Transcript Sledge

Lessons From Clinical Trials of
Targeted Therapies for Cancer
George W. Sledge M.D.
Indiana University
Simon Cancer Center
What is Targeted Therapy?
• Well-defined molecular target
• Target is correlated with tumor biology
• Target is measurable in the clinic, or so
common it doesn’t need to be
• Target is correlated with therapeutic
effect
The HER Family of Receptors
Ligands
TGF-α
EGF
Epiregulin
Betacellulin
HB-EGF
Amphiregulin
No ligandbinding
activity*
Heregulin
Ligandbinding
domain
Tyrosine
kinase
domain
Erb-B1
HER1
EGFR
*HER2 dimerizes with other members of the HER family.
Roskoski. Biochem Biophys Res Commun. 2004;319:1.
Rowinsky. Annu Rev Med. 2004;55:433.
Erb-B2
HER2
neu
Erb-B3
HER3
Heregulin (neuregulin-1)
Epiregulin
HB-EGF
Neuregulins-3, -4
Erb-B4
HER4
Fluorescence In Situ Hybridization Test
Measures HER2 Gene Amplification
Chromosome 17
centromere
HER2 gene
HER2-normal
Ratio <2.0
HER2-amplified
Ratio ≥2.0
• FISH tests are designed to detect amplification of the HER2 gene
PathVysion® PI. Revised May 2004.
Disease-Free Survival
ACTH
87%
85%
ACT
75%
%
67%
ACT
ACTH
N Events
1679
261
1672
134
HR=0.48, 2P=3x10-12
Years From Randomization
B31/N9831
Targets for which Targeted
Therapies exist
• Steroid receptors: for ER+ breast cancer, prostate cancer,
and lymphoma
• HER2: for breast and gastric ca
• ALK: for NSCLC
• CD20: for lymphoma
• bcr/Abl: for CML
• c-Kit: for GIST
• Hedgehog: for basal cell and medulloblastoma
• RET: for medullary thyoid ca
• b-RAF: for melanoma
Sort-of Targeted Therapy
• VEGF-targeted therapies (except renal cell ca)
– rarely drives tumor; hard to predict benefit
• EGFR (colon, lung, H&N ca)
– ras, EGFR mutations
• CMF chemotherapy in high RS breast cancer
– redefining targted therapy?
EGF Receptor:
Role in CRC Therapy
Ligand
Antibodies to EGFR
cetuximab, panitumumab
PI3K
pY
pY
PTEN
pY
pY
RAS
RAF
EGFR-TK
MEK
STAT
AKT
MAPK
mTOR
Gene transcription
Cell-cycle progression
Proliferation
Survival
(anti-apoptosis)
Chemotherapy /
radiotherapy resistance
Angiogenesis
Invasion and
metastasis
Meyerhardt & Mayer, N Engl J Med 2005
Venook, Oncologist 2005
Progression-free survival by treatment within KRAS groups
Mutant – 7.4 vs
7.3 weeks
Wild type –
12.3 vs. 7.3
weeks
P= <0.0001
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Copyright © American Society of Clinical Oncology
Oncotype DX 21 Gene
Recurrence Score (RS) Assay
16 Cancer and 5 Reference Genes From 3 Studies
PROLIFERATION
Ki-67
STK15
Survivin
Cyclin B1
MYBL2
ESTROGEN
ER
PR
Bcl2
SCUBE2
GSTM1
INVASION
Stromolysin 3
Cathepsin L2
HER2
GRB7
HER2
RS = + 0.47 x HER2 Group Score
- 0.34 x ER Group Score
+ 1.04 x Proliferation Group Score
+ 0.10 x Invasion Group Score
+ 0.05 x CD68
- 0.08 x GSTM1
- 0.07 x BAG1
BAG1
CD68
REFERENCE
Beta-actin
GAPDH
RPLPO
GUS
TFRC
Category
RS (0 – 100)
Low risk
RS < 18
Int risk
RS ≥ 18 and < 31
High risk
RS ≥ 31
Rate of Distant Recurrence at 10 years
Recurrence Score and
Distant Recurrence-Free Survival
Low
RS < 18
Rec. Rate = 6.8%
C.I. = 4.0% - 9.6%
40
35
Intermediate
RS 18 - 31
Rec. Rate = 14.3%
C.I. = 8.3% - 20.3%
High
RS  31
Rec. Rate = 30.5%
C.I. = 23.6% - 37.4%
30
25
20
15
Recurrence Rate
95% C.I.
