %"

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! #! &"

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5

15

25

35

45

0

2

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

pop

tosis

Rel. A

ctivity

! "

! #! $"

! #! %"

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! #! ' "

$" %" &" ' " ( " ) " *" +"DMSO LAP DOX L/D L--D D--L

0

10

20

30

40

50

0

4

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

popto

sis

Rel. A

ctivity

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10

20

30

40

50

0

4

actin

c-c8

0 .25 .5 1 2 4 6 8 hours

0 .25 .5 1 2 4 6 8 hours

% A

po

pto

sis

Rel. A

ctivity

ERLOTINIB

(EGFR)

LAPATINIB

(HER2/EGFR)

BT-2

0

(TN

BC

)

MB

A-M

B-4

53

(HE

R2)

BT-4

74

(HE

R2

)

Generalizing Time-Staggered Inhibition of RTK

Signaling for Tumor Sensitization

! "

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012"

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, 40"

055, "

, 550"

DMSO

ERL or LAP DOX

D/E or D/L E D or L D

D E or D L

Conclusions

1. The EGFR pathway cross-talks with the DNA damage response

pathway in a subset of TNBC cells and NSCLC cells to suppress an

extrinsic apoptotic pathway, limiting the efficacy of cytotoxic

chemotherapy.

3. The concept of dynamic re-wiring can shift the focus from drug

development to novel approaches to drug delivery…creating new

IP for old drugs.

2. Signaling pathways in cancer cells can be “dynamically re-wired”

to enhance cell killing by DNA damage. The underlying mechanisms,

along with biomarkers for patient selection and response can be

obtained using systems biology approaches to combination therapy.

4. We need to test these systems-based insights about dynamic

network modulation for optimizing combination therapies using

kinase inhibitors and DNA damaging agents in the clinic.

Acknowledgements

Funding

NIH NCI (ICBP) NIGMS, NIEHS, DOD

Mike Lee Stephen Morton

Albert Ye

Alexandra Gardino

Anne Margriet Heijink

Andrea Tentner

Gerry Ostheimer

Collaborators

MIT

Paula Hammond

Doug Lauffenburger

HMS

Peter Sorger

Gavin MacBeath




MIT

Cambridge, MA



Boston, MA


University of Utah

Salt Lake City, UT

October 22, 2014

Sponsored by:

Webinar Series


Tumor Resistance

Resistance to Tyrosine Kinase Inhibitors in Lung Cancer

Jeffrey Engelman, MD, PhD

Massachusetts General Hospital

Feb 2010, Baseline Dec 2010, TKI response July 2011, Resistance

Cancers with EGFR mutations are highly sensitive to EGFR kinase inhibitors

Lynch et al, NEJM 2004

Lux-Lung 2

Exon 19 Deletion

L858R

Pre-Rx Post-Rx (6 mo)

Cancers with ALK translocations are highly sensitive to ALK kinase inhibitors

~250 kb ~300 kb

t(2;5) ALK gene

breakpoint region

2p23 region

3’ 5’

Shaw et al JCO 2009, Kwak et al NEJM 2010

Pre-rx Post-rx (2 mo)

Acquired resistance to targeted therapies Baseline Response Resistance

EML4-ALK lung cancer

Cancer Drug Median Duration of

Response (months)

EGFR mutant lung cancers gefitinib/erlotinib 11

EML4-ALK lung cancers ALK inhibitors (crizotinib) 8-10

BRAF mutant melanomas BRAF + MEK inhibitors (dabrafenib and trametinib )

9

HER2 amplified breast cancer lapatinib 9

FLT3 AML quizartinib 3

CKIT GIST imatinib 20

Sensitive

Downstream signaling (PI3K and MEK)

Cell growth/ Survival



Sensitivity to tyrosine kinase inhibitors

(mutant EGFR or EML4-ALK)

Engelman et al, Science, 2007 n

on

gefitinib

HCC827 (EGFR exon 19)

