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. Author manuscript; available in PMC: 2008 Jun 9.
Published in final edited form as: Pancreas. 2007 Jan;34(1):70–79. doi: 10.1097/01.mpa.0000240615.20474.fd

Comparison of Pancreas Juice Proteins from Cancer Versus Pancreatitis Using Quantitative Proteomic Analysis

Ru Chen *, Sheng Pan , Kelly Cooke , Kara White Moyes *, Mary P Bronner , David R Goodlett §, Ruedi Aebersold ||, Teresa A Brentnall *
PMCID: PMC2423229  NIHMSID: NIHMS50761  PMID: 17198186

Abstract

Objectives

Pancreatitis is an inflammatory condition of the pancreas. However, it often shares many molecular features with pancreatic cancer. Biomarkers present in pancreatic cancer frequently occur in the setting of pancreatitis. The efforts to develop diagnostic biomarkers for pancreatic cancer have thus been complicated by the false-positive involvement of pancreatitis.

Methods

In an attempt to develop protein biomarkers for pancreatic cancer, we previously use quantitative proteomics to identify and quantify the proteins from pancreatic cancer juice. Pancreatic juice is a rich source of proteins that are shed by the pancreatic ductal cells. In this study, we used a similar approach to identify and quantify proteins from pancreatitis juice.

Results

In total, 72 proteins were identified and quantified in the comparison of pancreatic juice from pancreatitis patients versus pooled normal control juice. Nineteen of the juice proteins were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold compared with normal pancreatic juice. Of these 27 differentially expressed proteins in pancreatitis, 9 proteins were also differentially expressed in the pancreatic juice from pancreatic cancer patient.

Conclusions

Identification of these differentially expressed proteins from pancreatitis juice provides useful information for future study of specific pancreatitis-associated proteins and to eliminate potential false-positive biomarkers for pancreatic cancer.

Keywords: pancreatic juice, pancreatitis, ICAT, biomarker, pancreatic cancer, proteomics


Pancreatic cancer is a highly lethal disease.1,2 The death rate nearly matches the incidence because the diagnosis usually occurs late, after metastases have occurred, and the only chance for a cure (ie, surgical excision) has been eliminated. The problem of early diagnosis is complicated by the obscure location of the pancreas, the absence of reliable symptoms, and the insensitivity and expense of current tests. Better methods of detecting early stages of cancer or precancerous lesions are needed.

In the efforts to develop biomarkers for the early detection of pancreatic cancer, one of the problems is the false-positive involvement of pancreatitis patients. Pancreatitis is an inflammatory condition of the pancreas that shares many molecular features with pancreatic cancer. Thus, biomarkers present in the setting of pancreatic cancer frequently occur in pancreatitis, providing an unacceptably low level of specificity for screening. It is therefore important to understand the proteins that underlie pancreatitis, as they could be a source of false-positive biomarkers for pancreatic cancer. Moreover, chronic pancreatitis is risk factor for eventual neoplastic progression; thus, understanding the proteins involved in both diseases may yield some insights into the mechanisms that link these events.

Recently, there has been substantial interest in applying proteomic methods for the discovery of new targets for therapeutics and new biomarkers for diagnosis and early detection.3 In particular, quantitative proteomics has enabled researchers to use a combination of biochemistry, biology, and bioinformatics to detect proteins that are differentially expressed in cancer. In pancreatic cancer, recent studies using proteomics approach have focused on pancreatic cancer tissues.46 However, from a biomarker’s standpoint, pancreatic juice is an excellent starting specimen for the identification of protein biomarkers. Pancreatic juice is a rich source for cancer-specific proteins because the highly proliferative cancer cells are shed into the juice, as they undergo cellular turnover and degradation.7

Pancreatic juice was extensively studied in late 1970s and 1980s, primarily by early 2-dimensional electrophoresis analyses, which led to the discovery and description of several pancreatic enzymes.812 Recently, Gronborg and colleagues13 used a mass spectrometry-based proteomic approach for the analysis of pancreatic juice which used 1-dimensional electrophoresis and liquid chromatography (LC) tandem mass spectrometry (MS/MS). We previously used an isotope-coded affinity tag (ICAT)–based quantitative proteomic approach to identify and characterize potential biomarkers from pancreatic cancer juice.14 A total of 30 proteins were identified that exhibited greater than 2-fold abundance change in pancreatic cancer juice compared with normal pancreatic juice. Given the false-positive role of pancreatitis in pancreatic cancer, it is important to discover possible pancreatitis specific proteins that can be used to differentiate pancreatic cancer and pancreatitis. In addition, discovery of the proteins in pancreatitis could help identify proteins that might contribute to false-positive findings of pancreatic cancer.