10
5
0
0
5
10
15
20
25
30
Recurrence Score
35
40
45
50
Paik .S. et al. N Engl J Med 2004;351:2817-26
B-20: Absolute % Increase in DRFS at 10 Years
• Benefit of Chemo Depends on RS
n = 353
Low
RS<18
n = 134
Int
RS18-30
n = 164
High
RS≥31
0
10%
20%
30%
40%
% Increase in DRFS at 10 Yrs (mean ± SE)
Targeted Therapies Vary in
Effectiveness
• Based on degree of “pathway addiction”
– Is there an ideal target?
• Based on drug-related issues
The Ideal Target?
•
•
•
•
Driving mutation in a
“Dumb tumor” that is
Easily druggable
and the mutation is really common
Dumb Tumors vs. Smart Tumors
• CML, MTC, GIST
• Non-Small Cell Lung Cancer:
– Responses to EGFR and ALK-targeted therapy seen
predominantly in non-smokers
– Bronchial epithelium of smokers are loaded with
mutations (~1 mutation/cell/3 cigarettes)
• Breast Cancer: ER-neg vs. ER-pos
– BRCA and BRCA-ness of TNBC; large mutational load
– ER-pos: less LOH, more well-differentiated
Clinical Trial Implications of
Biomarker-Driven Therapy
• Number needed to study vs. Number needed to
treat: a source of tension
• Laboratory implications that follow from this
A Simulation of a Phase III Trial:
Assumptions:
Two subgroups (A and B)
A is sensitive to targeted therapy and
will have a 25% improvement in
median survival from 2227 mo.
B is insensitive to targeted therapy
Three scenarios:
A representing 100, 50, and 25%
of the study population.
The Crizotinib Story:
How It’s Supposed to Work
Crizotinib: Rationale for Development
of
a
c-MET
inhibitor
• c-MET is potentially one of the most frequently genetically altered
receptor tyrosine kinases in human cancers
– Activating mutations
• Hereditary papillary RCC: 100%, sporadic papillary RCC (13%)
• HNSCC: 10%
• NSCLC (8%) and SCLC (13%)
– Gene amplification
• Gastric carcinoma: 5-10%
• Colorectal carcinoma: 4% primary tumors, 20% liver metastases
• Esophageal adenocarcinoma: 5-10%
• Anaplastic Lymphoma Kinase (ALK) (2 target for crizotinib)
– Anaplastic lymphoma is very sensitive to chemotherapy
– ALK point mutations and gene amplification are implicated in neuroblastoma
… a rare tumor
– ALK translocations in inflammatory myofibroblastic tumors … a very rare
tumor
Crizotinib: Kinase Inhibition Profile
Upstate 102
kinase
Kinase
Met(h)
Tie2(h)
TrkA(h)
ALK(h)
TrkB(h)
Abl(T315I)(h)
Yes(h)
Lck(h)
Rse(h) [SKY]
Axl(h)
Fes(h)
Lyn(h)
Arg(m)
Ros(h)
CDK2/cyclinE(h)
Fms(h)
EphB4(h)
Bmx(h)
EphB2(h)
Fgr(h)
Fyn(h)
IR(h)
CDK7/cyclinH/MAT1(h)
cSRC(h)
IGF-1R(h)
Aurora-A(h)
Syk(h)
FGFR3(h)
PKCµ(h)
BTK(h)
CDK1/cyclinB(h)
p70S6K(h)
PRK2(h)
PAR-1Bα(h)
PKBß(h)
Ret(h)
GSK3ß(h)
Flt3(h)
MAPK1(h)
ZAP-70(h)
Abl(h)
c-RAF(h)
PKD2(h)
ROCK-II(h)
Rsk3(h)
GSK3α(h)
CDK5/p35(h)
PDGFRα(h)
Rsk1(h)
SGK(h)
CHK1(h)
ErbB4(h)
Rsk2(h)
JNK1α1(h)
PKBα(h)
Blk(m)
CDK3/cyclinE(h)
