Applications

Changes in glycosylation are a hallmark of many cancers and inflammatory diseases and show great potential as clinical disease markers.

The interaction of cell surface glycans with complementary glycan binding proteins (lectins) located on neighboring cells, other cell types, or pathogens like virus, bacteria or parasitesmediates is crucial in biologically and biomedically important processes like cell–cell adhesion, cell migration, development, pathogen recognition and infection. Their implication in nearly every pathological condition, consequently suggests an increasing role for glycans as disease markers.

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Only absolute glycan quantification can provide a complete picture of the disease related changes and will provide the method robustness required by clinical applications.

The entry into the clinical practice of glycan markers is delayed in large part due to a lack of adequate methodology for the precise and robust quantification of protein glycosylation. Probably the most important area for absolute quantification of specific glycan levels is clinical diagnostics, which requires robust, reliable and precise methods for the quantification of disease markers. A large number of glycan biomarker studies have revealed the perturbation of glycan profiles, but methods for quantifying singlemarkers in the context of a complexmatrix are still underdeveloped. As a result, the decade-long exploration of glycans as biomarkers has not been matched by their introduction as disease markers into clinical practice. An important reason for this could be the lack of robust, transferable and quantitative methods for themeasurement of single glycans in the clinical practice.

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Several applications in the field of glycobiology research and proteomics:

  • Rapid Absolute glycan quantification
  • Increase reproducibility in lab-to-lab method transfer (internal calibration standard)
  • De-convolute and quantify co-eluting peaks in LC-MS
  • Quantify glycan recovery after sample preparation
  • Protein characterization: Quick determination of the glycosylation profile of a expressed recombinant protein depending on the heterologous host. Correlation of the differences in glycosylation and protein function

Read more…

MALDI-Tof MS employing internal stable isotope labeled glycan standards is genuinely suited for clone selection and process development where highthroughput glycoprofiling is required. Our fast sample preparation and data aquisition routines permit the analysis of hundreds of samples with unparalleled speed.

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Most eukaryotic proteins, both membrane bound and soluble, and the large majority of commercial recombinant therapeutic proteins are modified with N-glycans that can have a major impact on protein solubility, structure, immunogenicity, circulatory half-life, and consequently drug efficacy.

Isotopic dilution mass spectrometry has been the golden standard for absolute metabolite quantification in newborn screening, quantification of immunosuppressor levels, in screening for illicit drugs, and in various approaches for quantitative proteomics. An application of isotopic dilution to glycan analysis, however, has been hampered largely by a lack of heavy isotope labeled glycan standards.

Read more…

Clinical Biomarker Discovery

Changes in glycosylation are a hallmark of many cancers and inflammatory diseases and show great potential as clinical disease markers.

The interaction of cell surface glycans with complementary glycan binding proteins (lectins) located on neighboring cells, other cell types, or pathogens like virus, bacteria or parasitesmediates is crucial in biologically and biomedically important processes like cell–cell adhesion, cell migration, development, pathogen recognition and infection.

Their implication in nearly every pathological condition, consequently suggests an increasing role for glycans as disease markers. The majority of mammalian proteins are N-glycosylated, a common post-translational modification of the asparagine residue within the consensus sequence Asn-X-Ser/ Thr. N-glycans are large complex and branched glycans that share a common pentasaccharide core and present considerable microheterogeneity due to variations in the number of antennae, terminal glycan residues and core modifications.

Glycan Biomarker Research

Although previous glycan biomarker research has also included analysis of glycosphingolipid and glycosaminoglycan levels by mass spectrometry (MS), immunostaining or lectin arrays the focus of most studies has been on the plasma N-glycome followed by the analysis of O-glycans on mucins which are highly over-expressed in carcinomas. This preference can be explained by the high abundance of N-glycans in serumand other body fluids, a manageable number of structures and more mature techniques for sample preparation and analysis of N-glycans compared to those available for other glycan classes. Human N-glycans, that are present on the majority of secreted proteins are easily obtained from a larger number of body fluids including serum/plasma, urine, saliva, tears, milk, semen or amniotic fluid by enzymatic or chemical removal.

