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
Erb-B1HER1EGFR
Erb-B2HER2neu
Erb-B3HER3
The HER Family of Receptors
Tyrosinekinase
domain
Ligand-bindingdomain
Erb-B4HER4
TGF-αEGFEpiregulinBetacellulinHB-EGFAmphiregulin Heregulin
Heregulin (neuregulin-1)EpiregulinHB-EGFNeuregulins-3, -4
No ligand-binding activity*
Ligands
*HER2 dimerizes with other members of the HER family. Roskoski. Biochem Biophys Res Commun. 2004;319:1. Rowinsky. Annu Rev Med. 2004;55:433.
Fluorescence In Situ Hybridization Test Measures HER2 Gene
Amplification
• FISH tests are designed to detect amplification of the HER2 gene
PathVysion® PI. Revised May 2004.
Chromosome 17centromere
HER2 gene
HER2-normalRatio <2.0
HER2-amplifiedRatio ≥2.0
Disease-Free Survival
87%87%85%85%
67%
75%
N EventsACT 1679 261ACTH 1672 134
%
HR=0.48, 2P=3x10-12
ACACTHTH
ACT
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?
Survival (anti-apoptosis)
Gene transcriptionGene transcriptionCell-cycle progressionCell-cycle progression
Angiogenesis
Invasion andmetastasis
Chemotherapy /radiotherapy resistance
Proliferation
pY
Ligand
Antibodies to EGFRcetuximab, panitumumab
EGFR-TKpY
EGF Receptor: Role in CRC Therapy
Meyerhardt & Mayer, N Engl J Med 2005Venook, Oncologist 2005
RAS RAF
MEK
MAPK
PI3K
AKTSTAT
PTEN
pY
pY
mTOR
Copyright © American Society of Clinical Oncology
Amado, R. G. et al. J Clin Oncol; 26:1626-1634 2008
Progression-free survival by treatment within KRAS groups
Mutant – 7.4 vs 7.3 weeks
Wild type –12.3 vs. 7.3 weeksP= <0.0001
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
Oncotype DX 21 Gene Recurrence Score (RS) Assay
PROLIFERATIONKi-67
STK15Survivin
Cyclin B1MYBL2
ESTROGENERPR
Bcl2SCUBE2
INVASIONStromolysin 3Cathepsin L2
HER2GRB7HER2
BAG1GSTM1
REFERENCEBeta-actinGAPDHRPLPO
GUSTFRC
CD68
16 Cancer and 5 Reference Genes From 3 Studies
Category RS (0 – 100)Low risk RS < 18
Int risk RS ≥ 18 and < 31
High risk RS ≥ 31
Recurrence Score and Distant Recurrence-Free Survival
40
35
30
25
20
15
10
5
00 5 10 15 20 25 30 35 40 45 50
Recurrence Score
Rat
e o
f D
ista
nt
Rec
urr
ence
at
10 y
ears
95% C.I.
Recurrence Rate
LowRS < 18Rec. Rate = 6.8%C.I. = 4.0% - 9.6%
IntermediateRS 18 - 31Rec. Rate = 14.3%C.I. = 8.3% - 20.3%
HighRS 31Rec. Rate = 30.5%C.I. = 23.6% - 37.4%
Paik .S. et al. N Engl J Med 2004;351:2817-26
LowRS<18
IntRS18-30
HighRS≥31
0 10% 20% 30% 40%
B-20: Absolute % Increase in DRFS at 10 Years
• Benefit of Chemo Depends on RS
n = 353
n = 134
n = 164
% 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 2227 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
Selectivity findings
• ALK and c-MET inhibition at clinically relevant dose levels
• Low probability of pharmacologically relevant inhibition of any other kinase at clinically relevant dose levels
Cellular selectivity on 10 of 13 relevant hits
Upstate 102 kinase
13 kinase “hits” <100X selective for c-MET
Kinase % InhibitionMet(h) 94Tie2(h) 103
TrkA(h) 102ALK(h) 100
TrkB(h) 100Abl(T315I)(h) 98
Yes(h) 96
Lck(h) 95
Rse(h) [SKY] 94
Axl(h) 93
Fes(h) 93
Lyn(h) 93
Arg(m) 91
Ros(h) 90
CDK2/cyclinE(h) 87
Fms(h) 84EphB4(h) 80Bmx(h) 79
EphB2(h) 77Fgr(h) 73Fyn(h) 68IR(h) 64
CDK7/cyclinH/MAT1(h) 58cSRC(h) 58
IGF-1R(h) 56Aurora-A(h) 54
Syk(h) 52FGFR3(h) 50PKCµ(h) 50BTK(h) 35
CDK1/cyclinB(h) 25p70S6K(h) 24PRK2(h) 22
PAR-1Bα(h) 21PKBß(h) 21Ret(h) 21
GSK3ß(h) 18Flt3(h) 17
MAPK1(h) 17ZAP-70(h) 17
Abl(h) 16c-RAF(h) 16PKD2(h) 15
ROCK-II(h) 14Rsk3(h) 14
GSK3α(h) 11CDK5/p35(h) 10PDGFRα(h) 10
Rsk1(h) 7SGK(h) 6
CHK1(h) 5ErbB4(h) 5Rsk2(h) 5
JNK1α1(h) 4PKBα(h) 4Blk(m) 3
CDK3/cyclinE(h) 3PKCι(h) 3PKCθ(h) 3
CDK2/cyclinA(h) 2PAK2(h) 2PKCßI(h) 2Pim-1(h) 1PKCη(h) 1
SAPK4(h) 1CaMKII(r) 0MKK7ß(h) 0CaMKIV(h) -1CHK2(h) -1CK2(h) -1
JNK2α2(h) -1MKK6(h) -1CK1δ(h) -2PKCα(h) -2
MAPK2(h) -3MEK1(h) -3PKCδ(h) -3PKCε(h) -3Plk3(h) -3
