- Open Access
Analysis of EGFR signaling pathway in nasopharyngeal carcinoma cells by quantitative phosphoproteomics
- Lin Ruan†1, 2,
- Xin-Hui Li†1,
- Xun-Xun Wan†1, 3,
- Hong Yi1,
- Cui Li1,
- Mao-Yu Li1,
- Peng-Fei Zhang1,
- Gu-Qing Zeng1,
- Jia-Quan Qu1,
- Qiu-Yan He1,
- Jian-Huang Li1,
- Yu Chen1,
- Zhu-Chu Chen1 and
- Zhi-Qiang Xiao1Email author
© Ruan et al; licensee BioMed Central Ltd. 2011
- Received: 28 April 2011
- Accepted: 28 June 2011
- Published: 28 June 2011
The epidermal growth factor receptor (EGFR) is usually overexpressed in nasopharyngeal carcinoma (NPC) and is associated with pathogenesis of NPC. However, the downstream signaling proteins of EGFR in NPC have not yet been completely understood at the system level. The aim of this study was identify novel downstream proteins of EGFR signaling pathway in NPC cells.
We analyzed EGFR-regulated phosphoproteome in NPC CNE2 cells using 2D-DIGE and mass spectrometry analysis after phosphoprotein enrichment. As a result, 33 nonredundant phosphoproteins including five known EGFR-regulated proteins and twenty-eight novel EGFR-regulated proteins in CNE2 were identified, three differential phosphoproteins were selectively validated, and two differential phosphoproteins (GSTP1 and GRB2) were showed interacted with phospho-EGFR. Bioinformatics analysis showed that 32 of 33 identified proteins contain phosphorylation modification sites, and 17 identified proteins are signaling proteins. GSTP1, one of the EGFR-regulated proteins, associated with chemoresistance was analyzed. The results showed that GSTP1 could contribute to paclitaxel resistance in EGF-stimulated CNE2 cells. Furthermore, an EGFR signaling network based on the identified EGFR-regulated phosphoproteins were constructed using Pathway Studio 5.0 software, which includes canonical and novel EGFR-regulated proteins and implicates the possible biological roles for those proteins.
The data not only can extend our knowledge of canonical EGFR signaling, but also will be useful to understand the molecular mechanisms of EGFR in NPC pathogenesis and search therapeutic targets for NPC.
- Epidermal Growth Factor Receptor
- Epidermal Growth Factor Receptor Signaling
- CNE2 Cell
- Human Protein Reference Database
- Epidermal Growth Factor Receptor Signaling Pathway
Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors in Southern China . Although NPC is a relatively radiosensitive disease, some of the NPC patients present local recurrences and distant metastases after radiotherapy due to radioresistance and the majority of these patients surrender recurrence and metastasis within 1.5 year after treatment . Hence, development of a specific targeted therapy for NPC is urgent for improving the patient survival and prognosis. Uncovering signaling pathway involved in NPC cancer biology will provide important information on targeted therapy for this disease.
Overexpression of epidermal growth factor receptor (EGFR) is common in NPC [3–5], and most NPC cell lines and about 85% of the Chinese patients with NPC have moderate to strong expression of EGFR [6, 7]. Moreover, overexpression of EGFR in primary tumors was associated with tumor metastasis, recurrence, and poor survival in patients with NPC [7, 8]. Recent data have proposed EGFR as a new target for NPC therapy [9, 10]. These studies suggest that EGFR plays a crucial role in the development and progression of NPC. EGFR is one of the most studied receptor tyrosine kinases. The natural ligands EGF and TGF-α bind to the extracellular domain of EGFR, and activate the receptor and its downstream signal proteins, ultimately causing activation or modulation of various cellular processes . About 200 targets of EGFR signaling pathway have been reported , and 177 molecules involved in EGFR signaling pathway are listed in the Human Protein Reference Database http://www.hprd.org, but the downstream signaling proteins of EGFR in NPC have not yet been completely understood at the system level.
