An atomic-level insight into the mechanisms of heterogeneous catalytic reduction of carbon dioxide
Heterogeneous mechanisms of primary and acquired...
Transcript of Heterogeneous mechanisms of primary and acquired...
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Heterogeneous mechanisms of primary and acquired resistance to third-
generation EGFR inhibitors
Sandra Ortiz-Cuaran1,†, Matthias Scheffler2,†, Dennis Plenker1,3, llona Dahmen1,
Andreas H. Scheel4, Lynnette Fernandez-Cuesta1,5, Lydia Meder4, Christine M. Lovly6,
Thorsten Persigehl7, Sabine Merkelbach-Bruse4, Marc Bos1, Sebastian Michels2, Rieke
Fischer2, Kerstin Albus4, Katharina König8, Hans-Ulrich Schildhaus9, Jana Fassunke4,
Michaela A. Ihle4, Helen Pasternack4,10, Carina Heydt4, Christian Becker11, Janine
Altmüller11, Hongbin Ji12,13, Christian Müller1, Alexandra Florin4, Johannes M.
Heuckmann14, Peter Nuernberg11, Sascha Ansén2, Lukas C. Heukamp4,14, Johannes
Berg15, William Pao6,Ψ, Martin Peifer1,16, Reinhard Buettner4,*, Jürgen Wolf2,*, Roman K.
Thomas1,4,*, Martin L. Sos3,*
1 Department of Translational Genomics, Center of Integrated Oncology Cologne–Bonn,
Medical Faculty, University of Cologne, 50931, Cologne, Germany.
2 Lung Cancer Group Cologne and Network Genomic Medicine (Lung Cancer),
Department I of Internal Medicine, Center for Integrated Oncology Cologne-Bonn,
University Hospital Cologne, Cologne, 50931, Cologne, Germany.
3 Molecular Pathology, Center of Integrated Oncology, University Hospital Cologne,
50937, Cologne, Germany.
4 Institute of Pathology, Center of Integrated Oncology, University Hospital Cologne,
50937, Cologne, Germany.
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5 Genetic Cancer Susceptibility Group, Section of Genetics, International Agency for
Research on Cancer (IARC-WHO), 69008 Lyon, France.
6 Department of Medicine, Vanderbilt University, Nashville, Tennessee 37212, USA.
7 Radiology Department, University Hospital Cologne, 50937, Cologne, Germany.
8 Labor Dr. Quade und Kollegen GmbH, Aachener Str. 338, 50933 Cologne, Germany.
9 Institute of Pathology, University Hospital Goettingen. Goettingen, Germany.
10 Pathology of the University Hospital of Luebeck and Leibniz Research Center Borstel,
Lübeck and Borstel, Germany.
11Cologne Center for Genomics (CCG), University of Cologne, 50931 Cologne,
Germany.
12 Key Laboratory of Systems Biology, CAS Center for Excellence in Molecular Cell
Science, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell
Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Science,
Shanghai, 200031, China.
13School of Life Science and Technology, Shanghai Tech University, Shanghai, 200120,
China.
14 NEO New Oncology AG, 51105, Cologne, Germany.
15 Institute for Theoretical Physics. University of Cologne. 50931 Cologne, Germany.
16 Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne,
Germany.
†These authors contributed equally to this work.
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ψ Current address: Roche Innovation Center Basel, Pharma Research and Early
Development, Roche, Basel, Switzerland.
Running Title
Resistant mechanisms to AZD9291 and rociletinib.
Keywords
Resistance, EGFR, adenocarcinoma, AZD9291, rociletinib
Financial Support
This work was supported by the German federal state North Rhine Westphalia (NRW)
and by the European Union (European Regional Development Fund: Investing In Your
Future) as part of the PerMed.NRW initiative (grant 005-1111-0025 to R.K.T., J.W. and
R.B) and by the German Ministry of Science and Education (BMBF) as part of the
e:Med program (grant no. 01ZX1303 to R.K.T., J.W., R.B. and M.P. and grant no.
01ZX1406 to M.L.S and M.P.). Additional funding was provided by the German Cancer
Aid (Deutsche Krebshilfe) as part of the small cell lung cancer genome sequencing
consortium (grant ID: 109679 to R.K.T., M.P., R.B.), by SFB832 (TP6 to R.K.T.), by the
Deutsche Forschungsgemeinschaft (DFG; through TH1386/3-1 to R.K.T and M.L.S.), by
the Deutsche Krebshilfe as part of the Oncology Centers of Excellence funding program
(to R.B., R.K.T. and J.W) by the EU-Framework program CURELUNG (HEALTH-F2-
2010-258677 to R.K.T. and J.W.), by a Stand Up to Cancer Innovative Research Grant
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(SU2C-AACR-IR60109 to R.K.T.) Stand Up To Cancer is a program of the
Entertainment Industry Foundation administered by the American Association for
Cancer Research, by the German Consortium for Translational Cancer Research
(DKTK) Joint Funding program. This study was supported in part by the National
Institutes of Health (NIH) and National Cancer Institute (NCI) R01CA121210 (C.M.L.)
and P01CA129243 (C.M.L.). C.M.L. was additionally supported by a Damon Runyon
Clinical Investigator Award a LUNGevity Career Development Award, a V Foundation
Scholar in Training Award, and an AACR-Genentech Career Development Award.
