Characterization of Pepsinogen C as a Potential Biomarker for Gastric

Aug 6, 2005 - Keywords: gastric cancer • proteomics • biomarker • ProteinChip technology • SELDI • microdissection • immunohistochemistry...
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Characterization of Pepsinogen C as a Potential Biomarker for Gastric Cancer Using a Histo-Proteomic Approach Christian Melle,† Gu1 nther Ernst,† Bettina Schimmel,† Annett Bleul,† Roland Kaufmann,‡ Merten Hommann,‡ Konrad K. Richter,‡ Wolfgang Daffner,‡ Utz Settmacher,‡ Uwe Claussen,† and Ferdinand von Eggeling*,† Core Unit Chip Application (CUCA), Institute of Human Genetics and Anthropology, Friedrich Schiller University, 07740 Jena, Germany, and University Hospital, Department of General and Visceral Surgery, Friedrich Schiller University, 07740 Jena, Germany Received April 29, 2005

We analyzed 74 cryostat sections of central gastric tumor, tumor margin, and normal gastric epithelium using ProteinChip Arrays and SELDI-TOF MS. One peak was significantly down-regulated in tumor tissue (P ) 1.43 × 10-6) and identified as pepsinogen C using MS/MS analysis and immunodepletion. This signal was further characterized by immunohistochemistry. This work demonstrates that differentially expressed signals can be identified and assessed using a proteomic approach comprising tissuemicrodissection, protein profiling, and immunohistochemistry. Keywords: gastric cancer • proteomics • biomarker • ProteinChip technology • SELDI • microdissection • immunohistochemistry

Introduction Gastric cancer is the second most common cancer-related cause of death in the world. This poor prognosis is primarily related to late diagnosis and therapeutic limitations. Chemotherapy and radiation have only a marginal success rate.1 It has been shown that several factors contribute to the cause of gastric cancer, including the living habits, nutrition, genetic predisposition, and bacterial infections, most predominantly by H. pylori.2-4 Cancer initiation and progression is a multistep process including several histopathological and genetic alterations and either activation of oncogenes as well as inactivation of tumor suppressor genes.5,6 Early identification and better control of risk factors may be the most effective means of prevention. The proteomic technique, SELDI-MS (surface-enhanced laser desorption/ionization-mass spectrometry), uses chromatographic surfaces able to retain proteins depending on their physicochemical properties followed by direct analysis via timeof-flight mass spectrometry (TOF-MS).7 This technique does not require large amounts of samples making it ideal for small biopsies or microdissected tissue which are required to produce the homogeneous tissue samples typically used in cancer research.8-10 We have previously shown that whole tumor biopsies as starting material are too heterogeneous for marker detection.11 Microdissected tissue material, free of contaminating and unwanted tissue components, is extremely important * To whom correspondence should be addressed. Tel: 0049(0)3641935526. Fax: 0049(0)3641-935518. E-mail: [email protected]. † Core Unit Chip Application (CUCA), Institute of Human Genetics and Anthropology, Friedrich Schiller University. ‡ University Hospital, Department of General and Visceral Surgery, Friedrich Schiller University. 10.1021/pr050123o CCC: $30.25

 2005 American Chemical Society

for producing clean data for biomarkers identification in cancer diagnostics and in elucidating clonal heterogeneity of tumors. In the case of gastric cancer, the epithelial tumor cells have to be separated from all surrounding tissue constituents. This separation can only be done with an extremely precise technique such as laser based microdissection. Laser-based microdissection has previously been combined with ProteinChip technology to identify protein markers in other cancers.10-13 In the present study, we analyzed pure microdissected populations of cells from normal gastric epithelium, the central area of the gastric tumor and the tumor margin using ProteinChip technology. One peak at 42.5 kDa showed decreased intensity in tumor cells as compared to normal epithelial cells. The 42.5 kDa peak was identified as pepsinogen C using 2D gel electophoresis and MS/MS analysis as well as by comparing the SELDI profiles of immunodepleted versus whole protein isolates from normal gastric epithelial cells. Pepsinogen C protein expression in sections of gastric biopsies was confirmed using immunohistochemistry. By combining microdissection with SELDI-TOF-MS and immunohistochemistry, it was possible to unequivocally identify pepsinogen C (pregastricsin) as being underexpressed in gastric tumor cells.

