Robustness of G1/S checkpoint pathways in cell cycle regulation based on probability of DNA-damaged cells passing as healthy cells.
We investigate the robustness and the behaviours of the critical proteins under parameter perturbations of G1/S checkpoint pathways with different levels of DNA-damage, based on a mathematical model of the pathways. We identify the peak times (PTs) of two key proteins as the in silico biomarkers based on the currently established biology, and the results from the local and global sensitivity analyses show the significant kinetic parameters that are associated with the key proteins. The robustness of the G1/S checkpoint pathways with or without DNA-damage is defined based on the probability (beta) of DNA-damaged cells passing as healthy cells under the given perturbation regimes. The results from the global sensitivity analyses based on four defined levels of parameter range reveal that we can accurately distinguish healthy cells from the defective cells when parameter variations are within a range of +/-10%. However, the probability of wrongly identifying damaged cells as healthy cells became very large (more than 0.43) when the level of change of parameters exceeds +/-30%. Provided that there are probably millions of cells that are oncogenically primed at any given time, these dangerous cells are disposed through apoptosis and cellular senescence. However, the very recent experimental findings state that this irreversible process happens not in the pre-tumoral stage but in the pre-malignant tissue where a non-invasive tumor is formed. This points out that a large number of damaged cells undergo proliferation without being caught at DNA-damage checkpoints. Our simulation results, in terms of percentage of damaged cells that pass G1/S checkpoint agree with this possibility.
Ling
Hong
H
Centre for Advanced Computational Solutions, Lincoln University, Christchurch, New Zealand. Hong.Ling2@lincolnuni.ac.nz
Kulasiri
Don
D
Samarasinghe
Sandhya
S
D018797:Cell Cycle Proteins / Q000502:physiology*; D002470:Cell Survival; D002471:Cell Transformation, Neoplastic; D003198:Computer Simulation; D004249:DNA Damage; D016193:G1 Phase / Q000502:physiology*; D008954:Models, Biological; D011336:Probability; D016196:S Phase / Q000502:physiology*; D012680:Sensitivity and Specificity
D018797:Cell Cycle Proteins