Corresponding authors (*)
Martin L. Sos
Roman K. Thomas
Jürgen Wolf
Reinhard Buettner
Conflicts of Interest:
R.K.T. is a founder and shareholder of NEO New Oncology AG, received commercial
research grants from AstraZeneca, EOS and Merck KgaA and honoraria from
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AstraZeneca, Bayer, NEO New Oncology AG, Boehringer Ingelheim, Clovis Oncology,
Daiichi-Sankyo, Eli Lilly, Johnson & Johnson, Merck KgaA, MSD, Puma, Roche and
Sanofi. M.P. is a founder and shareholder of NEO New Oncology AG and receives
consultation fees from NEO New Oncology AG. J.W. Consultant or Advisory Role and
Honoraria from Roche, Novartis, Pfizer, Boehringer-Ingelheim, AstraZeneca, Bayer
Pharmaceuticals, Eli Lilly, MSD and Clovis Oncology. C.M.L. has served as a consultant
for Pfizer, Novartis, Genoptix, Sequenom, and Ariad and has been an invited speaker
for Abbott and Qiagen. M.S. Consultant or Advisory role for Novartis, Boehringer
Ingelheim, and BMS, honoraria (lectures) from Novartis, AstraZeneca, Boehringer
Ingelheim, Roche, BMS. J.M.H. is a founder, employee and shareholder of NEO New
Oncology AG. S.M.B: received grants from Novartis and Merck Serono and honoraria
from Roche, AstraZeneca and Pfizer. M.L.S received a commercial research grant from
Novartis. R.B is a co-founder and CSO of Targos Molecular Pathology Inc, Kassel,
Germany. He has received lecture honoraria and participated in scientific advisory
boards with AstraZeneca, Roche, Pfizer, Novartis, Qiagen, Lilly, Boehringer, MSD, BMS
and Merck-Serono. H.U.S. has received research grants by Novartis Oncology and
ZytoVision, and honoraria and reimbursements for advisory membership and lectures
by Pfizer, Novartis, Roche, Zytomed, ZytoVision and Abbott Molecular. J.F received
honoraria from Roche.
Word count: 3502
Figures: 3 main, 4 supplementary
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Tables: 1 main
Translational relevance
Although the majority of EGFRT790M-mutant adenocarcinomas of the lung respond well
to third-generation EGFR inhibitors, resistance to these inhibitors remains a major
challenge in the field. We uncover ERBB2 and MET activation as potential bypass-track
mechanisms to third-generation EGFR inhibitors and suggest that treatment with third-
generation EGFR inhibitors may select for EGFR-mutant subclones that tolerate co-
occuring mutations in the MAPK pathway. Together with previous preclinical studies our
data supports the notion that activation of MAPK signaling might play a role in
resistance to these drugs. Our findings might be of broad interest to basic cancer
scientists and medical oncologists alike, as they provide insight related to the biology of
EGFR-mutant adenocarcinoma and have immediate implications for genetically
stratified treatment of these patients.
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Abstract
Purpose: To identify novel mechanisms of resistance to third-generation EGFR
inhibitors in lung adenocarcinoma patients that progressed under therapy with either
AZD9291 or rociletinib (CO-1686).
Experimental Design: We analyzed tumor biopsies from seven patients obtained
before, during and/or after treatment with AZD9291or rociletinib (CO-1686). Targeted
sequencing and FISH analyses were performed and the relevance of candidate genes
was functionally assessed in in vitro models.
Results: We found recurrent amplification of either MET or ERBB2 in tumors that were
resistant or developed resistance to third-generation EGFR inhibitors and show that
ERBB2 and MET activation can confer resistance to these compounds. Furthermore,
we identified a KRASG12S mutation in a patient with acquired resistance to AZD9291 as
a potential driver of acquired resistance. Finally, we show that dual inhibition of
EGFR/MEK might be a viable strategy to overcome resistance in EGFR-mutant cells
expressing mutant KRAS.
Conclusions: Our data suggests that heterogeneous mechanisms of resistance can
drive primary and acquired resistance to third-generation EGFR inhibitors and provides
a rationale for potential combination strategies.
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Introduction
In EGFR-mutant lung adenocarcinoma, targeted therapy with EGFR tyrosine
kinase inhibitors (TKIs) performs substantially better than standard chemotherapy in
terms of response rate (RR), progression-free survival (PFS) and tolerability (1).
Unfortunately, all patients will ultimately experience relapse with a median PFS of 7 to
16 months.
The major cause of resistance is the EGFR mutation T790M, at the gatekeeper
site (50-60%) (2–4). A third generation of covalent EGFR TKIs that specifically target
EGFR T790M as well as the activating EGFR mutations (e.g., L858R or exon 19
deletion), while sparing wild-type EGFR, have been evaluated clinically (5,6). In phase I
trials, rociletinib and AZD9291 have shown impressive clinical activity in patients with
EGFRT790M-mediated acquired resistance to reversible EGFR-TKIs with response rates
of 61% and 59%, and PFS of 13.5 and 13.1 months, respectively (5–9).
The acquisition of a secondary EGFR mutation, C797S, has been recently
reported in patients with relapse under therapy with AZD9291 (10,11). In preclinical
models, resistance to these inhibitors can also be driven by activation of the MAPK
pathway (12–14). These observations are of particular interest since EGFR mutations
are known to mainly occur in mutually exclusive manner with oncogenic mutations
within the MAPK pathway (15,16).
We performed genetic analyses on biopsies obtained from patients treated with
third-generation EGFR inhibitors in order to identify additional mechanisms of resistance
to these drugs.
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Patients and Methods
Study population
Whenever possible biopsies were obtained before treatment and after radiographic
progression under TKI therapy (with the exception of P2 and P3), at the times and with
the methods described in Table 1. Standard histopathology was performed to confirm
the histological subtype. Patients were treated in trials NCT01802632 and
NCT01526928. The Institutional Review Board (IRB) and the responsible ethics
committee approved collection and use of all patient specimens in this study. Written
informed consent was obtained from all subjects.
FISH analyses
Fluorescence in situ hybridization (FISH) for MET and ERBB2 was performed on
formalin-fixed paraffin-embedded tissue using labeled dual-color probes. Sections of
1.5µm were cut and hybridized with labeled probes for MET or ERBB2 and the
respective centromeric reference probe (ZytoLight Spec MET/CEN7 probes; ZytoLight
Spec ERBB2/CEN17 probes by ZytoVision, Bremerhaven, Germany). Slides were
reviewed at 630x and scored according to appropriate guidelines (17). For ERBB2 the
gastric cancer scoring system was used since no lung-specific recommendations are
available (18) .
DNA extraction and sequencing
Total DNA was obtained from formalin-fixed paraffin-embedded tumor tissue. DNA from
sections was extracted using the Puregene Extraction kit (Qiagen) according to the
manufacturer's instructions. DNA was eluted in 1× TE buffer (Qiagen), diluted to a
working concentration of 150 ng/µl and stored at –80 °C.
