The serum immunoglobulin G glycosylation signature of gastric cancer

Ruhaak, L. Renee; Barkauskas, Donald A.; Torres, Javier; Cooke, Cara L.; Wu, Lauren; Stroble, Carol; Özcan, Süreyya; Williams, Cynthia; Camorlinga, Margarita; Rocke, David M.; Lebrilla, Carlito B.; Solnick, Jay V.

doi:10.1016/j.euprot.2014.11.002

Cited by 46 publications

(45 citation statements)

References 51 publications

(57 reference statements)

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“…S3a). These glycoforms are also found on IgG in serum but in very low amounts (1–2.5%)4041, as well as in IgG resulting from monoclonal antibody production. Even at concentrations above the optimum of 0.15 mM (Fig.…”

Section: Resultsmentioning

confidence: 95%

Multi-level glyco-engineering techniques to generate IgG with defined Fc-glycans

Dekkers

Plomp

Koeleman

et al. 2016

Sci Rep

100

113

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Immunoglobulin G (IgG) mediates its immune functions through complement and cellular IgG-Fc receptors (FcγR). IgG contains an evolutionary conserved N-linked glycan at position Asn297 in the Fc-domain. This glycan consists of variable levels of fucose, galactose, sialic acid, and bisecting N-acetylglucosamine (bisection). Of these variations, the lack of fucose strongly enhances binding to the human FcγRIII, a finding which is currently used to improve the efficacy of therapeutic monoclonal antibodies. The influence of the other glycan traits is largely unknown, mostly due to lack of glyco-engineering tools. We describe general methods to produce recombinant proteins of any desired glycoform in eukaryotic cells. Decoy substrates were used to decrease the level of fucosylation or galactosylation, glycosyltransferases were transiently overexpressed to enhance bisection, galactosylation and sialylation and in vitro sialylation was applied for enhanced sialylation. Combination of these techniques enable to systematically explore the biological effect of these glycosylation traits for IgG and other glycoproteins.

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Section: Resultsmentioning

confidence: 95%

Multi-level glyco-engineering techniques to generate IgG with defined Fc-glycans

Dekkers

Plomp

Koeleman

et al. 2016

Sci Rep

100

113

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“…On the other hand, all five of the features addressing galactosylation and all two features addressing sialylation met the criteria for significance, indicating differential galactosylation and sialylation on serum proteins in NSCLC. Differential galactosylation on the high abundance protein IgG has previously been implicated in multiple types of cancer (20–23) and autoimmune diseases (24–26). …”

Section: Resultsmentioning

confidence: 99%

Serum Glycans as Risk Markers for Non–Small Cell Lung Cancer

Ruhaak

Stroble

Dai

et al. 2016

Cancer Prevention Research

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Previous studies have suggested occurrence of altered serum glycan profiles in patients with lung cancer. Here, we aimed to determine the predictive value of serum glycans to distinguish non-small cell lung cancer (NSCLC) cases from controls in prediagnostic samples using a previously validated predictive protein marker pro-SFTPB, as anchor. Blinded prediagnostic serum samples were obtained from the Carotene and Retinol Efficacy Trial (CARET), and included a discovery set of 100 NSCLC cases and 199 healthy controls. A second test set consisted of 108 cases and 216 controls. Cases and controls were matched for age at baseline (5-year groups), sex, smoking status (current vs. former), study enrollment cohort, and date of blood draw. Serum glycan profiles were determined by mass spectrometry. Twelve glycan variables were identified to have significant discriminatory power between cases and controls in the discovery set (AUC > 0.6). Of these, four were confirmed in the independent validation set. A combination marker yielded AUCs of 0.74 and 0.64 in the discovery and test set, respectively. Four glycan variables exhibited significant incremental value when combined with pro-SFTPB compared with pro-SFTPB alone with AUCs of 0.73, 0.72, 0.72, and 0.72 in the test set, indicating that serum glycan signatures have relevance to risk assessment for NSCLC. Cancer Prev Res; 9(4); 317-23. Ó2016 AACR.

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“…It has already been applied to rapid-throughput analysis of serum glycopeptides from several cancers. 22, 72–74 …”

Section: Sample Preparation and Methods To Partition The Glycoproteomementioning

confidence: 99%

“…The number of structures for one glycosylation site can vary by a large degree, from a handful for transferrin 21 to over 70 structures for IgG, the most abundant serum glycoprotein. 22–23 …”

Section: Introductionmentioning

confidence: 99%