Identifying N-Glycan Biomarkers in Colorectal Cancer by Mass

Sep 21, 2016 - Her project was focused on proteomic and glycomic analysis of colorectal cancer by mass spectrometry techniques to understand the assoc...
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Identifying N‑Glycan Biomarkers in Colorectal Cancer by Mass Spectrometry Manveen K. Sethi,† William S. Hancock,‡,§ and Susan Fanayan*,§ †

Department of Chemistry and Biomolecular Sciences, Macquarie University, North Ryde, NSW 2109, Australia Barnett Institute and Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States § Department of Biomedical Sciences, Macquarie University, North Ryde, NSW 2109, Australia ‡

CONSPECTUS: Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Delineating biological markers (biomarkers) for early detection, when treatment is most effective, is key to prevention and long-term survival of patients. Development of reliable biomarkers requires an increased understanding of the CRC biology and the underlying molecular and cellular mechanisms of the disease. With recent advances in new technologies and approaches, tremendous efforts have been put in proteomics and genomics fields to deliver detailed analysis of the two major biomolecules, genes and proteins, to gain a more complete understanding of cellular systems at both genomic and proteomic levels, allowing a mechanistic understanding of the human diseases, including cancer, and opening avenues for identification of novel gene and protein based prognostic and therapeutic markers. Although the importance of glycosylation in modulating protein function has long been appreciated, glycan analysis has been complicated by the diversity of the glycan structures and the large number of potential glycosylation combinations. Driven by recent technological advances, LC-MS/MS based glycomics is gaining momentum in cancer research and holds considerable potential to deliver new glycan-based markers. In our laboratory, we investigated alterations in N-glycosylation associated with CRC malignancy in a panel of CRC cell lines and CRC patient tissues. In an initial study, LC-MS/MS-based N-glycomics were utilized to map the N-glycome landscape associated with a panel of CRC cell lines (LIM1215, LIM1899, and LIM2405). These studies were subsequently extended to paired tumor and nontumorigenic CRC tissues to validate the findings in the cell line. Our studies in both CRC cell lines and tissues identified a strong representation of high mannose and α2,6-linked sialylated complex N-glycans, which corroborate findings from previous studies in CRC and other cancers. In addition, certain unique glycan determinants such as bisecting β1,4-GlcNAcylation and α2,3-sialylation, identified in the metastatic (LIM1215) and aggressive (LIM2405) CRC cell lines, respectively, were shown to be associated with epidermal growth factor receptor (EGFR) expression status. In this Account, we will describe the mass spectrometry based N-glycomics approach utilized in our laboratory to accurately profile the cell- and tissue-specific N-glycomes associated with CRC. We will highlight altered N-glycosylation observed by our studies, consistent with findings from other cancer studies, and discuss how the observed alterations can provide insights into CRC pathogenesis, opening new avenues to identify novel disease-associated glycan markers.

1. INTRODUCTION Colorectal cancer (CRC) is among the top three most prevalent cancers in terms of global incidence and mortality.1 The most important factor influencing outcome for CRC patients is early detection, while tumors are still localized, and the 5-year survival rate is >95%.2,3 Unfortunately current CRC screening tests suffer from low patient compliance due to their invasive, unpleasant, and inconvenient nature and high cost (colonoscopy) or lack of specificity and sensitivity (fecal occult blood testing).4,5 It is widely accepted that a new generation of screening tests, based on molecular biomarkers present in biological samples, would lead to increased patient compliance and improved survival. However, despite intense activity in biomarker research, translation of novel and reliable CRC biomarkers into clinically validated and commercially viable © 2016 American Chemical Society

assays has not yet eventuated. Currently, carcinoembryonic antigen (CEA) is the most widely used serum glycoprotein biomarker in CRC but lacks sensitivity and specificity when used for early detection.6,7 Similarly, other proposed CRC glycoprotein biomarkers, such as carbohydrate antigen 19-9 (CA 19-9), also lack sensitivity and specificity and are unsuitable for early detection.6−9 Cancer progression is accompanied by several parameters, including changes in the extent and nature of protein glycosylation and increased levels of blood glycoproteins,10−12 which is not surprising given that over 50% of current cancer biomarkers are glycoproteins.13 Aberrations in glycan structure Received: April 21, 2016 Published: September 21, 2016 2099