Materials and Methods Laser Microdissection of Tissue Sections. All 21 gastric central tumor samples (pT2/pT3) and matched normal gastric epithelium (n ) 35) as well as 18 gastric tumor margin samples were obtained after surgical resection at the Department of General and Visceral Surgery of the Friedrich Schiller University Jena; these were collected fresh, snap frozen in liquid nitrogen, and stored at -80 °C. Tumor specimens were categorized according to their WHO classification. Journal of Proteome Research 2005, 4, 1799-1804

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research articles Laser microdissection was performed with a laser microdissection and pressure catapulting microscope (LMPC; Palm, Bernried, Germany) as described elsewhere.12 Briefly, we microdissected on native air-dried cryostat tissue sections approximately 3000 to 5000 cells each in a maximum of 20-30 min. Proteins were extracted by 10 µL lysis buffer (100 mM Naphosphate (pH 7.5), 5 mM EDTA, 2 mM MgCl2, 3 mM 2-β-mercaptoethanol, 0.1% CHAPS, 500 µM leupeptin, and 0.1 mM PMSF) for 30 min on ice. After centrifugation (15 min; 15 000 rpm) the supernatant was immediately analyzed or frozen in liquid nitrogen for a maximum of 1 day. Profiling of Microdissected Normal Gastric Epithelium, Tumor Margin Tissue and Epithelial Central Tumor Tissue. The protein lysates from microdissected tissues (central tumor, tumor margin and normal) were analyzed on strong anion exchange arrays (Q10) (Ciphergen Biosystems Inc, Fremont, CA) as described elsewhere.12 In brief, array spots were preincubated by a washing/loading buffer containing 100 mM Trisbuffer, pH 8.5 with 0.02% Triton X-100 followed by application of 2 µL of sample extract on ProteinChip Arrays, which were incubated at room temperature for 90 min in a humidity chamber. After washing three times with the same buffer and two final washing steps with water, 2 × 0.5 µL sinapinic acid (saturated solution in 0.5% TFA/50% Acetonitrile) were applied. Mass analysis was performed in a ProteinChip Reader (series 4000, Ciphergen Biosystems Inc, Fremont, CA) according to an automated data collection protocol. Spectra were normalized with total ion current and cluster analysis of the detected signals and the determination of respective P-values for normal, central tumor and tumor margin tissue were carried out with the CiphergenExpress Program (Version 3.0; Ciphergen Biosystems Inc, Fremont CA). For P-value calculation, normalized spectra with signals in the range between 20 and 200 kDa exhibiting a signal-to-noise ratio (S/N) of at least 10 were selected and analyzed with the Mann-Whitney U test for nonparametric data sets. Two-Dimensional Gel Electrophoresis. Samples for twodimensional gel electrophoresis (2-DE) were prepared directly from surgical material of gastric tumor and corresponding normal gastric epithelium tissue assessed by a pathologist. Proteins were isolated and 2-DE was performed as described elsewhere.12 In brief, isoelectric focusing (IEF) was carried out on a Multiphor II (Amersham) using 7 cm IPG strips in a pI range of 3-10. Vertical SDS-PAGE was performed in a cooled PROTEAN II xi Cell (Bio-Rad) using 4-12% Bis-Tris Zoom gel (Invitrogen). The gels were stained with Simply Blue Safe Stain (Enhanced Coomassie, Invitrogen). In-Gel Digestion. Protein patterns of the 2-DE gels from normal gastric epithelium and tumor tissue were compared and consistent differentially expressed proteins with a size of approximately 40 kDa were excised. In-gel digestion of proteins was performed as described elsewhere.12 In brief, excised gel pieces were destained and dried. After rehydration and digestion with 10 µL of a trypsin solution (0.02 µg/µL; Roche) at 37 °C for 7 h supernatants were applied directly on a NP20 ProteinChip Array (Ciphergen Biosystems Inc, Fremont, CA). An empty gel piece underwent the same treatment as a control. After addition of the matrix (CHCA; Ciphergen Biosystems Inc., Fremont, CA), peptide fragment masses were analyzed using the ProteinChip Reader. The spectra for the peptide mapping experiments were externally calibrated using five standard proteins including Arg8-vasopressin (1082.2 Da), somatostatin (1637.9 Da), dynorphin (2147.5 Da), ACTH (2933.5 Da), and 1800

