Capillary Electrophoresis-Based N-Glycosylation Analysis in the Biomedical and Biopharmaceutical Fields.

Glycomics has a growing interest in the biopharmaceutical industry and biomedical research requiring new high-performance and high-sensitivity bioanalytical tools. Analysis of N-glycosylation is very important during the development of protein therapeutics and it also plays a key role in biomarker discovery. The most frequently used glycoanalytical methods are capillary electrophoresis, liquid chromatography, and mass spectrometry. In this chapter, the capillary electrophoresis-based N-linked carbohydrate analysis methods are conferred with emphasis on its use in the biopharmaceutical and biomedical fields.

Machine Learning Based Analysis of Human Serum N-glycome Alterations to Follow up Lung Tumor Surgery.

The human serum N-glycome is a valuable source of biomarkers for malignant diseases, already utilized in multiple studies. In this paper, the N-glycosylation changes in human serum proteins were analyzed after surgical lung tumor resection. Seventeen lung cancer patients were involved in this study and the N-glycosylation pattern of their serum samples was analyzed before and after the surgery using capillary electrophoresis separation with laser-induced fluorescent detection. The relative peak areas of 21 N-glycans were evaluated from the acquired electropherograms using machine learning-based data analysis. Individual glycans as well as their subclasses were taken into account during the course of evaluation. For the data analysis, both discrete (e.g., smoker or not) and continuous (e.g., age of the patient) clinical parameters were compared against the alterations in these 21 N-linked carbohydrate structures. The classification tree analysis resulted in a panel of N-glycans, which could be used to follow up on the effects of lung tumor surgical resection.

[The potential role of proteomic and glycomic biomarkers in chronic obstructive pulmonary disease diagnostics]. / Protein és glikán biomarkerek szerepe a krónikus obstruktív tüdobetegség diagnosztikájában.

Chronic obstructive pulmonary disease (COPD) is worldwide a significant representative of morbidity and mortality statistics. COPD is a preventable and treatable disease and smoking is the main risk factor of disease development. Prevention is crucial, but it has its limitations, so risk estimation and early non-invasive diagnostics are essential to decrease COPD mortality. Although diagnostic techniques are evolving, the perfect screening tool is lacking. Discovery of properly sensitive and specific biomarkers is important. They could be effective diagnostic, differential diagnostic, phenotyping and prognostic tools to clinicians. The manuscript is focusing on recently discovered potential protein and glycan biomarkers for COPD. Orv Hetil. 2020; 161(4): 123-128.

Proteomic and Glycomic Markers to Differentiate Lung Adenocarcinoma from COPD.

Lung adenocarcinoma is one of the leading causes of mortality among cancer patients worldwide and Chronic Obstructive Pulmonary Disease (COPD) is also high in death statistics. In addition, patients with Chronic Obstructive Pulmonary Disease (COPD) have a high risk of developing primary lung cancer. Prevention, risk estimation and a non-invasive diagnostics are essential to decrease COPD and lung cancer mortality. Therefore, better and more accurate molecular diagnostic markers (biomarkers) are needed for the early differential diagnosis of these lung diseases to help clinicians make better therapeutic decisions. This review focuses on recently discovered adenocarcinoma and COPD biomarkers at the proteome and glycome level. In the first part, the protein markers are summarized, while the second part is focused on glycan markers. Their use to differentiate between chronic inflammation (COPD) and malignant (adenocarcinoma) diseases is discussed in detail.

Comparative analysis of the human serum N-glycome in lung cancer, COPD and their comorbidity using capillary electrophoresis.

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) are prevalent ailments with a great challenge to distinguish them based on symptoms only. Since they require different treatments, it is important to find non-invasive methods capable to readily diagnose them. Moreover, COPD increases the risk of lung cancer development, leading to their comorbidity. In this pilot study the N-glycosylation profile of pooled human serum samples (90 patients each) from lung cancer, COPD and comorbidity (LC with COPD) patients were investigated in comparison to healthy individuals (control) by capillary gel electrophoresis with high sensitivity laser-induced fluorescence detection. Sample preparation was optimized for human serum samples introducing a new temperature adjusted denaturation protocol to prevent precipitation and increased endoglycosidase digestion time to assure complete removal of the N-linked carbohydrates. The reproducibility of the optimized method was <3.5%. Sixty-one N-glycan structures were identified in the pooled control human serum sample and the profile was compared to pooled lung cancer, COPD and comorbidity of COPD with lung cancer patient samples. One important finding was that no other sugar structures were detected in any of the patient groups, only quantitative differences were observed. Based on this comparative exercise, a panel of 13 N-glycan structures were identified as potential glycobiomarkers to reveal significant changes (>33% in relative peak areas) between the pathological and control samples. In addition to N-glycan profile changes, alterations in the individual N-glycan subclasses, such as total fucosylation, degree of sialylation and branching may also hold important glycobiomarker values.