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Figure 1. Schematic representation of biosynthesis and processing of N-linked oligosaccharides.

early processing of N-glycans by subsequent trimming in the ER, and (iii) maturation and modification of N-glycans by attachment of new residues to the nonreducing end, in the Golgi apparatus. Synthesis of N-glycan precursor is initiated by the formation of the LLO precursor through the sequential addition of monosaccharides, catalyzed by various glycosyltransferases, to form the glycan precursor Glc3Man9GlcNAc2. This 14-sugar unit is then transferred to the asparagine residue of the Asn-X-Ser/Thr sequon in the acceptor protein, a step catalyzed by oligosaccharyl transferase (OST), and undergoes subsequent trimming, extension, and modification in the ER and Golgi by a complex series of reactions to form hybrid or complex type N-glycans (Figure 1).

can result from a range of different mechanisms, including (i) differential regulation of enzymes, such as glycosyltransferases and glycosidases involved in glycosylation biosynthesis and degradation, (ii) deregulation of sugar donors and transporters, and (iii) competition between glycosylation enzymes for the same sugar substrate.14 Numerous studies have demonstrated the link between aberrant glycosylation and tumor behavior, by promoting tumor progression, metastasis, and invasion.15,16 Mapping the tumor glycome, along with information on the proteome, will provide a better understanding of disease pathogenesis. Driven by this knowledge and recent technological advances in mass spectrometry (MS)-based glycomics and glycoproteomics, tumor-associated glycans are explored for specific tumor markers and potential therapeutic targets.17−19

3. PREPARATION OF ENRICHED MEMBRANE PROTEOME FOR GLYCAN ANALYSIS Enrichment of certain protein subpopulations, such as glycoproteins, or specific subcellular fractions, such as plasma membrane, prior to omics analyses offers the advantage of reducing sample complexity and access to lower abundance proteins as well as providing insights into the subcellular localization of specific proteins. In our recent studies to profile CRC cell line- and tissue-derived N-glycans, we first enriched membrane proteins from these samples (Figure 2) to reduce sample complexity for a greater access to low abundant membrane-bound glycoproteins. High speed ultracentrifugation (∼100 000g) was used to separate postnuclear supernatant (PNS) into membrane and cytosolic fractions, followed by phase partitioning with triton X-114 to enrich integral membrane proteins.22 N-glycans were then released from the enriched membrane proteins, using the protocol outlined by Jensen et al.23 The first step in sample preparation is enzymatic release of N-glycans from the protein backbone with peptide-Nglycosidase F (PNGase F) enzyme (Figure 2). PNGase F is an asparagine deamidase that specifically cleaves between the asparagine residue and the innermost GlcNAc.14 Besides PNGase F, which removes almost all types of N-glycans,

2. MAMMALIAN PROTEIN GLYCOSYLATION Nearly half of all mammalian proteins are glycosylated, making glycosylation one of the most abundant post-translational modifications.20 Glycans are involved in a number of important biological processes including, cell adhesion, proliferation, differentiation and migration, cell−matrix interaction, cell signaling, and immune response.21 Protein glycosylation can be regulated at several levels, either directly by changes in the glycosylation machinery or indirectly by alterations in the protein substrate, with no associated changes in the glycosylation machinery. In mammals, glycans are most commonly attached either to an asparagine residue within the consensus sequence Asn-XSer/Thr (N-linked glycosylation) or to the consensus-free serine or threonine residue (O-linked glycosylation). All Nglycans share a common core structure (Man3GlcNAc2) and are classified into three main types: high mannose type, complex type, and hybrid type. In eukaryotes, biosynthesis of N-glycans occurs in the endoplasmic reticulum (ER) and Golgi apparatus in an elaborate process, involving three major steps and a plethora of different glycosidase and glycotransferase enzymes: (i) assembly of lipid-linked oligosaccharide (LLO) precursor, (ii) 2100

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steps are needed to remove excess borate and other impurities prior to LC-MS analysis.

