Phosphoproteomic analysis identifies activated MET-axis PI3K/AKT and MAPK/ERK in lapatinib-resistant cancer cell line

Abstract

Lapatinib, a dual inhibitor of epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2) tyrosine kinases, has shown promising results as a growth inhibitor of HER2-positive cancer cells in vitro. However, similar to other EGFR-targeting drugs, acquired resistance to lapatinib by HER2-positive cancer cells remains a major clinical challenge. To elucidate resistance mechanisms to EGFR/HER2-targeting agents, we performed a systematic quantitative comparison of the phosphoproteome of lapatinib-resistant (LR) human gastric cancer cells (SNU216-LR) versus parental cells (SNU216) using a titanium dioxide (TiO ₂ ) phosphopeptide enrichment method and analysis with a Q-Exactive hybrid quadrupole-Orbitrap mass spectrometer. Biological network analysis of differentially expressed phosphoproteins revealed apparent constitutive activation of the MET-axis phosphatidylinositide 3-kinase (PI3K)/α-serine/threonine-protein kinase (AKT) and mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling pathways in SNU216-LR. Inhibition of the PI3K/AKT and MAPK/ERK signaling pathways in SNU216-LR also leads to cell cycle arrest, confirming the biological network analysis. Lapatinib sensitivity was restored when cells were treated with several molecular targeting agents in combination with lapatinib. Thus, by integrating phosphoproteomic data, protein networks and effects of signaling pathway modulation on cell proliferation, we found that SNU216-LR maintains constitutive activation of the PI3K/AKT and MAPK/ERK pathways in a MET-dependent manner. These findings suggest that pathway activation is a key compensatory intracellular phospho-signaling event that may govern gastric cancer cell resistance to drug treatment.

Experimental & Molecular Medicine (2013) 45, e64; doi:10.1038/emm.2013.115 & 2013 KSBMB. All rights reserved 2092-6413/13

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ORIGINAL ARTICLE

Phosphoproteomic analysis identies activated MET-axis PI3K/AKT and MAPK/ERK in lapatinib-resistant cancer cell line

Yong Yook Lee1,2,5, Hwang-Phill Kim3,5, Min Jueng Kang1,5, Byoung-Kyu Cho1, Sae-Won Han4, Tae-You Kim3,4 and Eugene C Yi1,2

Lapatinib, a dual inhibitor of epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2) tyrosine kinases, has shown promising results as a growth inhibitor of HER2-positive cancer cells in vitro. However, similar to other EGFR-targeting drugs, acquired resistance to lapatinib by HER2-positive cancer cells remains a major clinical challenge. To elucidate resistance mechanisms to EGFR/HER2-targeting agents, we performed a systematic quantitative comparison of the phosphoproteome of lapatinib-resistant (LR) human gastric cancer cells (SNU216-LR) versus parental cells (SNU216) using a titanium dioxide (TiO2) phosphopeptide enrichment method and analysis with a Q-Exactive hybrid quadrupole-Orbitrap mass spectrometer. Biological network analysis of differentially expressed phosphoproteins revealed apparent constitutive activationof the MET-axis phosphatidylinositide 3-kinase (PI3K)/a-serine/threonine-protein kinase (AKT) and mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) signaling pathways in SNU216-LR. Inhibition of the PI3K/AKTand MAPK/ERK signaling pathways in SNU216-LR also leads to cell cycle arrest, conrming the biological network analysis. Lapatinib sensitivity was restored when cells were treated with several molecular targeting agents in combination with lapatinib. Thus, by integrating phosphoproteomic data, protein networks and effects of signaling pathway modulation on cell proliferation, we found that SNU216-LR maintains constitutive activation of the PI3K/AKT and MAPK/ERK pathways in a MET-dependent manner. These ndings suggest that pathway activation is a key compensatory intracellular phospho-signaling event that may govern gastric cancer cell resistance to drug treatment.

Experimental & Molecular Medicine (2013) 45, e64; doi:http://dx.doi.org/10.1038/emm.2013.115

Web End =10.1038/emm.2013.115; published online 22 November 2013

Keywords: drug resistance; HER2-positive gastric cancer; lapatinib; phosphoproteins; Q-Exactive; therapeutic targets

INTRODUCTIONHuman epidermal growth factor receptor 2 (HER2) is one of the receptor tyrosine kinases activated through dimerization with members of the epidermal growth factor receptor (EGFR) family.1 Overexpression of HER2 leads to tumor progression via intracellular signal transduction cascades2 and is observed in B20 30% of high-risk breast cancer cases,3,4 as well as in

6 35% of invasive gastric cancers.5 Lapatinib inhibits the

proliferation of cancer cells overexpressing EGFR and/or HER2

both in vitro and in vivo, and it was approved by the United States Food and Drug Administration as a treatment for advanced HER2-positive breast cancer in 2007.68 The

antitumor activity of lapatinib has also been examined in gastric cancer cells.9,10 A phase III clinical trial comparing the

effect of chemotherapy alone versus in combination with lapatinib in HER2-positive gastric cancer patients is currently on-going.11 However, acquired resistance to lapatinib has been and remains a limitation to its therapeutic use in the

1WCU Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and College of Medicine or College of Pharmacy, Seoul National University, Seoul, Republic of Korea; 2Wide River Institute of Immunology, Seoul National University, Seoul, Republic of Korea; 3Cancer Research Institute, Seoul National University, Seoul, Republic of Korea and 4Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

Correspondence: Professor EC Yi, WCU Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, 28 Yeongeon-Dong, Jongno-Gu, Seoul 110-799, Republic of Korea.

E-mail: mailto:[email protected]

Web End [email protected] or Professor T-Y Kim, Department of Internal Medicine, Seoul National University College of Medicine, 28 Yeongeon-Dong, Jongno-Gu, Seoul 110-744, Republic of Korea.

E-mail: mailto:[email protected]

Web End [email protected]

5YYL, H-PK and MJK contributed equally to this work.

