Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery
The human serum <i>N-</i>glycome is a valuable source of biomarkers for malignant diseases, already utilized in multiple studies. In this paper, the <i>N-</i>glycosylation changes in human serum proteins were analyzed after surgical lung tumor resection. Seventeen lung cancer...
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| Format: | Article |
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MDPI AG
2020-12-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/12/12/3700 |
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| author | Brigitta Mészáros Gábor Járvás Renáta Kun Miklós Szabó Eszter Csánky János Abonyi András Guttman |
| author_facet | Brigitta Mészáros Gábor Járvás Renáta Kun Miklós Szabó Eszter Csánky János Abonyi András Guttman |
| author_sort | Brigitta Mészáros |
| collection | DOAJ |
| description | The human serum <i>N-</i>glycome is a valuable source of biomarkers for malignant diseases, already utilized in multiple studies. In this paper, the <i>N-</i>glycosylation changes in human serum proteins were analyzed after surgical lung tumor resection. Seventeen lung cancer patients were involved in this study and the <i>N-</i>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 <i>N-</i>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 <i>N</i>-linked carbohydrate structures. The classification tree analysis resulted in a panel of <i>N-</i>glycans, which could be used to follow up on the effects of lung tumor surgical resection. |
| first_indexed | 2024-03-10T14:12:48Z |
| format | Article |
| id | doaj.art-84b09572fb034f4ba0cf9a6fd39c0881 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T14:12:48Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-84b09572fb034f4ba0cf9a6fd39c08812023-11-21T00:04:05ZengMDPI AGCancers2072-66942020-12-011212370010.3390/cancers12123700Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor SurgeryBrigitta Mészáros0Gábor Járvás1Renáta Kun2Miklós Szabó3Eszter Csánky4János Abonyi5András Guttman6Horváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, HungaryHorváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, HungaryHorváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, HungaryDepartment of Pulmonology, Semmelweis Hospital, 3526 Miskolc, HungaryDepartment of Pulmonology, Semmelweis Hospital, 3526 Miskolc, HungaryComplex Systems Monitoring Research Group, University of Pannonia, 8200 Veszprem, HungaryHorváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, 4032 Debrecen, HungaryThe human serum <i>N-</i>glycome is a valuable source of biomarkers for malignant diseases, already utilized in multiple studies. In this paper, the <i>N-</i>glycosylation changes in human serum proteins were analyzed after surgical lung tumor resection. Seventeen lung cancer patients were involved in this study and the <i>N-</i>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 <i>N-</i>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 <i>N</i>-linked carbohydrate structures. The classification tree analysis resulted in a panel of <i>N-</i>glycans, which could be used to follow up on the effects of lung tumor surgical resection.https://www.mdpi.com/2072-6694/12/12/3700lung cancer<i>N-</i>glycansmachine learningcapillary electrophoresissurgery |
| spellingShingle | Brigitta Mészáros Gábor Járvás Renáta Kun Miklós Szabó Eszter Csánky János Abonyi András Guttman Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery Cancers lung cancer <i>N-</i>glycans machine learning capillary electrophoresis surgery |
| title | Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery |
| title_full | Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery |
| title_fullStr | Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery |
| title_full_unstemmed | Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery |
| title_short | Machine Learning Based Analysis of Human Serum <i>N-</i>glycome Alterations to Follow up Lung Tumor Surgery |
| title_sort | machine learning based analysis of human serum i n i glycome alterations to follow up lung tumor surgery |
| topic | lung cancer <i>N-</i>glycans machine learning capillary electrophoresis surgery |
| url | https://www.mdpi.com/2072-6694/12/12/3700 |
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