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Rafal Dziadziuszko, MD, PhD
University of Colorado Cancer Center, Aurora, CO, USA
Medical University of Gdansk, Poland
Pharmacogenomic markersin EGFR-targeted therapy
of lung cancer
EMEA Workshop on Biomarkers, 15 December 2006
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Boyle et al., Ann Oncol 2005
Cancer mortalityin the European Union; 2004
LUNG 20%
COLON & RECTUM 12%
STOMACH 8%
BREAST 8%PROSTATE 5%
LYMPHOMAS 4%
LEUKAEMIAS 3%
OTHER 40%
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• Standard chemotherapy providesmodest survival benefit at the expenseof significant toxicity and costs
• Survival rates from lung cancer almostunchanged for decades
• Significant improvement from targeted therapiesin other solid tumors (breast cancer, renalcancer, GIST) and haematologic malignancies
Rationale for targeted therapyof lung cancer
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• Orally available EGFR tyrosine kinase inhibitors(TKIs: gefitinib, erlotinib, lapatinib, canertinib, HKI 272)
• Anti-EGFR monoclonal antibodies(cetuximab, panitumumab, matuzumab, pertuzumab)
Classes of EGFR inhibitorsunder clinical development
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• Phase I studies: relatively good tolerance; dose limiting toxicities: skin rash and diarrhea
• Phase II monotherapy studies in non-small celllung cancer (NSCLC): ~10-20% response ratesand ~40% disease control rates in pretreatedpatients
Gefitinib and erlotinib: findings from early clinical studies
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• No advantage of EGFR TKIs combined withchemotherapy in unselected NSCLC patientsin the first-line treatment (four phase III studies; >4.000 patients)
• Significant survival benefit (HR=0.70) with erlotinibmonotherapy vs placebo in unselected patients relapsedafter one or two lines of chemotherapy (BR.21)
• Insignificant survival benefit (HR=0.89) with gefitinibmonotherapy in a similar setting (ISEL)
Gefitinib and erlotinib: findings from phase III studies
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BR.21: survival
Shepherd et al., NEJM, 2005
HR=0.70 (0.58–0.85) Stratified log-rank p<0.001
100
80
60
40
20
0
Perc
enta
ge
0 6 12 18 24 30
ErlotinibPlacebo
At riskErlotinib 488 255 145 23 4 0 Placebo 243 107 50 9 0 0
Time (months)
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• Never-smokers (RRs ~ 20-30%)
• Asian ethnicity (RRs ~ 30%)
• Female gender (RRs ~ 15-20%)
• Adenocarcinoma (RRs ~ 10-20%)
Clinical markers of increasedresponsiveness to EGFR TKIs
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BR.21: Forest plot of survival by subsets
Erlotinib:placeboPS 0–1PS 2–3
MaleFemale
<65 years≥65 years
AdenocarcinomaSquamous-cell carcinoma
Other histologyPrior weight loss <5%
Prior weight loss 5–10%Prior weight loss >10%
Never-smokerCurrent/ex-smoker
1 prior regimen2+ prior regimens
0 1 2 3 4HR Tsao et al., NEJM, 2005
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Biologic selection to EGFR TKIs
GGCGGGCCAAACTGCTG
EGFR gene copy numberby FISH
EGFR gene mutations
EGFR protein expressionby IHC
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EGFR FISH
13.8%Gene Amplification
17.0%
27.3%
2.2%
24.1%
15.7%
EGFR (%)
High Polysomy
Low Polysomy
High Trisomy
Low Trisomy
Disomy
PATTERN
ISEL STUDY
Hirsch et al., J Clin Oncol 2006
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16% vs. 3%
20% vs. 2%
26% vs. 11%
36% vs. 3%
RR FISH+ vs. FISH-
31%
45%
32%
32%
% FISH Positive
0.50*(0.25-0.97)
Gefitinib500 mg/d
82Hirsch et al.SWOG 0126
0.44**(0.23-0.82)
Erlotinib150 mg/d
125Tsao et al.BR.21
0.61**(0.36-1.03)
Gefitinib250 mg/d
370Hirsch et al.ISEL
Gefitinib250 mg/d
Drug
0.44* (0.23-0.82)
102Cappuzzo et al.