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Targeted sequencing
Targeted sequencing analysis was performed as described previously (19) using a
custom-made lung cancer panel consisting of 102 amplicons for the detection of hotspot
mutations in 14 lung cancer related genes. Isolated DNA (up to 50 ng) was amplified
with two customized Ion AmpliSeq™ Primer Pools. Library products were quantified
using Qubit® 2.0 Fluorometer (Qubit®ds DNA HS Kit, Life Technologies™), diluted and
pooled in equal amounts. 6-8 pM were spiked with 5% PhiX DNA (Illumina® San Diego,
CA, USA) and sequenced with the MiSeq™ reagent Kit V2 (300-cycles, Illumina®). Data
were exported as FASTQ files and analyzed using the in-house pipeline.
Generation of stably transduced cell lines
H1975 (CRL-5908) and HCC827 (CRL-2868) cells were obtained from the American
Type Culture Collection (ATCC). PC9, PC9GR and HCC827GR cells were kindly
provided by Dr. Hongbin Ji (Shanghai Institutes for Biological Sciences, China), Dr.
Passi Jänne (Broad Institute, USA), and Dr. Jeffrey Engelman (MGH, USA).
respectively. Cells were cultured with RMPI medium supplemented with 10% FBS and
1% penicillin/streptomycin at 37ºC under 5% CO2.
Generation of cells harboring pBabe-puro empty vector, EGFRT790M, ERBB2WT, KRASWT
or KRASG12S was done by stable transduction as described previously (20) using a
pBabe-puro retroviral vector (Addgene). Cells expressing the corresponding mutants
were generated by retroviral transduction and subsequent puromycin selection. The
expression of the mutant was verified by RT-PCR and further Sanger sequencing and
by Western blot analysis.
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cDNA transcription
RNA was isolated from PC9KRAS-G12S and HCC827KRAS-G12S cells using TRIZOL reagent
(Invitrogen) and cleaned up using the RNeasy MinElute Cleanup Kit (Qiagen) following
the manufacturers’ protocols. Finally, 1 μg of RNA was transcribed into cDNA using
Superscript III reverse transcriptase (Invitrogen, #18064).
Reagents
AZD9291, rociletinib, afatinib, crizotinib, trametinib and selumetinib were synthesized
according to published methods. For cell culture experiments, each compound was
dissolved in dimethyl sulfoxide (DMSO), aliquoted and stored as 10mM stocks at -80°C.
HGF (R&D Systems) was re-suspended in PBS +0.1 % BSA and aliquots stored at -
20ºC.
Cell viability assays
Cells were plated into 96-well culture plates in RMPI medium supplemented with 10%
FBS and 1% penicillin/streptomycin, at a density of 1500 cells/well, cultured overnight
and treated the following day. Cell viability was determined after 4 to 6 days by
measuring cellular ATP content (CellTiter-Glo, Promega) as described previously (20).
GI50 values were calculated by plotting luminescence intensity against drug
concentration in nonlinear curves using GraphPad Prism (GraphPad). Synergy scores
were calculated as previously described (21). For long-term viability assays, the
reported “Cell number change (%)” was determined as: 100*(Value/Baseline)/Baseline.
Each point was performed with three replicates. Unless otherwise noted, three
independent experiments were performed and a representative result is presented.
Error bars are mean -/+ standard deviation (SD).
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Crystal Violet Staining
Cells were plated at a density of one million cells/well and incubated overnight. Cells
were treated with AZD9291 the following day and then again 72 hours after. After 6
days of drug exposure, cells were fixed with 1% paraformaldehyde. For staining, a
solution of 0.1% crystal violet was added and incubated for 20 minutes. Plates were
inverted and dried overnight and images were taken the next day.
Western blot analyses
Cells lysates were blotted as described previously (20). The following antibodies were
used: phospho-EGFR (Y1068), total EGFR, phospho-ERBB2 (Y1248), total ERBB2,
phospho-MET (Y1234/Y1235), total MET, phospho-AKT (Ser473), total AKT, phospho-
ERK (T202/Y204), total ERK, actin (Cell Signaling Technology) and conjugated
antibodies to rabbit and mouse (Millipore).
Statistical analyses
Statistical analyses were performed using Graph Pad Prism 5.0 (USA). We used
student’s t-test (unpaired, 2-sided). A p-value of <0.05 was used as a threshold
considered to call statistical significance. PFS was assessed from start of the respective
therapy until progression or death. Survival analyses were performed using Kaplan
Meier statistics, providing median and 95% confidence interval (CI). For response
evaluation, the Response Evaluation Criteria in Solid Tumors (RECIST V1.1) (22) were
used.
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Results
Mechanisms of primary and acquired resistance to third generation EGFR inhibitors
We obtained specimens from seven patients treated with third-generation EGFR
inhibitors AZD9291 (n=5) or rociletinib (n=2), within two clinical trials (clinicaltrials.gov,
NCT01802632 and NCT02147990) after acquired EGFRT790M positive resistance to first-
or second-generation EGFR kinase inhibitors. The PFS for third-generation EGFR TKI
therapy ranged from 1.2 to 19.4 months (median 4.2 months, CI 3.7 - 4.7 months,
Figure 1A). The best reduction of the sum of the largest tumor diameters under
treatment, according to RECIST V1.1 (22), ranged between 0.1% and 79.2%, with three
patients presenting growth of non-target lesions (P1, P3 and P5, Figure 1B).
The pattern of response varied across these patients: two patients (P1, P3)
experienced primary resistance to rociletinib (defined as progression on the first
restaging scan), while two patients had stable disease (P2, P4) under treatment with
AZD9291. Finally, three cases (P5, P6 and P7) presented with partial responses to
treatment with AZD9291, with reductions in diameters of more than 50% (Figure 1A and
1B). For these patients, unfortunately, disease recurred after 16.5, 19.4 and 7 months,
respectively.
