Modeling Cell Line-Specific Recruitment of Signaling Proteins to the Insulin-Like Growth Factor 1 Receptor

Receptor tyrosine kinases (RTKs) typically contain multiple autophosphorylation sites in their cytoplasmic domains. Once activated, these autophosphorylation sites can recruit downstream signaling proteins containing Src homology 2 (SH2) and phosphotyrosine-binding (PTB) domains, which recognize phosphotyrosine-containing short linear motifs (SLiMs). These domains and SLiMs have polyspecific or promiscuous binding activities. Thus, multiple signaling proteins may compete for binding to a common SLiM and vice versa. To investigate the effects of competition on RTK signaling, we used a rule-based modeling approach to develop and analyze models for ligand-induced recruitment of SH2/PTB domain-containing proteins to autophosphorylation sites in the insulin-like growth factor 1 (IGF1) receptor (IGF1R). Models were parameterized using published datasets reporting protein copy numbers and site-specific binding affinities. Simulations were facilitated by a novel application of model restructuration, to reduce redundancy in rule-derived equations. We compare predictions obtained via numerical simulation of the model to those obtained through simple prediction methods, such as through an analytical approximation, or ranking by copy number and/or K D value, and find that the simple methods are unable to recapitulate the predictions of numerical simulations. We created 45 cell line-specific models that demonstrate how early events in IGF1R signaling depend on the protein abundance profile of a cell. Simulations, facilitated by model restructuration, identified pairs of IGF1R binding partners that are recruited in anti-correlated and correlated fashions, despite no inclusion of cooperativity in our models. This work shows that the outcome of competition depends on the physicochemical parameters that characterize pairwise interactions, as well as network properties, including network connectivity and the relative abundances of competitors

Structural basis for activation of trimeric Gi proteins by multiple growth factor receptors via GIV/Girdin.

A long-standing issue in the field of signal transduction is to understand the cross-talk between receptor tyrosine kinases (RTKs) and heterotrimeric G proteins, two major and distinct signaling hubs that control eukaryotic cell behavior. Although stimulation of many RTKs leads to activation of trimeric G proteins, the molecular mechanisms behind this phenomenon remain elusive. We discovered a unifying mechanism that allows GIV/Girdin, a bona fide metastasis-related protein and a guanine-nucleotide exchange factor (GEF) for Gαi, to serve as a direct platform for multiple RTKs to activate Gαi proteins. Using a combination of homology modeling, protein-protein interaction, and kinase assays, we demonstrate that a stretch of ∼110 amino acids within GIV C-terminus displays structural plasticity that allows folding into a SH2-like domain in the presence of phosphotyrosine ligands. Using protein-protein interaction assays, we demonstrated that both SH2 and GEF domains of GIV are required for the formation of a ligand-activated ternary complex between GIV, Gαi, and growth factor receptors and for activation of Gαi after growth factor stimulation. Expression of a SH2-deficient GIV mutant (Arg 1745→Leu) that cannot bind RTKs impaired all previously demonstrated functions of GIV-Akt enhancement, actin remodeling, and cell migration. The mechanistic and structural insights gained here shed light on the long-standing questions surrounding RTK/G protein cross-talk, set a novel paradigm, and characterize a unique pharmacological target for uncoupling GIV-dependent signaling downstream of multiple oncogenic RTKs

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Orton et al.BACKGROUND: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway. RESULTS: We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors. CONCLUSION: Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel

Quantitative Analysis of EGFR Phosphorylation and SH2 Domain Binding in vivo

The work presented in the following thesis dissertation examines the regulation of phosphotyrosine (pY) signaling, an essential cellular process that relies on the activity of three major protein classes: Tyrosine kinases (TKs) which induce pY signaling by phosphorylating tyrosine residues on substrate proteins, Protein tyrosine phosphatases (PTPs) which suppress pY signaling by removing phosphate moieties from tyrosine phosphorylated proteins and Src-Homology 2 (SH2) containing proteins which bind to tyrosine phosphorylated proteins and connect them to downstream signaling pathways. The effects of kinase localization, temporal changes in kinase activation, SH2 protein concentration, and negative feedback from downstream signaling pathways are all examined by the research presented here. This is accomplished by exploiting the Epidermal Growth Factor Receptor (EGFR), a clinically important transmembrane TK, and its SH2 protein mediated downstream pathways. Using EGFR signaling as a tool, this dissertation research attempts to define innate properties of pY signaling systems which are broadly applicable and advance our understanding of the field