Received 5 May 2013; revised 25 July 2013; accepted 6 August 2013

Phosphoproteome in lapatinib-resistant cancer YY Lee et al

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clinic because of a poor understanding of the underlying mechanisms.

One possible mechanism driving therapeutic resistance is the compensatory activation of an alternate receptor tyrosine kinase that would restore the downstream signaling pathways.12,13 Many functional studies of cancers coexpressing hepatocyte growth factor receptor (MET) and EGFR have suggested that compensatory activation of MET in the presence of EGFR blockade may be responsible for EGFR tyrosine kinase inhibitor (TKI)-acquired resistance. For example, Engelman et al.14 detected MET amplication in patients with non-small-cell lung cancer who developed clinical resistance to the EGFR inhibitors getinib or erlotinib.14 Yano et al.15 also found that hepatocyte growth factor-mediated MET activation is a novel mechanism of getinib resistance in lung adenocarcinomas containing EGFR-activating mutations. These studies imply that the functional cross-talk between MET and the EGFR family of receptor tyrosine kinases plays an important role in the adaptive cellular response that may contribute to drug resistance. More recently, the activation of MET has been shown to confer resistance to lapatinib inhibition in HER2-positive gastric cancer cells.16

To identify the affected global cellular processes compensating for the selective pressure of lapatinib on EGFR/HER2, we performed a large-scale quantitative phosphoproteome analysis of lapatinib-resistant (LR) human gastric cancer cells generated from HER2-amplied gastric cancer cells during prolonged lapatinib treatment. By integrating differentially expressed phosphoproteins into the biological network analysis tools, we found that constitutive activation of the phosphatidylinositide 3-kinase (PI3K)/a-serine/threonine-protein kinase (AKT) and mitogen-activated protein kinase (MAPK)/extra-cellular signal-regulated kinase (ERK) signaling pathways induced by the MET axis may be a critical pathway conferring acquired lapatinib resistance. The phosphoproteomic results were conrmed by cell growth inhibition studies with a single or several molecular targeting agents in combination with lapatinib. These ndings provide novel insights into adaptive changes in phospho-signaling networks that occur during the development of lapatinib resistance in human HER2-positive gastric cancer cells. Our data also demonstrate that network-based global phosphoproteomic analysis is a reliable approach for predicting cellular signaling events, which in turn can lead to the identication of alternative targeting strategies for LR gastric cancer.

MATERIALS AND METHODS Cell lines and reagents

Human gastric carcinoma SNU216 cells were obtained from the Seoul National University Cell Bank (Seoul, Korea). Cells were cultured in RPMI-1640 medium containing 10% (v/v) fetal bovine serum (Gibco, Carlsbad, CA, USA) at 37 1C under 5% CO2. Lapatinib was a gift from GlaxoSmithKline (Research Triangle Park, NC, USA). NVP

BEZ235, selumetinib, saracatinib and crizotinib were purchased from Selleck Chemicals (Houston, TX, USA). Stock solutions were

prepared in dimethyl sulfoxide and stored at 20 1C. Ammonium

bicarbonate, dithiothreitol (DTT), formic acid (FA) and triuoroacetic acid (TFA) were purchased from Sigma-Aldrich (St Louis, MO, USA). The HPLC-grade acetonitrile (ACN) and water were from JT Baker (Phillipsburg, NJ, USA). Lyophilized trypsins were obtained from Promega (Madison, WI, USA).

Generation of LR clones from SNU216 cells in vitro SNU216 cells were exposed to increasing concentrations of lapatinib over a period of 8 months, reaching a nal concentration of 10 mM at

the end of this period. Single-cell cloning was done by serial dilution or isolation with cloning cylinders, and isolated resistant cells were expanded in culture medium containing 1 mM lapatinib.

Cell growth inhibition assayThe viability of cells was assessed using MTT assays (Sigma-Aldrich). A total of 3 103 cells were seeded in 96-well plates, incubated at

37 1C for 24 h for recovery and treated for 72 h with specic drugs as indicated. After treatment, MTT solution was added to each well followed by incubation for 4 h at 37 1C. The medium was removed, dimethyl sulfoxide was added and the samples were mixed thoroughly for 30 min at room temperature. Cell viability was determined by measuring absorbance at 540 nm using a VersaMax microplate reader (Molecular Devices, Sunnyvale, CA, USA).

Immunoblot analysisAntibodies against p-EGFR (pY1068), p-HER2 (pY1221/1222), p-MET (pY1234/1235), p-AKT (pS473), p-MAPK (pY202/pY204), p-SRC (pY416), p-RAF (pS338), EGFR, HER2, MET, AKT, MAPK, SRC (proto-oncogene tyrosine-protein kinase Src) and RAF were purchased from Cell Signaling Technology (Beverley, MA, USA). Antibodies directed against b-catenin, cyclin D and p27 were obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Subconuent cells (70 80%) were used for protein analyses. For the analysis of

signaling after drug treatments, cells were treated with different concentrations of the indicated drugs for 48 h. Cell lysates were prepared with RIPA buffer, consisting of 50 mM Tris-HCl (pH 7.5), 1% (v/v) NP-40, 0.1% (w/v) sodium deoxycholate, 150 mM NaCl, 50 mM NaF, 1 mM sodium pyrophosphate, 1 mM sodium vanadate, 1 mM nitrophenylphosphate, 1 mM benzamidine, 0.1 mM PMSF,0.1 mM aprotinin, 0.1 mM leupeptin and 0.1 mM pepstatin A, on ice for 10 min, after which the lysates were centrifuged at 14 000 g for

20 min. Samples containing equal amounts of protein were resolved by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) followed by transfer of the proteins onto nitrocellulose membranes. The membranes were blocked for 1 h at room temperature with 5% (w/v) skim milk and incubated overnight at 4 1C with primary antibody. After probing with secondary antibody for 1 h at room temperature, detection was performed using an enhanced chemiluminescence system (Amersham Pharmacia Biotech, Piscataway, NJ, USA).