Sensitive Resistant





Resistance to tyrosine kinase inhibitors



*

EGFR T790M ALK L1196M ALK G1269A ALK G1206Y ALK G1202R ALK 1151 ins

Mutation/ Amplification



MET amplification HGF/MET activation

HER2/HER3 activation IGF-IR activation PIK3CA mutation

BRAF mutation EGFR activation

C-KIT amplification

Bypass Tracks


EMT SCLC

Loss of BIM

Cell growth and/or Survival

Defect growth arrest/apoptosis

EGFR EML4-ALK

Sensitive Resistant








*








C-KIT amplification

Bypass Tracks


EMT SCLC

Loss of BIM



MORE POTENT INHIBITORS: CLO-1686, AZD9291 LDK378, CH5424802

Sensitive Resistant








*








C-KIT amplification

Bypass Tracks


EMT SCLC

Loss of BIM



COMBINATIONS: e.g., MET and EGFR inhibitors

ALK

mut

ALK

amp

No ALK

amp or mut

ALK+

Unknown

Bypass

tracks

EGFR

CKIT

About One-Third of Crizotinib-Resistant

Tumors Harbor ALK Resistance Mutations

Courtesy of Alice Shaw

Results from Repeat Biopsy Program

T790M 52% alone 42%

with EGFR amp 10%

No identified AR mechanism 26%

BRAF 2%

MET amp 5% SCLC 8% with EGFR amp 1%

alone 4%

with PI3K 3%

EGFR Amp 15% with T790M 10%

alone 4%

with SCLC 1%

PI3K 5% with SCLC3%

alone 2%

unpublished data, Lecia Sequist Sequist et al, Science Translational Medicine, 2011

Katyama, Shaw, et al, Science Translational Medicine, 2012

N=106

Heterogeneity of resistant clones within individual patients explain paradoxical

clinical findings

Serial Biopsies Reveal: Dynamic Populations of Different Clones

L858R PIK3CA

Histology

EGFR TKI

status

Tumor

Burden

Treatment

Timeline 2007 2008 2009 2010

Sensitive Resistant Sensitive

Genotype L858R

TP53

L858R

TP53 T790M

L858R

TP53

Adeno Adeno Adeno

Erlotinib Chemo Chemo Chemo Erlotinib*

Sequist et al, Sci Transl Med 2011

Serial Biopsies Reveal Fluctuating Dynamics of Cell Populations

L858R PIK3CA

Sequist et al, Sci Transl Med 2011

NO T790M

Pre-treatment

“Sensitive”

Sensitive

again

Resistant

D/C erlotinib

“FLARE”

Rx erlotinib

Post-treatment

“Response”

Rx erlotinib

Resistant

Rx erlotinib

+ T790M

Multiple Populations in a Single Tumor Nodule: “Microscopic heterogeneity”

Sensitive

Resistant

Resistant

“persistor cells”

Pre-treatment

“Sensitive”

Post-treatment

“Response”

Rx erlotinib

Resistant

Rx erlotinib

+ T790M

Each patient may have his/her own “pie chart” of resistance mechanisms

Sensitive

Resistant

Resistant

T790M 52% alone 42%

with EGFR amp 10%

No identified AR mechanism 26%

BRAF 2%

MET amp 5% SCLC 8% with EGFR amp 1%

alone 4%

with PI3K 3%

EGFR Amp 15% with T790M 10%

alone 4%

with SCLC 1%

PI3K 5% with SCLC3%

alone 2%

ARE WE FAILING TO FULLY SUPPRESS THE TARGET?

