A Core Response to the CDX2 Homeoprotein During Development and in Pathologies

Whether a gene involved in distinct tissue or cell functions exerts a core of common molecular activities is a relevant topic in evolutionary, developmental, and pathological perspectives. Here, we addressed this question by focusing on the transcription factor and regulator of chromatin accessibility encoded by the Cdx2 homeobox gene that plays important functions during embryonic development and in adult diseases. By integrating RNAseq data in mouse embryogenesis, we unveiled a core set of common genes whose expression is responsive to the CDX2 homeoprotein during trophectoderm formation, posterior body elongation and intestinal specification. ChIPseq data analysis also identified a set of common chromosomal regions targeted by CDX2 at these three developmental steps. The transcriptional core set of genes was then validated with transgenic mouse models of loss or gain of function of Cdx2. Finally, based on human cancer data, we highlight the relevance of these results by displaying a significant number of human orthologous genes to the core set of mouse CDX2-responsive genes exhibiting an altered expression along with CDX2 in human malignancies

Severe head dysgenesis resulting from imbalance between anterior and posterior ontogenetic programs

Head dysgenesis is a major cause of fetal demise and craniofacial malformation. Although mutations in genes of the head ontogenetic program have been reported, many cases remain unexplained. Head dysgenesis has also been related to trisomy or amplification of the chromosomal region overlapping the CDX2 homeobox gene, a master element of the trunk ontogenetic program. Hence, we investigated the repercussion on head morphogenesis of the imbalance between the head and trunk ontogenetic programs, by means of ectopic rostral expression of CDX2 at gastrulation. This caused severe malformations affecting the forebrain and optic structures, and also the frontonasal process associated with defects in neural crest cells colonization. These malformations are the result of the downregulation of genes of the head program together with the abnormal induction of trunk program genes. Together, these data indicate that the imbalance between the anterior and posterior ontogenetic programs in embryos is a new possible cause of head dysgenesis during human development, linked to defects in setting up anterior neuroectodermal structures

Lipodystrophy and obesity are associated with decreased number of T cells with regulatory function and pro-inflammatory macrophage phenotype

Background/Objectives:In lipodystrophy (LD) adipose tissue function to store lipids is impaired, leading to metabolic syndrome, similar to that found in obesity. Emerging evidence links dysmetabolism with disorders of the immune system. Our aim is to investigate whether T-cell populations with regulatory function and monocyte-derived macrophages (MDMs) are affected by LD and obesity.Subjects/Methods:Blood was collected from 16 LD, 16 obese (OB, BMI>30 kg m -2) and 16 healthy normal-weight women (CNT). Physical parameters, plasma lipid profile, glucose, HbA1c, leptin levels were determined. Flow cytometry was employed to assess the number of circulating CD4 + /CD25 hi regulatory T cells (Tregs) and invariant natural killer T (iNKT) cells. Characterization of MDMs included: 1. morphological/oil-Red-O staining analyses to define two morphotypes: lipid laden (LL) and spindle-like (sp) MDM; 2. gene expression studies; 3. use of conditioned medium from MDMs (MDMs CM) on human SGBS cells.Results:As compared to CNT, LD and, to a lesser extent, obesity were associated with reduced Tregs and iNKTs (P<0.001 and P<0.01 for LD and OB, respectively), higher number of LL-MDMs (P<0.001 and P<0.01 for LD and OB, respectively), lower number of sp-MDMs (P<0.001 for both LD and OB), which correlated with increased paracrine stimulation of lipid accumulation in cells (P<0.001 and P<0.01 for LD and OB, respectively). LD MDMs showed decreased and increased expression for anti-inflammatory (IL10 and CD163) and pro-inflammatory (CD68 and CCL20) marker genes, respectively. Analysis of correlation indicated that Tregs are directly related with HDL (P<0.01) and inversely related with LL-MDM (P<0.001) and that LL-MDM are directly related with triglycerides (P<0.01) and oxidized LDL (P<0.01).Conclusions:LD and obesity are associated with changes in the immune system: a significant reduction in the number of T cells with regulatory function and a shift of MDM towards lipid accumulation. Lipid profile of the patients correlates with these changes