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insulin beta-chain (3495.94 Da). Proteins were identified using the fragment masses generated through trypsin digestion by searching in a publicly available database (http://129.85.19.192/ profound_bin/WebProFound.exe). Tandem MS Analysis. The tryptic digest was analyzed on a tandem mass spectrometer (QStar Pulsar, ABI Applied Biosystems, Darmstadt, Germany) equipped with a PCI 1000 ProteinChip Interface (Ciphergen Biosystems Inc.). The system was externally calibrated in MS/MS mode using the parent ion and four selected fragments of human adenocorticotropic hormone (ACTH) (aa18-39 [M+H]+ ) 2465.1989 Da) (Sigma, Munich, Germany). Raw data were analyzed using the instruments Analyst Software (ABI). Databank searches were performed against the SwissProt database using the Mascot search algorithm. Immuno-Deplete Assay. Two microliters of anti-human pepsinogen C polyclonal antibody (ab9013; Abcam, Cambridge, UK) were incubated with 10 µL protein A-agarose (Sigma) for 15 min on ice. A pellet was generated by centrifugation and the supernatant was discarded. The pellet was washed two times with a buffer containing 20 mM Hepes (pH 7.8), 25 mM KCl, 5 mM MgCl2, 0.1 mM EDTA and 0.05% NP-40. Afterward, 5 µL of a lysate from laser-dissected normal gastric epithelium were incubated with this pellet for 45 min on ice. As a negative control 5 µL of the lysate were incubated with protein A-agarose without the specific antibody for 45 min on ice. After incubation samples were cleared by centrifugation and three microliters of each supernatant were analyzed by ProteinChip Arrays. Immunohistochemistry. Eight-micrometers cryostat sections of gastric cancer tissue and normal normal epithelium were placed on slides, air-dried for approximately 60 min at 20 °C and fixed in paraformaldehyde as described.12 After fixation, slides were treated in the microwave at 80 W (3 × 3 min) in 10 mM citric acid pH 6.0 to inhibit endogenous peroxidatic activity. Subsequently, they were rinsed twice with TBS pH 7.4, and incubated overnight at 4 °C in humidity chamber with the corresponding primary polyclonal antibody against pepsinogen C (ab9013; Abcam, Cambridge, UK). Slides were rinsed 3 × 10 min in TBS and the Vectastain Elite ABC kit (Vector Laboratories, Burlingame, CA) and the Jenchrom pxbl-kit (MoBiTec, Go¨ttingen, Germany) was used according manufacturer’s instructions to visualize antibody localization. Negative controls were incubated with the labeled secondary antibody only. Sections cut in parallel to the IHC-treated sections were stained by HE for better identification of different tissue areas. IHC staining was evaluated by a pathologist.