Although estimates for the human N-glycan repertoire go as far as 2000 different structures, the currently experimentally accessible human N-glycome is far smaller and very dependent on the employed analytical method. The plasma N-glycome has been reported to contain more than 100 different glycan structures but depending on the analytical method used only a fraction is routinely quantified due to either intense peak overlap during the chromatographic separation or a lack of sensitivity for detecting less abundant species by direct injection methods or MALDI-TOF (matrix assisted laser desorption/ionization coupled to time-of-flight detection) analysis. By nano-liquid chromatography coupled to tandem mass spectrometry (nano-LC MS/MS) recently over 170 distinct N-glycan structures where registered in the plasma glycome and partially assigned by exoglycosidase digestion and diagnostic fragment ions. The 20 most abundant plasma Nglycans that account for over half of the plasma glycome are mono and bis-sialylated or neutral core-fucosylated bi-antennary structures.

These are major structures present on the most abundant plasma glycoproteins like the immunoglobulin isotypes IgG, IgMand IgA, transferrin, alpha-2-macroglobin, C3-complement or haptoglobin. Alpha-2-macroglobin, C3-complement and haptoglobin are acute phase proteins (APPs) which are part of the innate immune system and that show expression levels that are sensitive to inflammatory processes. The high basal concentration of some APPs in plasma together with their significant changes in expression levels during inflammation ranging from 50% of ceruloplasmin to over 1000-fold for the C-reactive protein, can have an impact even on the total serum glycan levels which is measurable as an increase of mobile hexosamine N-acetyl methyl groups by nuclear magnetic resonance (NMR).

Clinical Disease markers

Only absolute glycan quantification can provide a complete picture of the disease related changes and will provide the method robustness required by clinical applications.

The entry into the clinical practice of glycan markers is delayed in large part due to a lack of adequate methodology for the precise and robust quantification of protein glycosylation. Probably the most important area for absolute quantification of specific glycan levels is clinical diagnostics, which requires robust, reliable and precise methods for the quantification of disease markers. A large number of glycan biomarker studies have revealed the perturbation of glycan profiles, but methods for quantifying singlemarkers in the context of a complexmatrix are still underdeveloped. As a result, the decade-long exploration of glycans as biomarkers has not been matched by their introduction as disease markers into clinical practice. An important reason for this could be the lack of robust, transferable and quantitative methods for themeasurement of single glycans in the clinical practice.

Glycosylation not only changes qualitatively but is also increased in absolute terms as several pioneering studies suggest, allowing the definition of clinically relevant cut-off values for individual serumglycan levels for the clinical practice. Elevated serum glycan levels for a large number of structures have been shown in a pancreatic cancer study by Nishimura et al. [1] which show little or no overlap with 95% confidence intervals for healthy controls over a broad age range. As the majority of methods employ mass spectrometry either as a standalone technique or coupled with chromatography for glycan analysis, improvements in reproducibility and robustness of MS facilitating method transfer between labs are urgently needed.

The use of stable isotope labeled glycans as internal standards and heavy-isotope labeling methods will provide the necessary method precision and robustness acceptable for clinical use.

Internal stable isotope labeled standards for glycan quantification.

The use of internal stable isotope labeled standards for glycan quantification by mass spectrometry has the potential to solve many of the current challenges in MS glycan analyses and to aid in the transfer and acceptance of glycan markers into the clinical practice.

An isotopically enriched and quantified internal standard allows the absolute quantification of individual glycan levels in complex mixtures independent of changes in a glycan profile. A recent roadmap report from the US National Research Council highlighted the need for developing isotopically labeled glycan standards formass spectrometry to overcome “the current practice of relative quantification”.

In analogy to existing clinical methods for quantifying metabolites or drug levels we anticipate that a single or a limited number of glycan disease markers will be most efficiently quantified by isotopic dilution e.g. by employing stable isotope labeled glycans. Glycan synthesis has come a long way and current chemo-enzymatic approaches are now capable of producing well defined pure and strategically labeled glycans for this purpose.

