Quantitative Proteomics Analysis Reveals That Proteins Differentially Expressed in Chronic Pancreatitis Are Also Frequently Involved in Pancreatic Cancer
2007; Elsevier BV; Volume: 6; Issue: 8 Linguagem: Inglês
10.1074/mcp.m700072-mcp200
ISSN1535-9484
AutoresRu Chen, Teresa A. Brentnall, Sheng Pan, Kelly Cooke, Kara White Moyes, Zhaoli Lane, David A. Crispin, David R. Goodlett, Ruedi Aebersold, Mary P. Bronner,
Tópico(s)Endoplasmic Reticulum Stress and Disease
ResumoThe effective treatment of pancreatic cancer relies on the diagnosis of the disease at an early stage, a difficult challenge. One major obstacle in the development of diagnostic biomarkers of early pancreatic cancer has been the dual expression of potential biomarkers in both chronic pancreatitis and cancer. To better understand the limitations of potential protein biomarkers, we used ICAT technology and tandem mass spectrometry-based proteomics to systematically study protein expression in chronic pancreatitis. Among the 116 differentially expressed proteins identified in chronic pancreatitis, most biological processes were responses to wounding and inflammation, a finding consistent with the underlining inflammation and tissue repair associated with chronic pancreatitis. Furthermore 40% of the differentially expressed proteins identified in chronic pancreatitis have been implicated previously in pancreatic cancer, suggesting some commonality in protein expression between these two diseases. Biological network analysis further identified c-MYC as a common prominent regulatory protein in pancreatic cancer and chronic pancreatitis. Lastly five proteins were selected for validation by Western blot and immunohistochemistry. Annexin A2 and insulin-like growth factor-binding protein 2 were overexpressed in cancer but not in chronic pancreatitis, making them promising biomarker candidates for pancreatic cancer. In addition, our study validated that cathepsin D, integrin β1, and plasminogen were overexpressed in both pancreatic cancer and chronic pancreatitis. The positive involvement of these proteins in chronic pancreatitis and pancreatic cancer will potentially lower the specificity of these proteins as biomarker candidates for pancreatic cancer. Altogether our study provides some insights into the molecular events in chronic pancreatitis that may lead to diverse strategies for diagnosis and treatment of these diseases. The effective treatment of pancreatic cancer relies on the diagnosis of the disease at an early stage, a difficult challenge. One major obstacle in the development of diagnostic biomarkers of early pancreatic cancer has been the dual expression of potential biomarkers in both chronic pancreatitis and cancer. To better understand the limitations of potential protein biomarkers, we used ICAT technology and tandem mass spectrometry-based proteomics to systematically study protein expression in chronic pancreatitis. Among the 116 differentially expressed proteins identified in chronic pancreatitis, most biological processes were responses to wounding and inflammation, a finding consistent with the underlining inflammation and tissue repair associated with chronic pancreatitis. Furthermore 40% of the differentially expressed proteins identified in chronic pancreatitis have been implicated previously in pancreatic cancer, suggesting some commonality in protein expression between these two diseases. Biological network analysis further identified c-MYC as a common prominent regulatory protein in pancreatic cancer and chronic pancreatitis. Lastly five proteins were selected for validation by Western blot and immunohistochemistry. Annexin A2 and insulin-like growth factor-binding protein 2 were overexpressed in cancer but not in chronic pancreatitis, making them promising biomarker candidates for pancreatic cancer. In addition, our study validated that cathepsin D, integrin β1, and plasminogen were overexpressed in both pancreatic cancer and chronic pancreatitis. The positive involvement of these proteins in chronic pancreatitis and pancreatic cancer will potentially lower the specificity of these proteins as biomarker candidates for pancreatic cancer. Altogether our study provides some insights into the molecular events in chronic pancreatitis that may lead to diverse strategies for diagnosis and treatment of these diseases. Pancreatitis is an inflammatory condition of the pancreas that shares many molecular features with pancreatic cancer. Many of the abnormally expressed proteins present in the setting of pancreatic cancer are also abnormally expressed in chronic pancreatitis, providing an unacceptably low level of specificity for use as protein biomarkers and cancer screening. Thus, a major obstacle for the development of biomarkers for early diagnosis of pancreatic cancer has been the dual expression of potential biomarkers in the neoplastic and non-neoplastic setting. It is therefore important to understand the proteins expressed in pancreatitis because they could be a source of false positive biomarkers for pancreatic cancer. Moreover chronic pancreatitis is a risk factor for eventual neoplastic progression. Patients with chronic pancreatitis have a 2-fold increased risk of pancreatic cancer. Understanding the molecular events involved in both diseases may lead to a better understanding of the mechanisms that link them. The DNA and gene expression profile of pancreatic cancer has been detailed by multiple technologies, including RNA expression arrays, DNA microarray, differential display, and serial analysis of gene expression (1Chen R. Pan S. Brentnall T.A. Aebersold R. Proteomic profiling of pancreatic cancer for biomarker discovery.Mol. Cell. Proteomics. 2005; 4: 523-533Abstract Full Text Full Text PDF PubMed Scopus (142) Google Scholar, 2Chen R. Pan S. Crispin D.A. Brentnall T.A. Gene expression and proteomic analysis of pancreatic cancer: a recent update.Cancer Genomics Proteomics. 2006; 3: 1-10PubMed Google Scholar). However, there are few large scale investigations at the protein level. A recent study by Shen et al. (3Shen J. Person M.D. Zhu J. Abbruzzese J.L. Li D. Protein expression profiles in pancreatic adenocarcinoma compared with normal pancreatic tissue and tissue affected by pancreatitis as detected by two-dimensional gel electrophoresis and mass spectrometry.Cancer Res. 2004; 64: 9018-9026Crossref PubMed Scopus (295) Google Scholar) identified 40 differentially expressed proteins in pancreatic cancer using two-dimensional gel electrophoresis and mass spectrometry. In another study, Crnogorac-Jurcevic et al. (4Crnogorac-Jurcevic T. Gangeswaran R. Bhakta V. Capurso G. Lattimore S. Akada M. Sunamura M. Prime W. Campbell F. Brentnall T.A. Costello E. Neoptolemos J. Lemoine N.R. Proteomic analysis of chronic pancreatitis and pancreatic adenocarcinoma.Gastroenterology. 2005; 129: 1454-1463Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar) used PowerBlot Western array screening to investigate protein expression in pancreatic cancer and pancreatitis. The study identified dysregulated proteins in disease states compared with normal: 30 proteins in chronic pancreatitis and 102 proteins in pancreatic cancer. We previously used ICAT (5Gygi S.P. Rist B. Gerber S.A. Turecek F. Gelb M.H. Aebersold R. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.Nat. Biotechnol. 1999; 17: 994-999Crossref PubMed Scopus (4324) Google Scholar, 6Han D.K. Eng J. Zhou H. Aebersold R. Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry.Nat. Biotechnol. 2001; 19: 946-951Crossref PubMed Scopus (826) Google Scholar)-based quantitative proteomics to study protein expression profiles of pancreatic cancer tissues and normal pancreas (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar) and identified a number of new biomarker candidates associated with pancreatic cancer. In this report, we extend our investigation to study protein profiles in chronic pancreatitis. We identified differentially expressed proteins in chronic pancreatitis and compared them with the differentially expressed genes and proteins identified in pancreatic cancer reported in the literature. The differentially expressed proteins identified in chronic pancreatitis were further investigated to reveal the biological pathways of these proteins in association with the pathogenesis of chronic pancreatitis and pancreatic cancer. Western blotting and immunohistochemistry (IHC) 1The abbreviations used are: IHC, immunohistochemistry; IGFBP-2, insulin-like growth factor-binding protein 2. 1The abbreviations used are: IHC, immunohistochemistry; IGFBP-2, insulin-like growth factor-binding protein 2. were also used to validate the relevancy of the proteomics results to the development of biomarker candidates for pancreatic cancer. Tissue specimens were obtained from patients with histologically proven pancreatic cancer or chronic pancreatitis and were collected in accordance with approved human subject guidelines at the University of Washington, Virginia Mason Hospital, and the Cleveland Clinic. For proteomics analysis, the chronic pancreatitis specimens were from patients who had no clinical or histological findings of pancreatic cancer at the time of diagnosis. To obtain a relatively homogeneous sample, we selected the chronic pancreatitis specimens with moderate fibrosis and occasional lymphocytes. It is difficult to obtain completely normal patients because they do not undergo surgery; thus we selected the 10 control specimens from patients who had as normal a pancreas as possible. The 10 normal controls were pooled from specimens derived from patients who had benign lesions of the pancreas such as pseudocyst, serous cystadenoma, serous microcystic adenoma, and non-pancreatic cancers such as cholangiocarcinoma and periampullary adenocarcinoma. All the control specimens were histologically verified normal pancreas specimens with one exception that had some periductal fibrosis but without significant inflammation. For the validation studies, we included specimens that were from patients who had ductal adenocarcinoma, primary pancreatitis, secondary pancreatitis associated with pancreatic cancer, and normal tissues. All of the specimens were obtained from surgical resections intraoperatively, immediately processed to minimize enzymatic destruction of the proteins, and frozen at −70 °C in minimal essential medium with 10% DMSO until use. DMSO was used to maintain cell architecture by reducing ice crystals within the cell during freezing. The ICAT labeling and mass spectrometry analysis were described previously (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar). Briefly frozen tissue was first rinsed with cold PBS, and 0.5–1.0 ml of T-Per buffer (Pierce) with 1× protease inhibitors was added to the tissue followed by tissue homogenization. The lysate was then centrifuged for 10 min at 10,000 rpm, and the debris were discarded. A Bradford assay (Sigma-Aldrich) was used to determine protein concentration. Ten normal pancreas samples were pooled together using an equal amount of protein from each individual sample as a pooled normal pancreas sample. Similarly 10 chronic pancreatitis samples were pooled together as a pooled chronic pancreatitis sample. For each pooled sample, 0.5 mg of protein was labeled with the acid-cleavable ICAT reagents, either the isotopically light (pooled normal pancreas) or heavy (pooled chronic pancreatitis) forms (Applied Biosystems, Foster City, CA) (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar). The labeled normal sample and the matching labeled pancreatitis sample were combined and digested into peptides by trypsin (Promega, Madison, WI). ICAT-labeled peptides were subsequently fractionated by cation-exchange chromatography and purified by avidin affinity chromatography. The resulting 40 cation-exchange fractions were then combined into 17 fractions based on the peak intensity, e.g. multiple original cation-exchange fractions could be further combined into one fraction if the peak intensities were low. The final 17 fractions were then analyzed by microcapillary HPLC-ESI-MS/MS using an ion trap mass spectrometer (LTQ, ThermoFinnigan, San Jose, CA) as described previously (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar). The raw data were converted to mzXML using ReAdW. MS/MS scans were then exported as .dta files without further processing using the program msxlm2other. MS/MS spectra were searched against the International Protein Index (IPI) human sequence database (IPI.HUMAN.v3.13.fasta, 57,032 entries) using SEQUEST (version 27) (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar). The SEQUEST database search criteria included a static modification of cysteine residues of 227 Da (light cleavable ICAT reagent) and a variable modification of 9 Da for cysteines (for the heavy cleavable ICAT reagent). The identified peptides were processed and analyzed through the mass spectrometry Trans-Proteomic Pipeline (TPP). In Trans-Proteomic Pipeline, the database search results were validated using the PeptideProphet program (8Keller A. Nesvizhskii A.I. Kolker E. Aebersold R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.Anal. Chem. 2002; 74: 5383-5392Crossref PubMed Scopus (3857) Google Scholar), which uses various