Differential Protein Expression Profiles of Gastric Epithelial Cells

H. pylori can cause gastric cancer, the second most prevalent cancer worldwide. To understand the role of gastric epithelial cells (GEC) in H. pylori ...
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Differential Protein Expression Profiles of Gastric Epithelial Cells Following Helicobacter pylori Infection Using ProteinChips Soumita Das,† Johanna C. Sierra,† Kizhake V. Soman,§ Giovanni Suarez,† Amin A. Mohammad,| Tu Anh T. Dang,⊥ Bruce A. Luxon,§ and Victor E. Reyes*,†, ‡ Department of Pediatrics, Department of Microbiology and Immunology, Bioinformatics Program, and Department of Human Biological Chemistry and Genetics; Department of Pathology, University of Texas Medical Branch, Galveston, Texas 77555, and Ciphergen Biosystems, Inc. 6611 Dumbarton Circle, Fremont, California 94555 Received February 8, 2005

Helicobacter pylori infects approximately half of the world’s population and the bacterium is associated with gastric cancer and peptic and duodenal ulcers. In this study, Surface Enhanced Laser Desorption /Ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was used to identify the biomarkers from H. pylori infected gastric epithelial cells (GEC) to understand key mechanisms associated with pathogenesis. Using different chip surfaces, differential protein expression profile of GEC was obtained and several upregulated or downregulated biomarkers were detected on GEC, following H. pylori infection. Four different H. pylori infected GECs were compared based on their expression of MHC class II, a receptor reported to trigger apoptosis. One biomarker was identified in H. pylori infected GEC as Annexin A2 (Annexin II) from the flow through of the anion-exchange resin. The increased expression of Annexin II in GEC following H. pylori infection was further confirmed by Western Blot analyses and indicates its involvement in H. pylori pathogenesis. Keywords: Helicobacter pylori • gastric epithelial cell • pathogenesis • surface enhanced laser desorption/ionization time off flight mass spectrometry (SELDI-TOF-MS) • ProteinChips • differential protein expression profile • biomarker • annexin II • gastric carcinoma

Introduction Helicobacter pylori is a Gram-negative bacterium infecting about half of the world’s population.1 It is linked with a diverse spectrum of gastrointestinal clinical disorders including peptic ulcer, gastric atrophy, gastric cancer, and mucosa-associated lymphoid tissue lymphoma in the stomach.2 The International Agency for Research on Cancer and the World Health Organization (IARC/WHO) concluded in 1994 that H. pylori has a causal linkage to gastric carcinogenesis and was therefore classified as a class I carcinogen in humans.3 The principal reservoir is the human stomach, and transmission probably occurs person-to-person passage via the oral-fecal route. The diversity in disease presentation is caused by variations in the interactions between H. pylori pathogenicity, host susceptibility, and other environmental factors.2 Comparative studies of the two fully sequenced H. pylori genomes are providing understanding of its large genetic diversity and bacterial * To whom correspondence should be addressed. Dr. Victor E. Reyes, Children’s Hospital, Room 2.300, University of Texas Medical Branch, 301 University Blvd. Galveston, TX 77555. Phone: (409) 772-3824. Fax: (409) 772-1761. E-mail address: [email protected]. † Department of Pediatrics. ‡ Department of Microbiology and Immunology. § Bioinformatics Program, and Department of Human Biological Chemistry and Genetics. | Department of Pathology, University of Texas Medical Branch. ⊥ Ciphergen Biosystems.

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Journal of Proteome Research 2005, 4, 920-930

Published on Web 05/19/2005

virulence factors. The discovery of the type IV secretion system cag pathogenicity island (PAI) in H. pylori and its role in translocation of the CagA protein from the bacterial cell into the host epithelial cell provided initial important insight into how host-bacterial interactions may lead to host disease.3 There are multiple other interactions between the bacteria and the host which are not yet characterized and whose consequences might be of central importance in the associated pathogenesis and chronicity of the infection. Understanding the mechanisms of interaction between this microorganism and its host, as well as the ensuing host responses, is essential to explain the diverse clinical manifestations. During H. pylori infection, gastric epithelial cells (GEC) play a major role due to their strategic location between luminal antigen and resident intraepithelial and lamina propria T cells. GEC may function as antigen presenting cells (APC) due to their constitutive expression of Major Histocompatibility Complex (MHC) class II molecules, antigen processing proteases and costimulatory molecules, which are increased during H. pylori infection.4-6 To eradicate H. pylori infection, it is important to understand the various pathways affected by the bacterium in epithelial cells in order to identify the critical steps leading to chronicity of infection and clinically significant disease. Recently, cDNA arrays were used to establish the global pattern of gene expression in gastric tissue of healthy subjects and of H. pylori infected patients.7 Some individual markers of im10.1021/pr050023i CCC: $30.25

 2005 American Chemical Society

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Protein Expression Profile of Gastric Epithelial Cells

munity in the H. pylori infected host have been identified by them, at the genetic level, but no study to date has exploited the global protein expression pattern from host cells using proteomics technology. Since proteins can exist in different posttranslational states (glycosylation, phosphorylation, ubiquitination) of functional consequence, gene and protein expression levels cannot easily be correlated. Proteomic analysis therefore provides a direct indication of the host response to infection at the protein level. The ProteinChip platform, based on surface enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry (TOF-MS)8 has recently been shown to be valuable in discovering new biomarkers and establishing differential protein profiles under different conditions.9,10 In SELDI, the approach of Retentate Chromatography Mass Spectrometry (RC-MS) is used in which proteins from biological samples are selectively retained on chromatographic surfaces and are analyzed directly by mass spectrometry for the purpose of performing differential protein display. This innovative technique has certain advantages over other methods such as two-dimensional gel electrophoresis (2-DE). SELDI has higher throughput capability, has subfemtomole range sensitivity, offers higher resolution at low mass ranges, and is easy to use. This technique is valuable for identifying novel biomarkers and for their validation.11 In addition, the knowledge of the surface property of the chip from which a peak was obtained can be helpful in the rapid purification and identification of that protein biomarker. In the present study, we hypothesize that gastric epithelial cells differentially express signaling molecules responsible for host responses following H. pylori infection. To test this hypothesis, we used SELDI-TOF-MS for the determination of differential protein expression profile of H. pylori infected GEC as compared to uninfected GEC. To the best of our knowledge, this is the first report that exploits SELDI to detect biomarkers from H. pylori infected gastric epithelial cells. In the studies reported herein, we applied SELDI-TOF-MS to examine the response of two GEC lines, N87 and AGS, to discover the biomarkers after infection and then we focused our efforts on the identification of one of the biomarkers as Annexin A2 (Annexin II) from the fractionated total cell lysates. We used the two cell lines since they differ in their expression of a receptor, class II MHC, used by H. pylori and that delivers intracellular signals leading to apoptosis.12 The differences that we observed between N87 and a variant of AGS were assumed to result from their differences in the expression of MHC Class II and the class II MHC associated invariant chain (Ii, CD74) which are expressed only on N87, but not on AGS cells. Invariant chain also has the ability to signal within cells that express it on the surface.13 The contribution of MHC class II in the observed responses was examined after transfecting AGS with the genes that code for MHC Class II alone (AGS DR) or the class II Transactivator CIITA (AGS CIITA),14 which led to their expression of class II MHC. One biomarker was identified as Annexin A2 (ANXA2 or Annexin II), the Ca2+ dependent protein of the annexin family that has a wide variety of activities in cells including cell proliferation, differentiation, cell-cell adhesion, and the pathogenesis of carcinoma.15 Annexin II has also been reported to be upregulated in gastric carcinoma.15 Thus, identification of Annexin II as a protein whose expression is increased in H. pylori infected GEC is of significance to the linkage of H. pylori infection and gastric carcinoma development.

