Advances in the Management
of Non Small Cell Lung
Cancer
Presenter Disclosures
Personal financial relationships with commercial interests relevant to this
presentation during the past 12 months:
Research support: Eli Lilly, Genetech, OSI pharmaceuticals
Personal financial relationships with non-commercial interests (e.g.,
government or other nonprofit funding) relevant to this presentation,
within past 12 months:
Relevant institutional financial interests:
Personal financial relationships with tobacco industry entities within the
past 3 years:
No relationship to disclose
NSCLC Epidemiology
Statistics for 2008
Cancer
Incidence
Colon
Breast
Prostate
Total
108,070
184,450
186,320
478,840
Lung
215,020
Deaths
49,960
40,930
28,660
119,550
161,840
Jemal, CA Cancer J Clin 2008; 58: 71
NSCLC: Stage at Diagnosis
Stage I 10%
Stage IV 40%
Stage II 20%
Stage IIIA 15%
Stage IIIB 15%
Ettinger et al. Oncology. 1996;10:81-111.
We had reached a Ceiling for Improved Benefit
of Cytotoxic Chemotherapy in Advanced NSCLC
ECOG 1594
1.0
Cisplatin/Paclitaxel
Cisplatin/Gemcitabine
Cisplatin/Docetaxel
Carboplatin/Paclitaxel
0.8
Stage
IIIB/IV 0.6
Patient
Survival, 0.4
%
• 1 yr survival plateau at
about 35-40%
• No clear efficacy benefit
for non-platinum
combinations or triplet
combinations
• New paradigm is needed
0.2
0.0
0
5
10
15
20
Months
25
Adapted with permission from Schiller JH et al. N Engl J Med. 2002
30
Platinum Doublet Chemotherapy in
Advanced NSCLC1
Overall response
Time-to-progression
Median survival
1-year survival
2-yr survival
25%-35%
4-6 months
8-12 months
30%-40%
10%-15%
Failed Paradigms:
Triplet Cytotoxic
Chemotherapy2,3
Non-Platinum Chemotherapy
1. NCCN Non-small Cell Lung Cancer Clinical
Practice Guideline,
v.2.2008. Available
at: http://www.nccn.org/professionals/physician_gls/PDF/nscl.pdf
Single
Agent
Chemotherapy
2. Frasci et al. J Clin Oncol. 1999;17:2316-2325
3. Kelly et al. Clin Cancer Res. 2000;6:3474-3479.
Strategies to improve treatment
effectiveness
• Better Patient Selection:
– What criteria?
• Better Predictive Markers:
– Which ones?
• Better Treatments:
– Less toxic
– More specific
Role of Histology in Patient Selection:
JMDB Trial: Pemetrexed-Cisplation vs
Gemcitabine-Cisplatin in Adv NSCLC
Randomization
Factors
•
•
•
•
•
Stage
PS
Gender
Histo vs cyto dx
Brain mets hx
Cisplatin 75 mg/m2 day 1 plus Pemetrexed 500
mg/m2 d 1
R
Cisplatin 75 mg/m2 day 1 plus Gemcitabine
1250 mg/m2 d 1 & 8
Vitamin B12, folate, and dexamethasone given in both arms
Scagliotti & Gandara: JCO, 2008
1st-line NSCLC: Preplanned Analysis
Squamous (n=473)
Nonsquamous* (n=1252)
HR=1.229
(95% CI: 1.00–1.51)
p=0.051
Pemetrexed+cisplatin
Median OS: 12.6 mos
Gemcitabine+cisplatin
Median OS: 10.9 mos
Survival Probability
Survival Probability
HR=0.844
(95% CI: 0.71–0.98)
p=0.011
Gemcitabine+cisplatin
Median OS: 10.9 mos
Pemetrexed+cisplatin
Median OS: 9.4 mos
Survival Time (months)
Survival Time (months)
* Non-squamous = adenocarcinoma, large cell carcinoma, and other/indeterminate NSCLC histology
Scagliotti, et al. J Clin Oncol 2008
JMDB Trial: Cisplatin-Pemetrexed (CP) vs. Cisplatin-Gemcitabine (CG) in
Adv NSCLC
No difference in overall
PFS or Survival between
study arms
CP improves Survival over CG
in Non-SCCA (HR 0.81, p=0.005)
CG improves Survival over CP
in SCCA (HR 1.23, p=0.05)
Insulin/IGF Receptor System
IGF-I
4
Insulin
IGF-II
IGF
Binding
Proteins
N
N
N
Hybrid
Receptors
C
C
IGF-IIR
(M6P-receptor)
C
N
N
C
IGF-IR
C
N
N
C
IR-A
C
N
C
IR-B
RAS /MAPK mitogenesis
PI3K/AKT survival
• Ligand: IGF-I, IGF-II. Local bioavailability subject to regulation by binding with IGF-BP
and release by IGF-BP protease
• IGF-IR: binds to IGF-I, II
• IGF-IR/IR-A: Hybrids with preferential binding to IGF-1 >> insulin.
