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Cancer Biology and Signal Transduction

Genomic and Molecular Screenings IdentifyDifferent Mechanisms for Acquired Resistance toMET Inhibitors in Lung Cancer CellsPol Gimenez-Xavier1, Eva Pros1, Ester Bonastre1, Sebastian Moran2, Ana Aza1,Osvaldo Gra~na3, Gonzalo Gomez-Lopez3, Sophia Derdak4,5, Marc Dabad4,5,Anna Esteve-Codina4,5, Jose R. Hernandez Mora2, Diana Salinas-Chaparro1,Manel Esteller2,6, David Pisano3, and Montse Sanchez-Cespedes1

Abstract

The development of resistance to tyrosine kinase inhibitors(TKI) limits the long-term efficacy of cancer treatments involvingthem. We aimed to understand the mechanisms that underlieacquired resistance (AR) to MET inhibitors in lung cancer. EBC1cells, which have MET amplification and are sensitive to TKIsagainst MET, were used to generate multiple clones with AR to aMET-TKI. Whole-exome sequencing, RNA sequencing, and globalDNAmethylation analysis were used to scrutinize the genetic andmolecular characteristics of the resistant cells. AR to the MET-TKIinvolved changes common to all resistant cells, that is, phenotypicmodifications, specific changes in gene expression, and reactiva-tion of AKT, ERK, and mTOR. The gene expression, global DNAmethylation, and mutational profiles distinguished at least two

groups of resistant cells. In one of these, the cells have acquiredsensitivity to erlotinib, concomitantly with mutations of theKIRREL, HDAC11, HIATL1, and MAPK1IP1L genes, amongothers. In the other group, some cells have acquired inactivationof neurofibromatosis type 2 (NF2) concomitantly with strongoverexpression of NRG1 and a mutational profile that includeschanges in LMLN and TOMM34. Multiple independent andsimultaneous strategies lead to AR to theMET-TKIs in lung cancercells. The acquired sensitivity to erlotinib supports the knowncrosstalk between MET and the HER family of receptors. For thefirst time, we show inactivation of NF2 during acquisition ofresistance to MET-TKI that may explain the refractoriness toerlotinib in these cells.Mol Cancer Ther; 16(7); 1366–76.�2017 AACR.

IntroductionMost novel therapeutic approaches in cancer are developed on

the basis of our increasing knowledge of underlying oncogenicmutations. In the case of lung cancer, our better understanding ofits genetic architecture has enabled novel treatments to bedesigned, most of which are based on drugs that target growthfactor receptors with tyrosine kinase activity (RTK) that are genet-ically activated in the tumors. A strong effect of decreasing cell

growth following the administration of specific tyrosine kinaseinhibitors (TKI) has been observed in lung cancer cells withalterations at various RTKs, including mutations, gene fusions,and strong focal gene amplification (GA) at ALK, EGFR, ERBB2,FGFR1,MET, PDGFRA, RET, and ROS genes, among others (1–9).Inasmuch as most of these observations are based on screeningsmade in cancer cell lines, these have become essential preclinicaltools for evaluating how the cancer genotype determines theresponse to these specific drugs (1–3).

Despite the success of genotype-directed therapies, sometumors with activated target RTK exhibit frequent failures in theprimary response to these specific TKIs. This is the so-calledintrinsic (i.e., primary) resistance, which has been associated withthe simultaneous activation of parallel signal transduction path-ways that circumvent the targeted pathway blockade (9). Further-more, inmost tumors that are initially sensitive to these therapies,acquired (i.e., secondary) resistance inevitably develops due to theacquisition of genetic alterations in the kinase target or in mole-cules acting in related signaling pathways (10–14). The origin ofthe genetic alterations responsible for the acquired resistance (AR)could either be generated de novo or arise as clonal expansionsfrom preexisting minor subclones. In lung cancer, this has beenextensively modeled, especially to study the responses to EGFRinhibitors, using isogenic pairs of drug-sensitive and drug-resis-tant human cancer cell lines (10, 12–14). It is well established thatresistance to TKIs against EGFR can be acquired through thep.T790M mutation at EGFR, which prevents the binding of theinhibitor to the receptor, or the amplification or overexpression of

1Genes and Cancer Group, Cancer Epigenetics and Biology Program (PEBC),Bellvitge Biomedical Research Institute-IDIBELL, Hospitalet de Llobregat, Bar-celona, Spain. 2Cancer Epigenetics Group, Cancer Epigenetics and BiologyProgram (PEBC), Bellvitge Biomedical Research Institute-IDIBELL, Barcelona,Spain. 3Bioinformatics Unit, Structural Biology and BioComputing Programme,Spanish National Cancer Centre (CNIO), Madrid, Spain. 4CNAG-CRG, Centre forGenomic Regulation (CRG), Barcelona Institute of Science and Technology(BIST), Barcelona, Spain. 5Universitat Pompeu Fabra (UPF), Barcelona, Spain.6Institucio Catalana de Recerca i Estudis Avancats (ICREA), Barcelona, Spain.

Note: Supplementary data for this article are available at Molecular CancerTherapeutics Online (http://mct.aacrjournals.org/).

P. Gimenez-Xavier and E. Pros contributed equally to this article.

Corresponding Author: Montse Sanchez-Cespedes, Bellvitge BiomedicalResearch Institute (IDIBELL), Av. Gran Via de Hospitalet, 199-203, Hospitaletde Llobregat, Barcelona 08908, Spain. Phone: 349-3260-7132; Fax: 349-3260-7219; E-mail: [email protected]

doi: 10.1158/1535-7163.MCT-17-0104

�2017 American Association for Cancer Research.

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RTKs such asMET, EGFR, AXL, and ERBB2 (10–15). Likewise, ARto crizotinib in EML4-ALK-positive lung cancer cell lines has beenassociated with point mutations or amplification in ALK or KIT,among other genes (15, 16).