Materials and Methods Cell Lines. The N87 and AGS gastric epithelial cells are of human gastric adenocarcinoma origin and were obtained from the American Type Culture Collection (ATCC, Rockville, MD). All cells were cultured in RPMI-1640 medium supplemented with 10% fetal calf serum (FCS), 1 mM glutamine, penicillin (1 U/mL) and streptomycin (100 µg/mL) in a humidified 37 °C, 5% CO2 incubator. AGS DR and AGS CIITA were grown in the same RPMI-1640 medium with respective antibiotic concentration of 50 µg/mL. Bacterial Cultures. LC-11 (Cag A+) H. pylori strain originally isolated from the antral mucosa of a patient with duodenal ulcer, as previously described,16 were grown on blood-agar plates (Becton Dickinson, Mountain View, CA) at 37 °C under microaerophilic conditions. After 48 h, LC-11 were grown in Brucella broth for 24 h. The bacteria were washed with normal saline and their concentration was measured by OD at the absorbance of 530 nm using a DU-65 spectrophotometer (Beckman Instruments, Inc., Fullerton, CA). The bacteria were adjusted to the required concentration by taking 2 × 108 bacteria/ml equivalent to 1 O. D. Antibody. For Annexin II Western Blot, mouse anti-human Annexin II antibody (BD Biosciences) and for the control R-tubulin, mouse anti-human R tubulin (Sigma) were used. Transfection of AGS. The AGS cell line was transfected to express DR using the retroviral vectors with the DRR chain of MHC Class II and DRβ (1*0401) chain of MHC Class II, which were kind gifts of Dr. Robert Hershberg (Corixa Corp., Seattle, WA) and have been previously described.17 The AGS cells were initially transfected with the DRR chain gene and were selected with hygromycin (200 µg/mL). Then, a second transfection was performed with the DRβ1*0401 gene and were selected with neomycin (200 ng/mL). The AGS transfected with CIITA were transfected using a pHA CIITA plasmid, which was a kind gift from Jeremy Boss (Emory University School of Medicine, Atlanta, GA). Briefly, AGS cells were transfected with the pHA CIITA plasmid (2 µg/mL) with Fugene6 (Roche) using manufacturer’s protocol. Infection of Gastric Epithelial Cells. In some cases, gastric epithelial cells were treated with IFN-γ (100 U/mL) for 48 h, washed to remove IFN-γ, and this was followed by incubation with regular medium for an additional day. The objective of the IFN-γ treatment was to induce a higher expression of class II MHC and the cells were rested for the additional 24 h to reduce any signaling processes initiated by the IFN-γ treatment. Once class II MHC molecules are expressed on the cell surface, their expression is stable for several days. Before infecting the GEC with H. pylori LC-11, GEC were washed, media was replaced with antibiotic-free media. The bacteria resuspended in RPMI media were used with a cell: bacteria ratio ) 1:100. Western Blot. Cell lysate proteins were separated by 12.5% SDS-PAGE, transferred to a nitrocellulose membrane (Bio-Rad) that was blocked in Tris-buffered saline with Tween (TBST) (20 mM Tris.HCl/500 mM NaCl, pH 7.5 with 0.1% (vol/vol) Tween 20) containing 5% dry milk for 1 h. The membranes were subsequently probed with the respective primary antibody in TBST containing 5% dry milk. For Annexin II and R tubulin, primary antibody was used in 1:5000 dilutions and incubated for 2 h. The membrane was washed with Tris-buffered saline with 0.1% (vol/vol) Tween 20. The binding of primary antibody was detected with horseradish peroxidase-conjugated donkey anti-mouse secondary antibody (BD Biosciences). SubseJournal of Proteome Research • Vol. 4, No. 3, 2005 921

research articles quently, membranes were washed and incubated in ECL reagent (Amersham Biosciences) and developed in KODAK XR film. Preparation of Total Cell Lysates. Two human gastric epithelial cell (GEC) lines, N87 and a variant of AGS, were thoroughly studied to get differential protein profiles before and after H. pylori infection. We used four different conditions; untreated GEC, GEC infected with H. pylori for 24 h, GEC treated with IFN-γ for 48 h, and 48 h IFN-γ pretreated cells infected with H. pylori for 24 h. For each condition, cells were washed with PBS, scraped with a cell scraper, centrifuged at 1700 rpm for 5 min. Whole cell lysates were prepared with cell lysis buffer (1% NP40, 9 M urea, 2% CHAPS (3-[(3-cholamidopropyl) dimethylammonio]-1-propanesulfonic acid), EDTA and protease inhibitor cocktail). Protein concentration was measured using BioRad DC protein assay kit. Sample concentration for each set of sample was adjusted to 5 mg/mL. Expression Difference Mapping (EDM) Analysis on ProteinChip Arrays. EDM analysis profiles of the samples were obtained by strong anion-exchange (SAX2), weak cation exchange (CM10), and hydrophobic (H50) ProteinChip Arrays (Ciphergen Biosystems, Fremont, CA). The ProteinChip Arrays were assembled into a deep-well type bioprocessor assembly (Ciphergen Biosystems). Prior to sample loading, H50, SAX2 and CM10 arrays were equilibrated with 150 µL of binding buffer (10% acetonitrile and 0.1% TFA for H50, 50 mM TrisHCl, pH 8.5, for SAX2 and 50 mM sodium acetate, pH 4.5 for CM10). After 5 min incubation for three consecutive times, 100 µL of total cell lysate (50 µg) diluted 1:9 in binding buffer was used for chip binding. Triplicate sets were performed for each condition. All arrays were incubated for 30 min on a shaker and washed three times with 150 µL of binding buffer. Last, after rinsing quickly with HPLC water, the arrays were removed from the Bioprocessor assembly and air-dried. 0.5 µL of saturated sinapinic acid (Ciphergen Biosystems) solution in 50% acetonitrile in water containing 0.5% trifluoroacetic acid was applied twice and they were allowed to air-dry. MS analysis was performed using a PBS-II mass reader (Ciphergen Biosystems). Spectra were collected with a laser intensity of 250 and a detector sensitivity of 10. Mass accuracy was calibrated externally using the All-in-1 peptide and All-in-1 Protein molecular mass standards (Ciphergen Biosystems). Fractionation of Total Cell Lysates. After recording the protein profiles with whole cell lysate from N87 cells, we fractionated N87 cells treated with IFN-γ and N87 cells treated with IFN-γ followed by exposure to H. pylori (IFN Hp). We used an anion exchange fractionation procedure where the negatively charged proteins bind to the resin and the unbound proteins are obtained as flow through. For the anion exchange fractionation, 60 µL of U9 buffer {9M Urea, 2% CHAPS and 50 mM Tris-HCl, (pH 9)} was added to 40 µL of total cell lysate in 1% NP40, 50 mM Tris and with a protease inhibitor cocktail. The sample was vortexed at 4 °C for 30 min. A 96-well microtiter plate containing Q HyperDF resin (BioSepra Corp., Fremont, CA) was equilibrated first by washing three times with 50 mM Tris-HCl pH 9 and then by washing three times with 200 µL of U1 buffer {1 M Urea, 0.22% CHAPS and 50 mM Tris-HCl (pH 9)} on a vacuum manifold (Beckman Coulter Inc., Fullerton, CA). 100 µL of U1 was added to each tube. From this mixture, 100 µL was added to the wells in duplicate. The plate was vortexed for 30 min at 4 °C to bind the protein with the anion-exchange resin. After binding, the unbound protein was collected in another 96-well microtiter plate as flow through 922

