966 resultados para BIOLOGICAL PATHWAYS


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Once melanoma metastasizes, no effective treatment modalities prolong survival in most patients. This notorious refractoriness to therapy challenges investigators to identify agents that overcome melanoma resistance to apoptosis. Whereas many survival pathways contribute to the death-defying phenotype in melanoma, a defect in apoptotic machinery previously highlighted inactivation of Apaf-1, an apoptosome component engaged after mitochondrial damage. During studies involving Notch signaling in melanoma, we observed a gamma-secretase tripeptide inhibitor (GSI; z-Leu-Leu-Nle-CHO), selected from a group of compounds originally used in Alzheimer's disease, induced apoptosis in nine of nine melanoma lines. GSI only induced G2-M growth arrest (but not killing) in five of five normal melanocyte cultures tested. Effective killing of melanoma cells by GSI involved new protein synthesis and a mitochondrial-based pathway mediated by up-regulation of BH3-only members (Bim and NOXA). p53 activation was not necessary for up-regulation of NOXA in melanoma cells. Blocking GSI-induced NOXA using an antisense (but not control) oligonucleotide significantly reduced the apoptotic response. GSI also killed melanoma cell lines with low Apaf-1 levels. We conclude that GSI is highly effective in killing melanoma cells while sparing normal melanocytes. Direct enhancement of BH3-only proteins executes an apoptotic program overcoming resistance of this lethal tumor. Identification of a p53-independent apoptotic pathway in melanoma cells, including cells with low Apaf-1, bypasses an impediment to current cytotoxic therapy and provides new targets for future therapeutic trials involving chemoresistant tumors.

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Notch receptor-mediated intracellular events represent an ancient cell signaling system, and alterations in Notch expression are associated with various malignancies in which Notch may function as an oncogene or less commonly as a tumor suppressor. Notch signaling regulates cell fate decisions in the epidermis, including influencing stem cell dynamics and growth/differentiation control of cells in skin. Because of increasing evidence that the Notch signaling network is deregulated in human malignancies, Notch receptors have become attractive targets for selective killing of malignant cells. Compared with proliferating normal human melanocytes, melanoma cell lines are characterized by markedly enhanced levels of activated Notch-1 receptor. By using a small molecule gamma-secretase inhibitor (GSI) consisting of a tripeptide aldehyde, N-benzyloxycarbonyl-Leu-Leu-Nle-CHO, which can block processing and activation of all four different Notch receptors, we identified a specific apoptotic vulnerability in melanoma cells. GSI triggers apoptosis in melanoma cells, but only G2/M growth arrest in melanocytes without subsequent cell death. Moreover, GSI treatment induced a pro-apoptotic BH3-only protein, NOXA, in melanoma cells but not in normal melanocytes. The use of GSI to induce NOXA induction overcomes the apoptotic resistance of melanoma cells, which commonly express numerous cell survival proteins such as Mcl-1, Bcl-2, and survivin. Taken together, these results highlight the concept of synthetic lethality in which exposure to GSI, in combination with melanoma cells overexpressing activated Notch receptors, has lethal consequences, producing selective killing of melanoma cells, while sparing normal melanocytes. By identifying signaling pathways that contribute to the transformation of melanoma cells (e.g. Notch signaling), and anti-cancer agents that achieve tumor selectivity (e.g., GSI-induced NOXA), this experimental approach provides a useful framework for future therapeutic strategies in cutaneous oncology.

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Inverse problems based on using experimental data to estimate unknown parameters of a system often arise in biological and chaotic systems. In this paper, we consider parameter estimation in systems biology involving linear and non-linear complex dynamical models, including the Michaelis–Menten enzyme kinetic system, a dynamical model of competence induction in Bacillus subtilis bacteria and a model of feedback bypass in B. subtilis bacteria. We propose some novel techniques for inverse problems. Firstly, we establish an approximation of a non-linear differential algebraic equation that corresponds to the given biological systems. Secondly, we use the Picard contraction mapping, collage methods and numerical integration techniques to convert the parameter estimation into a minimization problem of the parameters. We propose two optimization techniques: a grid approximation method and a modified hybrid Nelder–Mead simplex search and particle swarm optimization (MH-NMSS-PSO) for non-linear parameter estimation. The two techniques are used for parameter estimation in a model of competence induction in B. subtilis bacteria with noisy data. The MH-NMSS-PSO scheme is applied to a dynamical model of competence induction in B. subtilis bacteria based on experimental data and the model for feedback bypass. Numerical results demonstrate the effectiveness of our approach.

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This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).