Abstract
Pancreatic cancer is now the fourth leading cause of cancer deaths in the United States, and it is associated with an alarmingly low 5-year survival rate of 5%. However, a patient's prognosis is considerably improved when the malignant lesions are identified at an early stage of the disease and removed by surgical resection. Unfortunately, the absence of a practical screening strategy and clinical diagnostic test for identifying premalignant lesions within the pancreas often prevents early detection of pancreatic cancer. To aid in the development of a molecular screening system for early detection of the disease, we have performed glycomic and glycoproteomic profiling experiments on 21 pancreatic cyst fluid samples, including fluids from mucinous cystic neoplasms and intraductal papillary mucinous neoplasms, two types of mucinous cysts that are considered high risk to undergo malignant transformation. A total of 80 asparagine-linked (N-linked) glycans, including high mannose and complex structures, were identified. Of special interest was a series of complex N-linked glycans containing two to six fucose residues, located predominantly as substituents on β-lactosamine extensions. Following the observation of these "hyperfucosylated" glycans, bottom-up proteomics experiments utilizing a label-free quantitative approach were applied to the investigation of two sets of tryptically digested proteins derived from the cyst fluids: 1) all soluble proteins in the raw samples and 2) a subproteome of the soluble cyst fluid proteins that were selectively enriched for fucosylation through the use of surface-immobilized Aleuria aurantia lectin. A comparative analysis of these two proteomic data sets identified glycoproteins that were significantly enriched by lectin affinity. Several candidate glycoproteins that appear hyperfucosylated were identified, including triacylglycerol lipase and pancreatic α-amylase, which were 20- and 22-fold more abundant, respectively, following A. aurantia lectin enrichment.
Highlights
From the ‡Chemistry Department of Indiana University, Bloomington, Indiana 47405, the ¶Indiana University School of Medicine, Indianapolis, Indiana 46202, and the §National Center for Glycomics and Glycoproteomics, Bloomington, Indiana 47405
Pancreatic cysts are divided into three broad pathologic entities: serous cystadenomas (SCA),1 mucinous cystic neoplasms (MCN), and intraductal papillary mucinous neoplasms (IPMN)
As a consequence of the low numbers for the individual diagnoses (NSCA ϭ 3, NPC ϭ 4, NMCN ϭ 6, and NIPMN ϭ 7), the relative abundances included in the table are only rough approximations, and analysis of many more cysts would be necessary to clearly define the ranges of relative abundance for each of these structures in the pathologically different fluids
Summary
Patients and Pancreatic Cyst Fluid Collection—Twenty-one patients with pancreatic cysts identified by high-resolution cross-sectional imaging, including computed tomography or magnetic resonance imaging, were included in this study. Salts and other by-products were eluted during the washing step, whereas the N-glycans retained on the activated charcoal microspin columns were recovered using a 0.2-ml aliquot of 50% acetonitrile/H2O (v/v) containing 0.1% TFAA This wash was repeated four times, and all of the eluents were collected and evaporated using an Eppendorf Vacufuge. The filter membranes were prepared prior to the addition of cyst fluid by washing with 500 l of deionized water, followed by centrifugation for 15 min at 10 krpm. The following criteria were used: trypsin selected as the enzyme, one missed cleavage allowed from trypsin digestion, Ϯ 0.02 Da tolerance for precursors, Ϯ 0.8 Da for fragment peaks, ϩ2 and ϩ3 charges, carbamidomethylation of cysteine (fixed modification), oxidation of methionine (variable modification), ion score Ն 30, expect Յ 0.1, accept only bold red queries, rank 1 identifications, and a minimum peptide mass of 600.00 Da. A randomized UniProt database was queried with the same specifications, and the results were used to estimate the false discovery rate as previously described [21]. The protein area is a sum of the peptide areas
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