Comprehensive Proteomic Analysis of Human Pancreatic Juice

Comprehensive Proteomic Analysis of Human Pancreatic Juice Mads Grønborg,†,‡ Jakob Bunkenborg,†,‡ Troels Zakarias Kristiansen,†,‡ Ole Nørregaard Jensen,‡ Charles J. Yeo,§ Ralph H. Hruban,| Anirban Maitra,| Michael G. Goggins,| and Akhilesh Pandey*,† McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University, Baltimore, Maryland 21205, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, Odense M, Denmark, Department of Surgery, Johns Hopkins University, Baltimore, Maryland 21287, and Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21287 Received May 20, 2004

Proteomic technologies provide an excellent means for analysis of body fluids for cataloging protein constituents and identifying biomarkers for early detection of cancers. The biomarkers currently available for pancreatic cancer, such as CA19-9, lack adequate sensitivity and specificity contributing to late diagnosis of this deadly disease. In this study, we carried out a comprehensive characterization of the “pancreatic juice proteome” in patients with pancreatic adenocarcinoma. Pancreatic juice was first fractionated by 1-dimensional gel electrophoresis and subsequently analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). A total of 170 unique proteins were identified including known pancreatic cancer tumor markers (e.g., CEA, MUC1) and proteins overexpressed in pancreatic cancers (e.g., hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein (HIP/PAP) and lipocalin 2). In addition, we identified a number of proteins that have not been previously described in pancreatic juice (e.g., tumor rejection antigen (pg96) and azurocidin). Interestingly, a novel protein that is 85% identical to HIP/PAP was identified, which we have designated as PAP-2. The proteins identified in this study could be directly assessed for their potential as biomarkers for pancreatic cancer by quantitative proteomics methods or immunoassays. Keywords: liquid chromatography tandem mass spectrometry (LC-MS/MS) • functional annotation • body fluid

Introduction Approximately 30 000 new patients are diagnosed with pancreatic cancer each year in the United States, and nearly all die from their disease within months of diagnosis.1 At present, a cure is generally possible only with complete surgical resection excision; however, greater than 80% of patients present with locally advanced disease or distant metastases, rendering the tumor inoperable.2 Unfortunately, current imaging modalities and tumor markers lack the sensitivity and specificity to diagnose small, potentially curable lesions.3 In addition, the diagnosis of pancreatic cancer is often delayed in patients with symptomatic pancreatic cancer, many of whom undergo several negative investigations before a diagnosis can be established. The poor prognosis and late presentation of pancreatic cancer patients emphasize the importance of an effective early detection strategy, especially for patients at risk of developing pancreatic cancer. Therefore, more sensitive and * To whom correspondence should be addressed. E-mail: pandey@ jhmi.edu. † McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University. ‡ Department of Biochemistry and Molecular Biology, University of Southern Denmark. § Department of Surgery, Johns Hopkins University. | Department of Pathology, Johns Hopkins University.

1042

Journal of Proteome Research 2004, 3, 1042-1055

Published on Web 09/17/2004

specific biomarkers are required to improve the early diagnosis of pancreatic cancer.3 Development of better biomarkers could lead to earlier therapeutic intervention, thereby improving the prognosis of this deadly disease. The changes in expression patterns of proteins that are specific to disease tissues can be characterized using proteomic technologies.4-6 At the protein level, distinct changes occur during the transformation of a healthy cell into a neoplastic cell, including altered expression, differential protein modification, changes in specific activity, and aberrant localization. Cancer proteomics involves cataloging those changes that arise as a result of cancer. Pancreatic juice is an ideal specimen for identifying new biomarkers of pancreatic cancer using proteomic profiling.7 Compared to other sample specimens, such as serum or stool, pancreatic juice has a higher concentration of proteins and DNA released from pancreatic cancer cells. Once biomarkers have been identified in body fluids such as pancreatic juice using proteomics, they can subsequently be measured by more sensitive arrays (e.g., ELISA) in more accessible samples such as serum. A prerequisite for identifying biomarkers for pancreatic cancer in pancreatic juice is to first define the composition of the proteins found in this body fluid. Mass spectrometric approaches such as SELDI (surface enhanced laser desorption 10.1021/pr0499085 CCC: $27.50

 2004 American Chemical Society

Proteomic Analysis of Human Pancreatic Juice

ionization) have been applied to the study of body fluids from diseased individuals in order to identify cancer specific “patterns”.8 Although characteristic patterns of protein peaks that differentiate normal from diseased individuals can be obtained easily using SELDI, the identification of specific proteins corresponding to specific protein peaks is still a difficult task. We have previously utilized SELDI to identify novel protein peaks in serum and in pancreatic juice that distinguish samples from patients with pancreas cancer from controls.7,9 We have also reported the identification of one peak observed by SELDI as hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein, HIP/PAP that accurately distinguished pancreatic cancer from controls.7 However, SELDI alone does not provide the detected proteins’ identity, but rather only the mass/charge ratios, whereas liquid chromatography tandem mass spectrometric (LC-MS/MS) provides an actual list of proteins comprising the physiologic and/or pathologic proteome of the fluid analyzed.10,11 Here, we report the first comprehensive proteomic study of human pancreatic juice using an LC-MS/MS based approach. We analyzed endoscopically obtained pancreatic juice samples from patients with pancreatic cancer and identified 170 unique proteins. We expect that tandem mass spectrometric approaches will gain popularity for identification of diagnostic biomarkers especially when combined with ‘tagging’ methods for differential proteomics.

Materials and Methods Sample Preparation. Pancreatic juice samples were collected during surgery from the pancreatic duct of patients with pancreatic cancer undergoing pancreatectomy. A total volume of 20-500 µL was collected from each procedure and immediately stored at -80 °C without any protease inhibitors. Pancreatic juice from three patients (A, B, and C) was used in this study and analyzed separately. The samples were centrifuged at 14 000 rpm for 15 min at 4 °C to remove debris. The protein concentration for each sample was measured using a protein assay kit (DC-protein assay, BIO-RAD, Hercules, CA). The concentration was measured to 6.2 mg/mL, 1.53 mg/mL and 8.53 mg/mL for sample A, B, and C, respectively. Each sample was subsequently run on a 1-dimensional 10% Minigel (NuPAGE, Invitrogen, Carlsbad, CA) according to the manufacturers’ instructions. Approximately 100 µg of each sample was loaded on the gel. The gel was silver stained by a protocol compatible with mass spectrometry as previously described.12 In-Gel Digestion. Each gel lane was excised into approximately 20 bands and each band was further cut into smaller pieces (approximately 2 × 2 mm). Gel pieces from each band were washed with Milli-Q water and water/acetonitrile 1:1 (v/ v) two times for 15 min at room temperature. Solvent volumes in the washing step roughly equaled five times the gel volume. After washing, the liquid was removed and the gel pieces were covered in 100% acetonitrile to shrink the gel pieces. After approximately 5 min, the acetonitrile was removed and replaced by 10 mM dithiotreitol (DTT) in 100 mM ammonium bicarbonate for 45 min at 56 °C to reduce the cystines. The liquid was removed and replaced by 55 mM iodoacetamide in 100 mM ammonium bicarbonate and incubated for 30 min at room temperature in the dark to alkylate the cysteines. The iodoacetamide solution surplus was removed and the gel pieces were washed two times in water and acetonitrile as described above and subsequently dehydrated by adding 100% acetonitrile. The gel pieces were rehydrated in a digestion buffer

