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Understanding the reasons behind resistance to first-generation TKIs: mechanisms and therapeutic options

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Title: Understanding the reasons behind resistance to first-generation TKIs: mechanisms and therapeutic options


1
Mechanisms of Acquired Resistance to Epidermal
Growth Factor Receptor Tyrosine Kinase Inhibitors
(EGFR-TKI) in Non-Small Cell Lung Cancer (NSCLC)
Victor Cohen, MDCM, FRCPC Department of
Oncology Segal Cancer Center SMBD Jewish
General Hospital McGill University
2
Potential Conflict of Interest
  • Dr. Victor Cohen
  • Roche Canada/Research Support(2004-present)

3
Background
  • EGFR-TKI (gefitinib and erlotinib)developed as
    therapeutic agents for NSCLC
  • Members of a class of Quinazolium-derived agents
  • Inhibit EGFR pathway by binding (reversible) to
    ATP pocket domain
  • Antitumor activity in clinical trials but
    benefits modest

4
Background
  • 10 of (Western) patients treated with EGFR-TKI
    have dramatic and durable responses
  • Clinical features predicting sensitivity female,
    adenocarcinoma, Asian ethnicity and never-smoking
    history
  • 2004 EGFR mutations as a major determinant
    underlying dramatic responses following treatment
    with TKI

5
EGFR Mutations
6
EGFR Mutations
  • Mutations identified using DNA sequencing methods
  • Considered the gold standard
  • Non-sequencing assays offering ease of scoring
    and high sensitivity have been developed
  • Providing a robust and accessible approach to the
    rapid identification of EGFR mutations
  • Denaturing High Performance Liquid Chromatography
    (dHPLC)

7
EGFR Mutations
  • Prospective trials treating therapy-naïve
    patients with EGFR mutations with EGFR-TKI (200
    patients)
  • RR 55-82 and median TTP of 9-13 months (3 to
    4-fold greater than observed with chemotherapy)
  • Despite dramatic efficacy, all patients will
    ultimately develop resistance (acquired) to the
    agents

8
Acquired Resistance
  • Critical to understand mechanisms of acquired
    resistance
  • May lead to the development of effective
    therapies for patients who develop acquired
    resistance
  • Acquired resistance mechanisms have been studied
    most extensively in EGFR mutant cancers
  • Remains to be determined if mechanisms are shared
    with wild-type EGFR cancers

9
EGFR T790M Mutation
10
EGFR T790M Mutation
  • Detected from tumors of EGFR mutant NSCLC
    patients who have developed clinical resistance
    (in vitro EGFR-TKI resistant mutant cell lines)
  • Found in 50 of tumors
  • Analogous position to known resistance mutations
    to imatinib in other kinases gatekeeper
    mutation
  • ? Steric hindrance

11
Amplification of MET
12
Amplification of MET
  • Redundant activation of Her3 permits cells to
    transmit same downstream signaling in the
    presence of EGFR-TKI
  • Concomitant inhibition of both EGFR and MET is
    required to kill resistant cells
  • 22 of NSCLC with acquired resistance had MET
    amplification in specimens

13
Acquired Resistance
  • EGFR T790M and MET amplification account for
    60-70 of all known causes of acquired resistance
    to EGFR-TKI
  • Other mechanisms are likely to be discovered
  • TGF-ß IL-6 axis mediates selective and adaptive
    mechanisms of resistance to molecular targeted
    therapy in lung cancer
  • Yao et al. PNAS 35, 15535-40 (2010)

14
Acquired Resistance
  • Existence of subpopulation of cells intrinsically
    resistant to EGFR-TKI
  • Display features of EMT
  • Activation of TGF-ß mediated signaling was
    sufficient to induce EMT phenotypes
  • Upregulation of TGF-ß resulted in increased
    secretion of IL-6 (cells resisted treatment
    independently of EGFR pathway)

15
Acquired Resistance
  • Produced during inflammatory response
  • Mouse model used to determine whether
    inflammation might impair sensitivity
  • Induction of inflammation stimulated IL-6
    secretion and was sufficient to decrease tumor
    response
  • Data provide evidence indicating resistance could
    arise not only as a consequence of changes within
    cells but also through activation of tumor
    microenvironment

16
Challenges
  • Important to continue to study preclinical models
    (and tumors) that have developed resistance to
    uncover novel resistance mechanisms
  • Several challenges in translating preclinical
    studies into effective clinical therapies