Regarding the MET oncogene, the genetic and molecularmechanisms linking AR to its associated TKI are not fully under-stood. Amplification and overexpression of wild-type KRAS oractivation of BRAF and of the HER pathways are some of themechanisms that have been proposed for the AR to MET-TKIs invarious types of cancer (17–21).Here,wehaveused theEBC1 lungcancer cells, which are intrinsically sensitive to the MET-TKIs dueto genetic activation of MET by GA, as a cancer cell model toinvestigate AR. We obtained various clones from the EBC1 paren-tal cells that had become refractory to the MET-TKIs and, takingadvantage of next-generation sequencing technologies, scruti-nized these various cell subpopulations for genetic andmolecularalterations responsible for drug resistance.

Materials and MethodsGeneration of AR to PHA665752 and tyrosine kinase inhibitortreatments

The EBC1 lung cancer cell line was obtained from the JCRBCell Bank (National Institutes of Biomedical Innovation,Health and Nutrition, Japan), grown under recommendedconditions, and maintained at 37�C in a humidified atmo-sphere of 5% CO2. The cell line was obtained directly from therepository and passaged for fewer than 4 months after receipt,before generating the various derived resistant cells. The cellswere tested for mycoplasma infection prior to the generation ofthe various resistant cells and periodically thereafter. All thecells used in the experiments, tested negative for the infection.Genomic DNA and total RNA were extracted using standardprotocols. The identity of the EBC1 cells, both the parental andeach of the resistant pools and clones, was verified by deter-mining the presence of the TP53 mutation (5) and amplifica-tion of the MET gene in the cells.

To generate AR to MET inhibitors, the EBC1 cells were culturedfor about 16weeks in amediumwith an increasing concentrationof PHA665752 (Ref. 2693, Tocris Bioscience), from a startingconcentration of 62.5 nmol/L to a final concentration of 1 mmol/L. Individual cells capable of proliferation were allowed to growand were selected as individual clones. Individual clones or poolsof them were selected for subsequent experiments, transferred toseparate plates and treated with 100 nmol/L of PHA665752. TheEBC1 cells were also tested for sensitivity to the MET inhibitor,crizotinib (Ref. 4368, Tocris Bioscience), the FGFR1 inhibitor,PD173074 (Ref. 2499, Sigma-Aldrich), the EGFR inhibitor, erloti-nib (sc-202154, Santa Cruz Biotechnology), and the AXL inhibitor,R428 (BGB324, Selleckchem). Information about the chemicalstructure of the PHA665752, PD173074, and R428 compoundswas previously published (22–24).

Cell viability, wound healing, and colony formation assaysFor the cell-viability assays, cells were seeded at a density of

2,000 cells/well on 96-well plates and incubated overnightbefore being exposed to different concentrations of the drugfor 72 hours. Ten microliters of a solution of 5 mg/mL MTT (3-(4,5)-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide;Sigma Chemical Co.) was added and incubated for 3 hours at37�C. The precipitated formazan was dissolved with 100 mL of

lysis buffer and absorbance was measured at 596 nm. Data wereanalyzed by nonlinear regression using GraphPad Prism Soft-ware version 5.2 (GraphPad Software, Inc.). Viabilities wereexpressed as a percentage of the untreated controls. The IC50

was determined from the dose–response curve. Results arepresented as the median of at least three independent experi-ments performed in triplicate for each combination of cell lineand compound.

For wound-healing assays, cells were grown in 6-well plateswith complete medium. After 90% confluence was reached, themediumwas replaced with FBS-freemedia for 24 hours. A woundwas created with a germ-free 100-mL pipette tip in the monolayer.The cells were washed with PBS and grown in FBS-free media for72 hours. The wounds were observed under a phase contrastmicroscope (IX81, Olympus). The images were analyzed bydrawing lines at the wound edges. The width of the scratch wasmeasured using TScratch software (25).

For colony formation assays, cells were seeded at a density of2,000 to 4,000 cells per well, in 6-well plates, in DMEM mediacontaining 10% (v/v) FBS, with or without the correspondingtreatment, and stained 14 to 15 days later with Crystal Violet(Merck Millipore). Each assay was performed in triplicate. Col-onies were quantified using ImageJ software.

FISH analysisTo determine gene copy number of the MET gene, we per-

formed dual-color FISH analysis in interphase nuclei, followingpreviously described protocols (26). Briefly, we used a BAC clonelabeled in Spectrum Red for the MET gene (RP11-95I20) andcontrol BAC, labeled in Spectrum Green and located pericentro-merically (RP11-45N18).

Antibodies and Western blotsThe antibodies are indicated in the Supplementary Methods.

For Western blots, cells were lysed into ice-cold RIPA lysis cellbuffer supplemented with protease and phosphatase inhibitorcocktails (Complete Mini and Phosphostop), followed by clear-ance of lysates by microcentrifugation. Supernatants wereresolved on an SDS-PAGE gel, transferred onto nitrocellulosemembranes (Amersham,GEHealthcare Life Science), and probedwith the indicated antibodies. Detection was done using a chemi-luminescence system (Millipore).

Whole-exome sequencing and RNA sequencingGenomic DNA was extracted from the EBC1-P, EBC1-PR2,

and EBC1-PR4 cells. The cells were collected and placed in 1%SDS/proteinase K (10 mg/mL) at 58�C for 1 hour and subjectedto phenol–chloroform extraction and ethanol precipitationfollowing standard protocols. DNA was assessed for qualityby visualization in an agarose gel and quantified with Nano-Drop and PicoGreen. For RNA sequencing (RNA-seq), totalRNA was extracted from EBC1, EBC1-C1, EBC1-V8, EBC1-PR1,EBC1-PR2, EBC1-PR3, EBC1-PR4 cells, using a TRIzol Plus RNAPurification Kit (Purelink RNA Mini Kit, Ambion). RNA qualityand integrity (RIN) were measured with an Agilent 2100Bioanalyzer (Agilent Technologies) and quantified with aNanoDrop Spectrophotometer.