research articles containing 12.5 ng/µL trypsin (Promega, modified sequencing grade) in 50 mM ammonium bicarbonate and incubated for 45 min on ice. Enough digestion buffer was added to cover the gel pieces. After 45 min, the digestion buffer was replaced by approximately the same volume of 50 mM ammonium bicarbonate but without trypsin to keep the gel pieces wet during enzymatic digestion. The samples were incubated at 37 °C overnight. After digestion, the remaining supernatant was removed and saved. The remaining peptides were extracted from the gel pieces by incubating in 5% formic acid (enough to cover the pieces) for 15 min and then adding the same volume of 100% acetonitrile for a further incubation of 15 min. The extraction was repeated twice and all three fractions were pooled and dried down in a vacuum centrifuge and resuspended in 10 µL of 5% formic acid. Liquid Chromatography. Each fraction from the in-gel digestion (corresponding to approximately 1/20 of the gel) was analyzed by automated nano-flow liquid chromatography tandem mass spectrometry (LC-MS/MS). An Agilent 1100 series system (Agilent Technologies, CA) was used to deliver a flow of 4 µL/min during desalting of samples and 300 nl/min during elution of the peptides into the mass spectrometer. Each sample was loaded on-line onto a 75 µm fused silica precolumn packed with 10-µm C18 ODS-A (YMC Ltd, Japan) for washing and desalting in 95% mobile phase A (H2O with 0.4% acetic acid and 0.005% heptafluorobutyric acid v/v) and 5% mobile phase B (90% acetonitrile, 0.4% acetic acid and 0.005% heptafluorobutyric acid in water). After washing and desalting, the sample was eluted from the precolumn by a linear gradient of 90% mobile phase A to 60% mobile phase A onto a 75 µm fused silica analytical column packed with 5-µm Vydac C18 resin. A 34 min gradient was used for elution. A potential of 2.7 kV was applied to the emitter (New Objective, USA). The spectra were acquired on a Micromass Q-TOF API-US (Manchester, UK) equipped with an ion source designed at Proxeon Biosystems (Odense, Denmark). All spectra were obtained in positive ionmode. Data analysis was performed using MassLynx 4.0 software and the resulting MS/MS data set was analyzed using the Mascot search engine (Matrix Science Ltd., London, UK). Mass Spectrometry Analysis and Database Searching. Database searching was done using the Mascot search engine (Matrix Science, UK). A combination of computer scoring and evaluation by an experienced mass spectrometrist were employed in the screening of the data. The data were searched against the human RefSeq database (http:// www.ncbi.nlm.nih.gov/RefSeq/) with a mass accuracy of 0.3 Da for the parent ion (MS) and 0.2 Da for the fragment ions (MS/MS). The peptides were constrained to be tryptic with a maximum of 2 missed cleavages. Carbamidomethylation of cysteines was considered a fixed modification, whereas oxidation of methionine residues and formation of pyroglutamic acid for peptides containing an N-terminal glutamine were considered as variable modifications. An initial list of proteins was generated based on which further analysis was performed. A “positive list” was generated by the following screening procedure: Only proteins containing at least 1 unique peptide (we refer to a peptide as being unique for a specific protein if the sequence has not been assigned to a different protein) with a Mascot score above 20 (p-value > 35) were considered in the dataset. The highest scoring peptide was manually interpreted/ inspected to confirm the predicted sequence by the Mascot search engine and to eliminate potential false positives. In addition, the inspected peptide match was required to have a Journal of Proteome Research • Vol. 3, No. 5, 2004 1043

research articles

Figure 1. Strategy for proteomic analysis of pancreatic juice. The pancreatic juice was first centrifuged, and then separated by 1-dimensional gel electrophoresis and divided into approximately 20 equal sized bands. Each gel slice was then digested with trypsin and analyzed by LC-MS/MS.

length of at least 8 amino acids and to have a sequence tag of at least three to four consecutive amino acids. We only list proteins that fulfilled all of the above-mentioned criteria. If a protein had multiple splice forms, was differentially processed, or had multiple variable entries in the databases, then we only considered one particular form of that protein unless there was experimental evidence that allowed us to distinguish between different forms. If multiple peptides matching the same protein were not found in the same gel band or adjacent gel bands, then extra care was taken to confirm these entries based on single peptide hits. To identify proteins that have not been annotated in RefSeq, the peak list file was searched against the NCBI nr database and compared to the list generated from the search against the RefSeq database.

Results and Discussion Sample Preparation and Analysis. Pancreatic juice collected from the pancreatic duct from pancreatic cancer patients by endoscopic retrograde cholangiopancreaticography (ERCP) was analyzed according to the strategy used outlined in Figure 1. Briefly, a total of approximately 100 µg protein of each sample was loaded on a preparative 1-dimensional (1D) gel. To lower the complexity of the samples prior to liquid chromatography, the lane from each sample was divided up into approximately 20 gel bands and subsequently digested by trypsin. Each band was then analyzed by LC-MS/MS. The resulting tandem mass spectra were then searched against RefSeq database. The total number of proteins identified from the three samples was 76 proteins, 63 proteins, and 115 proteins, respectively. All MS/ 1044

Journal of Proteome Research • Vol. 3, No. 5, 2004

Grønborg et al.

MS spectra used to identify a protein were manually interpreted and validated as described under Materials and Methods. Of the 254 total proteins identified from the three pancreatic juice samples, 170 (67%) of the proteins turned out to be nonredundant among the three samples (see Table 1). As seen in Figure 2, 30 proteins were specific to sample A, 17 proteins specific to sample B and 67 proteins specific to sample C. Twenty-three proteins were found to be common to all three samples. The aggregate results obtained from the three different patient samples will be discussed below. Known Proteins Identified from Pancreatic Juice from Cancer Patients by 1D Gel Electrophoresis Followed by LCMS/MS Analysis. A large number of proteins identified in our analysis were those that are normally synthesized by exocrine pancreatic acini, and thus, their presence would be expected in pancreatic juice. These included enzymes such as pancreatic carboxypeptidases, pancreatic amylases, pancreatic lipases and phospholipases, pancreatic elastases, cationic and anionic trypsinogens (Table 1). Given the different modes of secretion and the vast preponderance of exocrine over endocrine cells in the pancreas (the latter representing less than 2% of the parenchyma by volume), it is not surprising that islet cell hormones (insulin, glucagon, pancreatic polypeptide) were not present in the list of proteins. However, Cystatin C, a cysteine protease strongly expressed by neuroendocrine cells of the pancreas and digestive tract,13 resistin, a recently identified adipokine,14 and regenerating islet-derived 1 R (Reg I R),15 were among the known islet-secreted proteins that we identified in this analysis. In addition, as the samples were obtained by ERCP, we also identified a minor population of hepatic and duodenal proteins (e.g., ceruloplasmin, apolipoprotein B, lactotransferrin, and transthyretin), most likely representing admixture with bile and duodenal juice, respectively. Alternatively, it is possible that they are actually secreted by the pancreas. In addition to normal pancreatic proteins, we also found several known “cancer-associated” proteins reflecting the fact that the juice samples were obtained from patients harboring pancreatic cancer. These included gene products, that we and others, have previously identified as overexpressed in pancreatic cancers by other detection methods such as DNA microarrays or immunohistochemistry (e.g., annexin I (lipocortin I), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), clusterin, deleted in malignant brain tumors 1 (DMBT1), heat shock 70kD protein 6 (HSP70B), lipocalin (oncogene 24p3), lumican, Galectin 3 binding protein (Mac-2 binding protein), mucin 1, pepsinogen C (progastricin), rasrelated C3 botulinum toxin substrate 1 (RAC1), and members of the S100 family of Ca2+ -binding proteins, reiterating the validity of our LC-MS/MS approach as a tool for biomarker detection.16-27 It should be remembered, however, that only a quantitative proteomic analysis comparing control samples to cancer-derived samples can establish that these proteins are indeed upregulated in cancer. Some of the molecules identified in our study included proteins not previously known to be a constituent of pancreatic juice, e.g., azurocidin and defensin R-3 (Figure 3). Both of these proteins are involved in immune responses and may play an important biological role in pancreas.28-31 A further affirmation of the LC-MS/MS technique was our ability to detect the HIP/ PAP protein in all of the three pancreatic juice samples; we have previously reported overexpression of the HIP/PAP protein in juice and serum from pancreatic cancer patients using a combination of SELDI-based proteomics and immunoassays.7

research articles

Proteomic Analysis of Human Pancreatic Juice Table 1. List of All Unique Proteins Identified from Pancreatic Juice

refseq no.

protein name

biological process

NP_001093

actinin R 1

NP_000468 NP_001076 NP_000508 NP_001125 NP_443204 NP_000925 NP_001141 NP_001145 NP_001148 NP_000691 NP_001144 NP_000479 NP_001634 NP_000375 NP_036202 NP_001691 NP_001092

albumin R 1antichymotrypsin R 2 globin (hemoglobin, R 2) R fetoprotein R-2-glycoprotein R-2-plasmin inhibitor aminopeptidase N annexin 5 annexin A11 annexin I annexin IV antithrombin III apolipoprotein AII apolipoprotein B attractin azurocidin β actin

NP_000509 NP_000033 NP_003397

β globin β-2-glycoprotein I brain protein 14-3-3, zeta

NP_004334 NP_001703

protein metabolism cell communication

NP_009203

calreticulin carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) catalase cathepsin G ceruloplasmin chitotriosidase chromosome 9 open reading frame 19 chymotrypsin C

NP_001898

chymotrypsin-like protease

protein metabolism

NP_001897

chymotrypsinogen B1

protein metabolism

NP_001822 NP_005498

clusterin cofilin 1

NP_000053 NP_000055 NP_009224 NP_000583 NP_000056 NP_000177 NP_009005

complement component 1 inhibitor complement component 3 complement component 4A complement component 4B complement component 6 complement factor H1 coronin 1A

immune response cell organization and biogenesis protein metabolism

NP_000558 NP_000090

C-reactive protein cystatin C

NP_000388 NP_005208 NP_015568

cytochrome b-245 β defensin, R 3 deleted in malignant brain tumors 1 isoform b (DMBT-1b)