Getting old through the blood. Circulating molecules in aging and senescence of cardiovascular regenerative cells

Global aging is a hallmark of our century. The natural multifactorial process resulting in aging involves structural and functional changes, affecting molecules, cells, and tissues. As the western population is getting older, we are witnessing an increase in the burden of cardiovascular events, some of which are known to be directly linked to cellular senescence and dysfunction. In this review, we will focus on the description of a few circulating molecules, which have been correlated to life span, aging, and cardiovascular homeostasis. We will review the current literature concerning the circulating levels and related signaling pathways of selected proteins (insulin-like growth factor 1, growth and differentiation factor-11, and PAI-1) and microRNAs of interest (miR-34a, miR-146a, miR-21), whose bloodstream levels have been associated to aging in different organisms. In particular, we will also discuss their potential role in the biology and senescence of cardiovascular regenerative cell types, such as endothelial progenitor cells, mesenchymal stromal cells, and cardiac progenitor cells

Yes-associated protein (YAP) in pancreatic cancer: at the epicenter of a targetable signaling network associated with patient survival.

Pancreatic ductal adenocarcinoma (PDAC) is generally a fatal disease with no efficacious treatment modalities. Elucidation of signaling mechanisms that will lead to the identification of novel targets for therapy and chemoprevention is urgently needed. Here, we review the role of Yes-associated protein (YAP) and WW-domain-containing Transcriptional co-Activator with a PDZ-binding motif (TAZ) in the development of PDAC. These oncogenic proteins are at the center of a signaling network that involves multiple upstream signals and downstream YAP-regulated genes. We also discuss the clinical significance of the YAP signaling network in PDAC using a recently published interactive open-access database (www.proteinatlas.org/pathology) that allows genome-wide exploration of the impact of individual proteins on survival outcomes. Multiple YAP/TEAD-regulated genes, including AJUBA, ANLN, AREG, ARHGAP29, AURKA, BUB1, CCND1, CDK6, CXCL5, EDN2, DKK1, FOSL1,FOXM1, HBEGF, IGFBP2, JAG1, NOTCH2, RHAMM, RRM2, SERP1, and ZWILCH, are associated with unfavorable survival of PDAC patients. Similarly, components of AP-1 that synergize with YAP (FOSL1), growth factors (TGFα, EPEG, and HBEGF), a specific integrin (ITGA2), heptahelical receptors (P2Y2R, GPR87) and an inhibitor of the Hippo pathway (MUC1), all of which stimulate YAP activity, are associated with unfavorable survival of PDAC patients. By contrast, YAP inhibitory pathways (STRAD/LKB-1/AMPK, PKA/LATS, and TSC/mTORC1) indicate a favorable prognosis. These associations emphasize that the YAP signaling network correlates with poor survival of pancreatic cancer patients. We conclude that the YAP pathway is a major determinant of clinical aggressiveness in PDAC patients and a target for therapeutic and preventive strategies in this disease

Preclinical and clinical studies of estrogen deprivation support the PDGF/Abl pathway as a novel therapeutic target for overcoming endocrine resistance in breast cancer