Cell cycle analysisCells were washed twice in phosphate-buffered saline, xed in 70% (v/v) ethanol and stored at 20 1C until analysis was performed.

Before analysis, thawed cell suspensions were washed with phosphate-buffered saline, digested with RNase A (50 mg ml 1) for 15 min at 37 1C and stained with propidium iodide (50 mg ml 1). The DNA content (10 000 cells per experimental group) was determined using a

FACSCalibur ow cytometer (Becton Dickinson Biosciences, San Jose,

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CA, USA) equipped with a ModFit LT program (Verity Software House, Topsham, ME, USA), as previously described.10

One-dimensional SDS-PAGE fractionation and in-gel digestionCells were lysed by sonication in lysis buffer, consisting of 1% (w/v) sodium deoxycholate, 6 M urea, 50 mM Tris-HCl (pH 7.5), 150 mM

NaCl, 5 mM EDTA, 50 mM NaF, 1 mM sodium orthovanadate, 0.5 mM

PMSF and phosphatase and protease inhibitor (Roche, Mannheim, Germany). Protein concentration was determined using the Micro BCA Protein Assay Kit (Thermo Scientic, Rockford, IL, USA). Protein samples (3 mg each) were dissolved in NuPAGE LDS sample buffer (Invitrogen, Carlsbad, CA, USA) containing 50 mM DTT and heated at 70 1C for 10 min. The cell lysates were separated on a 4 12% Bis-Tris NuPAGE gel (Invitrogen) and stained with Coo

massie Brilliant Blue (Sigma-Aldrich). The entire gel lane was cut into six pieces and subjected to in-gel tryptic digestion.17 The excised gels were destained with 50% (v/v) ACN in 25 mM NH4HCO3 and in 100 mM NH4HCO3 for 15 min. After destaining, the gels were dried and reduced with 20 mM DTT at 60 1C for 1 h. They were alkylated with 55 mM iodoacetamide at room temperature for 45 min in the dark. The gel pieces were dehydrated for 15 min in 50% ACN in 25 mM NH4HCO3, and the proteins in the gels were digested overnight at 37 1C with 13 ng ml 1 sequencing-grade modied trypsin (Promega) in a volume of 50 mM NH4HCO3 sufcient to cover the gel pieces. Peptides were extracted from the gel pieces with 50% (v/v) ACN in 5% (v/v) FA and dried under a Centrivap concentrator (Labconco, Kansas City, MO, USA).

Phosphopeptide enrichment by TiO2 afnity column chromatographyPhosphopeptides were enriched using the TitanspherePhospho-TiO Kit (GL Sciences, Tokyo, Japan) following the manufacturers protocol. Briey, the titanium dioxide (TiO2) afnity column was conditioned with 20 ml of Buffer A (0.4% w/v TFA in 80% v/v ACN) by centrifuging twice at 3000 g for 2 min and equilibrated with Buffer

B (25% w/v lactic acid and 0.3% w/v TFA in 60% v/v ACN) by again centrifuging twice as before. The extracted peptides, which had been resuspended in 150 ml Buffer B, were loaded onto the column. For sample adsorption, the column was rst centrifuged at 1000 g for

10 min, and the ow-through was loaded onto the column and centrifuged again. The column was washed three times with 20 ml

Buffer B by centrifugation at 3000 g for 2 min, followed by washing

with 20 ml Buffer A by centrifugation under the same conditions. Phosphorylated peptides were eluted twice with 50 ml 5% (v/v) NH4OH and 50 ml 30% ACN by centrifugation at 1000 g for

5 min. The eluate was evaporated in a Centrivap concentrator and stored at 20 1C until liquid chromatography-tandem mass spectro

metry (LC-MS/MS) analysis.

Mass spectrometric analysisPeptides were reconstituted in 2% (v/v) ACN in 0.4% (v/v) FA and separated on an in-house packed micro-capillary Michrom Magic C18 column (75 mm inner diameter, 12 cm length) by elution with a linear gradient of 2 32% Solvent B (0.1% v/v FA in ACN) in Solvent A

(0.1% v/v FA in water) for 65 min at a ow rate of 300 nl min 1. Samples were analyzed in triplicate on a Q-Exactive (Thermo Fisher

Scientic, San Jose, CA, USA) hybrid quadrupole-Orbitrap mass spectrometry (MS), interfaced with a nano-ultra performance liquid chromatography system (Easy nLC, Thermo Fisher Scientic). The

spray voltage was set to 2.0 kV, and the temperature of the heated capillary was set to 250 1C. The Q-Exactive was operated in data-dependent mode with one survey MS scan followed by 10 MS/MS scans and a dynamic exclusion time of 60 s. The full scans were acquired in the mass analyzer at 400 1600 m/z with the resolution of

70 000, and the MS/MS scans were obtained with a resolution of 17 500 by using a normalized collision energy of 27% for high-energy collisional dissociation fragmentation. The automatic gain control target was 5e,4 the maximum injection time was 120 ms and the isolation window was set to 3 m/z.

Database search and identication of the phosphoproteome Collected raw les were converted into mzXML les through the Trans Proteomic Pipeline (version 4.5; Seattle Proteomic Center, Seattle, WA, USA). The peptides were assigned by the SEQUEST algorithm (Thermo Fisher Scientic, version 27, rev. 11) against the decoy IPI.HUMAN database (v.3.18, 120180 entries), and the false discovery rate (FDR) was estimated by Sorcerer (Sage-N Research, Milpitas, CA, USA). All searches were carried out based on trypsin specicity, allowing two missed cleavages. Carbamidomethylation of cysteine was set as xed, and oxidation of methionine, phosphorylation of serine, threonine and tyrosine were set as variable modications. The search considered a precursor ion mass tolerance of 10 p.p.m., and the fragment ion mass tolerance was set to 1.0 Da Scaffold (version 3.4.9; Proteome Software, Portland, OR) was used to compare spectral counts, validate MS/MS-based peptides and identify matching proteins according to the criteria of 99% minimum protein probability by the Protein Prophet algorithm,18 with 80% minimum peptide probability and one minimum peptide (FDR o0.5%) as specied by the Peptide Prophet algorithm.19 Proteins that contained redundant peptides and multiple isoforms, which could not be differentiated based on MS/MS spectra, were grouped into a primarily assigned protein. Scaffold PTM (version 1.1.3; Proteome Software) was used to annotate Post-Translational Modication (PTM) sites derived from MS/MS sequencing results. The Scaffold PTM assigned possible phosphorylation sites from the Scaffold validated tandem data using the Ascore algorithm developed by Beausoleil et al.20