SEQUEST scores and a number of other parameters to calculate a probability score for each identified peptide. The peptides were then assigned for protein identification using the ProteinProphet software (9Nesvizhskii A.I. Keller A. Kolker E. Aebersold R. A statistical model for identifying proteins by tandem mass spectrometry.Anal. Chem. 2003; 75: 4646-4658Crossref PubMed Scopus (3589) Google Scholar). ProteinProphet allows filtering of large scale data sets with assessment of predictable sensitivity and false positive identification error rates. In this study, we used a ProteinProphet probability score ≥0.9 to ensure an overall false positive rate below 0.9%. Furthermore proteins with single peptide identification were also excluded in this study. Quantification of the ratio of each protein, isotopically heavy (pooled chronic pancreatitis) versus light (pooled normal), was achieved using the ASAPRatio program (10Li X.J. Zhang H. Ranish J.A. Aebersold R. Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry.Anal. Chem. 2003; 75: 6648-6657Crossref PubMed Scopus (316) Google Scholar). Information about PeptideProphet, ProteinProphet, and ASAPRatio programs and other programs in Trans-Proteomic Pipeline can be obtained from the Seattle Proteome Center. Fifteen micrograms of protein from each specimen were used for SDS-PAGE. The gels were then transferred to nitrocellulose membrane according to the manufacturer's protocol (Amersham Biosciences). Antibodies were used at the following dilutions: anti-annexin A2 (Santa Cruz Biotechnology, Santa Cruz, CA), 1:1000 dilution; anti-plasminogen (US Biological, Swampscott, MA), 1:1000 dilution; and glyceraldehyde-3-phosphate dehydrogenase (R&D Systems, Minneapolis, MN), 1:2000 dilution. Proteins were detected using an ECL Plus kit (Amersham Biosciences). The tissue microarray was constructed from representative regions of paraffin-embedded tissue samples fixed in formalin and Hollande's fixative from 71 patients' surgical resections from the Cleveland Clinic between the years 1993 and 2004. Single 1-mm-diameter-sized cores of each diagnosis were re-embedded as a tissue microarray using a standard microarray instrument (Beecher Instruments, Silver Spring, MD). The microarray included 128 core samples from 47 sporadic pancreatic ductal adenocarcinoma patients, six core samples from four primary benign chronic pancreatitis patients without cancer and 12 core samples from two normal pancreatic control patients. From the above indicated 47 patients with adenocarcinoma, additional so-called "secondary" chronic pancreatitis was separately sampled in 24 core samples from a subset of 16 of the cancer patients. The term secondary chronic pancreatitis is used here to distinguish the chronic pancreatitis observed in patients with synchronous pancreatic ductal adenocarcinoma as opposed to primary benign chronic pancreatitis without evidence of malignancy. IHC staining on tissue sections was performed as described previously (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar). Briefly the slides were immunohistochemically stained using primary antibodies specific for annexin A2, cathepsin D, and integrin β1 from BD Biosciences. Slides were processed for antigen retrieval using microwave heating in citrate buffer (0.1 m, pH 6.0) for 20 min followed by cooling to room temperature and then primary antibody incubation for 32 min. Secondary antibody and streptavidin-peroxidase were applied (ES autostains, Ventana Medical Systems, Tucson, AZ). Diaminobenzidine substrate was applied using the autostains and Iview detection chemistry. Results were scored as diffuse or focal and were graded (from 0, negative to 3+, intensely positive) for both neoplasm, admixed benign epithelial elements (ducts, acini, and islets), and surrounding stroma by an experienced pancreatic pathologist (M. P. B.). MetaCore (GeneGo, St. Joseph, MI) was used to map the differentially expressed proteins into biological networks. MetaCore is an integrated software suite for functional analysis of experimental data. It is based on a proprietary manually curated database of human protein-protein, protein-DNA, and protein-compound interactions; metabolic and signaling pathways; and the effects of bioactive molecules. Differentially expressed proteins were converted into gene symbols and uploaded into MetaCore for analysis. The biological process enrichment was analyzed based on