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Targeting Carbohydrates inCancer–Analytical and
Biotechnological Tools
Henrique O. Duarte
1
2
3
4
1,2
, Joana Gomes
1,2
, and Celso A. Reis
1,2,3,4
6.1 Aberrant Protein Glycosylation inCancer
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.

162
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 invivo 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 invitro and invivo 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
(Figure6.1).
163
Figure6.1 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.

164
6.2 Detection and Mapping ofCarbohydrate-Based
Antigens inHuman 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)
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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 invitro 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 MUC2intestinal 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.
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