Whole-exome sequencing (WES) andRNA-seqwere carried outat the Spanish National Genome Analysis Center (CNAG-CRG;ref. 27). For exome capture, the SureSelect Human All Exon Kit v4or v5 (Agilent Technologies) was used, and for RNA library

Acquired Resistance to MET Inhibitors in Lung Cancer

www.aacrjournals.org Mol Cancer Ther; 16(7) July 2017 1367




preparation the TruSeq RNA Library Preparation Kits (Illumina)were used before deep sequencing in an HiSeq 2000 IlluminaAnalyzer (Illumina) to generate 2� 100 read pairs for WES and 2� 75 read pairs for RNA-seq.

WES and RNA-seq and data analysis to identify variants specificto resistant cells

Data were analyzed at the Spanish National Cancer Centre(CNIO,Madrid, Spain) or at the CNAG-CRG. RNA-seq reads weremapped against the human reference genome (hg19), with theGEM RNA-seq pipeline (http://gemtools.github.io/; see supple-mentary methods for details).

The raw data produced by this study are available in thefollowing databases: RNA-seq and WES at the Sequence ReadArchive (SRA) under accession number SRP096814.

qRT-PCRWe used qRT-PCR to validate genes identified by RNA-seq

analysis. Total RNA was extracted with PureLink RNA Mini Kit(Ambion, Life Technologies) and reverse-transcribed withSuperScript II Reverse Transcriptase (Invitrogen, Thermo FisherScientific) and Random Primers (Promega), according to themanufacturers' instructions. qRT-PCR was performed in anApplied Biosystems 7900HT Fast Real-Time PCR System usingSYBR Green PCR Master Mix (Applied Biosystems, Life Tech-nologies). Three biological replicates were carried out. All datawere normalized against the expression of gene control ACTB.The sequences of the primers used are provided in Supplemen-tary Table S1.

Genetic screening of NF2To validate the inversion found at the neurofibromatosis type 2

(NF2) gene, exons 2 to 7 (NM_000268.3) were PCR-amplified atthe DNA level and specific primers were designed at the mRNAlevel to amplify the fusion transcript (primer sequences arepresented in Supplementary Table S1). PCR products were direct-ly sequenced using the BigDye Terminator v3.1 Cycle SequencingKit (Applied Biosystems) in an Applied Biosytems 3070 DNAAnalyzer. Mutation Surveyor u3.97 software (SoftGenetics, LLC)was used to analyze sequences. The presence of an intragenichomozygous deletion was concluded when product amplifica-tions at NF2 were recurrently negative in multiplexed PCR reac-tions with GAPDH.

Virus infection and shRNA experimentsTo deplete NF2 expression in the EBC1-P cells we used

shRNAs, which were purchased from SIGMA-MISSION (Len-tiExpress Technology, Sigma-Aldrich) as a glycerol stock of 5pLKO plasmids carrying NF2-specific shRNA sequences andscramble control (Supplementary Table S1). For the infections,lentiviruses carrying the short hairpin RNAs (shRNA) weregenerated within the 293T cells. 293T cells were cotransfectedwith each specific shRNA and the packaging plasmids psPAXand pMD2.6 (Sigma Aldrich). After 48 hours, 293T filteredsupernatants were collected and used in the culture media forthe different cell lines for an additional 24 to 48 hours. Aftervirus infection, different cell populations were selected withpuromycin for 72 or 96 hours. To obtain stable expression ofthe shRNAs, cell populations were selected with puromycin for2 to 3 weeks.

Global methylation microarray analysisFor DNA methylation microarrays, all DNA samples were

assessed for integrity, quantity, and purity by electrophoresis ina 1.3% agarose gel, PicoGreen quantification, and NanoDropmeasurement. We performed bisulfite conversion of 500 ng ofgenomic DNA using an EZ DNA Methylation Kit (ZymoResearch). Bisulfite-converted DNA (200 ng) was used for hybrid-ization on the MethylationEPIC BeadChip (Illumina). Raw fluo-rescence intensity values were normalized with Illumina GenomeStudio software (V2011.2) using "control normalization" withbackground correction. Normalized intensities were then used tocalculateDNAmethylation levels (b values). Likewise, valueswithlow statistical power (indicated by detection values of P > 0.01)were excluded from the analysis. Genotyping probes present onthe chip and DNA methylation probes overlapping with knownSNPs were also removed. Probes were considered to be in apromoter CpG island if they were located within a CpG island(UCSC database) and <2,000 bp away from a transcription startsite (outside chromosome X). Samples were clustered in anunsupervised manner by using the 5,000 most variable valuesfor CpGmethylation according to the SD for the CpG sites locatedin promoter regions by hierarchical clustering using the completemethod for agglomerating the Manhattan distances. Microarraymethylation data are available from the Gene Expression Omni-bus (GEO) under accession code GSE92608.

Statistical analysisAnalysis consisted of two-tailed unpaired Student t andMann–

Whitney U tests and ANOVA. Continuous variables were sum-marized asmeans and SDs.We considered group differences to besignificant for values of P < 0.05.

