EGFR S1166 Phosphorylation Induced by a Combination of EGF and

Article pubs.acs.org/jpr

EGFR S1166 Phosphorylation Induced by a Combination of EGF and Gefitinib Has a Potentially Negative Impact on Lung Cancer Cell Growth Bobby Fachrizal Assiddiq,† Kah Yap Tan,† Weiyi Toy,† Siew Pang Chan,‡ Poh Kuan Chong,† and Yoon Pin Lim*,†,§,∥ †

Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore Division of Health Sciences, La Trobe University, Bundoora VIC 3083, Australia § Bioinformatics Institute, Agency for Science, Technology and Research, Singapore ∥ NUS Graduate School of Integrative Sciences and Engineering, Singapore ‡

S Supporting Information *

ABSTRACT: Phosphorylation of protein plays a key role in the regulation of cellular signal transduction and gene expression. In recent years, targeted mass spectrometry facilitates functional phosphoproteomics by allowing specific protein modifications of target proteins in complex samples to be characterized. In this study, we employed multiple reaction monitoring (MRM) to examine the influence of gefitinib (also known as Iressa) on the phosphorylation sites of EGFR protein before and after EGF treatment. By coupling MRM to MS/MS, 5 phosphotyrosine (Y1110, Y1172, Y1197, Y1069, and Y1092) and 1 S/T (T693) sites were identified on EGFR. Y1197 and T693 were constitutively phosphorylated. All phosphorylation sites were sensitive to gefitinib treatment except T693. Interestingly, gefitinib treatment induced phosphorylation of S1166 only in the presence of EGF. We further showed that lung cancer cells overexpressing phosphomimic S1166D EGFR mutant possessed significantly lower growth and proliferation property compared to wildtype EGFR-expressing cells. While the function and mode of regulation of S1166 remain unclear, our data supports the notion that S1166 represents a regulatory site that exerts a negative regulation on growth and proliferation of cancer cells. The data presented has implication in our understanding of dynamic drug (gefitinib)−target (EGFR) interaction and in improving the efficacy of target-directed therapeutics. KEYWORDS: EGFR, gefitinib, multiple reaction monitoring, phosphorylation, lung cancer

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INTRODUCTION Phosphorylation of protein at serine, threonine, and tyrosine residues plays an important role in the regulation of cellular process and pathways such as cell division, signal transduction, and gene expression.1 Phosphoproteomics using a shotgun approach has been successful for large scale identification and characterization of phosphorylation sites in stem cell biology,2 oncogenic signaling and cancer research.3−7 For example, Gygi’s group8 have combined tandem phosphopeptide enrichment methods using immobilized metal ion affinity chromatography (IMAC), immunoprecipitation of pTyr-containing peptides, followed by MS analysis and database search/data filtering strategies to survey the liver phosphoproteome. In such shot-gun approaches, a large number of phosphoproteins and peptides are identified in a random fashion, and often, a substantial amount of information is potentially lost. It is, therefore, not amenable for characterization of phosphorylation sites on specific targets. © 2012 American Chemical Society

As we transit from discovery into the phase of functional phosphoproteomics, one can envisage increasing emphasis on specific disease effecters, their functions, and their modes of actions. In such circumstances, it becomes critical that an individual phosphoprotein be thoroughly characterized in various biological conditions. Multiple reaction monitoring (MRM) offers some features that are lacking in the shotgun approach. It is a specific detection methodology with low background, thereby enhancing detection of low abundance proteins in complex mixture.9 Furthermore, MRM can analyze multiple different transitions from the same analyte, for example, in monitoring multiple transitions for alternative phosphosites, thus facilitating in-depth analysis.9,10 Indeed, MRM has been designed to comprehensively analyze single or multiple target proteins. For example, Unwin et al.10 specifically targeted the potential phosphorylation sites on Cyclin B Received: March 1, 2012 Published: June 18, 2012 4110

