Fast and facile analysis of glycosylation and phosphorylation of fibrinogen from human plasma-correlation with liver cancer and liver cirrhosis.

Hepatocellular carcinoma (HCC) is one of the deadliest cancers due to its late diagnosis with the main risk factor being liver cirrhosis (LC). Glycan structures from glycoproteins are usually altered in cancer. Blood plasma from 111 healthy and sick donors was analyzed to determine the post-translational modifications (PTM) of intact Aα-, Bβ-, and γ-subunits of fibrinogen, a glycoprotein predominantly produced in liver cells.

Simultaneous characterization of sequence polymorphisms, glycosylation and phosphorylation of fibrinogen in a direct analysis by LC-MS.

Fibrinogen is an abundant plasma glycoprotein involved in pathologically important processes like blood clotting, hemostasis and angiogenesis. Sequence polymorphisms and posttranslational modification (PTM) status of fibrinogen are important factors of cardiovascular disease. We aim for the simultaneous analysis of fibrinogen subunits for sequence polymorphisms (SNPs), phosphorylation and glycosylation by top-down mass spectrometry.

Glycan analysis: scope and limitations of different techniques--a case for integrated use of LC-MS(/MS) and NMR techniques.

The structure of glycans from glycoproteins is highly relevant for their function. We tightly integrate liquid chromatography-mass spectrometry (LC-MS), MS/MS, and nuclear magnetic resonance (NMR) data to achieve a complete characterization of even isobaric glycans differing in only one linkage position or in the substitution in one branch. As example, we analyzed ten desialylated underivatized glycans from bovine fibrinogen.

Resolving the problem of chromatographic overlap by 3D cross correlation (3DCC) processing of LC, MS and NMR data for characterization of complex glycan mixtures.

Chromatographic overlap is a common problem in the analysis of complex mixtures. As a result, it is not possible to identify the components because each resulting NMR or MS spectrum contains multiple components. We introduce three-dimensional cross correlation (3DCC) that dissects NMR spectra of a mixture into spectra of the individual components without actually separating them.