17
Challenges
  • Accurately identifying which patients have which
    mechanisms of resistance
  • No repeated tumor biopsies
  • Critical in that the therapeutic strategy aimed
    at overcoming resistance may not be effective in
    all resistant patients
  • E.g. Irreversible inhibitors not effective in
    resistance mediated by MET amplification

18
Challenges
  • Multiple mechanisms of resistance can occur
    concurrently in same patient
  • Both EGFR T790M and MET have been detected in
    same specimens (occur independently in different
    metastatic sites in the same patient)
  • Therapeutic strategy aimed solely at one
    mechanism may not be effective or lead only to
    partial regressions
  • Combination strategies may be more comprehensive
    and potentially more effective

19
Challenges
  • Biological definition and detection of resistance
    mechanisms
  • T790M can sometimes be present as minor allele
    and yet be sufficient to cause resistance but may
    go undetected
  • Challenges with detection of MET amplification.
    Definition of what constitutes clinically
    significant amplification not well defined

20
Conclusion
  • Gefitinib and erlotinib are effective therapies
    for patients with EGFR mutant NSCLC
  • All patients ultimately develop resistance
  • Important to identify and study mechanisms of
    resistance as a means of rationally designing the
    next generation clinical studies
  • Several clinical trials (aimed at inhibiting
    known resistance mechanisms) are already underway

21
Clinical data on EGFR-TKIs and Overcoming
Resistance in Metastatic NSCLC2nd Quebec
Conference on Therapeutic Resistance in Cancer
Vera Hirsh, MD, FRCPC McGill University Health
Centre Montreal, QC, CANADA
22
Potential Conflict of Interest
  • Dr. Vera Hirsh
  • None

23
EGFR expression in human tumours
Tumours showinghigh EGFR expression
High expressiongenerally associatedwith
NSCLC 40-80 Prostate 40-80 Gastric 33-74 Head
and neck 90-100 Breast 14-91 Colorectal 25-77 P
ancreatic 30-50 Ovarian 35-70
Invasion Metastasis Late-stage disease Poor
outcome
24
EGFR mutation causes conformational change and
increased activation
Wild Type EGFR
Mutant EGFR
Ligand
Extracellular domain
Trans-membrane domain
Tyrosine kinase domain
ATP
Tyrosine phosphorylation
Ras-Raf-MAPK Proliferation
Pi3K-AKT Survival
EGFR internalisation Degradation/recycling
EGFR signals for longer at the cell membrane
Arteaga 2006, Gadzar et al 2004, Hendricks et al
2006, Sordella et al 2004
25
The distribution of activating mutations among
EGFR mutation positive patients is similar in
Asian and non-Asian studies
Distribution of mutation types ( of mutations) Distribution of mutation types ( of mutations) Distribution of mutation types ( of mutations)
Literature review Asian studies Non-Asian studies
Most prevalent mutation types Literature (n1523) Literature (n583)
Exon 19 deletion 51 58
Exon 21 point mutation L858R 42 32
Exon 20 2 6
Exon 18 G719A/C 3 2
Exon 21 L861Q 1 1
Some patients had more than one mutation type
26
BR.21 Study Design
Erlotinib 150 mg daily
RANDOM I ZE
Stratified by Centre PS, 0/1 vs 2/3 Response to
prior Rx (CR/PRSDPD) Prior regimens, (1
vs 2) Prior platinum, (Yes vs no)
Placebo 150 mg daily
21 Randomization
27
BR.21 Overall Survival
1.00 0.75 0.50 0.25 0
HR0.70 (95 CI, 0.58-0.85) P lt 0.001
Survival distribution function
31
42.5 improvement in median survival
Erlotinib Placebo
21
0 5 10 15 20 25 30
Survival time (months)
HR and P-value adjusted for stratification
factors at randomization plus HER1/EGFR status.
Shepherd et al. N Engl J Med. 2005353123-132.
28
IPASS first-line study design

Endpoints
  • Patients
  • Chemo-naïve
  • Age 18 years
  • Adenocarcinoma histology
  • Never or light ex-smokers
  • Life expectancy12 weeks
  • PS 0-2
  • Measurable stage IIIB/ IV disease
  • Primary
  • PFS (non-inferiority)
  • Secondary
  • ORR
  • OS
  • QoL
  • Disease-related symptoms
  • Safety and tolerability
  • Exploratory
  • Biomarkers
  • EGFR mutation
  • EGFR-gene-copy number
  • EGFR protein expression