dx.doi.org/10.1021/pr3002029 | J. Proteome Res. 2012, 11, 4110−4119

Journal of Proteome Research

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protein in Schizosaccharomyces pombe. Two phosphorylation sites (Y15 and T167) known to be important for regulation of the cell cycle and a novel site (S111) were identified. Their work demonstrated the capability of MRM−MS/MS in detecting and sequencing phosphopeptides at low femtomole level with high selectivity. In another study, six important tyrosine phosphorylation sites on FAK, including phosphorylated Y397 (pY397), pY407, pY576, pY577, pY861, and pY925, were successfully monitored.11 In addition, they were able to qualitatively differentiate between autocatalytic and Src-induced phosphorylation events on FAK. In yet a different flavor, WolfYadlin12 et al. used MRM following a data-dependent acquisition discovery mode to quantify the phosphorylation of 222 peptides from multiple proteins across 7 time points following EGF stimulation of human mammary epithelial cell.25 EGFR is an important oncogene in many human cancers including that of the lung, head, and neck.13 Gefitinib, a highly selective EGFR inhibitor, has been approved by FDA for treatment of chemo-refractory lung cancer.14 It is an ATP analogue and selectively blocks EGFR activity, EGFR autophosphorylation at tyrosine sites, and hence tyrosine phosphorylation of downstream substrates.15 While several reports have described the identification of phosphorylation sites on EGFR and its downstream substrates,16−18 there is no systematic study that characterizes the EGF-induced EGFR phosphorylation sites before and after gefitinib treatment. In this study, MRM was used to target and analyze possible S/T phosphorylation sites on EGFR protein in addition to the expected Y phosphorylation sites to examine closely the action of gefitinib on EGFR in the presence and absence of EGF.

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Biosciences, San Jose, CA, USA) to examine the phosphorylation states of EGFR. PY20H was diluted at 1:1000 for 1 h and washed with 1× phosphate-buffered saline (PBS). Protein bands were then detected using the enhanced chemiluminescence (ECL) Western blot detection kit (Amersham Biosciences). Protein Purification and Digestion

Following appropriate treatment of A431 cells and to purify EGFR proteins, 300−400 μg of lysates was resolved via 1D SDS-PAGE in batches and stained with coomassie blue. The 180 kDa protein band representing the EGFR protein was manually excised. The gel strips were destained and dehydrated with ammonium bicarbonate and acetonitrile (ACN). The proteins were then reduced with 10 mM DTT at 60 °C for 40 min followed by alkylation using 100 mM iodoacetamide at room temperature for 1 h. Sequencing grade trypsin was used to digest the protein with the ratio 1:50 at 37 °C for overnight. The generated tryptic peptides were then extracted from the gel by sequential extraction buffer 30% ACN, 3.5% formic acid, followed by 50% ACN, 5% formic acid, then 100% ACN. Gel pieces were incubated at 37 °C for 20 min at every step, and the supernatant was pooled together. Following centrifugation to dryness and prior to liquid chromatography−MS analysis, the peptides were resuspended in 2% acetonitrile and 0.1% formic acid. MIDAS Workflow

MRM-initiated detection and sequencing (MIDAS)10 was used as per manufacturer’s instruction. This software generates MRM transitions based on the peptide/phosphopeptide list created through in silico digestion or the incorporation of peptides/phosphopeptides identified from the discovery stage. MIDAS experiment requires a protein sequence, information on the enzyme employed, and selection of phosphorylated sites as potential post-translational modifications. For every peptide generated using in silico digestion, a MRM transition is generated through the monitoring of both the precursor ion and a fragment ion. To confirm the identification of the phosphopeptides, at least two charge states per peptide were employed during MRM analysis. In addition, a full MS/MS scan is triggered when a MRM signal reaches more than 150 counts to generate the peptide sequence. If the same peptide assignments were obtained from MRM−MS/MS of the different charged states, it would increase the confidence of the phosphopeptide identification. In addition, since different charge states of the peptide are likely to have different abundance, analysis of at least 2 charge states would increase the chance of detecting the phosphopeptides.

MATERIALS AND METHODS

Preparation of Cell Lysate from A431 Cells

Human epidermal carcinoma A431 cell line was obtained from the American Type Culture Collection (Rockville, MD, USA). The cells were cultured in DMEM supplemented with 10% FBS (Invitrogen), penicillin, and streptomycin and incubated at 37 °C in a humidified atmosphere containing 5% CO2. Cells were serum starved for 16 hrs before stimulation with 50 ng/ mL of epidermal growth factor (EGF, Sigma Aldrich) for 30 min. Where specified, cells were pretreated with 10 mM gefitinib (ZD1839, Iressa), kind gifts from AstraZeneca, for 1 h before EGF stimulation. Protein was extracted from A431cells as described previously.19 The total protein extracted was estimated using Protein Bradford Assay (Thermo Scientific, USA). Immunoprecipitation and Immunoblotting