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by vacuum manifold. Two 100 µL washings were performed to get the pH fractions. Each time after adding 100 µL of wash buffer, the plate was vortexed for 10 min at room temperature and the eluted fraction was collected via vacuum manifold. The wash buffers for the different fractions were 50 mM Tris-HCl, 0.1% octyl glucopyranoside [OGP] (pH 9); 50 mM HEPES, 0.1% OGP (pH 7); 100 mM Na-Acetate, 0.1% OGP (pH 5); 100 mM Na-Acetate, 0.1% OGP (pH 4); 50 mM Na-Citrate, 0.1% OGP (pH 3); and 33.3% 2-propanol/16.7% acetonitrile/0.1% trifluoroacetic acid (Organic Fraction). Collected fractions were stored at -80 °C until final analysis. 10 µL from each fraction were spotted on CM10 chips in triplicate sets. The rest of the samples were loaded on SDS-PAGE. Data Analysis. The SELDI spectra were analyzed using ProteinChip software version 3.1 in combination with Biomarker Wizard (Ciphergen Biosystems, Fremont, CA). The first steps were importing the spectra into an in-silico “experiment”, and designating sample groups. The sample groups for each cell line are, untreated (un), H. pylori infected (Hp), IFN-γ treated (IFN), and IFN-γ pretreated and then infected with H. pylori (IFN Hp). This was followed by automatic peak detection, after which manually detected peaks were added. Noise and baseline subtraction are performed for all spectra automatically. All of the spectra in the experiment were then normalized by the “Total Ion Content” method, as recommended in the Ciphergen manual. Peaks with m/z < 2000 were excluded as the energy absorbing matrix signal generally interfered with peak detection in this region. The Biomarker Wizard (BMW) module was then run to identify “clusters” (sets) of peaks across spectra and across sample groups. Each cluster consists of peaks of similar mass from each spectrum, where present. For each cluster BMW runs the Kruskal-Wallis statistical test (the nonparametric equivalent of the analysis of variance) to calculate a p-value to assess the significance of expression differences among the sample groups. From the peak intensities averaged for each sample group, fold-changes in expression were calculated compared to the average intensity of the untreated cell samples as reference ((Hp)/(un)). An additional fold change of expression was calculated for the IFNtreated-H. pylori-infected case with the IFN-treated sample as reference ((IFN Hp)/(IFN)). Clusters with statistically significant expression differences (p e 0.05), containing peaks of signalto-noise ratio g 5, and having at least one of the fold changes g 2.0 are considered “biomarkers”, because their expression levels differentiate the sample groups (Biomarkers usually are proteins or peptides, but have to be validated and identified by other experiments, as described below). Protein Identification by Peptide Mapping and Database Search. For protein identification, fractionated samples were loaded on 15% SDS-PAGE. Differentially expressed gel bands were incubated with trypsin (20 µg/mL in 25mM ammonium bicarbonate, pH-8; Promega Corp.) at 37 °C for 4 h. MALDITOF-MS was performed using the Applied Biosystems instrument for peptide mass fingerprinting. Using the M/Z value of the tryptic fragments as input, we performed database search with the program ProFound running on our local computer. Details of the program are available at http://65.219.84.5/ service/prowl/profound.html and a web version at http:// 129.85.19.192/profound_bin/WebProFound.exe. ProFound is a tool for searching protein sequence databases using information from mass spectral fingerprints. It uses a Bayesian algorithm to rank the protein sequences in the database according to their probability of producing the peptide map.

Protein Expression Profile of Gastric Epithelial Cells

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Figure 1. Protein profiles of gastric epithelial cell lysates on three different types of ProteinChip Array surfaces. Total cell lysates of N87 IFN-γ treated and N87 H. pylori infected after IFN-γ pretreatment were analyzed on (A) SAX2, (B) CM10 and (C) H50 Chip surfaces under the conditions described in the Materials and Methods section. IFN-γ (100 U/mL) treatment was done for 48 h. Arrows indicate biomarkers. Two sets of each condition are shown to illustrate reproducibility.

The basic input is a list of peptide masses obtained from each biomarker. In addition, a number of other details can be specified, such as the database to search, expected protein mass and isoelectric point (pI), cleavage chemistry, potential posttranslational modifications, and the number of potentially missed enzymatic cleavages. The search output contains the ranked “hits” (candidate proteins) with their “coverages” and “expectation” (E) values, based on which the matches can be evaluated. The coverage is the ratio of the protein’s sequence length covered by the matched peptides. The E-value is the number of matches from the database that would be expected to have the same, or a better, score if the matches were completely random. Thus, the lower the E-value of a match, the higher the chances that it is a true match.