Never smokers, lt100 cigarettes in lifetime
light ex-smokers, stopped ?15 years ago and
smoked ?10 pack yearsMaximum of 6 cycles
Carboplatin / paclitaxel was offered to
gefitinib patients upon progression AUC, area
under curve
Mok et al 2009
29
IPASS ORR
Odds ratio (95 CI) 1.59 (1.25, 2.01) p0.0001
Patients ()
(n609)
(n608)
Odds ratio gt1 implies a greater chance of
response on gefitinib Odds ratio and p-value from
logistic regression with covariates
Mok et al 2009
30
IPASS pre-planned analysis of ORR by EGFR
mutation status
  • Gefitinib
  • Carboplatin / paclitaxel
  • EGFR M OR (95 CI) 2.75 (1.65, 4.60), p0.0001
  • EGFR M- OR (95 CI ) 0.04 (0.01, 0.27), p0.0013

ORR ()
71.2
47.3
23.5
1.1
(n132)
(n129)
(n91)
(n85)
ITT populationORgt1 implies greater chance of
response on gefitinibOR and p-value from
logistic regression with covariate
Mok et al 2009
31
IPASS PFS
Probabilityof PFS
1.0
0.8
0.6
0.4
0.2
0.0
0
4
8
12
16
20
24
Months
Primary Cox analysis with covariates ITT
population HR lt1 implies a lower risk of
progression on gefitinibITT, intent-to-treat
Mok et al 2009
32
IPASS pre-planned analysis of PFSby EGFR
mutation status
EGFR M
1.0
N Median (m)
Gefitinib 132 9.5
Carboplatin / paclitaxel 129 6.3
0.8
HR (95 CI) 0.48 (0.36, 0.64) plt0.0001
0.6
Probability of PFS
0.4
0.2
0.0
0
4
8
12
16
20
24
Time from randomisation (months)
Primary Cox analysis with covariates
intent-to-treat (ITT) population Hazard ratio
(HR) lt1 implies a lower risk of progression on
gefitinib
Mok et al 2009
33
IPASS EGFR mutation is a strong predictor for
differential PFS benefit between gefitinib and
doublet chemotherapy
Gefitinib EGFR M (n132)Gefitinib EGFR M-
(n91)Carboplatin / paclitaxel EGFR M
(n129) Carboplatin / paclitaxel EGFR M- (n85)
Probabilityof PFS
1.0
EGFR MHR0.48, 95 CI 0.36, 0.64 plt0.0001 EGFR
M- HR2.85, 95 CI 2.05, 3.98 plt0.0001
0.8
Treatment by subgroup interaction test, plt0.0001
0.6
0.4
0.2
0.0
0
4
8
12
16
20
24
Time from randomisation (months)
M, mutation positive M-, mutation negative
34
PFS by EGFR mutation type IPASS
Exon 19 deletion
L858R
N
N
Gefitinib 64
Carboplatin / paclitaxel 47
Gefitinib 66
Carboplatin / paclitaxel 74
1.0
1.0
HR (95 CI) 0.553 (0.352, 0.868) p0.0101
HR (95 CI) 0.337 (0.255, 0.560) plt0.0001
0.8
0.8
0.6
0.6
Probability of PFS
Probability of PFS
0.4
0.4
0.2
0.2
0.0
0.0
0
4
8
12
16
20
24
0
4
8
12
16
20
24
Time from randomisation (months)
Time from randomisation (months)
Post hoc Cox analysis with covariates ITT
population
Mok et al 2009
35
IPASS QoL and symptom improvement rates for
overall population
p0.0148
p0.3037
plt0.0001
patients with sustained clinically relevant
improvementa
Evaluable for QoL population logistic
regression model with covariatesa6-point
improvement (FACT-L and TOI) 2-point
improvement (LCS), maintained 21 days