ResultsMorphologic modifications and changes in the levels of cellstructure and signal transduction-related proteins underlie ARto MET inhibitors in EBC1 cells

The EBC1 cell line endures high levels of MET-GA and is verysensitive to MET inhibition (5, 18). To generate resistance to theMET inhibitor, PHA665752,we exposed the EBC1 cells to increas-ing concentrations of the drug for sixteenweeks. By the end of thiscontinuous exposure, various clones or pools of resistant cells haddeveloped AR to the drug in vitro (Fig. 1A and B). We selected twoof these clones (EBC1-C1 and EBC1-V8) and four pools (EBC1-PR1, EBC1-PR2, EBC1-PR3, and EBC1-PR4) for various anal-yses aiming to characterize the cells morphologically andmolecularly. The levels of MET amplification remained similarin the parental and resistant cells, whereas the phosphorylation(activation) of MET (pMET) was abrogated in the resistant cells(Fig. 1B and C). Together, these observations indicate that, inall the resistant cells, the resistance to the TKI had been acquiredthrough a mechanism that does not involve genetic changes inMET. We confirmed that the various EBC1-resistant (henceforthEBC1-R) cells were also refractory to crizotinib treatment,another TKI known to inhibit the tyrosine kinase activity ofMET (Supplementary Fig. S1).

The EBC1-R cellswere very different,morphologically, from theEBC1-parental (henceforth EBC1-P) cells. Although the EBC1-Pcells had an elongated appearance with large protrusions, all theEBC1-R cells were polygonal and exhibited patchy growth (Fig.1D and Supplementary Fig. S1). The EBC1-R cellsmigrated slower

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than the EBC1-P cells in the wound-healing assay (Fig. 1E).Because these modifications are indicative of strong molecularand genetic shifts we determined the levels of various proteinsassociated with cell shape. Two of the EBC1-R cells (-PR3 and-PR4) underwent a sharp drop in the levels of vimentin (Fig.1F), suggesting the involvement of a mesenchymal-to-epithe-lial transition, associated with the resistance to PHA665752.We observed dramatic changes in the p120ctn protein (28) thataffected all the EBC1-R cells. Furthermore, there was a slightdecrease in the levels of the GAPDH protein in all the EBC1-Rcells (Fig. 1F). No changes in the levels of any of these proteinswere observed in the EBC1-P cells, following a short treatmentwith the TKI, indicating that these are stable molecular mod-ifications for the adaptation of cells to a constant exposure toMET inhibition.

EBC1 cells with AR to MET inhibitors bypass mTOR inhibitionand undergo a shift in gene expression profiles

Next, we examined the activation/inactivation of signaltransduction molecules acting downstream of the MET recep-tor. As expected, the administration of the PHA665752 drugto the EBC1-P cells greatly reduced the phosphorylation ofAKT and ERK as well as the levels of phosphorylation of theribosomal proteins S6, indicating the inactivation of mTOR.All the EBC1-R cells bypassed the inhibitory effect of the drugand maintained activation of AKT, ERK, and mTOR, althoughthe levels of phosphorylated AKT were somehow decreased inmost of the EBC1-R cells (Fig. 1F). Taken together, theseresults indicate that all the EBC1-R cells maintain activatedmTOR, but in a manner that is independent of the level ofMET activity.

Figure 1.

Characterization of EBC1-R cells. A, Description of the EBC1-R cells generated. They arose from clonal expansion of individual EBC1-R cells or from pools ofEBC1-R cells. B, Left, cell-growth inhibition upon administering PHA665752 treatment to EBC1 parental (EBC1-P) and resistant (EBC1-PR2) cells. Linesrepresent cell survival relative to untreated controls of the MTT assays in the cells treated with increasing concentrations of the inhibitor for 72 hours. Errorbars indicate the standard deviation. Right, examples of metaphase nuclei from EBC1-P cells and the indicated resistant cells at the MET gene (probesin red). Control probe in green. C, Western blot anti-phospho-MET (pMETY1234/Y1235) and anti-MET (MET) in the indicated cell lines. Constitutive METactivation is present in the EBC1 parental cells (EBC1-P) cells before treatment with the PHA665752 (PHA, 100 nmol/L) inhibitor. The EBC1-R cells maintain theability to inhibit MET phosphorylation in the presence of the drug. D, Phase contrast images showing the changes in cell morphology between EBC1parental (EBC1-P) and the indicated resistant cells. Scale bar, 100 mm. E, Left, phase contrast microscopy images of the wound-healing migration assay.Wound closure was monitored at the indicated times. On the right, quantification of the assay. The open wound area was quantified with TScratch softwareand the percentage calculated relative to the open area at 0 hour (100%). Error bars, SD of three replicates. F, Western blot analysis of the indicatedproteins in the EBC1-P and EBC1-R cells. In the case of EBC1-P, extracts with (þ) and without (�) treatment with the PHA665752 inhibitor (PHA, 100 nmol/L)are shown. The panels above indicate the levels of different proteins related to cell adhesion and morphology. The panels below show the phosphorylationlevels of proteins involved in signal transduction pathways. ACTIN, total protein loading controls.






To examine themolecular characteristics of the resistant cells ingreater detail we performed RNA sequencing (from herein RNA-seq) of the EBC1-P and of the six populations of EBC1-R cells. Wefound marked changes in gene expression. Some transcriptsshowed greater than 100-fold changes in most of the EBC1-Rcells, such as those ofABI3BP, CCL2, andNR3C2 (SupplementaryTable S2A). Consistent with the changes in cell morphology andin cell growth, the EBC1-R cells revealed an upregulation of genesassociated with cell adhesion, growth, and organization function-alities, whereas the downregulated genes were enriched in cellepithelial differentiation and in glucose metabolism functions(Fig. 2A; Supplementary Table S2A). As shown in the MDS plot,the gene expression profiles of the EBC1-PR2 and -C1 were verysimilar to each other and closely related to the EBC1-V8, whereas

the -PR1, -PR3, and -PR4 cells were closely related to each other(Supplementary Fig. S2). The EBC1-PR4 cells exhibited the mostdifferent profile and the closest similarity to the parental cells.