Implication of 4E-BP1 protein dephosphorylation and accumulation in pancreatic cancer cell death induced by combined gemcitabine and TRAIL

Pancreatic cancer cells show varying sensitivity to the anticancer effects of gemcitabine. However, as a chemotherapeutic agent, gemcitabine can cause intolerably high levels of toxicity and patients often develop resistance to the beneficial effects of this drug. Combination studies show that use of gemcitabine with the pro-apoptotic cytokine TRAIL can enhance the inhibition of survival and induction of apoptosis of pancreatic cancer cells. Additionally, following combination treatment there is a dramatic increase in the level of the hypophosphorylated form of the tumour suppressor protein 4E-BP1. This is associated with inhibition of mTOR activity, resulting from caspase-mediated cleavage of the Raptor and Rictor components of mTOR. Use of the pan-caspase inhibitor Z-VAD-FMK indicates that the increase in level of 4E-BP1 is also caspase-mediated. ShRNA-silencing of 4E-BP1 expression renders cells more resistant to cell death induced by the combination treatment. Since the levels of 4E-BP1 are relatively low in untreated pancreatic cancer cells these results suggest that combined therapy with gemcitabine and TRAIL could improve the responsiveness of tumours to treatment by elevating the expression of 4E-BP1

A Novel Copper Chelate Modulates Tumor Associated Macrophages to Promote Anti-Tumor Response of T Cells

At the early stages of carcinogenesis, the induction of tumor specific T cell mediated immunity seems to block the tumor growth and give protective anti-tumor immune response. However, tumor associated macrophages (TAMs) might play an immunosuppressive role and subvert this anti tumor immunity leading to tumor progression and metastasis.The Cu (II) complex, (chelate), copper N-(2-hydroxy acetophenone) glycinate (CuNG), synthesized by us, has previously been shown to have a potential usefulness in immunotherapy of multiple drug resistant cancers. The current study demonstrates that CuNG treatment of TAMs modulates their status from immunosuppressive to proimmunogenic nature. Interestingly, these activated TAMs produced high levels of IL-12 along with low levels of IL-10 that not only allowed strong Th1 response marked by generation of high levels of IFN-gamma but also reduced activation induced T cell death. Similarly, CuNG treatment of peripheral blood monocytes from chemotherapy and/or radiotherapy refractory cancer patients also modulated their cytokine status. Most intriguingly, CuNG treated TAMs could influence reprogramming of TGF-beta producing CD4(+)CD25(+) T cells toward IFN-gamma producing T cells.Our results show the potential usefulness of CuNG in immunotherapy of drug-resistant cancers through reprogramming of TAMs that in turn reprogram the T cells and reeducate the T helper function to elicit proper anti-tumorogenic Th1 response leading to effective reduction in tumor growth

Temperature extremes Estimation of non-stationary return levels and associated uncertainties

International audienceEstimating temperature extremes (TEs) and associated uncertainties under the non-stationary (NS) assumption is a key research question in several domains, including the nuclear safety field. Methods for estimating TEs and associated confidence intervals (CIs) have often been used in the literature but in a stationary context, separately and without detailed comparison. The extreme value theory is often used to assess risks in a context of climate change. It provides an accurate indication of distributions describing the frequency of occurrence of TEs. However, in an NS context, the notion of the return period is not easily interpretable. For instance, to predict a high return level (RL) in a future year, time-varying distributions must be used and compared. This study examines the performance of a new concept to predict RLs in an NS context and compares three methods for constructing the associated CIs (delta, profile likelihood, and parametric bootstrap). The present work takes up the concept of integrated return periods that define the T-year RL as the level for which the expected number of events in a T-year period is one and proposes a new method based on conditional predictions that is useful for predicting high RLs of extreme events in the near future (the 100-year RL in the year 2030, for instance). The daily maximum temperature (DMT) observed at the Orange Station in France was used as a case study. Several trend models were compared and a new likelihood-based method to detect breaks in TEs is proposed. The analyses were conducted assuming the time-varying Generalized Extreme Value (GEV) distribution. The concepts have been implemented in a software package (Non-Stationary Generalized Extreme Value (NSGEV)). The application demonstrates that the RL estimates for NS situations can be quite different from those corresponding to stationary conditions. Overall, the results suggest that the NS analysis can be helpful in making a more appropriate assessment of the risk for periodic safety reviews during the life of a nuclear power plant (NPP

