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ABSTRACT: National Kidney Foundation's Kidney Disease Outcome Quality Initiative (KDOQI) guidelines offer an outline for providing standardized care for best outcomes in chronic kidney disease (CKD). It is unknown whether real-world treatment practices follow these guidelines.
The Hectorol Registry Outcome in Chronic Kidney Disease (HeROICkd), an observational patient registry, captured information on adult patients with CKD Stage 3 or 4 throughout US clinics during a 9-month observation period. Data were collected quarterly from patients' medical records, throughout each patient's normal treatment course. The proportion of patients with intact parathyroid hormone (iPTH) levels within KDOQI guidelines, change in iPTH, Ca, P, and Ca x P product over the 9-month observation period, incidence of hypercalcemia and hyperphosphatemia, and predictors of change in iPTH were examined.
1,339 CKD Stage 3 and 4 patients from 78 nephrology and internal medicine clinics were included. 40% of CKD Stage 3 participants and 45% of Stage 4 had a 30% or greater reduction in iPTH levels from baseline to 9 months follow-up. While the proportion of CKD Stage 3 and 4 participants with iPTH levels within the KDOQI recommendations improved significantly over the 9 months, it was still modest, at 28% and 23%, respectively. Mean doxercalciferol dose was below that recommended in the package insert and a minority of patients had all mineral metabolism parameters (iPTH, Ca, P) regularly recorded in their medical records.
The results of this registry, which examined iPTH treatment with doxercalciferol in CKD Stage 3 and 4, suggest that in the real-world treatment setting, the adherence to KDOQI guidelines is not optimal.
American Journal of Nephrology 09/2008; 29(2):71-8. · 2.54 Impact Factor
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ABSTRACT: Small-molecule kinase inhibitors often modulate signaling pathways other than the one targeted, whether by direct "off-target" effects or by indirect "pathway cross-talk" effects. The presence of either or both of these classes of complicating factors impedes the predictive understanding of kinase inhibitor consequences for cell phenotypic behaviors involved in drug efficacy responses. To address this problem, we offer an avenue toward comprehending how kinase inhibitor modulations of cell signaling networks lead to altered cell phenotypic responses by applying a quantitative, multipathway computational modeling approach. We show that integrating measurements of signals across three key kinase pathways involved in regulating migration of human mammary epithelial cells, downstream of ErbB system receptor activation by epidermal growth factor (EGF) or heregulin (HRG), significantly improves prediction of cell migration changes resulting from treatment with the small-molecule inhibitors 2-(4-morpholinyl)-8-phenyl-4H-1-benzopyran-4-one (LY294002) and 2'-amino-3'-methoxyflavone (PD98059) for both normal and HER2-overexpressing cells. These inhibitors are primarily directed toward inhibition of phosphatidylinositol 3-kinase (PI3K) and mitogen-activated protein kinase kinase (MEK) but are known to exhibit off-target effects; moreover, complex cross-talk interactions between the PI3K/Akt and MEK/extracellular signal-regulated kinase (Erk) pathways are also appreciated. We observe here that treatment with LY294002 reduces migration of HRG-stimulated cells but not EGF-stimulated cells, despite comparable levels of reduction of Akt phosphorylation under both conditions, demonstrating that the target inhibition effect is not unilaterally predictive of efficacy against cell phenotypic response. Consequent measurement of levels of Erk and p38 phosphorylation, along with those for EGF receptor phosphorylation, after LY294002 treatment revealed unintended modulation of these nontargeted pathways. However, when these measurements were incorporated into a partial least-squares regression model, the cell migration responses to treatment were successfully predicted. Similar success was found for the same multipathway model in analogously predicting PD98059 treatment effects on cell migration. We conclude that a quantitative, multipathway modeling approach can provide a significant advance toward comprehending kinase inhibitor efficacy in the face of off-target and pathway cross-talk effects.
Molecular pharmacology 07/2008; 73(6):1668-78. · 4.53 Impact Factor
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ABSTRACT: The protein kinase Akt is a critical regulator of cell function and its overexpression and activation have been functionally linked to numerous pathologies such as cancer. Previous reports regarding the mechanism-regulating Akt's activation have revealed two phosphorylation events, at threonine 308 (T308) and serine 473 (S473), as necessary for the full activation of the kinase in response to insulin. For this reason and because of the availability of phospho-specific antibodies to both T308 and S473, many studies that focus on Akt's role in governing cell function rely on the measurement of these two sites to understand changes in kinase activity. Recent evidence, however, suggests the involvement of other phosphorylation sites; for example, in Src-transformed and epidermal growth factor (EGF)-treated cells, tyrosine phosphorylation has been found important for full kinase activation. In this study, we probed the quantitative reliability of using S473 and/or T308 phosphorylation as surrogates for Akt kinase activity across diverse treatment conditions. We performed quantitative Western blots and kinase activity assays on lysates generated during a 2h time course from two cell lines treated with either EGF or insulin. From the resulting approximately 250 quantitative measurements of phosphorylation and activity, we found that both T308 and S473 phosphorylation accurately captured quantitative changes in EGF-stimulated cells, but not in insulin-stimulated cells. Moreover, in all but one condition studied, we found a tight correlation between the onset of phosphorylation and dephosphorylation for both sites, despite the fact that they do not share common kinase- or phosphatase-mediated regulation. In sum, using a quantitative approach to study Akt activation identified ligand-dependent limits for the use of T308 or S473 as proxies for kinase activity and suggests the coregulation of Akt phosphorylation and dephosphorylation.