INTRODUCTION: The majority of breast tumors at primary diagnosis are estrogen receptor positive (ER+). Estrogen (E) mediates its effects by binding to the ER. Therapies targeting the estrogenic stimulation of tumor growth reduce mortality from ER+ breast cancer. However, resistance remains a major clinical problem. METHODS: To identify molecular mechanisms associated with resistance to E-deprivation, we assessed the temporal changes in global gene expression during adaptation to long-term culture of MCF7 human breast cancer cells in the absence of estradiol (E2), long term estrogen deprived (LTED), that leads to recovery of proliferative status and models resistance to an aromatase inhibitor (AI). The expression levels of proteins were determined by western blotting. Proliferation assays were carried out using the dual platelet derived growth factor receptor (PDGFR)/Abelson tyrosine kinase (Abl) inhibitor nilotinib. Luciferase reporter assays were used to determine effects on ER-mediated transactivation. Changes in recruitment of cofactors to the gene regulated by estrogen in breast cancer 1 (GREB1) promoter were determined by chromatin immunoprecipitation (ChIP). Gene expression data were derived from 81 postmenopausal women with ER+ BC pre-treatment and at two-weeks post-treatment with single agent anastrozole in a neoadjuvant trial. RESULTS: The PDGF/Abl canonical pathway was significantly elevated as early as one week post E-deprivation (P = 1.94 E-04) and this became the top adaptive pathway at the point of proliferative recovery (P = 1.15 E-07). Both PDGFRβ and Abl protein levels were elevated in the LTED cells compared to wild type (wt)-MCF7 cells. The PDGF/Abl tyrosine kinase inhibitor nilotinib, suppressed proliferation in LTED cells in the presence or absence of E. Nilotinib also suppressed ER-mediated transcription by destabilizing the ER and reducing recruitment of amplified in breast cancer-1 (AIB1) and the CREB binding protein (CBP) to the promoter of the E-responsive gene GREB1. High PDGFRβ in primary ER+ breast cancer of 81 patients prior to neoadjuvant treatment with an AI was associated with poorer antiproliferative response. Additionally PDGFRβ expression increased after two weeks of AI therapy (1.25 fold, P = 0.003). CONCLUSIONS: These preclinical and clinical data indicate that the PDGF/Abl signaling pathway merits clinical evaluation as a therapeutic target with endocrine therapy in ER+ breast cancer

Spatiotemporal modeling and model restructuration approaches in studies of intracellular signalling pathways

The main focus of the research is to understand the complex phenomena of cell transduction pathways and cell biology in a single cell. Mathematical modeling and experimental evaluation are widely used approaches for this kind of research. Firstly, A multiscale framework for protein-protein interaction has been established using Brownian dynamics algorithm. Sit specific feature, steric collision, diffusion, co-localization and complex formation with time and space has been included in this spatial modeling framework. By implementation of the time adaptive feature in this framework, the computation time reduces in an order of magnitude compared with traditional modeling framework. This multiscale Brownian framework has been used for the investigation FcεRI aggregation which is an important signaling pathway for immune cells. Using the spatial modeling framework, FcεRI aggregation in the presence of trivalent antigen showed consistent results with current experimental studies. Secondly, the rule-based modeling approach is an excellent way of performing large biochemical network modeling for a single cell as it considers the site-specific features. However, the major difficulty of rule-based modeling approach is combinatorial complexity. In this study, model restructuring approaches have been applied to overcome this problem for cell signaling pathway modeling. These mechanistic modeling approaches are very effective to model large network of signaling pathways together without compromising the accuracy. Finally, Cell size dependent cellular uptake study carried out using confocal microscopy and flow cytometer. To understand the particle uptake behavior with time and steady state condition, reaction-diffusion and kinetics model has been developed in these work. After a detailed analysis of experimental data and models, it showed that total particle uptake is increasing with cell size, however, particle flux is reducing in larger cells --Abstract, page iv

Computational Modeling and Analysis of Insulin Induced Eukaryotic Translation Initiation

Insulin, the primary hormone regulating the level of glucose in the bloodstream, modulates a variety of cellular and enzymatic processes in normal and diseased cells. Insulin signals are processed by a complex network of biochemical interactions which ultimately induce gene expression programs or other processes such as translation initiation. Surprisingly, despite the wealth of literature on insulin signaling, the relative importance of the components linking insulin with translation initiation remains unclear. We addressed this question by developing and interrogating a family of mathematical models of insulin induced translation initiation. The insulin network was modeled using mass-action kinetics within an ordinary differential equation (ODE) framework. A family of model parameters was estimated, starting from an initial best fit parameter set, using 24 experimental data sets taken from literature. The residual between model simulations and each of the experimental constraints were simultaneously minimized using multiobjective optimization. Interrogation of the model population, using sensitivity and robustness analysis, identified an insulin-dependent switch that controlled translation initiation. Our analysis suggested that without insulin, a balance between the pro-initiation activity of the GTP-binding protein Rheb and anti-initiation activity of PTEN controlled basal initiation. On the other hand, in the presence of insulin a combination of PI3K and Rheb activity controlled inducible initiation, where PI3K was only critical in the presence of insulin. Other well known regulatory mechanisms governing insulin action, for example IRS-1 negative feedback, modulated the relative importance of PI3K and Rheb but did not fundamentally change the signal flow