PI3K-dependent cross-talk interactions converge with Ras as quantifiable inputs integrated by Erk

Allosteric modulation of Ras-GTP is linked to signal transduction through RAF kinase

Ras is a key signal transduction protein in the cell. Mutants of Gly(12) and Gln(61) impair GTPase activity and are found prominently in cancers. In wild type Ras-GTP, an allosteric switch promotes disorder to order transition in switch II, placing Gln(61) in the active site. We show that the "on" and "off" conformations of the allosteric switch can also be attained in RasG12V and RasQ61L. Although both mutants have similarly impaired active sites in the on state, RasQ61L stabilizes an anti-catalytic conformation of switch II in the off state of the allosteric switch when bound to Raf. This translates into more potent activation of the MAPK pathway involving Ras, Raf kinase, MEK, and ERK (Ras/Raf/MEK/ERK) in cells transfected with RasQ61L relative to RasG12V. This differential is not observed in the Raf-independent pathway involving Ras, phosphoinositide 3-kinase (PI3K), and Akt (Ras/PI3K/Akt). Using a combination of structural analysis, hydrolysis rates, and experiments in NIH-3T3 cells, we link the allosteric switch to the control of signaling in the Ras/Raf/MEK/ERK pathway, supporting a GTPase-activating protein-independent model for duration of the Ras-Raf complex.

Systematic quantification of negative feedback mechanisms in the extracellular signal-regulated kinase (ERK) signaling network

Cell responses are actuated by tightly controlled signal transduction pathways. Although the concept of an integrated signaling network replete with interpathway cross-talk and feedback regulation is broadly appreciated, kinetic data of the type needed to characterize such interactions in conjunction with mathematical models are lacking. In mammalian cells, the Ras/ERK pathway controls cell proliferation and other responses stimulated by growth factors, and several cross-talk and feedback mechanisms affecting its activation have been identified. In this work, we take a systematic approach to parse the magnitudes of multiple regulatory mechanisms that attenuate ERK activation through canonical (Ras-dependent) and non-canonical (PI3K-dependent) pathways. In addition to regulation of receptor and ligand levels, we consider three layers of ERK-dependent feedback: desensitization of Ras activation, negative regulation of MEK kinase (e.g. Raf) activities, and up-regulation of dual-specificity ERK phosphatases. Our results establish the second of these as the dominant mode of ERK self-regulation in mouse fibroblasts. We further demonstrate that kinetic models of signaling networks, trained on a sufficient diversity of quantitative data, can be reasonably comprehensive, accurate, and predictive in the dynamical sense.

Macrophage-induced preadipocyte survival depends on signaling through Akt, ERK1/2, and reactive oxygen species

Obesity is associated with adipose tissue remodeling, characterized by macrophage accumulation, adipocyte hypertrophy, and apoptosis. We previously reported that macrophage-conditioned medium (MacCM) protects preadipocytes from apoptosis, due to serum withdrawal, in a platelet-derived growth factor (PDGF)-dependent manner. We have now investigated the role of intracellular signaling pathways, activated in response to MacCM versus PDGF, in promoting preadipocyte survival. Exposure of 3T3-L1 preadipocytes to J774A.1-MacCM or PDGF strongly stimulated Akt and ERK1/2 phosphorylation from initially undetectable levels. Inhibition of the upstream regulators of Akt or ERK1/2, i.e. phosphoinositide 3-kinase (PI3K; using wortmannin or LY294002) or MEK1/2 (using UO126 or PD98509), abrogated the respective phosphorylation responses, and significantly impaired pro-survival activity. J774A.1-MacCM increased reactive oxygen species (ROS) levels by 3.4-fold, and diphenyleneiodonium (DPI) or N-acetyl cysteine (NAC) significantly inhibited pro-survival signaling and preadipocyte survival in response to J774A.1-MacCM. Serum withdrawal itself also increased ROS levels (2.1-fold), and the associated cell death was attenuated by DPI or NAC. In summary, J774A.1-MacCM-dependent 3T3-L1 preadipocyte survival requires the Akt and ERK1/2 signaling pathways. Furthermore, ROS generation by J774A.1-MacCM is required for Akt and ERK1/2 signaling to promote 3T3-L1 preadipocyte survival. These data suggest potential mechanisms by which macrophages may alter preadipocyte fate.

Identification of optimal drug combinations targeting cellular networks: integrating phospho-proteomics and computational network analysis

Targeted therapeutics hold tremendous promise in inhibiting cancer cell proliferation. However, targeting proteins individually can be compensated for by bypass mechanisms and activation of regulatory loops. Designing optimal therapeutic combinations must therefore take into consideration the complex dynamic networks in the cell. In this study, we analyzed the insulin-like growth factor (IGF-1) signaling network in the MDA-MB231 breast cancer cell line. We used reverse-phase protein array to measure the transient changes in the phosphorylation of proteins after IGF-1 stimulation. We developed a computational procedure that integrated mass action modeling with particle swarm optimization to train the model against the experimental data and infer the unknown model parameters. The trained model was used to predict how targeting individual signaling proteins altered the rest of the network and identify drug combinations that minimally increased phosphorylation of other proteins elsewhere in the network. Experimental testing of the modeling predictions showed that optimal drug combinations inhibited cell signaling and proliferation, whereas nonoptimal combination of inhibitors increased phosphorylation of nontargeted proteins and rescued cells from cell death. The integrative approach described here is useful for generating experimental intervention strategies that could optimize drug combinations and discover novel pharmacologic targets for cancer therapy.

