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Quantifying assays: Inhibition of signalling pathways of cancer.

Roumen AnguelovG ManjunathAvulundiah E PhiriTrevor T NyakudyaPriyesh BipathJune C SeremYvette N Hlophe
Published in: Mathematical medicine and biology : a journal of the IMA (2023)
Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell's viability, cell division, and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) Deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) Estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. IC50 can be computed for any time point.
Keyphrases
  • high throughput
  • electronic health record
  • big data
  • squamous cell carcinoma
  • single cell
  • signaling pathway
  • cell therapy
  • high resolution
  • artificial intelligence
  • mass spectrometry