The use of internal standards for absolute glycan quantification accelerates glycan analysis rather than slowing it down as any external calibration is unnecessary. This will be particularly the case for the rapid assessment of individual glycan levels as surrogate metabolites, which reflect impact of hereditary and environmental factors on patient physiology, in a platform independent and robust manner.

Cancer Markers

Disease Aberrant glycosylation Glycan biomarker ref
Breast cancer Increased levels of highly sialylated antenna fucosylated glycans. High G1F, A3F1G1, A4F1G1 and A4F2G2 containing sLex 1
Increased levels of fucosylated and sialylated glycans A2F 2, 3
Increased levels of agalactosyl biantennary glycans G0F and glycans containing sLex epitope A3F1G1 and A2F1G1. Increase A3F1G1 and G1F, d G0F with sLex 4
Increased levels of high-mannose type structures. Man5 5
Increased levels of fucosylated glycans. Decreased leveles of sialylated glycans. G0F, G1F ,G2F, A3G0F 6
Gastric cancer Decreased levels of fucosylated non- and mono-sialylated glycans. Increased levels of A2 7
Decreased levels of biantennary asialo monogalactosylated glycans, and triantennary glycans carrying 2,3-linked sialic acids.

Increased levels of triantennary glycans carrying 2,6-linked sialic acids, and trisialylated triantennary glycans carrying sialyl Lewis X.

Decrease G1(3), G1(6) Increased A2F on IgG 8
Hepatocellular carcinoma Decreased levels of a tri- and a tetraantennary glycan. A3G0F, A3G3F, A4 9
Increased levels of the fucosylated triantennary glycan. A3G3F 10
Highly increase in the fucosylation.

 

Decrease of G2F levels correlates with halting of Hepatoma Cell Migration and Invasion

AFP-L3, Fucosylated glycoform of AFP

 

G2F

11,12

 

37

Lung cancer Increased levels of tri- and tetra-antennary highly sialylated glycans, some with antenna and some with core fucosylation.

Decreased levels of biantennary glycans, mostly with core fucose

High Tri- and tetra-sialylated glycans in serum

G0F, G1F ,G2F,

13
Ovarian cancer Increased levels of G0F, and A3G3F 14
Increased levels of core fucosylated agalactosyl biantennary glycans and glycans containing sialyl Lewis X G0F and sLexa3

 

15
Increased levels of tri- and tetra-antennary N-glycans.

Decreased levels of glycans containing a bisecting GlcNAc.

bA2F,A3G0F, A3G3F, A4 16
Increased levels of sialylated glycans and a small group of truncated glycans.

Decreased levels of several neutral glycans, including high-mannose-type glycans

MGn(3)F, MGn(6), A2 17
MUC1 O-glycans in serum Sialylated core 1type O-glycans 18
Prostate cancer Increased core fucosylation and increase a2,3-sialic acid compared with BPH patients serum Decreased A3G3

Decreased A4FS4

Increased A4S4

19
Decreased sialylation of PSA subforms in seminal plasma F3 PSA subform with low S1 and S2

F3 PSA subform with high a2,3 sial and low core fucose

F4 PSA subform with high S1

20, 21
Poor prognosis is associated with decreased levels of fucosylated glycans and increased levels of sialylated compounds 22
Pancreatic cancer Increase of core fucosylation and Lex in tri-antennary glycans Fucosylated haptoglobin 23, 24, 25
Colon cancer Levels of FUT3-7 and FUT9, responsible for a1,3-4 fucosylation at haptoglobin Asn241 a1,3-4 fucosylation at haptoglobin Asn241 2628

Non-Cancer Markers

Disease Aberrant glycosylation Glycan biomarker ref

Rheumatoid arthritis, Systemic lupus erythrematosus, Sjogren’s syndrome, Juvenile-onset chronic arthritis, Crohn´s syndrome, Tuberculosis

Elevated proportion of IgG G0 glycoforms

Reduced degree of antennae sialylation and galactosylation for IgG N glycans

G0F 29-32
Follicular lymphoma IgG and IgM variable region glycans containing one or more oligomannose sugars. Significant increase in potential glycosylation sites in the variable region. Man5-Man9 32
IgA nephropathy Aberrant glycosylation has been linked to diseases in which there is reduced clearance of IgA. Aberrant O-glycosylation of serum IgA1 in patients is ascribed to a decrease in terminal galactosylation and sialylation. Man5, G0F