Isotope-coded affinity tag (ICAT) technology provides a comprehensive approach for quantitative proteomic analysis.15,16 This methodology demonstrates a significant improvement over gel-based methods in identifying low-abundant proteins, and it minimizes problems associated with solubility and extremes of pH.17 In this study, we used ICAT technology to perform comprehensive quantitative protein profiling of the pancreatitis juice. We performed the analyses by comparing pooled normal pancreatic juice with pancreatic juice from a chronic pancreatitis patient. Identification and quantification of the proteins from pancreatic juice were accomplished by differentially labeling the target proteins (pancreatitis) with heavy ICAT reagents and the normal comparator proteins with light ICAT reagents. The isotopically labeled proteins were then combined, purified, and followed by LC MS/MS analysis. Protein identification and quantification were then accomplished by using a suite of bioinformatics software. The proteomic analysis of pancreatitis juice was then compared with the analysis of pancreatic cancer juice.

MATERIALS AND METHODS

Specimens

Pancreatic juice samples were collected during endoscopic retrograde cholangiopancreatography and immediately stored at −80°C. Pancreatic tissue specimens were collected at surgery and stored in freezing media (10% dimethyl sulfoxide) at −80°C. The specimens were collected in accordance with approved human subject’s guidelines at the University of Washington. Pancreatic juice from a chronic pancreatitis patient and 10 normal controls were included in this study. Pancreatic juices from 10 normal controls were pooled together by equal quantity of total protein. Because endoscopic retrograde cholangiopancreatography is an invasive procedure, it is uncommon to obtain pancreatic juice from patients with a completely normal pancreas. In this study, the normal juices were from the patients who have benign pancreatic diseases such as benign cystic neoplasms. Samples from potentially neoplastic precursor lesions, such as intrapapillary mucinous neoplasia, were not included as normal control. The pancreatitis sample was from a patient with chronic pancreatitis and history of alcoholism, without evidence of malignancy.

Isotope-Coded Affinity Tag Labeling and Mass Spectrometry

The ICAT labeling and mass spectrometry were performed as previously described.14 Briefly, protease inhibitor, phenyl methyl sulfonyl fluoride, was added to pancreatic juice at a final concentration of 0.5 mmol/L to prevent protein degradation. For each sample, 0.5-mg protein was labeled with the acid cleavable ICAT reagents, either in an isotopically light 12C (pooled normal pancreatic juice) or in heavy 13C (pancreatitis juice) isoforms (Applied Biosystems, Foster City, Calif) as previously described. The labeled 2 samples were then combined and digested into peptides by trypsin (Promega, Madison, Wis). Isotope-Coded affinity tag–labeled peptides were subsequently fractionated by cation-exchange chromatography and purified by avidin-affinity chromatography. The resulting 50 fractions were then combined into 21 fractions and analyzed by microcapillary high-performance LC–electrospray ionization–MS/MS using an ion-trap mass spectrometer (LCQ-DecaXP, ThermoFinnigan, San Jose, Calif) as previously described.4,14

Data Analysis

Tandem mass spectrometry spectra were searched against the National Cancer Institute human sequence database using SEQUEST.18 The database search results were validated using the PeptideProphet program.19 Peptide-Prophet uses various SEQUEST scores and a number of other parameters to calculate a probability score for each identified peptide. The identified peptides were then assigned a protein identification using the ProteinProphet software.20 Protein-Prophet allows filtering of large-scale data sets with predictable sensitivity and false-positive identification error rates. In this study, we used ProteinProphet probability score more than or equal to 0.9 as a cutoff value for protein identification. This will ensure that the false-positive rate (error rate) for protein identification in this study less than 0.9%. Quantification of the ratio of each protein (isotopically heavy vs light) was calculated using the ASAPRatio program.21 Information on the software can be found on line at http://www.systemsbiology.org/Default.aspx?pagename=FullList. The identified proteins were classified based on GO (Gene Ontology) consortium.22

RESULTS AND DISCUSSION

Proteins Identified in Pancreatitis Juice

In this study, we used the ICAT approach to identify and quantify proteins in a pair of pancreatic juices: pooled normal pancreatic juice versus pancreatic juice from a patient with pancreatitis. The approach was to label the comparator (pooled normal juice) and target (pancreatitis juice) proteins with the isotopically light and heavy ICAT reagents, respectively. The labeled proteins from the comparator and target proteomes were then combined, digested, fractionated, and purified by multidimensional chromatography and analyzed by MS/MS. The protein identification and quantification were accomplished by using a suite of bioinformatic software tools.1821 All together, 72 proteins were identified and quantified in the comparison of pancreatitis juice to pooled normal pancreatic juice, with an error rate of less than 0.9%.

The 72 proteins identified in the pancreatic juices were examined by cellular component, molecular function, and biological process classified accordingly based on GO22 nomenclature. The distribution of these proteins in cellular component, molecular function, and biological process are presented in Figure 1. Most of the identified proteins was from the extracellular region (72%) or bound to the plasma membrane (12%). This is consistent with the fact that proteins from pancreatic juice are primarily secreted and with a previous study in pancreatic cancer juice and normal pancreatic juice.14 In addition, about 3% of proteins were from the ductal cell cytoplasm and nucleus. Because pancreatic juice is mainly cell-free, the existent of these cellular proteins supports the assumption that cellular proteins may be shed into pancreatic juice by cell turnover or secretion.14

FIGURE 1.

FIGURE 1

Distribution of the identified proteins from pancreatic juice. The 72 proteins identified and quantified in pancreatic juice were classified into categories based on A, cellular component, B, molecular function, and C, biological process. The assignments were based on GO consortium.

Many of the proteins identified in pancreatic juice were enzymes (catalytic activity, 35%). Other molecular functions identified included: binding function 24%, enzyme regulation 3%, obsolete molecular function 1%, structural molecules 1%, and transporter activity 11%. The molecular functions for 25% of the proteins are still unknown at the present time.

In classifying the proteins by biological process, one third of the proteins identified were involved with metabolism; this finding is consistent with the fact that the major role of pancreatic juice is to provide enzymes for digestion. Other biological functions attributed to the discovered proteins include response to stimulus (24%) (not surprising in the setting of chronic inflammation), developmental (3%), cell communication (4%), regulators of biological processes (3%), and localization (6%).

We have previously identified a total of 105 proteins from pancreatic cancer juice.14 Comparison of the 2 disease states (pancreatitis and cancer) reveals that 31 of the 72 pancreatitis proteins identified in this pancreatitis study have not been detected in previous studies and are unique to this study of pancreatitis juice. In total, 136 proteins were identified in pancreatic juices in the 2 studies (current and previous) (Table 1).

TABLE 1.

List of Proteins Identified in the Pancreatic Juices

Database ID Protein Name Identified in CA/nl Identified in CP/nl Identified in nl/nl
3D:1clyH 1clyH IGG FAB (human IgG1, κ)
SW:W70T_HUMAN 70 kDa WD-repeat tumor rejection antigen
SW:A1AG_HUMAN α1-Acid glycoprotein 1 precursor
SW:A1AT_HUMAN α1-Antitrypsin precursor
SW:A1BG_HUMAN α1b-Glycoprotein precursor
SW:A2MG_HUMAN α2-Macroglobulin precursor
SW:AMYC_HUMAN α-Amylase 2b precursor
SW:AMYP_HUMAN α-Amylase, pancreatic precursor
IPI00025476 Amylase, α2A
SW:APOD_HUMAN Apolipoprotein D precursor
GP:AF332505_1 Apoptosis inhibitor–like protein mRNA
SW:CORI_HUMAN Atrial natriuteric peptide–converting enzyme
SW:AXU1_HUMAN Axin 1 up-regulated 1 protein (TGF-β–induced apoptosis protein 3)
IPI00179390 β-actin
SW:B2MG_HUMAN β2-microglobulin
SW:APOH_HUMAN β2–Glycoprotein 1 precursor (apolipoprotein H)
GP:BC042510_1 Bile salt–stimulated lipase
SW:BAL_HUMAN Bile salt–activated lipase precursor
SW:BMP8_HUMAN Bone morphogenetic protein 8 precursor
SW:C4BP_HUMAN C4b-binding protein α chain precursor
GP:AF127036_1 Calcium-activated chloride channel protein 1
SW:CRTC_HUMAN Calreticulin precursor
SW:CBP1_HUMAN Carboxypeptidase a1 precursor
SW:CPB2_HUMAN Carboxypeptidase a2 precursor
SW:CBPB_HUMAN Carboxypeptidase b precursor
SW:CATO_HUMAN Cathepsin o precursor
SW:CD5L_HUMAN CD5 antigen–like precursor
SW:CERU_HUMAN Ceruloplasmin precursor
GP:AF287894_1 CFTR-associated ligand (CAL)
GP:AL512883_3 Chymotrypsin C (caldecrin)
SW:CTRL_HUMAN Chymotrypsin-like protease ctrl-1 precursor
SW:CTRB_HUMAN Chymotrypsinogen b precursor
GP:BC005951_1 Clone MGC:14588
IPI00219642 Clusterin precursor
SW:COL_HUMAN Colipase precursor
SW:CO3_HUMAN Complement C3 precursor
SW:CO4_HUMAN Complement C4 precursor
SW:CFAH_HUMAN Complement factor H precursor
SW:FHR3_HUMAN Complement factor H-related protein 3 precursor
IPI00032293 Cystatin C precursor
SW:EL2A_HUMAN Elastase 2a precursor
SW:EL2B_HUMAN Elastase 2b precursor
IPI00240986 Elastase 3, pancreatic (protease E)
SW:EL3A_HUMAN Elastase iiia precursor
SW:EL3B_HUMAN Elastase iiib precursor
SW:FIBA_HUMAN Fibrinogen α/αe chain precursor
SW:FIBB_HUMAN Fibrinogen β chain precursor
SW:FIBG_HUMAN Fibrinogen γ chain precursor
SW:FGL1_HUMAN Fibrinogen-like protein 1 precursor
GP:AK074044_1 FLJ00102 protein
SW:FOL3_HUMAN Folate receptor γ precursor
IPI00023673 Galectin 3 binding protein
SW:SGCG_HUMAN γ-Sarcoglycan (35 kDa dystrophin-associated glycoprotein)
SW:KLK1_HUMAN Glandular kallikrein 1 precursor
SW:VGLH_HSV6U Glycoprotein H precursor
SW:HPT2_HUMAN Haptoglobin 2 precursor
SW:HPTR_HUMAN Haptoglobin-related protein precursor
SW:HBB_HUMAN Hemoglobin β chain
SW:HEMO_HUMAN Hemopexin precursor
GP:M19233_1 Human α-amylase-1 gene
GP:U88581_1 Human transferrin mRNA, C2 allele
GP:AL136795_1 Hypothetical protein DKFZp434G131
GP:AB083068_1 Hypothetical protein DKFZp434N1415
GP:BC027590_1 Hypothetical protein FLJ10261
IPI00168679 Hypothetical protein Tr:Q8NEJ1
IPI00152428 Hypothetical protein Tr:Q8TCS3
SW:ALC1_HUMAN Ig-α1 chain c region
PIR1:A2HU Ig-α2 chain C region
SW:GC2_HUMAN Ig-γ2 chain c region
SW:KAC_HUMAN Ig-κ chain c region
IPI00004574 Ig-κ chain C region
SW:MUC_HUMAN Ig-μ chain C region
GP:D84239_1 IgG Fc binding protein
SW:KAC_HUMAN IGK mRNA for immunoglobulin κ light chain VLJ region
GP:AJ294732_1 Immunoglobulin heavy chain constant region γ3 (IGHG3)
GP:AJ294733_1 Immunoglobulin heavy chain constant region γ4
GP:AB021510_1 Immunoglobulin heavy chain variable region
SW:GC1_HUMAN Immunoglobulin heavy constant γ1
SW:IBP2_HUMAN Insulin-like growth factor binding protein
SW:ITH4_HUMAN Inter–α-trypsin inhibitor heavy chain h4 precursor
GP:AB040939_1 KIAA1506 protein
SW:LITA_HUMAN Lithostathine 1 α precursor pancreatic stone protein)
SW:LITB_HUMAN Lithostathine 1β precursor
GP:AY044164_1 Lymphocyte α kinase
SW:LYC_HUMAN Lysozyme c precursor
GP:AK009737_1 Moderately similar to gallus gallus syndesmos
GP:AC003682_1 Most similar to zinc finger protein ZNF132
IPI00103397 Mucin 5
PIR2:S53362 Mucin 5AC
GP:AF244548_1 Na+ and H+ coupled amino acid transport system N mRNA
SW:CAML_HUMAN NCAM L1 (CD171 antigen)
IPI00220513 P21359 Neurofibromin
SW:PAX7_HUMAN Paired box protein pax-7 (hup1).
PIR2:A29934 Pancreatic elastase (EC 3.4.21.36) IIIA precursor
SW:LIPP_HUMAN Pancreatic lipase
SW:LIP1_HUMAN Pancreatic lipase–related protein 1 precursor
SW:LIP2_HUMAN Pancreatic lipase–related protein 2 precursor
SW:GP2_HUMAN Pancreatic secretory granule membrane major glycoprotein gp2 precursor
SW:IPK1_HUMAN Pancreatic secretory trypsin inhibitor precursor (tumor-associated trypsin inhibitor)
GP:AB035542_1 Pancreatic zymogen granule membrane–associated protein GP2β
SW:PAP1_HUMAN Pancreatitis-associated protein 1 precursor
IPI00022543 Phosphatidylinositol glycan
SW:PA21_HUMAN Phospholipase a2 precursor
SW:PLMN_HUMAN Plasminogen precursor
SW:PIGR_HUMAN Polymeric-immunoglobulin receptor precursor
SW:SAP_HUMAN Proactivator polypeptide precursor (contains saposin a)
IPI00022213 Progastricsin (pepsinogen C)
IPI00011694 Protease, serine, 1 preproprotein
IPI00011695 Protease, serine, 2 preproprotein
SW:CLPP_HUMAN Putative ATP-dependent clp protease proteolytic subunit
PIR2:S36262 Rearranged Ig-κ region V-domain
IPI00009197 Regenerating islet–derived 1β precursor
IPI00019176 Retinoic acid receptor responder
SW:RNP_HUMAN Ribonuclease pancreatic precursor
GP:AK090123_1 RNA binding protein homolog
IPI00032179 Serine (or cysteine) proteinase inhibitor, clade C (antithrombin)
SW:TRFE_HUMAN Serotransferrin precursor (transferrin)
SW:ALBU_HUMAN Serum albumin
IPI00156237 Similar to chymotrypsinogen B precursor
IPI00027722 Similar to elastase 1, pancreatic
IPI00247169 Similar to syncollin
SW:SODC_HUMAN Superoxide dismutase
GP:U66061_9 T-cell receptor β chain (human germline)
GP:AY190093_1 T-cell receptor β chain (clone PSA.S.20)
IPI00010675 Trefoil factor 2 (spasmolytic protein 1)
IPI00181107 Triacylglycerol lipase
SW:TRY1_HUMAN Trypsin I precursor
SW:TRY2_HUMAN Trypsin II precursor
IPI00015614 Trypsin III precursor
SW:TRY4_HUMAN Trypsin IV precursor
IPI00169276 Trypsinogen C
GP:AF305835_1 Uterus-ovary specific putative transmembrane protein UO
SW:VTDB_HUMAN Vitamin D–binding protein precursor
GP:U06117_1 Xanthine dehydrogenase
SW:ZA2G_HUMAN Zinc α2-glycoprotein precursor

GP indicates GenPept; PIR, Protein information resource; IPI, International Protein Index; SW, SWISS-PROT; CA, cancer; CP, chronic pancreatitis; nl, normal.

Proteins With at Least 2-Fold Change in Abundance in Pancreatitis Juice

The use of ICAT technology allows us to perform protein identification and quantification studies in the same experiment. The quantification of each protein is presented as a protein ratio between 2 samples tested. In the comparison of pancreatitis juice/pooled normal juice, 27 proteins showed differential expression in pancreatitis juice by at least 2-fold: 19 were overexpressed, and 8 were underexpressed in pancreatitis juice (Table 2). Below, we will discuss some of the differentially regulated proteins.

TABLE 2.

Proteins With at Least 2-fold Change in Abundance in Pancreatic Juice From Pancreatitis

Database ID Protein Name Ratio (pancreatitis/nl) SD Unique Peptide Identified
More abundant by at least 2-fold
 3D:1clyH 1clyH IGG FAB (human IGG1 7.0 5.1 4
 SW:A1BG_HUMAN α1b-Glycoprotein precursor 3.1 0.9 3
 SW:A2MG_HUMAN α2-Macroglobulin precursor 2.8 0.3 12
 SW:APOH_HUMAN β2-Glycoprotein I precursor (apolipoprotein H) 6.5 6.1 7
 SW:CTRB_HUMAN Chymotrypsinogen b precursor 2.1 0.3 19
 SW:FIBB_HUMAN Fibrinogen β chain precursor 3.0 0.9 13
 SW:HPT2_HUMAN Haptoglobin 2 precursor 2.4 0.3 16
 SW:HBB_HUMAN Hemoglobin β chain 6.8 6.6 12
 GP:AF542069_1 Human serum albumin 3.9 1.7 267
 SW:ALC1_HUMAN Ig-α1 chain c region 4.7 1.1 7
 SW:MUC_HUMAN Ig-μ chain c region 2.5 2.1 1
 GP:AJ294732_1 Immunoglobulin heavy chain constant region γ3 11.1 8.9 10
 GP:AB021510_1 Immunoglobulin heavy chain variable region (IgM) 9.6 1.0 1
 SW:CAML_HUMAN NCAM L1 precursor 34.5 4.8 1
 SW:PLMN_HUMAN Plasminogen/plasmin 2.7 1.3 1
 SW:RNP_HUMAN Ribonuclease pancreatic precursor 2.3 6.40 2
 SW:TRFE_HUMAN Serotransferrin precursor (transferrin) 2.7 0.4 29
 SW:TRY1_HUMAN Trypsin I precursor 3.8 1.7 16
 SW:TRY2_HUMAN Trypsin II precursor 2.2 0.5 26
Less abundant by at least 2-fold
 SW:BMP8_HUMAN Bone morphogenetic protein 8 precursor 0.2 0.17 1
 SW:CLCR_HUMAN Caldecrin precursor 0.4 0.19 3
 SW:EL2A_HUMAN Elastase 2a precursor 0.5 0.06 6
 SW:EL2B_HUMAN Elastase 2b precursor 0.4 0.18 4
 SW:SGCG_HUMAN γ-Sarcoglycan 0.1 0.00 1
 GP:D84239_1 IgG Fc binding protein 0.3 0.03 5
 PIR2:A29934 Pancreatic elastase IIIA 0.3 0.03 27
 GP:AY190093_1 T-cell receptor β chain (clone PSA.S.20) 0.1 0.02 1

GP indicates GenPept; PIR, Protein information resource; SW, SWISS-PROT.

Fibrinogen β Chain

Fibrinogen was found to be 3.0-fold up-regulated in pancreatitis juice compared with normal pancreatic juice in this study. The MS/MS spectrum of a unique peptide (PVVSGKECEEIIR) derived from fibrinogen β chain is presented in Figure 2A. Twelve other peptides from this protein were also identified in the experiment (MS/MS spectra not shown). The identification of these 13 peptides gave an explicit identification of fibrinogen β chain in the samples. The relative abundance of each peptide pair was calculated based on the signal intensities for each peptide using ASAPRatio software. The relative abundance data revealed that this peptide was 4-fold more abundant in the pancreatitis sample (heavy) than in the normal sample (light). The ratio of fibrinogen β chain between pancreatitis and pooled normal was eventually calculated to be 3.0 (Fig. 2B) by incorporation of the intensities of all 13 peptides identified.

FIGURE 2.

FIGURE 2

Identification and quantification of fibrinogen beta chain in pancreatic juice by ICAT labeling and MS/MS analysis. A, MS/MS spectrum of a unique peptide (PVVSGKECEEIIR) derived from fibrinogen beta chain. The peptide was identified by sequence database searching using SEQUEST. Twelve other peptides from the same protein were also identified (MS/MS spectra not shown) which lead to conclusive identification of fibrinogen beta chain. B, The relative abundance of each peptide pair was cacculated based on the signal intensities for each peptide using ASAPRatio software. The relative abundance data revealed that this peptide was more abundant in pancreatitis sample (heavy) than in normal sample (light): ratio = 4.0. The ratio of fibrinogen beta chain between pancreatitis and pooled normal was calculated to be 3.0 by incorporation of the intensities of all 13 peptides identified.

Blood coagulation/fibrinolytic systems are commonly activated in pancreatic cancer. Immunohistochemical staining of pancreatic cancer sections indicate that fibrinogen exists throughout the tumor stroma, and tumor cells are surrounded by fibrin.23 Our previous studies also detected overexpression of fibrinogen β chain in pancreatic cancer tissue4 and elevation of fibrinogen β chain in pancreatic cancer juice.24 It has been postulated that local coagulation activation may regulate growth of pancreatic cancer.23 Alternatively, the up-regulation of fibrinogen in pancreatitis juice discovered in this study may be consistent with the fact that fibrogen is a major acute response protein involved in the inflammation of pancreas. Our study verifies that pancreatic cancer and pancreatitis have some common protein alterations. As such, the consideration of proteins in these 2 diseases should be considered concurringly to avoid false-positive findings in the development of diagnostic biomarkers for cancer.

Plasmin/Plasminogen

Identification of a peptide NYCRNPDGDVGGPW-CYTTNPR derived from plasminogen or plasmin suggested the presence of plasminogen or/and plasmin in the juice samples; however, the exact form of the protein from which the peptide was derived cannot be determined. It is clear that plasminogen/plasmin is elevated in pancreatitis juice by 2.7-fold. In the plasminogen/plasmin system, the inactive proenzyme plasminogen can be transformed into the proteolytically active plasmin mainly by plasminogen activators. Plasmin is involved in fibrinolysis and inflammation. The pathophysiological importance of the plasminogen/plasmin system in classical inflammation diseases has been well established by several studies.25 Increase level of plasmin activator (uPA) and plasmin–α2-antiplasmin complexes were found in synovial fluid as well as in plasma in patients with rheumatic diseases.2527 Involvement of plasmin in inflammatory process has also been demonstrated in plasminogen-deficient mice. In light of these findings, novel approaches were proposed for the treatment of chronic inflammatory diseases. For one example, induction of adenoviral vectors encoding an engineered cell surface-targeted plasmin inhibitor seems to reduce synovial fibroblast-dependent cartilage degradation and invasion in rheumatoid arthritis.25,28 Enhanced plasminogen activation have also been revealed in pancreatitis.29,30 However, direct demonstration of enhanced level of plasminogen in pancreatitis juice has not been reported before. In addition to its role in inflammation, plasminogen activation also plays an important role in tumor cell invasiveness and metastasis.31,32 Plasmin generated at the surface of tumor cells is considered a key event in tumor invasion and metastasis in the pancreatic cancer.31,32