Results Expression Difference Mapping Analysis of GEC after H. pylori infection. Gastric epithelial cells play an important role during H. pylori infection, both as targets of the infection and contributors to the host response; however, the extent of their response is only partially characterized. To examine the extent of the response and gain an insight into the contribution of a previously described receptor, class II MHC, we evaluated proteome changes of gastric epithelial cells which differ in their expression of class II MHC prior to and after exposure to H. pylori. N87 are class II MHC+ and AGS are class II MHC negative. Also, to induce higher density of class II MHC on N87 cells, the cells were treated with IFN-γ. Profiles from lysates after the various treatments were obtained on SAX2 (strong anion exchange), CM10 (weak cation exchange) and H50 (reverse phase i.e., hydrophobic interaction) ProteinChip Arrays (Figure 1). Each type of array surface retains different groups of proteins depending on the array’s surface properties. Most of the peaks detected were in the range of 5000-40 000 Da M/Z (mass/charge). The analysis was carried out in triplicate sets. Cell lysates were examined at laser intensities of 190-250 several times, with the higher intensity of 250 being optimal for characterization of the total cell lysate (data not shown). Clearpeaks were obtained from 5000 to 30 000 m/z. Approximately 100 peaks were obtained in N87 datasets using CM10 chips (Figure 2). We discovered 15 biomarkers in the N87

total cell lysate with a statistically significant p e 0.05 and at least 2-fold changes in their level of expression. We ensured that each of the peaks at the specified condition where it is induced had a signal-to-noise ratio g 5.0. The fold change for each biomarker was calculated by dividing the average intensity at that condition compared to the control. We used untreated GEC (un) as a control to get the ratio from the GEC treated with H. pylori (Hp), IFN-γ (IFN), and IFN-γ plus H. pylori (IFN Hp). The cells treated with IFN-γ were allowed to rest for 24 h before they were exposed to the bacteria in order to reduce the signals induced by the IFN-γ treatment. Another set of fold changes was calculated with the ratio of cells treated with IFN-γ and H. pylori (IFN Hp) to those treated with IFN-γ alone (IFN). It is very clear from the spectra and table that the more differentially expressed biomarkers were obtained from IFN Hp samples compared to Hp samples. We selected those peaks as induced if the ratio was g 2.0, and repressed if the ratio was e 0.5. We found 9 peaks that are induced in IFN Hp samples when compared to untreated samples (GEC) as control, whereas only 3 peaks in Hp samples were induced compared to the same control (Table 1). This might reflect the effect of IFN-γ on the expression of receptors used by H. pylori, which in turn helps the interaction of H. pylori with GEC.12 The number of repressed peaks was 2 and 3 for Hp and IFN Hp, respectively, compared to the same control. Comparing GEC-IFN (IFN) with GEC (un), the effect of IFN-γ treatment on GEC is found to induce 3 and suppress 5 peaks. The peak at 7465 was absent in the untreated samples but appeared in Hp, IFN, and IFN Hp samples with a fold change of 7 in IFN Hp. When IFN Hp samples were compared with IFN, 8 induced peaks and only one repressed peak were observed. Four sets of N87 cells on CM10 chips are shown in trace view (Figure 2). The spectra are clearer in the “gel view” of the ProteinChip software with peak intensities converted to band intensities (Figure 2A,B). The profile obtained with AGS cells on CM10 chips is very interesting. It is known that IFN-γ treatment increases MHC Class II and invariant chain expression in GEC.12 AGS cells are devoid of these receptors, so we expect IFN-γ to have minimal effect on AGS cells with regards to class II MHC and Ii expression. The profile we obtained from AGS on CM10 chips Journal of Proteome Research • Vol. 4, No. 3, 2005 923

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Das et al. Table 1. Biomarkers Detected from Experiments on N87 Cells Using CM10 Chipsa m/z

Hp/unb

IFN/un

IFN Hp/IFN

IFN Hp/un

7190 7393 7465 7655 7768 8220 8931 8998 9133 10424 10543 11777 16176 24869 28993

0.837098 1.063706 nil 0.139349 1.629469 1.942614 2.597339 12.21136 5.620101 1.443716 0.238858 0.992222 1.275076 0.93584 1.455212

2.892845c 2.557678 nil 1.171933 0.332919 0.197839 1.71097 1.432144 0.804988 0.972338 0.617488 3.825866 0.319376 0.363633 0.388775

1.187987 1.182246 7.47143 0.041773 15.55021 15.65954 3.620172 14.35095 8.878787 3.232437 0.59109 0.669233 1.750424 1.156217 2.385283

3.436663 3.023806 nil 0.048955 5.176956 3.098074 6.194008 20.55262 7.147318 3.143021 0.364991 2.560397 0.559043 0.420439 0.927339

a Columns 2-5 give fold changes in expression compared to uninfected cells as reference. Biomarkers were selected by these criteria: signal to noise ratio of peaks g 5 and Statistical p-value among sample groups e 0.05. b Un: untreated N87, Hp: N87 cells infected with H. pylori for 24 h; IFN: N87 cells were treated with 100 U/mL IFN-γ for 48 h; IFN Hp: N87 cells infected with H. pylori for 24h after 48 h IFN-γ pretreatment. c Peaks induced in the particular condition are recorded in bold whereas repressed peaks are shown in italics.

Figure 2. Protein profiles of N87 on CM10 chip following H. pylori infection: A, m/z 6000-13 000; B, 13 000-26 000. Top panel in each figure is spectral view, and lower panel gel view. Asterisks (*) mark peaks that are prominent biomarkers in both views. One representative spectrum from triplicate sets is shown. The laser intensity setting for these spectra was 250 and detector sensitivity, 10. 924

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confirms this hypothesis, since the expression profiles of untreated and IFN-γ treated AGS cells are very similar (Figure 3). After H. pylori infection, 11 peaks were induced and 4 peaks were repressed, whereas H. pylori infection, after IFN-γ pretreatment produced 10 induced peaks and 3 repressed peaks (Table 2). The treatment with IFN-γ did not markedly affect the response to Hp since there were no marked differences in the number of biomarkers between IFN Hp and Hp samples in AGS cells, in contrast to what was observed with N87 cells. This observation suggests an important contribution by MHC Class II and Ii to protein expression profile in response to H. pylori. Transfection of AGS Cells with HLA-DR or the CIITA Transactivator that Induces the Expression of HLA-DR and the Associated Ii Protein Helps to Determine the Contribution of Each Receptor in GEC in Response to H. pylori. To specifically examine the contribution of class II MHC and Ii to the cell response to H. pylori, we used AGS cells that were transfected either with retroviral vectors containing DRR and DRβ chain of class II MHC (AGS DR), or with the class II transactivator (AGS CIITA), which induces the expression of both class II MHC and invariant chain (Ii). We compared the peaks between AGS DR and AGS CIITA against those in AGS and the N87 gastric epithelial cells in order to examine the peaks that represent proteins whose expression might be influenced by class II MHC and Ii. We used a margin of error of (20 Da. Though several peaks are common among all four cell lines (Table 3), five peaks (10184, 10882, 12323, 15982, 17948) showed the contribution of MHC Class II molecule since transfection of class II MHC in AGS (AGS DR) leads to peaks similar to those in N87. One peak at 8593 suggests the involvement of only Ii as it is induced in AGS CIITA and in N87, but not in AGS DR. We are unable to explain the origin of several other peaks at this point suggesting the involvement of other receptors or signaling molecules induced by the transfection of CIITA or due to other isoforms (HLA-DQ and HLA-DP) of class II MHC. Fractionation of GEC Lysates with Q Sepharose Containing Microtiter Plate. To increase the number of protein peaks visualized and spectral resolution, an anion exchange fraction-