PKCι(h)
PKCθ(h)
CDK2/cyclinA(h)
PAK2(h)
PKCßI(h)
Pim-1(h)
PKCη(h)
SAPK4(h)
CaMKII(r)
MKK7ß(h)
CaMKIV(h)
CHK2(h)
CK2(h)
JNK2α2(h)
MKK6(h)
CK1δ(h)
PKCα(h)
MAPK2(h)
MEK1(h)
PKCδ(h)
PKCε(h)
Plk3(h)
PKCßII(h)
MSK1(h)
PDGFRß(h)
PKCζ(h)
SAPK3(h)
MAPKAP-K2(h)
PKA(h)
AMPK(r)
CDK6/cyclinD3(h)
CSK(h)
SAPK2a(h)
JNK3(h)
PKBγ(h)
IKKα(h)
NEK2(h)
% Inhibition
94
103
102
100
100
98
96
95
94
93
93
93
91
90
87
84
80
79
77
73
68
64
58
58
56
54
52
50
50
35
25
24
22
21
21
21
18
17
17
17
16
16
15
14
14
11
10
10
7
6
5
5
5
4
4
3
3
3
3
2
2
2
1
1
1
0
0
-1
-1
-1
-1
-1
-2
-2
-3
-3
-3
-3
-3
-5
-6
-6
-6
-6
-7
-7
-9
-9
-9
-9
-10
-10
-11
-11
Cellular selectivity on 10 of 13
relevant hits
13 kinase “hits”
<100X
selective for
c-MET
Crizotinib
(PF-02341066)
Kinase
IC50 (nM)
mean*
Selectivity
ratio
c-MET
8
–
ALK
20
2X
298
34X
189
22X
294
34X
322
37X
Tie-2
448
52X
Selectivity findings
Trk A
580
67X
Trk B
399
46X
• ALK and c-MET inhibition at
clinically relevant dose levels
Abl
1,159
166X
IRK
2,887
334X
Lck
2,741
283X
Sky
>10,000
>1,000X
VEGFR2
>10,000
>1,000X
PDGFR
>10,000
>1,000X
RON
Axl
• Low probability of
pharmacologically relevant
inhibition of any other kinase
at clinically relevant dose
levels
*The cellular kinase activities were
measured using ELISA capture
Pfizer Inc. Data on file
A8081001: Phase I Trial of Crizotinib
Cohort 5
300 mg BID
MDZ sub-study
Cohort 4
Cohort 6
250 mg BID
MTD/RP2D
200 mg BID
Cohort 3
200 mg QD
Cohort 2
100 mg QD
Cohort 1
MDZ sub-study
50 mg QD
MTD = Maximum tolerated dose; RP2D = Recommended
phase 2 dose
MDZ = Midazolam (in-vitro data indicated that PF-02341066 Kwak EL, et al. ESMO/ECCO 2009
is a major substrate and inhibitor of CYP3A activity)
(Abstract G6 and oral presentation)
Adverse Events
(≥10%): Dose
Escalation Cohorts (N=37)
Adverse event
Grade
50 mg QD 100 mg QD 200 mg QD
(n=3)
(n=4)
(n=8)
200 mg BID 300 mgBID
(n=7)
(n=6)
250 mg BID
(n=9)
1–2
1–2
1–2
3
1–2
1–2
3
1–2
3
Nausea
2
3
6
0
3
4
0
4
0
Vomiting
2
2
5
0
2
2
0
3
0
Diarrhea
3
0
1
0
2
0
0
2
0
Fatigue
2
2
0
0
0
0
2
1
1
Headache
0
2
1
0
1
0
0
0
0
Visual disturbance
0
0
0
0
1
1
0
0
0
ALT increased
0
0
0
1
1
0
0
0
0
AST increased
0
0
0
0
1
0
0
0
0
DLTs
3 objective responses observed in this part of the Phase I trial
Kwak EL, et al. ASCO 2009 (Abstract 3509 and oral presentation)
First Description of EML4-ALK
Translocation in NSCLC
Evidence for EML4-ALK as a Lung Cancer Oncogene
• Insertion of EML4-ALK into NIH 3T3 fibroblasts was tumorigenic when
implanted subcutaneously into nude mice
• Engineered the specific expression of EML4-ALK fusion gene in lung
progenitor cells using a surfactant protein C gene promoter
• 100% of EML4-ALK transgenic mice developed lung adenocarcinoma that
were + for ALK by IHC. No other primary cancers were observed.
