Clinical glycomics comprises a spectrum of different analytical methodologies to analyze glycan structures, which provides insights into the mechanisms of glycosylation. Within clinical diagnostics, glycomics serves as a functional readout of genetic variants, and can form a basis for therapy development, as was described for PGM1-CDG. Integration of glycomics with genomics has resulted in the elucidation of previously unknown disorders of glycosylation, namely CCDC115-CDG, TMEM199-CDG, ATP6AP1-CDG, MAN1B1-CDG, and PGM1-CDG. This review provides an introduction into protein glycosylation and presents the different glycomics methodologies ranging from gel electrophoresis to mass spectrometry (MS) and from free glycans to intact glycoproteins. The role of glycomics in the diagnosis of congenital disorders of glycosylation (CDG) is presented, including a diagnostic flow chart and an overview of glycomics data of known CDG subtypes. The review ends with some future perspectives, showing upcoming technologies as system wide mapping of the N- and O-glycoproteome, intact glycoprotein profiling and analysis of sugar metabolism. These new advances will provide additional insights and opportunities to develop personalized therapy. This is especially true for inborn errors of metabolism, which are amenable to causal therapy, because interventions through supplementation therapy can directly target the pathogenesis at the molecular level.
Here a mass spectrometry-based platform for the analysis of glycoproteins is presented. Glycopeptides and released glycans are analyzed, the former by quadrupole orthogonal time-of-flight liquid chromatography/mass spectrometry (QoTOF LC/MS) and the latter by permethylation analysis using matrix-assisted laser desorption/ionization (MALDI)-TOF MS. QoTOF LC/MS analysis reveals the stochastic distribution of glycoforms at occupied sequons, and the latter provides a semiquantitative assessment of overall protein glycosylation. Hydrophilic interaction chromatography (HILIC) was used for unbiased enrichment of glycopeptides and was validated using five model N-glycoproteins bearing a wide array of glycans, including high-mannose, complex, and hybrid subtypes such as sulfo and sialyl forms. Sialyl and especially sulfated glycans are difficult to analyze because these substitutions are labile. The conditions used here allow detection of these compounds quantitatively, intact, and in the context of overall glycosylation. As a test case, we analyzed influenza B/Malaysia/2506/2004 hemagglutinin, a component of the 2006-2007 influenza vaccine. It bears 11 glycosylation sites. Approximately 90% of its glycans are high mannose, and 10% are present as complex and hybrid types, including those with sulfate. The stochastic distribution of glycoforms at glycosylation sites is revealed. This platform should have wide applications to glycoproteins in basic sciences and industry because no apparent bias for any glycoforms is observed.
Ovarian cancer is a fatal gynaecological malignancy in adult women with a five-year overall survival rate of only 30%. Glycomic and glycoproteomic profiling studies have reported extensive protein glycosylation pattern alterations in ovarian cancer. Therefore, spatio-temporal investigation of these glycosylation changes may unearth tissue-specific changes that occur in the development and progression of ovarian cancer. A novel method for investigating tissue-specific N-linked glycans is using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) on formalin-fixed paraffin-embedded (FFPE) tissue sections that can spatially profile N-glycan compositions released from proteins in tissue-specific regions. In this study, tissue regions of interest (e.g. tumor, stroma, adipose tissue and necrotic areas) were isolated from FFPE tissue sections of advanced serous ovarian cancers (n = 3). PGC-LC-ESI-MS/MS and MALDI-MSI were used as complementary techniques to firstly generate structural information on the tissue-specific glycans in order to then obtain high resolution images of the glycan structure distribution in ovarian cancer tissue. The N-linked glycan repertoires carried by the proteins in these tissue regions were structurally characterized for the first time in FFPE ovarian cancer tissue regions, using enzymatic peptide-N-glycosidase F (PNGase F) release of N-glycans. The released glycans were analyzed by porous graphitized carbon liquid chromatography (PGC-LC) and collision induced electrospray negative mode MS fragmentation analysis. The N-glycan profiles identified by this analysis were then used to determine the location and distribution of each N-glycan on FFPE ovarian cancer sections that were treated with PNGase F using high resolution MALDI-MSI. A tissue-specific distribution of N-glycan structures identified particular regions of the ovarian cancer sections. For example, high mannose glycans were predominantly expressed in the tumor tissue region whereas complex/hybrid N-glycans were significantly abundant in the intervening stroma. Therefore, tumor and non-tumor tissue regions were clearly demarcated solely on their N-glycan structure distributions.
In recent years, the use of lectins for screening of potential biomarkers has gained increased importance in cancer research, given the development in glycobiology that highlights altered structural changes of glycans in cancer associated processes. Lectins, having the properties of recognizing specific carbohydrate moieties of glycoconjugates, have become an effective tool for detection of new cancer biomarkers in complex bodily fluids and tissues. The specificity of lectins provides an added advantage of selecting peptides that are differently glycosylated and aberrantly expressed in cancer patients, many of which are not possibly detected using conventional methods because of their low abundance in bodily fluids. When coupled with mass spectrometry, research utilizing lectins, which are mainly from plants and fungi, has led to identification of numerous potential cancer biomarkers that may be used in the future. This article reviews lectin-based methods that are commonly adopted in cancer biomarker discovery research.