Upregulation of tyrosine kinase-receptor ligands andde novo sensitivity to the EGFR inhibitor, erlotinib,in multiple EBC1-R cells

There was strong upregulation (by 50-fold) of the transcripts,GAS6 and PROS1 (Supplementary Table S2A), which encode forligands of the RTKs named AXL, TYRO3, and MER, all of themmembers of the TAM receptor subfamily (24, 29). The expressionlevels of AXL were also slightly higher in the EBC1-R cells. Theseobservations indicate activation of signaling through the TAM-family of receptors. We extended our search to genes encoding

Figure 2.

Molecular characterization of EBC1-R cells. A, Enriched gene ontology (GO) classifications (P < 0.05 for all categories shown) among genes upregulated anddownregulated in the gene expression profile of EBC1-R cells relative to EBC1-P cells (from Supplementary Table S2A). B, mRNA levels of indicated genes,relative to ACTB, in the EBC1-P and various EBC1-R cells. C, Colony formation assay for the EBC1-P and for the various EBC1-R cells. Bottom, quantification of thenumber of colonies (cells treated with erlotinib relative to untreated cells). D, Western blots of the indicated total and phosphorylated proteins in EBC1-P andEBC1-R cells. EBC1-P, extracts with (þ) and without (�) treatment with the PHA665752 inhibitor are shown. ACTIN, total protein loading controls. E and F,Western blots indicating phosphorylation levels of EGFR, AKT, and S6 are shown for the indicated treatments and cells. PHA, PHA665752 (100 nmol/L);ERLO, erlotinib (100 nmol/L); CRIZO, crizotinib (100 nmol/L). Error bars, SD of three replicates. Two-tailed unpaired Student t test for EBC1-P versus eachEBC1-R cell type. � , P < 0.05; �� , P < 0.005; �� , P < 0.001; �� , P < 0.0001.






other RTKs or growth factors. Although we found a moderateincrease in the levels of FGFR1, ERBB4, and PDGFC, the signif-icance of these increases in levels is probably limited given themagnitude of these changes. It was of particular note that theEBC1-PR4 cells experienced a 100-fold increase in the level ofexpression of neuregulin (NRG1). We validated all these findingsby quantitative RT-PCR (Fig. 2B).

Taking previous reports (18) and our current observations intoconsideration, we explored the possible changes in sensitivity tothe FGFR1 inhibitor, PD173074, to the EGFR inhibitor, erlotinib,and to the AXL inhibitor, R428. We measured the effects on cellgrowth by assessing the IC50 of these compounds. None of thecells showed significant changes in sensitivity to the PD173074compound, but there was a decrease in the IC50 for erlotinib(about 10- to -20-fold) in many of the EBC1-R cells. The PR3 andPR4 cells were found to be the less sensitive (Supplementary Fig.S3A). The development of different degrees of secondary sensi-tivity to erlotinib, as a consequence to the AR to the MET-TKIs inthe EBC1 cells, was previously described (18). Furthermore, noneof the cells tested showed significant changes in the sensitivity toR428 (Supplementary Fig. S3A). The de novo acquisition of sen-sitivity to erlotinib, found in most of the EBC1-R cells, wasconfirmed in a cell colony formation assay (Fig. 2C). Interestingly,the acquisition of sensitivity to erlotinib was not accompanied bya rise in phosphorylation at EGFR (pEGFR), at least at Tyr1068and at Tyr1173 (Fig. 2D). Rather, the levels of pEGFR at theseresidues were higher in the EBC1-P and were partially reduced byPHA665752or crizotinib treatment, but not by erlotinib (Fig. 2E).Considered together, these observations suggest that a hyperactiveMET directly or indirectly drives the phosphorylation of EGFR atthese residues, and that this does not lead to erlotinib sensitivity.The treatment with R428 neither reduced the levels of pEGFR norinactivated the AKT/mTOR downstream pathway (Supplementa-ry Fig. S3B). Furthermore, it was intriguing to observe that thesuppression of cell growth triggered by erlonitib in the EBC1-Rcells did not involve inhibition of either the AKT or mTORpathways (Fig. 2F). This was also previously reported (18).

Characterization of genetic events of EBC1-R cells revealsselection of preexistent subclones in untreated parental cells

On the basis of the moderate changes observed in gene expres-sion we concluded that GA of RTKs could not explain the resis-tance phenotypes observed in our cells. Thus, we decided toperformWES.We selectedEBC1-PR2andEBC1-PR4 cells, becausethesewere the twoEBC1-R cells that differed themost in their geneexpression profiles and their sensitivity to erlotinib. The exomecoverage report is presented in Supplementary Table S2B. We

searched for variants that occurred at >30% allele frequency ineach of the EBC1-R cells but not in the EBC1-P cells. Using a set ofoptimized filtering criteria (see Materials and Methods) we iden-tified more than 250 novel single nucleotide variants (SNV) thatwere present in EBC1-PR2 or EBC1-PR4 cells but not in EBC1-Pcells. From these, we further selected genes with inactivatingmutations or those with nonsynonymous mutations that werealso present at the mRNA level Table 1. Only one gene wasmutated in both EBC1-PR2 and EBC1-PR4 cells, but this was anintronic mutation. No changes in amino acid coding sequenceswere shared by the two resistant cells, at least at a frequency higherthat 30% (Supplementary Table S2C).

There has beendebate about the originof the genetic alterationsarising in cells that have AR to a given TKI. Previous papers havereported the presence of these alterations in untreated specimens,albeit at low frequency, supporting the view that there is anexpansion of preexisting clones rather than de novo genetic muta-tions (15, 21). Taking this into account, wemanually searched forthese mutations in the EBC1-P and found that some of thechanges were already present in the parental cells (Table 1). Wealso searched for them in the other EBC1-R cells by examiningRNA-seq data, and found that the variants were also present inmost of them, although at different frequencies (Fig. 3A). Forexample, the missense mutations of KIRREL and HDAC11 arepresent in about 50% of the -PR1, -PR2, -C1, and -V8 cells,whereas their abundance is less than 10% in the -PR3 and -PR4cells. Together, the existence of identical mutations in differentEBC1-R cells indicates that these have emerged as an expansion ofsubclonal populations from the EBC1-P cells.

