Now showing 1 - 10 of 21
  • Publication
    HER2-HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status
    Overexpression of HER2 is an important prognostic marker, and the only predictive biomarker of response to HER2-targeted therapies in invasive breast cancer. HER2-HER3 dimer has been shown to drive proliferation and tumor progression, and targeting of this dimer with pertuzumab alongside chemotherapy and trastuzumab, has shown significant clinical utility. The purpose of this study was to accurately quantify HER2-HER3 dimerisation in formalin fixed paraffin embedded (FFPE) breast cancer tissue as a novel prognostic biomarker. FFPE tissues were obtained from patients included in the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) study. HER2-HER3 dimerisation was quantified using an improved fluorescence lifetime imaging microscopy (FLIM) histology-based analysis. Analysis of 131 tissue microarray cores demonstrated that the extent of HER2-HER3 dimer formation as measured by Förster Resonance Energy Transfer (FRET) determined through FLIM predicts the likelihood of metastatic relapse up to 10 years after surgery (hazard ratio 3.91 (1.61–9.5), p = 0.003) independently of HER2 expression, in a multivariate model. Interestingly there was no correlation between the level of HER2 protein expressed and HER2-HER3 heterodimer formation. We used a mathematical model that takes into account the complex interactions in a network of all four HER proteins to explain this counterintuitive finding. Future utility of this technique may highlight a group of patients who do not overexpress HER2 protein but are nevertheless dependent on the HER2-HER3 heterodimer as driver of proliferation. This assay could, if validated in a group of patients treated with, for instance pertuzumab, be used as a predictive biomarker to predict for response to such targeted therapies.
      274Scopus© Citations 21
  • Publication
    Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses
    We show theoretically and experimentally a mechanism behind the emergence of wide or bimodal protein distributions in biochemical networks with nonlinear input–output characteristics (the dose–response curve) and variability in protein abundance. Large cell-to-cell variation in the nonlinear dose–response characteristics can be beneficial to facilitate two distinct groups of response levels as opposed to a graded response. Under the circumstances that we quantify mathematically, the two distinct responses can coexist within a cellular population, leading to the emergence of a bimodal protein distribution. Using flow cytometry, we demonstrate the appearance of wide distributions in the hypoxia-inducible factor-mediated response network in HCT116 cells. With help of our theoretical framework, we perform a novel calculation of the magnitude of cell-to-cell heterogeneity in the dose–response obtained experimentally.
      391Scopus© Citations 18
  • Publication
    Bistability in the Rac1, PAK, and RhoA Signaling Network Drives Actin Cytoskeleton Dynamics and Cell Motility Switches
    Dynamic interactions between RhoA and Rac1, members of the Rho small GTPase family, play a vital role in the control of cell migration. Using predictive mathematical modeling, mass spectrometry-based quantitation of network components, and experimental validation in MDA-MB-231 mesenchymal breast cancer cells, we show that a network containing Rac1, RhoA, and PAK family kinases can produce bistable, switch-like responses to a graded PAK inhibition. Using a small chemical inhibitor of PAK, we demonstrate that cellular RhoA and Rac1 activation levels respond in a history-dependent, bistable manner to PAK inhibition. Consequently, we show that downstream signaling, actin dynamics, and cell migration also behave in a bistable fashion, displaying switches and hysteresis in response to PAK inhibition. Our results demonstrate that PAK is a critical component in the Rac1-RhoA inhibitory crosstalk that governs bistable GTPase activity, cell morphology, and cell migration switches.
      320Scopus© Citations 108
  • Publication
    Protein-protein interactions generate hidden feedback and feed-forward loops to trigger bistable switches, oscillations and biphasic dose-responses
    Protein-protein interactions (PPIs) defined as reversible association of two proteins to form a complex, are undoubtedly among the most common interaction motifs featured in cells. Recent large-scale proteomic studies have revealed an enormously complex interactome of the cell, consisting of tens of thousands of PPIs with numerous signalling hubs. PPIs have functional roles in regulating a wide range of cellular processes including signal transduction and post-translational modifications, and de-regulation of PPIs is implicated in many diseases including cancers and neuro-degenerative disorders. Despite the ubiquitous appearance and physiological significance of PPIs, our understanding of the dynamic and functional consequences of these simple motifs remains incomplete, particularly when PPIs occur within large biochemical networks. We employ quantitative, dynamic modelling to computationally analyse salient dynamic features of the PPI motifs and PPI-containing signalling networks varying in topological architecture. Our analyses surprisingly reveal that simple reversible PPI motifs, when being embedded into signalling cascades, could give rise to extremely rich and complex regulatory dynamics in the absence of explicit positive and negative feedback loops. Our work represents a systematic investigation of the dynamic properties of PPIs in signalling networks, and the results shed light on how this simple event may potentiate diverse and intricate behaviours in vivo.