• IR exists in two isoforms:
•IR-B: traditional insulin receptors.
•IR-A: preferentially binds IGF-II (a fetal form; re-expressed in some tumors)
• IGF-IIR: non-signaling receptor, acting as a “sink” for IGF-II.
IGF-I and risk of Cancers
prospective population-based case-control studies
Chan et al, 2002
Harman et al, 2000
Stattin et al, 2000
Stattin et al, 2000 (<59yrs)
Prostate cancer
Hankinson et al, 1998
Hankinson et al, 1998 (<50yrs)
Toniolo et al, 2000
Toniolo et al, 2000 (premenopausal)
Breast cancer
Zhao et al, 2003
Bladder cancer
Giovannucci et al, 2000
Kaaks et al, 2001
Ma et al, 1999
Probst-Hensch et al, 2001
Colorectal cancer
Lukanova et al, 2000
London et al, 2002
Lung cancer
Garnero et al, 2000
Osteoporotic fractures
IGT/NIDDM
Ischemic Heart disease
Sandhu et al, 2002
Juul et al, 2002
0,1
1
10
Adjusted Relative Risk
IGF1R Inhibitor Therapy: Randomized Phase II
Trial Paclitaxel/Carboplatin +/-CP-751,871 in
advanced NSCLC
n=97
TCI: paclitaxel 200 mg/m2,
carboplatin (AUC=6),
Stage 1: CP-751,871 10 mg/kg
Stage 2: CP-751,871 20 mg/kg
CP-751,871
Single agent
2:1 randomization
N=150, 2 stages
of 73 and 77 pts
n=53
TCI
TC: paclitaxel 200 mg/m2,
carboplatin (AUC=6)
Optional upon
progression
on TC alone
CP-751,871
Stage 3: single-arm,
post-study extension
in SCC
n=30, 14 pts
evaluable
2
Single agent
TCI: paclitaxel 200 mg/m ,
carboplatin (AUC=6)
CP-751,871 20 mg/kg
Karp: ASCO 08
Response Rate by Dose and Histology
Histology
TaxCarbo + TaxCarbo +
TaxCarbo CP (10mg/kg) CP (20mg/kg)
Squamous
(randomized)
6/13 (46%)
4/7 (57%)
7/9 (78%)
Squamous
(single arm)
–
–
11/14 (78%)
Adenoca
5/20 (25%)
8/21 (38%)
16/28 (57%)
NOS
8/15 (53%)
3/6 (50%)
9/18 (50%)
Karp: ASCO 08
Major Responses of TCI in Bulky Squamous
RR 78% vs 57%
Change in Lesion size
40.0
20.0
0.0
-20.0
-40.0
-60.0
-80.0
BEST RESPONSE IN
VISCERAL LESIONS > 5 cm
0 mg/kg
20 mg/kg
10 mg/kg
-100.0
October 2005
August 2007
November 2007
February 2006
October 2007
April 2008
 Choice
of treatment according to histology:
– Adenocarcinoma: Pemetrexed based
– Squamous cell carcinoma:


Gemcitabine based
Pac/carbo + IGF inhibitor CP 27181
?