Signaling transduction is regulated by the phosphorylation and dephosphorylation of proteins. Phosphoproteomics has an advantage for investigating cellular signaling pathways by simultaneously identifying a number of phosphoproteins at one experiment, but it also has a technical challenge because of the low abundance of phosphoproteins in cells. Therefore, enrichment of phosphoproteins is necessary before starting a phophoproteomic analysis to increase the sensitivity of identifying phosphoproteins. Two-dimensional difference gel electrophoresis (2D-DIGE) is a quantitative proteomics approach with great sensitivity and accuracy of quantitation compared to a conventional 2-DE. Using the 2D-DIGE, different samples prelabeled with mass- and charge-matched fluorescent cyanine dyes are co-separated in the same 2D gel, and an internal standard is used in every gel, overcoming the problem of intergel variation in classical 2-DE. Therefore, 2D-DIGE is able to efficiently provide accurate and reproducible differential expression values for proteins in two or more biological samples [13, 14].
To identify EGFR signaling proteins in NPC cells, in this study quantitative phosphoproteomics based on phosphate metal affinity chromatography-enriched phosphorproteins, 2D-DIGE and mass spectrometry analysis was applied to identify phosphoproteins after EGFR activation in NPC cells. We identified 33 EGFR-regulated phosphoproteins, and constructed an EGFR signaling network based on the identified phosphoproteins in NPC cells. The functional validation showed that GSTP1, one of the EGFR-regulated proteins, is involved in paclitaxel resistance in EGF-stimulated CNE2 cells. The data will provide insights into our understanding of EGFR signaling pathway and may have implications on target-directed therapeutics for NPC.
Cell culture and EGF treatment
NPC cell line CNE2 cells were cultured to 60-70% confluency in DMEM medium supplemented with 10% fetal bovine serum (Invitrogen) at 37°C, serum-starved for 24 h, and then were stimulated with 30 ng/mL EGF (Sigma) or mock-treated as a control. In EGFR blocking experiments, cells were pretreated with 1 μm EGFR tyrosine kinase inhibitor PD153035 (Calbiochem), and followed by incubation with EGF.
A phosphoprotein purification kit (BD Biosciences) was applied to enrich phosphoproteins from EGF-stimulated or unstimulated CNE2 cells according to the manufacturer's instructions. To validate the efficacy of phosphoprotein enrichment, 40 μg of proteins from total cellular lysate, elution fraction containing the highly-concentrated and purified phosphoproteins, and flow-through fraction were separated by 6% SDS-PAGE, followed by Western blotting using anti-phosphotyrosine antibody (4G10, Upstate). The concentration of the phosphoproteins was determined using a 2-D Quantification Kit (Amersham Biosciences).
Phosphoproteins from the elution fractions were precipitated using chloroform-methanol as described by Wessel and Flugge , resolubilized in 2D-DIGE sample buffer (30 mM Tris, 7 M urea, 2 M thiourea, 4% CHAPS, pH 8.5), and adjusted to pH 8.5. Equal amount phosphoproteins from six samples (three biological repeats) were pooled together as the internal standard. Three EGF-stimulated samples and three EGF-unstimulated samples were randomly labeled with Cy3 or Cy5, while internal standards were labeled with Cy2, using 200 pmol fluorochrome/25 μg protein (Amersham Biosciences). Labeling reactions were performed on ice in the dark for 30 min, and then quenched by the addition of 1 μL 10 mM lysine (Sigma) for 10 min.
Cy3- and Cy5-labelled samples (25 μg) from each pair of EGF-treated and untreated cells were combined before mixing with 25 μg Cy2-labelled internal standards. An equal volume of 2 × sample buffer (8 M urea, 130 mM DTT) was added to the sample and the total volume was made up to 450 μL with rehydration buffer (8 M urea, 4% CHAPS, 1% Biolyte, pH 4-7, 13 mM DTT). The samples were applied to IPG strips [pH 4-7; nonlinear (NL), 24 cm] and focused on an IPGphor (Amersham Biosciences). The focused IPG strips were equilibrated, and then were transferred to the tops of 12.5% polyacrylamide gels and run for about 7 h, using low-fluorescence glass plates on an Ettan DALT II system (Amersham Biosciences). All electrophoresis procedures were performed in the dark. The biological triplicate EGF-stimulated and unstimulated cells and the internal standard were run on three gels as analytic gels. In addition, we performed another strip in parallel as a preparative gel for spot pickings, as described above, except that the IPG strip was loaded with 1000 μg proteins and the gel was stained with Coomassie brilliant blue. After SDS-PAGE, the three analytic gels were scanned on a Typhoon 9410 scanner (GE Healthcare) at appropriate excitation/emission wavelengths specific for Cy2 (488/520 nm), Cy3 (532/580 nm) and Cy5 (633/670 nm), to generate nine protein spot maps.