HR (95% CI)
NAuthor
EGFR TKIs studies: impact of gene copy number by FISH
*HR for FISH+ vs. FISH- subsets; all patients treated with gefitinib
**HR for EGFR TKI vs. placebo in FISH+ patients
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Survival according to EGFR genecopy number – BR.21 and ISEL
MONTHS MONTHS
HR=0.44 (0.23, 0.82)P=.008
ISEL FISH + BR.21 FISH +
HR=0.61 (0.36, 1.04)P=.07
20
40
60
80
100
0 4 8 12 16MONTHS MONTHS
20
40
60
80
100
0 6 12 18 3024
HR=0.85 (0.48, 1.51)P=.59
BR.21 FISH -ISEL FISH -
HR=1.16 (0.81, 1.64)P=.42
20
40
60
80
100
0 4 8 12 16
20
40
60
80
100
0 6 12 18 3024
Surv
ival
, %
Surv
ival
, %
ISEL FISH interaction test P=.04 • BR.21 FISH interaction test P=.10
Gefitinib Placebo
GefitinibPlacebo
Erlotinib Placebo
Erlotinib Placebo
Tsao et al, NEJM 2005; Hirsch et al., J Clin Oncol 2006
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IHC and EGFR status: scoring systemScore=0
Score=300 Score=400
Score=200
EGFR POSITIVE: 62/100 pts=62%
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N= 166 5
(3.0%)
N=80 3
(3.8%)
N=17 1
(5.6%)
N=69 1
(1.5%)EGFR -
N=348 38
(10.9%)
N=106 12
(11.3%)
N=84 13
(13.4%)
N=158 13
(8.2%)EGFR +
ORR (%)ORR (%)ORR (%)ORR (%)
TOTALBR.21IDEALISELEGFR Status
Response according to EGFR protein expression (IHC)
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BR.21: Survival accordingto EGFR protein expression
Interaction P = 0.25
100
80
60
40
20
0
Perc
enta
ge
0 6 12 18 24 30
At riskErlotinib117 71 43 5 5 0 Placebo 67 23 12 5 0 0
100
80
60
40
20
0
Perc
enta
ge0 6 12 18 24 30
At riskErlotinib 93 42 22 8 3 0 Placebo 48 24 14 3 0 0
Months Months
ErlotinibPlacebo
Log-rank: p=0.02HR=0.68 (0.49, 0.95)
ErlotinibPlacebo
Log-rank: p=0.70HR=0.93 (0.63, 1.36)
EGFR+ EGFR–
Tsao et al., NEJM 2005
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EGFR gene mutations
747-750
L858G719
TM K DFG Y Y Y Y
Autophosphorylationdomain
Tyrosine kinaseLigand binding domain
K R H DFGGXGXXG L L Y
718 745 776 835 858 861 869 964
18 19 20 21 22 23 24
757-750
Exon:
Paez:
Lynch:
Pao:
Mutacje punktoweDelecje
719 858
Pao et al., PNAS 2004
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NS54% vs. 5%17%Gefitinib250 mg/d
89Cappuzzoet al.
0.16*(0.05-0.52)
64.7% vs. 13.7%
18.9%Gefitinib250 mg/d
90Han et al.
60% vs. 8.8%
82% vs. 11%
83% vs. 10%
RR Mut+ vs. Mut-
12%
59%
56%
% Mut+
0.27*(0.13-0.53)
Gefitinib250 mg/d
66Takano et al.
0.32*(0.12-0.91)
Gefitinib250 mg/d
83Cortes-Funeset al.
Gefitinib250 mg/d
Drug
0.34*(0.12-0.99)
59Mitsudomi et al.
