Pure Sciences

Pure Sciences Paper For Sale

Investigating tumor suppressor genes involved in renal cell carcinomas

Kidney cancer is a complex disease comprising several types of renal carcinomas, which are classified in different subtypes based on their histological characteristics. A small number of cases of renal cancers are due to hereditary predispositions and nearly all the knowledge on the molecular pathogenesis of kidney cancers was learned by the investigation of these hereditary forms of renal carcinomas. In this thesis, we studied two hereditary diseases predisposing to the development of kidney cancer, von Hippel Lindau (VHL) and Birt-Hogg-Dube (BHD) syndromes, and their causative genes, VHL and FLCN respectively. First, we investigated the role of the extracellular matrix (ECM) regulation by VHL during tumorigenesis and angiogenesis, and we demonstrated that inactivation of the VHL-ECM assembly pathway results in highly vascularized tumors with a disrupted ECM. We concluded that loss of the ECM assembly promotes and maintains tumor angiogenesis by providing a way for new blood vessels to invade the tumor tissue. In the second part of this thesis, we developed a novel VHL mouse model to investigate the possible cooperation between VHL and p53 during tumorigenesis. We observed that inactivation of both tumor suppressor genes accelerate the formation of liver hemangiomas and splenic hemangiosarcomas. Furthermore, concomitant deletion of VHL and p53 abolished the development of lymphoma usually associated with loss of p53. Our results indicate that the phenotypes arising following the inactivation of VHL and p53 is organ-dependent. Finally, to study the pathogenesis of the BHD syndrome, we developed a new mouse model using an established embryonic stem cell line. We described the murine Flcn expression pattern and noticed that homozygous disruption of Flcn was embryonically lethal early during development. Furthermore, we observed a continuum of kidney lesions from renal tubules hyperproliferation to rare adenoma. FLCN tumor suppressor role was also substantiated using a human kidney cancer cells system. Altogether, these studies have confirmed a role for the VHL-ECM pathway during tumor angiogenesis and have led to the development of two mouse models to study the molecular mechanisms linked to VHL and FLCN during the formation of various kidney tumors.

Perhaps You will be interested in these papers

Structural Characterization of Novel Antimicrobial Therapeutic Targets and Crystallographic Examination of Enzymes Involved in Xenobiotic Metabolism

Part I. Recently there has been an alarming rise in the number of infections due to pathogenic organisms that are insensitive to our current arsenal of pharmaceuticals, necessitating the identification of new antimicrobial targets. Here, we describe structural studies of two enzymes from the aspartate family of biosynthetic enzymes in order to assess their potential for drug targeting. Our first report details how an unlikely inhibitor with low millimolar binding characteristics, 5-hydroxy-4-oxo-norvaline, can effectively inactivate homoserine dehydrogenase HSD) through the formation of a tight-binding covalent adduct. This is followed by the structural characterization of the first phenolic-based non-amino acid inhibitor of HSD, which is shown to occupy the substrate binding site and make specific contacts with residues involved in catalysis. Together, these studies lay the foundation for further structure-based drug design of novel inhibitors of HSD. Following this, we report the first structure of the next enzyme in the aspartate pathway, homoserine transacetylase HTA). As the committal step in microbial methionine biosynthesis, this enzyme is essential to microbial survival. The high-resolution crystal structure identifies HTA as a new member of a larger structural family of enzymes known as the alpha/beta hydrolases. Using the structure as a guide, we propose a rationale for the previously reported ping-pong reaction mechanism for this enzyme. We conclude with a preliminary look into how the natural substrate, homoserine, binds in the active site and some subtle differences between HTAs from different sources. Part II. Microbes have long been admired for their ability to process virtually any chemical. In Part II of this work we will engage in the structural characterization of two enzymes involved in the microbial degradation of xenobiotic compounds. The first enzyme, cyclohexylamine oxidase CHAO), is the enabling step in the bacterial metabolism of cyclohexylamine. Preliminary crystallographic analysis of cofactor bound and ternary complexes of CHAO, will be used to highlight differences between this enzyme and its closest human homologue. This information will then be used to direct structure inspired mutagenesis studies in order to better understand the substrate specificity of this enzyme and how it might be altered. Finally, the last enzyme to be discussed in this work will be cyclohexanone monooxygenase CHMO). Also from the same biodegradation pathway as CHAO this enzyme is responsible for the stereo- and regio-specific conversion of small cyclic ketones into lactones. This reaction, known as the Baeyer-Villiger Oxidation, is of tremendous importance in the pharmaceutical industry as lactones often serve as the building blocks of other larger compounds. Surprisingly, despite many years of research there has never been a published report on the structure of this enzyme. We detail here, for the first time, the crystallographic structure of CHMO in multiple conformations. Together, the various structures of CHAO and CHMO presented will provide insight into how bacteria are able to process xenobiotics and how we might use this information for structure based protein design.