NP_004354

NP_002474

NP_001743 NP_001902 NP_000087 NP_003456 NP_071738

cell organization and biogenesis transport protein metabolism transport transport transport protein metabolism protein metabolism cell communication cell communication cell communication cell communication protein metabolism transport transport immune response immune response cell organization and biogenesis transport transport cell communication

molecular function

cellular component

MASCOT protein score

structural molecule activity

cytoplasm

transporter activity protease inhibitor activity transporter activity transporter activity transporter activity protease inhibitor activity enzyme (aminopeptidase) calcium ion binding calcium ion binding receptor ligand calcium ion binding protease inhibitor activity transporter activity transporter activity complement enzyme (protease) structural molecule activity

extracellular extracellular extracellular extracellular extracellular extracellular plasma membrane cytoplasm cytoplasm plasma membrane cytoplasm extracellular extracellular extracellular plasma membrane other cytoplasm

transporter activity transporter activity soluble molecule recognition chaperone activity cell adhesion molecule activity

extracellular extracellular cytoplasm

934 40 89

endoplasmic reticulum plasma membrane

88 121

immune response

cell adhesion molecule activity

plasma membrane

199

immune response

cell adhesion molecule activity

plasma membrane

54

energy pathways protein metabolism transport energy pathways unclassified

enzyme (oxidoreductase) enzyme (serine-type peptidase) transporter activity enzyme (hydrolase) unclassified

cytoplasm extracellular extracellular extracellular unclassified

167 636 1163 204 260

protein metabolism

enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (serine-type peptidase) complement structural molecule activity protease inhibitor activity complement complement complement complement complement structural molecule activity unclassified protease inhibitor activity enzyme (oxidase) complement unclassified

extracellular

450

extracellular

297

endoplasmic reticulum

940

extracellular cytoplasm

333 117

plasma membrane

558

immune response immune response immune response immune response immune response cell organization and biogenesis cell communication protein metabolism energy pathways immune response immune response

116 3595 543 448 35 52 31 158 112 87 529 156 81 51 183 87 382 938

extracellular extracellular extracellular extracellular extracellular cytoplasm

1367 511 145 100 182 65

extracellular extracellular

51 115

plasma membrane extracellular extracellular

64 192 828

Journal of Proteome Research • Vol. 3, No. 5, 2004 1045

research articles

Grønborg et al.

Table 1 (Continued)

refseq no.

protein name

biological process

molecular function

cellular component


NP_060049 deleted in malignant brain tumors 1 isoform c (DMBT-1c) NP_000510 δ globin NP_001963 elastase neutrophil

cell communication

receptor ligand

plasma membrane

104

transport protein metabolism


740 604

NP_001419 enolase 1 NP_000493 eosinophil peroxidase NP_001954 epidermal growth factor

energy pathways immune response cell organization and biogenesis cell communication

transporter activity enzyme (serine-type peptidase) enzyme (hydratase) enzyme (peroxidase) receptor ligand

cytoplasm cytoplasm extracellular

129 214 66

plasma membrane organization and biogenesis transporter activity blood coagulation factor blood coagulation factor structural molecule activity

plasma membrane cytoplasm extracellular extracellular extracellular

385 138 245 258

unclassified receptor activity

cytoplasm extracellular

125 507

transport transport cell communication protein metabolism

transporter activity transporter activity calcium ion binding enzyme (isomerase)

99 99 56 81

energy pathways

enzyme (dehydrogenase)

cytoplasm cytoplasm extracellular endoplasmic reticulum cytoplasm

unclassified transport protein metabolism

unclassified transporter activity heat shock protein activity

transport cell communication

transporter activity enzyme (tyrosine kinase)

unclassified extracellular endoplasmic reticulum extracellular cytoplasm

regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism transport regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism immune response

DNA binding

nucleus

transporter activity DNA binding

extracellular nucleus

20 275

DNA binding

nucleus

254

DNA binding

nucleus

236

DNA binding

nucleus

204

DNA binding

nucleus

85

DNA binding

nucleus

204

DNA binding

nucleus

574 1968

unclassified

extracellular

58

unclassified cell adhesion molecule activity receptor activity


71 260

NP_071317 estrogen regulated gene 1 NP_000137 NP_000499 NP_000500 NP_002017

ferritin light chain fibrinogen, R chain fibrinogen, γ chain fibronectin 1

XP_039332 frigg NP_005558 galectin 3 binding protein (Mac-2 binding protein) NP_000550 γ globin A NP_000175 γ globin G NP_000168 gelsolin NP_005304 glucose regulated protein (ERp57) NP_002037 glyceraldehyde3-phosphate dehydrogenase NP_006409 GW112 NP_005134 haptoglobin NP_002146 heat shock 70kDa protein 6 NP_000604 hemopexin NP_002101 hemopoietic lcell kinase (HCK) NP_002119 high-mobility group box 1

NP_000403 histidine rich glycoprotein NP_003500 histone H2A (member C)

NP_003512 histone H2B (member E)

NP_003519 histone H2B (member Q)

NP_003520 histone H3 (member A)

NP_003484 histone H3 (member T)

NP_002098 histone H3 (member3A)

NP_003529 histone H4 (member A) AAA65221

transport protein metabolism protein metabolism cell organization and biogenesis unclassified immune response

immunoglobulin heavy chain VH3 NP_653247 immunoglobulin J chain immune response NP_000588 insulin-like growth factor cell communication binding protein 2 (IGFBP-2) NP_000878 integrin R X cell communication 1046


plasma membrane

55

134

166 673 75 384 53 45

85

research articles

Proteomic Analysis of Human Pancreatic Juice Table 1 (Continued)

refseq no.

protein name

biological process

molecular function

NP_002206 inter R inhibitor, heavy chain H1 NP_002207 inter R trypsin inhibitor, heavy chain 2 NP_003632 interferon induced transmembrane protein 1 NP_002248 kallikrein 1 NP_006206 kallistatin

protein metabolism

NP_006112 keratin 1

cell organization and biogenesis cell organization and biogenesis cell organization and biogenesis cell organization and biogenesis energy pathways transport cell organization and biogenesis cell organization and biogenesis transport unclassified cell organization and biogenesis cell communication calcium ion binding immune response complement

NP_000412 keratin 10 NP_000414 keratin 2a NP_006762 keratin 8 type i NP_005557 lactate dehydrogenase A NP_002334 lactotransferrin NP_002287 lamin B receptor NP_005550 laminin R-1 NP_005555 lipocalin 2 (oncogene 24p3) NP_940850 LPPM429 (PAP-2) NP_002336 lumican

cellular component


protein metabolism

protease inhibitor activity

extracellular

50

protein metabolism

protease inhibitor activity

extracellular

37

cell communication unclassified

plasma membrane

86

protein metabolism

extracellular

87

extracellular

46

enzyme (serine-type peptidase) protease inhibitor activity structural molecule activity structural molecule activity structural molecule activity structural molecule activity enzyme (dehydrogenase) transporter activity structural molecule activity extracellular matrix binding transporter activity unclassified structural molecule activity

cytoplasm

300

cytoplasm

138

cytoplasm

117

cytoplasm

44

cytoplasm extracellular nucleus

123 2825 32

extracellular

49

extracellular extracellular extracellular

257 279 70

NP_002289 lymphocyte cytosolic protein-1 NP_002285 lysosomal-associated membrane protein 2 (CD107b) NP_000230 lysozyme energy pathways NP_000005 macroglobulin, R 2 protein metabolism

cytoplasm lysosome extracellular extracellular

241 621

NP_004659 maltase glucoamylase

plasma membrane

271

plasma membrane extracellular

71 121

extracellular

150

NP_005898 mannosidase R 1,2 member IA NP_002415 matrix metalloproteinase 8 NP_001701 momplement factor B NP_002447 mucin 1, transmembrane NP_000241 myeloperoxidase NP_002464 myosin, heavy chain 9, non muscle NP_065139 neutrophil specific antigen 1 NP_056146 nicastrin NP_000598 NP_000599 NP_000690 NP_066188 NP_001859 NP_001860 NP_001862 NP_001823 NP_254275 NP_056933 NP_031378 NP_005738 NP_000927 NP_006220 NP_000919 NP_001493

orosomucoid 1 orosomucoid 2 pancreatic amylase, R 2A pancreatic amylase, R 2B pancreatic carboxypeptidase A1 pancreatic carboxypeptidase A2 pancreatic carboxypeptidase B1 pancreatic colipase pancreatic elastase IIA pancreatic elastase IIB pancreatic elastase IIIB pancreatic elastase IIIE pancreatic lipase pancreatic lipase-related protein 1 pancreatic phospholipase A2 pancreatic zymogen granule membrane protein 2 (GP2)

98 42

enzyme (hydrolase) protease inhibitor activity energy pathways enzyme (glycoamylase) (HPRD) energy pathways enzyme (mannosidase) protein metabolism enzyme (metallo protease) protein metabolism enzyme (serine-type peptidase) immune response complement immune response enzyme (peroxidase) cell organization structural molecule and biogenesis activity immune response complement cell communication plasma membrane organization and biogenesis immune response enzyme (protease) immune response transporter activity energy pathways enzyme (amylase) energy pathways enzyme (amylase) protein metabolism enzyme (carboxypeptidase)

extracellular extracellular extracellular extracellular extracellular

176 64 1716 1565 1735

protein metabolism

enzyme (carboxypeptidase)

extracellular

650

protein metabolism

enzyme (carboxypeptidase)

extracellular

1968

energy pathways protein metabolism protein metabolism protein metabolism protein metabolism energy pathways energy pathways

enzyme (colipase) enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (lipase) enzyme (lipase)

extracellular extracellular extracellular endoplasmic reticulum endoplasmic reticulum extracellular extracellular

197 514 424 612 942 1705 91

energy pathways unclassified

enzyme (phospholipase) extracellular plasma membrane organization plasma membrane and biogenesis

plasma membrane extracellular cytoplasm

39 1951 211

plasma membrane plasma membrane

101 92

250 669


research articles

Grønborg et al.