Green cells staying alive because ALK is not fully suppressed

# ##

Antitumor Efficacy of Ceritinib

NSCLC with prior ALKi

NSCLC ALKi naïve

Ch

an

ge

fro

m b

ase

line

in

su

m o

f lo

ng

est d

iam

ete

rs (

%)

*Patients with measurable disease at baseline and at least 1 post baseline assessment

without unknown response for target lesion or overall response

N=228*

#

#

#

#

#

# #

#

#

# #

# # # # # #

# # # #

# # # # #

# #

# # # # # #

# # #

# # # # # #

# #

# # #

#

# #

# # # # # #

#

#

# #

#

# # # #

# # #

# # # #

# #

# #

#

#

# # # # # #

# # # #

# # # #

# # # #

# # # # # # # #

# #

# # #

# #

# # # #

# #

#PFS event

-100

-80

-60

-40

-20

0

20

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

++

ALK FISH

ALK mutation

PFS on LDK378

(wks)

Best % response

+ + + + + + + + + + + + + + + + + + + +

ALK amplification

22 26 32 34 43 44 45 48 49 49 49 51 52 58 59 60 60 63 63 85

- - - - - - - - - + - - - + - - - - - -

- - - - - - + - - - + + + - + - - - + -

19 71 12 8 36 49 18 29 30 41 31 23 12 18 71 77 21 42 61 39

Ceritinib is Active Against Resistant Tumors

With and Without ALK Resistance Mutations

Decre

ase

fro

m b

ase

line (

%)

ALK

mut

ALK

amp

No ALK

amp or mut

ALK+

Unknown

Bypass

tracks

EGFR

CKIT

Incomplete ALK inhibition may allow minimal

bypass track activation to cause resistance

INCOMPLETE ALK

INHIBITION

Courtesy of Alice Shaw

Baseline

After 8 weeks of crizotinib

After 34 months of crizotinib

WT S1206Y

After 12 weeks of LDK378

After 15 months of LDK378

G1202R EML4-ALK sequence:

Selection of new resistant clones on LDK378

(certinib)

Ba/F3 EML4-ALK V1

0

50

100

S1206Y v1 crizotinib

S1206Y v1 LDK378

0 100001000100101

Drug Concentration (nM)

% C

ell

Via

bili

ty

Ba/F3 EML4-ALK V1

0

50

100G1202R crizotinib

G1202R LDK378

0 100001000100101

Drug Concentration (nM)

% C

ell

Via

bili

ty

Friboulet et al, Cancer Discovery, 2014

Baseline

After 8 weeks of crizotinib

After 34 months of crizotinib

After 12 weeks of LDK378

After 15 months of LDK378

WT S1206Y G1202R EML4-ALK sequence:

Patient Id EML4-ALK sequence

at Crizotinib

Resistance

EML4-ALK sequence

at LDK378

Resistance MGH011 S1206Y G1202R MGH015 WT WT MGH023 WT F1174C MGH034 WT WT MGH049 N/A WT MGH051 WT G1202R MGH057 WT WT MGH061 WT WT JCR013 N/A WT

JCR021 G1269A (right lung) F1174V (left lung) and

G1202R (right lung)

Selection of new resistant clones on LDK378

Friboulet et al, Cancer Discovery, 2014

Autopsies reveals heterogeneity of resistance

mechanisms

T790M

MET amplification

EMT

Adeno T790M

Autopsy #1 Autopsy #2

Science, 2007; Cancer Cell, 2010, Science Translational Medicine, 2011

Develop Regimens: Alternating and Intermittent Therapeutic Combinations

EGFR TKI Current Treatment

Future Regimen

Conclusions

• Resistance to tyrosine kinase inhibitors limits clinical impact

• Resistance can be mediated by mutation of the gene target or activation of bypass track

• Multiple resistant clones can co-exist in a single patient

• Future treatment regimens may require complex combinations to overcome resistance.