• Following IV injection of EML4-ALK/3T3
cells into nude mice, all developed lung
cancer. Ten animals were treated with an
ALK-specific TKI and 10 were observed:
Key Collaboration
Pfizer and Massachusetts General Hospital
• Of the 3 objective responders, all had ALK
translocations:
– Inflammatory myofibroblastic sarcoma: NPM-ALK
translocation
– NSCLC (2): EML4-ALK translocation
Kwak EL, et al. ESMO/ECCO 2009 (Abstract G6 and oral presentation)
Clinical and Demographic Features of Patients with
ALK-positive NSCLC
Mean (range) age, years
Gender, male/female
0
Performance
1
status,* n (%)
2
3
Race, n (%)
Smoking
history, n (%)
Histology, n (%)
Prior treatment
regimens, n (%)
Caucasian
N=82
51 (25–78)
43/39
24 (29)
44 (54)
13 (16)
1 (1)
Asian
Never smoker
Former smoker
Current smoker
46 (56)
29 (35)
62 (76)
19 (23)
1 (1)
Adenocarcinoma
79 (96)
Squamous
Other
0
1
2
≥3
Not reported
1 (1)
2 (2)
5 (6)
27 (33)
15 (18)
34 (41)
1 (1)
Y Bang et al: ASCO 2010
Tumor Responses to Crizotinib for
Patients with ALK-positive NSCLC
Objective RR = 57%
60
Maximum change in tumor size (%)
(95% CI: 46-68%)
40
DCR (CR+PR+SD): 87%
(95% CI: 77-93%)
20
Progressive disease
Stable disease
Confirmed partial response
Confirmed complete response
0
–20
–30%
–40
–60
–80
–100
*
*Partial response patients with 100% change have non-target disease present
Y Bang et al: ASCO 2010
77% of Patients with ALK-positive NSCLC
Remain on Crizotinib Treatment
Individual patients
• Reasons for discontinuation
– Related AEs
1
– Non-related AEs 1
– Unrelated death 2
– Other
2
– Progression
13
0
3
6
9
12
15
18
21
Treatment duration (months)
N=82; red bars represent discontinued patients
Y Bang et al: ASCO 2010
Progression-free survival probability
Median PFS Has Not been Reached
1.00
PFS probability at 6 months: 72%
(95% CI: 61, 83%)
0.75
0.50
0.25
Median follow-up for PFS: 6.4 months
(25–75% percentile: 3.5–10 months)
95% Hall–Wellner confidence bands
0.00
0
2.5
5.0
7.5
10.0
12.5
Progression-free survival (months)
15.0
17.5
Y Bang et al: ASCO 2010
Current Crizotinib Clinical Trials
PROFILE 1007
Key entry criteria
● Positive for ALK by central
laboratory
● 1 prior chemotherapy
(platinum-based)
R
A
N
D
O
M
I
Z
E
N=318
Crizotinib 250 mg BID (n=159)
administered on a continuous
dosing schedule
Pemetrexed 500 mg/m2 or
docetaxel 75 mg/m2 (n=159)
infused on day 1 of a 21-day cycle
PROFILE 1005
Key entry criteria
● Positive for ALK by central
laboratory
● Progressive disease in Arm B of
study A8081007
Crizotinib 250 mg BID (N=250)
N=250
administered on a continuous
dosing schedule
● >1 prior chemotherapy
PROFILE 1007: NCT00932893; PROFILE 1005: NCT00932451
Crizotinib: The Good News
• Important unmet medical need
• Straightforward, biology-based biomarker
predicting response
• High response rate in heavily pre-treated patients
(i.e., low NNT)
• Relatively non-toxic
A triumph for targeted therapy
Crizotinib as an Example:
The Bad News
• 4-5% of Non Small Cell Lung Cancer, so…
– 20-25 patients screened for every EML4-ALK+ patient
– Not all patients are trial eligible
– Not all patients give informed consent
– Best guess: 50+ patients screened for every patient
entered on trial
– Screening = FISH, which requires trained lab tech, time,
and supply money
– Lab requires CLIA certification
A Thought Experiment:
Imagine ALK in Esophageal Cancer
• Esophageal cancer = 16,640 cases/year, with
14,500 deaths
• Assume ALK-like rates of gene expression of 5%
• .05 X 16,640 = 832 patients/year in the US
• Only 3% of patients with cancer go onto clinical
trials
• .03 X 832 = 25 patients/year entering trial
Medullary Thyroid Cancer
•Thyroid cancer: 2% of all
cancers
•MTC: 5% of all thyroid cancers
•RET proto-oncogene
mutations drive
all hereditary MTC and
~50% of sporadic
•RTKi’s for RET exist
Vandetanib
• Inhibits VEGFR1,2, and RET
• A dud in lung cancer
• ASCO 2010: Phase III trial of 331 MTC patients
– 54% reduction in rate of progression, p = 0.0001
– ORR 45% vs. 13%
• International trial required; accrued in 1 year
• NB: the “biomarker” was the diagnosis of MTC
It Gets Worse
Multiple kinases
are activated
Optimal cell kill
requires
inhibition of
multiple kinases
Stommel et al. SCIENCE VOL 318: 287,2007
It Gets Worse
• Assume: Cancers have multiple drivers
• Targeting multiple RTK’s increases benefit
• So now imagine esophageal cancers with two
drivers, requiring two different targeted therapies
• What is the number needed to screen to perform a
trial of a combination of 2 RTKi’s?
Number Needed to Study:
A New Concept for Biomarker-Driven
Clinical Research
• NNS = ___________1________
(fraction with biomarker X assay specificity
X fraction trial-eligible X fraction giving
informed consent X)
Example: HER2+ = 1/(0.25 X 0.9 X 0.5 X 0.5)
= 17.8 patients screened/patient
entered into trial
NNS Implications
• Fraction with biomarker is fixed by biology
• Maximize true positives (specificity) by optimized
assay development
• Minimize number of exclusion criteria
• Make trial as user-friendly as possible for patients
Problems With Biomarker
Studies
•
•
•
•
•
•
Poor study design
Lack of assay reproducibility
Specimen availability issues
Issues with quantity, quality & preservation
Variability in assay results
Underpowered studies/overly optimistic reporting
due to multiple testing, subset analyses & cut point
optimization
McShane, LM et al. J Clin Oncol 23: 9067-72, 2005
Assay & Marker Space
Phase of
Trial:
Preclinical
0
I
II
III
IV
Discovery
Clinical Practice
Pharmacokinetic
Pharmacodynamic
Prognostic
CLIA
Predictive
Pharmacogenomic
Research Lab
Clinical Lab
If Assay Used For
Individual Patient
Decision Making
Assess feasibility of
detection/assay
technology and
marker prevalence
Marker/technology
discovery
Assess assay
performance in
context:
reproducibility,
sensitivity,
specificity, etc.