Results Profiling of Microdissected Normal Gastric Epithelium, Gastric Central Tumor Tissue, and Tumor Margin Tissue. For this study, areas corresponding to about 3000 to 5000 cells per tissue probe were excised, and 74 tissue sections in total (21 central tumor, 18 tumor margin, and 35 normal gastric epithelium tissues) were successfully dissected by a pathologist. All protein lysates from the microdissected tissues were applied to Q10 arrays and analyzed on a PCS 4000 instrument. In the high range (20 kDa to 200 kDa), up to 64 peaks were detected with normalized intensities. After evaluation with CiphergenExpress Program, the peak mass with the lowest P-value was selected for further characterization and identification. This signal of nearly 42.5 kDa seen on a Q10 array was downregulated in gastric tumor tissue and discriminated significantly between normal gastric mucosa and gastric central tumor and

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Figure 1. Distribution of the intensities of 42.5 kDa peak in normal gastric epithelium samples (NG LCM), gastric tumor margin samples (TR LCM), and gastric central tumor samples (TZ LCM). The spectra were obtained using Q10 arrays. X-axis indicate the sample groups, Y-axis the intensity (µA).

gastric tumor margin (P ) 1.43 × 10-6) as well as between normal epithelium and central tumor or tumor margin, respectively (P ) 8.79 × 10-6 or P ) 4.39 × 10-5, respectively). In samples only derived from normal gastric epithelium, the differentially expressed signal of 42.5 kDa was detectable by SELDI-TOF MS. The distribution of the intensities for the different tissues is given in Figure 1. Representative examples of SELDI-MS spectra from normal gastric epithelium, tumor margin, and central tumor are shown in Figure 2 in the range from 35 to 50 kDa. Identification of the Differentially Expressed Signal. Histologically checked gastric tumor pieces and biopsies from normal gastric epithelium were subjected to 2-DE to detect the differentially expressed signal at 42.5 kDa (Figure 3). Numerous protein spots showing differential expression in both specimens were observed. Due to the binding of the unknown protein species to a strong anion exchanger surface at pH 8.5 in our ProteinChip analysis, we expected the isoelectrical point of this protein candidate to be below 8.5. We therefore decided to concentrate on 21 spots in range of 35 to 55 kDa exhibiting a pI 3 to 7 in our 2-D gel electrophoresis. Selected spots were cut out from the second dimension gel and were subsequently subjected to in-gel digestion with trypsin and protein identification. An empty gel piece underwent the same treatment as a control. The digest solution was spotted on a NP20 array and the masses of the fragments determined by the ProteinChip Reader. Database searches (Profound; http://129.85.19.192/ profound_bin/WebProFound.exe) revealed pepsinogen C as the best candidate. These results were further confirmed by tandem MS analysis. The NP20 array with the tryptic digests was transferred to a tandem MS equipped with a SELDI ProteinChip Interface. The peptides generated were selected and fragmented into smaller ions by collision-induced dissociation (Figure 4). Sequence of the analyzed peptide is given in Table 1. These result confirmed the identification of the protein as pepsinogen C. The reassurance that pepsinogen C is matching to the differentially expressed peak at 42.5 kDa found by ProteinChip

Figure 2. Representative examples of SELDI-TOF MS spectra of normal gastric epithelium, gastric tumor margin and gastric central tumor. Data are obtained using Q10 array. The peak of interest at 42.5 kDa is marked with a frame.

analysis was done with an immuno-deplete assay using microdissected normal gastric epithelium tissue as starting material. Analysis of the supernatant of the immuno-deplete assay by Journal of Proteome Research • Vol. 4, No. 5, 2005 1801

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Figure 3. 2-DE analysis of normal (A) and tumor tissue (B). C and D are enlargements of the frame in A and B, respectively. The arrow indicate the spot that was analyzed by in-gel digestion later identified as pepsinogen C using both MS/MS analysis and immunodepletion assay.

Figure 5. Immunodepletion assay of normal gastric epithelium. A peak (labeled by asterisk) representing pepsinogen C was detectable in the negative control but not in the corresponding depleted probe. Table 1. Protein Identification by Peptide Mapping and CID MS/MS

protein

Pepsinogen C (Progastricsin) Figure 4. (A) Tandem MS analysis on ProteinChip Interface in single MS mode from the tryptic digest. A peptide (indicated by *) was further selected for CID-MS/MS analysis. In (B) the CIDMS/MS of the peptide with m/z 1451.66 is shown.