Perhaps You will be interested in these papers

Host-pathogen interactions: The NLR protein Naip5 and susceptibility to Legionella pneumophila

The innate immune system uses pathogen recognition receptors (PRRs) that recognize conserved microbial structures called pathogen-associated molecular patterns (PAMPs). PRRs include the membrane-associated Toll-like receptors (TLRs) family and the intracellular cytosolic sensors: retinoic acid inducible gene I (RIG-I)-like receptors (RLRs), the IFN-inducible double-stranded RNA (dsRNA)-dependent protein kinase (PKR), DNA-dependent activator of IRFs (DAI), and nucleotide-binding oligomerization domain (Nod)-like receptors (NLRs). One of these NLR proteins, the Neuronal Apoptosis Inhibitory Protein 5 (Naip5), has been first identified as a locus controlling susceptibility to Legionella pneumophila in mice. The work described in this thesis covers three aspects of host-pathogen interaction study based on Naip5/Legionella model: (1) Morphological and biochemical characterization of Legionella–containing phagosomes in Naip5 transgenic and non transgenic murine macrophages by fluorescence and electron microscopy; (2) Identification of the transcriptional regulators Irf1 and Irf8 as essential for restriction of Legionella pneumophila replication in macrophages in addition to the Nod-Like receptors Naip5 and Nlrc4; (3) Analysis of global cellular changes induced by Legionella pneumophila infection of bone marrow-derived macrophages at the transcriptional level and the protein expression and phosphorylation level.

Perhaps You will be interested in these papers

Integrative computational analysis of micro RNA and mRNA expression profiles in human cancer

Mature microRNAs miRNAs) are short 19-24 nt), non-protein-coding ribonucleic acids that play very important roles in the regulation of gene expression in animals and plants. miRNAs mainly bind to the 3 untranslated regions of target mRNAs to cause translational blockade or transcript degradation. Although miRNAs have been implicated in growing number of diseases, their protein targets and the specific biological functions of these targets remain largely unknown. Computational prediction of miRNA targets provides an alternative approach to assign biological functions. Although the experimental validation of miRNA target genes increases dramatically, majority of miRNA targets are still unknown and bioinformatic algorithms remain the key means of predicting putative miRNA targets. The principles of miRNA target predictions are based on sequence complementary, conservation across species, thermodynamic stability, site accessibility and inverse relationship between the expression profiles of miRNAs and predicted target mRNAs. Here we use partial least square PLS) and sparse partial least square SPLS) methods to predict miRNA targets from miRNA and mRNA microarray data. Based on the inverse relationship between miRNA and mRNA, we selected two sets of differentially expressed miRNAs and mRNAs from human colon cancer microarray data. The first set consisted of 71 upregulated mRNAs and 31 downregulated miRNAs and the second set consisted of 56 downregulated mRNAs and 2 upregulated miRNAs. Using PLS and SPLS methods, we detected significant inverse interactions/associations between miRNA and mRNA. Then we compared these miRNA target genes with the four other widely used miRNA target prediction programs: TargetScan 5.1, PicTar, miRanda and miRBase. We identified a set of miRNA targets predicted by PLS and/or Sparse PLS that were also predicted by TargetScan5.1, PicTar, miRanda and miRBase through union of them or intersection combinations. We also used our predicted miRNA target genes to explore miRNA-mediated biological networks or pathways in human cancer.

Perhaps You will be interested in these papers

Regression methods of time-dependent ROC curve for evaluating the prognosis capacity of biomarkers