Protein Expression Profile of Gastric Epithelial Cells

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Figure 3. Protein profiles of AGS cells on CM10 chips following H. pylori infection. One representative spectrum was selected from triplicate set of samples for each condition. For these spectra, laser intensity was 250 and sensitivity 10. The top panel in of the figure is spectral view and lower panel, gel view. Stars, arrows, circles, and ellipses mark prominent differential peaks. Table 2. Biomarkers Detected from Experiments on AGS Cells Using CM10 Chipsa m/z

Hp/unb

IFN/un

IFN Hp/IFN

IFN Hp/un

4482 7769 9005 9130 9188 9552 10128 10440 10987 11114 11699 13875 14476 17956 18473 19440 27806 31881 38591 44470

7.385886c

nil 0.447778 1.345294 1.034019 1.023418 1.037953 1.674126 1.618107 1.107699 1.327836 1.494884 0.93169 0.92045 0.836579 0.787809 0.100948 0.629145 0.675989 0.610166 1.338065

nil 22.91216 15.9751 9.904474 2.274521 0.620141 0.506178 1.615703 0.259875 0.404261 0.688497 5.419078 0.711219 0.535644 0.783886 123.5263 2.943391 8.122317 0.480726 5.517083

4.294149 10.25957 21.4912 10.24142 2.327786 0.643677 0.847406 2.61438 0.287864 0.536792 1.029224 5.048899 0.654641 0.448109 0.617553 12.46979 1.851821 5.4906 0.293323 7.382215

10.41447 27.82424 10.03233 2.42471 0.439834 0.639825 2.649635 0.296599 0.435092 0.62007 5.828754 0.708053 0.575811 0.66705 18.4938 2.104033 5.660239 0.250163 9.334408

a Columns 2-5 give fold changes in expression compared to uninfected cells as reference. Biomarkers were selected by these criteria: signal to noise ratio of peaks and statistical p-value among sample groups 0.05. b Un: untreated AGS, Hp: AGS cells infected with H. pylori for 24 h; IFN: AGS cells were treated with 100 U/mL IFN-γ for 48 h; IFN Hp: AGS cells infected with H. pylori for 24 h after 48 h IFN-γ pretreatment. c Peaks induced in the particular condition are given in bold whereas repressed peaks are shown in italics.

ation procedure was performed in which the cell lysates were separated into different fractions (flow through, pH 9, pH 7, pH 5, pH 4, pH 3, and organic wash) using Q Sepharose Hyper DF resin (BioSepra Corp. Fremont, CA) microtiter plate. This fractionation procedure significantly increases the number of peaks detectable from individual cell lysates.18 Each fraction was then applied to CM10 ProteinChip array surfaces in triplicate sets. We obtained several more biomarkers from flow through than from the other pH fractions (Figure 4). We observed four

peaks in total cell lysate that were also present in the different pH fractions; for example, 7768 and 8993 in flow through, 9133 in pH 4 fraction and 10424 in pH 7 fraction. The fractions also contained other new peaks not observed in total cell lysate. No strong peaks were observed in the pH 3 fractions. To validate these CM10 chip peaks by an independent technique, we separated the flow through and the different pH fractions using gels. We obtained 14 differentially expressed peaks in flow through, 1 in pH 9, 4 in pH 7, 6 in pH 5, 8 in pH 4, and 4 in organic fractions (Table 4). The flow through fraction in 15% SDS-PAGE shows two overexpressed bands in IFN Hp samples compared to IFN (Figure 5A). The band near 30 kDa (marked by an asterisk in Figure 5A) corresponds to peaks at 31862 Da from the N87IFN Hp flow through sample on CM10 chips (Figure 4B). We excised the band from the gel for protein identification. Identification of the Biomarker Candidate. The band near 30 kDa was digested with trypsin and the tryptic fragments were used for protein identification by mass spectrometry (matrixassisted laser desorption ionization spectroscopy or MALDI). The MALDI spectrum from the tryptic fragment is shown in Figure 5B. A search in the ProFound database revealed that the tryptic fragment had homology with human Annexin II (Table 5), with an expectation value 1.3 × 10-12 and a coverage of 42% of the sequence. In the ProFound search, we included microbial sequence databases with Homosapiens, to eliminate any H. pylori protein attached to gastric epithelial cells. Another protein in the gel, around 28 kDa (marked by an arrow in Figure 5A), did not show any homology to human proteins, but had homology with H. pylori cell binding factor 2 (gi15644804). This procedure permits the identification of the biomarkers from GECs after H. pylori infection, distinct from contaminating bacterial protein either due to invasion of H. pylori or due to strong attachment of H. pylori to GECs. To confirm the SELDI results showing Annexin II upregulation in GEC infected with H. pylori, we performed Western Blot analysis of IFN-γ pretreated GEC and infected with Journal of Proteome Research • Vol. 4, No. 3, 2005 925

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Table 3. Comparison of AGS, AGS DR, AGS CIITA, and N87 Biomarkers after IFN-γ Treatment and H. pylori Infection after IFN-γ Pretreatment (CM10 chips)a m/z

4480

AGS

AGS DR

AGS CIITA

N87

present only in hp no change

increase no change

increase

increase

increase increase increase

increase increase increase

decrease

decrease decrease

increase increase increase increase decrease decrease

increase increase increase decrease no change decrease

10316 10433 10548 10882

decrease increase no change decrease

decrease increase decrease no change

no change

11107 11700 12323

decrease no change decrease

increase decrease no change

decrease decrease no change

no change

15982

no change

increase

increase

increase

17948

no change

decrease

decrease

decrease

19414

increase

increase

increase

increase

8593 8995 9133 9181 9692 10129 10184

comments+

other

increase

decrease increase decrease no change decrease

Ii may be contributing commonb common common other other class II may be contributing other common other class II may be contributing other other class II may be contributing class II may be contributing class II may be contributing common

a

Fold change was calculated as the ratio of average intensity of IFN Hp to IFN samples. The peaks with induction ratio g2 or repression ratio e0.5 are in bold. “Increase” refers to fold change g1.5, and “decrease” to fold change e0.66. The m/z values in column 1 refers to the N87 result, unless the peak was absent in N87, in which case it refers to the AGS results. For comparison of the m/z between cell lines, a window size of (20 was used. b +”Common” ) the peak is present in all cell lines with similar average intensity ratio; “other” ) the peak is not due to the contribution of MHC Class II and Ii; “-“ ) peak absent in the cell line.