Five hundred micrograms worth of total proteins from cell lysate was used for small-scale immunoprecipitation of EGFR, using 5 μg of antibody and 40 μL of a 50% slurry of protein ASepharose for 16 h at 4 °C. Immune complexes were then washed three times in lysis buffer and boiled in Laemmli buffer. The migration of EGFR on SDS-PAGE was examined by conducting immunoblotting as described elsewhere.17,18 Briefly, immunoprecipitates were probed with anti-EGFR antibodies (BD Transduction Laboratories, Lexington, KY, USA) at 1:1000 dilution for 16 h at 4 °C, washed 3 × 5 min with 1× phosphate-buffered saline with Tween-20 (PBST), and incubated with antimouse secondary antibody conjugated to horseradish peroxidase (1:25 000) for 1 h. In addition, EGFR immunoprecipitates were also probed with antiphosphotyrosine antibodies conjugated to horseradish peroxidase (PY20H, BD

Nano-LC-ESI-MS/MS Analysis and Database Searches

All samples were analyzed by reverse phase liquid chromatography/mass spectrometry (rpHPLC−MS/MS) with MRM. Experiments were performed on a hybrid triple quadrupole linear ion trap mass spectrometer 4000 QTRAP (Applied Biosystems, Foster City, CA, USA). Chromatography was performed on a Tempo 1D-plus nano-LC system (Applied Biosystems, Foster City, CA, USA) with buffer A containing 2% acetonitrile and 0.1% formic acid while buffer B was composed of 98% acetonitrile and 0.1% formic acid. Initially, the samples were washed in a precolumn (30 m inner diameter × 5 mm) (Dionex) with 98% buffer A for 5 min. Subsequently, samples were injected into a PepMap C18 nanocolumn (75 μm inner diameter × 150 mm) (Dionex) and eluted at 300 nL/min. The 4111



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Table 1. Comparison of the Phosphotyrosine Peptides of EGFR Detected in Previous Reports (1st Column from Left) versus Those Detected in This Study (1st Column from Right) reported sites y270 y316 y727 y764 Y869 Y944 Y978 Y998 Y1016 Y1092

in silico digested peptides

a

type of cells

Y1110 Y1125 Y1138 Y1172

DTCPPLMLYNPTTYQMDVNPEGK ACGADSYEMEEDGVR VLGSGAFGTVYK EILDEAYVMASVDNPHVCR EYHAEGGKb LPQPPICTIDVYMIMVK YLVIQGDER MHLPSPTDSNFYR not found in MIDAS in silico digest due to parameters used but intentionally included for MRM analysis not found in MIDAS in silico digest due to parameters used, but this peptide was identified via manual inspection of MS/MS spectra from MRM experiments; YSSDPTGALTEDSIDDTFLPVPEYINQSVPKc RPAGSVQNPVYHNQPLNPAPSR Not found in MIDAS in silico digest due to parameters used not found in MIDAS in silico digest due to parameters used GSHQISLDNPDYQQDFFPK

Y1197

GSTAENAEYLR

Y1069

not found in MIDAS in silico digest due to parameters used but intentionally included for MRM analysis

ref for reported sites

identified in this study

HeLa HeLa HN5 cells HeLa HeLa HN5 cells HeLa HeLa

21 21 17 21 21 17 22 18, 22

no no no no yes no no no no yes

HeLa HeLa HeLa 184A1 HMECs, HeLa 184A1 HMECs, HeLa HeLa

18, 22 22 18, 22 18, 12, 22

yes N/A N/A yes

18, 12, 22

yes

18

yes

a

Parameters are set up in such a way that only peptide 30 amino acids or less are displayed. See text for more explanation. bMisscleaved peptide identified using MS/MS protein identification. cIdentified using manual inspection of MS/MS spectra obtained from MRM experiment.

using QuikChange II XL Site-Directed Mutagenesis Kit (Stratagene, La Jolla, CA, USA). Mutation was verified by DNA sequencing.

separation was performed using a 50 min continuous gradient. It started with 4% B, reaching 10% B at 0.5 min, 55% B at 25 min, and 100% B at 35 min. This is followed by washing with 100% B for 5 min before conditioning the column with 4% B from 40.1 min to 50 min. Samples eluted from the chromatographic column were ionized by the electrospray ionization (ESI) source (Applied Biosystems) and analyzed by the 4000 QTRAP mass analyzer. The column was connected to the ESI source using 70 μm inner diameter fused silica tubing that was threaded through the metal ion source needle. The ion source voltage was set at 2300 V, and a nitrogen sheath gas flow was employed. The detector was set at 2300 and DP was increased to 80 to enhance the measurement of peptide. Mass spectrometric data were analyzed with in-house licensed bioinformatics database search engine system, Mascot (Matrix Sciences, London, United Kingdom). The actual protein/peptide identification is done by database searching of the MS/MS spectra. Spectra were searched against a human subset of the SwissProt nonredundant database (version 3.41, date of release: March 2008, 72155 sequences), combined with ion cut of 10. The search parameters were set to include a maximum of two missed cleavages with full trypsin enzymatic limits; average precursor mass tolerance of 1.0 Da; and monoisotopic fragment ion mass with tolerance of 1.0 Da. Mowse Score is a probability algorithm used by Mascot to evaluate data obtained from MS/MS experiments. In this experiment, proteins with a (MOWSE) score greater than 40 were considered significant. In addition, the MS/MS spectrum was inspected manually for further confirmation of identified peptides.