ProteinChip arrays showed that the peak corresponding to pepsinogen C was significantly reduced. In the negative control without the specific antibody the peak at 42.5 kDa was clearly detectable (Figure 5). Characterization of Pepsinogen C by Immunohistochemistry. To further characterize the identified marker and to localize pepsinogen C in tissue sections, we examined their expression in several gastric epithelium tissue samples by immunohistochemistry using a specific polyclonal antibody 1802

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sequence peptide (m/z) coverage for (%) CID-MS/MS

6

1451.7

sequence

SYYSVYDLGNNR (Progastricsin)

average mass (calcd.) [kDa]

42.42

against pepsinogen C. Negative controls without the primary antibody or without antibody at all demonstrated negative results. Both normal gastric epithelial cells as well as malignant tumor cells demonstrated cytoplasmic signals for pepsinogen C in all tissue samples examined. The signal in last named samples was unequivocally decreased compared to the signal detected in normal epithelial cells (Figure 6). Quantitative differences between the expression of pepsinogen C in normal epithelial gastric cells and malignant tumor cells are not as clear as in ProteinChip Array results. To further confirm that the localized pepsinogen C is identical to the peak found by ProteinChip analysis, areas of similar size from tumorous and normal tissue that were prior

Pepsinogen C as a Potential Biomarker

Figure 6. Immunohistochemistry of pepsinogen C. Gastric tumor (Tu) and normal gastric epithelium (N) with a magnification of 100x.

Figure 7. Areas of similar size of tumorous and normal tissue that were applied in IHC were microdissected and analyzed on ProteinChip Arrays. A signal (marked with a frame) with a molecular mass of nearly 42.5 kDa representing pepsinogen C was detectable in protein lysate derived from normal gastric epithelium. In the protein lysate from the gastric tumor fraction this signal is absent.

analyzed in IHC were obtained by tissue laser microdissection. In protein lysate from the normal epithelium fraction, a signal identical in mass to the peak obtained with the initial SELDIMS analysis was detected on a Q10 array. In the protein lysate from the gastric tumor fraction this peak was absent (Figure 7).

Discussion New molecular biomarkers or biomarker patterns found by genomic or proteomic high-throughput techniques will enable a more reliable early diagnosis of malignant tumors, and facilitate the prediction of their progression. In this way, biomarkers may contribute to a more differentiated, individually orientated tumor therapy. Despite enormous efforts, relevant markers useful for screening have been established only in a few tumor types.14,15 Gastric tumors belong to cancer types that are frequently diagnosed when the tumor has reached an advanced stage.6,16 The overall poor prognosis of patients with gastric cancer could be improved by identifying specific molecular markers for precursor lesions or the detection of cancer in its early stages. Besides two-dimensional gel electrophoresis (2-DE), ProteinChip technology is a promising proteomic tool for the detection of new cancer biomarkers. Previously, this technique has been predominantly used for analysis of body fluids, such as serum, due to availability and simplicity of array preparation.17-19 Nevertheless, it is known that inter- and intraindividual differences in serum depending on sex, hormonal,

