Now showing 1 - 4 of 4
  • Publication
    Signaling pathway models as biomarkers: Patient-specific simulations of JNK activity predict the survival of neuroblastoma patients
    Signaling pathways control cell fate decisions that ultimately determine the behavior of cancer cells. Therefore, the dynamics of pathway activity may contain prognostically relevant information different from that contained in the static nature of other types of biomarkers. To investigate this hypothesis, we characterized the network that regulated stress signaling by the c-Jun N-terminal kinase (JNK) pathway in neuroblastoma cells. We generated an experimentally calibrated and validated computational model of this network and used the model to extract prognostic information from neuroblastoma patient–specific simulations of JNK activation. Switch-like JNK activation mediates cell death by apoptosis. An inability to initiate switch-like JNK activation in the simulations was significantly associated with poor overall survival for patients with neuroblastoma with or without MYCN amplification, indicating that patient-specific simulations of JNK activation could stratify patients. Furthermore, our analysis demonstrated that extracting information about a signaling pathway to develop a prognostically useful model requires understanding of not only components and disease-associated changes in the abundance or activity of the components but also how those changes affect pathway dynamics.
      1349Scopus© Citations 109
  • Publication
    Endocytosis and signalling: A meeting with mathematics
    Although endocytosis has traditionally been understood as a signal attenuation mechanism, an emerging view considers endocytosis as an integral part of signal propagation and processing. On the short time scale, trafficking of endocytic vesicles contributes to signal propagation from the surface to distant targets, with bi-directional communication between signalling and trafficking. Mathematical modelling helps combine the mechanistic, molecular knowledge with rigorous analysis of the complex output dynamics of endocytosis in time and space. Simulations reveal novel roles for endocytosis, including the control of cell polarity, enhancing the spatial signal propagation, and controlling the signal magnitudes, kinetics, and synchronization with stimulus dynamics.
    Scopus© Citations 29  374
  • Publication
    Feedback regulation in cell signalling: Lessons for cancer therapeutics
    The notion of feedback is fundamental for understanding signal transduction networks. Feedback loops attenuate or amplify signals, change the network dynamics and modify the input-output relationships between the signal and the target. Negative feedback provides robustness to noise and adaptation to perturbations, but as a double-edged sword can prevent effective pathway inhibition by a drug. Positive feedback brings about switch-like network responses and can convert analog input signals into digital outputs, triggering cell fate decisions and phenotypic changes. We show how a multitude of protein-protein interactions creates hidden feedback loops in signal transduction cascades. Drug treatments that interfere with feedback regulation can cause unexpected adverse effects. Combinatorial molecular interactions generated by pathway crosstalk and feedback loops often bypass the block caused by targeted therapies against oncogenic mutated kinases. We discuss mechanisms of drug resistance caused by network adaptations and suggest that development of effective drug combinations requires understanding of how feedback loops modulate drug responses.
    Scopus© Citations 45  966
  • Publication
    Competing to coordinate cell fate decisions: the MST2-Raf-1 signaling device
    How do biochemical signaling pathways generate biological specificity? This question is fundamental to modern biology, and its enigma has been accentuated by the discovery that most proteins in signaling networks serve multifunctional roles. An answer to this question may lie in analyzing network properties rather than individual traits of proteins in order to elucidate design principles of biochemical networks that enable biological decision-making. We discuss how this is achieved in the MST2/Hippo-Raf-1 signaling network with the help of mathematical modeling and model-based analysis, which showed that competing protein interactions with affinities controlled by dynamic protein modifications can function as Boolean computing devices that determine cell fate decisions. In addition, we discuss areas of interest for future research and highlight how systems approaches would be of benefit
    Scopus© Citations 23  311