Final late stage
Test cut-points in
new retrospective development, assay
qualification
specimen set
Set preliminary cutpoints
Test biomarker
in retrospective
set of specimens
Trial
activation
NCI Clinical Assay Development Program
Clinical Assay
Development
Network
(CADN)
Patient
Characterization
Center (PCC)
Clinical Assay
Development
Center
(CADC)
Specimen Retrieval
System/caHUB
CADP: overarching program to
move assays from research to the
clinic
CADN: network of CLIA certified
labs providing services, including
assay optimization, assessment of
analytical performance, clinical
validity in context of clinical trials
PCC: internal lab performing gene
expression profiling and somatic
mutation detection using semiquantitative NextGen sequencing
on newly diagnosed cancers
CADC: internal lab, part of CADN,
the assay development arm of PCC;
develop “high risk” standardized
assays that can be disseminated
Why Drugs Fail
Failure Rates of Investigational
Drugs in Clinical Trials
• 9 of 10 drugs entering Phase 1 clinical trials
will fail
Historical timing of drug development failures
• 10% discontinuation in Phase 1
• 50-60% discontinuation in Phase 2
• 20-35% discontinuation in Phase 3
Why “Targeted” Agents Fail
•
•
•
•
•
The drug isn’t a drug
The drug isn’t used correctly
The drug is used in the wrong disease
Too much is asked of the drug
The drug is too toxic
The Drug isn’t a Drug:
SU5416
SU5416
• Potent, selective inhibitor of VEGFR2
• Preclinical activity in animal models
• Additivity/synergy with chemotherapeutics
SU5416: not a drug, a rock
• High lipophilicity (Log P= 4.4), an extremely low
aqueous solubility (< 10 ng/ml at pH 2-13) and low
solubility in common pharmaceutically acceptable
organic solvents (i.e., ethanol, PEG 400, propylene
glycol, etc.)
• Rapid clearance (half-life < 1 hour)
• Major metabolites are inactive
18FDG-PET
of patient with GIST treated initially with
SU5416 and later with imatinib mesylate.
Pre- and posttreatment with SU5416
Pre- and posttreatment with
imatinib
Heymach et al, CCR, 2004
The Drug Isn’t Used Right:
PTK-787/ZK 225846 (Vatalanib)
PTK/ZK-787 - Oral VEGF Receptor
Inhibitor
Receptor
PTK/ZK IC50, M*
VEGFR-2 (KDR)
0.037
VEGFR-1 (Flt-1)
0.077
PDGF-
VEGFR-3 (Flt-4)
c-kit
0.58
0.66
0.73
* in vitro
• Potent inhibitor of VEGFR-1 and 2 tyrosine kinases
– Also inhibits VEGFR-3 and the PDGF- and c-kit
receptors
Wood JM, et al. Cancer Research, 2000;60:2178-2189.
DCE-MRI of PTK-787
A
B
Enhancement of a liver metastasis at baseline (A)
and 30 hours (B) after treatment with PTK/ZK
CONFIRM-1 Trial Design
1168 Patients
Stratification Factors:
PS: 0, 1-2
LDH: ≤, >1.5 x ULN
R
A
N
D
O
M
I
Z
E
D
FOLFOX 4 +
PTK/ZK 1250 mg po qd
FOLFOX 4 +
Placebo
Multinational randomized phase III trial in
previously untreated mCRC:
Negative!
Why Didn’t it Work? One Possible Answer
“The MTD of PTK/ZK administered
is 750 mg bid. The DCE-MRI
suggests that the biologically active
dose of PTZ/ZK is at least 1000
mg/day.
Thomas, AL et al. J Clin Oncol 23: 4162-71, 2005.
“Pharamacokinetic data from this
study show that at equivalent daily
doses, drug exposure is comparable
with the previous once daily-dosing
study; however, the trough levels
are significantly higher with the
bid dosing. Whether this will
translate into improved efficacy is at
this time unknown.”