Neural Cell Adhesion Molecule L1

Another up-regulated protein in pancreatitis juice is neural cell adhesion molecule L1 (NCAM L1). Neural cell adhesion molecule L1 is a multidomain membrane glycoprotein of the immunoglobulin superfamily3336 that is over-expressed by a variety of highly malignant tumors, including neuroblastomas,37 ovarian tumors,38 renal cell carcinoma,39 and endometrial tumors.40 Neural cell adhesion molecule L1 promotes many cellular activities by interacting through its extracellular domain with other cell adhesion molecules, extracellular matrix molecules, and signal receptors.4143 In light of its role in cell proliferation44 and tumor progression,41 NCAM L1 has emerged as a promising marker for cancers.45 Expression of NCAM L1 has not been previously reported in pancreatic cancer or pancreatitis. However, another adhesion molecule, neural cell adhesion molecule, has expression in 66.7% of pancreatic cancer cases.46 These 2 cell adhesion proteins are generated from different genes on different chromosomes; however, both are membrane glycoproteins belonging to a superfamily of immunoglobulins that mediate cell-to-cell adhesion at the cell surface. The expression of neural cell adhesion molecule has been detected more frequently in lesions where neural invasion was excessive.46 It is not clear why NCAM L1 was up-regulated in the setting of pancreatitis and not in pancreatic cancer juice. It will be interesting in the future to determine the expression pattern of this protein in normal pancreas and pancreatic disease, such as cancer and pancreatitis.

Caldecrin

One of the down-regulated proteins in pancreatitis juice is caldecrin (2.5-fold decrease). Caldecrin, also known as serum calcium-decreasing factor or chymotrypsin C, is a novel-type serine protease expressed in the pancreas.47 Its association with pancreatic disease has not been reported before. Given the fact that several digestive enzymes were differentially regulated in pancreatitis juice presented in this study, it is not surprising to see caldecrin also differentially expressed in pancreatitis juice. Further work is needed to evaluate the role of caldecrin in various pancreatic diseases.

Comparison of Differentially Expressed Proteins in the Pancreatic Juices from Pancreatic Cancer and Pancreatitis

Comparison of the differentially expressed proteins in pancreatitis to those from pancreatic cancer juice and normal juice,14 revealed 9 proteins (hemoglobin, fibrinogen, trypsin I, trypsin II, chymotrypsinogen b, Ig-α1 chain c region, Ig-μ chain c region, ribonuclease, and human serum albumin) that were both up-regulated in pancreatic cancer juice and pancreatitis juice (Table 3). These proteins should be excluded in future biomarker study for pancreatic cancer. Interestingly, down-regulated proteins in pancreatic cancer do not overlap with those from pancreatitis. There are 21 proteins that were differentially expressed only in pancreatic cancer, whereas 18 proteins were differentially expressed only in the pancreatitis (Fig. 3 and Table 3). In addition, elastase 2b, which was variable in comparison of normal juice with pooled normal juice,14 was also down-regulated pancreatitis juice but not found in pancreatic cancer juice. These data thus provide useful basis for future development of biomarkers for pancreatic cancer and pancreatitis and reduce the chance of false-positive biomarkers.

TABLE 3.

Comparison of Proteins With at Least 2-fold Change in Pancreatic Juice from Pancreatitis and Cancer