Table 1 (Continued)

refseq no.

protein name

NP_002571

pancreatitisassociated protein/ hepatocarcinomaintestine-pancreas (HIP/PAP) paraoxonase 1 pepsinogen C peptidoglycan recognition protein peptidylprolyl isomerase A (cyclophilin A) pigment epitheliumderived factor polymeric immunoglobulin receptor profilin 1

NP_000437 NP_002621 NP_005082 NP_066953 NP_002606 NP_002635 NP_005013 NP_002764 NP_002768 NP_002645 NP_061485 NP_006498 NP_065148 NP_002880

prostasin proteinase 3 pyruvate kinase 3 ras related C3 botulinum toxin substrate 1 reg I R

NP_002924

resistin retinoic acid receptor responder 2 rho GDP dissociation inhibitor β ribonuclease A family 1

NP_002926

ribonuclease A family 3

NP_002945 NP_005971

ribosomal protein S27a S100 calcium binding protein P S100 calcium-binding protein A12 S100 calcium-binding protein A8 S100 calcium-binding protein A9 solute carrier family 2, member 3 spectrin β, nonerythrocytic 2 stomatin

NP_001166

NP_005612 NP_002955 NP_002956 NP_008862 NP_008877 NP_004090 XP_371167 NP_006397 NP_006746 NP_001054 NP_001055 NP_000362 NP_000356 NP_002762 NP_002760 NP_002761 NP_821133 NP_003290 NP_003371

1048

syncollin thioredoxin peroxidase (peroxiredoxin 4) transaldolase 1 transferrin transketolase transthyretin triosephosphate isomerase 1 trypsinigen IV trypsinogen 1 trypsinogen 2 tubulin, β 5 tumor rejection antigen (gp96) vimentin

biological process

molecular function

cellular component


cell communication

receptor ligand

extracellular

241

energy pathways protein metabolism immune response

enzyme (esterase) enzyme (aspartic protease) unclassified

plasma membrane extracellular extracellular

90 65 68

protein metabolism

chaperone activity

cytoplasm

66

cell communication

enzyme (serine-type peptidase) extracellular

immune response

receptor activity

plasma membrane

600

cell organization and biogenesis protein metabolism protein metabolism energy pathways cell communication


cytoplasm

256

enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (kinase) enzyme (GTPase)

extracellular lysosome cytoplasm cytoplasm

46 143 157 103

cell organization and biogenesis cell communication cell communication

extracellular matrix binding receptor ligand receptor activity

extracellular

383

extracellular cytoplasm

61 46

cell communication

soluble molecule recognition enzyme (ribonuclease)

cytoplasm

47

extracellular

62

34

regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism regulation of nucleobase, enzyme (ribonuclease) nucleoside, nucleotide and nucleic acid metabolism unclassified unclassified cell communication calcium ion binding

extracellular

142

ribosome cytoplasm

130 81

cell communication

calcium ion binding

cytoplasm

122

cell communication

calcium ion binding

extracellular

675

cell communication

calcium ion binding

cytoplasm

565

transport

plasma membrane

68

plasma membrane

90

plasma membrane

274

unclassified energy pathways

structural molecule activity structural molecule activity plasma membrane organization and biogenesis unclassified enzyme (peroxidase)

cytoplasm cytoplasm

energy pathways transport energy pathways transport energy pathways

enzyme (transaldolase) transporter activity enzyme (transkelotase) transporter activity enzyme (isomerase)

cytoplasm extracellular cytoplasm extracellular cytoplasm

46 2286 253 92 195

protein metabolism protein metabolism protein metabolism cell organization and biogenesis protein metabolism

enzyme (serine-type peptidase) enzyme (serine-type peptidase) enzyme (serine-type peptidase) structural molecule activity

extracellular extracellular extracellular cytoplasm

438 676 501 49

heat shock protein activity

endoplasmic reticulum cytoplasm

177

cell organization and biogenesis cell communication

cell organization and biogenesis



71 81

95

research articles

Proteomic Analysis of Human Pancreatic Juice Table 1 (Continued)

refseq no.

protein name

NP_000574 NP_003922

vitamin D binding protein wiskott aldrich syndrome protein family member 1 zinc R-2 glycoprotein

NP_001176

biological process

molecular function

cellular component

transport cell communication

transporter activity soluble molecule recognition

cytoplasm cytoplasm

regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism

enzyme (ribonuclease)

extracellular


528 50 98

out of three samples (sample A and C) with a MASCOT protein score of 104 and 828 in sample A and C, respectively. It is important to note that either commercial or previously characterized research ELISA reagents are already available for almost 20 of the “cancer-associated” proteins identified by us by LC/MS analysis of pancreatic juice, providing a fertile soil for biomarker discovery and validation for this lethal cancer. A summary of proteins identified in this study that were previously shown to be involved in various types of cancer is provided in Table 2.

Figure 2. Summary of proteins identified in this study. A Venn diagram indicating the number of proteins identified from each sample. A total of 254 proteins were identified from the three pancreatic juice samples of which 170 proteins were nonredundant.

Two interesting cancer associated proteins identified in pancreatic juice were Mac-2 binding protein and DMBT1. Mac-2 binding protein is a secreted glycoprotein that binds galectins, β1-integrins, collagens, and fibronectin, and is implicated in cell-cell and cell-extracellular matrix adhesion.32,33 Elevated serum levels of Mac-2 binding protein are often observed in patients with different types of solid tumors, including breast, ovarian, lung, and colorectal cancers, and are usually associated with a poor survival and metastatic spread in these malignancies.34-38 Overexpression of Mac-2 binding protein has been previously reported in pancreatic cancer tissues;26 this is the first report identifying this protein in pancreatic juice. Mac-2 binding protein was identified in two out of the three samples analyzed (sample A and C). In sample A, Mac-2 binding protein was identified with a very high MASCOT protein score (507) with 8 identified peptides while it was identified with a lower protein score in sample C (MASCOT protein score of 84 and two peptides identified). DMBT1 encodes an opsonin receptor, the gene is located on a region of chromosome 10q that is frequently deleted in gliomas and other malignant brain tumors.39 DMBT1 encoded protein is principally expressed in the lung, trachea, salivary gland, small intestine, and stomach.40 Curiously, while loss of its expression has been reported in several tumor types,41,42 a recent study suggests that this protein is overexpressed in pancreatic cancers.43 In fact, using a peptidomic approach to screen the conditioned media from pancreatic adenocarcinoma cell lines, Sasaki et al. identified a 29-residue carboxyl terminal fragment of DMBT1 that is secreted by pancreatic adenocarcinoma cell lines, but not by cell lines derived from normal pancreatic ductal epithelium.43 DMBT1 was identified in two

Identification of Human Syncollin as a Pancreatic Juice Constituent. Syncollin was initially identified in rats as a novel component of the zymogen granule membrane and its ability to bind to other membrane proteins, e.g., syntaxins 1 and 2.44 Syncollin is highly expressed in the pancreas in mouse, although it is either absent or expressed in very low levels in other secretary tissues.45 The exact function of syncollin is still not understood, although it has been suggested that it might play a role in the control of exocytotic membrane fusion in the pancreatic acinar cell and maturation of zymogens in zymogen granules.45 In addition, it has been suggested that syncollin might be a pore forming protein and its interaction with the zymogen granule glycoprotein (GP-2) might play a role in signal transduction across the granule membrane in rat.46,47 Because all human proteins have not yet been cloned and completely characterized, it is possible to miss them if a detailed bioinformatics analysis is not carried out. One very high scoring peptide with a continuous y-ion series of eight amino acids that we identified matched an entry derived from automatic annotation of the human genome, XP_371167. A bioinformatics analysis of this entry revealed that the encoded protein was 73% identical to the mouse protein called syncollin. BLAST analysis of the human protein that we identified against the human genome did not reveal the presence of any other similar protein. Thus, we conclude that the protein that we have identified is the human ortholog of mouse syncollin. Identification of human syncollin and confirmation of its presence in pancreatic juice will pave the way for more detailed study of this protein in humans. Identification of a Novel Protein, Designated PAP-2, that is Related to Hepatocarcinoma-Intestine Pancreas/Pancreatitis Associated Protein (HIP/PAP). One of the peptides that we identified (Figure 4) corresponded to a cDNA clone that was isolated in a high-throughput study.48 The aim of that study was to identify cDNAs encoding novel human secreted and transmembrane proteins by a combination of biological and bioinformatics strategies. A total number of 1021 cDNAs were identified of which 879 encoded secreted and transmembrane proteins and 136 encoded cytoplasmic and nuclear proteins. BLAST search against the non redundant (nr) database revealed that the protein sequence encoded by this cDNA was Journal of Proteome Research • Vol. 3, No. 5, 2004 1049

research articles

Grønborg et al.

Figure 3. MS/MS spectrum of Azurocidin and defensin R-3. MS/MS spectra of two peptides originating from proteins not previously described as constituents of pancreatic juice. Panel A show the fragment ions from a doubly charged precursor ion m/z 619.81 derived from azurocidin and panel B show the fragment ions from a doubly charged precursor ion m/z 559.27 originating from defensin R-3. Peaks corresponding to y and a2 b2 ions are marked. Table 2. List of Identified Proteins Whose Expression Has Previously Been Associated with Pancreatic Cancer and Other Cancers protein name

cancer

R fetoprotein annexin 5 annexin 1 carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM 5) carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) cystatin C deleted in malignant brain tumors 1 (DMBT 1) epidermal growth factor (EGF) fibronectin 1 mac-2 binding protein (Galectin 3 binding protein) hepatocarcinoma-intestine-pancreas/Pancreatitisassociated protein precursor I (HIP/PAP) insulin-like growth factor binding protein 2 (IGFBP-2) inter R inhibitor, heavy chain H1 inter R trypsin inhibitor, heavy chain 2 kallikrein 1 lactotransferrin lipocalin 2 (oncogene 24p3) lysosomal-associated membrane protein 2 (CD107b) lumican melanoma inhibitory activity (MIA) pepsinogen C profilin 1 prostasin S100 calcium binding protein P S100 calcium-binding protein A8 S100 calcium-binding protein A9 tumor rejection antigen (gp96)

gastric carcinoma, liver pancreas, pituitary pancreas, esophagus, pituitary, lung pancreas, lung, gastrointestinal, colorectal.

60, 61 62 16, 62-65 66-68

pancreas, lung, gastrointestinal, colorectal.

66, 67

pancreas, lung, gastrointestinal, colorectal.

66, 67, 69, 70

pancreas pancreas, brain, lung, colon, gastric colon pancreas pancreas, breast, colon pancreas, liver, cholangiocarcinoma cells

55 41-43 71, 72 16 37, 73-75 7, 76, 77

pancreas, CSF, serum, prostate gland, liver lung stomach ovarian, kidney colon, uterus pancreas pancreas pancreas pancreas pancreas, breast, prostate pancreas prostate, breast, ovarian pancreas gastric, skin gastric, skin esophagus, colon

55, 61, 78-80 81 82 83, 84 85-87 55 26 53 54, 55 55, 88, 89 55 90-92 54, 55 93, 94 93, 94 95, 96

85% identical to the protein sequence of hepatocarcinoma intestine pancreas/pancreatitis associated protein (HIP/PAP). We have, therefore, designated this protein as PAP-2. As previously discussed, HIP/PAP has recently been identified as a novel biomarker for pancreatic adenocarcinoma.7 Serum and pancreatic juice obtained from cancer and control patients were initially screened by SELDI mass spectrometry and differentially expressed proteins were subsequently identified by protein chip immunoassay. Quantification by ELISA revealed that HIP/PAP was significant upregulated in serum and pan1050


reference

creatic juice in patients with pancreatic adenocarcinoma when compared to control patients. In addition, HIP/PAP levels were found to be a 1000-fold higher in pancreatic juice compared to serum.7 Pancreatic juice measurements of HIP/PAP can therefore be used as a biomarker to identity patients with pancreatic adenocarcinoma.7 Four different REG family member genes in humans were initially described as a family; these included genes encoding REG I-R, REG I-β, REG-related sequence (RS) and HIP/PAP.49 More recently, an additional member, Reg IV, has been


research articles

Figure 4. MS/MS spectrum of a peptide derived from a novel protein, PAP-2. MS/MS spectrum of a peptide derived from a novel protein PAP-2. The spectrum shows the fragment ions from a doubly charged precursor ion m/z 855.46 that permitted assignment of the sequence of the peptide from PAP-2. The ions are marked as in Figure 3.

reported.50 A multiple sequence alignment revealed that PAP-2 was 85% identical to HIP/PAP, 48% identical to Regenerating protein 1 R (Reg I-R), 47% identical to Regenerating protein 1 β (Reg I-β) and even more distantly related to Reg IV (Figure 5A). Reg-related sequence (RS) was not included in the multiple alignment because it contains an in-frame stop codon in the cDNA producing a truncated protein of only 42 amino acids.49 Amino acids are marked in red in Figure 5A wherever a minimum of three sequences was identical. A high degree of identity is clearly seen among the proteins. The cladogram shows that PAP-2 is most closely related to HIP/PAP and Reg I R is related to Reg I β, whereas Reg IV is not closely related to either of these two subfamilies (Figure 5B). PAP-2 was identified in two out of the three samples (A and B) with a MASCOT protein score of 330 and 47, respectively. We identified four unique peptides originating from PAP-2 in sample A and one unique peptide from PAP-2 in sample B corresponding to a sequence coverage of 33% and 10%, respectively. It is tempting to speculate that PAP-2 could also turn out to be a biomarker for pancreatic cancer. However, detailed studies will be required to fully characterize this molecule and to determine its utility as a biomarker for pancreatic cancer. Functional Annotation of Proteins Identified from Pancreatic Juice. One of our goals was to discover novel components of the ‘human pancreatic juice proteome’ in order to identify potentially new biomarkers for pancreatic cancer. To gain a better understanding of the 170 proteins identified in this study, a functional annotation analysis of all the proteins was carried out. This annotation was carried out by scientists at the Institute of Bioinformatics (http:// www.ibioinformatics.org) and all the annotated proteins were deposited in the Human Protein Reference Database (HPRD, http://www.hprd.org).51 Grouping and naming of the identified proteins in the functional annotation analysis was done according to the Gene

Figure 5. Alignment of PAP-2 and other members of the Reg family. Panel A shows a multiple alignment of the novel protein, PAP-2, with HIP/PAP, regenerating protein 1 R (Reg 1 R), regenerating protein 1 β (Reg 1 β) and Reg IV. PAP-2 is 85% identical to HIP/PAP and 48% and 47% identical to Reg 1 R and Reg 1 β, respectively. Amino acids are marked in red when a minimum of three out of five sequences was identical. Panel B shows a cladogram of the five proteins shown in Panel A demonstrating that HIP/PAP and PAP-2 belong to the same subfamily whereas Reg 1 R and Reg 1 β belong to a different subfamily and Reg IV is not related to either of these two subfamilies.

Ontology (GO) convention.52 Information for the three ontologies (biological process, molecular function, and cellular component) was collected from the 170 identified proteins. Biological process assignment included: (1) cell communication, (2) transport, (3) regulation of nucleobase, nucleoside, nucleoJournal of Proteome Research • Vol. 3, No. 5, 2004 1051

research articles

Figure 6. Distribution of the identified proteins based on biological process. The pie chart depicts the distribution of the biological processes among the 170 unique proteins that were identified.

Figure 7. Distribution of the identified proteins based on molecular function. The pie chart depicts the distribution of the molecular function among the identified proteins.

tide and nucleic acid metabolism, (4) protein metabolism, (5) immune response, (6) energy pathways, (7) cell organization and biogenesis and (8) unclassified as shown in Figure 6. The largest fraction of proteins (24%) was classified under “protein metabolism” whereas only 5% of the identified proteins could not be classified. The rest of the proteins were classified into subgroups of almost equal sizes except for proteins involved in regulation of nucleic acid metabolism, which only constituted 6% of the total number of identified proteins. Molecular function provides a more detailed description of the actual function of the identified proteins (Figure 7). The proteins were divided into 17 different subgroups and, as expected, enzymes turned out to be the major subgroup of the identified proteins (32%). Since proteolytic digestion is one of the major tasks of pancreas, it is not surprisingly that a large part of the identified proteins are various enzymes. Several other subgroups turned out to be significant including transport activity (13%), structural molecules (10%), complement factors (6%), and protease inhibitors (5%). The majority of the functions of the identified proteins correlate well with their presence in pancreatic juice. Some groups of proteins (e.g., DNA binding and heat shock protein) are perhaps derived from the lysis or turnover of cells. Since enzymes represented a large part of the identified proteins in our study, we decided to classify them according 1052


Grønborg et al.

Figure 8. Distribution of the identified enzymes based on enzyme categories. The pie chart depicts the distribution of enzyme categories among the enzymes identified in this study.