Images were cropped using ImageQuant TL 2005 software (GE Healthcare) from 2D-DIGE gels, and analyzed using DeCyder 6.5 software (GE Healthcare) according to the manufacturer's recommendations. The DeCyder differential in-gel analysis (DIA) module was used for pairwise comparisons of each EGF-stimulated and unstimulated cell sample to the internal standard in each gel. The DeCyder biological variation analysis (BVA) module was then used to simultaneously match all nine protein-spot maps and, using the Cy3: Cy2 and Cy5: Cy2 DIA ratios, to calculate average abundance changes and paired Student's t -test p values for the variance of these ratios for each protein pair across all samples. The differential protein spots (ratio ≥ 1 .5, p ≤ 0 .05) that altered consistently in all nine protein-spot maps were selected for identification.
Protein identification by MS
All the differential phosphoprotein spots were excised from stained preparative gels using punch, destained, and in-gel trypsin digestion was performed as previously described by us . Briefly, the gel spots were destained with 100 mM NH4HCO3 in 50% acetonitrile, dried in a vacuum centrifuge, and incubated in the digestion solution (40 mM NH4HCO3, 9% acetonitrile, and 20 μg/mL proteomics grade trypsin) at 37°C for 14-16 h. The resulted peptides were extracted with 50% acetonitrile/2.5% TFA, purified with ZipTip C18 column (Millipore) and mixed with CCA matrix solution[4-hydroxy-α-cyanocinnamic acid (HCCA; Sigma) in 30% ACN/0.1% TFA] followed by analysis with Voyager System DE-STR 4307 MALDI-TOF Mass Spectrometer (ABI) to obtain the peptide mass fingerprint (PMF). The standard peptide mixture was analyzed at the same time to correct the machine. The parameters of MALDI-TOF were set up as follows: positive ionreflector mode, accelerating voltage 20 kV, grid voltage 64.5%, mirror voltage ratio 1.12, N2 laser wavelength 337 nm, pulse width 3 ns, the number of laser shots 50, acquisition mass range 500-3000 Da, delay 100 ns, and vacuum degree 4 × 10-7 Torr.
In peptide mass fingerprint map database searching, Mascot Distiller was used to obtain the monoisotopic peak list from the raw mass spectrometry files. Peptide matching and protein searches against the Swiss-Prot database were performed using the Mascot search engine http://www.matrixscience.com/ with a mass tolerance of ± 50 p.p.m. Protein scores of ≥ 56 (threshold) indicate identity or extensive homology (P < 0.05) and were considered significant.
To do phosphorylation site prediction of the identified proteins, we used on-line PhosphoSitePlus™ system biology resource http://www.phosphosite.org/ and the Phospho.ELM database http://phospho.elm.eu.org/index.html for predicting the presence of the phosphorylation modification sites , and PubMed database searching http://www.ncbi.nlm.nih.gov for comparing with the phosphorylated proteins reported in the literature. In addition, KEGG pathway analysis of the identified proteins was done in DAVID bioinformatics resources [18, 19].
Validation of EGFR signaling phosphoproteins by IP-Western blotting
Cells were lysed in the lysis buffer containing 150 mM NaCl, 50 mM Tris-HCl (pH 7.4), 1 mM EDTA, 1% Ttiton X-100, 1% NP-40 supplemented with phosphatase inhibitor cocktail 1 and 2 (Sigma-Aldrich) at 4°C, and subsequently centrifuged at 12000 g for 30 min at 4°C. Total cellular proteins were immunoprecipitated with protein G Sepharose (Amersham Biosciences), and anti-target protein antibody overnight at 4°C. Immunocomplexes were used for Western blotting. Briefly, proteins were separated by 7% SDS-PAGE, and transferred to a PVDF membrane. Blots were blocked with 3% BSA for 1 h at room temperature, and then incubated with primary antibody, followed by incubation with HRP-conjugated secondary antibodies for 1 h at room temperature. The signal was visualized using ECL detection reagent.