Biochemical and Biophysical Research Communications 04/2007; 354(1):14-20. · 2.48 Impact Factor
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ABSTRACT: Cellular behavior in response to stimulatory cues is governed by information encoded within a complex intracellular signaling network. An understanding of how phenotype is determined requires the distributed characterization of signaling processes (e.g., phosphorylation states and kinase activities) in parallel with measures of resulting cell function. We previously applied quantitative mass spectrometry methods to characterize the dynamics of tyrosine phosphorylation in human mammary epithelial cells with varying human epidermal growth factor receptor 2 (HER2) expression levels after treatment with epidermal growth factor (EGF) or heregulin (HRG). We sought to identify potential mechanisms by which changes in tyrosine phosphorylation govern changes in cell migration or proliferation, two behaviors that we measured in the same cell system. Here, we describe the use of a computational linear mapping technique, partial least squares regression (PLSR), to detail and characterize signaling mechanisms responsible for HER2-mediated effects on migration and proliferation. PLSR model analysis via principal component inner products identified phosphotyrosine signals most strongly associated with control of migration and proliferation, as HER2 expression or ligand treatment were individually varied. Inspection of these signals revealed both previously identified and novel pathways that correlate with cell behavior. Furthermore, we isolated elements of the signaling network that differentially give rise to migration and proliferation. Finally, model analysis identified nine especially informative phosphorylation sites on six proteins that recapitulated the predictive capability of the full model. A model based on these nine sites and trained solely on data from a low HER2-expressing cell line a priori predicted migration and proliferation in a HER2-overexpressing cell line. We identify the nine signals as a "network gauge," meaning that when interrogated together and integrated according to the quantitative rules of the model, these signals capture information content in the network sufficiently to predict cell migration and proliferation under diverse ligand treatments and receptor expression levels. Examination of the network gauge in the context of previous literature indicates that endocytosis and activation of phosphoinositide 3-kinase (PI3K)-mediated pathways together represent particularly strong loci for the integration of the multiple pathways mediating HER2's control of mammary epithelial cell proliferation and migration. Thus, a PLSR modeling approach reveals critical signaling processes regulating HER2-mediated cell behavior.
PLoS Computational Biology 02/2007; 3(1):e4. · 5.22 Impact Factor
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ABSTRACT: Computational models of cells, tissues and organisms are necessary for increased understanding of biological systems. In particular, modeling approaches will be crucial for moving biology from a descriptive to a predictive science. Pharmaceutical companies identify molecular interventions that they predict will lead to therapies at the organism level, suggesting that computational biology can play a key role in the pharmaceutical industry. We discuss pharmaceutically-relevant computational modeling approaches currently used as predictive tools. Specific examples demonstrate how companies can employ these computational models to improve the efficiency of transforming targets into therapies.
Drug Discovery Today 10/2006; 11(17-18):806-11. · 6.83 Impact Factor
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ABSTRACT: Human epidermal growth factor receptor 2 (HER2) overexpression has been associated with increased invasiveness in mammalian breast cancer cell lines, but the effects of overexpression on key underlying cell migration properties such as translational speed and directional persistence are not understood. Moreover, the differential effect of HER2 activation through heterodimerization with epidermal growth factor receptor versus human epidermal growth factor receptor 3 (HER3) on cell speed and persistence has not been studied. To investigate these issues, we developed a high-throughput wound closure assay in which individual cell locomotion and wound closure kinetics were quantified in human mammary epithelial cells with varying levels of HER2 under epidermal growth factor or heregulin (a HER3 ligand) stimulation. Increasing levels of HER2 elevated wound closure with closure kinetics dependent on ligand treatment. Cell speed increased with HER2 levels under epidermal growth factor treatment, but decreased under heregulin treatment. In contrast, directional persistence increased with HER2 levels under both ligand treatments. Increasing persistence quantitatively accounted for observed elevated wound closure, as measured by the effective diffusion of the cells. Taken together, the data show that the HER2 overexpression mediates cell migration through differential control of translational speed and directional persistence dependent on epidermal growth factor receptor-HER2 versus HER2-HER3 heterodimerization. Observed consistent increases in persistence associated with HER2 overexpression indicate a prospective mechanism for invasiveness previously documented in HER2-overexpressing human breast tumors.
