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Immunoglobulin G (IgG) is a major effector molecule of the human immune response, and aberrations in IgG glycosylation are linked to various diseases. However, the molecular mechanisms underlying protein glycosylation are still poorly understood. We present a data-driven approach to infer reactions in the IgG glycosylation pathway using large-scale mass-spectrometry measurements. Gaussian graphical models are used to construct association networks from four cohorts. We find that glycan pairs with high partial correlations represent enzymatic reactions in the known glycosylation pathway, and then predict new biochemical reactions using a rule-based approach. Validation is performed using data from a GWAS and results from three in vitro experiments. We show that one predicted reaction is enzymatically feasible and that one rejected reaction does not occur in vitro. Moreover, in contrast to previous knowledge, enzymes involved in our predictions colocalize in the Golgi of two cell lines, further confirming the in silico predictions.

Background Image-guided tumor ablation is a technique whereby needle-like applicators are placed directly into solid tumors under guidance typically with computed tomography or ultrasound. Changes in IgG and IgM antibody glycosylation were studied during ablation-induced immune response to cancer, and the use of glycosylation as a biomarker for diagnosis, prognosis and disease treatment was examined. Methods Plasma from 27 tumor patients was collected immediately before, after and for 6 months following ablation. IgG and IgM antibodies were isolated by use high-throughput chromatography, and analyzed by hydrophilic liquid chromatography. Thorough identification of glycan structures in each chromatography peak was performed by nano-liquid chromatography electrospray ionization mass spectrometry. Results Although antibody glycosylation was found to vary with cancer type, discernable patterns of change based on the successful treatment of tumors by ablation were not identified. One patient with renal clear cell carcinoma and poor disease outcome had unexpectedly high amount of oligomannose IgG glycans during the whole period of monitoring. In contrast, IgM antibodies did not follow the same pattern. Conclusions These findings suggest that glycosylation patterns are indicative of an immune system that is unable to prevent different types of cancer, rather than products of the immunostimulatory response to the ablation of tumor itself. Analyses of the outcome effect suggested that IgG glycosylation and IgM glycosylation are not associated with tumor ablation. General significance Present work opens a new way for parallel determination of glycosylation changes of both IgG and IgM antibodies by use of high-throughput methods, and their future use as biomarkers for disease diagnosis and prognosis. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc.