ABSTRACT
PURPOSE: Pancreatic cancer is commonly detected at advanced stages when the tumor is no longer amenable to surgical resection. Therefore, finding biomarkers for early stage disease is urgent. Here, we show that high-definition mass spectrometry (HDMS(E)) can be used to identify serum protein alterations associated with early stage pancreatic cancer. METHODS: We analyzed serum samples from patients with resectable pancreatic cancer, benign pancreatic disease, and healthy controls. The SYNAPT G2-Si platform was used in a data-independent manner coupled with ion mobility. The dilution of the samples with yeast alcohol dehydrogenase tryptic digest of known concentration allowed the estimated amounts of each identified protein to be calculated (Silva et al. in Anal Chem 77:2187-2200, 2005; Silva et al. in Mol Cell Proteomics 5:144-156, 2006). A global protein expression comparison of the three study groups was made using label-free quantification and bioinformatic analyses. RESULTS: Two-way unsupervised hierarchical clustering revealed 134 proteins that successfully classified pancreatic cancer patients from the controls, and identified 40 proteins that showed a significant up-regulation in the pancreatic cancer group. This discrimination reliability was further confirmed by principal component analysis. The differentially expressed candidates were aligned with protein network analyses and linked to biological pathways related to pancreatic tumorigenesis. Pancreatic disease link associations could be made for BAZ2A, CDK13, DAPK1, DST, EXOSC3, INHBE, KAT2B, KIF20B, SMC1B, and SPAG5, by pathway network linkages to p53, the most frequently altered tumor suppressor in pancreatic cancer. CONCLUSION: These pancreatic cancer study candidates may provide new avenues of research for a noninvasive blood-based diagnosis for pancreatic tumor stratification.
Subject(s)
Biological Specimen Banks , Biomarkers, Tumor/metabolism , Blood Proteins/metabolism , Pancreas/metabolism , Pancreatic Neoplasms/metabolism , Proteomics/methods , Aged , Case-Control Studies , Computational Biology , Female , Humans , Male , Middle Aged , Prognosis , Spectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationABSTRACT
BACKGROUND/AIM: Mucin 4 (MUC4) has been linked to resistance to gemcitabine in pancreatic cancer cells. The aim of the present study was to assess whether epigenetic control of MUC4 expression can sensitize pancreatic cancer cells to gemcitabine treatment. MATERIALS AND METHODS: A 76-member combined epigenetics and phosphatase small-molecule inhibitor library was screened for anti-proliferative activity against the MUC4(+) gemcitabine-resistant pancreatic cancer cell line Capan-1, followed by high-content screening of protein expression. RESULTS: Apicidin, a histone deacetylase inhibitor, showed the greatest anti-proliferative activity with a lethal dose 50 (LD50) value of 5.17 µM. Apicidin significantly reduced the expression of MUC4 and its transcription factor hepatocyte nuclear factor 4α. Combined treatment with a sub-therapeutic concentration of apicidin and gemcitabine synergistically inhibited growth of Capan-1 cells. CONCLUSION: Apicidin appears to be a novel anti-proliferative agent against pancreatic cancer cells that may reverse chemoresistance by epigenetically regulating MUC4 expression.
Subject(s)
Deoxycytidine/analogs & derivatives , Drug Resistance, Neoplasm/genetics , Epigenesis, Genetic/drug effects , Gene Expression Regulation, Neoplastic/drug effects , Mucin-4/genetics , Pancreatic Neoplasms/genetics , Peptides, Cyclic/pharmacology , Antimetabolites, Antineoplastic/pharmacology , Cell Line, Tumor , Deoxycytidine/pharmacology , Dose-Response Relationship, Drug , Drug Screening Assays, Antitumor , Histone Deacetylase Inhibitors/pharmacology , Humans , Pancreatic Neoplasms/drug therapy , Small Molecule Libraries , GemcitabineABSTRACT
BACKGROUND/AIM: Mucin 4 (MUC4) is a cell surface glycoprotein that is overexpressed in most pancreatic tumors. The aim of the present study was to characterize MUC4 expression in experimental pancreatic cancer in order to clarify the correlation between MUC4 and pancreatic cancer histology in vivo. MATERIALS AND METHODS: Pancreatic xenograft tumors were generated in immunodeficient mice (n=15) by subcutaneous injection of MUC4(+) human pancreatic cancer cell lines Capan-1, HPAF-II or CD18/HPAF. MUC4 immunoreactivity was compared between the cancer models. Alpha-smooth muscle actin (α-SMA) was used to identify cancer-associated fibroblasts and the amount of collagen fibers was quantified with sirius red. RESULTS: Tumor incidence was 100%. Tumor size showed no difference across groups (p=0.796). The median MUC4 count was highest in Capan-1 tumors (p=0.002). α-SMA and collagen extent were also highest in Capan-1 tumors (p=0.018). CONCLUSION: The Capan-1 xenograft model could serve as a valuable resource to test new therapeutic strategies targeting MUC4 in pancreatic cancer.
