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Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5904_Библиотеки_им_академика_М_И_Перельмана

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Targeting Carbohydrates inCancer–Analytical and Biotechnological Tools
Henrique O. Duarte
1


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

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
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
1,2
, Joana Gomes
1,2
, and Celso A. Reis
1,2,3,4
6.1 Aberrant Protein Glycosylation inCancer
161
Glycosylation is defined as the enzymatic assembly of complex carbohydrate chains, or glycans, from simple monosaccharide sugar building blocks, and their covalent attachment to a diverse range of macromolecules to form an ensemble of distinct types of glycoconjugates, which, as a whole, constitute the cellular glycome [1]. Depending on the nature of their nonglycan component, glycoconjugates can be grouped into glycosphingolipids, proteoglycans, and glycoproteins. Glycoproteins constitute the main focus of this chapter. Although numerous cytoplasmic proteins represent eligible targets for dynamic glycosylation, the majority of a cell’s glycan repertoire decorates both secreted and membrane‐bound macromolecules[2]. The oligosaccharidic component of cell surface glycoproteins, which faces the extracel­lular space, forms an electron‐dense layer known as the glycocalyx, which, under homeostasis, actively regulates a plethora of biological processes occurring inside and around a cell. Indeed, this layer of glycoconjugates constitutes a vital interface between a cell and the surrounding microenvironment, which includes not only neighboring cells but also noncellular components, such as elements of the extra­cellular matrix (ECM). This privileged localization grants the cellular glycome sig­nificant control over key biological processes, including proliferation, differentiation, motility, cytoskeletal rearrangements, inter‐ and extracellular communication, and neoplastic transformation[3].
The major glycan signatures that are significantly enriched in tumor cells and
that have been mechanistically linked to malignant cellular transformation include:
Carbohydrate-Based Therapeutics, First Edition. Edited by Roberto Adamo and Luigi Lay. © 2024 WILEY-VCH GmbH. Published 2024 by WILEY-VCH GmbH.
 
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highly branched N‐glycan chains [4], highly fucosylated and sialylated glycans (including Lewis antigens)[5, 6], extended lactosamine polymers[7], and short pre­maturely terminated O‐glycan structures (such as Tn, sialyl Tn [STn], and T antigens) [8]. The upregulation of specific aberrant carbohydrate antigens is accom panied by the concomitant reduction of specific homeostatic signatures, including bisected N‐glycans. Aberrant glycan traits actively tune key malignant properties of proteins participating in central cellular processes driving oncogenic transformation, including mitogenic signaling, cell adhesion, motility, and invasion; metabolic regulation; interaction with cellular and acellular components of the immune system; angiogenic growth; apoptosis evasion; and acquisition of molecu­lar resistance to targeted therapeutic agents[1, 9–11].
Given that tumor‐associated carbohydrate antigens (TACAs) have their expres­sion highly restricted to neoplastic tissues and play an undeniable role in the gov­erning of malignant cell behavior, they have emerged as valuable theranostic tools in the clinical oncology field, either as robust and specific biomarkers for disease detection and monitoring, or as promising, yet still underexplored candidates for therapeutic targeting[10, 12–14]. Such efforts require the thorough characterization of aberrant tumor‐specific glycan alterations in patient neoplastic lesions as well as the mechanistic dissection of their oncogenic role through the establishment of robust in vitro and invivo models of disease. However, several structural and bio­logical features of glycans pose unique challenges to their study. Firstly, despite the limited number of monosaccharides from which complex carbohydrates can be generated, glycans exhibit remarkable structural diversity stemming from: the spe­cific composition and sequence of their constituent building blocks; the precise ano­meric configuration and position of glycosidic linkages; variable degrees of branching and extension; and their potential to undergo further structural modifi­cations, including sulfation, phosphorylation, and acetylation. Secondly, as glyco­sylation reflects the post-translational modification of multiple proteins, the accurate identification and tissue mapping of specific glycan epitopes through the use of traditional immunohistochemical approaches based on monoclonal antibod­ies (mAbs) and glycan‐binding proteins (GBPs), including lectins of mammalian or plant origin, can be difficult to achieve. Furthermore, the expression of a single carbohydrate product results from the coordinated expression, activity, and localiza­tion of multiple isoenzymes, often showing partially redundant and overlapping specificities. This significantly increases the biological complexity required from genome‐edited invitro and invivo models for the dissection of glycan biosynthetic pathways. Moreover, the cellular glycosylation landscape is highly dynamic and sensitive to spatiotemporal regulation, which further compromises the translational value of data retrieved from simpler glycoengineered cell and animal models. In addition, since identical monosaccharide compositions often reflect distinct tridi­mensional carbohydrate structures with distinct functional attributes, the develop­ment of analytical tools capable of retrieving isomeric linkage information has become fundamental for glycan structural characterization. Finally, although infor­mation on the glycan site occupancy and microheterogeneity of a given glycoprotein
    
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is essential to define its biological role, it may prove difficult to determine experi­mentally. Indeed, linking a particular glycan structure to a defined biological func­tion remains a challenging task.
This chapter will discuss how recently developed analytical and biotechnological tools have significantly contributed to overcome the challenges posed by the unique features of glycans and their intricate biosynthetic pathways, thus supporting the structural and functional characterization of protein glycosylation in the context of human neoplastic transformation and the successful establishment of glycan‐based biomarkers and therapeutic targets for the clinical management of cancer patients (Figure6.1).
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Figure6.1 Biotechnological and analytical tools for the identification, functional characterization, and clinical application of glycan-based cancer biomarkers; FFPE - formalin-fixed paraffin-embedded; MS - mass spectrometry; GT - glycosyltransferase; GBP - glycan-binding protein.
 
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6.2 Detection and Mapping ofCarbohydrate-Based Antigens inHuman Neoplastic Tissues
Over the past decades, numerous studies have sought to comprehensively charac­terize both the nature and impact of glycosylation alterations occurring within malignant cells and tissues (reviewed in[9]). In particular, the advent of hybridoma technology just under 50 years ago has supported the generation of a virtually unlimited catalog of highly specific mAbs for the reliable detection of any type of biological antigen, including glycans, and has, therefore, revolutionized the field of cancer biomarker discovery[15]. Indeed, the development of highly specific mAbs targeting TACAs, such as the prematurely truncated O‐glycan determinant STn, allowed the unprecedented disclosure of their tissue-based cancer‐specific expres­sion pattern [16–18]. In the hybridoma system, activated immunoglobulin‐secreting B cells, previously challenged with an isolated and structurally defined antigen of interest (ideally), are fused with myeloma cells, generating a hybrid, isogenic, and immortalized cell line with antibody‐producing capacity [19]. Generally, mAb‐ based tissue mapping of entirely peptidic epitopes with a known sequence can be performed with reasonable certainty, as the specificity of the used mAb can be accu­rately determined. However, the signals produced by carbohydrate‐binding mAbs often reflect the expression of a variety of distinct protein carriers, which hinders the precise identification of the target glycan epitope[20]. The same limitation applies to other glycan‐recognizing molecules whose carbohydrate specificity is not fully determined, including polyclonal antibody mixtures and other GBPs. The poor affinity of lectins, usually in the low micromolar range, frequently limits their appli­cation for histochemical staining purposes[1, 21]. Indeed, these glycan‐ binding molecules do not provide insights on complete monosaccharide compositions, gly­can tridimensional conformation, glycosylation site occupancy, microheterogene­ity, or the precise location of glycan chains on the backbone of specific glycoproteins. Such affinity reagents facilitate the identification of broader glycosylation traits (e.g. N‐glycan branching, core fucosylation, and linkage‐specific sialylation) rather than elucidating the exact tridimensional structure of individual glycan species. In fact, such information may only be accurately retrieved through the implementation of increasingly complex mass spectrometry (MS)‐based methods. However, the major­ity of glycan‐directed analytical techniques, including MS‐based workflows, require analyte extraction from the target tissue, which, in turn, leads to the loss of informa­tion on glycan spatial distribution and tissue histopathological architecture.
6.3 Imaging Mass Spectrometry
The recent development and maturation of imaging mass spectrometry (IMS) tech­nology has significantly contributed to the circumvention of such technical limita­tions since it does not rely on target‐specific reagents but rather on direct molecular measurements[22]. Indeed, this technique has been used to directly characterize the N‐glycosylation profile of neoplastic tissue sections by generating two‐ and
   
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three‐dimensional (3D) molecular maps of hundreds of distinct glycan species across a wide mass range while also providing information on analyte relative abun­dance and on‐tissue spatial distribution, which can be directly linked to the histo­pathological data from the same clinical specimen [22–29]. The IMS technology provides the mass accuracy and chemical specificity of MS‐based detection and sup­ports further on‐tissue tandem MS fragmentation (e.g. collision‐induced fragmenta­tion) to achieve exact structure identification while still preserving the spatial distribution of individual analytes and the histopathological landscape of the target tissue. The implementation of IMS workflows in the cancer research field is of par­ticular relevance since most clinically approved cancer biomarkers are either glyco­proteins or carbohydrate antigens.