(inflammation)

32
Primary Sjogren’s syndrome Levels of serum IgA1 and IgA2 are elevated as a result of increased sialylation of the glycans.
Congenital Disorders of Glycosylation Glycan analysis of serum proteins, such as the Igs that collectively account for up to 50% of the serum glycoproteins, provides diagnostic information that can pinpoint the faulty step in the pathway. monoantennary fucosylated and α2,3 sialylated
schistosomiasis unusual O-glycan, glycan epitopes of soluble egg antigens of Schistosoma mansoni Fuc1-2Fuc1-3GalNAc1- 4(Fuc1-2Fuc1-3)
maturity-onset diabetes of the young (MODY) Lewis a in tri- biantennary N-glycans in serum and plasma Lewis a in tri- biantennary N-glycans in serum and plasma 33
Diabetes Severity and duration of glucose dysregulation in individuals can be estimated by monitoring the levels of O-GlcNAc simultaneously at specific sites on several key proteins in erythrocytes. Increase in antenna fucosylation of AGP in plasma from patients with Type 1 Diabetes Mellitus O-GlcNAc 34
Type 2 Diabetes Mellitus increased levels of glycans carrying α1-6 linked fucose G0F, G1F ,G2F,
aging Individuals of ages above 50 had increased levels of non-galactosylated glycans, while the levels of galactosylated structures decreased with increasing age. Bisecting N-acetylglucosamine showed an age-dependency: bisecting GlcNAc is generally increasing with age and seems to reach a plateau at 50 years of age. bA2F  35
aging, smoke and lipid profiles Very large biological variability in glycosylation. Increased ratio of bisecting GlcNAc in IgG of smokers bA2F  36
Alzheimer’s disease The glycosylation pattern of Reelin decrease in fucose content

Biosimilar Glycosylation

Comparability studies of biosimilars reveal that products differ widely in composition and not always meet self-declared specifications. Glycosylation profile can exhibit batch-to-batch variation affecting the activity of a recombinant protein directly, and products that are similar from a qualitative perspective often differ quantitatively in the glycosylation profile, i.e. the clones are undergalactosylated.
Customized mAbsolute kits allow the absolute quantification of  the glycans attached to a given specific biosimilar in a few hours.

BioPharmaceutical N-Glycan Profiling

Most eukaryotic proteins, both membrane bound and soluble, and the large majority of commercial recombinant therapeutic proteins are modified with N-glycans that can have a major impact on protein solubility, structure, immunogenicity, circulatory half-life, and consequently drug efficacy.

Changes in protein glycosylation are also a hallmark of many cancers, infectious and autoimmune diseases, and the growing number of congenital disorders of glycosylation (CDG)4 suggesting an increasingly important role of glycans as biomarkers.

Consequently, robust and quantitative methods for the analysis of glycans are not only required for mapping glycan structure to function but also highly relevant in biopharmaceutical quality control and in the development of glycans as selective and complementary disease markers.

Relative Quantification methods

Many profiling methods require the enzymatic or chemical release of the glycans from the peptide backbone. The resulting mixture of glycans can then be chemo-selectively derivatized with a fluorescent label8 like 2-aminobenzoic acid (2-AA), 2-aminobenzamide (2-AB), or 9-aminopyrene-1,4,6-trisulfonic acid (APTS), separated by HPLC or capillary electrophoresis and analyzed by fluorescence and/or mass spectrometry detection. Alternatively, glycans can be profiled, often after permethylation, directly by mass spectrometry although isobaric structures remain unresolved, unless diagnostic fragment ions can be produced by tandem MS. While the chromatographic methods are sensitive and provide relative quantification of glycans via uniform labeling,10 they are more time-consuming, expensive, and in general more prone to error due to additional sample preparation steps. More importantly, current methods only provide relative but no absolute quantification of individual glycans, e.g., for diagnostic applications or quantification of immunogenic glycan levels. While the relative quantification of glycans is thought to be sufficient to track changes in glycosylation between samples in many biopharmaceutical applications, a clinical use of glycans as disease markers that goes beyond glycan ratios would require methods that measure absolute concentrations of individual glycans.