HR (95% CI)
NAuthor
*Mut+ vs. mut- subsetsNS - non significant
Retrospective studies: impact of EGFR mutations
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Prospective studies: impact of EGFR mutations
NR1.77
(0.25-0.97)
46% vs. 10%72% vs. 55%
18%10%
Gefitinib250 and500 mg/d
79312
Bell et al.IDEALINTACT
53% vs. 18%
37.5% vs. 2.6%
16% vs. 7%
RR Mut+ vs. Mut-
12.7%
12%
22.6%
% Mut+
NRGefitinib250 mg/d
215Hirsch et al.ISEL
NR (NS)Erlotinib150 mg/d
228Eberhardt et al.TRIBUTE
Erlotinib150 mg/d
Drug
0.77 (0.40-1.50)
197Tsao et al.BR.21
HR (95% CI)
NAuthor
NR – not reported; NS – non significant
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BR.21: Survival accordingto EGFR mutations
NErlotinib 21 11 5 1 1 0 Placebo 19 10 5 1 0 0
Log-rank: p=0.13HR=0.73 (0.49, 1.10)
Interaction test, P= 0.97
NErlotinib 93 59 34 9 1 0Placebo 44 18 11 6 0 0
Wild-type EGFR100
80
60
40
20
00 6 12 18 24 30
MONTHS
ErlotinibPlacebo
Mutant EGFR100
80
60
40
20
0
MONTHS
ErlotinibPlacebo
Log-rank: p=0.45HR=0.77 (0.40, 1.50)
0 6 12 18 24 30
SUR
VIVA
L PR
OB
AB
ILIT
Y
Tsao et al., NEJM 2005
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Prognostic value of EGFR mutationsin advanced NSCLC
I
II I
I I
I I I II
I I II I I
II IIIIIIIIIIIIIIII IIIIIIIIII IIIIIIIIII III I I IIII II IIIIIIIII I I I III I I I
I
IIII I I II I I II I I II II I I I
1839IL/0014 and 1839IL/0017FIGURE FS5.EGFR MUTATION SURVIVAL: KAPLAN MEIER PLOT
POPULATION : INTENTION-TO-TREAT
TICK MARKS INDICATE CENSORED OBSERVATIONS
GROUP IRESSA & EGFR MUT. + PLACEBO & EGFR MUT. +IRESSA & EGFR MUT. - PLACEBO & EGFR MUT. -
PROPORTION EVENT FREE
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
SURVIVAL TIME (MONTHS)0 4 8 12 16 20 24
Prop
ortio
n Ev
ent F
ree
EGFR mutation-positive (chemotherapy & gefitinib)
EGFR mutation-negative (chemotherapy & gefitinib)
EGFR mutation-positive (chemotherapy & placebo)
EGFR mutation-negative (chemotherapy & placebo)
Overall Survival (months)
EGFR Mutation Status and Overall Survival INTACT
Bell et al., Clin Cancer Res, 2006
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Survival vs. EGFR mutation type
Jackman et al., Clin Cancer Res, 2006
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• Several biomarkers identified (gene copynumber, EGFR protein expression, EGFR mutations, serum proteomics)
• None routinely used for patient selection
• Clinical trials in selected patient populationsor stratified for these markers ongoing
Current status of biomarkers for selectionof NSCLC patients to EGFR TKIs
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• Poor translational components of clinical studies(none prospectively enriched or stratifiedfor biomarkers)
• Neglecting differences in biology accordingto demographic and clinical characteristics(i.e. smoking history, ethnicity)
• Poor standarization and validationof technologies for biomarker assesment
What went wrong with biomarkers in clinicaldevelopment of EGFR TKIs in NSCLC?
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EGFR TKI preclinical studies in Colorado
Sensitive Resistant
ResistantSensitive
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Clinical trial design issues
Prognostic markerAssociates with maineffect regardlessof treatment
May be used for risk-stratified treatment
Not suitable for targeted-therapy trialdesigns
Predictive markerInteraction withtreatment
Appropriate for targeted-therapytrial designs
Crowley J., Taormina IASLC Meeting, 2006
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Targeted therapy clinical trial designs
• All-comers design: Randomize everyone, measure marker / stratify by marker
• Targeted design: Randomize positive patients only
• Strategy design: Randomize to strategy based on marker
Register Measure marker Randomize
Register Measure marker Randomize M+
Register Measure marker Randomize
AB
BA
Tx basedon marker
Tx not basedon marker
A or B
A or B
M+ M-
M+
M+
Crowley J., Taormina IASLC Meeting, 2006
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• Incorporation of biomarker studies early in preclinical and clinical development
• Understanding of biomarker significance for disease biology (prognostic vs. predictive)
• Better standarization and validationof technologies for biomarker assesment
Future directions