The typical IMS glycomic workflow requires the total release of asparagine‐linked N‐glycans through the surface digestion of the target tissue section with Peptide‐N‐ glycosidase F (PNGase F), an endoglycosidase that efficiently hydrolyzes the amide bond linking the innermost N‐acetylglucosamine (GlcNAc) of the N‐glycan core to the asparagine’s side chain of the protein’s peptidic backbone, and the subsequent MS‐based identification and relative quantification of the released carbohydrate species. Possible additives in the enzyme’s storage buffer, including glycerol or detergents, may cause ion suppression during the ionization process, which dimin­ishes the quality of the retrieved spectra[30, 31]. IMS‐based analysis of biological samples can be performed using one of several MS ionization techniques, which offer complementary capabilities regarding both spatial resolution and the mass range of the target analytes. The matrix‐assisted laser desorption/ionization (MALDI)‐IMS has become increasingly popular in the analysis of glycans due to its high sensitivity and wide mass range. The preparation of tissue sections involves the automated and uniform coating of the target sample with an energy‐absorbing matrix for efficient and homogeneous analyte ionization. Conveniently, IMS work­flows are compatible with on‐tissue sialic acid (Neu5Ac) chemical derivatization, which allows for linkage‐specific discrimination of sialylated glycan species, and with positive glycan labeling, which significantly improves signal‐to‐noise ratios [29, 32]. Generated molecular maps of analyte spatial distribution and relative abundance can then be overlapped with brightfield optical images, such as the cor­responding hematoxylin/eosin (H&E) staining of the same tissue section. The obtained structural and semiquantitative data can then be allocated to well‐defined histological regions (e.g. nontransformed adjacent mucosa, immune infiltrate, necrosis, and tumor regions) based on a pathologist’s annotation, making the IMS technology particularly valuable in the study of solid tumors. Furthermore, subse­quent off‐tissue extraction and MS‐based fragmentation of released N‐glycan spe­cies allow for unequivocal structural identification. Typically, the MALDI‐IMS analysis of one cancer tissue section allows the reliable detection of 40–60 distinct glycan structures[33].
This methodology is highly versatile, and its robustness has been validated across various types of clinical samples, including formalin‐fixed paraffin‐embedded (FFPE) tissue blocks and fresh frozen tissue specimens[23, 24, 34–36]. The incorpo­ration of multiple individual FFPE tissue specimens in the tissue microarray (TMA)
165
 
166
format reduces intersample technical variability and further allows the IMS‐based multiplexed analysis of larger cohorts of clinical samples, which is of extreme rele­vance to the cancer biomarker discovery field, particularly when conducting retro­spective studies[36]. Moreover, the proven applicability of IMS in the analysis of FFPE tissues is of extreme significance since these samples can be easily archived at room temperature for several years in tissue banks and biorepositories and are more widely available than cryopreserved clinical specimens. Additionally, by directly linking detailed and spatially resolved structural data to well‐defined histopatho­logical regions at the individual sample scale, IMS‐based analysis of whole tissue sections provides invaluable molecular insights on intratumor heterogeneity. This is of particular relevance when defining tumor margins and interfaces. IMS analysis of neoplastic tissues has clearly demonstrated the expression of tumor‐associated molecular signatures in apparently healthy histological regions. The comprehensive comparative characterization and relative quantification of glycan species from nontransformed adjacent mucosa, premalignant lesions, and fully transformed neo­plastic regions may lead to the identification of robust glycan‐based biomarkers of malignant transformation capable of accurately discriminating patient clinical out­comes and tumor subtypes. The MALDI‐IMS technology has been successfully used to illustrate the astonishing differences in the glycosylation patterns between cor­responding healthy and malignant tissues across multiple epithelial cancers, includ­ing prostate, pancreatic, ovarian, gastric, and hepatocellular carcinoma, as well as myxoid liposarcoma[24–28, 33, 35, 37]. IMS technology has thus emerged as a novel source of robust cancer‐specific biomarkers, either as individual glycan masses or as more complex panels of combined mass spectra from multiple glycan species, for unequivocal tissue region identification.