H. pylori for varying time points (Figure 6). After 2, 6, 16, and 24 h of H. pylori infection, Western Blot with anti-Annexin II antibody, showed the increased expression of Annexin II after 2h, and it was highest at 24 h (Figure 6). These data correlate with our results from SELDI analysis. In the case of AGS, the expression of Annexin II increased from 2 h, reached maximum at 16 h, and decreased at 24 h (Figure 6). With densitometric scan using R-tubulin as an internal control, we observed that Annexin II expression increased 2.5-fold after 24 h of H. pylori infection on N87 cells, compared to untreated N87 cells.

Discussion H. pylori is the major cause of gastric carcinogenesis and in this chronic infection, several signaling pathways on gastric epithelial cells are probably implicated in disease progression. The current knowledge regarding the epithelial response to the infection is based on numerous studies where individual pathways or proteins have been evaluated. In this study, SELDI-TOF-MS approach was used to determine the differential protein profiles of GEC following H. pylori infection as it is important for therapeutic strategies to identify the differentially expressed proteins from GEC. We have identified several biomarkers from the gastric epithelial cell lines AGS and N87 on CM10 chips after H. pylori infection, after IFN-γ treatment, (since IFN-γ is produced within the infected mucosa) and after IFN-γ pretreatment followed by H. pylori infection. The differences in the protein profiles between AGS and N87 cells were assumed to be due to the presence of MHC Class II and Ii on N87 cells but not on AGS cells. From previous studies, it was established that two major surface receptors MHC Class II and Ii play an important role in host epithelial cells and bacterial interaction.12,19,20 The contribution of these two receptors was evaluated after introducing the molecules 926

Journal of Proteome Research • Vol. 4, No. 3, 2005

in AGS cells by transfections, and comparing the four different cell lysates on CM10 chips. To develop specific therapeutics, it is important to identify the contributing factors for disease progression among a set of molecules. We fractionated the total cell lysates on anionexchange resins, profiled on the same CM10 chips with each pH fraction and loaded side by side on SDS-PAGE to identify the protein bands from the gels using MALDI-TOF-MS. The 31862 Da peak of H. pylori infected N87 cells in flow through on CM10 chips was detected as Annexin A2 (Annexin II) from the corresponding band in 15% SDS-PAGE. Although the results presented were obtained with N87 and AGS which are transformed cells, it was important to determine that Annexin II upregulation is not restricted to transformed cell lines. We examined the Annexin II expression in the nontransformed gastric epithelial cells HS738 which were shown to express Annexin II in response to H. pylori similarly to N87 and AGS cells (data not shown). This is the first report in our knowledge where SELDI-based technology was applied to study gastric epithelial cell responses to H. pylori infection for the purpose of identifying biomarkers. IFN-γ is perhaps the most potent stimulus for MHC class II expression on cells, including GECs.12 MHC class II molecules play a pivotal role in the induction and regulation of adaptive immune responses to pathogens. The N87 and the variant of AGS are different in the expression of MHC class II molecule and Ii. Thus, AGS was transfected with the DR R and β chains of MHC class II to obtain the AGS DR line but it does not express Ii. Therefore, AGS cells were transfected with the class II MHC transactivator using the pHA CIITA plasmid to get the AGS-CIITA cells. The class II transactivator (CIITA) has been referred to as the “master control factor” for the expression of MHC class II genes. In addition to genes encoding classical

Protein Expression Profile of Gastric Epithelial Cells

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Figure 4. Profiles of N87 on CM10 chips after fractionating on Q sepharose. (A & B) Flowthrough, (C) pH 9, (D) pH 7, (E) pH 5, (F) pH 4, and (G) organic. The fractions were loaded on CM10 chips and analyzed at laser intensity of 250 and sensitivity 10. One spectrum from triplicate set of samples is shown for each pH fraction. Stars to indicate the prominent biomarkers. Open star: the peak obtained in gel and identified later.

MHC II molecules (HLA-DR, -DP, and -DQ), CIITA activates the expression of several genes encoding the accessory proteins required for MHC restricted antigen presentation, namely the invariant chain (Ii), HLA-DM and HLA-DO.21 The last two are intracellular proteins and are unlikely to contribute in the response to extracellular H. pylori. CIITA also contributes, albeit to a lesser degree, to classical and non classical MHC I

expression.21 In one report, DNA microarray analysis was used to compare the expression profiles of the CIITA expressing B cell line Raji and its CIITA negative counterpart RJ2.2.5. CIITA regulated genes were found to have diverse functions which include antigen processing, intracellular signaling and proliferation.22 These effects of CIITA provide clues about the differences we observed between AGS CIITA and N87 (Table Journal of Proteome Research • Vol. 4, No. 3, 2005 927

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Table 4. Biomarkers from N87 IFN and N87 IFN Hp Samples after Fractionation on Anion Exchange Resin and Profiling on CM10 Chipsa fraction

flow through

pH 9 pH 7

pH 5

pH 4

organic fraction

m/z

fold change

5421 6479 7758 8466 8993 10419 10867 11085 11580 12318 18805 27777 31862 38858 9007 5382 6796 10433 11183 11216 13092 13560 16200 25873 44699 2184 6962 9136 10642 11837 13100 29043 44765 8512 10990 13232 44915

0.497 0.367 7.95 0.456 64.84 5.55 0.354 0.436 6.6 0.407 3.74 14.69 8.4 0.30 11.36 8.99 0.20 13.02 0.19 0.315 only in Hp 10.37 3.49 5.34 12.28 2.82 present only in IFN Hp 65.13 0.36 0.31 18.44 0.41 2.51 4.89 0.23 31.23 2.08

a Fold change is the ratio of the average intensity of each biomarker in IFN Hp sample to IFN sample. Only biomarkers with fold changes g 2 or e 0.5 are listed. The m/z values that are common between pH fractions and total cell lysate are bolded.

