Abstract
Simple SummaryGlobally, there were around 2.1 million lung cancer cases and 1.8 million deaths in 2018. Hungary—where this study was carried out—had the highest rate of lung cancer in the same year. We developed a new analytical method which can be readily used to follow up the tumor surgery by investigating the glycan (sugar) structures of proteins. As the results of such investigations are very complex, computer-assisted machine learning methods were utilized for data interpretation.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.
Highlights
Lung cancer is the leading cause of cancer mortality in men and the second in women worldwide, with around a 19% five-year survival rate [1,2]
Based on the machine learning analysis described in this paper, novel information was gained regarding the relationship between certain clinical variables and the change in the relative peak areas of serum N-glycan structures
Positive outcome of the surgery showed a significant correlation with N-glycan change for even smoker or non-smoker patients and either atherosclerosis or without atherosclerosis
Summary
Lung cancer is the leading cause of cancer mortality in men and the second in women worldwide, with around a 19% five-year survival rate [1,2]. We suggested a panel of asparagine-linked carbohydrates for lung cancer diagnosis even at early stages by identifying slight changes in the human serum N-glycan profile [9]. Investigated the N-glycome profiles of tissue samples from patients with lung cancer Their results revealed substantial differences in N-glycan distribution associated with the disease compared between cancerous and healthy samples [21]. Serum samples can be analyzed to explore any possible changes in the N-glycan profile Such sample analysis is dubbed liquid biopsy and considered to be a non-invasive method. Based on the evaluation of the acquired electropherograms, relative peak areas of 21 N-glycans were compared before and after tumor removal and machine learning-based data analysis was performed to explore any possible relationship between clinical parameters and the change in the abundance of certain asparagine-linked carbohydrates
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