4. LIQUID CHROMATOGRAPHY MASS SPECTROMETRY-BASED ANALYSIS OF N-GLYCANS Recent advances in MS methods and instruments, capable of accurate and reliable detection of low amounts of oligosaccharides, coupled with separation methods such as liquid chromatography (LC-MS) or capillary electrophoresis (CEMS), have made MS a key technology for glycan analysis. The hyphenated technique allows a simpler work flow by combining sample separation with the highly sensitive structural characterization of MS. Liquid chromatography coupled to tandem MS (LC-MS/MS) is the most widely used hyphenated technique, which offers accurate structural elucidation of glycans, with high sensitivity and analytical versatility and small sample requirement. Some examples of the various LC-based separation methods include reversed-phase LC (RPLC),28−30 hydrophilic interaction LC (HILIC),31,32 high pH anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD),33 and porous graphitized carbon chromatography (PGC).34,35 PGC, which was utilized in our glycomics study (Figure 2), is a versatile, sensitive, and powerful separation technique, with excellent capability for separation of structural and linkage isomers of glycans as well as isobaric glycan species. The high separation power of PGC-LC has been used to resolve high mannose isomers and complex N-glycan structures such as Lewisx/a/y/b structures36,37 or separate mixtures of complex type N-glycans such as bisecting, fucosylated, and sialylated N-glycans. Moreover, PGC is capable of separating mono-, di-, tri-, and tetra-antennary sialylated glycans, and when coupled with exoglycosidase treatment, a better separation and quantitation of such glycan classes can be achieved.38 Certain structural features of N-glycans are known to influence the retention or elution behavior of PGC, for example, earlier elution of bisecting GlcNAc-containing N-

Figure 2. Schematic diagram of the protocol for enrichment of membrane glycoproteins, followed by release and processing of Nglycans for LC-MS/MS analysis.

other endoglycosidases such as endoglycosidase H (removes only selected N-linked glycans) as well as chemical deglycosylation methods such as hyrazinolysis24 (removes both N- and O-linked glycans) have also been used for Nlinked glycan release.25,26 Released N-glycans can be analyzed in free native or reduced form, with or without derivatization. Native/reduced free glycans often have lower HPLC-UV/fluorescence and MS sensitivity compared to derivatized glycans, such as those obtained by permethylation with enhanced ionization efficiency and increased detection sensitivity.27 In our study, released Nglycans were reduced with sodium borohydride (NaBH4), which converts the α and β anomers of the reducing terminus to sugar alditols (Figure 2). Extensive desalting and cleanup

Figure 3. CID MS/MS negative ion fragmentation for a complex type N-glycan from CRC tissue samples (m/z 893.3 (2−)). Red circles indicate all fragment ions for the N-glycan structure. Major diagnostic ions are indicated as D ion (m/z 688), D-18 (m/z 670), Z1 (m/z 350), and Z2 (m/z 553). Image taken from Sethi et al.54 Published 2015 by Oxford University Press. 2101

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Figure 4. CRC-, tumor stage-, and EGFR-specific N-glycosylation patterns observed in our CRC N-glycomics study. The size of each N-glycan structure is indicative of its relative abundance in each group. (A) Abundance of high mannose type structures, increased α2,6-sialylation, and reduced α2,3-sialylation in CRC tumors, relative to adjacent normal colon tissues. (B) Higher levels of bisecting GlcNAcylation and lower α2,3sialylation in EGFR+ CRC tumors compared to EGFR− tumor tissues. (C) Higher total sialylation, mainly α2,6-sialylation, and lower bisecting GlcNAcylation and Lewis-type fucosylation in mid- to late stage tumors, relative to early tumors.

