Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.

Journal: Computers in biology and medicine
PMID: 39874811

Abstract

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three lung cancer patients undergoing chemotherapy treatments. Serum samples were taken before and after the treatment. The N-linked oligosaccharides were enzymatically released, fluorophore-labeled, and analyzed by capillary electrophoresis with laser-induced fluorescence detection. The resulting electropherograms were thoroughly processed and evaluated by artificial intelligence-based classifiers, i.e., utilizing a machine learning algorithm to categorize the data into two (binary) classes. The classifier analysis method revealed a strong association between the structural changes in the N-glycans and the outcomes of the chemotherapy treatments (ROC >0.9). This novel combination of bioanalytical and AI methods provided a precise and rapid tool for predicting the effectiveness of chemotherapy.

Authors

  • Rebeka Torok
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary.
  • Brigitta Meszaros
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary; Horváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
  • Veronika Gombas
    Department of Computer Science and Systems Technology, University of Pannonia, Veszprem, Hungary.
  • Agnes Vathy-Fogarassy
    Department of Computer Science and Systems Technology, University of Pannonia, Veszprem, Hungary.
  • Miklos Szabo
    Department of Pulmonology, Borsod Academic County Hospital, Miskolc, Hungary.
  • Eszter Csanky
    Department of Pulmonology, Borsod Academic County Hospital, Miskolc, Hungary.
  • Gabor Jarvas
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary.
  • Andras Guttman
    Research Institute of Biomolecular and Chemical Engineering, University of Pannonia, Veszprem, Hungary; Horváth Csaba Memorial Laboratory of Bioseparation Sciences, Research Center for Molecular Medicine, Doctoral School of Molecular Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary. Electronic address: guttmanandras@med.unideb.hu.

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