Recently optimized methods are capable of the simultaneous multimodal acquisi­tion of MALDI‐IMS spectra derived from both N‐glycans and proteolytic peptides from the same tissue section[38]. The spatial distribution map of identified peptidic sequences can then be combined with the corresponding N‐glycan map for the iden­tification of overlapping regions. Subsequent bioinformatic analysis may lead to the identification of glycoprotein candidates, and their spatial distribution can be fur­ther assigned to well‐defined histological regions. Such studies may provide mecha­nistic insights on the functional roles played by particular glycan signatures in malignant cell transformation, in particular through the identification of proteins modified with specific aberrant glycan determinants. Furthermore, the combina­tion of N‐glycan‐ and protein‐derived structural data may provide novel combinato­rial sets of cancer‐specific biomarkers with improved sensitivity and specificity.
6.4 In Situ Proximity Ligation Assay
The unbiased and comprehensive identification of glycoproteins for biomarker dis­covery purposes through on‐tissue IMS analysis can be laborious and time‐ consuming. Moreover, glycoprotein validation through direct immunoprecipitation experiments from cryopreserved clinical specimens can be technically challenging
due to heterogeneous or reduced expression of the target protein and the require-
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ment of considerable amounts of starting frozen material. Furthermore, although methodologies based on genetically modified cell models represent powerful tools to dissect the interactome of specific proteins, they are not compatible with patient samples. On the other hand, traditional immuno‐ or lectin‐based histochemical staining methods remain limited to the detection and tissue mapping of individual proteins and carbohydrate signatures while overlooking biologically significant molecular interactions. In addition, such techniques do not allow the unequivocal identification of the protein carriers that are modified with a given type of glycan structure. To circumvent such technical limitations, numerous studies have instead pursued the direct on‐tissue validation of specific protein glycoform candidates, ini­tially identified in invitro models of malignant transformation, using large cohorts of tumor clinical samples. As a result, several oncogenic proteins modified with specific glycosylation signatures may emerge as more sensitive and specific bio­markers of human malignancy when compared to more classical biomarkers target­ing fully peptidic or carbohydrate‐based epitopes.
The in situ
proximity ligation assay (PLA) allows the on‐tissue detection, imag­ing, and relative quantification of a plethora of cellular events at single‐molecule resolution, including protein–protein interactions, protein translation, and degrada­tion, as well as multiple post-translational modifications such as protein phospho­rylation and glycosylation. This assay relies on the dual binding of highly specific affinity reagents, such as primary antibodies or lectins, for the in situ detection of the molecular proximity between two prespecified target epitopes on either FFPE or cryopreserved tissue specimens[39, 40]. In this method, a pair of affinity reagents labeled with single‐stranded DNA molecules, also termed oligonucleotide proxim­ity/detection probes, are bound to their respective target epitopes in a whole tissue section. If the epitopes recognized by both antibodies/lectins are found in close molecular proximity (10–40 nm), a proper detection complex is formed, which allows for the antibody‐bound oligonucleotide molecules to be enzymatically joined into a circular DNA strand through rolling‐circle amplification. The resulting DNA ligation product can then serve as a template for PCR‐based multimeric signal amplification. The final amplification product can then be hybridized with fluores­cent or chromogenic oligonucleotide strands (detection probes) for microscopic visualization and counting of individual spots at single complex resolution. The requirement for two proximal recognition reactions ensures highly selective map­ping of interacting complexes since individual probe binding is insufficient to pro­duce visible detection signals. In the typical approach to identify proteins carrying specific glycosylation traits, one antibody binds to a peptidic epitope within the tar­get protein, and a second glycan‐ binding affinity reagent (mAb or lectin) targets the carbohydrate motif. Conveniently, the in situ PLA method can be performed using labeled secondary affinity reagents, avoiding the need for the conjugation of numer­ous pairs of primary antibodies or lectins. The PLA methodology is highly versatile, as a myriad of affinity reagents can be readily and easily converted into proximity probes. This is of particular significance when studying protein‐specific glycosyla­tion reactions, as it allows the use of carbohydrate‐binding lectins for the detection
1676.4 In Situ 
 
168
of the target glycoprotein’s glycan component. The successful implementation of the PLA system requires several methodological considerations, such as the optimi­zation of histochemical staining protocols for each individual target antigen and possible incompatibilities with antigen retrieval steps. Furthermore, for the same target epitope, multiple affinity reagents may have to be tested since the oligonu­cleotide conjugation reaction may sterically hinder their antigen‐binding capacity. Although the exact minimal distance required for the generation of a positive PLA signal has yet to be fully investigated, such values may be estimated and optimized based on the dimensions of the selected affinity reagents and lengths of the oligonu­cleotide strands. Despite its high selectivity and nanometric resolution, in situ PLA provides only indirect evidence on molecular interactions or protein modifications[41].