Mok et al 2009
36
IPASS post hoc QoL and symptom improvement
rates for EGFR M patients
plt0.0001
plt0.0001
p0.0003
patients with sustained clinically relevant
improvementa
Evaluable for QoL population logistic regression
model with covariatesa6-point improvement
(FACT-L and TOI) 2-point improvement
(LCS),maintained 21 days
Mok et al N Engl J Med 2009
37
IPASS 2010 updated OS analysis (ITT)
Gefitinib (n609)Carboplatin / paclitaxel
(n608) HR (95 CI) 0.90 (0.79, 1.02)
p0.109 No. events G 484 (80) C / P 470
(77)Median OS G 18.8 months C / P 17.4
months
1.0
Probabilityof survival
0.8
0.6
0.4
0.2
0.0
48
0
8
16
28
36
44
52
4
12
20
24
32
40
Patients at risk
Primary Cox analysis with covariates A hazard
ratio lt1 implies a lower risk of death on
gefitinibNo formal adjustment made for multiple
testing
Yang CH et al. ESMO 2010
38
IPASS 2010 summary of subsequent systemic
therapy (ITT)
Gefitinib (n609) C / P (n608)
No further systemic treatment 31 38
Chemotherapy 65 41
Platinum based 60 9
C / P 49 1
EGFR TKI 20 52
Gefitinib 5 41
Erlotinib 12 14
Other 5 6
exclude 20 patients in the gefitinib arm with
ongoing randomised treatmentPatients may have
also received other chemotherapy and / or EGFR
TKI during the study. Excludes single platinum
based chemotherapy Categories are not mutually
exclusive Radiotherapy, surgery, medical
procedures and other treatments excluded
Yang CH et al. ESMO 2010
39
IPASS 2010 OS by EGFR mutation status (ITT)
  • EGFR mutation

EGFR mutation -
Gefitinib (n132)Carboplatin / paclitaxel
(n129) HR (95 CI) 1.00 (0.76, 1.33)
p0.990No. events G 104 (79) C / P 95
(74) Median OS G 21.6 months C / P 21.9
months
Gefitinib (n91)Carboplatin / paclitaxel
(n85) HR (95 CI) 1.18 (0.86, 1.63)
p0.309No. events G 82 (90) C / P 74
(87)Median OS G 11.2 months C / P 12.7
months
1.0
0.8
0.6
Probability of survival
Probability of survival
0.4
0.2
0.0
52
0
4
8
12
16
20
44 48
24
28
32
36
40
Time from randomisation (months)
Time from randomisation (months)
0 0
Cox analysis with covariates a hazard ratio lt1
implies a lower risk of death on gefitinib No
formal adjustment for multiple testing was made,
therefore statistical significance at the
traditional 5 level cannot be claimed
Yang CH et al. ESMO 2010
40
IPASS 2010 overall survival EGFR mutation
non-evaluable (ITT)
Gefitinib (n386)Carboplatin / paclitaxel
(n394) HR (95 CI) 0.82 (0.70, 0.96)
p0.015No. events G 298 (77) C / P 301
(76) Median OS G 18.9 months C / P 17.2
months
Primary Cox analysis with covariates a hazard
ratio lt1 implies a lower risk of death on
gefitinibNo formal adjustment for multiple
testing was made, therefore statistical
significance at the traditional 5 level cannot
be claimed
Yang CH et al. ESMO 2010
41
IPASS PFS and OS by known EGFR mutation status
PFS (2008)
1.0
0.8
0.6
Probability of progression-free survival
0.4
0.2
0.0
0
Time from randomisation (months)
Patients at risk Gefitinib M Gefitinib M- C / P
M C / P M-
132 91 129 85
Yang CH et al. ESMO 2010
Patients at risk excludes censored patients and
those who have experienced an event
42
IPASS summary of biomarker outcomesPFS and OS
(ITT)
PFS (2008)
OS (2010)
All patients
Non-evaluable mutation status
Evaluable mutation status
EGFR mutation
EGFR mutation -
Non-evaluable gene copy status
Evaluable gene copy status
EGFR-gene-copy high
EGFR-gene-copy low
Non-evaluable expression status
Evaluable expression status
EGFR expression
EGFR expression -
0.5
1.0
2.0
4.0
0.5
1.0
2.0
4.0
Hazard ratio (G C / P) and 95 CI
Hazard ratio (G C / P) and 95 CI
Cox analysis with covariates A hazard ratio lt1
implies a lower risk of death or progression on
gefitinib No formal adjustment for multiple
testing was made, therefore statistical
significance at the traditional 5 level (95 CI
lt1) cannot be claimed
Yang CH et al. ESMO 2010
43
IPASS conclusions updated survival analysis
  • Mature OS (secondary endpoint) was similar for
    gefitinib and carboplatin / paclitaxel with no
    statistically significant difference between
    treatments in the overall population
  • A consistent OS outcome was observed across
    clinical subgroups with no significant difference
    in OS
  • There was no significant difference in OS across
    the EGFR biomarker subgroups
  • The true effect of the initial randomised
    treatment on OS is likely to have been confounded
    by the subsequent therapy, in particular the
    switching of patients to the alternative study
    therapy