In order to characterize the molecular mechanisms that may be linked with such
heterogeneous response patterns, we performed fluorescence in-situ hybridization
(FISH) for known EGFR resistance markers (ERBB2 and MET) and targeted next-
generation sequencing on tumor tissue from these patients (see Methods). FISH
analyses of a massively progressive pleural effusion (non-target lesion) collected after
three weeks of treatment initiation from P1 (PD, 625 mg rociletinib twice daily) and a
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lung biopsy sample collected before treatment from P2 (SD, 180mg AZD9291 daily),
revealed ERBB2 amplification (7.3 and 3.7 gene copies, respectively) (Figure 1C).
Since ERBB2 amplification has been shown to confer resistance to first
generation EGFR TKIs (23), we hypothesized that amplified ERBB2 might substitute for
EGFR signaling in this context and explain the lack of response to of AZD9291 and
rociletinib in P1 and P2. To test this hypothesis, we evaluated the impact of ERBB2
overexpression on the sensitivity to AZD9291 and rociletinib in PC9GR cells
(EGFRT790M). Despite relatively a relatively low overexpression of ERBB2 in PC9GR
cells we observed decreased sensitivity to both drugs at nanomolar concentrations
(Figure 1D and Supplementary Figure 1A). Thus, our results indicate that ERBB2
activation may contribute to resistance against rociletinib and AZD9291.
The tumor biopsy collected before treatment of P3 (PD, 625mg rociletinib twice
daily) showed high-level amplification of MET (MET/CEN7 ratios 2.10, 4.42 MET
copies) (Figure 2A). Unfortunately, no baseline comparative sample (prior to erlotinib
treatment) was available for this patient. In the case of P4 (SD, 80mg AZD9291 daily)
an initial tumor reduction (20.8%) was followed by an increase in the tumor volume after
4.1 months of treatment (Figure 2B). In this patient too, the biopsy taken after the initial
response exhibited high-level amplification of MET (MET/CEN7 ratio 5.35, 11.42 MET
copies) that was not observed before therapy with AZD9291 (Figure 2C). P5 (PR, 80
mg AZD9291 daily) had an initial tumor response of 79% and presented a new lesion in
the liver that harbored a high-level MET amplification (MET/CEN7 ratios 1.88, 21.92
MET copies, Figure 2D, left panel) and ERBB2 amplification (4.25 gene copies, Figure
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2D, right panel). Of note, targeted sequencing of these samples did not show additional
clinically relevant mutations (Table 1).
To functionally test whether MET amplification might reduce the sensitivity to
AZD9291 or rociletinib, we stably overexpressed EGFRT790M-mutant constructs in
HCC827 cells (MET wild type) and their gefitinib-resistant derivate, HCC827GR cells
(MET amplified) (Supplementary Figure 1B). In line with previous reports (24), the
presence of MET amplification decreased the sensitivity to both third-generation EGFR
inhibitors (Figure 2E) and led to sustained phosphorylation of ERK and AKT (Figure 2F).
Furthermore, concomitant inhibition with either AZD9291 or rociletinib and the MET
inhibitor, crizotinib, resulted in pronounced cytotoxicity and reduced AKT and ERK
activation in HCC827GREGFR-T790M cells (Figure 2E and 2G). These results were
confirmed in EGFRT790M expressing cells (H1975 and PC9GR) where MET was
activated through addition of exogenous HGF (Supplementary Figure 1 C-F).
Thus, our clinical observations are in line with previous reports where both
ERBB2 and MET amplification has been found to be associate with loss of efficacy of
third-generation EGFR inhibitors in EGFR-mutant tumors (25). More importantly, we
provide functional evidence that activation of ERBB2 and MET signaling may induce
resistance to this new class of EGFR inhibitors.
Finally, patient 6 (P6) presented with a tumor response of 72.6% followed by
emergence of new liver metastases 19.4 months after start of therapy. The liver biopsy
revealed the retention of the initial EGFR exon19 deletion (allelic fraction, AF: 42.6%,
Supplementary Figure 2A) and the EGFRT790M mutation (AF: 27.66%) together with the
presence of a secondary EGFRC797S mutation (Figure 2H) that was not present in the
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pre-treatment biopsy (Supplementary Figure 2B). Of note, the liver biopsy obtained at
relapse also harbored an intermediate-level MET amplification (MET/CEN7 ratios 1.14,
5.67 MET copies, Figure 2I). The EGFRC797S mutation abrogates the irreversible binding
of third-generation EGFR inhibitors and has been described to confer resistance to
AZD9291 thus providing a rational for the observed resistance phenotype in P6
(10,26,27).
KRAS mutation and resistance to third-generation EGFR inhibition
In our cohort, a forth patient (P7) relapsed after having initially responded to
treatment with AZD9291. This patient received different lines of treatment before
developing resistance through EGFRT790M under combination therapy with afatinib and
cetuximab. After enrollment into the AURA trial (NCT01802632) the tumor responded to
AZD9291 treatment (160 mg/d) with a PR (best response: 54.3%, Figure 3A) for 8
months. However, the fifth follow-up revealed the appearance of a new lesion in a fast
growing cervical lymph node. Targeted sequencing of the specimens obtained before
and after treatment with AZD9291 (both from the cervical lymph nodes) showed a slight
decrease in the fraction of reads containing the original activating EGFR mutation (43%
before treatment with AZD9291 vs. 32% after treatment, Supplementary Figure 2C) and
the disappearance of EGFRT790M (25% before treatment with AZD9291, Supplementary
Figure 2D). Finally, in two independent sequencing runs we found a novel KRASG12S
mutation (38% of the reads), which had not been detected before therapy with AZD9291
(Figure 3B). In general, the disproportionate levels of C>T/G>A changes that occur as a
consequence of formalin fixation are more apparent at low allelic fractions (1-10%) (28).
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In the relapse sample of P7, the C>T/G>A changes where comparable to other patient
samples or freshly prepared DNA from cell lines sequenced in the same batch,
suggesting that the KRAS mutation detected is not a formalin-fixation artifact
(Supplementary Figure 2E). The EGFRC797S mutation had also been found in the
plasma of this patient (10) but was not observed in the lymph node biopsy
(Supplementary Figure 2F). Moreover, the KRASG12S mutation was not detected in the
plasma of this patient. These observations suggest, that heterogeneous mechanisms of
acquired resistance might be operant in this patient.
To investigate whether expression of an activated KRAS allele might contribute
to resistance to third-generation EGFR inhibitors we stably transduced EGFR-mutant
PC9 cells with the KRASG12S-mutant. PC9 cells that expressed the KRASG12S-mutant
were selected under treatment with puromycin for at least two weeks. The resulting
PC9KRAS-G12S cells expressed both the original EGFR exon19 deletion and the KRASG12S
mutation (Supplementary Figure 3A). Concomitant expression of both mutants was also
observed in a PC9KRAS-G12S clone obtained by serial dilution (Supplementary Figure 3B).
When compared to the KRAS wild type transduced cells (PC9KRAS-wt), PC9KRAS-
G12S were less sensitive to AZD9291 (Figure 3C and 3D). Furthermore, introduction of
KRASG12S resulted in increased KRAS expression and sustained ERK phosphorylation
under treatment with AZD9291 (Figure 3E). Similar results were observed in
HCC827KRAS-G12S cells (Supplementary Figures 3C and 3D) where the introduction of
the KRAS mutation also resulted in decreased sensitivity to rociletinib (Supplementary
Figure 3C). Confirming a role of MAPK signaling in inducing resistance in PC9KRAS-G12S
cells, combined treatment with AZD9291 and the MEK inhibitor, trametinib, was highly
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synergistic (synergy score: 5.48 (21), p-value 4.14E-08) (Figure 3F and Supplementary
Figure 4A). Consistent with these results, AZD9291 failed to fully inhibit downstream
MAPK signaling except in the presence of trametinib (Figure 3G). Similar results were
observed with the combination of AZD9291 and selumetinib (Figure 3F and
Supplementary Figure 4B). Finally, concomitant EGFR and MEK inhibition was also
synergistic in HCC827KRAS-G12S cells (Supplementary Figures 4C and 4D). These
findings demonstrate that mutant KRAS may induce acquired resistance to third-
generation EGFR inhibitors.
Discussion
Here, we provide clinical and functional evidence for the role of ERBB2 and MET
amplifications as well as KRAS mutations as possible mechanisms of resistance to
third-generation EGFR inhibitors. The role of ERBB2 activation in resistance has been
previously reported for first-generation EGFR inhibitors (23). The activity of AZD9291
against ERBB2 is known to be limited and despite the presence of a metabolite AZ5104
that shows inhibition of ERBB2 it is conceivable that ERBB2 signaling may reduce the
overall activity of third generation inhibitors in patients (6). Since the potency against
ERBB2 was greater with the AZ5104 metabolite than with AZD9291, it would be
interesting to determine the metabolites levels in the plasma of patients to predict the
emergence of ERBB2 as a potential bypass mechanism of resistance to AZD921. Our
functional in vitro results suggest that the activity of both AZD9291 and rociletinib may
decrease through specific activation of ERBB2 signaling. These observations go in line
with the studies reporting ERBB2 as a mechanism of resistance to first-generation
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EGFR inhibitors (29). The use of patient-derived EGFRT790M-mutant cell lines may help
defining the activity of these inhibitors on ERBB2 and characterizing the molecular
context of the role of ERBB2 as a mechanism of resistance to third-generation EGFR
inhibitors.
The role of MET amplification in acquired resistance to first-generation EGFR
inhibitors has been studied extensively (30–32). According to our results MET activation
may similarly play a role in resistance to third-generation EGFR inhibitors since MET is
not a relevant off-target for these drugs. Our observations also confirm previous reports
on the efficacy of the combination of rociletinib with crizotinib in these tumors (33).
Combination therapies have proven successful in the setting of resistance to first-
generation EGFR inhibitors (34) and early phase clinical trials are evaluating the
combination of rociletinib with crizotinib (33), or AZD9291 with the MET inhibitor,
savolitinib, in EGFR-mutant lung cancer (35). It might therefore be important to
determine the presence of these alterations before therapy with any EGFR inhibitor.
Interestingly, we identify an activating KRASG12S mutation in a tumor rebiopsy
obtained at the time of acquired resistance to AZD9291. This mutation is of particular
interest since EGFR and KRAS mutations typically occur in a mutually exclusive fashion
in lung cancer (16,36). Indeed, a recent report evidenced that the expression of
inducible KRASG12V constructs in EGFR-mutant PC9 cells results in decreased cell
viability after seven days of selection with doxycyclin (37). Anecdotal reports show
evidence of co-occurrence of KRAS and EGFR mutations in lung cancer patients
(38,39). More recently Hata et al. described two distinct evolutionary paths for the
development of resistance to EGFR inhibition (14). In this study cell lines that developed
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resistance at late stages were enriched for NRAS and KRAS mutations suggesting that
under prolonged selection a distinct population of EGFR mutant cells may well tolerate
the presence of oncogenic MAPK pathway activation. In our functional experiments,
decreased cell viability was observed in cells expressing both EGFR and KRAS
mutants; however, this phenotype was overcome after about 10 passages under
antibiotic selection. In line with our results, in the study performed by Unni et al. (37) the
induction of mutant KRAS rescued PC9 cells from the lethal effects of erlotinib, thus
implying that the toxicity of co-expression of mutant KRAS and EGFR depend on the
kinase activity of mutant EGFR. We speculate that EGFR inhibition through AZD9291
may functionally deplete oncogenic EGFR signaling to a degree that would allow the
emergence of cells that harbor EGFR and KRAS mutations. Unfortunately, our analyses
do not permit distinguishing the individual clones that harbor each individual lesion.
RAS activation is an alternative bypass pathway of resistance in lung
adenocarcinomas. Reactivation of the MAPK pathway via either KRAS copy number
gain or decreased expression of the MAPK phosphatase DUSP6 was associated with
resistance to ALK inhibitors in patients with EML4-ALK–rearranged lung
adenocarcinoma (40). Furthermore, activation of members of the RAS family was
shown to confer resistance to ROS1 inhibitors (41). In EGFR-mutant lung cancers,
resistance to EGFR TKIs may be associated with increased dependency on RAS-MAPK
signaling, including ERK activation, loss of NF1 and CRKL amplification (13,42–44).