glycans compared to their non-bisected counterparts, α2,3linked sialic acid residues relative to α2,6-linked structures, or fucosylated terminal Lewis-type structures compared to core fucosylated isomers.39,40 This unique isomer separation feature provides valuable structural information in disease-centric studies where alterations may only occur in certain determinants. Currently, the two widely used MS methods for glycan analysis are electrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI).41,42 MALDI is primarily based on laser desorption of analytes, cocrystallized with an excess of a solid matrix material and deposited on a substrate, while ESI is a liquid phase ionization technique, which involves spraying of analytes in solution from the tip of an electrically charged capillary into the mass spectrometer. We used ESI ionization in our study, which produces better resolved peaks for glycans compared to MALDI, due to the absence of matrix adduct peaks.43 For detailed structural elucidation, MS-generated information on the accurate molecular mass and the fragmentation pattern (MS/MS or MSn) of the intact glycan of interest were utilized. MS/MS, in particular, has become an essential tool for structural glycomics because it provides data that may yield complete or partial information on the fine structural details of the glycan of interest in only a single round of fragmentation. In tandem MS, collisional induced dissociation (CID) is the most common technique for generation of fragment ions in which the isolated precursor ion is fragmented by energetic collisions with an inert gas (such as nitrogen, argon, or helium). CID, which was used as a fragmentation technique in our CRC Nglycomics studies, induces two types of fragmentation; cleavage of glycosidic links between two monosaccharides and cross-ring cleavages within the sugar ring. We adopted the negative ion mode for N-glycan analysis, capable of generating more abundant and specific diagnostic fragment ions, useful for confident assignment of glycan structures.44−47 A negative ion CID mass spectrum of a complex type N-glycan, observed in our CRC tissue N-glycome, is shown in Figure 3. The sets of diagnostic ions generated include D- and D-18 ions that aided the identification of the glycan substructure on the α1,6 arm and Z1-/Z2-ions to identify α1,6-core fucosylation (m/z 350 and 553).

glycan analysis resulted in the development of several free, online software tools. One such tool is GlycoWorkbench (GWB), employed in our work, which is a popular free online tool and can be used for analysis of both MS and MS/MS spectra of glycans.48 It supports multiple data formats from a variety of MS instrument platforms and has a glycan drawing tool (Glycan Builder) that allows users to draw specific glycan structures and substructures to be annotated. To utilize the glycan fragmentation feature of this tool, the user defines the likely glycan structures (which often can be predicted based on the molecular mass and the rules of the biosynthetic machinery) and inputs the spectral peak lists, following which the software calculates the theoretical glycan fragments and annotates the most likely peaks. We also used the online GlycoMod software49 to predict the possible glycan compositions based on MS-derived molecular masses. Other bioinformatics tools available for analysis of MS glycan data include GlycoX, GlycoSpectrumScan, STAT, SysBioWare, Glycolyzer, SimGlycan, and Glyco-Peakfinder, some of which are publicly available.50 Development of repositories and procedures for sharing and storing of experimental glycan data is also lagging behind genomics and proteomics research, where it is a common practice. Several initiatives for depositing and cataloguing of glycan-related information were launched, including GLYCOSCIENCES.de, KEGG-GLYCAN (Kyoto Encyclopedia of Genes and Genomes Glycans), the Consortium for Functional Glycomics (CFG), GlycomeDB, EUROCarbDB, and GIyTouCan, but only a few have remained due to funding withdrawal. Recently, Unicarb-DB, to which MS/MS glycomics data generated from our work have been deposited, and UnicarbKB were developed as initiatives to centralize these data repositories.51,52

6. ABERRANT N-GLYCOSYLATION OBSERVED IN CRC SAMPLES 6.1. Over-representation of High Mannose and α2,6-Sialylated Glycans in CRC N-Glycome

An abundance of high mannose type structures was a commonly observed feature in both CRC cell lines and tumor tissues (Figure 4A)53,54 and reported in various tumors.55−57 In a recent study, Chik et al. have shown high mannose structures as the most abundant glycan type in a panel of CRC cell lines and CRC tissues.58 Another recent study by Kapiro et al. compared the N-glycan profiles of CRC adenomas and carcinomas and found CRC carcinomas, but not adenomas, to have elevated levels of processed high mannose type N-

5. DATA ANALYSIS Unlike in proteomics where a wide variety of data analysis tools are available, the MS glycan analysis can be labor intensive, requiring extensive manual annotation. Efforts to fully automate 2102