3). The peaks that cannot easily be explained due to contributions by either MHC class II or Ii might be due to other genes upregulated or down regulated by the CIITA introduced in AGS CIITA cells. The AGS DR cells express MHC class II of DR isoform but the AGS CIITA can express DR, DQ, and DP. Therefore, the results we obtained using the AGS-DR might be due to their expression of only the DR isoform of MHC class II. Further investigation is required to assess the contributions from the other isoforms of class II MHC, DQ, or DP. Annexin A2 or Annexin II is a member of the annexin family which contains more than 160 unique proteins found in more than 65 different species, ranging from fungi and protists to plants and higher vertebrates.23 Annexin II (ANXA2) belongs to a family of calcium-dependent, phospholipids-binding proteins, and its functions include the inhibition of phospholipase A2, membrane-cytoskeletal linkage, and the initiation of membrane fusion in exocytosis.24 In addition to these functions, it has been suggested that Annexin II is involved in cell proliferation/differentiation, cell-cell adhesion and the pathogenesis of carcinoma.14 Overexpression of Annexin II has been reported in brain, breast, lung, liver, pancreatic, hematologic, and colon malignant tumors. Among 153 upregulated genes in gastric carcinoma, Annexin II was also detected.14 It is more strongly expressed in the cell membrane than in the cytoplasm 928

Journal of Proteome Research • Vol. 4, No. 3, 2005

Figure 5. A, 1-D gel of the flow through fraction of N87 IFN and IFN Hp samples in 15% SDS-PAGE. The three bands are as follows: Molecular weight marker (M), 48 h IFN-γ treated N87 (1), and N87 pretreated with IFN-γ before infecting with H. pylori for 24 h (2). 1 & 2 both were obtained as flow through from anionexchange resin (Q ceramic Hyper DF). Arrow and asterisk indicate the band excised from the gel. B, shows MALDI spectra obtained after trypsin digestion (see text for details of protein identification).

of tumor cells in primary gastric carcinoma tissue. Annexin II is overexpressed in advanced gastric carcinomas and contributes to the progression of gastric carcinoma. Because of its functional importance, it is highly significant and important to study the expression level of Annexin II in GECs following H. pylori infection. We have confirmed the upregulation of Annexin II from SELDI approach by Western Blot of N87 and AGS cells after infection with H. pylori. Gastric malignancies have been closely linked to infection of the gastric mucosa with H. pylori,25 but the individual factors involved in the multistage process of tumor development are still poorly understood. H. pylori evades the host defense system and causes persistent infection and chronic inflammation. Immune activation leads to DNA damage by the release of oxygen and nitrogen radicals. Ongoing tissue repair mechanisms and the secretion of cytokines and growth factors, as well as bacterial effector molecules, cause disturbances in the balance between epithelial cell proliferation and apoptosis, promote the accumulation of potential oncogenic mutations, and support neovascularization and tumor growth. In addition, H. pylori might hamper the development of an efficient antitumor immunity and provoke immune-mediated pathol-

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Protein Expression Profile of Gastric Epithelial Cells Table 5. Results of Profound Database Search for Biomarker Candidate Identification

ranka

expectation

1

1.3 ×

2

0.89

10-12

protein identity

gi|18645167|gb|AAH23990.1| annexin A2 [Homo sapiens] gi|30158436|ref|XP_304576.1| hypothetical protein XP_304576 [Homo sapiens]

coverage (%)b

pI

molecular weight (kDa)

42

7.7

38.56

7

9.8

86.42

a The number of matches from the database that would be expected to have the same, or a better, score if the matches were completely random. b Percentage of the protein’s sequence length covered by the matched peptides.

c-myc and the H. pylori induced apoptosis in host epithelium by c-myc have pointed out that Annexin II can be an early marker for tumor progression. Abbreviations. GEC, gastric epithelial cell; APC, antigen presenting cell; MHC, major histocompatibility complex; SELDI, surface-enhanced laser desorption/ ionization; SELDI-TOFMS, surface-enhanced laser desorption/ ionization time-offlight mass spectrometry; RC-MS, retentate chromatography mass spectrometry; 2-DE, two-dimensional gel electrophoresis; TBST, tris buffered saline with Tween 20; IFN, Interferon-γ; Hp, H. pylori; CIITA, Class II Transactivator; m/z, mass/charge; SAX2, strong anion exchange resin; CM10, weak cation exchange; H50, hydrophobic; OGP, octyl gluco pyranoside; BMW, biomarker wizard.

Figure 6. A, Western Blot of Annexin II in N87 and AGS. Both the cell lines were infected with H. pylori LC-11 strain for the indicated time period, after 48 h of IFN-γ pretreatment and loaded in 12.5% SDS-PAGE. R tubulin was used as a loading control. B, Densitometric scan using BioRad’s quantity one software. The % adjacent volume was determined for each band of Annexin II and R tubulin, and plotted against timepoints.

ogy. To elucidate this phenomenon, it is relevant to identify Annexin II in H. pylori mediated gastric carcinoma. In a recent report, it was observed that Annexin II interacts with c-myc mRNA and results in the up-regulation of c-Myc protein.26 c-Myc is a multifunctional nuclear phosphoprotein that can promote cell cycle progression, apoptosis, and cellular transformation. c-Myc regulates these activities at the molecular level by functioning as a regulator of gene transcription, activating, or repressing specific target genes.26 Thus, binding of Annexin II to c-myc mRNA may have an important physiological role in the regulation of c-myc mRNA. Interestingly, c-myc is up-regulated in many forms of cancer including pancreatic carcinoma,27 acute promyelocytic leukemia,28 and glioma.29 Cell proliferation and apoptosis are essential events involved in the cellular turnover of epithelial tissue. In gastric epithelium, apoptosis plays an essential role in maintaining tissue integrity. Normally, the rate of cell loss by apoptosis is matched by the rate of new cell production by proliferation. It has been shown that H. pylori infection induces apoptosis in gastric epithelial cells and subsequently results in an increase in cell proliferation as a host response to apoptosis.30 H. pylori can induce apoptosis by altered expression of c-myc gene.30 We identified an important biomarker Annexin II from H. pylori infected GEC which is an important contributor of gastric carcinoma. Reports from other laboratories regarding the interaction of Annexin II with

Acknowledgment. We are thankful to Dr. Randall Goldblum for critically evaluating this manuscript and to Dr. Anthony Haag, Biomolecular resource facility core for all MALDI results. K.V.S. was supported by the Grant Nos. N01HV-28184 and 1U01-AI-054827. We also thank Monaliza S. Evangelista and Elizabeth C. Elefano for their assistance with some of the assays. This work was supported by the National Institutes of Health Grant Nos. DK50669 and DK56338. References (1) Marshall, B. J. Helicobacter pylori. Am. J. Gastroenterol. 1994, 89 (8 Suppl), S116-128. (2) Ernst, P. B.; Gold, B. D. The disease spectrum of Helicobacter pylori: the immunopathogenesis of gastroduodenal ulcer and gastric cancer. Annu. Rev. Microbiol. 2000, 54, 615-640. (3) IARC, in IARK Working Group on the evaluation of carcinogenic risks to humans. Lyon 1994, 61, 1-261. (4) Barrera, C.; Ye, G.; Espejo, R.; Gunasena, S.; Almanza, R.; Leary, J.; Crowe, S.; Ernst, P.; Reyes, V. E. Expression of cathepsins B, L, S, and D by gastric epithelial cells implicates them as antigen presenting cells in local immune responses. In Hum. Immunol. 2001, 62, 1081-1091. (5) Barrera, C.; Espejo, R.; Reyes, V. E. Differential glycosylation of MHC class II molecules on gastric epithelial cells: implications in local immune responses. Hum. Immunol. 2002, 63 (5), 384393. (6) Ye, G.; Barrera, C.; Fan, X.; Gourley, W. K.; Crowe, S. E.; Ernst, P. B.; Reyes, V. E. Expression of B7-1 and B7-2 costimulatory molecules by human gastric epithelial cells: potential role in CD4+ T-cell activation during Helicobacter pylori infection. J. Clin. Invest. 1997, 99 (7), 1628-1636. (7) Wen, S.; Felley, C. P.; Bouzourene, H.; Reimers, M.; Michetti, P.; Pan-Hammarstrom, Q. Inflammatory gene profiles in gastric mucosa during Helicobacter pylori infection in humans. J. Immunol. 2004, 172 (4), 2595-2606. (8) Chapman, K. The ProteinChip Biomarker System from Ciphergen Biosystems: a novel proteomics platform for rapid biomarker discovery and validation. Biochem. Soc. Trans. 2002, 30 (2), 8287. (9) Merchant, M.; Weinberger, S. R. Recent advancements in surfaceenhanced laser desorption/ionization-time-of-flight-mass spectrometry. Electrophoresis 2000, 21 (6), 1164-1177.