Gene Ontology processes. For network analysis, two algorithms were used: 1) the direct interaction algorithm to map direct protein-protein interaction and 2) the shortest path algorithm to map the shortest path for interaction. Using ICAT labeling and MS/MS, 657 proteins were identified and quantified in the comparison of pooled chronic pancreatitis tissues with pooled normal pancreas tissues. These identified proteins had a ProteinProphet score ≥0.9 with error rate ≤0.9% for protein identification. For the purpose of this study, single peptide-based protein identifications were further excluded, resulting in 498 proteins with a ProteinProphet score ≥0.9 and at least two-peptide identification (see the supplemental table for the complete list). In addition to protein identification, quantification of protein abundance ratios between pancreatitis and normal pancreas could also be achieved using ASAPRatio software. A total of 116 proteins showed an abundance change of at least 2-fold in chronic pancreatitis tissues compared with normal pancreas: 96 were overexpressed and 20 were underexpressed in chronic pancreatitis compared with normal pancreas (Table I).Table IProteins with at least 2-fold change in abundance in chronic pancreatitis compared with normal pancreasDatabase IDGene symbolProtein descriptionRatio CP/NLS.D.Unique peptidesCA ICAT studyOther CA studyOther CP studyMore abundant by at lease 2-fold IPI00178744aProtein group, only one is listed.ACADVLAcyl-CoA dehydrogenase (splice isoform 2)14.296.122Yes (27Nakamura T. Furukawa Y. Nakagawa H. Tsunoda T. Ohigashi H. Murata K. Ishikawa O. Ohgaki K. Kashimura N. Miyamoto M. Hirano S. Kondo S. Katoh H. Nakamura Y. Katagiri T. Genome-wide cDNA microarray analysis of gene expression profiles in pancreatic cancers using populations of tumor cells and normal ductal epithelial cells selected for purity by laser microdissection.Oncogene. 2004; 23: 2385-2400Crossref PubMed Scopus (220) Google Scholar) IPI00419237LAP3LAP3 protein9.090.832 IPI00029039REG1ARegenerating islet-derived protein 3α (pancreatitis-associated protein 1)8.332.782Yes (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar)Yes (28Patard L. Lallemand J.Y. Stoven V. An insight into the role of human pancreatic lithostathine.JOP J. Pancreas. 2003; 4: 92-103Google Scholar) IPI00010274aProtein group, only one is listed.TPSAB1Tryptase α-1 precursor (splice isoform 1)7.141.532Yes (29Ferrero S. Serum levels of mast cell tryptase, vascular endothelial growth factor, and basic fibroblast growth factor in patients with acute pancreatitis.Pancreas. 2004; 28: 450-451Crossref PubMed Scopus (0) Google Scholar) IPI00219713aProtein group, only one is listed.FGGγ-A of fibrinogen γ chain precursor (splice isoform)6.672.224Yes (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar)Yes (12Lu Z. Hu L. Evers S. Chen J. Shen Y. Differential expression profiling of human pancreatic adenocarcinoma and healthy pancreatic tissue.Proteomics. 2004; 4: 3975-3988Crossref PubMed Scopus (89) Google Scholar, 30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar) IPI00032179aProtein group, only one is listed.SERPINC1Antithrombin III variant, SERPINC1 protein6.253.133Yes (30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar) IPI00641737HPHaptoglobin precursor6.251.172Yes (31Quilliot D. Walters E. Guerci B. Fruchart J.C. Duriez P. Drouin P. Ziegler O. Effect of the inflammation, chronic hyperglycemia, or malabsorption on the apolipoprotein A-IV concentration in type 1 diabetes mellitus and in diabetes secondary to chronic pancreatitis.Metabolism. 2001; 50: 1019-1024Abstract Full Text PDF PubMed Scopus (13) Google Scholar) IPI00102821PACAPPituitary adenylate cyclase-activating polypeptide protein6.252.735 IPI00019004TLOC1Translocation protein-16.251.172 IPI00384428BPHLValacyclovir hydrolase precursor5.881.042 IPI00021854APOA2Apolipoprotein A-II precursor5.562.477 IPI00639937aProtein group, only one is listed.CFBComplement B-factor5.561.232Yes (30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar, 32Holzmann K. Kohlhammer H. Schwaenen C. Wessendorf S. Kestler H.A. Schwoerer A. Rau B. Radlwimmer B. Dohner H. Lichter P. Gress T. Bentz M. Genomic DNA-chip hybridization reveals a higher incidence of genomic amplifications in pancreatic cancer than conventional comparative genomic hybridization and leads to the identification of novel candidate genes.Cancer Res. 2004; 64: 