research articles nutritional, or inflammation status at the time of blood collection vary drastically causing differences in the protein profile. Analysis of tissue samples is more time-consuming because it is necessary to microdissect tumor cells out of tumor sections. However, this effort ensures that any potential marker identified is highly likely to have originated from the cancer tissue itself. Studies using tissue as the starting material are under-represented in the literature to date, and include prostate cancer,20-22 melanoma,8 lung tumors,23 RCC,24,25 endometrial carcinoma,26,27 HCC,28 and HNSCC.11,12,29 In most cases, these studies have analyzed only a limited numbers of samples which may be due to the tedious nature of laser-based microdissection or that the technique requires an experienced pathologist. In the present study, we applied a technical triad composing tissue microdissection, protein profiling and immunohistochemistry for the detection, identification and characterization of a potential biomarker for gastric cancer. A total of 74 samples containing 3000-5000 cells were microdissected from sections of gastric tumor biopsies and adjacent normal gastric epithelium for protein profiling using SELDI-TOF-MS. Microdissection was carried out using an extremely precise technique, LMCP, because the boundaries between tumor and normal tissue are irregular, and thus, contamination with nontumor cells was avoidable. Differentially expressed proteins were detected, and a 42.5 kDa protein was observed to be less expressed in the cells of gastric tumor as compared to normal gastric epithelium and tissue at the margin of the tumor (P ) 1.43 × 10-6). This protein was identified as pepsinogen C (pregastricsin) by both MS/MS analysis and in an independent immunodepletion assay. Pepsinogen C (pregastricsin) is the precursor of pepsin C or gastricsin. Pepsinogen C (PGC) can be detected throughout the stomach and proximal duodenum from the late infant stages of development into maturation. The protein is a mature marker of stomach cells, and consists of two electrophoretically differentiable isozymogens expressed the gastric mucosa.30-32 Human pepsinogens (PGs) are synthesized as isozymogens and are classified into two groups, PGA and PGC, according to their biological and immunological characteristics.33 Several reports have pointed out the role of PGs as tumor markers. A low PGA or PGA/PGC ratio in serum were determined in patients with atrophic gastritis or gastric cancer.34,35 These findings suggest that PGs may be potentially useful parameters to identify gastric cancer. In two recent studies carried out protein profiling of gastric tumors using SELDI-TOF-MS.18,36 These studies analyzed serum instead of tissue samples, and did not present data for proteins above 15 kDa making comparison with the study presented here difficult. Using immunohistochemistry (IHC), we localized pepsinogen C in both normal gastric epithelium and to a lesser extent in tumor cells. IHC demonstrated the heterogeneous distribution of pepsinogen C in all tissue samples examined underlying the importance of tissue microdissection prior to analysis. Microdissection enables exact separation of the epithelial and mesenchymal tissue components as well as the separation of benign and malignant cell groups. Microdissection is a powerful technique to enable the comparison of differential protein expression between normal and cancerous cells in biopsies. ProteinChip analysis was better able to analyze differential pepsinogen C expression than IHC, since background staining partially obscured the results. SELDI analysis of microdissected IHC-positive normal epithelial areas and gastric tumor cells confirmed a clear difference in pepsinogen C expression level. Journal of Proteome Research • Vol. 4, No. 5, 2005 1803

research articles Using protein profiling, we were able to detect and identify pepsinogen C as a differentially expressed protein, downregulated in gastric tumors. The combination of tissue microdissection with SELDI-TOF-MS and IHC in a proteomic triad provides a foundation for a clear picture of tumor progression by the eliminiation of background signal from tissue compartments that are uneasily separated surgically. Further studies are required to investigate the role that reduced pepsinogen C may play in gastric tumor biology, and its possible use as a biomarker for the early detection of gastric cancer. Abbreviations: HE, hematoxylin and eosin; IHC, Immunohistochemistry; LMPC, Laser microdissection and pressure catapulting microscope; SELDI, Surface enhanced laser desorption ionization; MS, mass spectrometry; CID, collisioninduced dissociation; TOF, time-of-flight; 2-DE, two-dimensional gel electrophoresis; PG, pepsinogen.

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Acknowledgment. This work was supported by a grant of the German Federal Ministry of Education and Research (BMBF) and the Interdisciplinary Center for Clinical Research (ICCR), Jena. We would like to thank Ralf Bogumil (Ciphergen GmbH) for the preparation of MS/MS analysis and Kathy Astrahantseff for critical reading of the manuscript.