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Accounts of Chemical Research glycans (i.e., Man5GlcNAc2).59 These findings, together with our observations, suggest increased levels of high mannose type N-glycan structures to be a key molecular feature in CRC. Another key observation in our study was increased α2,6sialylation (Figure 4A), which was accompanied by upregulation of ST6GAL1 (which encodes a specific sialyltransferase responsible for catalyzing α2,6-sialylation) at the transcript level.53,54 Interestingly, high ST6GAL1 expression has been associated with tumors with greater potential for progression, invasion, and metastasis as well as epithelial mesenchymal transition (EMT) in different cancers, including CRC, breast, ovarian, and hepatocellular carcinoma.55,60−63 Similar observation of preferential α2,6-sialylation in CRC, coupled with reduced expression of α2,3-linked sialylated glycans, has been previously reported,62,64,65 which together with our data further confirm the importance of ST6GAL1 and α2,6-sialylation in CRC pathogenesis and their potential clinical utility.

sialylation in the CRC cells.53 CRC-specific oversialylation, contributed primarily by overrepresentation of α2,6-sialylation, has been confirmed by a lectin histochemical study, showing strong staining with Sambucus nigra agglutinin (which recognizes α2,6-sialic acid) and weak staining with Maackia amurensis (which recognizes α2,3-sialic acid).77 Conversely, mid- to late tumor tissues were characterized with lower bisecting GlcNAcylation and Lewis-type fucosylation (Figure 4C).54 Lewis epitopes have been implicated in diverse biological processes such as cell signaling, growth, apoptosis, adhesion, and migration, with some recognized as tumor markers and used in the clinical diagnosis and prognosis of certain cancers.78 The lower levels of bisecting GlcNAc structures in advanced stage CRC tumors is in agreement with reports of inhibitory effects of these structures on tumor progression and invasion.79−81 Correlation between expression of Lewis type fucosylation and metastatic and invasive potential has also been demonstrated in different cancers.82−86

6.2. Certain N-Glycan Features Correlate with Metastatic Phenotypes and EGFR Expression in CRC

An interesting observation in our CRC glycomics study was the correlation between the phenotypic states of the CRC cell lines and expression of certain N-glycan features. One such example was the unique expression of bisecting type GlcNAcylation in the metastatic LIM1215 CRC cell line and its absence in LIM1899 and LIM2405,53 which was somewhat a surprising observation since N-acetylglucosaminyltransferase III (GnTIII), and its bisecting GlcNAc structures have been proposed as suppressors of cancer metastasis.65−68 Exclusive expression of α2,3-sialylated residues in the aggressive LIM2405 CRC cell line was another interesting observation.53 High expression of α2,3-sialyltransferase and α2,3-sialyl epitopes have been reported in different cancers, including skin, breast, and pancreatic cancers, and shown to correlate with increased motility, invasion, and metastatic potential of tumor cells.69−71 While a link between α2,6sialylation and the invasion and metastasis potential of CRC tumors has been previously reported,60,72 no positive correlation between CRC invasion or metastasis and α2,3sialylation has yet been shown. These observations indicate that the expression of these epitopes may also depend on other factors such as the EGFR expression status of the cell lines (LIM1215 EGFR+ and LIM12405 EGFR−) in addition to their metastatic and aggressive behavior. Similar relationship between EGFR expression status and Nglycosylation profiles was also observed in CRC tissue samples, with significantly higher levels of bisecting GlcNAcylation and lower α2,3-sialylation in EGFR+ CRC tissues compared to EGFR− tissues (Figure 4B).54 Notably, no EGFR-specific Nglycosylation was observed in normal colon tissues, suggesting a regulatory mechanism, dependent, at least in part, on EGFR expression for the N-glycosylation landscape of the CRC tissues. EGFR activity has been shown to be regulated by Nglycosylation features, including sialylation, fucosylation, and bisecting GlcNAcylation, as well as certain glycosyl enzymes such as N-acetylgalactosaminyltransferase 2 (GALNT2) and MGAT5.73−76