A new Absolute Quantification method

Isotopic dilution mass spectrometry has been the golden standard for absolute metabolite quantification in newborn screening, quantification of immunosuppressor levels, in screening for illicit drugs, and in various approaches for quantitative proteomics. An application of isotopic dilution to glycan analysis, however, has been hampered largely by a lack of heavy isotope labeled glycan standards.

Monoclonal Antibody N-glycan Characterization

Human Serum IgG High-Throughput N-glycan Absolute Quantification

Glycobiology

Several applications in the field of glycobiology research and proteomics:

  • Rapid Absolute glycan quantification
  • Increase reproducibility in lab-to-lab method transfer (internal calibration standard)
  • De-convolute and quantify co-eluting peaks in LC-MS
  • Quantify glycan recovery after sample preparation
  • Protein characterization: Quick determination of the glycosylation profile of a expressed recombinant protein depending on the heterologous host. Correlation of the differences in glycosylation and protein function

References

[1] R. Saldova, et al., Levels of specific serum N-glycans identify breast cancer patients with higher circulating tumor cell counts, Ann. Oncol. 22 (2011) 1113–1119.

[2] U.M. Abd Hamid, et al., A strategy to reveal potential glycan markers from serum glycoproteins associated with breast cancer progression, Glycobiology 18 (2008) 1105

[3] Z. Kyselova, et al., Breast cancer diagnosis and prognosis through quantitative measurements of serum glycan profiles, Clin. Chem. 54 (2008) 1166–1175.

[4] A. Pierce, et al., Levels of specific glycans significantly distinguish lymph node

[5] de Leoz, M. L., et al., (2011) High-mannose glycans are elevated during breast cancer progression. Mol. Cell. Proteomics 10, M110.00271

[6] Alley, W. R., Jr., et al., (2010) Chip-based reversed-phase liquid chromatography-mass spectrometry of permethylated N-linked glycans: a potential methodology for cancerbiomarker discoveryAnal. Chem. 82, 5095–5106

[7] J. Bones, et al., Ultra performance liquid chromatographic profiling of serum N-glycans for fast and efficient identification of cancer associated alterations in glycosylation, Anal. Chem. 82 (2010) 10208–10215.

[8] J. Bones, et al., Glycomic and glycoproteomic analysis of serum from patients with stomach cancer reveals potential markers arising from host defence response mechanisms, J. Proteome Res. 10 (2011) 1246–1265.

[9] Goldman, R., et al., (2009) Detection of hepatocellular carcinoma using glycomic analysisClin. Cancer Res. 15, 1808–1813

[10] Liu, X. E., et al., (2007) N-glycomic changes in hepatocellular carcinoma patients with liver cirrhosis induced by hepatitis B virusHepatology 46, 1426–1435

[11] K. Noda, et al, Gene expressionof α1-6 fucosyltransferase in human hepatoma tissues: a possible implicationfor increased fucosylation of α-fetoprotein, Hepatology 28 (1998), 944–952.

[12] Y. Sato, et al.,Early recognition of hepatocellular carcinoma based on altered profiles of alphafetoprotein,N. Engl. J. Med. 328 (1993) 1802–1806.

[13] J.N. Arnold, R. Saldova, M.C. Galligan, T.B. Murphy, Y. Mimura-Kimura, J.E. Telford, A.K. Godwin, P.M. Rudd, Novel glycan biomarkers for the detection of lung cancer, J. Proteome Res. 10 (2011) 1755–1764.

[14] Kim, Y. G., et al., (2009) Rapid and high-throughput analysis of N-glycans from ovarian cancer serum using a 96-well plate platformAnal. Biochem. 391, 151–153.

[15]  R. Saldova, et al., Ovarian cancer is associated with changes in glycosylation in both acute-phase proteins and IgG, Glycobiology 17 (2007) 1344.