Proliferation Assay

H838 cells were obtained from ATCC and cultured in RPMI1640 (Sigma, St Louis, MO, USA) supplemented with 10% FBS (Hyclone, Cramlington, UK) and 1% penicillin/ streptomycin (PAA, Pasching, Austria). Cells were grown in 6well plates and transfected at 80% confluency with 1 μg of pMyc-EGFR (wildtype) plasmid or pMyc-EGFR (S1166D) plasmid using jetPrime (Polyplus, Illkirch, France) according to manufacturer’s protocol. Twenty-four hours later, 2500 transfected cells were reseeded in triplicates in 100 μL of culture media per well in 96 well plates. The remaining cells were harvested to monitor exogenous EGFR protein expression. The next day, the number of cells transfected with WT or mutant EGFR not treated with gefinitib was measured using CellTiter 96 Aqueous One Solution (MTS) Cell Proliferation Assay Reagent (Promega, Madison, Wisconsin USA) according to manufacturer’s protocol. This is referred to as day 0. At the same time, the media for the rest of the transfected cells was changed to RPMI1640 supplemented with 0.5% FBS and 1× penicillin/streptomycin at various concentrations (0 μM, 1 μM, 5 μM, and 10 μM) of gefitinib (AstraZeneca). Culture media and drugs were replenished every day. On day 4, cell number was measured again. The fold change in cell proliferation was obtained by dividing the values for day 4 with that of day 0. The experiment was repeated independently twice, with 3 technical replicates for each condition as per the approach used in our previous report.20 A total of at least 48 readings were subsequently used for statistical analysis (see Supplementary Data 2, Supporting Information).

Mutagenesis

pMyc-EGFR plasmid was a kind gift from Dr. Graeme Guy (Institute of Molecular and Cell Biology, Singapore). Mutation of serine-1166 to aspartic acid in pMyc-EGFR was performed 4112



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Figure 1. (A) Representative ion chromatogram showing coelution of the three MRM transitions 772.7/653.3 (red line), 772.7/909.4 (blue line), and 772.7/1364.6 (green line). These transition ions were derived from the same precursor ion of m/z 772.7, which corresponds to GSHQISLDNPDpYQQDFFPK (pTyr-1172). The red, blue, and green signals correspond to the mass fragments of y5, y7, and y10, respectively. (B) MS/MS spectrum that confirms the presence of the peptide GSHQISLDNPDpYQQDFFPK.

adjusting for the effect of different dosages (0, 1, 5, and 10 μM). The models are not required to make any distributional assumption about the outcome. Residual analyses were conducted to ascertain if the models provide a reasonable fit

Statistical Analysis

Both the multiple linear regression and the linear mixed-effect models were applied for analyzing the variations in the proliferation between EGFR WT and S1166D mutant, while 4113



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Figure 2. (A) Coeluting of MRM transitions from precursor ion m/z 1160.2 that corresponds to the peptide YSSDPTGALTEDSIDDTFLPVPEYINQSVPK with two possible sites of phosphorylation at (B) Tyr-1092 or (C) Tyr-1069. The triply charged peptide has the same m/z value whether it is phosphorylated at Tyr-1092 or Tyr-1069. Inspection of the MS/MS spectra revealed the existence of peptides phosphorylated singly either at Tyr-1069 or Tyr-1092.

we have previously shown they were highly responsive to EGF stimulation, which could be blocked by gefitinib.19 To characterize EGF-induced phosphorylation of EGFR, purified EGFR was prepared for mass spectrometry analysis as per described under the materials and methods section. To generate MRM transitions, in silico digest was first performed using MIDAS. The parameters for in silico digest were set to produce only peptides with less than 30 amino acids and with one site of tyrosine phosphorylated. The reason for focusing on peptides of a certain size is because peptides that are too large

to the data. Analyzed with Stata 11.0 (Stata Corp, Texas, U.S.A.), all statistical tests were performed with 95% confidence intervals (C.I.). A factor (cell group, SD versus WT; dosage, 0, 1, 5, and 10 μM) is deemed to be statistically significant in explaining the outcome if the resultant 95% C.I. contains 0.

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RESULTS AND DISCUSSION

Tyrosine Phosphorylation of EGFR

To study phosphorylation events of EGFR, human A431 cell line was chosen due to its high level of EGFR expression,17 and 4114



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and MS/MS spectra for the other tyrosine-phosphorylated peptides are provided in the Supporting Information. A previous study by Wolf-Yaldin et al. had also utilized the MRM−MS/MS approach to study tyrosine phosphorylation of EGFR.12 Our study detected two of the several tyrosinephosphorylated sites on EGFR (Tyr-1197 and Tyr-1172) identified in Wolf-Yaldin’s work. However, our results identified more phosphotyrosine peptides of EGFR using the MRM− MS/MS method alone. This is likely due to the fact that analysis of EGFR phosphorylation sites in Wolf-Yadlin’s work was performed on whole cell lysates,12 whereas purified EGFR was used in this study. The results in this study are also consistent with the work done by Schulze et al.21 that detected EGFR peptides containing phosphorylated Tyr-1110, Tyr1172, and Tyr-1197. Moreover, using different MS platforms, they were able to identify in total six phosphotyrosine sites of EGFR, including two novel phosphorylation sites (Tyr-801 and Tyr-998).22 This demonstrates that various MS systems are complementary to each other.

are usually highly charged and low in intensity. This may result in the mass spectrometer failing to detect them or resulting in futile scanning and prolonged duty cycles. Sixty-eight MRM transitions (Supplementary Data 1, Supporting Information) were generated from the in silico digested peptides to be used later for detection of EGFR tyrosine phosphorylation sites. The MRM transitions generated for EGFR in this experiment included only oxidation of methionine in peptide as a variable modification. Note that the in silico digest and subsequent mass spectrometric analysis employ only trypsin. Hence, the approach used will not provide all the peptides of interest with the optimal length for mass spectrometric analysis. Combinational use of different proteases should expand the coverage of identifiable target peptides/sites. Most of the phosphopeptides in the MRM list were previously reported to have biological relevance12,17,18,21,22 such as those involved in the interaction of EGFR with downstream signaling components22 and the binding of EGFR to the SH2 domain of c-src.21 Some of the target sites have been reported to play a role in EGFR signaling in squamous carcinoma cells.17 Table 1 shows a comparison of the reported EGFR phosphopeptides versus those detected in this study through MRM of the transitions generated from the in silico digested peptides. Although there were five reported phosphopeptides that were longer than 30 amino acids (Tyr-1016, Tyr-1092, Tyr-1125, Tyr-1138, and Tyr-1069) (see Table 1), two of them (Tyr-1016 and Tyr-1069) were intentionally included for analysis as we wanted to determine whether the MRM−MS/ MS approach could detect peptides larger than 30 amino acids. Note that only 6/17 (35%) of the reported EGF-induced tyrosine phosphorylation sites on EGFR were detected (including Tyr-1069, which is one of the two peptides longer than 30 amino acids). The fact that only about one-third of all reported phosphopeptides could be detected might be due to the sensitivity of the machine used and/or that not all the sites were phosphorylated at the duration of EGF treatment used. Since phosphatase inhibitors were routinely added into the lysis buffer, it is unlikely that phosphatase activity could have caused the low number of phosphosites being detected. Of the six phosphopeptides detected, five of them (pTyr-869, pTyr-1110, pTyr-1172, pTyr-1197, and pTyr-1069) were identified from the lysates of EGF-treated cells using MRM-triggered MS/MS analyses that target phosphorylated tyrosine only (pY-MRM). pTyr-1092 were identified via manual inspection of MS/MS spectra obtained from MRM experiment. Identification of the phosphotyrosine-containing peptide GSHQISLDNPDpY(1172)QQDFFPK is illustrated as an example. The precursor ion of m/z 772.7 that represents the triply charged peptide was selected for fragmentation. Three different MRM transition ions of m/z 909.4, 653.3, and 1364.6, representing y5, y7, and y10, respectively, were detected (Figure 1A). Each of these transitions produced a peak, and all three peaks coeluted, which is indicative of a positive identification for this phosphorylated peptide. Furthermore, when a MRM signal is more than 150 counts, a full MS/MS scan of the target precursor ion in the ion trap mode is triggered, generating the total compliment of fragment ions from which the peptide sequence can be constructed. Figure 1B shows a representative MRM-triggered MS/MS spectrum obtained from the fragmentation of the triply charged ion (m/z 772.7), which helped to confirm the presence of the phosphorylated peptide concerned in the sample. MRM traces

Multiple Phosphorylation Sites within the Same EGFR Peptide

MRM approach also enables us to identify different tyrosine phosphorylation sites on the same peptide. Figure 2A shows the MRM transitions of an m/z 1160.2 precursor ion that represents the phosphorylated peptide Tyr-1092 YSSDPTGALTEDSIDDTFLPVPEpYINQSVPK. Note that this peptide also has another possible tyrosine phosphorylation site at Tyr1069. The triply charged peptide has the same m/z value whether it is phosphorylated at Tyr-1069 or Tyr-1092. Two ions at m/z 672.3 and 785.5 representing y6 and y7 were targeted as they would be common fragments between the peptide phosphorylated at Tyr-1069 and Tyr-1092. This is to ensure that the parent ion is indeed present. Discriminatory fragment ions at m/z 1157.6 and 1254.6 representing y9 and y10 were also set up to target the peptide phosphorylated at Tyr-1092. In contrast, the same fragment ions (y9 and y10) for the peptide phosphorylated at Tyr-1069, namely, m/z 1077.6 and 1174.6 were also targeted. If the fragment ions m/z 1157.6 and 1254.6 could be detected, it would be indicative that Tyr1092 is phosphorylated. However, if m/z 1077.6 and 1174.6 ions were detected, it would imply that Tyr-1069 is phosphorylated. It was observed that the precursor ion of m/z 1160.2 eluted at different times within the same injection. Following investigation of the mass spectra, we found that the peptide containing phosphorylated Tyr-1092 and Tyr-1069 eluted at 37.5 min and 39.2 min, respectively. Figure 2B,C show the representative MS/MS spectra for the peptides containing phosphorylated Tyr-1092 or Tyr-1069. Note that the data only supported the notion that Y1069 and Y1096 could be phosphorylated singly. There is no further MS/MS evidence to suggest that a diphosphopeptide exist since the MRM method in this study was designed to target peptide with only 1 phosphorylated site. It is possible to target two or three phosphosites within the same peptide, and this will be an interesting area to explore using MRM approach in the future. Effect of Gefitinib Treatment on EGFR Phosphorylation

Gefitinib, also known as Iressa, is a tyrosine kinase inhibitor. This drug belongs to the class of anilinoquinazoline, as an active, selective, and reversible EGFR tyrosine kinase inhibitor.23 The inhibition of EGFR by tyrosine kinase inhibitor, gefitinib, has been studied for cancer treatment24 4115



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Figure 3. (A) Tyrosine phosphorylation EGFR in A431 cells in the presence or absence of EGF and gefitinib. EGFR was immunoprecipitated (IP) from 500 μg worth of proteins from cells treated with various conditions. Upper panel, immunoprecipitates were immunoblotted (IB) with antiphosphotyrosine antibodies to reveal the tyrosine phosphorylation level of EGFR. Lower panel, immunoprecipitates were probed with antiEGFR antibodies to reveal the amount of EGFR precipitated. (B) Table shows the phosphorylated sites from EGFR identified using discovery (identification) method and MRM−MS/MS approach. O, nonstimulated (control); E, EGF stimulated; OI, gefitinib pretreatment; IE, gefitinib pretreatment followed by EGF stimulation.

and cancer therapy.25 Studies have shown that mutation in EGFR that renders it constitutively active sensitize EGFR to gefitinib inhibition.26,27 However, the precise effect of gefitinib on the phosphorylation sites of EGFR has never been investigated. We, therefore, studied EGFR phosphorylation in A431 cells in the absence or presence of EGF and/or gefitinib using the pY-MRM methodology as described above. EGFR was first immunoprecipitated and then immunoblotted with antiphosphotyrosine antibodies (PY20H) to reveal the tyrosine phosphorylation level. The corresponding level of immunoprecipitated EGFR was shown following probing with anti-EGFR antibodies. Figure 3A shows that the tyrosine phosphorylation level of EGFR in A431 cells increased upon treatment with EGF and that this was abrogated by pretreating the cells with gefitinib. There is a very faint PY20H signal following treatment with gefitinib. It is likely that these represent background noise rather than real signal since the residual signals have the same intensities in both EGF treated and untreated cells. If the signal was indeed due to residual EGFR activity, one would expect a higher intensity in EGF-treated cells compared to nonEGFtreated cells. Four tyrosine-phosphorylated sites were identified, i.e., Tyr-1069, Tyr-1110, Tyr-1172, and Tyr-1197, from EGFR protein in EGF-stimulated cells, compared to a single phosphotyrosine site identification (Tyr-1197) from cells not stimulated with EGF (see Figure 3B). In other words, phosphorylation at Tyr-1197 is constitutive in A431 cells grown in culture. This is consistent with the immunoblot data shown in Figure 3A where tyrosine phosphorylation of EGFR was observed even in the absence of EGF. This data is not

surprising since A431 cells expressed very high levels of EGFR, and overexpression of EGFR could have resulted in forced dimerization of the receptors, a key step toward receptor activation. However, no phosphotyrosine peptide was identified from cells treated with gefitinib (Figure 3B). Gefitinib treatment had completely inhibited tyrosine phosphorylation in EGFR protein even when cells were stimulated with EGF. The mass spectrometry results are congruent with the immunoblotting data shown in Figure 3A, lanes 3 and 4. The result is comparable to the previous work reported in which gefitinib was found to block EGF-stimulated EGFR phosphorylation completely in various cancer cells such as Du145 (prostate), A549 (lung), KB (oral squamous), and HT29 (colon).25 Our results also show similarity with the inhibition of EGFR by erlonitib (OSI774) drug, another tyrosine kinase inhibitor that is similar to gefitinib and that which belongs to the class of anilinoquinazoline.17 Utilizing both LC−MS/MS and MALDI studies, the previous study showed that inhibition of autophosphorylated EGFR by erlotinib significantly decreased phosphorylation of EGFR at site Tyr-1069, Tyr-869, and Tyr1092.17 Apart from targeting the reported phosphotyrosine sites (see Table 1), we have also developed a method of analysis to target all possible phosphorylation in EGFR protein using MIDAS (pSTY-MIDAS). Similarly to pY-MRM, the developed method targeted only one possible phosphosite in target peptides. Unlike pY-MRM, the pSTY-MIDAS method aims to detect phosphoserine and phosphothreonine in addition to phospho4116



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tyrosine sites. A total of 127 transitions were included. This method was designed to determine the effect of gefitinib on various phosphorylated sites including those of serine and threonine on EGFR. Overall, a total of 5 phosphosites were identified in various conditions. They include Ser-1166, Thr693, Tyr-1197, Tyr-1110, and Tyr-1172 (Figure 3B), the last three of which were also detected by the pY-MIDAS approach described earlier. Phosphorylation at Thr-693 of EGFR protein was identified in all conditions, indicating that phosphorylation of this site is independent of EGF treatment and gefitinib treatment. Interestingly, phosphorylation at Ser-1166 was identified only in the sample treated with both gefitinib and EGF. Serine/threonine phosphorylations of EGFR by members in the MAP kinase family28 and CaMKII29 have been reported and are usually part of the negative feedback mechanism. Phosphorylation of both Thr-69330 and Ser-116631 has been detected by several recent mass spectrometry-based global mapping of phosphorylation sites. The key aim of this study is to detect qualitative appearance/ disappearance of phosphorylation events in the presence/ absence of gefitinib instead of obtaining quantitative data. Monitoring the absence/presence of phosphorylation events should not be surprising since gefitinib is well-known to be a very potent inhibitor of EGFR signaling in our hands and that of many others, oftentimes completely abolishing EGFR activity (see Figure 3A as supporting evidence). Hence, no quantitative data was generated for this experiment. Instead, the evidence in Figure 3B in the main text and Figure S5 in the Supporting Information support the notion that phosphoSer1166 exists in the presence of EGF and gefitinib. The above data also supported the notion that the presence of gefitinib does not affect phosphorylation on serine and threonine sites significantly compared to tyrosine phosphorylation. This is consistent with the fact that gefitinib does not act usually on serine and threonine kinases such as raf, MEK-1, and MAPK, which are downstream targets of EGFR.25

Figure 4. Molecular characterization of S1166 phosphorylation on H838 lung cancer cell growth and response to gefitinib. Cells were first transfected with either wildtype (WT) EGFR or S1166D (SD) phosphomimic mutant. Cells were then grown in the absence or presence of gefitinib at the indicated doses and viable cell numbers were measured at day 0 and 4. Two separate experiments, each with triplicate readings, were conducted. The number of folds of growth was then obtained by using day 0 as the denominator. Box plots were generated and statistical analyses performed. The expression of the WT and SD EGFR is shown in the inset.

Table 2. Description of the Level of Proliferation of WT and Mutant (SD) EGFR-Expressing Cells in Response to Gefitinib Treatment dose (μM)

SD (n = 24) mean (range)

0 1 5 10

1.56 1.71 1.29 0.94

(1.45−1.69) (1.48−1.88) (1.08−1.54) (0.87−1.05)

WT (n = 24) mean (range) 1.83 2.15 1.57 1.10

(1.64−2.06) (2.11−2.21) (1.40−1.86) (1.06−1.21)

Table 3. Regression Analyses of Proliferation of WT and Mutant (SD) EGFR-Expressing Cells in Response to Gefinitib Treatment

Role of S1166 Phosphorylation on Growth and Proliferation of Lung Cancer Cells

Phosphorylation of Ser-1166 occurred only in the presence of EGF and gefitinib but not in the presence of gefitinib alone. It is conceivable that this site is exposed only following EGFR activation. It might then be phosphorylated by a serine/ threonine kinase that is activated by gefitinib treatment. While this hypothesis will have to be tested in a separate dedicated study, it is conceivable that phosphorylation of S1166 has a negative effect on cell growth and proliferation. To investigate this postulation, we overexpressed EGFR wildtype (WT) and S1166D phosphomimic mutant in H838 lung cancer cells and compared the growth and proliferation of these transfectants in the presence or absence of gefitinib. H838 lung cancer cells were chosen because it had a very low endogenous level of EGFR. This is such that the endogenous EGFR will not interfere with the effects of exogenously expressed EGFR substantially. Two separate experiments were conducted. Figure 4 and Table 2 show that, while the trends in proliferation were similar in both cell groups, the level of proliferation was higher in cells transfected with EGFR WT when compared with the S1166D mutant. The results are confirmed with both the linear regression and the linear mixedeffect model. That is, the proliferation of EGFR S1166D mutant was indeed significantly lower than that of EGFR WT (Table 3). Other things being equal, the proliferation was

factor

linear regression model coefficient

95% C.I.

linear mixed-effect model coefficient

95% C.I.

reference

reference

reference

reference

−0.29

−0.34

−0.29

−0.17 to −0.40

SD dose (μM)a 0

reference

−0.20 reference

reference

reference

0.23

1 5

0.07 to 0.39 −0.43 to −0.11 −0.84 to −0.52

cell groupa WT

−0.27

0.12 − 0.35 −0.38

−0.27

−0.68

−0.15

−0.68

0.23

−0.79 to −0.56

10 a

Statistically significant.

significantly higher when the cells were treated with 1 μM gefinitib compared with untreated cells. This was somewhat surprising, but it could be due to compensatory mechanisms triggered by the cells in response/adaptation to the drug. If this observation could be reproduced in other lung cancer cell lines, it would have an important implication in clinical management 4117



Article

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of lung cancer with gefinitib. Nonetheless, the proliferation declined significantly with the higher dosages (5 μM and 10 μM) as expected. Both models are found to be satisfactory in analyzing proliferation with cell group and dosage as factors. The explanatory power of the linear regression model, quantified by the adjusted R2, is as high as 87.3%. In previous studies, it has been reported that mutation that led to constitutive activation of the EGFR is more sensitive to gefitinib inhibition than wildtype, nonactivated EGFR.26,27 Although the functional significance of Ser-1166 phosphorylation with respect to sensitivity to gefitinib or to gefitinib’s action remains unclear, our data suggested that S1166 phosphorylation might exert a negative influence on cell growth and proliferation. However, it is noted that the effect of S1166D phosphomimic mutant on cell growth and proliferation was not a strong one, implying that other negative modes of regulation, in addition to the potential contribution from S1166 phosphorylation, may account for gefitinib’s action.

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CONCLUSIONS MRM is a useful method for mass spectrometry-based characterization of protein translational modifications. Using MRM, we revealed that S1166 phosphorylation site following EGFR activation and gefitinib treatment might constitute part of the mechanism through which gefitinib exerts its inhibitory effect on cancer cell growth and proliferation.

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ASSOCIATED CONTENT

S Supporting Information *

This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone: (65)66011891. Fax: (65)67791453. E-mail: bchlyp@ nus.edu.sg. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by funding from the Singapore Cancer Syndicate, Agency for Science, Technology, and Research (A*STAR). We would like to thank Dr. Sahana Mollah from ABI Sciex, USA, for scientific discussions and advice.

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REFERENCES

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EGFR S1166 Phosphorylation Induced by a Combination of EGF and

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