Quantication and bioinformatic analysis of phosphoproteinsTo quantify phosphoproteins, we used spectral counts of phosphopeptides from triplicate samples of SNU216 and SNU216-LR. The data set was entered into the R program (version 2.15) with power law global error model (PLGEM, version 1.28), a statistical analysis software package (www.bioconductor.org) used to determine signal-to-noise ratio and P-value.21 Based on PLGEM, the annotation of protein cellular localization and evaluation of biological function was performed after uploading the signal-to-noise ratio and P-value to the Ingenuity Pathway Analysis (IPA; Ingenuity Systems; Redwood City, CA, USA) database content version 14197757. Hence, the phosphopeptides of the identied proteins, including those in proteins of the MET-mediated MAPK/ERK and PI3K/AKT signaling pathways, were manually quantied by the XCalibur program (Thermo Fisher Scientic). The quantication of precursor ion for the rst isotopes of each ion was performed using the area of the peptides present in the raw data set across all samples in extracted ion chromatograms.

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RESULTSIdentication of phosphoproteins in SNU216 and SNU216-LR cellsTo investigate possible mechanisms responsible for acquiring resistance to HER2-targeted therapy in gastric cancer, we established a LR cell line (SNU216-LR) by chronically exposing HER2-positive SNU216 cells (lapatinib-hypersensitive gastric cancer cells) to increasing concentrations of lapatinib in vitro for 8 months. A LR cell clone (SNU216-LR) was selected and characterized. The half-maximal inhibitory concentration value in SNU216-LR cells was 410 mM, which is 500-fold higher than that of parental cells (0.02 mM).

Next, we performed a large-scale quantitative phosphoproteome analysis to identify differentially phosphorylated proteins (DPPs) between SNU216-LR and SNU216 cells. A total of 6556 unique phosphopeptides representing 1686 phospho-proteins was identied with high condence by MS analysis of the TiO2-enriched phosphopeptides (protein: probability 499% and FDR o1.5%; peptide: probability 480% and FDR o0.5%), and 97.7% of proteins overlapped between

SNU216 and SNU216-LR cell lines (Supplementary Figure 1A and Supplementary Tables 1 and 2). We then determined the phosphorylation sites of all identied phosphopeptides using Ascore and localization probability by Scaffold PTM.20 Our

approach identied 7791 phosphorylation sites (Ascore 480%) among 11 852 unique phosphorylation sites (Supplementary Table 3). Serine was found to be the most abundantly phosphorylated residue (9745 sites, 82%), followed by threonine (1763 sites, 15%) and tyrosine (344 sites, 3%) (Supplementary Figure 1B). The reproducibility of detecting the same proteins in triplicate analysis by LC-MS/MS exceeded 91% for both cell lines (Supplementary Figures 1C and 1D).

To estimate quantitative changes in the phosphorylation of each phosphopeptide, we selected DPPs in SNU216-LR cells using the spectral counting method in Scaffold (version 3.4.9). The signal-to-noise ratio and P-values for the DPPs were obtained using PLGEM. A list of 95 signicantly regulated phosphoproteins (Po0.006) is presented in Table 1. As shown in the volcano plot, 69 proteins were upregulated (red box), and 26 proteins were downregulated (blue box) in SNU216-LR cells (Figure 1a). To understand the functions of the DPPs, we examined cellular processes represented by the 95 regulated proteins using the IPA tool and found that they belong to enzyme (14%), transcription regulator (12%) and kinase (6%) groups of proteins (Figure 1b). We also examined the cellular distribution of these proteins and found that most were associated with either the nucleus (40%) or cytoplasm (35%), with fewer associated with the membrane (9%) (Figure 1c).

We further evaluated quantitative changes in phosphorylation of proteins using label-free quantication methods (MS/ MS spectral count and extraction ion chromatography) that are generally accepted in phosphoproteomic studies.2224 More

MS/MS spectral counts of phosphorylated EGFR and HER2 peptides were identied in SNU216-LR than SNU216 cells (Supplementary Figures 2A and 2B). These data were

consistent with the peptide extracted ion chromatogram, which showed signicantly greater signal intensities of phosphorylated peptides in SNU216-LR cells (Supplementary Figures 2C and 2D). Using the same quantication approaches, we were able to measure the phosphorylation levels of key molecules (MET, RAS, C-RAF, ERK1/2, PI3K and AKT; see Supplementary Figures 2EJ). In addition, we found a new phosphorylation site in HER2 (S1073) based on the phosphopeptide reference database phosphoSitePlus (http://www.phosphosite.org

Web End =www. http://www.phosphosite.org

Web End =phosphosite.org ). This phosphorylation site was conrmed by the matched tandem mass spectra shown in Supplementary Figure 3.

Network analysis and quantication of differentially phosphorylated proteinsTo investigate the extent to which activation of signaling pathways contributes to EGFR/HER2-targted therapy, we integrated the DPPs (Po0.006) into the protein interaction network using the IPA tool to interpret the DPPs in the context of biological processes. The IPA tool generated the top three networks that are associated with cancer, cell morphology and cellular and tissue development (Supplementary Figure 4). Considering this network analysis, our upregulated phosphoproteins, including EGFR and MET, appeared to be closely related to PI3K, AKT and ERK1/2 in SNU 216-LR (Figure 2).