Yang CH et al. ESMO 2010
44
IPASS conclusions overall summary
  • IPASS has demonstrated that positive EGFR
    mutation status is predictive of benefit from
    treatment with gefitinib over chemotherapy in
    terms of PFS, ORR and HRQoL
  • PFS is an endpoint unlikely to be confounded by
    subsequent treatments, therefore is a more
    appropriate endpoint for evaluation of treatment
    effect in first-line treatment of NSCLC than OS
  • IPASS has demonstrated the importance of
    biomarker testing in NSCLC, making a significant
    step towards personalised medicine
  • IPASS has changed clinical practice and treatment
    guidelines for patients with advanced NSCLC who
    harbour an EGFR mutation

HRQoL, health-related quality of life NSCLC,
non-small-cell lung cancer ORR, objective
response rate
Yang CH et al. ESMO 2010
45
Recently reported Phase III studies of gefitinib
as first-line treatment for NSCLC in selected
populations
NEJ002 (Japan)
  • Endpoints
  • Primary
  • PFS (superiority)
  • Secondary
  • OS, ORR, QoL, disease-related symptomssafety
    and tolerability

Gefitinib250 mg/day
  • Patients
  • Chemo-naïve
  • EGFR mutation-positive
  • PS 01

Carboplatin AUC 6 paclitaxel 200 mg/m2
3-weekly
Eastern Cooperative Oncology Group Maximum 9
cycles
Kobayashi et al 2009 Lee et al 2009
46
PFS and ORR with first-line gefitinib versus
doublet chemotherapy in EGFR mutation-positive
Asian patients across three Phase III studies
HR (95 CI) 0.613 (0.308, 1.221) p0.084
HR (95 CI) 0.48 (0.36, 0.64) plt0.0001
HR (95 CI) 0.36 (0.25, 0.51) plt0.001
Probability of PFS
Probability of PFS
Probability of PFS
0 100 200 300 400 500
0 5 10 15 20 25 30
0 4 8 12 16 20 24
months
days
months
First-SIGNAL
IPASS
NEJ002
plt0.001
p0.002
plt0.0001
ORR
ORR
ORR
Mok et al 2009 Lee et al 2009 Kobayashi et al
2009
47
1st-line treatment for mutation positive
patients with NSCLC
EURTAC Spanish Lung Cancer GroupPhase III1
Erlotinib
IIIB/IV NSCLC chemotherapy-naïve EGFR mutation
Platinum taxane or gemcitabine
48
New-generation erbB inhibitors
Reversible Irreversible
Gefitinib BIBW 2992
Erlotinib Neratinib (HKI-272)
AV-412 XL647
Lapatinib PF-00299804
BIBW 2992 potency and selectivity (IC50)
EGFR nM 0.5
HER2 nM 14
c-Met nM gt10000
VEGFR nM gt10000
Solca F et al. Proceedings, AACR-NCI-EORTC
International Conference on Molecular Targets and
Cancer Therapeutics. 2005118A242 Solca F et
al. Proceedings, AACR-NCI-EORTC International
Conference on Molecular Targets and Cancer
Therapeutics. 2005118A244
49
Resistance mutations
  • Mutations known to cause resistance to
    1st-generation EGFRi include
  • Exon 20 in-frame insertions
  • Exon 20 point-mutations (e.g. T790M)

Sharma et al. Nat Rev Cancer. 20077169181
50
BIBW 2992 active against resistance mutation
  • NCI-H1975 cells express L858R/T790M double-mutant
    EGFR

Li et al. Oncogene. 20082747024711
51
LUX-Lung 1 Trial design
  • Patients with
  • Adenocarcinoma of the lung
  • Stage IIIB/IV
  • Progressed after one or two lines of chemotherapy
    (incl. one platinum-based regimen) and 12 weeks
    of treatment with erlotinib or gefitinib
  • ECOG 02
  • N585