1
Histology will ultimately prove to be Suboptimal for Selecting
Chemotherapy (or Targeted Therapy)
• Histological sub typing groups tumors based on microscopic pattern
recognition by a pathologist (using 18th century technology)
• At best, Histology is the phenotypic expression of complex genetic and
molecular interactions
• 21st century approach will refine choice at the molecular level
Robert Hooke
Tissue Microarray
Thymidylate Synthtase Expression in Lung Cancer
Bhattacharjee PNAS 2001
TS
• SCLC – High TS
• Squamous – High TS
• Adeno – Low TS
Possible explanation to SQCCA sensitivity to CP 721871
• De-regulation of the IGFR pathway seems a possibility in
squamous cell carcinoma:
– ILGF binding protein 3 levels, which regulates activity
of IGF-1, are low in SQCCA
– IGF-R appears to be expressed more in SQCCA
– IGF-IIR gene which codes for a negative regulator of
the IGF-IR pathway is mutated in up to 60% of
SQCCA
Karp JCO 2009
Strategies to improve treatment
effectiveness
•Better Patient Selection:
-What criteria?
•Better Predictive markers:
-Which Ones?
•Better Treatments:
-Less Toxic
-More Specific
HGF mAb
AMG102
OA5D5
EGFR
HGF
HER
C-MET
P
P
P
P
Anti-HER
Lapatinib
BMS599626
BMS690514
PF00299804
XL647
BIBH2992
ARRY334543
Anti-cMET
XL880
ARQ197
PF02341066
JNJ388
MGCD265
SU11274
PHA665752
IGF-1 mAb
CP721871
AMG479
IMC-A12
R1507
BIIB022
IGF-1/
Insulin
Anti-PI3k
PI103
BGT226
BEZ235
XL765
XL147
Anti-IGF-1R
XL228
OSI906
NDGA
IGF-1R/
IR
P
P
P
Ras
P
PDK-1
PIP2
IRS
P
PI3k
P
P
PIP3
P
PTEN
mTOR
Ras
Src
Raf
Anti-Ras
Tipifarnib
Lonafarnib
BMS214662
MEK
Anti-Raf
Sorafenib
RAF265
XL281
PLX4032
UCN01
rictor
Akt
Anti-Src
Bosutinib
XL999
AZD0530
KX010107
Anti-Akt
Perifosine
GSK690693
BAD
Apoptosis
mTOR
raptor
Erk
Anti-mTOR
Everolimus
Deforolimus
FoxO3a
Transcription
p70s6k
4EBP
Anti-MEK
AZD6244
RDEA119
XL518
Cell Cycle Progression
Hif-1α
Proliferation
Differentiation
Anti-DNMT
5-azacitadine
5-aza-2’-deoxycitidine
Protein Translation
Anti-HDAC
SNDX275
CI994
Apicidin
Desipeptide
Trapoxin
Depeudecin
SK7068
vorinostat
Angiogenesis
• The trick is:



To pick right target
To have the right agent
To have the right pairing
Many Targeted Therapies Failed to Show Additional
Benefit when Combined with Platinum Based CT
Median Survival results in months
INTACT-1
INTACT-2
TRIBUTE
TALENT
SPIRIT-1
SPIRIT-2
Paz-Ares et al.
ISIS-3521
AG-3340-017
BR.18
Study 5404
ESCAPE
BR.24
Courtesy: E. Vokes
CG ± gefitinib
CP ± gefitinib
CP ± erlotinib
CG ± erlotinib
VC ± bexarotene
CP ± bexarotene
CG ± aprinocarsen
CP ± aprinocarsen
CG ± prinomastat
CG ± BMS-275291
CP± panitumumab
CbP ± sorafenib
CbP ± cediranib
Placebo
Agent
10.9
9.9
10.5
10.0
9.9
9.2
10.4
9.7
10.8
9.2
8.0
9.9/9.9
9.8/8.7
10.6
10.3
8.7
8.5
10.0
10.0
11.5
8.6
8.5
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
Phase III study stopped due to high mortality
Will not proceed to Phase III because of
toxicity
Bevacizumab Blocks Angiogenesis
Recombinant
humanized
monoclonal
antibody to
VEGF-A
E4599. Ph III RCT :Bevacizumab and
CP vs CP in non-squamous NSCLC
IIIB and IV non-squamous
No brain mets
No hemoptysis
No prior chemotherapy
Stratification by:
• Stage (IIIB or IV)
R
A
N
D
O
M
I
Z
E
Paclitaxel 200 mg/m2 IV
Carboplatinum AUC 6 q 21d
X6 cycles
Paclitaxel 200 mg/m2 IV +
Carboplatinum AUC 6 q 21d
X6 cycles
Bevacizumab 15mg/kg q3 wk
til PD
• Geographic region
Sandler. NEJM 2006; 355: 2542
Phase III ECOG 4599 trial: Paclitaxel/Carboplatin
± Bevacizumab
Non-Squamous histology, no hemoptysis, brain metastases
Proportion surviving
1.0
12 mo 24 mo
0.8
0.6
Pac/carbo + bev, n=434
51%
23%
Pac/carbo, n=444
44%
15%
12.3
HR: 0.79, 0.67-0.92
P = .003
10.3
0.4
0.2
0.0
0
6
12
18
24
Months
30
36
42
48
~37% of patients with advanced NSCLC are eligible to receive bevacizumab, <20% if also exclude age ≥70 years
Sandler AB, et al. New Engl J Med. 2006;355:2542-2550.
