(A-38) Investigating the Impact of Intrinsic and Extrinsic Cell Properties on Apoptotic Signaling in Tumor Cells Using an ODE model

Introduction:: Apoptosis, or programmed cell death, is a critical innate biological process that helps keep the balance between cell growth and cell death in our bodies. The absence of proper cell death programming strongly contributes to tumor growth. Promoting apoptosis helps to prevent uncontrolled proliferation that occurs during tumor growth. Therefore, a quantitative understanding of the signaling leading to apoptosis can be exploited to regulate malignant tumor growth. Extracellular death ligands, such as CD95L, promote intracellular signaling leading to apoptosis. This signaling is affected by both cell intrinsic and extrinsic properties. We aim to investigate how these properties influence apoptosis signaling.


Materials and Methods:: We used a published ODE model (Eissing, 2004) of the apoptotic cell signaling pathway that represents how caspases intrinsically release proteins to help a cell finally decide to initiate apoptosis. When activated, caspases, a common family of proteins present along the death-inducing signaling complex, cause the apoptotic process of programmed cell death. In particular, the model predicts the level of activated caspase 3 (C3a), which can be used to characterize whether the cell will undergo apoptosis. Importantly, we expanded the model to incorporate extrinsic features such as ligand-receptor binding and complex internalization, along with receptor production and degradation. This expanded in -silico model now predicts the cell fate decision of tumor cells to commence apoptosis or proliferation in response to ligand activation. Then, we varied ligand, receptor, and intracellular protein concentrations to quantitatively elucidate the effect of these properties on the capacity for a cell to initiate apoptosis. Computational modeling offers a useful and feasible foundation for predicting the effects of crosstalk between signaling pathways while incorporating quantitative data that inform the probability that a specific decision will ensue.

Results, Conclusions, and Discussions:: We applied the expanded model to predict the number of apoptotic cells in a heterogeneous

population as a function of time. The model predicts that given heterogeneity in the receptor expression and intracellular signaling species’ concentrations, the cell population exhibits a wide range of dynamics for C3a. By setting a threshold that C3a must reach to initiate apoptosis, we find that even after several hours of ligand stimulation, many cells do not become apoptotic due to low levels of C3a. As Figure 1 shows, the time required to reach the C3a threshold for apoptosis also varied widely across the population. Higher non-zero initial protein concentrations showed faster and definitive activation of apoptosis, while lower concentrations quickly plateaued.

The level of activated caspases is very sensitive to the initial concentrations of intracellular

anti-apoptotic proteins, ligands, and receptors. This modeling framework can be used to predict the behavior of different types of tumor cells with varying sensitivity to caspase activation and investigate strategies to promote greater apoptosis.




Acknowledgements (Optional): : I would like to thank members of the Finley lab for their helpful insights.

References (Optional): : Eissing T, Conzelmann H, Gilles ED, Allgöwer F, Bullinger E, Scheurich P. Bistability analyses of a caspase activation model for receptor-induced apoptosis. J Biol Chem. 2004 Aug 27;279(35):36892-7. doi: 10.1074/jbc.M404893200. Epub 2004 Jun 18. PMID: 15208304.