Randomization 21 (Double Blind)
Oral afatinib 50 mg once daily plus BSC
Oral placebo once daily plus BSC
Primary endpoint Overall survival
(OS) Secondary PFS, RECIST response, QoL (LC13
C30), safety
  • Radiographic assessments at 4, 8, 12 wks and
    every 8 wks thereafter
  • Exploratory biomarkers
  • Archival tissue testing for EGFR mutations
    (optional central lab)
  • Serum EGFR mutational analysis (all patients)

52
Demographics/prior treatment
Afatinib (n390) Afatinib (n390) Placebo (n195)
Median age, (range) 58 (3085) yrs 59 (3282) yrs 59 (3282) yrs
Female () 59 60 60
ECOG PS 0/1/2 () 24/69/8 27/65/8 27/65/8
Caucasian/East Asian/other () 31/58/11 37/56/7 37/56/7
Never smoker/Light ex-smoker/Other () 63/7/30 62/7/31 62/7/31
Stage IIIB/IV () 4/96 3/97 3/97
Prior chemo 1 line/gt 1 line () 59/41 61/39 61/39
Prior EGFR TKI E/G/EG () 55/39/6 55/41/4 55/41/4
Median duration of prior E/G 10.2 mos 9.7 mos 9.7 mos
48 wks duration on prior E/G () 45 47 47
lt 8 wks between prior E/G and randomization () 57 63 63
CR/PR on prior E/G () 46 44 44
52
53
Disease control rate and objective responses
Independent Review Independent Review
Afatinib () Placebo ()
PR, (regardless of confirmation) PR, (confirmed) 13 7 0.5 0.5
SD 8 wks 51 18
DCR (PRSD) 8 wks 58 19
Median duration of confirmed response 24
weeks P lt 0.01 compared to placebo P lt
0.0001 compard to placebo
54
PFS by independent review
55
Primary analysis Overall survival
56
Summary of anticancer therapy after treatment
discontinuation
Anticancer therapy Afatinib () Placebo ()
Any 68 79
Chemotherapy 61 70
Pemetrexed 36 47
Docetaxel 21 26
Vinorelbine 15 19
Other 26 26
EGFR TKI 12 24
Anti-angiogenesis 4 6
Radiotherapy 9 14
57
Patient reported outcomes
All scores were estimated from the EORTC
QLQ-LC13 except for Short of Breath and Pain
which used EORTC QLQ-C30 improved means that
EORTC symptom scores were 10 points lower than
baseline at any time during the study EORTC
cough, dyspnea and pain endpoints as
pre-specified in the trial protocol
58
LUX-Lung 2 Study design
Patients with Adenocarcinoma of the lung
Stage IIIB/IV EGFR mutation Chemo-naïve or
progressive disease following first-line
chemotherapy ECOG 02 N120
Oral BIBW 2992 once-daily until disease
progression or undue toxicity
Response assessment at 4, 8, 12 weeks every 8
weeks thereafter
Primary endpoint objective response
rateSecondary endpoints PFS, clinical benefit
time to OR duration of OR OS safety
59
Results
  • High degree of efficiency observed
  • - For all patients
  • Confirmed ORR 60
  • DCR 86
  • Median PFS 14 months
  • Median OS 24 months
  • For patients with del19/L858R
  • Confirmed ORR 64
  • DCR 88
  • Median PFS 15 months
  • Similar efficacy results in the first and
    second-line settings and across all subgroups
  • Similar magnitude of efficacy in patients with
    L858R as with del19 mutations

60
LUX-Lung 3 Phase III first-line trial in lung
cancer patients with EGFR mutations
Patients (n330) with Stage IIIB/IV
adenocarcinoma of the lung Presence of EGFR
mutation in the tumour tissue Chemonaive ECOG
0 or 1
Randomization
21
Oral BIBW 2992 40 mg once-daily
Cisplatin/pemetrexed
Primary endpoint PFS
61
Conclusion
  • EGFR-TKIs for EGFR-mutated tumours are becoming
    standard Rx in first-line metastatic NSCLC
  • BIBW 2992 activity in NSCLC, especially in
    EGFR-mutated tumours
  • Active against receptors that are resistant to
    first generation inhibitors (e.g.EGFRL858R/T790M)

62
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63
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