Figure 9. Distribution of the identified proteins based on cellular component. The pie chart depicts the distribution of the cellular component among the identified proteins.

to their enzymatic function. The enzymes were divided into a total of 27 subgroups. As shown in Figure 8, proteases represented the majority of the identified enzymes (52%) with serine proteases comprising 33% and other types of proteases (e.g., aminopeptidase, hydrolase, aspartic protease, carboxypeptidase, metalloproteases), constituting the remaining 20%. The high percentage of proteases is not surprising since the major function of pancreas is proteolytic digestion. The rest of the enzymes were distributed in small subgroups with each representing less than 4% of the enzymes identified. Cellular component provides information about subcellular localization of the identified proteins (Figure 9). As expected, a majority (62%) of all proteins identified from pancreatic juice were known to be extracellular or bound to the plasma membrane. Comparison of Protein and mRNA Expression Data. A number of the proteins identified from pancreatic juice in this study are the products of genes that have been previously identified as overexpressed in pancreatic cancers or other pancreatic neoplasms. Some of us have previously carried out studies to examine pancreatic adenocarcinoma as well as premalignant lesions such as intraductal papillary mucinous pancreatic neoplasms (IPMN) using serial analysis of gene expression (SAGE), oligonucleotide and cDNA microarrays.16,17,53-55 Therefore, we wished to determine if any of the proteins identified in this study previously were found to be

research articles


Table 3. Proteins Identified by Our Proteomic Approach that Were Previously Found to Be Overexpressed in Pancreatic Neoplasms at the MRNA Level

protein name

annexin 1 carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) carcinoembryonic antigen-related cell adhesion molecule 6 (CEACAM6) cystatin C enolase 1 fibronectin 1 mac-2 binding protein (Galectin 3 binding protein) hepatocarcinoma-intestine-pancreas/ Pancreatitis-associated protein precursor I (HIP/PAP) insulin-like growth factor binding protein 2 (IGFBP-2) keratin 8 lipocalin 2 (oncogene 24p3) lumican melanoma inhibitory activity (MIA) pepsinogen C profilin 1 S100P

fold increase in expression in pancreatic adenocarcinoma

fold increase in expression in intraductal papillary mucinous neoplasm

references

6 13

N/A N/A

16, 17, 54 56

59

20

16, 54, 55

182

N/A

54-57

upregulated upregulated 7 upregulated

42 N/A N/A N/A

54, 55 16 16, 17 16

upregulated

N/A

7

not available

47

upregulated 9

N/A 5.5

16 16, 17, 54, 55

upregulated N/A N/A N/A 22

N/A 48 48 118 378

53 55 55 55 16, 17, 54-56

upregulated at the transcript level. Indeed, we found the transcripts of several molecules to be upregulated in both pancreatic adenocarcinomas as well as IPMNs as shown in Table 3. The CEACAM family of proteins (CEACAM1, CEACAM5, and CEACAM6) was found to be highly upregulated at the mRNA level in pancreatic adenocarcinomas and CEACAM 5 was also found to be upregulated in IPMNs. Interestingly, the S100P gene was found to be upregulated by a factor of 22 in pancreatic cancer compared to normal pancreas tissues, whereas it was upregulated 378-fold in IPMNs when compared to normal pancreas.55,56 A number of other proteins that we have identified in this study were also found to be overexpressed including pepsinogen C and melanoma inhibitory activity (MIA), CEACAM6, annexin A1, and lipocalin 2.16,17,53-55,57 Overall, our study clearly shows that proteomic data can be used to validate gene expression microarray data. However, it must be pointed out that the two approaches are complementary and that this study only allows confirmation of the presence of proteins in pancreatic juice and not their relative expression level in cancers as compared to controls.

Conclusions To the best of our knowledge, this is the first report detailing the proteome of human pancreatic juice. Here, we present a comprehensive proteomic analysis of pancreatic juice from patients with pancreatic adenocarcinoma using a combination of 1D gel electrophoresis and LC-MS/MS analysis. Our goal was to establish a catalog of pancreatic juice constituents and reasoned that it is likely that the local concentration of putative diagnostic markers for pancreatic cancers is higher in pancreatic juice than in more accessible and complex body fluids such as serum. Once such a catalog is available, more directed studies to validate individual proteins in serum of pancreatic cancer can be carried out.

55

We identified a total of 170 unique proteins in our analysis. In addition to several known markers for pancreatic cancer, we identified a novel protein, designated as PAP-2, which is 85% identical to a recently discovered biomarker for pancreatic adenocarcinoma HIP/PAP.7 Because a large amount of data from SAGE, oligonucleotide and cDNA microarrays is already available, we were able to compare our results with those reported by previous studies. We identified several proteins that were shown to be upregulated at the mRNA level in pancreatic adenocarcinoma and IPMN. This clearly shows that proteomics studies can be used to confirm gene expression data for identification of potential biomarkers. We believe that the catalog of pancreatic juice proteins generated in this study is merely a starting point. Quantitative proteomic analysis using reagents such as ICAT58 or 18O labeling59 will help identify biomarkers for pancreatic cancer that could be subsequently validated in a larger patient population by more highthroughput methods such as ELISA.

Acknowledgment. Partially funded by the family of Margaret Lee and NCI SPORE P50 CA 62924. Akhilesh Pandey is supported by a Sidney Kimmel Scholar Award from the Sidney Kimmel Foundation for Cancer Research. A.M. is supported by a grant from the Cancer Research Foundation of America, and a Johns Hopkins Clinical Scientist Award. Jakob Bunkenborg was supported by a postdoctoral fellowship from the Danish Natural Sciences Research Council. We thank scientists at the Institute of Bioinformatics in Bangalore, India for carrying out the annotations of the proteins identified in this study. References (1) Greenlee, R. T.; Hill-Harmon, M. B.; Murray, T.; Thun, M. CA Cancer J. Clin. 2001, 51, 15-36.


research articles (2) Yeo, T. P.; Hruban, R. H.; Leach, S. D.; Wilentz, R. E.; Sohn, T. A.; Kern, S. E.; Iacobuzio-Donahue, C. A.; Maitra, A.; Goggins, M.; Canto, M. I.; Abrams, R. A.; Laheru, D.; Jaffee, E. M.; Hidalgo, M.; Yeo, C. J. Curr. Probl. Cancer 2002, 26, 176-275. (3) Rosty, C.; Goggins, M. Hematol. Oncol. Clin. North Am. 2002, 16, 37-52. (4) Srinivas, P. R.; Srivastava, S.; Hanash, S.; Wright, G. L., Jr. Clin. Chem. 2001, 47, 1901-1911. (5) Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. A. Lancet 2002, 359, 572-577. (6) Hanash, S. Proteomics 2001, 1, 1189-1190. (7) Rosty, C.; Christa, L.; Kuzdzal, S.; Baldwin, W. M.; Zahurak, M. L.; Carnot, F.; Chan, D. W.; Canto, M.; Lillemoe, K. D.; Cameron, J. L.; Yeo, C. J.; Hruban, R. H.; Goggins, M. Cancer Res. 2002, 62, 1868-1875. (8) Verma, M.; Wright, G. L., Jr.; Hanash, S. M.; Gopal-Srivastava, R.; Srivastava, S. Ann. N. Y. Acad. Sci. 2001, 945, 103-115. (9) Koopmann, J.; Fedarko, N. S.; Jain, A.; Maitra, A.; IacobuzioDonahue, C.; Rahman, A.; Hruban, R. H.; Yeo, C. J.; Goggins, M. Cancer Epidemiol. Biomarkers Prev. 2004, 13, 487-491. (10) Mann, M.; Hendrickson, R. C.; Pandey, A. Annu. Rev. Biochem. 2001, 70, 437-473. (11) Pandey, A.; Mann, M. Nature 2000, 405, 837-846. (12) Shevchenko, A.; Wilm, M.; Vorm, O.; Mann, M. Anal. Chem. 1996, 68, 850-858. (13) Lignelid, H.; Jacobsson, B. Virchows Arch. A Pathol. Anat. Histopathol. 1992, 421, 491-495. (14) Minn, A. H.; Patterson, N. B.; Pack, S.; Hoffmann, S. C.; Gavrilova, O.; Vinson, C.; Harlan, D. M.; Shalev, A. Biochem. Biophys. Res. Commun. 2003, 310, 641-645. (15) Bartoli, C.; Gharib, B.; Giorgi, D.; Sansonetti, A.; Dagorn, J. C.; Berge-Lefranc, J. L. FEBS Lett. 1993, 327, 289-293. (16) Iacobuzio-Donahue, C. A.; Maitra, A.; Olsen, M.; Lowe, A. W.; van Heek, N. T.; Rosty, C.; Walter, K.; Sato, N.; Parker, A.; Ashfaq, R.; Jaffee, E.; Ryu, B.; Jones, J.; Eshleman, J. R.; Yeo, C. J.; Cameron, J. L.; Kern, S. E.; Hruban, R. H.; Brown, P. O.; Goggins, M. Am. J. Pathol. 2003, 162, 1151-1162. (17) Iacobuzio-Donahue, C. A.; Maitra, A.; Shen-Ong, G. L.; van Heek, T.; Ashfaq, R.; Meyer, R.; Walter, K.; Berg, K.; Hollingsworth, M. A.; Cameron, J. L.; Yeo, C. J.; Kern, S. E.; Goggins, M.; Hruban, R. H. Am. J. Pathol. 2002, 160, 1239-1249. (18) Gress, T. M.; Wallrapp, C.; Frohme, M.; Muller-Pillasch, F.; Lacher, U.; Friess, H.; Buchler, M.; Adler, G.; Hoheisel, J. D. Genes Chromosomes Cancer 1997, 19, 97-103. (19) Furutani, M.; Arii, S.; Mizumoto, M.; Kato, M.; Imamura, M. Cancer Lett. 1998, 122, 209-214. (20) Ringel, J.; Lohr, M. Mol. Cancer 2003, 2, 9. (21) Hollingsworth, M. A. Ann. N. Y. Acad. Sci. 1999, 880, 38-49. (22) Truan, N.; Vizoso, F.; Fresno, M. F.; Fernandez, R.; Quintela, I.; Alexandre, E.; Martinez, A. Int. J. Biol. Markers 2001, 16, 31-36. (23) Xie, M. J.; Motoo, Y.; Su, S. B.; Mouri, H.; Ohtsubo, K.; Matsubara, F.; Sawabu, N. Pancreas 2002, 25, 234-238. (24) Ping Lu, Y.; Ishiwata, T.; Asano, G. J. Pathol. 2002, 196, 324-330. (25) Crnogorac-Jurcevic, T.; Efthimiou, E.; Capelli, P.; Blaveri, E.; Baron, A.; Terris, B.; Jones, M.; Tyson, K.; Bassi, C.; Scarpa, A.; Lemoine, N. R. Oncogene 2001, 20, 7437-7446. (26) Kunzli, B. M.; Berberat, P. O.; Zhu, Z. W.; Martignoni, M.; Kleeff, J.; Tempia-Caliera, A. A.; Fukuda, M.; Zimmermann, A.; Friess, H.; Buchler, M. W. Cancer 2002, 94, 228-239. (27) Crnogorac-Jurcevic, T.; Missiaglia, E.; Blaveri, E.; Gangeswaran, R.; Jones, M.; Terris, B.; Costello, E.; Neoptolemos, J. P.; Lemoine, N. R. J. Pathol. 2003, 201, 63-74. (28) Cunliffe, R. N. Mol. Immunol. 2003, 40, 463-467. (29) Zhao, C.; Wang, I.; Lehrer, R. I. FEBS Lett. 1996, 396, 319-322. (30) Lee, T. D.; Gonzalez, M. L.; Kumar, P.; Chary-Reddy, S.; Grammas, P.; Pereira, H. A. Am. J. Pathol. 2002, 160, 841-848. (31) Watorek, W. Acta Biochim. Pol. 2003, 50, 743-752. (32) Koths, K.; Taylor, E.; Halenbeck, R.; Casipit, C.; Wang, A. J. Biol. Chem. 1993, 268, 14 245-14 249. (33) Inohara, H.; Akahani, S.; Koths, K.; Raz, A. Cancer Res. 1996, 56, 4530-4534. (34) Marchetti, A.; Tinari, N.; Buttitta, F.; Chella, A.; Angeletti, C. A.; Sacco, R.; Mucilli, F.; Ullrich, A.; Iacobelli, S. Cancer Res. 2002, 62, 2535-2539. (35) Fusco, O.; Querzoli, P.; Nenci, I.; Natoli, C.; Brakebush, C.; Ullrich, A.; Iacobelli, S. Int. J. Cancer 1998, 79, 23-26. (36) D′Ostilio, N.; Natoli, C.; Grassadonia, A.; Rossi, N.; Di Stefano, P.; Amatetti, C.; Tinari, N.; Iacobelli, S. Ann. N. Y. Acad. Sci. 1996, 784, 288-293.