7. SUMMARY AND OUTLOOK This Account presents an overview of the capacity of presentday LC-MS/MS-based N-glycomics technologies, which were employed in our laboratory to accurately map the glycan alterations associated with CRC pathogenesis. While allowing high-resolution structural determination of the N-glycans, there are certain limitations associated with the MS technologies employed in our study, including (i) lower MS sensitivity of native glycans compared to derivatized glycans, (ii) more pronounced signal intensities of acidic glycans compared to neutral glycans detected in negative-ion mode,87 and (iii) absence of sulfated N-glycans in the glycome profiles from our CRC tissue and cell line studies, most likely due to an alkaline NaBH4-based elimination of these relatively labile glycan modifications prior to PGC-LC-MS/MS analysis. It should be noted that such potential biases and limitations would most likely not affect the overall conclusions provided by this work since the individual glycans within the glycome profiles were compared between samples and as such any biases or technical limitations would be reflected across the whole glycome profiles, irrespective of their biological origin. The detailed N-glycan profiles and CRC-related altered glycosylation patterns illustrated by our work provide a knowledge base for better understanding of CRC pathophysiology. Further explorations and validations by larger sample cohorts and targeted N-glycan strategies are warranted to establish the underlying regulatory mechanisms.



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest. Biographies

6.3. Tumor Stage-Specific N-Glycan Features in CRC

Manveen K. Sethi obtained her Ph.D. in 2015 with Dr. Morten Thaysen-Andersen and Dr. Susan Fanayan (Macquarie University). Her project was focused on proteomic and glycomic analysis of colorectal cancer by mass spectrometry techniques to understand the associated biomolecular deregulations. Currently, she is a postdoctoral researcher in the laboratory of Prof. Joseph Zaia at Boston University

Correlation between N-glycosylation profiles and disease stage and progression was also observed. Higher total sialylation, predominantly contributed by α2,6-sialylation, was found in mid- to late CRC stages, relative to early stage tumors (Figure 4C).54 α2,6-Sialylation was also observed as the major form of 2103