ECOG Trial (E4599): Treatment Related
Deaths*
PC
n=427
PCB
n=420
Hemoptysis
0
5
GI Bleed
1
2
Neutropenic Fever
1
5
CNS
0
2*
Pulmonary Embolus
0
1
Total
2
15
Hemorrhage
Sandler AB, et al. New Engl J Med. 2006;355:2542-2550.
 Just
when you think you’ve got it right…..
2
AVAIL Study design
2
Previously
untreated, stage
IIIb, IV or
recurrent
non-squamous
NSCLC
N=1050
R
A
N
D
O
M
I
Z
E
1
Bevacizumab
7.5mg/kg +
Cis/Gem (CG)
PD
Placebo 7.5 + CG
PD
1
Placebo 15 + CG
2
Bevacizumab
15mg/kg + CG
Positive for primary endpoint: PFS
Negative for Overall Survival
Manegold, et al. ASCO 2007, LBA 7514
Bevacizumab
Bevacizumab
PD
AVAIL Efficacy
PFS
(mos)
OS
(mos)
Bevacizumab
Bevacizumab
Placebo
7.5 mg/kg
15 mg/kg
CG
+CG
+CG
6.8
6.6
HR 0.75 (0.64-0.87)
HR 0.85 (0.73-1.00)
P= 0.0003
P=0.0456
13.6
13.4
HR 0.93 (0.78-1.11)
HR 1.03 (0.86-1.23)
P=0.42
P=0.76
6.2
13.1
The 1o endpoint for the trial: PFS
So that this was reported as a positive trial
But is it really clinically significant?
Epidermal Growth Factor Receptor (EGFR) Inhibitors
in NSCLC: Status of Predictive Biomarkers
Gefitinib
Erlotinib
Single Agent
EGFR mut=predictive
EGFR FISH=predictive
KRAS mut=predictive
TKIs + Chemo
are negative
(INTACT I/II
TRIBUTE, TALANT
all negative)
Cetuximab
TKI
MoAb
Biomarkers Unclear
Ligand
TKI K K
Single Agent
K K
Cetux + Chemo
(FLEX=positive)
Signal
Transduction
Blocked
Signal
Transduction
Blocked
Cetuximab Mechanism of Action
• IgG1 monoclonal antibody
• Binds to EGFR and competitively inhibits
ligand binding (e.g. EGF)
• Mechanisms different from TKI:
– Receptor Internalization
– Antibody-Dependent Cellular Cytotoxicity
(ADCC)
• Combinations with Radiation or Chemotherapy
effective in other tumor types
– Radiation: H & N Cancer
– Chemotherapy: Colon Cancer
Cetuximab
IgG1 MAb
ADCC
EGFR
Harari: Clin Cancer Res, 2004
FLEX: Pivotal Trial
Cetuximab + Chemotherapy in 1st-Line Advanced NSCLC
Up to 6 cycles of chemotherapy; patients not
progressing continue on cetuximab maintenance
Chemotherapynaïve advanced
NSCLC
Stratified by


IIIB or IV
ECOG PS 0,1
or 2
R
A n=557
N
D
O
M
I
Z n=568
E
Cetuximab 400 mg/m2 d1 wk1, then 250 mg/m2, QW
+ Vinorelbine 25 mg/m2 d1,8
+ cisplatin 80 mg/m2 d1, Q3W
Vinorelbine 25 mg/m2 d1,8
+ cisplatin 80 mg/m2 d1, Q3W
Primary endpoint: OS
Secondary endpoints: PFS, ORR, DCR, QoL, Safety, PK




All histologic subtypes included
ECOG PS 0–2
No known brain metastases
EGFR expression by IHC (≥1 positive tumor cells)
Pirker R, et al. Lancet 373(9674): 1525 – 1531, 2009.