The cells were transfected with GSTP1 siRNA or control siRNA (Santa Cruz Biotechnology) according to the siRNA transfection protocol provided by the manufacturer. Briefly, the day before transfection, CNE2 cells were plated into 6-well plates at the density of 105 cells/mL in DMEM medium containing 10% FBS (Invitrogen). When the cells were 60-80% confluent, they were transfected with 10 nmol/L of GSTP1 siRNA or control siRNA in serum-free DMEM medium using Lipofectamine 2000 reagent (Invitrogen). 4 h after the beginning of the transfection, the medium was replaced with DMEM medium containing 10% FCS, and continued to culture the cells for additional 44 h, and then GSTP1 expression level was determined by Western blotting.
Flow cytometry analysis of apoptotic cells after treatment of paclitaxel and EGF
At the end of the transfection, the cells were incubated with 30 nM paclitaxel and 30 ng/mL EGF for 48 h, and cell apoptosis was examined by flow cytometry as previously described by us . Briefly, cells were harvested, fixed with ice-cold 70% ethanol in PBS at -20°C for 1 h and then centrifuged at 1 500 rpm for 5 min. The pellets were incubated with 0.5% Triton X-100 (Sigma) and 0.05% RNase (Sigma) in 1 mL PBS at 37°C for 30 min, and then centrifuged at 1 500 rpm for 5 min. The cell pellets were incubated with 40 μg/mL propidium iodide (Sigma) in 1 mL PBS at room temperature for 30 min. Samples were immediately analyzed by a FACScan flow cytometry (Becton Dickinson). Apoptosis was evaluated based on the proportion of sub-G1 hypodiploid cells. Three independent experiments were done.
Analysis of cell viability by MTT after treatment of paclitaxel and EGF
At the end of the transfection, the cells were incubated with the different concentrations of paclitaxel and 30 ng/mL EGF for 48 h, and cell viability was examined using MTT assay as previously described by us . Briefly, 20 μl of 5 mg/mL MTT (Sigma) was added to each well, and the medium was removed after 4 h of incubation. 150 μL DMSO (Sigma) was added to each well for 10 min at room temperature. The absorbance of each well was read with a Bio-Tek Instruments EL310 Microplate Autoreader at 490 nm. Three independent experiments were done.
To construct EGFR signaling network (biological interaction network of the proteins) of identified phosphoproteins, functional and pathway analyses were performed using Pathway Studio 5.0 software, a tool for the description of networks and signaling pathways .
Enrichment of phosphoproteins in EGF-stimulated and unstimulated NPC cells
Identification of differential phosphoproteins in EGF-stimulated and unstimulated NPC cells by 2D-DIGE and MS
Identification of differential phosphoproteins in EGF-stimulated and unstimulated NPC CNE2 cells by 2-D DIGE and MS
Translation endoplasmic reticulam ATPase (TERA)
Heat shock cognate 71kDa protein
Keratin,type ‖ cytoskeletal 8
BAG family molecular chaperone regulator 5
Heterogeneous nuclear ribonucleoprotein K
60KD Heat shock protein
Keratin,type ‖ cytoskeletal 8
Proliferating cell nuclear antigen
F-actin-capping protein subunit beta
laminin receptor 1
Creatine kinase B-type
Heterogeneous nuclear ribonucleoproteins C1/C2
ATP synthase D chain mitochondrial
Elongation factor 1- delta
Glutathione S-transferase P1
Ran-specific GTPase- activating protein
Myosin light polypeptide 6
Nucleoside diphosphate kinase A (NDKA)
Heat shock protein beta-1
Growth factor receptor-bound protein 2
Glutathione S-transferase P1
3-Hydroxyisobutyrate dehydrogenase mitochondrial
Bioinformatics analysis of the identified proteins
Phosphorylation modification sites of 33 identified proteins were analyzed with two online resources (PhosphoSitePlusTM system biology resource, and the Phospho.ELM database) to confirm the identified proteins being phosphoproteins. The results showed that 32 of 33 identified proteins contain phosphorylation modification sites except BAG5 (Table 1). In addition, KEGG pathway analysis showed that 17 identified proteins (HSP7C, KRT8, TUBB, VIM, HSP60, PCNA, RSSA, CKB, ATP5H, STMN1, GSTP1, KRT18, NME1, HSP27, GRB2, PARK7, and 3HIDH) are signaling proteins involved in MAPK, JAK/STAT and VEGF pathways, etc.. Taken together, these results support that the proteins identified by phophoproteomics are phosphoproteins.