Amplification of MAPK1 was reported as a resistance mechanism of WZ4002 and has
been observed in AZD9291 (12). Moreover, NRAS mutations as well as copy number
gain of KRAS and NRAS (12,13) were recently identified as mechanisms of resistance
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to AZD9291 in preclinical models. Our data therefore add to these findings and provide
clinical evidence for a possible role of MAPK pathway activation in the context of
acquired resistance to third-generation EGFR inhibitors.
Our findings also highlight the role of dual EGFR/MEK inhibition in cells that
express EGFR and KRAS mutations and are in line with previous reports that identified
that this combination may be effective in cell that display EGFR-TKI resistance through
activation of MAPK signaling (13). The combination of AZD9291 and selumetinib is
currently being evaluated in a phase I trial (NCT02143466) and may thus help to further
delineate the role of MAPK signaling in modulating the response to third-generation
EGFR inhibitors.
Of note, a plasma sample collected from P7 one month after the cervical lymph
node had been obtained for these studies, revealed the presence of a EGFR C797S
mutation (AF: 1.3%), as well as EGFR T790M (AF: 0.7%), yet no KRAS mutation
(Subject 2, (10)). Neither the EGFRC797S nor the EGFRT790M mutations were detected in
the lymph node lesion after progression (Supplementary Figures 2D and 2F), thus
suggesting that the KRAS mutation might not necessarily be the unique driver of
resistance in this patient and likely reflecting heterogeneity in the acquisition of
resistance to third-generation EGFR inhibitors. Our data provides further evidence
multiple clones with unique resistance mechanisms may give rise to the overall
resistance observed in patients treated with third-generation tyrosine kinase inhibitors
(45).
The analysis of a larger cohort of patients would be key to confirm our
observations and perform a more comprehensive profile of primary and/or acquired
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resistance to AZD9291 and rociletinib. Moreover, a longitudinal analysis of the
emergence of multiple mechanisms of resistance using liquid biopsies could provide
evidence of the prevalence of each mechanism and help defining their individual role in
resistance to third-generation EGFR inhibitors.
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Acknowledgments:
We are grateful to all the patients who contributed their tumor specimens. We thank
Lead Discovery GmbH for synthetizing the compounds used for this study, as well as
the computing center of the University of Cologne (RRZK) for providing the CPU time on
the DFG-funded supercomputer ‘CHEOPS’. We thank Nike Bahlmann, Seda Ercanoglu,
Graziella Bosco, Gladys Cuarán and Ximena Ortiz for their technical assistance.
Author’s Contributions:
Conception and design: S.Ortiz-Cuaran, M. Scheffler, R. Büttner, J. Wolf, M.L.Sos,
R.K. Thomas.
Development of methodology: S.Ortiz-Cuaran, M. Scheffler, L. Fernandez-Cuesta, W.
Pao, R. Büttner, J. Wolf, M.L.Sos, R.K. Thomas.
Acquisition of data (provided animals, acquired and managed patients, provided
facilities, etc.): S.Ortiz-Cuaran, M. Scheffler, D. Plenker, A. H. Scheel, I. Dahmen, L.
Meder, T. Persigehl, S. Michels, R. Fischer, M.A. Ihle, C. Becker, K. Albus, J. Fassunke,
J. Altmüller, C. Müller, P. Nuernberg, L.C. Heukamp, R. Büttner.
Analysis and interpretation of data (e.g., statistical analysis, biostatistics,
computational analysis): S.Ortiz-Cuaran, M. Scheffler, A. H. Scheel, T. Persigehl, S.
Merkelbach-Bruse, J. Berg, M. Peifer.
Writing, review, and/or revision of the manuscript: S.Ortiz-Cuaran, M. Scheffler, J.
Wolf, M.L.Sos, R.K. Thomas.
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28
Administrative, technical, or material support (i.e., reporting or organizing data,
constructing databases): D. Plenker, A. H. Scheel, I. Dahmen, C.M. Lovly, M. Bos, K.
König, S. Merkelbach-Bruse, H-U Schildhaus, H. Künstlinger, C. Heydt, H. Ji, C.
Becker, A. Florin, J. Heuckmann, P. Nuernberg, S. Ansén, R. Büttner.
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Figure Legends
Figure 1. Primary and acquired resistance to third-generation EGFR inhibitors. A,
duration of treatment of patients that underwent therapy with AZD9291 (blue) or
rociletinib (green). PD: progressive disease; SD: stable disease; PR: partial response.
MET and/or ERBB2 amplification were detected before treatment (gray) or at relapse
(black) under AZD9291 or rociletinib. B, waterfall plots showing best percentage change
in the size of target or non-target (*) lesions. C, FISH analyses with probes for
chromosomal loci containing ERBB2 (P1 and P2, green signal) and the respective
centromeric reference probe (red signal). D, viability assays of PC9GRe.v and
PC9GRERBB2 cells indicating the change in cell number after 6 days of treatment with
DMSO or increasing concentrations of either AZD9291 or rociletinib, in comparison to
the number of cells at the initiation of drug exposure.
Figure 2. Activation of MET confers resistance to third-generation EGFR inhibitors. A,
FISH analyses with probes for chromosomal loci containing MET (P3, green signal) and
the respective centromeric reference probe (red signal). B, tumor response analysis for
P4 using the quantitative imaging tool mint Lesion™. Here, the volumes of the target
lesions are shown and added up, according to RECIST. This representation shows how
the different lesions respond individually as well as the sum of the changes in the target
lesions. Follow-up scans (*) were performed every eight weeks. C, FISH analyses
assessing the presence of MET amplification in the liver lesion collected before
AZD9291 and after relapse. D, evaluation of MET (left panel) and ERBB2 amplification
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(right panel) by FISH in a new liver lesion presented by P5. E, Viability assay of
HCC827GREGFR-T790M cells after treatment with AZD9291 (A) or rociletinib (R), alone or
in combination with crizotinib (C). Presented is the change in cell number in comparison
to the number of cells at baseline. After 6 days of treatment, cell viability was
determined by measuring intracellular ATP content. ***, P < 0.001. HCC827EGFR-T790M
and HCC827GREGFR-T790M cells treated with AZD9291 (1µM) or rociletinib (1µM) for 24
hours and lysed. Protein expression and phosphorylation of the MET, EGFR, AKT and
ERK, as well as expression of BIM and actin was monitored by immunoblotting. G,
HCC827GREGFR-T790M cells treated with AZD9291 (1µM) or rociletinib (1µM) alone or in
combination with crizotinib (1µM) for 24 hours. Expression of the indicated proteins actin
was monitored by immunoblotting. H, Integrative Genomics Viewer (IGV) - based
visualization of reads of targeted NGS that identify the EGFRT790M and EGFRC797S
mutations in P6. I, FISH analyses with probes for chromosomal loci containing MET
(green signal) and the corresponding centromeric reference probe (red signal).
