Model-based identification of the crosstalks and feedbacks that determine the doxorubicin response dynamics of the JNK-p38-p53 network

Abstract

AbstractCellular responses to perturbations and drugs are determined by interconnected networks, rather than linear pathways. Individually, the JNK, p38 and p53 stress and DNA-damage response networks are well understood and regulate critical cell-fate decisions, such as apoptosis, in response to many chemotherapeutical agents, such as doxorubicin. To better understand how interactions between these pathways determine the dynamic behaviour of the entire network, we constructed a data-driven mathematical model. This model contains mechanistic details about the kinase cascades that activate JNK, p38, AKT and p53, and free parameters that describe possible interactions between these pathways. Fitting this model to experimental time-course perturbation data (five time-courses with six time-points under five different conditions), identified specific network interactions that can explain the observed network responses. JNK emerged as an important control node. JNK exhibited a positive feedback loop, was tightly controlled by negative feedback and crosstalk from p38 and AKT, respectively, and was the strongest activator of p53. Compared to static network reconstruction methods, such as modular response analysis, the model-based approach identifies biochemical mechanisms and explains the dynamic control of cell signalling.