Abstract
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 beta1, 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.
Highlights
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)
We used ICAT-based quantitative proteomics to analyze protein expression in chronic pancreatitis in comparison with normal pancreas. 116 proteins were shown to be differentially expressed by at least 2-fold in chronic pancreatitis of which 15 proteins were shown to be differentially expressed in our previous ICAT proteomics analysis of pancreatic cancer, and 47 and 13 proteins have been previously shown in the literature to be involved in pancreatic cancer and chronic pancreatitis, respectively
Integrin 1, cathepsin D, and plasminogen were shown to be overexpressed in chronic pancreatitis and pancreatic cancer by ICAT analysis and IHC staining of pancreatic tissue sections or Western blot
Summary
Specimens—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. The chronic pancreatitis specimens were from patients who had no clinical or histological findings of pancreatic cancer at the time of diagnosis. We included specimens that were from patients who had ductal adenocarcinoma, primary pancreatitis, secondary pancreatitis associated with pancreatic cancer, and normal tissues. In Trans-Proteomic Pipeline, the database search results were validated using the PeptideProphet program [8], which uses various SEQUEST scores and a number of other parameters to calculate a probability score for each identified peptide. Quantification of the ratio of each protein, isotopically heavy (pooled chronic pancreatitis) versus light (pooled normal), was achieved using the ASAPRatio program [10]. 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. 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
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