Validation of identified phosphoproteins
Interaction of identified proteins with phospho-EGFR
IP-Western blotting were performed detect whether activated (phosphorylated) EGFR interacted with the two identified phosphoproteins (GSTP1 and GRB2) in CNE2 cells. As shown in Figure 3B, GSTP1 and GRB2 could be detected in the immunoprecipitation complex of phospho-EGFR antibody in 30 ng/mL EGF-stimulated CNE2 cells, and could not be detected by the pretreatment of the cells with 1 μm EGFR inhibitor PD153035, which indicates that GSTP1 and GRB2 can interact with phospho-EGFR, are downstream targets of EGFR signaling pathway.
Association of EGFR-regulated GSTP1 with chemoresistance
Construction of EGFR signaling network in NPC cells
EGFR play an important role in development, progression and therapeutic resistance of NPC [6–8], but the role and mechanisms of EGFR in the NPC are not fully understood. Activation of EGFR initiates important cell signaling cascades such as PI3K/AKT/mTOR, JAK/STAT, and Ras/Raf/MAPK pathways . About 200 targets of EGFR signaling pathway have been reported , and 177 molecules involved in EGFR signaling pathway are listed in the Human Protein Reference Database http://www.hprd.org, but EGFR signaling pathway in NPC still needs to be elucidated.
In the present study, we used quantitative phosphoproteomics to identify EGFR-regulated phosphoproteins to elucidate EGFR signaling pathway in NPC cells at the system level. 33 proteins were identified in enriched phosphoproteins from EGFR-activated NPC CNE2 cells, and three phosphoproteins were validated by IP-Western blotting. Among the identified proteins, five are known EGFR signaling proteins and twenty-eight are novel EGFR signaling proteins. To confirm the phosphoproteins identified by phosphoproteomics, online bioinformatics resources were used to predict phosphorylation sites of 33 identified proteins. The results showed that 32 proteins contain phosphorylation modification sites. KEGG pathway analysis also showed that 17 identified proteins are signaling proteins. Taken together, these results support that the proteins identified by phosphoproteomics are phosphoproteins. Interestingly, our result showed that two identified proteins (GSTP1 and GRB2) could interact with phospho-EGFR in EGF-stimulated CNE2 cells, further supporting that the identified phosphoproteins are EGFR signaling proteins.
To uncover the biological context of EGFR signaling proteins, we constructed a biological interaction network of the identified phosphoproteins, which has biological significance beyond static phosphoproteome data. Interestingly, 28 of 33 identified phosphoproteins could be networked. This strongly suggests that the majority of the phophoproteins identified in this study were integral part of the dynamic complex of EGFR signaling. The proteins that could be networked were linked by various relationships such as protein binding, protein interactions, modifications including phosphorylation, and expression regulation. This biological interaction network will be useful for formulating testable hypotheses to understand the function of novel phosphorylated targets of EGFR signaling pathway in NPC cells.