Receiver operating characteristic (ROC) curves are commonly used for visualizing sensitivity and specificity of a continuous biomarker or diagnostic test result, Y, for a binary disease outcome D. In practice, however, many disease outcomes depend on time. Therefore, it is appropriate to derive the corresponding time-dependent ROC curves. In this work. I first introduce a new semi-parametric regression approach for estimating the covariate adjusted time-dependent ROC curves by modeling time-dependent sensitivities, or true positive rates (TPRs), and time-dependent false positive rates (FPRs), based on a transformation model for the event time, T, and a semi-parametric location model for the biomarker, Y. I further discuss the new method according to whether the disease time, T, is subject to censoring. Different transformation model is used for the two situations. Since the transformation model does not place any assumptions on the distribution of an event time outcome, this approach can be applied to more general case and is more robust than previous semi-parametric methods. Numerical study was implemented for the heteroscedastic transformation model when the error term follows the standard extreme value distribution, the standard normal distribution and the logistic distribution. The results show that our estimator is unbiased and robust to mis-specification of the time-to-event model. The efficiency is comparable with the correctly specified model and much higher than the mis-specified model. The new method was applied to analyze data from HIVNET 012 randomized trial for evaluating the two biomarkers of predicting mother-to-infant transmission of HIV-1 virus, and to analyze data front VA lung cancer trial for evaluating the performance score of predicting the lung cancer event. The regression approach for censored disease time was applied to VA Lung Cancer Trial to evaluate biomarkers for predicting the mortality of the study subjects. The other regression approach I proposed is a directly modeling method for the time-dependent sensitivity (ROC curve) at a given specificity for biomarkers with repeated measurements. I show, in this work, that the direct time-dependent ROC model is equivalent to a transformation model with unknown transformation function and error distribution. The proposed semi-parametric ROC model have a good interpretation for its regression parameters and is relatively easy to implement. Numerical studies showed that the proposed estimator is unbiased when the biomakers data are completely balanced and is missing completely at random in a monotone pattern. The proposed ROC model and estimation procedure is demonstrated using VAX004 HIV-1 vaccine trial.

Perhaps You will be interested in these papers

Physico-chemical characterization of 10-hydroxycamptothecin and formulation approach towards improving its solution stability and solubility

Naturally occurring alkaloid, 10-hydroxy-camptothecin 10HC) is a promising structural derivative of camptothecin which possesses the ability to inhibit a wide range of human tumors. However, its anti-tumor potential has not been fully realized owing to the pH dependent hydrolytic instability and poor aqueous solubility. To obtain the kinetic and thermodynamic parameters of hydrolysis, a derivative spectrophotometric technique was used for the simultaneous estimation of lactone and carboxylate forms of 10HC. Validation of the analytical method was done with respect to reproducibility, % recovery, and level of detection. Hydrolysis of the lactone ring of 10HC followed a 1st order decay with a rate constant equal to 0.0281 +/- 0.001) min-1 in PBS at pH 7.4 and at a temperature of 37 °C. The activation energy for the hydrolysis reaction as calculated from the Arrhenius equation was 79.41 +/- 0.92) kJ mol -1, whereas the enthalpy and entropy of hydrolysis of 10-hydroxy-camptothecin were on average 12.45 kJ mol-1 and 52.37 J K-1 mol-1, respectively. The positive enthalpy and entropy values of the 10HC-lactone hydrolysis indicate that the reaction is endothermic and entropically driven. Physicochemical characterization was carried out to fully characterize the poor aqueous solubility and solid-state properties of 10-hydroxy-camptothecin 10HC). Molecular and system properties were determined from titration, partition and solubility studies using UV and fluorescence spectroscopy, while solid state characterization of the 10HC was carried out with x-ray, DSC and TGA. The enthalpies of solution of the unionized and ionized forms of 10HC, as deduced from isothermal and iso-pH equilibrium solubility measurements, were 45.4 kJ·mol-1 and 22.7 kJ·mol-1, respectively. The pKa of 10HC was determined to be 1.42 at 25 °C, while the basicity of the quinoline group of 10HC was shown to decrease with increasing temperature due to a positive enthalpy of deprotonation of 23.6 kJ.mol-1. The intrinsic partition coefficient of 10HC was determined to be 6.49, which is significantly smaller than that of the parent camptothecin. Evidently, the hydroxyl substitution on the A ring of camptothecin renders the molecule considerably more polar, though still hydrophobic and sparingly soluble in aqueous media. Dissolution studies supported by x-ray and thermal analysis revealed polymorphism and serious metastability of the 10HC anhydrous form in aqueous solutions. The aqueous solubility of 10HC-lactone monohydrate was found to be pH and temperature dependent with an estimated intrinsic solubility of 1.81 +/- 0.215 muM. Contrary to the low intrinsic solubility, the solubility of 10HC in extremely acidic media increased by more than 3 orders of magnitude. Furthermore, the purpose of the present work was to study the pH-solubilization behavior of 10HC, and to systematically discern the improved solubility and stability of 10-hydroxy-camptothecin in presence of pharmaceutically acceptable co-solvents and surfactants. Drug concentrations following equilibration of 10HC in various pH solutions and at different weight fractions of the cosolvents; PEG400, PEG1450, PEG6000, PEG8000, glycerol and propylene glycol and, surfactants; F-68, F127, Gelucire and Sodium Dodecyl Sulfate SDS) were determined using HPLC. The kinetic and thermodynamic parameters of hydrolysis were determined by monitoring the drug hydrolysis using a derivative spectroscopic method. Association of drug to micelles was studied using fluorescence anisotropic technique. Based on the pH-solubility profile, the pKa of the phenol group of 10HC was determined to be 7.6 +/- 0.023. The presence of 10HC-lactone at highly basic pH was attributed to the pseudo- equilibrium between the anionic 10HC-lactone and 10HC-carboxylate. An exponential and a linear increase in the solubility of 10HC was observed with increasing concentrations of the cosolvents and the surfactants, respectively, with PEG400 and SDS showing the maximum solubilization efficiency. Abstract shortened by UMI.)