Uniformly curated signaling pathways reveal tissue-specific cross-talks and support drug target discovery

MOTIVATION

Signaling pathways control a large variety of cellular processes. However, currently, even within the same database signaling pathways are often curated at different levels of detail. This makes comparative and cross-talk analyses difficult.

RESULTS

We present SignaLink, a database containing eight major signaling pathways from Caenorhabditis elegans, Drosophila melanogaster and humans. Based on 170 review and approximately 800 research articles, we have compiled pathways with semi-automatic searches and uniform, well-documented curation rules. We found that in humans any two of the eight pathways can cross-talk. We quantified the possible tissue- and cancer-specific activity of cross-talks and found pathway-specific expression profiles. In addition, we identified 327 proteins relevant for drug target discovery.

CONCLUSIONS

We provide a novel resource for comparative and cross-talk analyses of signaling pathways. The identified multi-pathway and tissue-specific cross-talks contribute to the understanding of the signaling complexity in health and disease, and underscore its importance in network-based drug target selection.

AVAILABILITY

http://SignaLink.org.

Signalling ballet in space and time

Although we have amassed extensive catalogues of signalling network components, our understanding of the spatiotemporal control of emergent network structures has lagged behind. Dynamic behaviour is starting to be explored throughout the genome, but analysis of spatial behaviours is still confined to individual proteins. The challenge is to reveal how cells integrate temporal and spatial information to determine specific biological functions. Key findings are the discovery of molecular signalling machines such as Ras nanoclusters, spatial activity gradients and flexible network circuitries that involve transcriptional feedback. They reveal design principles of spatiotemporal organization that are crucial for network function and cell fate decisions.

Cancer systems biology: a network modeling perspective

Cancer is now appreciated as not only a highly heterogenous pathology with respect to cell type and tissue origin but also as a disease involving dysregulation of multiple pathways governing fundamental cell processes such as death, proliferation, differentiation and migration. Thus, the activities of molecular networks that execute metabolic or cytoskeletal processes, or regulate these by signal transduction, are altered in a complex manner by diverse genetic mutations in concert with the environmental context. A major challenge therefore is how to develop actionable understanding of this multivariate dysregulation, with respect both to how it arises from diverse genetic mutations and to how it may be ameliorated by prospective treatments. While high-throughput experimental platform technologies ranging from genomic sequencing to transcriptomic, proteomic and metabolomic profiling are now commonly used for molecular-level characterization of tumor cells and surrounding tissues, the resulting data sets defy straightforward intuitive interpretation with respect to potential therapeutic targets or the effects of perturbation. In this review article, we will discuss how significant advances can be obtained by applying computational modeling approaches to elucidate the pathways most critically involved in tumor formation and progression, impact of particular mutations on pathway operation, consequences of altered cell behavior in tissue environments and effects of molecular therapeutics.

Epidermal growth factor-induced cyclooxygenase-2 expression in oral squamous cell carcinoma cell lines is mediated through extracellular signal-regulated kinase 1/2 and p38 but is Src and nuclear factor-kappa B independent

The intracellular signalling cascade(s) mediating epidermal growth factor (EGF)-induced cyclooxygenase-2 (COX-2) expression is poorly defined in oral carcinomas. Investigation of two different oral squamous cell carcinoma (OSCC) cell lines with high EGF-induced COX-2 expression revealed, however, that this expression was dependent on two mitogen-activated protein kinase (MAPK) pathways [extracellular signal-regulated kinase 1/2 (ERK1/2) and p38] because combined inhibition of these pathways was needed to abolish EGF-induced COX-2 expression. Surprisingly, inhibition of phosphoinositide-3 kinase (PI3K) increased EGF-induced COX-2 expression in the basaloid OSCC cell line (C12), suggesting a PI3K-controlled, inhibitory COX-2-regulating pathway. Neither the transcription factor nuclear factor-kappaB (NF-kappaB), nor Src, was involved in EGF-induced COX-2 expression. The results suggest that EGF-induced COX-2 expression is regulated by several pathways, and emphasizes that individual tumors use different strategies for intracellular signalling.

Pathway databases and tools for their exploitation: benefits, current limitations and challenges

In past years, comprehensive representations of cell signalling pathways have been developed by manual curation from literature, which requires huge effort and would benefit from information stored in databases and from automatic retrieval and integration methods. Once a reconstruction of the network of interactions is achieved, analysis of its structural features and its dynamic behaviour can take place. Mathematical modelling techniques are used to simulate the complex behaviour of cell signalling networks, which ultimately sheds light on the mechanisms leading to complex diseases or helps in the identification of drug targets. A variety of databases containing information on cell signalling pathways have been developed in conjunction with methodologies to access and analyse the data. In principle, the scenario is prepared to make the most of this information for the analysis of the dynamics of signalling pathways. However, are the knowledge repositories of signalling pathways ready to realize the systems biology promise? In this article we aim to initiate this discussion and to provide some insights on this issue.

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.