GSTP1, a major drug-metabolizing and stress response signaling protein, belongs to GST family member . Overexpression of GSTP1 has been reported in various types of human tumors, including colon cancer , gastric cancer , esophageal cancer , and head and neck squamous carcinoma , and enhances human cancer cell chemoresistance [23, 28]. Chen reported that 58% (83/143) primary NPC, 69.8% (30/43) recurrent NPC, and 65% (13/20) metastatic NPC tissues highly expressed GSTP1 . Jayasurya reported that all 55 NPC tissues showed positive GSTP1 immunoreactivity, and a significant correlation was found between GSTP1 expression and regional nodal metastasis of NPC . In tumors with EGFR aberrant activation, GSTP1 was phosphorylated and activated, leading to drug inactivation and drug resistance . Our results showed that activation of EGFR induced GSTP1 phosphorylation and interaction with EGFR, and GSTP1 is an important downstream target of EGFR signaling network in NPC cells. Overexpression of EGFR is frequent in NPC cell lines and tissues [6, 7], and is associated with chemoresistance . To explore the effect of EGFR-regulated GSTP1 in EGFR-induced chemoresistance in NPC cells, we evaluated the effects of GSTP1 knockdown on the paclitaxel sensitivity in EGF-stimulated CNE2 cells, and found that knockdown of GSTP1 expression by siRNA could increase EGF-stimulated CNE2 cells to paclitaxel sensitivity. It was obvious that GSTP1 is involved in EGFR-mediated chemoresistance in NPC cells. Our findings suggest that in NPC therapy, the double targeting of EGFR and GSTP1 could, potentially, be more effective than the current strategy of targeting either protein individually.
In this study, we identified 33 EGFR signaling proteins using quantitative phosphoproteomics, constructed an EGFR signaling network based the identified phosphoproteins in NPC cells, and validated that GSTP1, one of the EGFR-regulated proteins, is involved in chemoresistance in NPC cells. The data not only can extend our knowledge of canonical EGFR signaling, but also will be useful to understand the molecular mechanisms of EGFR in NPC pathogenesis and search therapeutic targets for NPC.
This work was supported by National Nature Science Foundation of China (30973290), Outstanding Scholars of New Era from Ministry of Education of China (2002-48), Lotus Scholars Program of Hunan Province, China (2007-362), Key research program from Science and Technology Committee of Hunan Province, China (2010FJ2009), Aid program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan Province, China, a project from Natural Science Foundation of Hunan Province, China(10JJ3045), and Scientific Research Fund from Higher Educational Institutions of Hunan Province, China(08C566).
- Ho JH: An epidemiologic and clinical study of nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 1978, 4: 182–198.PubMedView ArticleGoogle Scholar
- Lee AW, Poon YF, Foo W, Law SC, Cheung FK, Chan DK, Tung SY, Thaw M, Ho JH: etrospective analysis of 5037 patients with nasopharyngeal carcinoma treated during 1976–1985: overall survival and patterns of failure. Int J Radiat Oncol Biol Phys 1992, 23: 261–270. 10.1016/0360-3016(92)90740-9PubMedView ArticleGoogle Scholar
- Leong JL, Loh KS, Putti TC, Goh BC, Tan LK: Epidermal growth factor receptor in undifferentiated carcinoma of the nasopharynx. Laryngoscope 2004, 114: 153–157. 10.1097/00005537-200401000-00029PubMedView ArticleGoogle Scholar
- Zheng X, Hu L, Chen F, Christensson B: Expression of Ki67 antigen, epidermal growth factor receptor and Epstein-Barr virus-encoded latent membrane protein (LMP1) in nasopharyngeal carcinoma. Eur J Cancer 1994, (30B):290–295.Google Scholar