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References (1) Roth, A. D. Crit. Rev. Oncol. Hematol. 2003, 46, 59-100. (2) Botterweck, A. A. M.; Van den Brandt, P. A.; Goldbohm, R. A. Cancer 2000, 88, 737-748. (3) Zhang, Z. F.; Kurtz, R. C.; Klimstra, D. S.; Yu, G. P.; Sun, M.; Harlap, S.; Marshall, J. R. Cancer Detect. Prev. 1999, 23, 357367. (4) Yao, X. X.; Yin, L.; Sun, Z. C. World J. Gastroenterol. 2002, 8, 586590. (5) Fuchs, C. S.; Mayer, R. J. New Engl. J. Med. 1995, 333, 32-41. (6) Rhyu, M. G.; Park, W. S.; Jung, Y. J.; Choi, S. W.; Metlzer, S. J. Gastroenterology 1994, 106, 1584-1591. (7) Hutchens, T. W.; Yip, T. T. Rapid Commun. Mass Spectrom. 1993, 7, 576-580. (8) von Eggeling, F.; Davies, H.; Lomas, L.; Fiedler, W.; Junker, K.; Claussen, U.; Ernst, G. Biotechniques 2000, 29(5), 1066-1070. (9) Craven, R. A.; Banks, R. E. Proteomics 2001, 1, 1200-1204. (10) Cheung, P. K.; Woolcock, B.; Adomat, H.; Sutcliffe, M.; Bainbridge, T. C.; Jones, E. C.; Webber, D.; Kinahan, T.; Sadar, M.; Gleave, M. E.; Vielkind, J. Cancer Res. 2004, 64, 5929-5933. (11) Melle, C.; Ernst, G.; Schimmel, B.; Bleul, A.; Koscielny, S.; Wiesner, A.; Bogumil, R.; Moller, U.; Osterloh, D.; Halbhuber, K. J.; von Eggeling, F. Cancer Res. 2004, 64, 4099-4104. (12) Melle, C.; Ernst, G.; Schimmel, B.; Bleul, A.; Koscielny, S.; Wiesner, A.; Bogumil, R.; Moller, U.; Osterloh, D.; Halbhuber, K. J.; von Eggeling, F. Mol. Cell. Proteomics 2003, 2, 443-552. (13) Kwapiszewska, G.; Meyer, M.; Bogumil, R.; Bohle, R. M.; Seeger; W. Weissmann, N.; and Fink, L. BMC Biotechnol. 2004, 4(1), 30. (14) van’t Veer, L. J.; Dai, H. Y.; van de Vijver, M. J.; He, Y. D. D.; Hart, A. A. M.; Mao, M.; Peterse, H. L.; van der Kooy, K.; Marton, M. J.;

1804

Journal of Proteome Research • Vol. 4, No. 5, 2005

(26) (27) (28) (29) (30) (31) (32) (33) (34) (35) (36)

