The lectin concanavalin-A signals MT1-MMP catalytic independent induction of COX-2 through an IKKγ/NF-κB-dependent pathway

The lectin from Canavalia ensiformis (Concanavalin-A, ConA), one of the most abundant lectins known, enables one to mimic biological lectin/carbohydrate interactions that regulate extracellular matrix protein recognition. As such, ConA is known to induce membrane type-1 matrix metalloproteinase (MT1-MMP) which expression is increased in brain cancer. Given that MT1-MMP correlated to high expression of cyclooxygenase (COX)-2 in gliomas with increasing histological grade, we specifically assessed the early proinflammatory cellular signaling processes triggered by ConA in the regulation of COX-2. We found that treatment with ConA or direct overexpression of a recombinant MT1-MMP resulted in the induction of COX-2 expression. This increase in COX-2 was correlated with a concomitant decrease in phosphorylated AKT suggestive of cell death induction, and was independent of MT1-MMP’s catalytic function. ConA- and MT1-MMP-mediated intracellular signaling of COX-2 was also confirmed in wild-type and in Nuclear Factor-kappaB (NF-κB) p65−/− mutant mouse embryonic fibroblasts (MEF), but was abrogated in NF-κB1 (p50)−/− and in I kappaB kinase (IKK) γ−/− mutant MEF cells. Collectively, our results highlight an IKK/NF-κB-dependent pathway linking MT1-MMP-mediated intracellular signaling to the induction of COX-2. That signaling pathway could account for the inflammatory balance responsible for the therapy resistance phenotype of glioblastoma cells, and prompts for the design of new therapeutic strategies that target cell surface carbohydrate structures and MT1-MMP-mediated signaling. Concise summary Concanavalin-A (ConA) mimics biological lectin/carbohydrate interactions that regulate the proinflammatory phenotype of cancer cells through yet undefined signaling. Here we highlight an IKK/NF-κB-dependent pathway linking MT1-MMP-mediated intracellular signaling to the induction of cyclooxygenase-2, and that could be responsible for the therapy resistance phenotype of glioblastoma cells

Cellular and Molecular Mechanisms Underlying the Strong Neonatal IL-12 Response of Lamb Mesenteric Lymph Node Cells to R-848

International audienceabsen

An Estimate of the Numbers and Density of Low-Energy Structures (or Decoys) in the Conformational Landscape of Proteins

The conformational energy landscape of a protein, as calculated by known potential energy functions, has several minima, and one of these corresponds to its native structure. It is however difficult to comprehensively estimate the actual numbers of low energy structures (or decoys), the relationships between them, and how the numbers scale with the size of the protein.We have developed an algorithm to rapidly and efficiently identify the low energy conformers of oligo peptides by using mutually orthogonal Latin squares to sample the potential energy hyper surface. Using this algorithm, and the ECEPP/3 potential function, we have made an exhaustive enumeration of the low-energy structures of peptides of different lengths, and have extrapolated these results to larger polypeptides.We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length. The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space. These results are consistent with earlier reports that were based on other models and techniques

Non-irradiation-derived reactive oxygen species (ROS) and cancer: therapeutic implications

Owing to their chemical reactivity, radicals have cytocidal properties. Destruction of cells by irradiation-induced radical formation is one of the most frequent interventions in cancer therapy. An alternative to irradiation-induced radical formation is in principle drug-induced formation of radicals, and the formation of toxic metabolites by enzyme catalysed reactions. Although these developments are currently still in their infancy, they nevertheless deserve consideration. There are now numerous examples known of conventional anti-cancer drugs that may at least in part exert cytotoxicity by induction of radical formation. Some drugs, such as arsenic trioxide and 2-methoxy-estradiol, were shown to induce programmed cell death due to radical formation. Enzyme-catalysed radical formation has the advantage that cytotoxic products are produced continuously over an extended period of time in the vicinity of tumour cells. Up to now the enzymatic formation of toxic metabolites has nearly exclusively been investigated using bovine serum amine oxidase (BSAO), and spermine as substrate. The metabolites of this reaction, hydrogen peroxide and aldehydes are cytotoxic. The combination of BSAO and spermine is not only able to prevent tumour cell growth, but prevents also tumour growth, particularly well if the enzyme has been conjugated with a biocompatible gel. Since the tumour cells release substrates of BSAO, the administration of spermine is not required. Combination with cytotoxic drugs, and elevation of temperature improves the cytocidal effect of spermine metabolites. The fact that multidrug resistant cells are more sensitive to spermine metabolites than their wild type counterparts makes this new approach especially attractive, since the development of multidrug resistance is one of the major problems of conventional cancer therapy

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

méthodologie basée sur les mesures de dépendance HSIC pour l'analyse de sensibilité de second niveau

International audienceWe are interested in the sensitivity analysis of numerical simulators in the case where the probability distributions of the uncertain input variables are themselves (even partially) unknown. The objective is to quantify the impact of these uncertainties on the sensitivity analysis results. To achieve it, we propose a single Monte Carlo loop methodology based on Hilbert-Schmidt dependence measures and importance sampling techniques. This approach significantly limits the number of simulator evaluations. A numerical application is proposed to illustrate the whole methodology, while comparing its different options.Nous nous intéressons à l'analyse de sensibilité des simulateurs numériques dans le cas où les distributions de probabilités des variables d'entrées incertaines sont elles-mêmes méconnues. L'objectif est de quantifier l'impact de ces incertitudes sur les résultats de l'analyse de sensibilité. Pour cela, on propose une méthodologie de type simple boucle Monte-Carlo basée sur les mesures de dépendance de Hilbert-Schmidt et inspirée des techniques de tirage d'importance, cette approche permettant de limiter significativement le nombre d'évaluations du simulateur. Une application numérique est proposée pour illustrer l'ensemble de la méthodologie et tester ses différentes options

New statistical methodology for second-level global sensitivity analysis of numerical simulators

International audienceGlobal sensitivity analysis (GSA) of numerical simulators aims at studying the global impact of the input uncertainties on the output. To perform the GSA, statistical tools based on inputsoutput dependence measures are commonly used. We focus here on dependence measures based on reproducing kernel Hilbert spaces the Hilbert-Schmidt Independence Criterion denoted HSIC. Sometimes, the probability distributions modeling the uncertainty of inputs may be themselves uncertain and it is important to quantify the global impact of this uncertainty on GSA results. We call it here the second-level global sensitivity analysis (GSA2). However, GSA2, when performed with a double Monte Carlo loop, requires a large number of model evaluations which is intractable with CPU time expensive simulators. To cope with this limitation, we propose a new statistical methodology based on a single Monte Carlo loop with a limited calculation budget. Firstly, we build a unique sample of inputs from a well chosen probability distribution and the associated code outputs are computed. From this inputsoutput sample, we perform GSA for various assumed probability distributions of inputs by using weighted HSIC measures estimators. Statistical properties of these weighted estimators are demonstrated. Finally, we define 2nd-level HSIC-based measures between the probability distributions of inputs and GSA results, which constitute GSA2 indices. The efficiency of our GSA2 methodology is illustrated on an analytical example, thereby comparing several technical options. Finally, an application to a test case simulating a severe accidental scenario on nuclear reactor is provided