ATP concentration as possible marker of liver damage at leukaemia treatment: confocal microscopy-based experimental study and numerical simulations

V. Malashchenko; A. Zyubin; S. Babak; A. Lavrova

doi:10.1117/12.2267951

14 April 2017 ATP concentration as possible marker of liver damage at leukaemia treatment: confocal microscopy-based experimental study and numerical simulations

V. Malashchenko, A. Zyubin, S. Babak, A. Lavrova

Author Affiliations +

Proceedings Volume 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III; 103371B (2017) https://doi.org/10.1117/12.2267951
Event: Saratov Fall Meeting 2016: Fourth International Symposium on Optics and Biophotonics, 2016, Saratov, Russian Federation

Abstract

We consider the method of confocal microscopy as a convenient instrument for determination of chemical compounds in biological tissues and cells. In particular, we study the dynamics of adenosine triphosphate (ATP) concentration that could be used as a bio-marker of energy metabolism pathologies at the treatment of acute lymphoblastic leukaemia (ALL). On the basis of data obtained by the confocal microscopy, the values of ATP concentration have been calculated for each case. Possible correlations with other characteristics of pathology processes obtained from plasma of leukemia patients show that ATP value could be a prognostic factor of the treatment success. The role of ATP in the drug metabolism switching is also discussed within the context of kinetic modelling of metabolism processes leading to the production of 6-Thioguanosine monophosphate, which is a principal acting agent in chemotherapy.

Citation Download Citation

V. Malashchenko, A. Zyubin, S. Babak, and A. Lavrova "ATP concentration as possible marker of liver damage at leukaemia treatment: confocal microscopy-based experimental study and numerical simulations", Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 103371B (14 April 2017); https://doi.org/10.1117/12.2267951

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