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A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of α-1-β glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p

A unique approach of automating the integration of monolithic capillary HPLC-based protein separation and on-plate digestion for subsequent MALDI-MS analysis has been developed. All liquid-handling procedures were performed using a robotic module. This automated high-throughput method minimizes the amount of time and extensive labor required for traditional in-solution digestion followed by exhaustive sample cleanup and analysis. Also, precise positioning of the droplet from the capillary HPLC separation onto the MALDI plate allows for preconcentration effects of analytes for improved sensitivity. Proteins from primary esophageal Barrett's adenocarcinoma tissue were prefractionated by chromatofocusing and analyzed successfully by this automated configuration, obtaining rapid protein identifications through PMF and sequencing analyses with high sequence coverage. Additionally, intact protein molecular weight values were obtained as a means to further confirm protein identification and also to identify potential sequence modifications of proteins. This simple and rapid method is a highly versatile and robust approach for the analysis of complex proteomes.

We describe a label-free relative quantification LC-MS/MS method for core-fucosylation in alpha-2-macroglobulin (A2MG) immunoprecipitated from human sera. The method utilizes endoglycosidase F partial deglycosylation to reduce glycosylation microheterogeneity, while retaining the innermost N-acetylglucosamine (GlcNAc) and core fucose. Precursor ion peak areas of partially deglycosylated peptides were obtained and site-specific core-fucosylation ratios based on the peak areas of core-fucosylated and nonfucosylated counterparts were calculated and evaluated for assay development. This assay was applied in a preliminary study of sera samples from normal controls and patients with pancreatic diseases, including pancreatic cancer and chronic pancreatitis. A2MG fucosylation levels at sites N396 and N1424 were found to decrease in both chronic pancreatitis and pancreatic cancer compared to normal controls. The two sites were identified by two peptides and their core-fucosylation ratios were found to be internally consistent. This method provides a platform to quantify fucosylation levels and can be used to study site-specific core-fucosylation aberrations in other glycoproteins for other diseases.

We describe a label-free relative quantification LC-MS/MS method for core-fucosylation in alpha-2-macroglobulin (A2MG) immunoprecipitated from human sera. The method utilizes endoglycosidase F partial deglycosylation to reduce glycosylation microheterogeneity, while retaining the innermost N-acetylglucosamine (GlcNAc) and core fucose. Precursor ion peak areas of partially deglycosylated peptides were obtained and site-specific core-fucosylation ratios based on the peak areas of core-fucosylated and nonfucosylated counterparts were calculated and evaluated for assay development. This assay was applied in a preliminary study of sera samples from normal controls and patients with pancreatic diseases, including pancreatic cancer and chronic pancreatitis. A2MG fucosylation levels at sites N396 and N1424 were found to decrease in both chronic pancreatitis and pancreatic cancer compared to normal controls. The two sites were identified by two peptides and their core-fucosylation ratios were found to be internally consistent. This method provides a platform to quantify fucosylation levels and can be used to study site-specific core-fucosylation aberrations in other glycoproteins for other diseases.

Protein microarrays have been used to explore whether a humoral response to pancreatic cancer-specific tumor antigens has utility as a biomarker of pancreatic cancer. To determine if such arrays can be used to identify novel autoantibodies in the sera from pancreatic cancer patients, proteins from a pancreatic adenocarcinoma cell line (MIAPACA) were resolved by 2-D liquid-based separations, and then arrayed on nitro-cellulose slides. The slides were probed with serum from a set of patients diagnosed with pancreatic cancer and compared with age- and sex-matched normal subjects. To account for patient-to-patient variability, we used a rank-based non-parametric statistical testing approach in which proteins eliciting significant differences in the humoral response in cancer compared with control samples were identified. The prediction analysis for microarrays classification algorithm was used to explore the classification power of the proteins found to be differentially expressed in cancer and control sera. The generalization error of the classification analysis was estimated using leave-one-out cross-validation. A serum diagnosis of pancreatic cancer in this set was predicted with 86.7% accuracy, with a sensitivity and specificity of 93.3 and 80%, respectively. Candidate autoantibody biomarkers identified using this approach were studied for their classification power by performing a humoral response experiment on recombinant proteins using an independent sample set of 238 serum samples. Phosphoglycerate kinase-1 and histone H4 were noted to elicit a significant differential humoral response in cancer sera compared with age- and sex-matched sera from normal patients and patients with chronic pancreatitis and diabetes. This work demonstrates the use of natural protein arrays to study the humoral response as a means to search for the potential markers of cancer in serum.