Our analysis of results from the IPA tool also revealed that EGFR/HER2, MET and ERK/MAPK signaling pathways were enriched (Supplementary Figure 5). Based on the results from the network and canonical signaling pathway analyses, we constructed the signaling network for EGFR/HER2 and MET with the two major downstream signaling pathways (PI3K/ AKT and MAPK/ERK) including SRC (Figure 3). As shown in Figure 3a, categorization of expression levels of specic phosphorylated sites revealed that the majority of signaling molecules were highly expressed in SNU216-LR. We further compared SNU216 and SNU216 LR, as well as three other resistant clones (SNU216-LR1, 2 and 3), using immunoblot analysis with phospho-specic antibodies. Consistent with the quantitative MS results, the phosphorylation level of selected proteins (EGFR, HER2, MET, AKT, MAPK, SRC, and RAF) was increased in SNU216-LR (Figure 3b).

Effects of targeted anticancer agents on SNU216-LR cells To verify whether constitutive activation of the PI3K/AKT and MAPK/ERK signaling pathways is the MET-mediated cascade that confers an acquired lapatinib resistance, we investigated the effects of selected kinase inhibitors, including lapatinib, NVP-BEZ235 (PI3K/mTOR inhibitor), selumetinib (MEK inhibitor), saracatinib (SRC inhibitor) and crizotinib (MET inhibitor), on the growth of SNU216-LR cells. As shown in Figure 4a, combination treatment with these drugs had a greater inhibitory effect on cell growth in SNU216-LR cells compared with single-agent treatment. The combination of lapatinib and NVP-BEZ235 produced the best growth inhibition effect. To conrm our data, we investigated cell cycle

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Table 1 Differentially expressed phosphoproteins in SNU216-LR (Po0.006)

ID Protein Symbol Location Type(s) S/N P-value

IPI00292009 Palladin PALLD Cytoplasm Other 6.09 0.00000 IPI00555610 313 kDa protein 4.97 0.00000 IPI00657687 Isoform 1 of Actin-binding protein anillin ANLN Cytoplasm Other 4.60 0.00000 IPI00008868 Microtubule-associated protein 1B MAP1B Cytoplasm Other 3.61 0.00002 IPI00008918 Isoform b of LIM domain and actin-binding protein 1 LIMA1 Cytoplasm Other 3.61 0.00004

IPI00291802 Isoform 3 of LIM domain only protein 7 LMO7 Cytoplasm Enzyme 3.42 0.00005 IPI00304589 182 kDa tankyrase 1-binding protein TNKS1BP1 Nucleus Other 3.10 0.00008 IPI00029273 Isoform 1 of Hepatocyte growth factor receptorprecursor

MET Plasma membrane

Kinase 3.01 0.00010

IPI00009286 Isoform 1 of zinc nger protein HRX MLL Nucleus Transcription regulator

2.96 0.00010

IPI00219301 Myristoylated alanine-rich C-kinase substrate MARCKS Plasma membrane

Other 2.90 0.00014

2.88 0.00018

IPI00013076 Isoform 1 of FGFR1 oncogene partner FGFR1OP Cytoplasm Other 2.77 0.00021 IPI00028481 Ras-related protein Rab-8A RAB8A Plasmamembrane

Other 2.68 0.00026

IPI00006196 Isoform 2 of Nuclear mitotic apparatus protein 1 NUMA1 Nucleus Other 2.65 0.00028 IPI00329115 Isoform 1 of protein C10orf47 C10orf47 Unknown Other 2.57 0.00030 IPI00289334 Isoform 1 of lamin-B FLNB Cytoplasm Other 2.55 0.00030 IPI00658152 Tensin-like SH2 domain containing 1 TNS3 Unknown Phosphatase 2.54 0.00030 IPI00237884 Isoform 1 of A-kinase anchor protein 12 AKAP12 Cytoplasm Transporter 2.51 0.00046 IPI00216219 Isoform long of tight junction protein ZO-1 TJP1 (includes

EG:21872)

Plasma membrane

IPI00745518 Microtubule-associated protein 4 isoform 1 variant(Fragment)

Other 2.48 0.00046

IPI00218753 Isoform 3 of DNA topoisomerase 2-a TOP2A Nucleus Enzyme 2.47 0.00046 IPI00294742 HDCMA18P protein LARP7 Unknown Other 2.45 0.00047

IPI00020513 Zyxin ZYX Plasma membrane

Other 2.36 0.00060

IPI00298289 Isoform 2 of reticulon-4 RTN4 Cytoplasm Other 2.27 0.00068 IPI00157144 GYS1 protein GYS1 Cytoplasm Enzyme 2.21 0.00076 IPI00010471 Plastin-2 LCP1 Cytoplasm Other 2.20 0.00078 IPI00178440 Elongation factor 1-b EEF1B2 Cytoplasm Translationregulator

2.18 0.00078

IPI00220740 Isoform 2 of nucleophosmin NPM1 Nucleus Transcription regulator

2.16 0.00081

MDC1 Nucleus Other 2.16 0.00083

IPI00294840 Absent in melanoma 1 protein AIM1 (includes

EG:11630)

IPI00552897 Isoform 1 of mediator of DNA damage checkpoint protein 1

Unknown Other 2.15 0.00084

IPI00031605 AHNAK nucleoprotein, isoform 2 AHNAK Nucleus Other 2.12 0.00098 IPI00015029 Prostaglandin E synthase 3 PTGES3 Cytoplasm Enzyme 2.11 0.00099 IPI00032064 Isoform A of A-kinase anchor protein 2 2.10 0.00099 IPI00152011 PTPL1-associated RhoGAP 1 ARHGAP29 Cytoplasm Other 2.10 0.00101 IPI00015953 Isoform 1 of nucleolar RNA helicase 2 DDX21 Nucleus Enzyme 2.09 0.00101 IPI00004233 Isoform long of antigen KI-67 MKI67 Nucleus Other 2.08 0.00103 IPI00027831 Glutamate-rich WD repeat-containing protein 1 GRWD1 Nucleus Other 2.02 0.00111 IPI00419933 Pleckstrin homology domain containing, family Amember 2

