Oncogenic Ras activation of Raf/mitogen-activated protein kinase-independent pathways is sufficient to cause tumorigenic transformation

Substantial evidence supports a critical role for the activation of the Raf-1/MEK/mitogen-activated protein kinase pathway in oncogenic Ras-mediated transformation. For example, dominant negative mutants of Raf-1, MEK, and mitogen-activated protein kinase all inhibit Ras transformation. Furthermore, the observation that plasma membrane-localized Raf-1 exhibits the same transforming potency as oncogenic Ras suggests that Raf-1 activation alone is sufficient to mediate full Ras transforming activity. However, the recent identification of other candidate Ras effectors (e.g., RalGDS and phosphatidylinositol-3 kinase) suggests that activation of other downstream effector-mediated signaling pathways may also mediate Ras transforming activity. In support of this, two H-Ras effector domain mutants, H-Ras(12V, 37G) and H-Ras(12V, 40C), which are defective for Raf binding and activation, induced potent tumorigenic transformation of some strains of NIH 3T3 fibroblasts. These Raf-binding defective mutants of H-Ras induced a transformed morphology that was indistinguishable from that induced by activated members of Rho family proteins. Furthermore, the transforming activities of both of these mutants were synergistically enhanced by activated Raf-1 and inhibited by the dominant negative RhoA(19N) mutant, indicating that Ras may cause transformation that occurs via coordinate activation of Raf-dependent and -independent pathways that involves Rho family proteins. Finally, cotransfection of H-Ras(12V, 37G) and H-Ras(12V, 40C) resulted in synergistic cooperation of their focus-forming activities, indicating that Ras activates at least two Raf-independent, Ras effector-mediated signaling events

Characterizing Operations Preserving Separability Measures via Linear Preserver Problems

We use classical results from the theory of linear preserver problems to characterize operators that send the set of pure states with Schmidt rank no greater than k back into itself, extending known results characterizing operators that send separable pure states to separable pure states. We also provide a new proof of an analogous statement in the multipartite setting. We use these results to develop a bipartite version of a classical result about the structure of maps that preserve rank-1 operators and then characterize the isometries for two families of norms that have recently been studied in quantum information theory. We see in particular that for k at least 2 the operator norms induced by states with Schmidt rank k are invariant only under local unitaries, the swap operator and the transpose map. However, in the k = 1 case there is an additional isometry: the partial transpose map.Comment: 16 pages, typos corrected, references added, proof of Theorem 4.3 simplified and clarifie

The CAAX peptidomimetic compound B581 specifically blocks farnesylated, but not geranylgeranylated or myristylated, oncogenic ras signaling and transformation

Recently developed CAAX peptidomimetic compounds have been shown to be potent and specific inhibitors of farnesyl protein transferase activity and to block the growth of Ras-transformed cells. However, whether this growth inhibitory action is specifically a consequence of blocking oncogenic Ras signaling has not been determined. To address this question, we have utilized mutants of the normally farnesylated oncogenic Ras protein (Ras-F) that are modified by alternative lipids, a geranylgeranyl isoprenoid (Ras-GG) or the fatty acid myristate (Myr-Ras), to determine the specificity of the CAAX peptidomimetic compound, B581

Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone.National Institutes of Health (U.S.) (NIH grant P50-GM68762)National Institutes of Health (U.S.) (Grant U54-CA112967)United States. Dept. of Defense (Institute for Collaborative Biotechnologies