Over the past decade, several studies have successfully used the PLA technology to validate, in whole tissue tumor clinical samples, the modification of several cancer‐associated proteins with aberrant glycan antigens, aiming at the identifica­tion of clinically relevant diagnostic and prognostic biomarker candidates. Such is the example of the MUC2intestinal mucin and the CD44 co‐receptor, both disclosed by fluorescence‐based PLA as carriers of the short‐truncated O‐glycan epitope STn in advanced gastric adenocarcinomas[42–44]. The PLA‐based association between
x
the sialyl Lewis x (sLe
) tetrasaccharide and several membrane‐anchored proteins in gastric cancer tissues, including the RON receptor tyrosine kinase (RTK) and the carcinoembryonic antigen (CEA) adhesion molecule, has further unveiled the active role played by aberrant glycans in tuning the malignant features of oncogenic
x
receptors[45, 46]. Of note, the expression of sLe
‐containing CEA proteoforms was associated with worse patient clinical outcome, portraying the PLA technology as a valuable source of prognostic markers. Recently, the E‐cadherin cellular adhesion molecule has been validated as a molecular carrier of highly branched N‐glycan chains by brightfield PLA analysis of advanced gastric adenocarcinoma tissue sec­tions, highlighting this particular E‐cadherin glycoform as a robust predictive bio­marker of patient dismal prognosis[47]. In addition, the use of PLA technology has demonstrated the modification of the oncogenic ErbB2 RTK, which currently remains one of the few actionable therapeutic targets in the gastric cancer setting, with α2,6‐linked Neu5Ac moieties in whole tissue sections of intestinal‐type gastric carcinomas[48]. In situ PLA analysis has also provided valuable insights on the glycosylation status of mucin receptors required for Helicobacter pylori (H. pylori) adhesion to the gastric epithelium of glycoengineered mice models[49]. The com­bination of glycan metabolic labeling with the PLA‐based analysis of protein– carbohydrate interactions has allowed the disclosure of the mechanistic contribution of specific glycan traits (e.g. sialylation and fucosylation) to various functional aspects of cancer‐relevant proteins at the subcellular scale, including the turnover and ligand‐induced dimerization of oncogenic cell surface receptors[50].
Importantly, the in situ PLA technology holds tremendous translational potential as it may be readily incorporated into the routine workflows of cancer‐dedicated pathology laboratories as a robust source of novel glycoprotein‐based biomarkers bearing both diagnostic and prognostic utility, thus improving patient stratification and clinical management.
  
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6.5 Glycan Microarrays
Although the exact dimension of the cellular glycome remains a matter of debate, it is estimated to be in the range of 100 Such structural diversity has created the need for molecular tools capable of linking the structure of a given glycan to its biological function. The development of glycan microarrays, just under 20
years ago, has propelled the high‐throughput systematic interrogation of glycan‐based molecular interactions[52–55]. By facilitating the fast and highly reproducible screening of a great number of glycan epitopes and compo­sitions, this technology has allowed the unprecedented elucidation of the carbohydrate‐binding specificity of a multitude of pathogens, whole cells, and GBPs. Indeed, the use of glycan microarrays for the comprehensive validation of the glycan ligand repertoire of several mAbs and plant-derived lectins has solidified their applicability as invaluable research tools to address the role of glycans in bio­logical systems[54, 56–58]. The Consortium for Functional Glycomics (CFG) has used glycan microarray technology to disclose the detailed specificity of over 100 plant lectins (http://www.functionalglycomics.org/)[59]. Furthermore, the binding specificity and affinity data provided by glycan microarrays will pave the way for the rational design of carbohydrate‐based therapeutic agents. Printed carbohydrate microarrays enable the simultaneous analysis of thousands of binding events between a single target analyte (e.g. lectin, soluble ligand, and mAb) and a minia­turized catalog containing hundreds of spatially defined glycan species immobilized onto a solid phase in a covalent or noncovalent manner[54, 60]. Moreover, the con­densation of hundreds of different ligands into a miniaturized format significantly reduces the required amount of both the target analyte and each unique immobi­lized ligand. In addition, glycan microarrays represent ideal platforms for the screening of glycan‐dependent molecular interactions by allowing the multivalent display of immobilized ligands on a solid surface, which mimics the weak and reversible nature of cell–cell interactions. Additionally, glycan microarrays are highly reproducible, cost‐effective, and allow the fast screening of multiple samples.
Depending on the biological question, different types of macromolecules can be immobilized on the array solid substrate (e.g. glycans, glycoproteins, glycopeptides, mAbs, or lectins), giving rise to a diversified set of platforms. A standard‐size micro­scope glass slide represents the original solid surface for ligand immobilization and remains the most widely used[61]. In the case of glycan microarrays, the immobilized library of pure carbohydrate structures can be either chemically synthesized or iso­lated from natural sources[53, 55, 58, 62, 63]. Chemoenzymatic strategies combining automated glycan assembly with selected enzymatic steps allow the controlled syn­thesis of glycosaminoglycans, branched N‐glycans, and sialylated structures in a linkage‐specific manner [64–68]. The selection of the most appropriate strategy for the covalent or noncovalent immobilization of glycans onto the solid phase depends on the synthetic method used in the preparation of a given glycan library or the source from which naturally occurring ligands are isolated. Glycans produced by fully chemi­cal or chemoenzymatic synthesis are derivatized with orthogonal bi‐functional link­ers to allow their covalent attachment to a functionalized solid surface[69, 70]. On the
000–500 000 unique glycan structures[51].
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other hand, naturally occurring carbohydrates, such as milk oligosaccharides and free reducing glycans released from glycoproteins by enzymatic digestion or chemical hydrolysis, also require proper derivatization prior to immobilization[55, 62, 71, 72]. Although, in principle, polysaccharides can be directly attached to the array by simple adsorption, enzymatically released glycans require the introduction of a functional group at their reducing end, which can be accomplished through different conjuga­tion strategies.
Immobilized ligand libraries are spotted with micrometric resolution onto the selected surface by automated arraying robots in a prespecified, spatially resolved manner. For a single carbohydrate ligand, several replicates of serial concentrations are printed. Since glycans naturally establish low‐affinity interactions with other macromolecules, the density at which individual glycan structures are spotted onto the microarray surface is a determinant in the generation of detectable signals and subsequent data interpretation[73]. After spotting is concluded, a washing step is performed for the removal of unbound carbohydrate molecules. A single‐array slide may contain up to 20 000 spots[74]. Despite the significant advances in the chemical synthesis of structurally defined glycan chains made over the last two decades, both the number and structural diversity of the glycans that can be immobilized onto a single microarray remain far from representative of the human glycome’s estimated dimension[72, 73].
The glycan microarray technology has been most extensively applied in the dis­section of protein–carbohydrate interactions, namely in the characterization of the binding specificity of mAbs and GBPs[54, 75–77]. There are several possible strate­gies for the detection and quantification of bound molecular partners at the micro­array surface. In the case of glycan microarrays, the analytes of interest, either in a pure isolated form (e.g. single GBP) or as a complex mixture (e.g. serum), are labeled and incubated on the solid substrate to allow ligand binding. Following the washing of unbound macromolecules, the signal emitted by the labeled bound analytes can be detected and quantified in individual spatially resolved spots, each one corre­sponding to a unique glycan structure. Fluorescence‐based quantification of ligand binding remains the most widely used method for signal detection due to its high sensitivity and wide availability of fluorescence scanning equipment[62, 69, 70, 78]. Of note, the labeling of proteins with fluorescent tags may lead to protein denatura­tion or alterations in their carbohydrate‐binding domain. Alternatively, a fluores­cently tagged antibody for the recognition of bound analytes can be used. An adaptation of this detection strategy, known as sandwich array, relies on the use of fluorescently labeled secondary antibodies or lectins for the detection of ligands bound to the microarray solid substrate via a primary set of immobilized antibod­ies[79]. Due to the limited availability of specific carbohydrate‐recognizing anti­bodies and lectins, label‐free detection methods, such as quantitative on‐chip MS and surface plasmon resonance (SPR), have become increasingly popular for signal quantification[80]. Interestingly, SPR‐based analysis of glycan microarray signals provides valuable quantitative parameters on the reaction kinetics, including asso­ciation and dissociation constants. As the volume and complexity of information generated by glycan microarrays grow exponentially, so does the need for software tools and algorithms capable of comprehensive and integrative data analysis.