MIT

Cambridge, MA



Boston, MA


University of Utah

Salt Lake City, UT

October 22, 2014

Sponsored by:

Webinar Series


Tumor Resistance

55

Teaching Old Dogs New Tricks: Tyrosine

Kinase Inhibitor Resistance due to Mutations

in the Target Kinase

Michael Deininger, MD, PhD

56 Manning et al. Science 2002

518 PTKs

(1.7% of HG

90 TKs (+ 5

pseudogenes)

32 Non-

receptor TKs 58 Receptor

TKs

Several catalytically inactive or

predicted to be inactive

Protein Kinases Regulate Key Cell Functions

Chronic phase Blastic phase

Chronic Myeloid Leukemia

BCR { q11

Ph

9q+

22

9

{ q34

The Philadelphia Chromosome is the Cytogenetic Hallmark of CML

ABL

BCR

ABL ABL

BCR

BCR-ABL Kinase Activity is Central to CML

Pathogenesis

NALM-1 cells (Ph+)

0.1 0.5 1.0 5.0 10

Imatinib (mM)

BCR-ABL-

Deininger et al Blood 1997

BCR - ABL

Imatinib Greatly Improved Survival in Chronic

Phase CML

Quintas-Cardama et al, 2006

BCR-ABL1 Tyrosine Kinase Inhibitors (TKIs)

61

DCC-2036

ponatinib

HG-7-85-01

PPY-A (SGX393-

like)

DCC-2036

62

Inhibitor Binding Conformations

Type II Inhibitor:

INACTIVE

CONFORMATION

(“DFG-out”)

Type I Inhibitor:

ACTIVE

CONFORMATION

(“DFG-in”)

Mechanisms of TKI Resistance

BCR-ABL

Reactivation?

Yes No

Resistance Mutations in BCR-ABL1

O’Hare, et al. Nature Reviews in Cancer (2012)

Preclinical Characterization of Ponatinib

Ile315

Ponatinib

Ile315

Ponatinib Imatinib

O’Hare T, et al. Cancer Cell. 2009;16:401-412.

Ba/F3 BCR-ABL cells ENU mutagenesis

(overnight)

+ ENU

Culture with inhibitor(s)

Monitor for outgrowth

(~28 days) Expand positive wells Sequence BCR-ABL

kinase domain for

mutations

Accelerated Mutagenesis Screen:

Predicting Mutational Resistance to TKIs

Mutation Screening in a T315I Background:

Anticipating Combinations of Mutations

E255V has highest IC50 shift ratio for ponatinib

Native BCR-ABL background BCR-ABL T315I background

O’Hare T, et al. Cancer Cell. 2009;16:401-412.

100 80 60 40 20 0

Native

G250

Q252

Y253

E255

K285

E292

L298

T315

F317

V339

F359

L387

S438

100 80 60 40 20 0

Native

G250

Q252

Y253

E255

K285

E292

L298

T315

F317

V339

F359

L387

S438

100 80 60 40 20 0

Native

G250

Q252

Y253

E255

K285

E292

L298

T315

F317

V339

F359

L387

S438

Fre

qu

en

cy a

mo

ng

re

co

ve

rd c

lon

es (

%)

E H

F H

K

V N V V I I G

C

I F C

V I

* NO CLONES RECOVERED *

Outgrowth

(% of wells)

11.7%

0.2%

0.0%

100 80 60 40 20 0

T315I only

G250

Q252

Y253

E255

E281

K285

I293

F311

I315

L327

F359

A380

H396

100 80 60 40 20 0

T315I

E H

F

H

N K

V K N N

I

V M M

L C

V I

S R P

+

Outgrowth

(% of wells)

40.0%

15.0%

0.8%

0.2%

0.0%

Fre

qu

en

cy a

mo

ng

re

co

ve

rd c

lon

es (

%)

100 80 60 40 20 0

T315I

40 nM (N = 140)

80 nM (N = 71)

160 nM (N = 32)

320 nM (N = 1)

640 nM (N = 0)

100 80 60 40 20 0

T315I only

G250

Q252

Y253

E255

E281

K285

I293

F311

I315

L327

F359

A380

H396

100 80 60 40 20 0

T315I

100 80 60 40 20 0

T315I

H

H K

L S

I

V

H

V

+

+

+

* NO CLONES RECOVERED * E255V

100 80 60 40 20 0

T315I only

G250

Q252

Y253

E255

E281

K285

I293

F311

I315

L327

F359

A380

H396

100 80 60 40 20 0

T315I only

G250

Q252

Y253

E255

E281

K285

I293

F311

I315

L327

F359

A380

H396

100 80 60 40 20 0

T315I only

G250

Q252

Y253

E255

E281

K285

I293

F311

I315

L327

F359

A380

H396

40 nM (N = 0)