FLEX: Results
OS (%)
Median OS
1-Yr Surv.
CV + Cetuximab 11.3 mos
47%
CV 10.1 mos
42%
HR: 0.871; P=0.044
Months
CV + Cetuximab
CV
P
RR
36%
29%
0.012
PFS
4.8 mos
4.8 mos
NS
TTF
4.2 mos
3.7 mos
0.015
Pirker R, et al. Lancet 373(9674): 1525 – 1531, 2009.
NS=not significant; TTF=time to treatment failure.
FLEX: Differences in Ethnicity
Caucasian
(N=946)
Asian
(N=121)
Adenocarcinoma
44%
72%
Female
27%
46%
Never smoker
17%
52%
ECOG PS 0/1
81%
94%
17%
61%
9.6 mos
19.5 mos
[9.0–10.4]
[16.4–23.3]
Prognostic Factors
Poststudy Treatment
EGFR TKIs
Median OS
[95% CI]
Pirker R, et al. Lancet 373(9674): 1525 – 1531, 2009.
FLEX: Asian Subgroup (N=121)
CV + Cetuximab
(N=62)
CV
(N=59)
65%
80%
50%
73%
OS
17.6 mos
20.4 mos
NS
RR
50%
44%
NS
P Value
Baseline Prognostic Factors
Adenocarcinoma
Post-Study Treatment
EGFR TKIs
Cannot draw definitive conclusions because of small sample size (10% of total),
differences in histology and differences in post-study EGFR TKI treatment
Pirker R, et al. Lancet 373(9674): 1525 – 1531, 2009.
FLEX: OS – Caucasians (N=946)
Prespecified Analysis
Overall Survival (%)
CV + Cetuximab
(N=466)
CV
(N=480)
Median OS
1-Year
Survival
10.5 mos
45%
9.1 mos
37%
HR=0.803; P=0.003
P value: stratified log-rank test (2-sided)
Months
Median OS
CV + Cetuximab
CV
HR
10.5 mos
9.1 mos
0.803
Adenocarcinoma (N=413)
12.0 mos
10.3 mos
0.815
Squamous Cell (N=347)
10.2 mos
8.9 mos
0.794
Other (N=185)
9.0 mos
8.2 mos
0.807
Caucasians (N=946)
CV=cisplatin/vinorelbine.
Pirker R, et al. Lancet 373(9674): 1525 – 1531, 2009.
Overall Survival (%)
FLEX: OS Early Acne-Like Rash
Pre-Planned Analysis
Patients at Risk
Grade 0
228
Any Grade
290
Any grade:
(N=290)
CT + Cetuximab
Grade 0:
(N=228)
CT + Cetuximab
HR=0.631 (95% CI: 0.515-0.774)*
P<0.001
Months
145
238
CV + Cetuximab
88
163
54
101
15
38
0
3
Any grade
Grade 0
OS
15.0 mos
8.8 mos
RR
44%
28%
PFS
5.4 mos
4.3 mos
*Landmark analysis.
Gatzemeier et al, JTO 2008, Vol 3, No. 11, S4 (abstract 8)
Cetuximab + Platinum-Based Chemotherapy in
1st line NSCLC: Consistent Efficacy
Reference
Phase
Regimen
N
ORR, %
TTP/PFS, m
OS, m
Thienelt et al, 2005
I/II
Cet + pac/carbo
31
26
5
11
Robert et al, 2005
I/II
Cet + gem/carbo
35
28.6
5.5
10.3
Herbst et al, 2007
II
Cet + pac/carbo
204
34/31*
4/4
11/11
Socinski et al, 2009
II
Cet + pac/carbo
168
29.6/25†
4.7/4.3
11.4/9.8
Langer et al, 2007
II
Cet + pac/carbo‡
53
57
5.5
13.8
Belani et al, 2007
II
Cet + doc/carbo
76
14.5
4.7
11
Rosell et al, 2008
II
Cet + vin/cis
43
35
5.0
Kim et al, 2008
II
Cet+ bev/pac/carb
99
53
7
14.0
Butts et al, 2007
II
Cet + gem/pla
65
27.7
5.1
12.0
Lynch et al, 2007
III
Cet + tax/carbo
338
25.7
4.4
9.7**
Pirker et al, 2009
III
Cet + vin/cis
1125
36
4.8
11.3
*Randomized to concurrent vs sequential cetuximab;
†Randomized to pac/carbo q3w vs pac qw/carbo q4w
‡Pac qw/carbo q4w
* *Press release Aug 2008
8.3
Structure of the EGFR-ATP Binding Site
Exons 18, 19, 20
and 21- Tyrosine
kinase domain
In frame deletions
and missense
mutations
Red: deletions
Light blue: missense mutations
Dark blue: gefitinib
From: Lynch TJ et al. N Engl J Med. 2004;350:2129-2139.