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research articles (10) Tang, N.; Tornatore, P.; Weinberger, S. R. Current developments in SELDI affinity technology. Mass Spectrom. Rev. 2004, 23 (1), 34-44. (11) Fung, E. T. Strategies in clinical proteomics: from discovery to assay. Preclinica 2004, 2, 253-258. (12) Fan, X.; Crowe, S. E.; Behar, S.; Gunasena, H.; Ye, G.; Haeberle, H.; Van Houten, N.; Gourley, W. K.; Ernst, P. B.; Reyes, V. E. The effect of class II major histocompatibility complex expression on adherence of Helicobacter pylori and induction of apoptosis in gastric epithelial cells: a mechanism for T helper cell type 1-mediated damage. J. Exp. Med. 1998, 187 (10), 1659-1669. (13) Leng, L.; Metz, C. N.; Fang, Y.; Xu, J.; Donnelly, S.; Baugh, J.; Delohery, T.; Chen, Y.; Mitchell, R. A.; Bucala, R. MIF signal transduction initiated by binding to CD74. J. Exp. Med. 2003, 197 (11), 1467-1476. (14) Harton, J. A.; Ting, J. P. Class II transactivator: mastering the art of major histocompatibility complex expression. Mol. Cell Biol. 2000, 20 (17), 6185-6194. (15) Emoto, K.; Sawada, H.; Yamada, Y.; Fujimoto, H.; Takahama, Y.; Ueno, M.; Takayama, T.; Uchida, H.; Kamada, K.; Naito, A.; Hirao, S.; Nakajima, Y. Annexin II overexpression is correlated with poor prognosis in human gastric carcinoma. Anticancer Res. 2001, 21 (2B), 1339-1345. (16) Crowe, S. E.; Alvarez, L.; Dytoc, M.; Hunt, R. H.; Muller, M.; Sherman, P.; Patel, J.; Jin, Y.; Ernst, P. B., Expression of interleukin 8 and CD54 by human gastric epithelium after Helicobacter pylori infection in vitro. Gastroenterology 1995, 108 (1), 65-74. (17) Hershberg, R. M.; Framson, P. E.; Cho, D. H.; Lee, L. Y.; Kovats, S.; Beitz, J.; Blum, J. S.; Nepom, G. T. Intestinal epithelial cells use two distinct pathways for HLA class II antigen processing. J. Clin. Invest. 1997, 100 (1), 204-215. (18) Fung, E. T.; Enderwick, C. ProteinChip clinical proteomics: computational challenges and solutions. Biotechniques 2002, Suppl. 34-8, 40-41. (19) Fan, X.; Gunasena, H.; Cheng, Z.; Espejo, R.; Crowe, S. E.; Ernst, P. B.; Reyes, V. E. Helicobacter pylori urease binds to class II MHC on gastric epithelial cells and induces their apoptosis. J. Immunol. 2000, 165 (4), 1918-24.

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Das et al. (20) Beswick E. J, B. D. A., Suarez, G, Barrera, C. A, Fan X, Reyes V. E, Helicobacter pylori binds to CD74 on gastric epithelial cells and stimulates interlukin-8 production. Infect. Immun. 2005, in press. (21) Leibund Gut-Landmann, S.; Waldburger, J. M.; Krawczyk, M.; Otten, L. A.; Suter, T.; Fontana, A.; Acha-Orbea, H.; Reith, W. Minireview: Specificity and expression of CIITA, the master regulator of MHC class II genes. Eur. J. Immunol. 2004, 34 (6), 1513-1525. (22) Nagarajan, U. M.; Bushey, A.; Boss, J. M., Modulation of gene expression by the MHC class II transactivator. J. Immunol. 2002, 169 (9), 5078-5088. (23) Gerke, V.; Moss, S. E. Annexins: from structure to function. Physiol. Rev. 2002, 82 (2), 331-371. (24) Gilmore, W. S.; Olwill, S.; McGlynn, H.; Alexander, H. D. Annexin A2 expression during cellular differentiation in myeloid cell lines. Biochem. Soc. Trans. 2004, 32 (Pt 6), 1122-1123. (25) Uemura, N.; Okamoto, S.; Yamamoto, S.; Matsumura, N.; Yamaguchi, S.; Yamakido, M.; Taniyama, K.; Sasaki, N.; Schlemper, R. J. Helicobacter pylori infection and the development of gastric cancer. N. Engl. J. Med. 2001, 345 (11), 784-789. (26) Filipenko, N. R.; MacLeod, T. J.; Yoon, C. S.; Waisman, D. M. Annexin A2 is a novel RNA-binding protein. J. Biol. Chem. 2004, 279 (10), 8723-8731. (27) Schleger, C.; Verbeke, C.; Hildenbrand, R.; Zentgraf, H.; Bleyl, U. c-MYC activation in primary and metastatic ductal adenocarcinoma of the pancreas: incidence, mechanisms, and clinical significance. Mod. Pathol. 2002, 15 (4), 462-469. (28) Lens, D.; Matutes, E.; Farahat, N.; Morilla, R.; Catovsky, D. Differential expression of c-myc protein in B and T lymphocytes. Leukemia 1994, 8 (12), 2102-2110. (29) Herms, J. W.; von Loewenich, F. D.; Behnke, J.; Markakis, E.; Kretzschmar, H. A. c-myc oncogene family expression in glioblastoma and survival. Surg. Neurol. 1999, 51 (5), 536-542. (30) Yang, Y.; Deng, C. S.; Peng, J. Z.; Wong, B. C.; Lam, S. K.; Xia, H. H. Effect of Helicobacter pylori on apoptosis and apoptosis related genes in gastric cancer cells. Mol. Pathol. 2003, 56 (1), 19-24.

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