PLEKHA7 Cytoplasm Other 2.02 0.00111

IPI00017450 Transcription initiation factor IIF a subunit GTF2F1 Nucleus Transcription regulator

2.01 0.00132

IPI00219841 DNA ligase 1 LIG1 Nucleus Enzyme 1.97 0.00144 IPI00218136 137 kDa protein CGN Plasma

Membrane

Other 1.95 0.00149

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Table 1 (Continued )

ID Protein Symbol Location Type(s) S/N P-value

IPI00020021 Protein DEK DEK nucleus Transcription regulator

1.92 0.00161

IPI00031698 Hypothetical protein MGC5509 C2orf49 Unknown Other 1.90 0.00177 IPI00033054 CTD small phosphatase like 2 CTDSPL2 Unknown Other 1.89 0.00179 IPI00376199 Interferon regulatory factor 2 binding protein 2 IRF2BP2 Nucleus Transcriptionregulator

1.85 0.00195

IPI00411635 KIAA0802 protein 1.83 0.00202 IPI00005688 Zinc nger protein 185 ZNF185 Nucleus Other 1.82 0.00206 IPI00470483 WD repeat domain 62 WDR62 Nucleus Other 1.77 0.00219 IPI00152881 Shroom-related protein SHROOM3 Cytoplasm Other 1.76 0.00225 IPI00337426 Isoform 1 of BMP-2-inducible protein kinase BMP2K Nucleus Kinase 1.76 0.00225 IPI00025512 Heat-shock protein b-1 HSPB1 Cytoplasm Other 1.73 0.00265

IPI00456887 Scaffold attachment factor A2 HNRNPUL2 Nucleus Other 1.71 0.00272 IPI00020418 Ras-related protein R-Ras RRAS Cytoplasm Enzyme 1.70 0.00277 IPI00291175 Isoform 1 of vinculin VCL Plasmamembrane

Enzyme 1.66 0.00291

IPI00010746 Phosphatidylserine synthase 1 PTDSS1 Cytoplasm Enzyme 1.61 0.00336 IPI00216654 Isoform b of nucleolar phosphoprotein p130 NOLC1 Nucleus Transcriptionregulator

1.59 0.00365

IPI00645814 KIAA1187 protein MAP7D1 Unknown Other 1.58 0.00370 IPI00019996 modulator of estrogen induced transcriptionisoform b

SLTM Nucleus Other 1.56 0.00388

IPI00013743 Hypothetical protein BUD13 BUD13 (includesEG:215051)

Nucleus Other 1.54 0.00400

IPI00024579 Postreplication repair protein RAD18 RAD18 Nucleus Other 1.52 0.00406 IPI00025087 Isoform 1 of Cellular tumor antigen p53 TP53 (includes

EG:22059)

Nucleus Transcription regulator

1.52 0.00406

IPI00008708 Ribosomal L1 domain-containing protein 1 RSL1D1 Cytoplasm Other 1.51 0.00448 IPI00295457 Myosin phosphatase-Rho interacting protein isoform

1

MPRIP Cytoplasm Other 1.50 0.00449

IPI00002135 Transforming acidic coiled-coil-containing protein 3

TACC3 Nucleus Other 1.49 0.00458

IPI00184317 Isoform short of transcription intermediary factor 1-a

TRIM24 Nucleus Transcription regulator

1.49 0.00508

IPI00394829 Hypothetical protein LOC286077 FAM83H Unknown Other 1.48 0.00512 IPI00294618 Proline-rich protein PRCC PRCC Nucleus Other 1.45 0.00534 IPI00181905 Isoform 1 of protein KIAA1914 AFAP1L2 Cytoplasm Other 1.44 0.00560 IPI00302829 Retinoblastoma-associated protein RB1 Nucleus Transcriptionregulator

1.43 0.00569

IPI00018274 Isoform 1 of epidermal growth factor receptor precursor

EGFR Plasma membrane

Kinase 1.40 0.00598

IPI00289819 Cation-independent mannose-6-phosphate receptor precursor

IGF2R Plasma membrane

Transmembrane receptor

1.39 0.00592

Other 1.43 0.00543

IPI00301294 Protein C2orf17 FAM134A Unknown Other 1.43 0.00543

IPI00100151 5030 exoribonuclease 2 XRN2 Nucleus Enzyme 1.44 0.00528

IPI00010080 Serine/threonine-protein kinase OSR1 OXSR1 Nucleus Kinase 1.45 0.00520

IPI00719818 Nucleolar protein 5A NOP56 Nucleus Other 1.46 0.00496

IPI00011635 Isoform 2 of Bcl-2-like 13 protein BCL2L13 Cytoplasm Other 1.47 0.00482

IPI00006987 ATP-dependent RNA helicase DDX24 DDX24 Nucleus Enzyme 1.49 0.00474

IPI00032107 Sulfate transporter SLC26A2 Plasma membrane

Transporter 1.49 0.00465

IPI00019870 Isoform a of caveolin-2 CAV2 Plasma membrane

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Table 1 (Continued )

ID Protein Symbol Location Type(s) S/N P-value

IPI00297859 Isoform 1 of myeloid/lymphoid or mixed-lineage leukemia protein 2

MLL2 Nucleus Transcription regulator

1.49 0.00465

IPI00019502 Myosin-9 MYH9 Cytoplasm Enzyme 1.54 0.00377

IPI00004273 RNA binding motif protein 25 RBM25 Nucleus Other 1.54 0.00377

IPI00009146 FLN29 gene product TRAFD1 Unknown Other 1.62 0.00291

IPI00719759 Akt substrate AS250 RALGAPA2 Cytoplasm Other 1.62 0.00291

IPI00396634 OTTHUMP00000028561 KIAA1671 Unknown Other 1.65 0.00274

IPI00217709 Isoform b-1 of DNA topoisomerase 2-b TOP2B Nucleus Enzyme 1.72 0.00251