Individualizing Anti-EGFR Therapy: Methodology
• EGFR mutation status by
gene sequencing
GGCGGGCCAAACTGCTGGGTGCG
• EGFR gene copy number by
fluorescence in situ hybridization
(FISH)
• EGFR protein expression by
immunohistochemistry (IHC)
• Serum Proteomics by MALDI MS
NCIC-C BR.21 TRIAL
NSCLC
1 prior
combination
regimen (no more
than 2)
Elderly may have
had single-agent
No requirement
for PD
R
A
N
D
O
M
I
Z
E
Erlotinib
150 mg daily
n=488
Placebo
n=243
Shepherd et al.NEJM, 2005
BR-21 Overall survival: all patients
Survival distribution function
1.00
42.5% improvement in median survival
0.75
T
M
T
a
r
c
e
v
a P
l
a
c
e
b
o
(
n
=
4
8
8
) (
n
=
2
4
3
)
M
e
d
i
a
n
s
u
r
v
i
v
a
l(
m
o
n
t
h
s
)
6
.
7
4
.
7
1
y
e
a
r
s
u
r
v
i
v
a
l(
%
)
3
1
2
1
HR=0.73, P<0.001
0.50
31%
0.25
Tarceva
TM
Placebo
21%
0
0
5
10
15
20
25
30
Survival time (months)
*HR and P-value adjusted for stratification factors at randomization plus HER1/EGFR status.
BR.21 Survival According to EGFR Mutation
+ EGFR mutation
No mutation
100
Log-rank: p=0.13
HR=0.73 (0.49, 1.10)
60
40
40
20
0
0
6
12
18
Months
24
30
Log-rank: p=0.45
HR=0.77 (0.40, 1.50)
60
20
0
Erlotinib
Placebo
80
Percentage
80
Percentage
100
Erlotinib
Placebo
0
p value for interaction = 0.97
6
12
18
Months
24
EGFR Mutation is NOT a Prognostic Marker
30
BR.21: EGFR FISH predicts Survival
BR21 FISH +
1.0
BR21 FISH -
1.0
0.8
0.8
Erlotinib
Placebo
0.6
Erlotinib
Placebo
0.6
0.4
0.4
0.2
Log-rank: p=0.008
HR=0.44 (0.23, 0.82)
0.0
0
6
12
18
24
Time (months)
30
Log-rank: p=0.59
HR=0.85 (0.48, 1.51)
0.2
0.0
0
6
12
18
24
Time (months)
30
FISH positivity is a prognostic marker
Tsao: NEJM, 2005
Biomarkers for EGFR-directed Therapy:
Summary of Current Status
 EGFR
TKIs
– EGFR protein (IHC) equivocal for predictive value
– EGFR mutation predicts response
– EGFR FISH predicts survival (BR.21)
– KRAS mutation predicts lack of activity
 Cetuximab
– EGFR protein (IHC): selection factor for FLEX
– EGFR mutation: not predictive (preclinical)
– EGFR FISH: conflicting data (S0342, BMS-099)
– KRAS mutation: not predictive (S0342, BMS-099)
N0723: Predictive Marker Study Design
NCCTG (Study Chair: Alex Adjei) + CALGB, ECOG, SWOG, NCIC
Others: C-Path & industry partners, Pharma
Initial
Registration
Strata
2nd
line
NSCLC
with
specimen
FISH
Testing
4 years accrual, 1196 patients
EGFR FISH +
(~ 30%)
EGFR FISH −
(~ 70%)
Randomize
Erlotinib
Pemetrexed
Erlotinib
Pemetrexed
957 patients
Outcome
1° PFS
2° OS,
ORR
1-2 years
minimum
additional
follow-up
• Power: validation of EGFR FISH as predictive biomarker
– 90% to detect 50% PFS improvement favoring erlotinib in FISH+
– 90% to detect 30% PFS improvement favoring pemetrexed in FISH−
– > 90% to detect interaction
• SWOG: Tumor repository & EGFR pathway analysis
Possible Selection Factors for
Individualizing Therapy of NSCLC
Characteristic
Clinical Factors
Drug Class
EGFR TKIs
Bevacizumab
Tumor Histology
Molecular Factors
Population
Female, Neversmoker, Asian
No Hemoptysis
EGFR TKIs
Adenoca
Bevacizumab
No SCCA b/o risk
Pemetrexed
Non-SCCA
IGF1R Inhibitors
SCCA (?)
