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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.

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.

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