[16] Alley, W. R., Jr., et al., (2012) N-linked glycan structures and their expressions change in the blood sera of ovarian cancer patientsJ. Proteome Res. 11, 2282–2300

[17] Kronewitter, S. R., et al., (2012) The glycolyzer: automated glycan annotation software for high performance mass spectrometry and its application to ovarian cancer glycan biomarker discoveryProteomics 12, 2523–2538

[18] Storr SJ, et al., The O-linked glycosylation of secretory/shed MUC1 from an advanced breast cancer patient’s serum. Glycobiology 2008, 18(6):456-462.

[19] R. Saldova, et al., Core fucosylation and alpha2-3 sialylation in serum N-glycome is significantly increased in prostate cancer comparing to benign prostate hyperplasia, Glycobiology 21 (2011) 195–205.

[20] A. Sarrats, et al., Glycan characterization of PSA 2-DE subforms from serum and seminal plasma, OMICS: A J. of Integr. Biol. 14 (2010) 465–474.

[21] A. Sarrats, et al., Differential percentage of serum prostate-specific antigen subforms suggests a new way to improve prostate cancer diagnosis, Prostate 70 (2010) 1–9.

[22] Hua, S., et al., (2011) Comprehensive native glycan profiling with isomer separation and quantitation for the discovery of cancer biomarkersAnalyst 136, 3663–3671.

[23] N. Okuyama, et al., Fucosylated haptoglobin is a novel marker for pancreatic cancer: a detailed analysis of the oligosaccharide structure and a possible mechanism for fucosylation, Int. J. Cancer 118 (2006) 2803–2808.

[24] E. Miyoshi, M. Nakano, Fucosylated haptoglobin is a novel marker for pancreatic cancer: detailed analyses of oligosaccharide structures, Proteomics 8 (2008) 3257–3262.

[25] Nakano M, et al., Site specific analysis of N-glycans on haptoglobin in sera of patients with pancreatic cancer: a novel approach for the development of tumor markers. Int J Cancer 2008;122: 2301–9.

[26] Kukowska-Latallo JF, et al., A cloned human cDNA determines expression of a mouse stagespecific embryonic antigen and the Lewis blood group a(1,3/1,4)fucosyltransferase. Genes Dev 1990;4:1288–303.

[27] Hanski C, et al.,  Fucosyltransferase III and sialyl-Le(x) expression correlate in cultured colon carcinoma cells but not in colon carcinoma tissue. Glycoconj J 1996;13:727–33.

[28] Majuri ML, et al., Expression and function of a2,3-sialyl- and a,3/l,4- fucosyltransferases in colon adenocarcinoma cell lines: role in synthesis of E-selectin counter-receptors. Int J Cancer 1995;63:551–9.

[29] Ercan et al. Hypogalactosylation of serum N-glycans fails to predict clinical response to methotrexate and TNF inhibition in rheumatoid arthritis.Arthritis Research & Therapy 2012, 14:R43

[30] James N. Arnold et al., Mannan binding lectin and its interaction with immunoglobulins inhealth and in disease, Immunology Letters 106 (2006) 103–110

[31] Pauline M. Rudd et al. Glycosylation and the Immune System. Science 291, 2370 (2001)

[32] Arnold, J. N:, et al., The impact of glycosylation on the biological function and structure of human immunoglobulins. Annu. Rev. Immunol. 25, 21-50 (2007)

[33] Gaya Thanabalasingham, G. Lauc, et al., “Mutations in HNF1A Result in Marked Alterations of Plasma Glycan Profile“, Diabetes 2013, 62, 1329.

[34] Zihao Wang, et al., “Site-Specific GlcNAcylation of Human Erythrocyte Proteins“, Diabetes 2009, 59, 309 .

[35] Krištić J., et al “Glycans are a novel biomarker of chronological and biological ages.”J Gerontol A Biol Sci Med Sci. 2014

[36] Wahl et al. “IgG glycosylation and DNA methylation are interconnected with smoking“. Biochim Biophys Acta. 2017

[37] Kizuka Y. “An Alkynyl-Fucose Halts Hepatoma Cell Migration and Invasion by Inhibiting GDP-Fucose-Synthesizing Enzyme FX, TSTA”. Cell Chem Biol. 2017

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