- Roychowdhury DF, Tseng A Jr, Fu KK, Weinburg V, Weidner N: New prognostic factors in nasopharyngeal carcinoma. Tumor angiogenesis and C-erbB2 expression. Cancer 1996, 77: 1419–1426. 10.1002/(SICI)1097-0142(19960415)77:8<1419::AID-CNCR1>3.0.CO;2-7PubMedView ArticleGoogle Scholar
- Ma BB, Lui VW, Poon FF, Wong SC, To KF, Wong E, Chen H, Lo KW, Tao Q, Chan AT, Ng MH, Cheng SH: Preclinical activity of gefitinib in non-keratinizing nasopharyngeal carcinoma cell lines and biomarkers of response. Invest New Drugs 2010, 28: 326–333. 10.1007/s10637-009-9316-7PubMed CentralPubMedView ArticleGoogle Scholar
- Ma BB, Poon TC, To KF, Zee B, Mo FK, Chan CM, Ho S, Teo PM, Johnson PJ, Chan AT: Prognostic significance of tumor angiogenesis, Ki 67, p53 oncoprotein, epidermal growth factor receptor and HER2 receptor protein expression in undifferentiated nasopharyngeal carcinoma - a prospective study. Head Neck 2003, 25: 864–872. 10.1002/hed.10307PubMedView ArticleGoogle Scholar
- Pan J, Kong L, Lin S, Chen G, Chen Q, Lu JJ: The clinical significance of coexpression of cyclooxygenases-2, vascular endothelial growth factors, and epidermal growth factor receptor in nasopharyngeal carcinoma. Laryngoscope 2008, 118: 1970–1975. 10.1097/MLG.0b013e3181805134PubMedView ArticleGoogle Scholar
- Sung FL, Poon TC, Hui EP, Ma BB, Liong E, To KF, Huang DP, Chan AT: Antitumor effect and enhancement of cytotoxic drug activity by cetuximab in nasopharyngeal carcinoma cells. Vivo 2005, 19: 237–245.Google Scholar
- Xiao X, Wu J, Zhu X, Zhao P, Zhou J, Liu QQ, Zheng L, Zeng M, Liu R, Huang W: Induction of cell cycle arrest and apoptosis in human nasopharyngeal carcinoma cells by ZD6474, an inhibitor of VEGFR tyrosine kinase with additional activity against EGFR tyrosine kinase. Int J Cancer 2007, 121: 2095–2104. 10.1002/ijc.22955PubMedView ArticleGoogle Scholar
- Olayioye MA, Neve RM, Lane HA, Hynes NE: The ErbB signaling network: receptor heterodimerization in development and cancer. EMBO J 2000, 19: 3159–3167. 10.1093/emboj/19.13.3159PubMed CentralPubMedView ArticleGoogle Scholar
- Blagoev B, Ong SE, Kratchmarova I, Mann M: Temporal analysis of phosphotyrosine-dependent signaling networks by quantitative proteomics. Nat Biotechnol 2004, 22: 139–1345. 10.1038/nbt0204-139View ArticleGoogle Scholar
- Van den Bergh G, Arckens L: Fluorescent two-dimensional difference gel electrophoresis unveils the potential of gel-based proteomics. Curr Opin Biotechnol 2004, 15: 38–43. 10.1016/j.copbio.2003.12.001PubMedView ArticleGoogle Scholar
- Friedman DB, Hill S, Keller JW, Merchant NB, Levy SE, Coffey RJ, Caprioli RM: Proteome analysis of human colon cancer by two-dimensional difference gel electrophoresis and mass spectrometry. Proteomics 2004, 4: 793–811. 10.1002/pmic.200300635PubMedView ArticleGoogle Scholar
- Wessel D, Flugge UI: A method for the quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal Biochem 1984, (138):141–143.PubMedView ArticleGoogle Scholar
- Chen Y, Ouyang GL, Yi H, Li MY, Zhang PF, Li C, Li JL, Chen ZC, Xiao ZQ: Identification of RKIP as an invasion suppressor protein in nasopharyngeal carcinoma by proteomic analysis. J Proteome Res 2008, 7: 5254–5262. 10.1021/pr800602cPubMedView ArticleGoogle Scholar
- Diella F, Gould CM, Chica C, Via A, Gibson TJ: Phospho.ELM: a database of phosphorylation sites--update 2008. Nucleic Acids Res 2008, 36: D240–244.PubMed CentralPubMedView ArticleGoogle Scholar
- Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA: DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003, 4: P3. 10.1186/gb-2003-4-5-p3PubMedView ArticleGoogle Scholar
- Huang DW, Sherman BT, Lempicki RA: Systematic and integrative analysis of large gene lists using DAVID Bioinformatics Resources. Nature Proto 2009, 4: 44–57.View ArticleGoogle Scholar
- Yang Y, Xiao Z, Chen Z, Zhang G, Yi H, Zhang P, Li J, Zhu G: Proteome analysis of multidrug resistance in vincristine-resistant human gastric cancer cell line SGC7901/VCR. Proteomics 2006, 6: 2009–2021. 10.1002/pmic.200402031PubMedView ArticleGoogle Scholar
- Nikitin A, Egorov S, Daraselia N, Mazo I: Pathway studio-the analysis and navigation of molecular networks. Bioinformatics 2003, 19: 2155–2157. 10.1093/bioinformatics/btg290PubMedView ArticleGoogle Scholar
- Prenzel N, Fischer OM, Streit S, Hart S, Ullrich A: The epidermal growth factor receptor family as a central element for cellular signal transduction and diversification. Endocr Relat Cancer 2001, 8: 11–31. 10.1677/erc.0.0080011PubMedView ArticleGoogle Scholar
- Hayes JD, Pulford DJ: The glutathione S-transferase supergene family: regulation of GST and the contribution of the isoenzymes to cancer chemoprotection and drug resistance. Crit Rev Biochem Mol Biol 1995, 30: 445–600. 10.3109/10409239509083491PubMedView ArticleGoogle Scholar
- Mulder TP, Verspaget HW, Sier CF, Roelofs HM, Ganesh S, Griffioen G, Peters WH: Glutathione S-transferase pi in colorectal tumors is predictive for overall survival. Cancer Res 1995, 55: 2696–2702.PubMedGoogle Scholar
- Peters WH, Wormskamp NG, Thies E: Expression of glutathione S-transferases in normal gastric mucosa and in gastric tumors. Carcinogenesis 1990, 11: 1593–1596. 10.1093/carcin/11.9.1593PubMedView ArticleGoogle Scholar
- Ishioka C, Kanamaru R, Shibata H, Konishi Y, Ishikawa A, Wakui A, Sato T, Nishihira T: Expression of glutathione S-transferase-pi messenger RNA in human esophageal cancers. Cancer 1991, 67: 2560–2564. 10.1002/1097-0142(19910515)67:10<2560::AID-CNCR2820671028>3.0.CO;2-MPubMedView ArticleGoogle Scholar
- Wang X, Pavelic ZP, Li Y, Gleich L, Gartside PS, Pavelic L, Gluckman JL, Stambrook PJ: Overexpression and amplification of glutathione S-transferase pi gene in head and neck squamous cell carcinomas. Clin Cancer Res 1997, 3: 111–114.PubMedGoogle Scholar
- Goto S, Iida T, Cho S, Oka M, Kohno S, Kondo T: Overexpression of glutathione S-transferase pi enhances the adduct formation of cisplatin with glutathione in human cancer cells. Free Radic Res 1999, 31: 549–558. 10.1080/10715769900301121PubMedView ArticleGoogle Scholar
- Chen CL, Sheen TS, Lou IU, Huang AC: Expression of multidrug resistance 1 and glutathione-S-transferase-Pi protein in nasopharyngeal carcinoma. Hum Pathol 2001, 32: 1240–1244. 10.1053/hupa.2001.28950PubMedView ArticleGoogle Scholar
- Jayasurya A, Yap WM, Tan NG, Tan BK, Bay BH: Glutathione S-transferase pi expression in nasopharyngeal cancer. Arch Otolaryngol Head Neck Surg 2002, 128: 1396–1399.PubMedView ArticleGoogle Scholar
- Okamura T, Singh S, Buolamwini J, Haystead T, Friedman H, Bigner D, Ali-Osman F: Tyrosine phosphorylation of the human glutathione S-transferase P1 by epidermal growth factor receptor. J Biol Chem 2009, 284: 16979–16989. 10.1074/jbc.M808153200PubMed CentralPubMedView ArticleGoogle Scholar
- Hsu CH, Gao M, Chen CL, Yeh PY, Cheng AL: Inhibitors of epidermoid growth factor receptor suppress cell growth and enhance chemosensitivity of nasopharyngeal cancer cells in vitro. Oncology 2005, 68: 538–547. 10.1159/000086998PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.