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Boolean dynamic modeling of TNFR1 signaling predicts a nested feedback loop regulating the apoptotic response at single-cell level

Cell-to-cell variability during Tumor Necrosis Factor Receptor 1 (TNFR1) signaling triggered by the pleiotropic cytokine TNFα can lead to pro-survival and apoptotic phenotypic responses at single-cell level. Harnessing the ability to modulate the signal flow responsible for the balance between these two phenotypes and make cells favour apoptosis have been considered in cancer therapies. We show that a 6-node nested feedback loop facilitates the crucial crosstalk regulation modulating the signal flow between these two responses. We identify this by systematically analysing the partial state transition graph (pSTG) underlying a Boolean dynamic model of the TNFR1 signaling network that accounts for signal flow path variability. We demonstrate a novel approach “Boolean Modeling based Prediction of Steady-state probability of Phenotype Reachability (BM-ProSPR)” that enables constructing a reliable pSTG in a computationally efficient manner and predicting accurately the network’s ability to settle into different phenotypes. We deduce that knocking-off Comp1 – IKK* complex tweaks the signal flow paths leading to a 62% increase in the steady state probability of TNFR1 signaling culminating in apoptosis and thereby favours phenotype switching from pro-survival to apoptosis. Priming cancerous cells with inhibitors targeting the interaction involving Comp1 and IKK* prior to TNFα exposure could be a potential therapeutic strategy.