      311Scopus© Citations 18
  • Publication
    Distinct noise-controlling roles of multiple negative feedback mechanisms in a prokaryotic operon system
    (Institution of Electrical Engineers, 2011-03-01) ;
    Molecular fluctuations are known to affect dynamics of cellular systems in important ways. Studies aimed at understanding how molecular systems of certain regulatory architectures control noise therefore become essential. The interplay between feedback regulation and noise has been previously explored for cellular networks governed by a single negative feedback loop. However, similar issues within networks consisting of more complex regulatory structures remain elusive. The authors investigate how negative feedback loops manage noise within a biochemical cascade concurrently governed by multiple negative feedback loops, using the prokaryotic tryptophan (trp) operon system in Escherechia coli as the model system. To the authors knowledge, this is the first study of noise in the trp operon system. They show that the loops in the trp operon system possess distinct, even opposing, noise-controlling effects despite their seemingly analogous feedback structures. The enzyme inhibition loop, although controlling the last reaction of the cascade, was found to suppress noise not only for the tryptophan output but also for other upstream components. In contrast, the Repression (Rep) loop enhances noise for all systems components. Attenuation (Att) poses intermediate effects by attenuating noise for the upstream components but promoting noise for components downstream of its target. Regarding noise at the output tryptophan, Rep and Att can be categorised as noise-enhancing loops whereas Enzyme Inhibition as a noise-reducing loop. These findings suggest novel implications in how cellular systems with multiple feedback mechanisms control noise.
      294Scopus© Citations 6
  • 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
      265Scopus© Citations 21
  • Publication
    Substrate-Trapped Interactors of PHD3 and FIH Cluster in Distinct Signaling Pathways
    Amino acid hydroxylation is a post-translational modification that regulates intra- and inter-molecular protein-protein interactions. The modifications are regulated by a family of 2-oxoglutarate- (2OG) dependent enzymes and, although the biochemistry is well understood, until now only a few substrates have been described for these enzymes. Using quantitative interaction proteomics, we screened for substrates of the proline hydroxylase PHD3 and the asparagine hydroxylase FIH, which regulate the HIF-mediated hypoxic response. We were able to identify hundreds of potential substrates. Enrichment analysis revealed that the potential substrates of both hydroxylases cluster in the same pathways but frequently modify different nodes of signaling networks. We confirm that two proteins identified in our screen, MAPK6 (Erk3) and RIPK4, are indeed hydroxylated in a FIH- or PHD3-dependent mechanism. We further determined that FIH-dependent hydroxylation regulates RIPK4-dependent Wnt signaling, and that PHD3-dependent hydroxylation of MAPK6 protects the protein from proteasomal degradation.
      262Scopus© Citations 59
  • 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.
      578Scopus© Citations 37
  • Publication
    Integrated signaling pathway and gene expression regulatory model to dissect dynamics of Escherichia coli challenged mammary epithelial cells
    Cells transform external stimuli, through the activation of signaling pathways, which in turn activate gene regulatory networks, in gene expression. As more omics data are generated from experiments, eliciting the integrated relationship between the external stimuli, the signaling process in the cell and the subsequent gene expression is a major challenge in systems biology. The complex system of non-linear dynamic protein interactions in signaling pathways and gene networks regulates gene expression. The complexity and non-linear aspects have resulted in the study of the signaling pathway or the gene network regulation in isolation. However, this limits the analysis of the interaction between the two components and the identification of the source of the mechanism differentiating the gene expression profiles. Here, we present a study of a model of the combined signaling pathway and gene network to highlight the importance of integrated modeling. Based on the experimental findings we developed a compartmental model and conducted several simulation experiments. The model simulates the mRNA expression of three different cytokines (RANTES, IL8 and TNFα) regulated by the transcription factor NFκB in mammary epithelial cells challenged with E. coli. The analysis of the gene network regulation identifies a lack of robustness and therefore sensitivity for the transcription factor regulation. However, analysis of the integrated signaling and gene network regulation model reveals distinctly different underlying mechanisms in the signaling pathway responsible for the variation between the three cytokine's mRNA expression levels. Our key findings reveal the importance of integrating the signaling pathway and gene expression dynamics in modeling. Modeling infers valid research questions which need to be verified experimentally and can assist in the design of future biological experiments.
      216Scopus© Citations 7
  • Publication
    Polyubiquitin chain assembly and organization determine the dynamics of protein activation and degradation
    Protein degradation via ubiquitination is a major proteolytic mechanism in cells. Once a protein is destined for degradation, it is tagged by multiple ubiquitin (Ub) molecules. The synthesized polyubiquitin chains can be recognized by the 26S proteosome where proteins are degraded. These chains form through multiple ubiquitination cycles that are similar to multi-site phosphorylation cycles. As kinases and phosphatases, two opposing enzymes (E3 ligases and deubiquitinases DUBs) catalyze (de)ubiquitination cycles. Although multi-ubiquitination cycles are fundamental mechanisms of controlling protein concentrations within a cell, their dynamics have never been explored. Here, we fill this knowledge gap. We show that under permissive physiological conditions, the formation of polyubiquitin chain of length greater than two and subsequent degradation of the ubiquitinated protein, which is balanced by protein synthesis, can display bistable, switch-like responses. Interestingly, the occurrence of bistability becomes pronounced, as the chain grows, giving rise to "all-or-none" regulation at the protein levels. We give predictions of protein distributions under bistable regime awaiting experimental verification. Importantly, we show for the first time that sustained oscillations can robustly arise in the process of formation of ubiquitin chain, largely due to the degradation of the target protein. This new feature is opposite to the properties of multi-site phosphorylation cycles, which are incapable of generating oscillation if the total abundance of interconverted protein forms is conserved. We derive structural and kinetic constraints for the emergence of oscillations, indicating that a competition between different substrate forms and the E3 and DUB is critical for oscillation. Our work provides the first detailed elucidation of the dynamical features brought about by different molecular setups of the polyubiquitin chain assembly process responsible for protein degradation.
      261Scopus© Citations 20