PKCßII(h) -5MSK1(h) -6
PDGFRß(h) -6PKCζ(h) -6
SAPK3(h) -6MAPKAP-K2(h) -7
PKA(h) -7AMPK(r) -9
CDK6/cyclinD3(h) -9CSK(h) -9
SAPK2a(h) -9JNK3(h) -10PKBγ(h) -10IKKα(h) -11NEK2(h) -11 *The cellular kinase activities were
measured using ELISA capture method
KinaseIC50 (nM)mean*
Selectivity ratio
c-MET 8 –
ALK 20 2X
RON298 34X
189 22X
Axl294 34X
322 37X
Tie-2 448 52X
Trk A 580 67X
Trk B 399 46X
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
Pfizer Inc. Data on file
Crizotinib (PF-02341066)
Crizotinib: Kinase Inhibition Profile
A8081001: Phase I Trial of Crizotinib
Cohort 1
50 mg QD
Cohort 2100 mg QDMDZ sub-study
MTD = Maximum tolerated dose; RP2D = Recommended phase 2 doseMDZ = Midazolam (in-vitro data indicated that PF-02341066 is a major substrate and inhibitor of CYP3A activity)
Cohort 3
200 mg QD
Cohort 4
200 mg BID
Cohort 6250 mg BID
MTD/RP2D
Kwak EL, et al. ESMO/ECCO 2009(Abstract G6 and oral presentation)
Cohort 5300 mg BIDMDZ sub-study
Most Common Treatment-related Adverse Events
(≥10%): Dose Escalation Cohorts (N=37)
Adverse event50 mg QD
(n=3)100 mg QD
(n=4)200 mg QD
(n=8)200 mg BID
(n=7)300 mgBID
(n=6)250 mg BID
(n=9)
Grade 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
Kwak EL, et al. ASCO 2009 (Abstract 3509 and oral presentation)
3 objective responses observed in this part of the Phase I trial
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 CollaborationPfizer 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
Clinical and Demographic Features of Patients with ALK-positive NSCLC
N=82Mean (range) age, years 51 (25–78)
Gender, male/female 43/39
Performance status,* n (%)
0 24 (29)
1 44 (54)2 13 (16)3 1 (1)
Race, n (%)Caucasian 46 (56)Asian 29 (35)
Smoking history, n (%)
Never smoker 62 (76)Former smoker 19 (23)Current smoker 1 (1)
Histology, n (%)Adenocarcinoma 79 (96)Squamous 1 (1) Other 2 (2)
Prior treatment regimens, n (%)
0 5 (6)
1 27 (33)
2 15 (18)≥3 34 (41)Not reported 1 (1)
Y Bang et al: ASCO 2010
60
40
20
0
–20
–40
–60
–80
–100
Progressive disease
Stable disease
Confirmed partial response
Confirmed complete response
Max
imu
m c
han
ge
in t
um
or
size
(%
)
–30%
Tumor Responses to Crizotinib for Patients with
ALK-positive NSCLC
*Partial response patients with 100% change have non-target disease present
*
Objective RR = 57% (95% CI: 46-68%)DCR (CR+PR+SD): 87%(95% CI: 77-93%)
Y Bang et al: ASCO 2010
77% of Patients with ALK-positive NSCLC Remain on Crizotinib
Treatment
0 3 6 9 12 15 18 21
Treatment duration (months)
N=82; red bars represent discontinued patients
Indi
vidu
al p
atie
nts
• Reasons for discontinuation– Related AEs 1– Non-related AEs 1– Unrelated death 2– Other 2– Progression 13
Y Bang et al: ASCO 2010
Median PFS Has Not been Reached
1.00
0.75
0.50
0.25
0.00
Pro
gre
ssio
n-f
ree
surv
ival
pro
bab
ilit
y
0 2.5 5.0 7.5 10.0 12.5 15.0 17.5Progression-free survival (months)
PFS probability at 6 months: 72% (95% CI: 61, 83%)
Median follow-up for PFS: 6.4 months (25–75% percentile: 3.5–10 months) 95% Hall–Wellner confidence bands
Y Bang et al: ASCO 2010
Current Crizotinib Clinical Trials
PROFILE 1007: NCT00932893; PROFILE 1005: NCT00932451
Key entry criteria
● Positive for ALK by central laboratory
● 1 prior chemotherapy (platinum-based)
N=318
PROFILE 1007
Crizotinib 250 mg BID (N=250)
administered on a continuous dosing schedule
Key entry criteria
● Positive for ALK by central laboratory
● Progressive disease in Arm B of study A8081007
● >1 prior chemotherapy
PROFILE 1005
RANDOMIZE
N=250
Crizotinib 250 mg BID (n=159)
administered on a continuous dosing schedule
Pemetrexed 500 mg/m2 ordocetaxel 75 mg/m2 (n=159)
infused on day 1 of a 21-day cycle
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 requiresinhibition ofmultiple 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
If Assay Used For Individual Patient Decision Making
Discovery Clinical Practice
PharmacokineticPharmacokinetic
PharmacodynamicPharmacodynamic
PrognosticPrognostic
PredictivePredictive
PharmacogenomicPharmacogenomic
CLIA
Research Lab Clinical Lab
Phase of Trial: Preclinical 0 I II III IV
Assay & Marker Space
Marker/technology discovery
Assess feasibility of detection/assay technology and
marker prevalence
Test biomarker in retrospective set of specimens
Assess assay performance in
context: reproducibility,
sensitivity, specificity, etc.
Set preliminary cut-points
Final late stage development, assay
qualification
Trial activation
Test cut-points in new retrospective specimen set
NCI Clinical Assay Development Program
Patient Characterization Center (PCC)
Clinical Assay Development
Center (CADC)
Clinical Assay Development
Network(CADN)
Specimen Retrieval System/caHUB
CADP: overarching program to move assays from research to the clinicCADN: network of CLIA certified labs providing services, including assay optimization, assessment of analytical performance, clinical validity in context of clinical trialsPCC: internal lab performing gene expression profiling and somatic mutation detection using semi-quantitative 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.
Heymach et al, CCR, 2004
Pre- and post- treatment with SU5416
Pre- and post- treatment with imatinib
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- 0.58
VEGFR-3 (Flt-4) 0.66
c-kit 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
Enhancement of a liver metastasis at baseline (A) and 30 hours (B) after treatment with PTK/ZK
A
B
1168 Patients
Stratification Factors:PS: 0, 1-2
LDH: ≤, >1.5 x ULN
FOLFOX 4 +PTK/ZK 1250 mg po qd
CONFIRM-1 Trial Design
FOLFOX 4 +Placebo
Multinational randomized phase III trial in
previously untreated mCRC:
Negative!
RANDOMIZED
“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.
“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.”
Thomas, AL et al. J Clin Oncol 23: 4162-71, 2005.
Why Didn’t it Work? One Possible Answer
The Drug is Used in the Wrong Disease
• Bevacizumab in pancreatic cancer
Locally advanced/metastatic pancreatic cancer: CALGB
80303
Locally advanced or metastatic Pancreatic Ca
N=602
R
Gemcitabine 1000mg/m2 d1 8 15 q28d Placebo
Gemcitabine 1000mg/m2 d1 8 15 q28d Bevacizumab 10mg/kg d1 d15 q28d
Primary endpoint:
•Overall survival
Secondary endpoints:
• objective response rate, duration of response, progression-free survival, toxicity
Kindler et al ASCO 2007
Trial closed by DSMB as crossed futility boundary
Locally advanced/metastatic pancreatic cancer
CALGB 80303Gemcitabine
PlaceboGemcitabine 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-GenTranscriptome
Tumor vs Normal
Next-GenFold Change/
P-value
ClinicalTrial
Outcome
Cetuximab& Gefitinib
EGFR Overexpressionof EGFR
NotOverexpressed
-1.61(p= 0.09)
NEGATIVE
Imatinib c-KIT Overexpressionof c-KIT
Not Overexpressed
-6.82(p= 1.8E-06)
NEGATIVE
BSI-201 PARP Overexpressionof PARP/Synthetic
lethality in DNA repair
Overexpressed 3.97(p = 2.0E-05)
POSITIVE
ASCO-Plenary; 2009PARP 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)
O’Shaughnessy et al
While other reasons may explain these trial results…. Finding genes that are differentially expressed maybe a good start….
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
(10-11)– MDR = 19 w (18-20)
Burstein et al. J Clin Oncol 26: 1810-16, 2008
• 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
Results of SUN1107
SunitinibCapecitabine
Median PFS 2.8 mo 4.2 moHazard Ratio 1.47p value 0.002
Clinical Benefit (%) 19.3 27.0MDR (mo) 6.9 9.3Any 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 Runyan20th Century American Philosopher
Thank You
Laissez les bon temps rouler!