Biophysical Journal 09/2006; 91(4):L32-4. · 3.65 Impact Factor
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ABSTRACT: Although human epidermal growth factor receptor 2 (HER2) overexpression is implicated in tumor progression for a variety of cancer types, how it dysregulates signaling networks governing cell behavioral functions is poorly understood. To address this problem, we use quantitative mass spectrometry to analyze dynamic effects of HER2 overexpression on phosphotyrosine signaling in human mammary epithelial cells stimulated by epidermal growth factor (EGF) or heregulin (HRG). Data generated from this analysis reveal that EGF stimulation of HER2-overexpressing cells activates multiple signaling pathways to stimulate migration, whereas HRG stimulation of these cells results in amplification of a specific subset of the migration signaling network. Self-organizing map analysis of the phosphoproteomic data set permitted elucidation of network modules differentially regulated in HER2-overexpressing cells in comparison with parental cells for EGF and HRG treatment. Partial least-squares regression analysis of the same data set identified quantitative combinations of signals within the networks that strongly correlate with cell proliferation and migration measured under the same battery of conditions. Combining these modeling approaches enabled association of epidermal growth factor receptor family dimerization to activation of specific phosphorylation sites, which appear to most critically regulate proliferation and/or migration.
Molecular Systems Biology 02/2006; 2:54. · 8.63 Impact Factor
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Neil Kumar
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ABSTRACT: Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, February 2007. Includes bibliographical references. The fundamental question posed in this thesis is: how does a cell 'decide' to behave in a particular way? The human body is comprised of [approx.] 1014 cells that interpret extracellular information and respond with such behavior as migration, proliferation, apoptosis, or differentiation. Thirty years of research in the related fields of biochemistry, molecular biology, and genetics have demonstrated that, in most cases, the cellular decision-making process cannot be described or predicted by regulation of only one gene or one protein alone. Instead, it has become clear that cellular behavior is a function of information flow through multiple intracellular molecules. Furthermore, the molecules responsible for the control of cell behavior comprise a surprisingly short list, indicating that factors such as signaling dynamics and intensity coupled with combinatorial control are essential to produce the wide array of observed cell behavior. The identification of protein kinases as transducers of large amounts of intracellular information led us to pose the hypothesis that the quantitative regulation of key kinases governs cellular behavior. The goal of this thesis was to identify rules governing multi-kinase behavioral control and to then, on the basis of these rules, predict changes in cell function in response to changes in receptor expression, ligand treatment, and pharmacological intervention. (cont.) A human mammary epithelial cell (HMEC) system with varying levels of the human epidermal growth factor receptor 2 (HER2) was chosen to explore cell decision processes. HER2 overexpression is found in 30% of breast cancers and correlates with poor prognosis and increased metastasis. In particular, we investigated the effects of HER2 overexpression on signaling networks and resultant cell proliferation and migration in the presence of epidermal growth factor (EGF) or heregulin (HRG), two EGFR-family ligands that promote HER2 heterodimerization. To investigate HER2-mediated signaling and cell behavior we developed and applied high-throughput experimental techniques to measure kinase activity and phosphorylation as well as cell proliferation and migration. Measurement of -~100 different kinases downstream of HER2 resulted in the identification of network signaling mechanisms. Application of a novel high-throughput migration assay enabled the identification of HER2-mediated increases in cell migration due to increases in the directional persistence of movement. Linear mapping techniques related to partial least squares regression (PLSR) defined and predicted cell behavior in response to HER2 overexpression. (cont.) Combining quantitative datasets of both biological signals and behavior using PLSR, we identified subsets of kinase phosphorylation events that most critically regulate HER2-mediated migration and proliferation. Importantly, we demonstrated that our models provide predictive ability through a priori predictions of cell behavior in HER2-overexpressing cells. Application of linear models in response to pharmacological inhibition resulted in the a priori prediction of cell migration, and identified an EGFR kinase inhibitor Gefitinib as a potent inhibitor of HER2-mediated migration. In conclusion, the application of computational linear modeling to quantitative biological signaling and behavior datasets captured systems-level regulation of cell behavior and, based on this, predicted cell migration and proliferation in response to HER2 overexpression and pharmacological inhibition. Further application of quantitative measurement together with linear modeling should enable the identification of salient cell signal-cell response elements to understand how cells make decisions and to predict how those decisions can be therapeutically manipulated. by Neil Kumar. Ph.D.