4428-4433Crossref PubMed Scopus (130) Google Scholar) IPI00375676FTLFerritin light chain5.261.113Yes (3Shen J. Person M.D. Zhu J. Abbruzzese J.L. Li D. Protein expression profiles in pancreatic adenocarcinoma compared with normal pancreatic tissue and tissue affected by pancreatitis as detected by two-dimensional gel electrophoresis and mass spectrometry.Cancer Res. 2004; 64: 9018-9026Crossref PubMed Scopus (295) Google Scholar) IPI00328113FBN1Fibrillin-1 precursor4.761.5915Yes (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar)Yes (21Buchholz M. Kestler H.A. Bauer A. Bock W. Rau B. Leder G. Kratzer W. Bommer M. Scarpa A. Schilling M.K. Adler G. Hoheisel J.D. Gress T.M. Specialized DNA arrays for the differentiation of pancreatic tumors.Clin. Cancer Res. 2005; 11: 8048-8054Crossref PubMed Scopus (38) Google Scholar, 33Grutzmann R. Boriss H. Ammerpohl O. Luttges J. Kalthoff H. Schackert H.K. Kloppel G. Saeger H.D. Pilarsky C. Meta-analysis of microarray data on pancreatic cancer defines a set of commonly dysregulated genes.Oncogene. 2005; 24: 5079-5088Crossref PubMed Scopus (150) Google Scholar) IPI00298994TLN1Talin-14.554.134Yes (34Aguirre A.J. Brennan C. Bailey G. Sinha R. Feng B. Leo C. Zhang Y. Zhang J. Gans J.D. Bardeesy N. Cauwels C. Cordon-Cardo C. Redston M.S. DePinho R.A. Chin L. High-resolution characterization of the pancreatic adenocarcinoma genome.Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 9067-9072Crossref PubMed Scopus (233) Google Scholar) IPI00021263YWHAZ14-3-3 protein ζ/δ4.353.785Yes (3Shen J. Person M.D. Zhu J. Abbruzzese J.L. Li D. Protein expression profiles in pancreatic adenocarcinoma compared with normal pancreatic tissue and tissue affected by pancreatitis as detected by two-dimensional gel electrophoresis and mass spectrometry.Cancer Res. 2004; 64: 9018-9026Crossref PubMed Scopus (295) Google Scholar) IPI00022463TFSerotransferrin precursor4.351.8950Yes (11Gronborg M. Kristiansen T.Z. Iwahori A. Chang R. Reddy R. Sato N. Molina H. Jensen O.N. Hruban R.H. Goggins M.G. Maitra A. Pandey A. Biomarker discovery from pancreatic cancer secretome using a differential proteomic approach.Mol. Cell. Proteomics. 2006; 5: 157-171Abstract Full Text Full Text PDF PubMed Scopus (388) Google Scholar) IPI00017601CPCeruloplasmin precursor4.171.222Yes (4Crnogorac-Jurcevic T. Gangeswaran R. Bhakta V. Capurso G. Lattimore S. Akada M. Sunamura M. Prime W. Campbell F. Brentnall T.A. Costello E. Neoptolemos J. Lemoine N.R. Proteomic analysis of chronic pancreatitis and pancreatic adenocarcinoma.Gastroenterology. 2005; 129: 1454-1463Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar, 30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar) IPI00003348GNB3Guanine nucleotide-binding protein Gi/Gs/Gt β subunit 24.000.962Yes (30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar, 32Holzmann K. Kohlhammer H. Schwaenen C. Wessendorf S. Kestler H.A. Schwoerer A. Rau B. Radlwimmer B. Dohner H. Lichter P. Gress T. Bentz M. Genomic DNA-chip hybridization reveals a higher incidence of genomic amplifications in pancreatic cancer than conventional comparative genomic hybridization and leads to the identification of novel candidate genes.Cancer Res. 2004; 64: 4428-4433Crossref PubMed Scopus (130) Google Scholar) IPI00022488HPXHemopexin precursor4.001.4411Yes (7Chen R. Yi E.C. Donohoe D. Pan S. Eng J. Crispin D.A. Lane Z. Goodlett D.A. Bronner M.P. Aebersold R. Brentnall T.A. Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.Gastroenterology. 2005; 129: 1187-1197Abstract Full Text Full Text PDF PubMed Scopus (164) Google Scholar)Yes (27Nakamura T. Furukawa Y. Nakagawa H. Tsunoda T. Ohigashi H. Murata K. Ishikawa O. Ohgaki K. Kashimura N. Miyamoto M. Hirano S. Kondo S. Katoh H. Nakamura Y. Katagiri T. Genome-wide cDNA microarray analysis of gene expression profiles in pancreatic cancers using populations of tumor cells and normal ductal epithelial cells selected for purity by laser microdissection.Oncogene. 2004; 23: 2385-2400Crossref PubMed Scopus (220) Google Scholar, 30Bloomston M. Zhou J.X. Rosemurgy A.S. Frankel W. Muro-Cacho C.A. Yeatman T.J. Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples.Cancer Res. 2006; 66: 2592-2599Crossref PubMed Scopus (87) Google Scholar) IPI00293303aProtein group, only one is listed.LGMNLegumain precursor4.000.804Yes (35Missiaglia E. Blaveri E. Terris B. Wang Y.H. Coste
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