Figure 3. Acquired resistance to AZD9291 mediated by acquired KRASG12S mutation.
A, tumor response analysis for P5 using the quantitative imaging tool mint Lesion™
showing the volumes of the target lesions. This representation shows how the different
lesions respond individually as well as the sum of the changes in the target lesions.
Follow-up scans (*) were performed every eight weeks. B, Integrative Genomics Viewer
(IGV) - based visualization of reads of targeted NGS that identify the wild type KRAS
(baseline, top panel) and an acquired CT mutation in 38% of reads, encoding a
KRASG12S mutation (relapse, bottom panel). C, long-term viability assay of PC9KRASWT
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and PC9KRAS-G12S cells treated with AZD9291 at the indicated concentrations for 6 days.
Cell viability is presented as the percentage of change in cell number (compared to
baseline). D, long-term proliferation assay of PC9KRAS-WT and PC9KRAS-G12S cells
exposed to increasing concentrations of AZD9291 for 6 days. Cells were stained using
crystal violet. **, P<0.01; ***, P<0.001. E, cellular signaling of PC9KRAS-WT and PC9KRAS-
G12S cells treated with increasing concentrations of AZD9291 for 24 hours. Whole cell
lysates were analyzed by immunoblotting. F, long-term viability assay of PC9KRAS-G12S
cells demonstrating the change in cell number after treatment with AZD9291 (100nM)
alone or in combination with either trametinib (1µM) or selumetinib (1µM), in comparison
with the cell number before drug exposure. Cell viability was determined after 6 days of
treatment. G, PC9KRAS-G12S cells were treated with AZD9291 (100nM) alone or in
combination with either trametinib (1µM) for 24 hours and lysed. Protein expression and
phosphorylation levels of EGFR, AKT, ERK and the expression of and KRAS, BIM and
actin were monitored by immunoblotting.
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A
C
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P6
P5
P4
P3
P2
P1
Time of treatment (months)
ME
T a
mp
ER
BB
2 a
mp
AZD9291
Rociletinib
PD
SD
PD
SD
PR
PR
PR
P1 (PD) ERBB2 amp
EGFR p.T790M
P2 (SD) ERBB2 amp
EGFR p.T790M
Before AZD9291 Before AZD9291
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A
F
Figure 2
H
B
AZD9291(1µM)
Rociletinib (1µM)
HCC827GR EGFR T790M
EGFR
pEGFRY1068
pAKTS473
AKT
ERK
BIM
pERKT202/Y204
Actin
Crizotinib (1µM)
MET
pMETY1234/Y1235
-
-
-
+
-
-
-
-
+
+
-
+
-
+
-
-
+
+
DM
SO
A (
1µ
M)
R (
1µ
M)
C (
1µ
M)
Co
mb
o A
+C
Co
mb
o R
+C
0
50
100
150
200
250
Ch
an
ge in
cell n
um
ber
(%)
******
HCC827GREGFR T790M E G
EGFR
pEGFRY1068
pAKTS473
AKT
ERK
pERKT202/Y204
MET
pMETY1234/Y1235
HCC827EGFR T790M
DM
SO
A
ZD
9291
R
oci
letinib
HCC827GREGFR T790M
DM
SO
A
ZD
9291
R
oci
letinib
BIM
Actin
D
I
Baseline 1 2 3
Follow-ups
300mm
250mm
200mm
150mm
100mm
50mm
0mm
June 14’
*
Aug 14’ Sep 14’
*
Nov 14’
*
Pleura
Liver S8
Liver S2/3
Kidney left
C
T790M
Patient 6
C797S
P3 (PD) MET amp
EGFR p.T790M
Before AZD9291
P4 (SD) MET amp and EGFR p.T790M
Before AZD9291 Under AZD9291
P5 (PR) EGFR p.T790M
MET amp ERBB2 amp
Under AZD9291 Under AZD9291
P6 (PR) MET amp, EGFR p.T790M
Under AZD9291
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A B
C
F
Figure 3
EGFR
pEGFRY1068
pAKTS473
AKT
ERK
Actin
BIM
pERK/Y204
KRAS wt
AZD9291 (µM)
KRAS
KRAS G12S
0 0.1 1 0 0.1 1
PC9 KRAS G12S
EGFR
pEGFRY1068
pAKTS473
AKT
ERK
BIM
pERKT202/Y204
KRAS
Actin
- -
+ -
- +
+ +
AZD9291(100nM)
Trametinib (1µM)
D E
G
DMSO 10nM 100nM 1µM-200
0
200
400
600
800
Concentration AZD9291 (µM)
Ch
an
ge in
cell n
um
ber
(%)
PC9 KRAS wt
PC9 KRAS G12S
**
** ***
AZD9291 (µM) 0 0.1 1
PC9
KRAS wt
PC9
KRAS G12S
DM
SO
A (
10
0n
M)
T (
1µ
M)
Co
mb
o T
S (
1µ
M)
Co
mb
o S
-200
0
200
400
600
Ch
an
ge in
cell n
um
ber
(%)
******
Before
AZD9291
Under
AZD9291
KRAS G12S
Patient 7
140mm
120mm
100mm
80mm
60mm
40mm
10mm
0mm
Baseline 1
Kidney left
Thorax left
Liver S8
Liver S6
Lung left
Oct. 13’
*
Dec. 13’
*
Jan. 14’ Feb. 14’
*
April 14’
*
June 14’
*
2 3 4 5
Follow-ups
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Patie
nt
num
ber
Age
Sex
Initi
al
biop
sy
site
FISH
Pr
imar
y m
utat
ion
TKI
resi
stan
cePF
S (m
onth
s)St
art o
f tr
eatm
ent
Tim
e on
tr
eatm
ent
(mon
ths)
Trea
tmen
t his
tory
(tim
e on
trea
tmen
t in
mon
ths)
OS
(yea
rs)
Dat
e of
re
biop
syR
ebio
psy
site
Type
of
rebi
opsy
Type
of
sam
ple
FISH
Met
hod
Mea
n co
vera
geO
ther
m
utat
ions
171
FN
AN
ot d
one
EG
FR E
xon
19 d
el; E
GFR
T7
90M
Roc
iletin
ib1.
