5 resultados para Polynomial differential systems

em DigitalCommons@The Texas Medical Center


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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

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Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

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There have been multiple reports which indicate that variations in $\beta$AR expression affect the V$\sb{\rm max}$ observed for the agonist-dependent activation of adenylylcyclase. This observation has been ignored by most researchers when V$\sb{\rm max}$ values obtained for wild type and mutant receptors are compared. Such an imprecise analysis may lead to erroneous conclusions concerning the ability of a receptor to activate adenylylcyclase. Equations were derived from the Cassel-Selinger model of GTPase activity and Tolkovsky and Levitzki's Collision Coupling model which predict that the EC$\sb{50}$ and V$\sb{\rm max}$ for the activation of adenylylcyclase are a function of receptor number. Experimental results for L cell clones in which either hamster or human $\beta$AR were transfected at varying levels showed that EC$\sb{50}$ decreases and V$\sb{\rm max}$ increases as receptor number increases. Comparison of these results with simulations obtained from the equations describing EC$\sb{50}$ and V$\sb{\rm max}$ showed a close correlation. This documents that the kinetic parameters of adenylylcyclase activation change with the level of receptor expression and relates this phenomenon to a theoretical framework concerning the mechanisms involved in $\beta$AR signal transduction.^ One of the terms used in the equations which expressed the EC$\sb{50}$ and V$\sb{\rm max}$ as a function of receptor number is coupling efficiency, defined as $\rm k\sb1/k\sb{-1}$. Calculation of $\rm k\sb1/k\sb{-1}$ can be accomplished for wild type receptors with the easily measured experimental values of agonist K$\sb{\rm d}$, EC$\sb{50}$ and receptor number. This was demonstrated for hamster $\beta$AR which yielded a coupling efficiency of 0.15 $\pm$ 0.003 and human $\beta$AR which yielded a coupling efficiency of 0.90 $\pm$ 0.031. $\rm k\sb1/k\sb{-1}$ replaces the traditional qualitative evaluation of the ability to activate adenylylcyclase, which utilizes V$\sb{\rm max}$ without correction for variation in receptor number, with a quantitative definition that more accurately describes the ability of $\beta$AR to couple to G$\sb{\rm s}$.^ The equations which express the EC$\sb{50}$ and V$\sb{\rm max}$ for adenylylcyclase activation as a function of receptor number and coupling efficiency were tested to determine whether they could accurately simulate the changes seen in these parameters during desensitization. Data from original desensitization experiments and data from the literature (24,25,52,54,83) were compared to simulated changes in EC$\sb{50}$ and V$\sb{\rm max}$. In a variety of systems the predictions of the equations were consistent with the changes observed in EC$\sb{50}$ and V$\sb{\rm max}$. In addition reductions in the calculated value of $\rm k\sb1/k\sb{-1}$ was shown to correlate well with $\beta$AR phosphorylation and to be minimally affected by sequestration and down-regulation. ^

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The ability to regulate cell cycle progression is one of the differences that separates normal from tumor cells. A protein, which is frequently mutated or deleted in a majority of tumor cells, is the retinoblastoma protein (pRb). Previously, we reported that normal cells, which have a wild-type Rb pathway, can be reversibly arrested in the G1 phase of the cell cycle by staurosporine (ST), while tumor cells were unaffected by this treatment. As a result, ST may be used to protect normal cells against the toxic affects of chemotherapy. Here we set out to determine the mechanism(s) by which ST can mediate a reversible G1 arrest in pRb positive cells. To this end, we used an isogenic cell model system of normal human mammary epithelial cells (HMEC) with either intact pRb+ (p53-) or p53+ (pRb-) treated with ST. Our results show that pRb+ cells treated with low concentrations of ST, arrested in the G1 phase of the cell cycle; however, in pRb - cells there was no response. This was verified as a true G 1 arrest in pRb+ cells by two different methods for monitoring cell cycle kinetics and in two additional model systems for Rb (i.e. pRb -/- mouse embryo fibroblasts, and downregulation of RB with siRNA). Our results indicated that ST-mediated G1 arrest required pRb, which in turn initiated a cascade of events leading to inhibition of CDK4 and CDK2 activities and up-regulation of p21 protein. Further assessment of this pathway revealed the novel finding that Chk1 expression and activity were required for the Rb-dependent, ST-mediated G1 arrest. In fact, overexpression of Chk1 facilitated recovery from ST-mediated G1 arrest, an effect only observed in RB+ cells. Collectively, our data suggest pRb is able to cooperate with Chk1 to mediate a G1 arrest in pRb+ cells, but not in pRb- cells. The elucidation of this pathway can help identify novel agents that can be used to protect cancer patients against the debilitating affects of chemotherapy, by targeting only the normal proliferating cells in the body that are otherwise destroyed. ^

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Despite having been identified over thirty years ago and definitively established as having a critical role in driving tumor growth and predicting for resistance to therapy, the KRAS oncogene remains a target in cancer for which there is no effective treatment. KRas is activated b y mutations at a few sites, primarily amino acid substitutions at codon 12 which promote a constitutively active state. I have found that different amino acid substitutions at codon 12 can activate different KRas downstream signaling pathways, determine clonogenic growth potential and determine patient response to molecularly targeted therapies. Computer modeling of the KRas structure shows that different amino acids substituted at the codon 12 position influences how KRas interacts with its effecters. In the absence of a direct inhibitor of mutant KRas several agents have recently entered clinical trials alone and in combination directly targeting two of the common downstream effecter pathways of KRas, namely the Mapk pathway and the Akt pathway. These inhibitors were evaluated for efficacy against different KRAS activating mutations. An isogenic panel of colorectal cells with wild type KRas replaced with KRas G12C, G12D, or G12V at the endogenous loci differed in sensitivity to Mek and Akt inhibition. In contrast, screening was performed in a broad panel of lung cell lines alone and no correlation was seen between types of activating KRAS mutation due to concurrent oncogenic lesions. To find a new method to inhibit KRAS driven tumors, siRNA screens were performed in isogenic lines with and without active KRas. The knockdown of CNKSR1 (CNK1) showed selective growth inhibition in cells with an oncogenic KRAS. The deletion of CNK1 reduces expression of mitotic cell cycle proteins and arrests cells with active KRas in the G1 phase of the cell cycle similar to the deletion of an activated KRas regardless of activating substitution. CNK1 has a PH domain responsible for localizing it to membrane lipids making KRas potentially amenable to inhibition with small molecules. The work has identified a series of small molecules capable of binding to this PH domain and inhibiting CNK1 facilitated KRas signaling.