IPI00025156 Isoform 1 of STIP1 homology and U box-containing protein 1

STUB1 Cytoplasm Enzyme 1.84 0.00180

IPI00554788 Keratin, type I cytoskeletal 18 KRT18 Cytoplasm Other 1.84 0.00179

IPI00061758 PRR8 protein RBM33 Unknown Other 1.89 0.00168

IPI00304587 Dispatched B DISP2 Unknown Other 2.02 0.00120

IPI00021275 Isoform 1 of ephrin type-B receptor 2 precursor EPHB2 Plasma membrane

Kinase 2.33 0.00063

IPI00024062 Band 4.1-like protein 1 EPB41L1 Plasma membrane

Other 2.49 0.00044

IPI00744036 Tight junction protein 3 TJP3 Plasma membrane

Other 3.04 0.00007

IPI00748920 Splicing coactivator subunit SRm300 SRRM2 Nucleus Other 3.40 0.00004

IPI00304875 Isoform 1 of HIRA-interacting protein 3 HIRIP3 Nucleus Other 3.62 0.00002

IPI00395887 Thioredoxin domain-containing protein 1 precursor TMX1 Cytoplasm Enzyme 5.34 0.00000 Abbreviation: S/N, signal-to-noise ratio.

Up- or down-regulated phosphoproteins in SNU216-LR compared with SNU216 cells. S/N and P-values were generated by the power law global error model (PLGEM) statistical analysis tool.

Figure 1 Differentially expressed phosphoproteins in SNU216-LR and their functional annotations. (a) Volcano plot showing the P-value ( log10) versus signal-to-noise ratio (S/N) of phosphoproteins determined by power law global error model (PLGEM) statistical analysis

for label-free quantication. (b) Molecular functions of identied phosphoproteins by the Ingenuity Pathway Analysis (IPA) tool. (c) Subcellular localization of identied phosphoproteins by the IPA tool.

arrest by staining the cells with the DNA-intercalating dye propidium iodide. Combination treatment with lapatinib and NVP-BEZ235, selumetinib, saracatinib or crizotinib induced an increase in the percentage of SNU216-LR cells in the G1 phase compared with single-agent treatment (Figure 4b). Next, we examined the levels of total and phosphorylated EGFR, HER2, MET, AKT, MAPK, SRC, cyclin D and p27 in SNU216-LR cells (Figure 4c). As expected, treatment with NVPBEZ235, selumetinib, sacaratinib or crizotinib alone reduced the phosphorylation level of each target or of the downstream

effectors (AKT, MAPK, SRC and MET, respectively). The phosphorylation levels of the selected signaling molecules remained the same after treatment with dimethyl sulfoxide (control) or lapatinib. Treatment with a single kinase inhibitor had no effect on the expression of cell cycle regulatory molecules, including cyclin D. The combination treatment of lapatinib with a kinase inhibitor showed markedly decreased phosphorylation levels in each of the target molecules, such as EGFR and HER2, as well as in the downstream effectors, compared with single treatment. Furthermore, the levels of cell

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Figure 2 Biological network analysis of phosphoproteins. Associations among phosphoproteins are shown by solid or dashed lines, which represent direct or indirect interactions, respectively. Upregulated proteins are shown in red, and downregulated proteins are shown in green.

proliferation-related cyclin D were reduced, and those of the cell cycle inhibitor p27 were increased, after combination treatment. The levels of p-SRC in SNU216-LR were not affected by individual TKI treatment or the combination treatment except the SRC inhibitor (saracatinib) when p-SRC was monitored with the specic tyrosine antibody (Y416). As SRC is known to be an essential communicator between EGFR and MET in LR cancer cells,25 maintaining SRC activation may be necessary for efcient compensatory TKI activation for acquired TKI resistance.

DISCUSSIONLapatinib inhibits growth of HER2-positive gastric cancer cell lines.9 Presently, a phase III clinical trial in patients with advanced gastric cancer is on-going, studying the effects of lapatinib in combination with capecitabine plus oxaliplatin.26

Interest in this trial reects lapatinib being regarded as one of the promising chemotherapeutic drugs for gastric cancer treatment. On the other hand, the medium duration of response to lapatinib is o1 year, and almost 80% of trastuzumab-pretreated patients fail to respond to lapatinib.27

Hence, understanding the mechanisms of acquired lapatinib resistance may help to improve the therapeutic efcacy of lapatinib in HER2-positive cancers.

To identify molecular changes conferring resistance to lapatinib at the system level, we performed a quantitative

phosphoprotein proling of the isogenic gastric cancer cell lines SNU216-LR and SNU216, in which we identied a total of 11 852 phosphorylation sites on 1686 phosphoproteins. Integrating the DPPs into cellular signaling pathways using the IPA network analysis tool provided potential signaling pathways that are regulated in response to lapatinib-induced resistance in SNU216-LR. Among the predominant signaling pathways generated from the IPA analysis, we highlighted the following: three receptor tyrosine kinases (EGFR, HER2 and MET); the two major downstream signaling pathways (PI3K/ AKT and MAPK/ERK); and SRC. We found that the PI3K/ AKT and MAPK/ERK signaling pathways and SRC were constitutively activated in SNU216-LR cells. This observation is similar to those of Rexer et al.,28 who observed active PI3K/AKT and MAPK pathways, including increased phosphorylation of SRC, in LR HER2-overexpressing human breast cancer cells. Activation of the SRC pathway is essential for communication between EGFR and MET.25 For example, lateral signaling in the EGFR/SRC/MET axis was indicated by a delay in the EGFR activation of MET in non-small-cell lung cancer produced by an inhibitor of SRC. Interestingly, our data in SNU216-LR cells show a similar pattern of lateral activation of EGFR/SRC/MET, suggesting that cross-talk between EGFR and MET may play a signicant role in the regulation of SNU216-LR cells. Our conclusions are also supported by the fact that functional cross-talk between EGFR and MET has

