Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal cancer (CRC). Following immunodepletion of the most abundant plasma proteins, the plasma N -linked glycoproteins were enriched using lectin affinity chromatography and subsequently further separated by nonporous silica reversed-phase (NPS-RP)-HPLC. Individual RP-HPLC fractions were printed on nitrocellulose coated slides which were then probed with lectins to determine glycan patterns in plasma samples from 9 normal, 5 adenoma, and 6 colorectal cancer patients. Statistical tools, including principal component analysis, hierarchical clustering, and Z-statistics analysis, were employed to identify distinctive glycosylation patterns. Patients diagnosed with colorectal cancer or adenomas were shown to have dramatically higher levels of sialylation and fucosylation as compared to normal controls. Plasma glycoproteins with aberrant glycosylation were identified by nano-LC-MS/MS, while a lectin blotting methodology was used to validate proteins with significantly altered glycosylation as a function of cancer progression. The potential markers identified in this study for diagnosis to distinguish colorectal cancer from adenoma and normal include elevated sialylation and fucosylation in complement C3, histidine-rich glycoprotein, and kininogen-1. These potential markers of colorectal cancer were subsequently validated by lectin blotting in an independent set of plasma samples obtained from 10 CRC patients, 10 patients with adenomas, and 10 normal subjects. These results demonstrate the utility of this strategy for the identification of N -linked glycan patterns as potential markers of CRC in human plasma, and may have the utility to distinguish different disease states.

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.

Protein glycosylation has been implicated in key biological processes including immunological recognition, cellular adhesion, protein folding, and signaling as well as disease progression. Although several methods are available to assess glycosylation of protein structures, none of them is able to screen complex biological samples at a global as well as an individual scale. A novel strategy presented here uses an all-liquid phase enrichment and prefractionation methodology coupled to glycoprotein microarray technology using a multiple lectin-based, biotin-streptavidin detection scheme. Selective detection of glycan structures was made possible by employing multiple lectins to screen glycoprotein standards as well as serum samples from normal subjects or patients with chronic pancreatitis or pancreatic cancer. Interestingly, in some instances, a greater degree of glycosylation was seen in proteins that were underexpressed based on the reversed-phase chromatogram alone. Studies with standard proteins established the limits of detection to be in the 2.5-5-fmol range. Studies on serum samples showed differences in glycosylation patterns, particularly with respect to sialylation, mannosylation, and fucosylation, in normal, pancreatitis, and cancer sera. By coupling glycoprotein enrichment and fractionation with a microarray platform, we have shown that naturally occurring glycoproteins from human serum can be screened and characterized for different glycan structures, thereby allowing one to do comparative studies that monitor individual glycosylation changes within a glycoproteome representing different biological states. This approach may be useful to identify potential biomarkers in cancer.

Protein glycosylation plays an important role in a multitude of biological processes such as cellcell recognition, growth, differentiation, and cell death. It has been shown that specific glycosylation changes are key in disease progression, and can have diagnostic value for a variety of disease types such as cancer and inflammation. The complexity of carbohydrate structures and their derivatives makes their study a real challenge. Improving the isolation, separation, and characterization of carbohydrates and their glycoproteins is a subject of increasing scientific interest. With development of new stationary phases and molecules that have affinity properties for glycoproteins, the isolation and separation of these compounds have advanced significantly. In addition to detection with mass spectrometry, the microarray platform has become an essential tool to characterize glycan structure and to study glycosylation-related biological interactions, by using probes as a means to interrogate the spotted or captured glycosylated molecules on the arrays. Furthermore, the high-throughput and reproducible nature of microarray platforms have been highlighted by its extensive applications in the field of biomarker validation, where a large number of samples must be analyzed multiple times. This review covers a brief survey of the other experimental methodologies that are currently being developed and used to study glycosylation, and emphasizes methodologies that involve the use of microarray platforms. This review describes recent advances in several options of microarray platforms used in glycoprotein analysis, including glycoprotein arrays, glycan arrays, lectin arrays, and antibody/lectin arrays. The translational use of these arrays in applications related to characterization of cells and biomarker discovery is also included.