Taku Nakahara

Glycoconjugate Data Bank:Structures—an annotated glycan structure database and N-glycan primary structure verification service

Glycobiology has been brought to public attention as a frontier in the post-genomic era. Structural information about glycans has been accumulating in the Protein Data Bank (PDB) for years. It has been recognized, however, that there are many questionable glycan models in the PDB. A tool for verifying the primary structures of glycan 3D structures is evidently required, yet there have been no such publicly available tools. The Glycoconjugate Data Bank:Structures (GDB:Structures, http://www.glycostructures.jp) is an annotated glycan structure database, which also provides an N-glycan primary structure (or glycoform) verification service. All the glycan 3D structures are detected and annotated by an in-house program named ‘getCARBO’. When an N-glycan is detected in a query coordinate by getCARBO, the primary structure of the glycan is compared with the most similar entry in the glycan primary structure database (KEGG GLYCAN), and unmatched substructure(s) are indicated if observed. The results of getCARBO are stored and presented in GDB:Structures.

Prognostic value of altered N-glycosylation of circulating glycoproteins in patients with unresectable pancreatic cancer treated with gemcitabine.

Objectives The objectives of this study were to examine the whole-serum N-glycan profile of patients with unresectable pancreatic cancer and to evaluate the ability of glycans to predict gemcitabine treatment efficacy and patient survival. Methods We collected serum from 52 patients with advanced pancreatic cancer before they began gemcitabine monotherapy. The serum glycan profile was measured through comprehensive quantitative high-throughput glycome analysis and compared with the treatment efficacy and patient survival. Results Of the 61 glycans detected, the serum levels of glycan 4310 (molecular weight [m/z] 1549.566), 6301 (m/z 2032.724), and 9200 (m/z 2010.692) were high in patients with a short time to tumor progression (TTP). Multivariate analysis revealed that a high glycan 9200 concentration was an independent risk factor for shorter TTP (hazard ratio, 2.11; 95% confidence interval, 1.07–4.17) and poor overall survival (hazard ratio, 2.56; 95% confidence interval, 1.08–6.19). The median TTP of patients with up-regulation of 9200 after gemcitabine treatment was shorter than for the remaining patients (91 vs 301 days; P = 0.0005). A similar relationship was observed for overall survival (median, 181 vs 561 days; P = 0.001). Conclusions Glycan 9200 is a possible biomarker predicting gemcitabine efficacy survival in patients with unresectable pancreatic cancer.

High-throughput glycomics for discovery of cancer biomarkers.

9 Background: While the importance of glycosylation in many cancers is well established, the use of glycomics in biomarker research has lagged behind genomics and proteomics. This is due, in part, to the lack of practical platforms capable of analyzing clinically relevant sample numbers. To address these challenges, we have developed a novel glycomics technology (the GlycanMap platform) that combines a high-throughput assay with custom bioinformatics and rapidly provides both biomarker candidates and information on the underlying biology. METHODS N-glycans were enzymatically released from their parent glycoproteins and captured on chemoselective beads. After washing to remove non-glycan components, purified glycans were derivatized to stabilize labile sialic acids and released from the beads. The steps described above were automated on a 96-well format robotics system to maximize throughput and reduce variability and can be performed in less than 24 hours. Released glycans were analyzed by MALDI-TOF MS using internal standards to facilitate quantitation. In addition to comparing individual glycans between groups, glycan changes were also analyzed with respect to known glycan biosynthetic pathways. RESULTS The automated assay was compatible with multiple biological sample types, including serum/plasma, tissue, and cell lysates. Human serum was used to assess assay performance and yielded 50-60 glycans with CVs of 10-15% and good linearity. The lower limit of detection was approximately 100 nM. The assay was applied to drug-treated colon cancer cells (HCT116) and revealed significant (> 2-fold) changes in 17 glycans. Projection of these glycan changes on the known N-glycan pathway showed that the most significant changes occurred in the medial-Golgi. CONCLUSIONS We have developed and optimized a high-throughput glycomics platform to facilitate large-scale biomarker studies and assured its practical performance in terms of sensitivity, repeatability, and linearity. Application of this assay to drug-treated colon cancer cells demonstrated that projection of individual glycan changes against known glycan pathways provided additional information about biological mechanism and relevance.