20 nM (N = 3)

10 nM (N = 157)

E255V/T315I

Months After First MCyR

Pro

bab

ilit

y o

f R

em

ain

ing

in R

esp

on

se (

%)

0 6 12 18 24 300

20

40

60

80

100

R/I

T315I

Total

N N Lost MCyR

149

104

45

14

0

14

Months After First MaHR

Pro

bab

ilit

y o

f R

em

ain

ing

in R

esp

on

se (

%)

0 6 12 18 24 30 360

20

40

60

80

100

R/I

T315I

Total

N N Lost MaHR

47

37

10

33

6

27

Ponatinib Phase 2 Study: Duration of Response

Duration of MaHR in AP-CML Duration of MCyR in CP-CML

• 21% estimated to maintain

MaHR for at least 2 yrs

(95% CI: 8%, 37%)

• 89% estimated to maintain

MCyR for at least 2 yrs

(95% CI: 82%, 93%)

a

Ponatinib Phase 2 Study: OS in BP-CML and Ph+ ALL

• OS at 2 years in BP-CML: 18%

(median 7 months)

• OS at 2 years in Ph+ ALL: 21%

(median 8 months)

Ph+ ALL BP-CML

Months

Pro

ba

bil

ity

of

OS

(%

)

0 6 12 18 24 30 360

10

20

30

40

50

60

70

80

90

100R/I (N=38)

T315I (N=24)

Total (N=62)

No. at riskTotal

62 32 17 12 9 3 0

Months

Pro

ba

bil

ity

of

OS

(%

)

0 6 12 18 24 30 360

10

20

30

40

50

60

70

80

90

100R/I (N=10)

T315I (N=22)

Total (N=32)

No. at riskTotal

32 15 10 6 4 1 0

Cortez, et al. NEJM (2013)

Ponatinib Resistance

T315I-Inclusive Compound Mutations Confer

Universal TKI Resistance

Zabriskie, et al. Cancer Cell (2014)

Cellular BCR-ABL TKI Sensitivity


Rationalizing Resistance due to E255V/T315I


Forcing BCR-ABL1 to Commit Mutational Suicide

Khorashad, et al. Blood (2013)

Auto-Inhibition of ABL Kinase Activity

Nagar et al., Cell 2003

Allosteric Inhibitors Targeting the Myristoyl

Binding Pocket

Adrian FJ, et al., Nat Chem Biol 2006; Zhang J, et al. Nature. 2010;463:501-506.

Zhang J, et al. Nature. 2010;463:501-506.

Inhibition of T315I in vitro with GNF-5 Plus Nilotinib

100

50

0

0 5 10

Nilotinib/GNF-5 (µM)

Inhib

itory

eff

ect (%

)

GNF-5 + nilotinib (1:1)

Nilotinib

GNF-5

T315I T315I/E505K

10 µM nilotinib

0 0.5 5 10 0 0.5 5 10 GNF-5 (µM)

p-BCR-ABL

BCR-ABL

p-STAT5

E505K = mutation in the

myristoyl binding pocket

T315I T315I/E505K

Acknowledgements

Patrick Gunning

Brent Page

Steven Fletcher

Amie Corbin

Brian Druker

Chris Eide Deininger/ O’Hare Lab

University of Utah

College of Pharmacy Ricardo Baron

Nadeem Vellore

Anna Eiring

Ira Kraft

Matthew Zabriskie

Tony Pomicter

Clint Mason

Johanna Estrada

Kimberly Reynolds

Jamshid Khorashad

Zhimin Gu

Srinivas Tantravahi

David Anderson

Anna Senina

William Heaton

College of Pharmacy



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