Genetic inactivation of the NF2 gene in one of the erlotinib-resistant EBC1-R cells

In addition to SNVs, we used the WES and RNA-seq data tosearch for structural variations, intragenic homozygous deletions(HD), and GA using specific analytical pipelines (see Materialsand Methods). No regions were found with high levels of GA,whereas several fusions of unknown relevance were identified(Supplementary Table S2D). Interestingly, in the EBC1-PR4 cellswe detected an HD that affected between 5 and 16 exons of thetumor suppressor gene NF2. This alteration corresponded to aninversion that predicted a truncated protein (Fig. 3B and C). Asexpected, the cells carrying the NF2 inversion showed no NF2protein (also called Merlin; Fig. 3D). By contrast, the levels of theNF2/Merlin protein were higher in the EBC1-PR1, PR2, and PR3cells than in the EBC1-P cells (Fig. 3D).

Next, we attempted to determine whether the inactivationof NF2 was responsible for the AR of the EBC1-PR4 cells to the

Table 1. List of validated SNVs from WES data, and frequency of reads in EBC1-PR2, EBC1-PR4, and EBC1-P cells

Gene name Official full name EffectCodonchange

Amino acidchange

Reads-PR2

Reads-PR4

ReadsEBC1-P

HDAC11 Histone deacetylase 11 Modify Ggg/Agg p.G152R 14/30 0/24 0/47HIATL1 Hippocampus abundant transcript-like 1 Moderate caG/caT p.Q168H 7/21 0/105 0/52KIRREL Kin of IRRE-like Moderate Gca/Tca p.A398S 9/26 0/59 0/51MAPK1IP1L Mitogen-activated kinase 1 interacting protein 1-l Modifier cCt/cTt p.P39L 15/60 0/55 0/64PLXND1 Plexin D1 Moderate atG/atA p.M845I 29/86 0/65 0/115LMLN Leishmanolysin-like peptidase High Cga/Tga p.R322X 0/40 58/239 0/72PGF Placental growth factor Moderate gTg/gGg p.V59G 3/14 11/34 0/35TOMM34 Translocase of outer mitochondrial membrane 34 Moderate aaA/aaC p.K72N 0/113 13/66 1/34TRPC4AP Transient receptor potential cation channel subfamily C member

4-associated proteinModerate Caa/Gaa p.Q535E 0/81 13/71 1/116






MET-TKI. First, we tested whether downregulation of NF2 inthe EBC1-P cells mimicked the phenotypic and molecularcharacteristics found in EBC1-PR4 cells. To this end, wedepleted the expression of NF2 in the EBC1-P cells, usingvarious shRNAs. Compared with scramble RNA, cells infectedwith different shNF2 underwent morphological changes,which closely resembled those of the EBC1-R cells, that is,polygonal-shaped cells that grow in patches (Fig. 4A). How-ever, downregulation of NF2 in the EBC1-P cells did not triggersome of the molecular changes observed in the EBC1-PR4 cells,such as the shift in the expression of p120ctn isoforms or thereduced levels of vimentin (Fig. 4B). In contrast, depletion ofNF2 did induce an increase in the levels of ABI3BP and NRG1(Fig. 4C). Finally, the drop in NF2 levels did not affect thegrowth inhibition capability of the PHA665752 compound inthe EBC1-P cells (Fig. 4D).

Notwithstanding these observations, the involvement ofNF2inactivation in the AR to MET-TKI in EBC1-P cells cannot becompletely ruled out. Low levels of the Merlin protein were stilldetectable in the EBC1-P cells after infection with shNF2 (Fig.4B). These levels could be high enough for Merlin to exert itsfunction and so prevent refractoriness to MET inhibition in theEBC1-P cells.

Changes in global DNA methylation discriminate variousEBC1-R cells

To determine whether AR involves modifications in DNAmethylation we performed genome-wide DNA methylation pro-filing (30). We selected the 5,000 CpGs with the most variablemethylation levels plotted in an unsupervised manner (Fig. 5Aand Supplementary Table S2E). The analysis segregated the cellsinto two clusters that were consistent with the similarities in the

Figure 3.

WES analysis identifies inactivation of NF2 as one mechanism for AR to MET-TKI. A, Radial chart (left) and table (right) showing the percentage of mutatedreads for each SNV relative to the total number of reads at the mRNA level in the indicated cells. SNVs were identified by WES (see Table 1). B, Top,schematic representation of the structure of the NF2 gene and the position of the different exons, highlighting the region affected by the inversion and the deletedexons; bottom, agarose gene with the PCR products of the indicated exons and EBC1 cells, depicting some of the deletions (red). Neg., negative control. C,Chromatogram depicting the inversion found in the EBC1-PR4 at the mRNA level. D, Western blot analysis showing the levels of NF2/Merlin protein in theindicated cells. The LOU-NH91 carry a mutation at NF2 (p.P257fs�39), predicting no protein expression and was used as negative control. The H322, H1439, andMCF7- cancer cells were positive controls. The band observed in the LOU-NH91 and the lower bands in the EBC1-related cells are nonspecific. NUCLEOLIN,total protein loading control.






genetic and gene expression profiles (Figs. 2B and 3A). One ofthe clusters included the resistant cells, -PR1, -PR2, -C1, and -V8,and the other included the parental cells (EBC1-P) and the -PR3and -PR4.