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Figure 3 Merged signaling pathways in SNU216-LR. (a) Reconstructed EGFR/HER2 and MET signaling pathways with two downstream signaling pathways (PI3K/AKT and MAPK/ERK). Red, blue and yellow closed circles on each protein represent increased, decreased and newly identied phosphorylation sites in SNU216-LR, respectively. Specic phosphorylated sites (marked with an asterisk) of HER2, EGFR, MET, SRC, C-RAF and MAPK were also identied from immunoblot analysis with antibodies against p-EGFR (pY1068), p-HER2 (pY1221/1222), p-MET (pY1234/1235), p-AKT (pS473), p-MAPK (pY202/pY204), p-SRC (pY416) and p-RAF (pS338). Protein names for symbols are as follows: AKT, a-serine/threonine-protein kinase; C-RAF, RAF proto-oncogene serine/threonine-protein kinase; EGFR, epidermal growth factor receptor; ERK, extracellular signal-regulated kinase; HER2, human epidermal growth factor receptor 2; MAPK, mitogen-activated protein kinase 1; GRB2, growth factor receptor-bound protein 2; MET, hepatocyte growth factor/mesenchymalepithelial transition factor; PI3K, phosphatidylinositide 3-kinase; RAC1, Ras-related C3 botulinum toxin substrate 1; RAS, Ras-related protein R-Ras; SOS, son of sevenless homolog; SRC, proto-oncogene tyrosine protein kinase Src. (b) Immunoblot analysis of SNU216 and three different resistant clones (SNU216-LR 1, 2 and 3) with phospho-tyrosine or serine-specic antibodies. a-Tubulin was used as a loading control. Data are representative of three independent experiments.

been extensively documented as playing an important role in drug resistance. Engelman et al.14 have demonstrated that the compensatory activation of MET is responsible for resistance to EGFR-targeting drugs.14 Puri et al.29 also observed that inhibition of MET in non-small-cell lung cancer is synergistic with EGFR inhibition.

Having found the constitutive activation in LR gastric cancer cells of the PI3K/AKT and MAPK/ERK signaling pathways, as well as activation of SRC, we hypothesized that the constitutive activation of PI3K/AKT and MAPK/ERK confers resistance to lapatinib and may be mediated by MET-axis signaling along the two major downstream pathways. Our data are consistent with the notion of compensatory activation of MET-mediated downstream cellular signaling pathway in response to EGFR blockade.30,31 Results from

several studies have indicated that MET activation is associated with both primary and acquired resistance to EGFR inhibitors in non-small-cell lung cancer.14,15,32,33 Therefore, we postulate

that constitutive activation of the MET-axis PI3K/AKT and MAPK/ERK signaling pathways, including the lateral

activation of SRC, is a compensatory signaling cascade counteracting the selective pressure on EGFR/HER2 in LR human gastric cancer cells.

In the present study, we found that cotreatment with lapatinib and crizotinib is able to induce lapatinib sensitivity. Thus, the active PI3K/AKT and MAPK/ERK signaling pathways induced by the MET axis may be a critical compensatory intracellular event for the survival of LR cells.28 To the best of

our knowledge, the present study is the rst large-scale proling of peptide/protein phosphorylation in gastric cancer cell lines to study lapatinib resistance. Our site-specic and semiquantitative approach demonstrates a useful bioinformatics application, and phosphoproteomic data from the study provide information directly relevant to the mechanisms of lapatinib resistance.

In conclusion, we demonstrated that network-based global phosphoproteomic analysis is a reliable approach for predicting cellular signaling events in LR gastric cancer cells. Our results suggest that the MET-directed PI3K/AKT and MAPK/ ERK cellular signaling pathways contribute to lapatinib

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Figure 4 Antiproliferative effects of selected tyrosine kinase inhibitors on SNU216-LR. SNU216-LR cells were treated via single or combined treatment of lapatinib (Lap; 1 mM), NVP-BEZ235 (BEZ; 100 nM), selumetinib (Selu; 1 mM), saracatinib (Sara; 1 mM) and crizotinib (Crizo; 1 mM). (a) Viable cells were measured after 72 h. The percentage of viable cells is shown relative to untreated controls.

Data represent the means.d. (*Po0.05 for single vs dimethyl sulfoxide (DMSO); **Po0.05 for combination vs single) from three independent experiments. (b) Cells were xed with 70% (v/v) ethanol, stained with propidium iodide and analyzed using ow cytometry.

The proportion of cells in the G1, S and G2/M phases were quantied using the ModFit LT program (Verity Software House). Columns represent the means of three independent experiments. (c) SNU216-LR cells were treated with the indicated drug for 48 h. Whole-cell extracts were analyzed by western blot with antibodies recognizing phosphorylated and total EGFR, HER2, MET, AKT, MAPK, SRC, cyclin D and p27. Data are representative of three independent experiments. AKT, a-serine/threonine-protein kinase; EGFR, epidermal growth factor receptor; HER2, human epidermal growth factor receptor 2; MAPK, mitogen-activated protein kinase 1; MET, hepatocyte growth factor/mesenchymalepithelial transition factor; SRC, proto-oncogene tyrosine protein kinase Src.

resistance, and the constituent signaling molecules may be potential targets for the development of complementary therapeutic options. Therefore, the validity of MET-axis PI3K/AKT and MAPK/ERK signaling pathways should be evaluated using clinical samples and will be the subject of further investigations.

CONFLICT OF INTERESTThe authors declare no conict of interest.

ACKNOWLEDGEMENTSThis research was supported by Grant No. R31-2008-000-10103-0 from the World Class University program of the Ministry of Education, Science, and Technology, the National Research Foundation of Korea and the Proteogenomic Research Program through the National Research Foundation of Korea.

Author Contributions: The manuscript was written through contributions of all authors. All authors have given approval to the nal version of the manuscript.

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