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(14) Sethi, M. K.; Fanayan, S. Mass spectrometry-based N-glycomics of colorectal cancer. Int. J. Mol. Sci. 2015, 16, 29278−29304. (15) Kannagi, R.; Sakuma, K.; Cai, B. H.; Yu, S. Y. Tumor-associated glycans and their functional roles in the multistep process of human cancer progression. In Sugar Chains; Suzuki, T., Ohtsubo, K., Taniguchi, N., Eds.; Springer: Tokyo, Japan, 2015; pp 139−158. (16) Glavey, S. V.; Huynh, D.; Reagan, M. R.; Manier, S.; Moschetta, M.; Kawano, Y.; Roccaro, A. M.; Ghobrial, I. M.; Joshi, L.; O’Dwyer, M. E. The cancer glycome: Carbohydrates as mediators of metastasis. Blood Rev. 2015, 29, 269−279. (17) Watson, M. E.; Diepeveen, L. A.; Stubbs, K. A.; Yeoh, G. C. Glycosylation-related diagnostic and therapeutic drug target markers in hepatocellular carcinoma. J. Gastrointest. Liver Dis. 2015, 24, 349−357. (18) Wang, D.; Liu, X.; Hsieh, B.; Bruce, R.; Somlo, G.; Huang, J.; Sambucetti, L. Exploring glycan markers for immunotyping and precision-targeting of breast circulating tumor cells. Arch. Med. Res. 2015, 46, 642−650. (19) Zhao, Y. P.; Zhou, P. T.; Ji, W. P.; Wang, H.; Fang, M.; Wang, M. M.; Yin, Y. P.; Jin, G.; Gao, C. F. Validation of N-glycan markers that improve the performance of CA19−9 in pancreatic cancer. Clin. Exp. Med. 2015, DOI: 10.1007/s10238-015-0401-2. (20) Apweiler, R.; Hermjakob, H.; Sharon, N. On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database. Biochim. Biophys. Acta, Gen. Subj. 1999, 1473, 4−8. (21) Varki, A. Biological roles of oligosaccharides: all of the theories are correct. Glycobiology 1993, 3, 97−130. (22) Mathias, R. A.; Chen, Y. S.; Kapp, E. A.; Greening, D. W.; Mathivanan, S.; Simpson, R. J. Triton X-114 phase separation in the isolation and purification of mouse liver microsomal membrane proteins. Methods 2011, 54, 396−406. (23) Jensen, P. H.; Karlsson, N. G.; Kolarich, D.; Packer, N. H. Structural analysis of N- and O-glycans released from glycoproteins. Nat. Protoc. 2012, 7, 1299−1310. (24) Mechref, Y.; Novotny, M. V. Structural investigations of glycoconjugates at high sensitivity. Chem. Rev. 2002, 102, 321−369. (25) Maley, F.; Trimble, R. B.; Tarentino, A. L.; Plummer, T. H., Jr. Characterization of glycoproteins and their associated oligosaccharides through the use of endoglycosidases. Anal. Biochem. 1989, 180, 195− 204. (26) Hagan, A. K.; Wang, M.; Liu, L. Current approaches to glycoprotein analysis. Protein Pept. Lett. 2014, 21, 986−999. (27) Alvarez-Manilla, G.; Warren, N. L.; Abney, T.; Atwood, J., 3rd.; Azadi, P.; York, W. S.; Pierce, M.; Orlando, R. Tools for glycomics: relative quantitation of glycans by isotopic permethylation using 13CH3I. Glycobiology 2007, 17, 677−687. (28) Wuhrer, M.; Deelder, A. M.; Hokke, C. H. Protein glycosylation analysis by liquid chromatography-mass spectrometry. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 2005, 825, 124−133. (29) Chen, X.; Flynn, G. C. Analysis of N-glycans from recombinant immunoglobulin G by on-line reversed-phase high-performance liquid chromatography/mass spectrometry. Anal. Biochem. 2007, 370, 147− 161. (30) Wuhrer, M.; Koeleman, C. A.; Deelder, A. M. Two-dimensional HPLC separation with reverse-phase-nano-LC-MS/MS for the characterization of glycan pools after labeling with 2-aminobenzamide. Methods Mol. Biol. 2009, 534, 79−91. (31) Wuhrer, M.; de Boer, A. R.; Deelder, A. M. Structural glycomics using hydrophilic interaction chromatography (HILIC) with mass spectrometry. Mass Spectrom. Rev. 2009, 28, 192−206. (32) Zauner, G.; Deelder, A. M.; Wuhrer, M. Recent advances in hydrophilic interaction liquid chromatography (HILIC) for structural glycomics. Electrophoresis 2011, 32, 3456−3466. (33) Rohrer, J. S.; Thayer, J.; Weitzhandler, M.; Avdalovic, N. Analysis of the N-acetylneuraminic acid and N-glycolylneuraminic acid contents of glycoproteins by high-pH anion-exchange chromatography with pulsed amperometric detection. Glycobiology 1998, 8, 35−43. (34) Ruhaak, L. R.; Deelder, A. M.; Wuhrer, M. Oligosaccharide analysis by graphitized carbon liquid chromatography-mass spectrometry. Anal. Bioanal. Chem. 2009, 394, 163−174.

School of Medicine, working on glycomic and proteomic study of extracellular matrix abnormalities in schizophrenic brain. William S. Hancock received his Ph.D. in Chemistry in 1970 and a D.Sc. in 1993 from the University of Adelaide, South Australia. He holds the Bradstreet Chair in Bioanalytical Chemistry within the Barnett Institute of Chemical and Biological Analysis at Northeastern University (Boston, MA). His main research interests are the study of biomarkers (proteins and glycoproteins) for detection and monitoring of diseases such as cancer, autoimmune (psoriasis, rheumatoid arthritis, multiple sclerosis), and diabetes through proteomic platforms such as HPLC coupled to ion trap and Fourier transform mass spectrometry. Susan Fanayan received her Ph.D. in cancer biology from the University of Sydney. She then joined Jennifer A. Byrne at the Westmead Children’s Hospital (Sydney) as a postdoctoral fellow, followed by another postdoctoral position with Professor Mark S. Baker at Macquarie University (Sydney), in 2008. Since 2009, she has been a group leader at Macquarie University. Her research interests include development of lectin affinity chromatography for discovery of disease-associated changes in glycan composition and identification of early cancer biomarkers through proteomics and glycoproteomics.



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