Database ID Protein Name Ratio (CP/nl) Ratio (CA/nl)
At least 2-fold change in abundance in both of pancreatic cancer and pancreatitis
 SW:CTRB_HUMAN Chymotrypsinogen b precursor 2.1 2.8
 SW:FIBB_HUMAN Fibrinogen β chain precursor 3.0 3.8
 SW:HBB_HUMAN Hemoglobin β chain 6.8 3.3
 GP:AF542069_1 Human serum albumin 3.9 3.7
 SW:ALC1_HUMAN Ig-α1 chain C region 4.7 4.0
 SW:MUC_HUMAN Ig-μ chain C region 2.5 3.9
 SW:RNP_HUMAN Ribonuclease pancreatic precursor 2.3 2.8
 SW:TRY1_HUMAN Trypsin I precursor 3.8 2.5
 SW:TRY2_HUMAN Trypsin II precursor 2.2 2.9
At least 2-fold change in abundance in pancreatic cancer only
 SW:A1AG_HUMAN α1-Acid glycoprotein 1 precursor 1.2 0.3
 SW:B2MG_HUMAN β2-Microglobulin 3.3
 SW:CPB2_HUMAN Carboxypeptidase a2 precursor 0.7 0.3
 SW:CO3_HUMAN Complement C3 precursor 1.7 3.0
 SW:EL3B_HUMAN Elastase 3b precursor 1.7 2.2
 SW:FIBA_HUMAN Fibrinogen α/αe chain precursor 0.2
 SW:FIBG_HUMAN Fibrinogen γ chain precursor 1.4 7.1
 SW:KAC_HUMAN Ig-κ light chain VLJ region 1.5 4.7
 SW:IBP2_HUMAN Insulin-like growth factor binding protein 2 4.8
 SW:KLK1_HUMAN Kallikrein 1 precursor 2.7
 SW:LITA_HUMAN Lithostathine 1α (pancreatic stone protein) 0.72 2.3
 SW:LITB_HUMAN Lithostathine 1β precursor 4.8
 SW:GP2_HUMAN Pancreatic secretory granule membrane major glycoprotein 0.72 2.4
 SW:PAP1_HUMAN Pancreatitis-associated protein 1 precursor 3.1
 SW:SAP_HUMAN Proactivator polypeptide precursor 0.2
 SW:CLPP_HUMAN Putative ATP-dependent clp protease proteolytic subunit 0.3
 PIR2:S36262 Rearranged Ig-κ region V-domain 3.7
 GP:U66061_9 T-cell receptor β chain (human germline) 10.2
 GP:U88581_1 Transferrin, C2 allele 0.4
 SW:TRY4_HUMAN Trypsin IV precursor 5.6
 SW:IPK1_HUMAN Tumor-associated trypsin inhibitor 5.6
At least 2-fold change in abundance in pancreatitis only
 3D:1clyH 1clyH IGG FAB (human IGG1) 7.0
 SW:A1BG_HUMAN α1b-Glycoprotein precursor 3.1 0.9
 SW:A2MG_HUMAN α2-Macroglobulin precursor 2.8 1.1
 SW:APOH_HUMAN β2-glycoprotein I precursor (apolipoprotein H) 6.5 1.1
 SW:BMP8_HUMAN Bone morphogenetic protein 8 precursor 0.2
 SW:CLCR_HUMAN Caldecrin precursor 0.4 1.2
 SW:EL2A_HUMAN Elastase 2a precursor 0.5 1.0
 SW:EL2B_HUMAN Elastase 2b precursor 0.4
 SW:SGCG_HUMAN γ-Sarcoglycan 0.1
 SW:HPT2_HUMAN Haptoglobin 2 precursor 2.4 2.0
 GP:D84239_1 IgG Fc binding protein 0.3
 GP:AJ294732_1 Immunoglobulin heavy chain constant region γ3 11.1
 GP:AB021510_1 Immunoglobulin heavy chain variable region (IgM) 9.6
 SW:CAML_HUMAN NCAM L1 precursor 34.5
 PIR2:A29934 Pancreatic elastase IIIA 0.3 1.7
 SW:PLMN_HUMAN Plasminogen/plasmin 2.7
 SW:TRFE_HUMAN Serotransferrin precursor (transferrin) 2.7 1.7
 GP:AY190093_1 T-cell receptor β chain (clone PAS.S.20) 0.1

GP indicates GenPept; PIR, Protein information resource; IPI, International Protein Index; SW, SWISS-PROT; CA, cancer; CP, chronic pancreatitis; nl, normal.

FIGURE 3.

FIGURE 3

Comparison of protein abundance changes in pancreatic juices from pancreatic cancer and pancreatitis patients. Of the 27 differentially regulated proteins in pancreatitis juice, 9 proteins were also differentially regulated in pancreatic cancer, and they are all up-regulated. Eighteen and 21 proteins are only differentially regulated in pancreatitis and pancreatic cancer, respectively.

Summary

In this study, we performed a comparative and comprehensive proteomic analysis on pancreatic juice from pancreatitis versus pooled normal controls. In total, we identify and quantify 72 proteins in comparison of the pancreatic juice from pancreatitis and pooled normal control, of which 19 were overexpressed, and 8 were underexpressed in pancreatitis juice by at least 2-fold. In these 27 differentially expressed proteins, several proteins (including plasminogen, NCAM L1, and caldecrin) have not been previously associated with pancreatic cancer or pancreatitis, and pancreatic juice. Further study is needed to elucidate the roles of these newly discovered proteins in pancreatitis and pancreatic cancer. In addition, 9 proteins (hemoglobin, fibrinogen, trypsin I, trypsin II, chymotrypsinogen b, Ig-α1 chain c region, Ig-μ chain c region, ribonuclease, and human serum albumin) that were previously shown to be up-regulated in pancreatic cancer juice are also differentially expressed in pancreatitis juice. Thus, these proteins may create false-positive results as biomarkers for pancreatic cancer.

Acknowledgments

Supported by the National Cancer Institute NIH R01-CA-107209, Canary Foundation, the Concern Foundation, Gene and Mary Ann Walters Pancreatic Cancer Foundation, the AACR-PanCAN Career Development Award for Pancreatic Cancer Research, and Federal funds from the National Heart, Lung and Blood Institute NIH, under contract no. NOI-HV-28179.

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