1054


Grønborg et al. (37) Iacobelli, S.; Arno, E.; D’Orazio, A.; Coletti, G. Cancer Res. 1986, 46, 3005-3010. (38) Scambia, G.; Panici, P. B.; Baiocchi, G.; Perrone, L.; Iacobelli, S.; Mancuso, S. Anticancer Res. 1988, 8, 761-764. (39) Mollenhauer, J.; Wiemann, S.; Scheurlen, W.; Korn, B.; Hayashi, Y.; Wilgenbus, K. K.; von Deimling, A.; Poustka, A. Nat. Genet. 1997, 17, 32-39. (40) Holmskov, U.; Mollenhauer, J.; Madsen, J.; Vitved, L.; Gronlund, J.; Tornoe, I.; Kliem, A.; Reid, K. B.; Poustka, A.; Skjodt, K. Proc. Natl. Acad. Sci. U. S. A. 1999, 96, 10 794-10 799. (41) Mori, M.; Shiraishi, T.; Tanaka, S.; Yamagata, M.; Mafune, K.; Tanaka, Y.; Ueo, H.; Barnard, G. F.; Sugimachi, K. Br. J. Cancer 1999, 79, 211-213. (42) Wu, W.; Kemp, B. L.; Proctor, M. L.; Gazdar, A. F.; Minna, J. D.; Hong, W. K.; Mao, L. Cancer Res. 1999, 59, 1846-1851. (43) Sasaki, K.; Sato, K.; Akiyama, Y.; Yanagihara, K.; Oka, M.; Yamaguchi, K. Cancer Res. 2002, 62, 4894-4898. (44) Edwardson, J. M.; An, S.; Jahn, R. Cell 1997, 90, 325-333. (45) Antonin, W.; Wagner, M.; Riedel, D.; Brose, N.; Jahn, R. Mol. Cell Biol. 2002, 22, 1545-1554. (46) Hodel, A.; An, S. J.; Hansen, N. J.; Lawrence, J.; Wasle, B.; Schrader, M.; Edwardson, J. M. Biochem. J. 2001, 356, 843-850. (47) Kalus, I.; Hodel, A.; Koch, A.; Kleene, R.; Edwardson, J. M.; Schrader, M. Biochem. J. 2002, 362, 433-442. (48) Clark, H. F.; Gurney, A. L.; Abaya, E.; Baker, K.; Baldwin, D.; Brush, J.; Chen, J.; Chow, B.; Chui, C.; Crowley, C.; Currell, B.; Deuel, B.; Dowd, P.; Eaton, D.; Foster, J.; Grimaldi, C.; Gu, Q.; Hass, P. E.; Heldens, S.; Huang, A.; Kim, H. S.; Klimowski, L.; Jin, Y.; Johnson, S.; Lee, J.; Lewis, L.; Liao, D.; Mark, M.; Robbie, E.; Sanchez, C.; Schoenfeld, J.; Seshagiri, S.; Simmons, L.; Singh, J.; Smith, V.; Stinson, J.; Vagts, A.; Vandlen, R.; Watanabe, C.; Wieand, D.; Woods, K.; Xie, M. H.; Yansura, D.; Yi, S.; Yu, G.; Yuan, J.; Zhang, M.; Zhang, Z.; Goddard, A.; Wood, W. I.; Godowski, P.; Gray, A. Genome Res. 2003, 13, 2265-2270. (49) Miyashita, H.; Nakagawara, K.; Mori, M.; Narushima, Y.; Noguchi, N.; Moriizumi, S.; Takasawa, S.; Yonekura, H.; Takeuchi, T.; Okamoto, H. FEBS Lett. 1995, 377, 429-433. (50) Hartupee, J. C.; Zhang, H.; Bonaldo, M. F.; Soares, M. B.; Dieckgraefe, B. K. Biochim. Biophys. Acta 2001, 1518, 287-293. (51) Peri, S.; Navarro, J. D.; Amanchy, R.; Kristiansen, T. Z.; Jonnalagadda, C. K.; Surendranath, V.; Niranjan, V.; Muthusamy, B.; Gandhi, T. K.; Gronborg, M.; Ibarrola, N.; Deshpande, N.; Shanker, K.; Shivashankar, H. N.; Rashmi, B. P.; Ramya, M. A.; Zhao, Z.; Chandrika, K. N.; Padma, N.; Harsha, H. C.; Yatish, A. J.; Kavitha, M. P.; Menezes, M.; Choudhury, D. R.; Suresh, S.; Ghosh, N.; Saravana, R.; Chandran, S.; Krishna, S.; Joy, M.; Anand, S. K.; Madavan, V.; Joseph, A.; Wong, G. W.; Schiemann, W. P.; Constantinescu, S. N.; Huang, L.; Khosravi-Far, R.; Steen, H.; Tewari, M.; Ghaffari, S.; Blobe, G. C.; Dang, C. V.; Garcia, J. G.; Pevsner, J.; Jensen, O. N.; Roepstorff, P.; Deshpande, K. S.; Chinnaiyan, A. M.; Hamosh, A.; Chakravarti, A.; Pandey, A. Genome Res. 2003, 13, 2363-2371. (52) Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H.; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T.; Harris, M. A.; Hill, D. P.; Issel-Tarver, L.; Kasarskis, A.; Lewis, S.; Matese, J. C.; Richardson, J. E.; Ringwald, M.; Rubin, G. M.; Sherlock, G. Nat. Genet. 2000, 25, 25-29. (53) Ryu, B.; Jones, J.; Hollingsworth, M. A.; Hruban, R. H.; Kern, S. E. Cancer Res. 2001, 61, 1833-1838. (54) Iacobuzio-Donahue, C. A.; Ashfaq, R.; Maitra, A.; Adsay, N. V.; Shen-Ong, G. L.; Berg, K.; Hollingsworth, M. A.; Cameron, J. L.; Yeo, C. J.; Kern, S. E.; Goggins, M.; Hruban, R. H. Cancer Res. 2003, 63, 8614-8622. (55) Sato, N.; Fukushima, N.; Maitra, A.; Iacobuzio-Donahue, C. A.; van Heek, N. T.; Cameron, J. L.; Yeo, C. J.; Hruban, R. H.; Goggins, M. Am. J. Pathol. 2004, 164, 903-914. (56) Logsdon, C. D.; Simeone, D. M.; Binkley, C.; Arumugam, T.; Greenson, J. K.; Giordano, T. J.; Misek, D. E.; Kuick, R.; Hanash, S. Cancer Res. 2003, 63, 2649-2657. (57) Ryu, B.; Jones, J.; Blades, N. J.; Parmigiani, G.; Hollingsworth, M. A.; Hruban, R. H.; Kern, S. E. Cancer Res. 2002, 62, 819-826. (58) Gygi, S. P.; Rist, B.; Gerber, S. A.; Turecek, F.; Gelb, M. H.; Aebersold, R. Nat. Biotechnol. 1999, 17, 994-999. (59) Yao, X.; Freas, A.; Ramirez, J.; Demirev, P. A.; Fenselau, C. Anal. Chem. 2001, 73, 2836-2842. (60) McIntire, K. R.; Waldmann, T. A.; Moertel, C. G.; Go, V. L. Cancer Res. 1975, 35, 991-996. (61) Cariani, E.; Lasserre, C.; Kemeny, F.; Franco, D.; Brechot, C. Hepatology 1991, 13, 644-649. (62) Mulla, A.; Christian, H. C.; Solito, E.; Mendoza, N.; Morris, J. F.; Buckingham, J. C. Clin. Endocrinol. (Oxf) 2004, 60, 107-119.