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation

<p>Abstract</p> <p>Background</p> <p>External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.</p> <p>Results</p> <p>We therefore develop the concept of graph-decorrelation. We encode prior knowledge like transcriptional regulation, protein interactions or metabolic pathways in a weighted directed graph. By linking features along this underlying graph, we introduce a partial ordering of the features (e.g. genes) and are thus able to define a graph-delayed correlation function. Using this framework as constraint to the matrix factorization task allows us to set up the fast and robust graph-decorrelation algorithm (GraDe). To analyze alterations in the gene response in <it>IL-6 </it>stimulated primary mouse hepatocytes, we performed a time-course microarray experiment and applied GraDe. In contrast to standard techniques, the extracted time-resolved gene expression profiles showed that <it>IL-6 </it>activates genes involved in cell cycle progression and cell division. Genes linked to metabolic and apoptotic processes are down-regulated indicating that <it>IL-6 </it>mediated priming renders hepatocytes more responsive towards cell proliferation and reduces expenditures for the energy metabolism.</p> <p>Conclusions</p> <p>GraDe provides a novel framework for the decomposition of large-scale 'omics' data. We were able to show that including prior knowledge into the separation task leads to a much more structured and detailed separation of the time-dependent responses upon <it>IL-6 </it>stimulation compared to standard methods. A Matlab implementation of the GraDe algorithm is freely available at <url>http://cmb.helmholtz-muenchen.de/grade</url>.</p

Induction of Epithelial Mesenchimal Transition and Vasculogenesis in the Lenses of Dbl Oncogene Transgenic Mice

BACKGROUND: The Dbl family of proteins represents a large group of proto-oncogenes involved in cell growth regulation. The numerous domains that are present in many Dbl family proteins suggest that they act to integrate multiple inputs in complicated signaling networks involving the Rho GTPases. Alterations of the normal function of these proteins lead to pathological processes such as developmental disorders and neoplastic transformation. We generated transgenic mice introducing the cDNA of Dbl oncogene linked to the metallothionein promoter into the germ line of FVB mice and found that onco-Dbl expression in mouse lenses affected proliferation, migration and differentiation of lens epithelial cells. RESULTS: We used high density oligonucleotide microarray to define the transcriptional profile induced by Dbl in the lenses of 2 days, 2 weeks, and 6 weeks old transgenic mice. We observed modulation of genes encoding proteins promoting epithelial-mesenchymal transition (EMT), such as down-regulation of epithelial cell markers and up-regulation of fibroblast markers. Genes encoding proteins involved in the positive regulation of apoptosis were markedly down regulated while anti-apoptotic genes were strongly up-regulated. Finally, several genes encoding proteins involved in the process of angiogenesis were up-regulated. These observations were validated by histological and immunohistochemical examination of the transgenic lenses where vascularization can be readily observed. CONCLUSION: Onco-Dbl expression in mouse lens correlated with modulation of genes involved in the regulation of EMT, apoptosis and vasculogenesis leading to disruption of the lens architecture, epithelial cell proliferation, and aberrant angiogenesis. We conclude that onco-Dbl has a potentially important, previously unreported, capacity to dramatically alter epithelial cell migration, replication, polarization and differentiation and to induce vascularization of an epithelial tissue

The P2X1 receptor and platelet function

Extracellular nucleotides are ubiquitous signalling molecules, acting via the P2 class of surface receptors. Platelets express three P2 receptor subtypes, ADP-dependent P2Y1 and P2Y12 G-protein-coupled receptors and the ATP-gated P2X1 non-selective cation channel. Platelet P2X1 receptors can generate significant increases in intracellular Ca2+, leading to shape change, movement of secretory granules and low levels of αIIbβ3 integrin activation. P2X1 can also synergise with several other receptors to amplify signalling and functional events in the platelet. In particular, activation of P2X1 receptors by ATP released from dense granules amplifies the aggregation responses to low levels of the major agonists, collagen and thrombin. In vivo studies using transgenic murine models show that P2X1 receptors amplify localised thrombosis following damage of small arteries and arterioles and also contribute to thromboembolism induced by intravenous co-injection of collagen and adrenaline. In vitro, under flow conditions, P2X1 receptors contribute more to aggregate formation on collagen-coated surfaces as the shear rate is increased, which may explain their greater contribution to localised thrombosis in arterioles compared to venules within in vivo models. Since shear increases substantially near sites of stenosis, anti-P2X1 therapy represents a potential means of reducing thrombotic events at atherosclerotic plaques