9D
ecem
ber
2014
1.9
CIS
/PEM
(5),
gap
(6),
Erlo
tinib
(11)
, CO
-168
6 (2
) 2.
1 ∆
Janu
ary
2015
Pleu
ral
effu
sion
†.
FFPE
ER
BB
2 a
mp
miS
eq49
75E
GFR
Exo
n 19
de
l, E
GFR
T7
90M
264
FLu
ngE
RB
B22
am
p E
GFR
L86
1Q;
EG
FR T
790M
AZD
9291
4.2
Oct
ober
20
147.
4*C
IS/V
INO
/RTX
(3),
Afat
inib
(4
), AZ
D92
91 (7
*)1.
2 ∆
..
..
.m
iSeq
9560
EG
FR L
861Q
, E
GFR
T79
0M
354
FLi
ver
ME
T a
mp
EG
FR E
xon
19 d
el; E
GFR
T7
90M
Roc
iletin
ib1.
2N
ovem
ber
2014
3.2
CIS
/PEM
(1),
Erlo
tinib
/RTX
(2
), G
efiti
nib
(9),
Roc
iletin
ib (3
), R
ocile
tinib
/Criz
otin
ib (1
)
1.3
..
..
..
..
457
MLi
ver
No
ME
T a
mp
EG
FR L
858R
; E
GFR
T79
0MAZ
D92
914.
0Ju
ly 2
014
4.6
Gef
itini
b (2
), C
arbo
/PEM
(2
), m
aint
enan
ce P
EM (3
), C
ARBO
/DO
CE
(4),
AZD
9291
(4),
EMD
12
1406
3 (3
), Er
lotin
ib/C
rizot
inib
(1)
1.9
Nov
embe
r 20
14Li
ver
CT-
guid
ed
biop
syFF
PEM
ET
am
pm
iSeq
4561
EG
FR L
858R
, E
GFR
T79
0M
560
MLi
ver
Bloc
k no
t av
aila
ble
EG
FR E
xon
19 d
el, E
GFR
T7
90M
AZ
D92
9116
.5M
ay 2
014
17.5
Erlo
tinib
(7),
CAR
BO/P
ACLI
(2),
inte
rmitt
end
RTX
(13)
, AZ
D92
91 (1
8)
3.2
∆O
ctob
er
2015
Live
rC
T-gu
ided
bi
opsy
FFPE
ME
T a
mp,
E
RB
B2
am
pm
iSeq
1217
EG
FR E
xon
19
del,
EG
FR
T790
M
656
FLi
ver
(2x)
Not
don
eE
GFR
Exo
n 19
del
, EG
FR
T790
M
AZD
9291
19.4
Oct
ober
20
1322
.3
Gef
itini
b (9
), R
TX (3
), Er
lotin
ib (7
), Af
atin
ib (1
5),
Afat
inib
/Cet
uxim
ab (3
), PE
M/E
rlotin
ib (9
), AZ
D92
91 (2
2)
5.9
∆Ju
ly 2
015
Live
rC
T-gu
ided
bi
opsy
FFPE
ME
T a
mp
miS
eq21
76
EG
FR E
xon
19
del,
EG
FR
T790
M, E
GFR
C
797S
751
FLy
mph
no
de
No
ME
T am
p,
no
ER
BB
2 a
mp
EG
FR E
xon
19 d
el, E
GFR
T7
90M
AZ
D92
917.
5N
ovem
ber
2013
8.9
Gef
itini
b (1
7),
CIS
/PEM
/RTX
(4),
Afat
inib
(6
), Af
atin
ib/C
etux
imab
(1
1), A
ZD92
91 (9
)
4.5
May
201
4Ly
mph
no
de
Endo
scop
ic
biop
sy v
ia
esop
hagu
sFF
PEN
o M
ET
amp,
n
o E
RB
B2
am
pm
iSeq
540
EG
FR E
xon
19
del,
KR
AS
G
12S
* Tre
atm
ent o
ngoi
ng
∆ St
ill al
ive
† O
btai
ned
durin
g th
erap
y
PFS:
Pro
gres
sion
free
sur
viva
l. O
S: O
vera
ll su
rviv
al. H
et: H
eter
ogen
eity
CIS
= C
ispl
atin
, PEM
= p
emet
rexe
d, V
INO
= v
inor
elbi
ne, R
TX =
radi
atio
n th
erap
y, C
ARBO
= c
arbo
plat
in, D
OC
E =
doce
taxe
l, O
P =
surg
ery,
BEV
A =
beva
cizu
mab
, TR
O =
trof
osfa
mid
e, G
EMC
I = g
emci
tabi
ne, P
ACLI
= p
aclit
axel
Patie
nt in
form
atio
nPr
e-tr
eatm
ent a
mpl
eD
rug
resi
stan
t sam
ple
Sequ
enci
ng d
ata
rebi
opsy
Reb
iops
y in
form
atio
n
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Published OnlineFirst June 1, 2016.Clin Cancer Res Sandra Ortiz-Cuaran, Matthias Scheffler, Dennis Plenker, et al. to third-generation EGFR inhibitorsHeterogeneous mechanisms of primary and acquired resistance
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