research articles

Proteomic Analysis of Human Pancreatic Juice (63) Wang, Y.; Serfass, L.; Roy, M. O.; Wong, J.; Bonneau, A. M.; Georges, E. Biochem. Biophys. Res. Commun. 2004, 314, 565570. (64) Fang, M. Z.; Liu, C.; Song, Y.; Yang, G. Y.; Nie, Y.; Liao, J.; Zhao, X.; Shimada, Y.; Wang, L. D.; Yang, C. S. Carcinogenesis 2004. (65) Pencil, S. D.; Toth, M. Clin. Exp. Metastasis 1998, 16, 113-121. (66) Kodera, Y.; Isobe, K.; Yamauchi, M.; Satta, T.; Hasegawa, T.; Oikawa, S.; Kondoh, K.; Akiyama, S.; Itoh, K.; Nakashima, I.; et al. Br. J. Cancer 1993, 68, 130-136. (67) Hasegawa, T.; Isobe, K.; Tsuchiya, Y.; Oikawa, S.; Nakazato, H.; Nakashima, I.; Shimokata, K. Br. J. Cancer 1993, 67, 58-65. (68) Sienel, W.; Dango, S.; Woelfle, U.; Morresi-Hauf, A.; Wagener, C.; Brummer, J.; Mutschler, W.; Passlick, B.; Pantel, K. Clin. Cancer Res. 2003, 9, 2260-2266. (69) Scholzel, S.; Zimmermann, W.; Schwarzkopf, G.; Grunert, F.; Rogaczewski, B.; Thompson, J. Am. J. Pathol. 2000, 156, 595605. (70) Duxbury, M. S.; Ito, H.; Zinner, M. J.; Ashley, S. W.; Whang, E. E. Oncogene 2004, 23, 465-473. (71) Rajagopal, S.; Huang, S.; Moskal, T. L.; Lee, B. N.; el-Naggar, A. K.; Chakrabarty, S. Int. J. Cancer 1995, 62, 661-667. (72) Messa, C.; Russo, F.; Caruso, M. G.; Di Leo, A. Acta Oncol 1998, 37, 285-289. (73) Iacobelli, S.; Arno, E.; Sismondi, P.; Natoli, C.; Gentiloni, N.; Scambia, G.; Giai, M.; Cortese, P.; Panici, P. B.; Mancuso, S. Breast Cancer Res. Treat. 1988, 11, 19-30. (74) Iacobelli, S.; Bucci, I.; D’Egidio, M.; Giuliani, C.; Natoli, C.; Tinari, N.; Rubistein, M.; Schlessinger, J. FEBS Lett. 1993, 319, 59-65. (75) Iacobelli, S.; Sismondi, P.; Giai, M.; D’Egidio, M.; Tinari, N.; Amatetti, C.; Di Stefano, P.; Natoli, C. Br. J. Cancer 1994, 69, 172176. (76) Christa, L.; Simon, M. T.; Brezault-Bonnet, C.; Bonte, E.; Carnot, F.; Zylberberg, H.; Franco, D.; Capron, F.; Roskams, T.; Brechot, C. Am. J. Pathol. 1999, 155, 1525-1533. (77) Christa, L.; Carnot, F.; Simon, M. T.; Levavasseur, F.; Stinnakre, M. G.; Lasserre, C.; Thepot, D.; Clement, B.; Devinoy, E.; Brechot, C. Am. J. Physiol. 1996, 271, G993-1002. (78) Muller, H. L.; Oh, Y.; Lehrnbecher, T.; Blum, W. F.; Rosenfeld, R. G. J. Clin. Endocrinol. Metab. 1994, 79, 428-434. (79) Cohen, P. J. Natl. Cancer Inst. 1998, 90, 876-879. (80) Ho, P. J.; Baxter, R. C. Clin. Endocrinol. (Oxf) 1997, 46, 333-342. (81) Bourguignon, J.; Borghi, H.; Sesboue, R.; Diarra-Mehrpour, M.; Bernaudin, J. F.; Metayer, J.; Martin, J. P.; Thiberville, L. J. Histochem. Cytochem. 1999, 47, 1625-1632.

(82) Nishino, N.; Aoki, K.; Tokura, Y.; Sakaguchi, S.; Fujie, M.; Sugawara, Y.; Takada, Y.; Takada, A. Haemostasis 1989, 19, 112119. (83) Diamandis, E. P.; Scorilas, A.; Fracchioli, S.; Van Gramberen, M.; De Bruijn, H.; Henrik, A.; Soosaipillai, A.; Grass, L.; Yousef, G. M.; Stenman, U. H.; Massobrio, M.; Van Der Zee, A. G.; Vergote, I.; Katsaros, D. J. Clin. Oncol. 2003, 21, 1035-1043. (84) Rae, F.; Bulmer, B.; Nicol, D.; Clements, J. Immunopharmacology 1999, 45, 83-88. (85) DePrimo, S. E.; Wong, L. M.; Khatry, D. B.; Nicholas, S. L.; Manning, W. C.; Smolich, B. D.; O’Farrell, A. M.; Cherrington, J. M. BMC Cancer 2003, 3, 3. (86) Damiens, E.; El Yazidi, I.; Mazurier, J.; Duthille, I.; Spik, G.; BoillyMarer, Y. J. Cell Biochem. 1999, 74, 486-498. (87) Walmer, D. K.; Padin, C. J.; Wrona, M. A.; Healy, B. E.; Bentley, R. C.; Tsao, M. S.; Kohler, M. F.; McLachlan, J. A.; Gray, K. D. Cancer Res. 1995, 55, 1168-1175. (88) Sanchez, L. M.; Freije, J. P.; Merino, A. M.; Vizoso, F.; Foltmann, B.; Lopez-Otin, C. J. Biol. Chem. 1992, 267, 24725-24731. (89) Diaz, M.; Rodriguez, J. C.; Sanchez, J.; Sanchez, M. T.; Martin, A.; Merino, A. M.; Vizoso, F. Int. J. Biol. Markers 2002, 17, 125-129. (90) Takahashi, S.; Suzuki, S.; Inaguma, S.; Ikeda, Y.; Cho, Y. M.; Hayashi, N.; Inoue, T.; Sugimura, Y.; Nishiyama, N.; Fujita, T.; Chao, J.; Ushijima, T.; Shirai, T. Prostate 2003, 54, 187-193. (91) Chen, L. M.; Chai, K. X. Int. J. Cancer 2002, 97, 323-329. (92) Mok, S. C.; Chao, J.; Skates, S.; Wong, K.; Yiu, G. K.; Muto, M. G.; Berkowitz, R. S.; Cramer, D. W. J. Natl. Cancer Inst. 2001, 93, 1458-1464. (93) El-Rifai, W.; Moskaluk, C. A.; Abdrabbo, M. K.; Harper, J.; Yoshida, C.; Riggins, G. J.; Frierson, H. F., Jr.; Powell, S. M. Cancer Res. 2002, 62, 6823-6826. (94) Gebhardt, C.; Breitenbach, U.; Tuckermann, J. P.; Dittrich, B. T.; Richter, K. H.; Angel, P. Oncogene 2002, 21, 4266-4276. (95) Zhou, G.; Li, H.; DeCamp, D.; Chen, S.; Shu, H.; Gong, Y.; Flaig, M.; Gillespie, J. W.; Hu, N.; Taylor, P. R.; Emmert-Buck, M. R.; Liotta, L. A.; Petricoin, E. F., 3rd; Zhao, Y. Mol. Cell Proteomics 2002, 1, 117-124. (96) Sasatomi, T.; Yamana, H.; Shichijo, S.; Tanaka, S.; Okamura, T.; Ogata, Y.; Itoh, K.; Shirouzu, K. Dis. Colon Rectum 2000, 43, 1754-1758.

PR0499085


Comprehensive Proteomic Analysis of Human Pancreatic Juice

Recommend Documents