A strategy is developed in this study for identifying sialylated glycoprotein markers in human cancer serum. This method consists of three steps: lectin affinity selection, a liquid separation and characterization of the glycoprotein markers using mass spectrometry. In this work, we use three different lectins (Wheat Germ Agglutinin, (WGA) Elderberry lectin,(SNA), Maackia amurensis lectin, (MAL)) to extract sialylated glycoproteins from normal and cancer serum. Twelve highly abundant proteins are depleted from the serum using an IgY-12 antibody column. The use of the different lectin columns allows one to monitor the distribution of alpha(2,3) and alpha(2,6) linkage type sialylation in cancer serum vs that in normal samples. Extracted glycoproteins are fractionated using NPS-RP-HPLC followed by SDS-PAGE. Target glycoproteins are characterized further using mass spectrometry to elucidate the carbohydrate structure and glycosylation site. We applied this approach to the analysis of sialylated glycoproteins in pancreatic cancer serum. Approximately 130 sialylated glycoproteins are identified using microLC-MS/MS. Sialylated plasma protease C1 inhibitor is identified to be down-regulated in cancer serum. Changes in glycosylation sites in cancer serum are also observed by glycopeptide mapping using microLC-ESI-TOF-MS where the N83 glycosylation of alpha1-antitrypsin is down regulated. In addition, the glycan structures of the altered proteins are assigned using MALDI-QIT-MS. This strategy offers the ability to quantitatively analyze changes in glycoprotein abundance and detect the extent of glycosylation alteration as well as the carbohydrate structure that correlate with cancer.

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Glycoproteins play important roles in various biological processes including intracellular transport, cell recognition, and cell-cell interactions. The change of the cellular glycosylation profile may have profound effects on cellular homeostasis and malignancy. Therefore, we have developed a sensitive screening approach for the comprehensive analysis of N-glycans and glycosylation sites on human serum proteins. Using this approach, N-linked glycopeptides were extracted by double lectin affinity chromatography. The glycans were enzymatically cleaved from the peptides and then profiled using capillary hydrophilic interaction liquid chromatography coupled online with ESI-TOF MS. The structures of the separated glycans were determined by MALDI quadrupole ion-trap TOF mass spectrometry in both positive and negative modes. The glycosylation sites were elucidated by sequencing of PNGase F modified glycopeptides using nanoRP-LC-ESI-MS/MS. Alterations of glycosylation were analyzed by comparing oligosaccharide expression of serum glycoproteins at different disease stages. The efficiency of this method was demonstrated by the analysis of pancreatic cancer serum compared to normal serum. Ninety-two individual glycosylation sites and 202 glycan peaks with 105 unique carbohydrate structures were identified from approximately 25 mug glycopeptides. Forty-four oligosaccharides were found to be distinct in the pancreatic cancer serum. Increased branching of N-linked oligosaccharides and increased fucosylation and sialylation were observed in samples from patients with pancreatic cancer. The methodology described in this study may elucidate novel, cancer-specific oligosaccharides and glycosylation sites, some of which may have utility as useful biomarkers of cancer.

Pancreatic cancer is the fourth leading cause of cancer-related death in the United States, with a 5-year survival rate of less than 4%. Effective early detection and screening are currently not available, and tumors are typically diagnosed at a late stage, frequently after metastasis. Existing clinical markers of pancreatic cancer lack specificity, as they are also found in inflammatory diseases of the pancreas and biliary tract. In the work described here, naturally occurring glycoproteins were enriched by using lectin affinity chromatography and then further resolved by nonporous reversed-phase chromatography. Glycoprotein microarrays were then printed and probed with a variety of lectins to screen glycosylation patterns in sera from normal, chronic pancreatitis, and pancreatic cancer patients. Ten normal, 8 chronic pancreatitis, and 6 pancreatic cancer sera were investigated. Data from the glycoprotein microarrays were analyzed using bioinformatics approaches including principal component analysis (PCA) and hierarchical clustering (HC). Both normal and chronic pancreatitis sera were found to cluster close together, although in two distinct groups, whereas pancreatic cancer sera were significantly different from the other two groups. Both sialylation and fucosylation increased as a function of cancer on several proteins including Hemopexin, Kininogen-1, Antithrombin-III, and Haptoglobin-related protein, whereas decreased sialylation was detected on plasma protease C1 inhibitor. Target alterations on glycosylations were verified by lectin blotting experiments and peptide mapping experiments using microLC-ESI-TOF. These altered glycan structures may have utility for the differential diagnosis of pancreatic cancer and chronic pancreatitis and identify critical differences between biological samples from patients with different clinical conditions.