We next determined whether there was an association betweenchanges in DNA methylation and in gene expression. We foundno major differences in promoter hypermethylation among theupregulated or downregulated genes common to all the resistantcells (Supplementary Table S2A), indicating that the changesin gene expression profiles did not arise as a consequence oflarge differences in global DNA methylation (Fig. 5B). We didobserve a significant increase in global CpG methylation,specifically the bodies of genes that were upregulated in theEBC1-R cells (Fig. 5B).

DiscussionIn lung cancers, de novomutations acquired at EGFR or ALK are

not always associated with the AR to their respective TKIs, andalterations at other RTKs or signal transductionmolecules can alsoaccount for theAR (15, 31, 32).Genetic alterations that have so farbeen reported to confer AR on MET-TKIs include not only METpoint mutations and MET GA, but also a constitutively activeSND1-BRAF fusion protein and amplification and overexpressionof wild-type KRAS (17, 19, 20, 33). None of these was observed inthe EBC1-R cells that we generated in this study to model AR toMET-TKI inhibitors. Instead, as previously reported (18), wefound that the PHA665752 compound readily inhibited METphosphorylation in all the EBC1-R cells, indicating that the

activation of related RTKs or effectors that act as a bypass tracksmediated secondary refractoriness. Furthermore, all the EBC1-Rcells exhibited very similar shifts in cell morphology, from mes-enchymal to epithelioid-like features. All these morphologicalmodifications are consistent with the marked molecular changesobserved in these cells, that is, enriched cell adhesion, decreasedglucose metabolism, and cell proliferation-related transcripts, aswell as a shift in the mobility of p120ctn protein, shown byWestern blot analysis, due to variations in the protein isoformabundances or in posttranslational modifications. The p120ctnprotein plays a crucial role in the regulation of cell–cell adhesionat adherens junctions and in the epithelial-to-mesenchymal tran-sition (34). In previous works, morphological modificationssuch as shifts from NSCLC to either SCLC or epithelial-to-mes-enchymal transformations have been reported after AR to theEGFR-TKIs (32, 35).

Another characteristic common to all the EBC1-R cells was adramatic upregulation of theGAS6 transcript, which codes for theligand of RTK, AXL, which itself was also slightly more abundantin all the resistant cells. Increased levels of GAS6 and AXL havebeen reported in studies of AR to various TKIs, such as erlotiniband PIK3 inhibitors, although its significance is still unclearbecause no genetic alterations at AXL or GAS6 have been found(13, 36–38). Interestingly, AXL belongs to the TAM receptorsubfamily, together with TYRO3 and MER (24, 29), and GAS6has the ability to activate all these receptors. It is of note that all theEBC1-R cells also showed strong upregulation of PROS1, whichcodes for another ligand of the receptors TYRO3 and MER. Thisindicates that signaling through the TAM receptor family is

Figure 4.

Effects of downregulation of NF2 inEBC-P cells with various independentshRNAs targeting NF2 (sh#1, sh#2,sh#3, sh#4, sh#5). A, Phase contrastimages showing the changes in cellmorphology between EBC1-P cellsinfected with scramble RNA (scr) orwith independent shRNAs targetingNF2. Scale bar, 100 mm. B, Westernblot analysis showing the levels ofNF2/Merlin and other indicatedproteins related to cell adhesion andmorphology in EBC1-P and EBC1-Pcells after downregulating NF2expression with various independentshRNAs targeting NF2 (sh#1, sh#2,sh#3, sh#4, and sh#5). Scr, scramblecontrol. NUCLEOLIN OR ACTIN, totalprotein loading controls. C, mRNAlevels of ABI3BP and NRG1, relative toACTB, in EBC1-P and EBC1-P cells withscramble mRNA, and in EBC1-P cellsafter downregulating NF2 expressionwith four shRNAs (sh#1-4). Error bars,SD of three replicates. Two-tailedunpaired Student t tests for EBC1-Pversus each EBC1-R cells. � , P < 0.05;�� , P < 0.005; �� , P < 0.001. D,Representative examples of thecolony formation assay for EBC1-P andEBC1-P cells after downregulatingNF2expression (sh#1 and sh#2) inuntreated cells (�) and in cells treatedwith MET-TKI (þ).






strongly activated in these cells. In spite of this, the inactivation ofthe AXL receptor did not have a significant effect on cell growth,suggesting that AXL activation does not drive theAR toMET-TKI inthese cells.

Although changes in cellmorphology andupregulationofAXL/GAS6/PROS1 were common to all the EBC1-R cells, others weremore specific. We found at least two clusters of genetic variantsand gene methylation profiles among the EBC1-R cells, one thatcontained -PR1, -PR2, -C1, and -V8 cells, and another featuring-PR3 and -PR4 cells. This highlights the expansion of minorsubclonal populations that are already present in the parentalcells, following a population bottleneck as a result of the massivereduction in population size due to the anti-MET treatment.Interestingly, the former group was strongly associated withmarked de novo sensitivity to erlotinib. Although could befurther validated in in vivo models, our observations are con-sistent with previous reports (18), and evidence of the existenceof multiple simultaneous mechanisms of AR within the sametumor specimen. Collectively, the findings highlight the impor-tance of determining the type and degree of tumor heteroge-neity within a primary tumor to predict and prevent recurrencewith cancer treatments.