Perhaps You will be interested in these papers

Expression and regulation of vasoactive intestinal peptide receptors in murine T lymphocytes

The immune system is tightly regulated in order to balance host protection and autoimmunity. Two G-protein coupled receptors that assist in immune regulation and are expressed in both thymocytes and peripheral T cells are termed vasoactive intestinal peptide receptor 1 (VPAC1) and VPAC2. Both receptors have a common ligand, vasoactive intestinal peptide (VIP), which evokes intracellular signaling to modulate numerous functions including proliferation and trafficking. However, the expression profile and regulatory mechanisms of these receptors have not been mapped throughout thymocyte development or during the T cell immune response. Gaining knowledge of VIP receptor’s T cell expression profile will be critical in understanding how this signaling axis mediates immune protection. We hypothesized that VPAC1:VPAC2 expression ratios would be adjusted during high bursts of proliferation in thymocyte development stages and immune response phases. We demonstrated that the VPAC1:VPAC2 ratio was low during early double negative (DN) 1, 2, and 3 thymocyte development stages. At latter stages of development (DN4), there was a receptor switch to a high VPAC1:VPAC2 ratio, which remained into mature, peripheral T cells. During an immune T cell response, we demonstrated that VPAC2 expression was undetected, while VPAC1 expression was downregulated 163-fold during expansion, was restored during contraction and into the memory phase. After re-challenge, VPAC1 was downregulated five-fold in expanding memory T cells and remained at this decreased expression level in secondary memory cells. We also explored the signaling pathway regulation controlling VPAC1 expression in activated T cells and discovered that osmotic stress alters VPAC1 and VPAC2 expression in T cells. Regarding the signaling mechanism, after T cell activation, VPAC1 downregulation was through a Fyn/Lck3 → Zap70 → JNK signaling pathway. With respect to osmolarity, VPAC1 was indirectly proportional, while VPAC2 was directly proportional to osmolarity changes. Overall, VPAC1 and 2 receptors function in directing progression of T cells through thymocyte development and T cell homeostasis. Additionally, we determined that VPAC1 regulation in T cells is controlled by T cell receptor engagement and signaling through JNK, as well as changes in osmolarity. These findings suggest strong roles for these two GPCRs in maintaining a tightly regulated immune system network.

Perhaps You will be interested in these papers

Improved generalized estimating equations for incomplete longitudinal binary data, covariance estimation in small samples, and ordinal data

The focus of this research is to improve existing methods for the marginal modeling of associated categorical outcomes. Generalized estimating equations, based on quasilikelihood, is in wide use to make inference on marginal mean parameters, especially for categorical data. In the case that response data are not all observed, generalized estimating equations give inconsistent parameter estimates when missingness depends on observed or unobserved outcomes. Inverse-probability weighted generalized estimating equations give valid results if missingness depends only on observed outcomes, and a missingness model is correctly specified. For our first topic we propose specific forms of semi-parametric efficient estimators in marginal models when dropouts for longitudinal binary data are missing at random. The efficiency of inverse-probability weighted generalized estimating equations is also explored in this setting. The other specific topics of concern in this research are related to extensions of generalized estimating equations that allow for modeling associations between categorical outcomes. Although associations are often considered nuisances, it is not uncommon that they are scientifically relevant. It may be of interest in this case to model associations on covariates defined by characteristics of clusters or outcome pairs. Alternating logistic regressions model marginal means of correlated binary outcomes while simultaneously allowing for an association model that parameterizes the odds ratio for outcome pairs. Our second topic concerns point and variance estimation of association parameters for finite samples. Bias adjustments in estimating outcome variance have recently been introduced for small samples in generalized estimating equations. We propose an extension of these adjustments to odds ratio parameters in alternating logistic regressions. The remaining topic of our research concerns generalized estimating equations for ordinal data, for which alternating logistic regressions has recently been adapted. An alternate formulation of alternating logistic regressions based on orthogonalized residuals has been introduced for binary data resolving some problems in the existing procedure, including lack of invariance of the variance estimator to observation order. In our final topic we define this alternate formulation of alternating logistic regressions for correlated ordinal data, and examine its efficiency with regards to estimating within-cluster association parameters.