Witteveen, A. T.; Schreiber, G. J.; Kerkhoven, R. M.; Roberts, C.; Linsley, P. S.; Bernards, R.; Friend, S. H. Nature 2002, 415, 530536. Sidransky, D. Nat. Rev. Cancer 2002, 2, 210-219. Ebert, M. P.; Malfertheiner, P. Aliment. Pharmacol. Ther. 2002, 16, 1059-1066. Kozak, K. R.; Amneus, M. W.; Pusey, S. M.; Su, F.; Luong, M. N.; Luong, S. A.; Reddy, S. T.; Farias-Eisner, R. Proc. Natl. Acad. Sci. U.S.A. 2003, 100, 12343-12348. Ebert, M. P. A.; Meurer, J.; Wiemer, J. C.; Schulz, H. U.; Reymond, M. A.; Traugott, U.; Malfertheiner, P.; Ro¨cken, C. J. Proteome Res. 2004, 3, 1261-1266. Zhang, Z.; Bast, R. C. Jr.; Yu, Y.; Li, J.; Sokoll, L. J.; Rai, A. J.; Rosenzweig, J. M.; Cameron, B.; Wang, Y. Y.; Meng, X. Y.; Berchuck, A.; van Haaften-Day, C.; Hacker, N. F.; de Bruijn, H. W. A.; van der Zee, A. G. J.; Jacobs, I. J.; Fung, E. T.; Chan, D. W. Cancer Res. 2004, 64, 5882-5890. Wright, G. L. Jr.; Cazares, L. H.; Leung, S. M.; Nasim, S.; Adam, B. L.; Yip, T. T.; Schellhammer, P. F.; Gong, L.; Vlahou, A. Prostate Cancer Prostatic Dis. 1999, 2, 264-276. Cazares, L. H.; Adam, B. L.; Ward, M. D.; Nasim, S.; Schellhammer, P. F.; Semmes, O. J.; Wright, G. L. Jr. Clin. Cancer Res. 2002, 8, 2541-2552. Wellmann, A.; Wollscheid, V.; Lu, H.; Ma, Z. L.; Albers, P.; Schutze, K.; Rohde, V.; Behrens, P.; Dreschers, S.; Ko, Y.; Wernert, N. Int. J. Mol. Med. 2002, 9, 341-347. Zhukov, T. A.; Johanson, R. A.; Cantor, A. B.; Clark, R. A.; Tockman, M. S. Lung Cancer 2003, 40, 267-279. von Eggeling, F.; Junker, K.; Fiedler, W.; Wollscheid, V.; Durst, M.; Claussen, U.; Ernst, G. Electrophoresis 2001, 22, 2898-2902. Fetsch, P. A.; Simone, N. L.; Bryant-Greenwood, P. K.; Marincola, F. M.; Filie, A. C.; Petricoin, E. F.III; Liotta, L. A.; Abati, A. Am. J. Clin. Pathol. 2002, 118, 870-876. Yang, C. C.; Guo, J.; Diehl, G.; DeSouza, L.; Rodrigues, M. J.; Romaschin, A. D.; Colgan, T. J.; Siu, K. W. M. J. Proteome Res. 2004, 3, 636-643. Guo, J.; Yang, E. C. C.; DeSouza, L.; Diehl, G.; Rodrigues, M. J.; Romaschin, A. D.; Colgan, T. J.; Siu, K. W. M. Proteomics 2005, Apr 7; [Epub ahead of print]; DOI 10.1002/pmic.200401059. Melle, C.; Kaufmann, R.; Hommann, M.; Bleul, A.; Driesch, D.; Ernst, G.; von Eggeling, F. Int. J. Oncol. 2004, 24, 885-891. Roesch Ely, M.; Nees, M.; Karsai, S.; Ma¨gele, I.; Bogumil, R.; Vorderwu ¨ lbecke, S.; Reuss, A.; Dietz, A.; Schno¨lzer, M.; Bosch, F. X. Eur. J. Cell Biol. 2005, 84, 431-444. Kageyama, T.; Ichinose, M.; Tsukada-Kato, S.; Omata, M.; Narita, Y.; Moriyama, A.; Yonezawa, S. Biochem. Biophys. Res. Commun. 2000, 267, 806-812. Kageyama, T. Cell. Mol. Life Sci. 2002, 59, 288-306. Samloff, I. M.; Liebman, W. M. Gastroenterology 1973, 65, 3642. Samloff, I. M. Gastroenterology 1969, 57, 659-669. Miki, K.; Ichinose, M.; Ishikawa, K. B.; Yahagi, N.; Matsushima, M.; Kakei, N.; Tsukada. S.; Kido, M.; Ishihama, S.; Shimizu, Y. et al. Jpn. J. Cancer Res. 1993, 53, 1086-1090. Fernandez, R.; Vizoso, F.; Rodriguez, J. C.; Merino, A. M.; Gonzalez, L. O.; Quintela, I.; Andicoechea, A.; Truan, N.; Diez, M. C. Ann. Surg. Oncol. 2000, 7, 508-514. Ebert, M. P.; Lamer, S.; Meurer, J.; Malfertheimer, P.; Reymond, M.; Buschmann, T.; Ro¨cken, C.; Seibert, V. J. Proteome Res. 2005, 4, 586-590.

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