De novo sensitivity to erlotinib following AR to MET-TKIs hadpreviously been demonstrated but, although the mechanisminvolved the upregulation of the EGFR ligand amphiregulin, theunderlying genetic event is unknown (18). Previous observationshave revealed de novo sensitivity to MET-TKI, due to amplificationof MET, following AR to EGFR TKI (11). Collectively, theseobservations demonstrate a functional connection between METand EGFR that is responsible for the reciprocal activation of thereceptors during AR. As further evidence of this relationship, weobserved that treating EBC1-P cells with MET-TKIs, but not witherlotinib, readily reduced the levels of phosphorylation of

Tyr1068 and Tyr 1173 of EGFR. This suggests that MET activityinduces EGFR phosphorylation either directly or through down-stream targets. In spite of thoroughly examining the genetic andgene expression background of some EBC1-R cells, we have notidentified the alteration responsible for this feature. Because ofthat, we still cannot provide with candidate markers that could beuseful for patient's selection. We foundmutations that weremoreprevalent in the EBC1-R cells with sensitivity to erlotinib, such asKIRREL (also called NEPH1), which is involved in cell–cellinteractions that modulate ERK signaling through phosphoryla-tion-dependent interaction with GRB2 (39).

After exhaustive genetic screening of the EBC1-R cells in searchof the event underlying AR to the MET-TKI, we identified, only inthe EBC1-PR4 cells, a rearrangement of theNF2 gene, which leadsto an absence of the encoded protein, Merlin. Merlin is a scaffoldprotein that mediates RTK signaling events associated with cellproliferation and survival. It also allows the connection betweenRTKs, actin, and intracellular effectors (40). ReducedNF2 levels inEBC1-P cells triggered someof the features of the resistant cells butdid not lead to resistance to theMET inhibitor. In spite of this, theinvolvement of NF2 inactivation in AR to MET-TKI cannot beruled out. TheMerlin protein could still be detected in the EBC1-Pcells, although at levels possibly low enough to prevent refracto-riness toMET inhibition in the EBC1-P cells. The genetic alterationat NF2 detected in the EBC1-PR4 cells could also be the cause ofthe refractoriness to erlotinib, since inactivation ofNF2 is knownto be associated with AR to the EGFR inhibitors afatinib andcetuximab in lung adenocarcinoma patients (41). In this regard,the EBC1-PR4 cells showed very high levels of NRG1. This codesfor a ligand of various HER-family of receptors, including HER4,which are known to be highly active in human schwannomas andin NF2-deficient cell lines. In addition, Merlin is rapidly phos-phorylated following NRG1 binding toHER-receptors, indicating

Figure 5.

Analysis of the changes in genomewide methylation, using an 850,000CpG methylation microarray. A,Unsupervised hierarchical clustering inthe indicated parental EBC1 cells(EBC1-P) and EBC1-R cells for the5,000 most variable CpGs (fromSupplementary Table S2E). Theheatmap colors illustrate beta valuesrepresenting the degree ofmethylation, from low (green) to high(red), as shownby the scale at the top-right of the Figure. B, Box-plotshowing the delta beta values of theCpGs at the promoters (only CpGislands) or bodies of the upregulated(Up) and downregulated (Down)genes, from Supplementary TableS2A. Two-tailed unpaired Student ttests of the b values of EBC1-Pversus each EBC1-R cell. � , P < 0.05;��, P < 0.005; �� , P < 0.001;�� , P < 0.0001; NS, not significant.






that Merlin mediates signal transduction in response to NRG1–HER4 binding (42).

In conclusion, our results provide evidence that AR to METinhibitors in EBC1 cells involves several simultaneously actingmechanisms. These include an acquired sensitivity to erlotinib insome, but not all, resistant cells. Our findings draw attention tothe importance of considering combinatorial therapeutics whendesigning strategies for second-line treatments in TKI-treated lungcancer patients.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: P. Gimenez-Xavier, M. Sanchez-CespedesDevelopment of methodology: P. Gimenez-Xavier, E. Pros, E. Bonastre, A. Aza,D. Salinas-ChaparroAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): E. Bonastre, S. Moran, M. EstellerAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): P. Gimenez-Xavier, E. Pros, A. Aza, O. Gra~na,G. Gomez-Lopez, S. Derdak,M. Dabad, A. Esteve-Codina, J.R. HernandezMora,D. Pisano, M. Sanchez-CespedesWriting, review, and/or revisionof themanuscript:P.Gimenez-Xavier, E. Pros,E. Bonastre, S. Moran, A. Aza, S. Derdak, M. Esteller, D. Pisano, M. Sanchez-Cespedes

Administrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): P. Gimenez-Xavier, E. Pros, S. Derdak,M. Sanchez-CespedesStudy supervision: M. Sanchez-Cespedes

AcknowledgmentsThe authors acknowledge the technical assistance of Patricia Cabral of the

Genes and Cancer Group at IDIBELL.

Grant SupportThis work was supported by Spanish grants SAF2014-54571-R, RTICC

(RD12/0036/0045 to M. Sanchez-Cespedes); from the ISCIII under the Inte-grated Project of Excellence no. PIE13/00022 (ONCOPROFILE; to M. Estellerand M. Sanchez-Cespedes), cofunded by FEDER funds/European RegionalDevelopment Fund (ERDF)-A Way to Build Europe; from the Ministerio deEconomía y Competitividad (PTA201409515 to M. Dabad); and from theAGAUR Agency to Grups de recerca consolidats (2014SGR641; to M. Sanchez-Cespedes). The CNAG-CRG laboratory is a member of the Spanish NationalBioinformatics Institute (INB), PRB2-ISCIII, and is supported by grant PT13/0001, of the PE IþDþi 2013-2016, funded by ISCIII and FEDER (toA. Esteve-Codina). S. Derdak was supported by the Torres Quevedo subpro-gramme (MICINN) under grant agreement PTQ-12-05391.

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received January 31, 2017; revised January 26, 2017; accepted April 3, 2017;published OnlineFirst April 10, 2017.

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2017;16:1366-1376. Published OnlineFirst April 10, 2017.Mol Cancer Ther Pol Gimenez-Xavier, Eva Pros, Ester Bonastre, et al. for Acquired Resistance to MET Inhibitors in Lung Cancer CellsGenomic and Molecular Screenings Identify Different Mechanisms

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