The Drug is Used in the Wrong Disease
• Bevacizumab in pancreatic cancer
Locally advanced/metastatic pancreatic
cancer: CALGB 80303
Gemcitabine 1000mg/m2 d1 8 15
q28d Placebo
Locally advanced
or metastatic
Pancreatic Ca
R
N=602
Primary endpoint:
•Overall survival
Gemcitabine 1000mg/m2 d1 8 15
q28d Bevacizumab 10mg/kg d1
d15 q28d
Secondary endpoints:
• objective response rate, duration of
response, progression-free survival, toxicity
Trial closed by DSMB as crossed futility boundary
Kindler et al ASCO 2007
Locally advanced/metastatic pancreatic cancer
CALGB 80303
Gemcitabine
Placebo
Gemcitabine
Bevacizumab
CR (%)
2
1
PR (%)
8
10
SD (%)
31
36
Disease control
rate (%)
40
47
Median OS
(months)
6.1
5.8
P=0.78
PFS (months)
4.7
4.9
P=0.99
1yr OS (%)
20
18
Kindler et al ASCO 2007
Is Pancreatic Cancer Inherently Resistant to
Anti-VEGF Therapy?
• Hypovascularized with dense stroma
• Pre-adapted to survive hypoxia
• Frequent TP53 inactivating mutations, which render
tumors insensitive to hypoxia
The power of NORMAL
The tale of 3 therapies in TNBC…
Treatment
Target
Rationale
(prior data)
Tumor vs Tumor
Next-Gen
Transcriptome
Tumor vs Normal
Next-Gen
Fold Change/
P-value
Clinical
Trial
Outcome
Cetuximab &
Gefitinib
EGFR
Overexpression
of EGFR
Not
Overexpressed
-1.61
(p= 0.09)
NEGATIVE
Imatinib
c-KIT
Overexpression
of c-KIT
Not
Overexpressed
BSI-201
PARP
Overexpression Overexpressed
of PARP/Synthetic
lethality in DNA
repair
-6.82
NEGATIVE
(p= 1.8E-06)
3.97
(p = 2.0E-05)
POSITIVE
ASCO-Plenary; 2009
PARP inhibitor: Overall Survival
BSI-201 + Gem/Carbo (n = 57)
Median OS = 9.2 months
Gem/Carbo (n = 59)
Median OS = 5.7 months
P = 0.0005
HR = 0.348 (95% CI, 0.189-0.649)
While other reasons may explain these trial results…. Finding genes that are
differentially expressed maybe a good start….
O’Shaughnessy et al
Too Much is Asked of the Drug
• Sunitinib in breast cancer
Sunitinib and Capecitabine in
Advanced Breast Cancer
• Sunitinib
– All prior A and T
– RR = 11% (4-21)
– Median TTP = 10w (1011)
– MDR = 19 w (18-20)
• Capecitabine
– All prior A, and T-resistant
– RR = 20% (14-28)
– Median TTP = 3.1 mo
– MDR = 8.1 mo
Blum et al. J Clin Oncol 17: 485-93, 1999
Burstein et al. J Clin Oncol 26: 1810-16, 2008
Results of SUN1107
Sunitinib
Capecitabine
Median PFS
2.8 mo
4.2 mo
Hazard Ratio
1.47
p value
0.002
Clinical Benefit (%)
19.3
27.0
MDR (mo)
6.9
9.3
Any SAE (%)
30
17
SUN1007: Shooting for the Fence?
• Capecitabine actually works in MBC
– it shrinks tumors
– it has easily manageable toxicity
• Sunitinib had a lower TTP, RR, and TTP in Phase II in
a similar patient population
• Stats require huge sunitinib benefit: 33% increase in
PFS
• Why would one expect this to work?
Conclusions
• Many of our trials fail for simple reasons:
– the drug isn’t a drug
– the drug isn’t used right
– the drug is used in the wrong disease/setting
– too much is asked of the drug
• We owe it to our patients to avoid unforced errors
Avoiding Unforced Errors
•
•
•
•
Get dose and schedule more or less right
Spend $$ on PK/PD (including combinations)
Don’t ignore Phase II data sets
Respect the disease
– Its unique biology
– Its therapeutic context
“The race is not always to the swift, nor the
battle to the strong, but that’s the the way to
bet.”
Damon Runyan
20th Century American Philosopher
Thank You
Laissez les bon temps rouler!