EGFR TKIs
EGFR Mut/FISH
Cetuximab
EGFR IHC/FISH (?)
ERCC1/RRM1
Platinum Chemo
TS
Pemetrexed
Anti-Angiogenics
(?)
Iressa Pan Asian Study (IPASS) Phase III Trial: Gefitinib
vs Carboplatin/Paclitaxel in Selected Patients With
Advanced NSCLC
Never or light
ex-smoker* with
adenocarcinoma
histology
PS 0-2
Stage IIIB or IV
chemotherapy-naïve
NSCLC
N=1217
Gefitinib (250 mg/day)
R
A
N
D
O
M
I
Z
E
Offered carboplatin/paclitaxel
on progression
Carboplatin (AUC 5 or 6)
+
Paclitaxel (200 mg/m2)
3 times weekly up to 6 cycles
Primary endpoint: PFS (noninferiority)
Secondary endpoints: ORR, OS, QOL, disease-related symptoms, safety, and tolerability
Exploratory: biomarkers – EGFR mutation, gene copy number, and protein expression
*Never smoker=smoked <100 cigarettes in lifetime; light ex-smoker=stopped ≥15 years ago and
smoked ≤10 pack-years.
Mok. ESMO. 2008 (abstr LBA2).
Progression-Free Survival in ITT
Population
Probability
of PFS
1.0
Carboplatin /
Gefitinib
N
Events
0.8
609
453 (74.4%)
paclitaxel
608
497 (81.7%)
HR (95% CI) = 0.741 (0.651, 0.845) p<0.0001
0.6
Median PFS (months)
4 months progression-free
6 months progression-free
12 months progression-free
0.4
5.8
74%
48%
7%
5.7
61%
48%
25%
Gefitinib demonstrated superiority relative to
carboplatin / paclitaxel in terms of PFS
0.2
0.0
At risk :
Gefitinib
Carboplatin /
paclitaxel
0
4
8
12
16
20
24 Months
609
608
363
412
212
118
76
22
24
3
5
1
0
0
Primary Cox analysis with covariates
HR <1 implies a lower risk of progression on gefitinib
Progression-Free Survival in EGFR Mutation
Positive and Negative Patients
EGFR mutation positive
Gefitinib (n=132)
Carboplatin / paclitaxel (n=129)
HR (95% CI) = 0.48 (0.36, 0.64)
p<0.0001
No. events gefitinib, 97 (73.5%)
No. events C / P, 111 (86.0%)
0.8
0.6
Gefitinib (n=91)
Carboplatin / paclitaxel (n=85)
1.0
0.4
0.2
0.0
Probability of progression-free survival
1.0
Probability of progression-free survival
EGFR mutation negative
HR (95% CI) = 2.85 (2.05, 3.98)
p<0.0001
No. events gefitinib , 88 (96.7%)
No. events C / P, 70 (82.4%)
0.8
0.6
0.4
0.2
0.0
0
4
8
12
16
20
24
0
4
8
Months
At risk :
Gefitinib 132
C/P
129
108
103
71
37
31
7
12
20
24
1
0
0
0
0
0
Months
11
2
3
1
0
0
91
85
21
58
4
14
Treatment by subgroup interaction test, p<0.0001
ITT population – Mutation rate ~60%
Cox analysis with covariates
16
2
1
CONCLUSIONS
• Treatment paradigm are evolving due to:
– Molecular characterizations of disease and
agents to pick best fit
– Realization that all populations with this
disease are not the same
– Realization that lung cancer is quite
heterogeneous