Perhaps You will be interested in these papers

Antibody carriers of CpG oligodeoxynucleotides for solid tumor immunotherapy

The use of CpG oligodeoxynucleotide ODN) TLR9 agonists for oncology therapy has been primarily limited to its use as an adjuvant in combination therapies. Successful anti-cancer therapy has been limited to the intratumoral and peritumoral routes of administration. Subcutaneous SC) administration has showed promise, but results have been modest at best. For cancer monotherapy with CpG, we developed a delivery system utilizing an endogenous antibody as a carrier for CpG ODNs. Our system first involves conjugation of a small molecule 2,4-dinitrophenyl DNP) hapten to CpG. Next, we immunize mice against the hapten such that a high titer of anti-DNP antibodies is maintained in the systemic circulation. Upon injection of DNP-CpG, an immune complex will be formed. Subsequently, the immune complex will be taken up by dendritic cells for CpG processing by TLR9 endosomal receptors. This system was shown to be effective in tumor growth inhibition in our animal model upon intravenous IV) delivery of CpG ODNs, an administration route that has never shown to be effective. In the following investigations, we found that the SC route of administration exhibited great efficacy. Anti-tumor response was as good as IV delivery and showed an improvement over SC administration of underivatized CpG. Pharmacokinetic analysis suggests that increased half-life of CpG may play a role toward the therapeutic effect. In vitro studies suggest that our immune complex effectively activates dendritic cells and that this effect is possibly due to facilitated processing of the immune complexes via Fc receptor-mediated endocytosis and not due to the extent of CpG uptake. Based on collective results, we proposed mechanisms by which we were able to garner such a positive immunological response. Additional opportunities stemming from this work will certainly be of great value. The establishment of SC and IV formulations that exhibit desirable properties carries tremendous implications for the deliver of other therapeutic agents.

Perhaps You will be interested in these papers

Towards understanding the molecular details of beta-amyloid neurotoxicity in Alzheimer’s disease

Alzheimers disease AD) is the most common form of dementia. AD fatalities are constantly increasing, so are the financial costs associated with the disease. Despite significant scientific advancements during the last 20 years in understanding the disease, there are still no approved drugs available that slow or reverse AD progression. AD is thought be initiated by the accumulation of the beta-Amyloid Abeta) peptide in the brain, which aggregates extracellularly to form neurotoxic species. Abeta eventually forms insoluble fibrillar senile plaque, though certain forms of soluble aggregated oligomers are believed to be more toxic. One of the main barriers to curing AD is the lack of understanding of Abeta toxicity. Two critical issues in elucidating mechanism of Abeta toxicity are identifying the cellular damage induced by Abeta, and elucidating the surfaces or amino acids of Abeta that are key for the interaction with cells. In the work presented in this dissertation we attempted to answer the latter, and contributed new information to our molecular understanding of Abeta neurotoxicity. We have identified differences in the structure of Arg5 between Abeta fibrils and the toxic oligomers. This is one of only a few molecular differences identified so far between the less toxic fibrils and the highly toxic oligomers, thus we suggest that this region may be important for Abeta biological activity. We then showed that alterations of Abeta around Arg5 change the propensity of Abeta to bind to cells. In the following chapter, using a simplified diffusion-limited reaction model for the interaction of Abeta with cells, we demonstrated that differences in the toxicity of Abeta aggregates with different sizes can be explained, at least partially, based on the diffusivity and concentration of species. We then used a combination of computational and experimental tools, to elucidate the Abeta binding sites of known toxicity inhibitors as a means to indirectly identify loci on Abeta aggregates that may be important for Abeta neurotoxicity. Our data indicates that despite their structural differences, the inhibitors bind at two common loci on Abeta, near Lys28 and near the C-terminus. We then explored the possible role of Lys28 in Abeta cell binding. We also launched a structure-based virtual screening to discover novel small molecular weight inhibitors that can bind at the two loci identified, and potentially inhibit Abeta biological activity. The results of our work provide new information that contributes to our understanding of Abeta neurotoxicity, and provides a foundation for the development of novel therapies for AD.

Perhaps You will be interested in these papers