Regional frequency analysis of extreme storm surges along the French coast

A good knowledge of extreme storm surges is necessary to ensure protection against flood. In this paper we introduce a methodology to determine time series of skew surges in France as well as a statistical approach for estimating extreme storm surges. With the aim to cope with the outlier issue in surge series, a regional frequency analysis has been carried out for the surges along the Atlantic coast and the Channel coast. This methodology is not the current approach used to estimate extreme surges in France. First results showed that the extreme events identified as outliers in at-site analyses do not appear to be outliers any more in the regional empirical distribution. Indeed the regional distribution presents a curve to the top with these extreme events that a mixed exponential distribution seems to recreate. Thus, the regional approach appears to be more reliable for some sites than at-site analyses. A fast comparison at a given site showed surge estimates with the regional approach and a mixed exponential distribution are higher than surge estimates with an at-site fitting. In the case of Brest, the 1000-yr return surge is 167 cm in height with the regional approach instead of 126 cm with an at-site analysis. © 2011 Author(s)

Extreme storm surges A comparative study of frequency analysis approaches

International audienceIn France, nuclear facilities were designed around very low probabilities of failure. Nevertheless, some extreme climatic events have given rise to exceptional observed surges (outliers) much larger than other observations, and have clearly illustrated the potential to underestimate the extreme water levels calculated with the current statistical methods. The objective of the present work is to conduct a comparative study of three approaches to extreme value analysis, including the annual maxima (AM), the peaks-over-threshold (POT) and the r-largest order statistics (r-LOS). These methods are illustrated in a real analysis case study. All data sets were screened for outliers. Non-parametric tests for randomness, homogeneity and stationarity of time series were used. The shape and scale parameter stability plots, the mean excess residual life plot and the stability of the standard errors of return levels were used to select optimal thresholds and r values for the POT and r-LOS method, respectively. The comparison of methods was based on (i) the uncertainty degrees, (ii) the adequacy criteria and tests, and (iii) the visual inspection. It was found that the r-LOS and POT methods have reduced the uncertainty on the distribution parameters and return level estimates and have systematically shown values of the 100 and 500-year return levels smaller than those estimated with the AM method. Results have also shown that none of the compared methods has allowed a good fit at the right tail of the distribution in the presence of outliers. As a perspective, the use of historical information was proposed in order to increase the representativeness of outliers in data sets. Findings are of practical relevance, not only to nuclear energy operators in France, for applications in storm surge hazard analysis and flood management, but also for the optimal planning and design of facilities to withstand extreme environmental conditions, with an appropriate level of risk. © Author(s) 2014

Development of a target-site-based regional frequency model using historical information

International audienceNuclear power plants in France are designed to withstand natural hazards. Nevertheless, some exceptional storm surges, considered as outliers, are not properly addressed by classical statistical models. Local frequency estimations can be obtained with acceptable uncertainties if the data set containing the extreme storm surge levels is sufficiently complete and not characterized by the presence of an outlier. Otherwise, additional information such as regional and historical storm surges may be used to mitigate the lack of data and the influence of the outlier by increasing its representativeness in the sample. The objective of the present work is to develop a regional frequency model (RFM) using historical storm surges. Here we propose a RFM using historical information (HI). The empirical spatial extremogram is used herein to form a homogenous region of interest centered on a target site. A related issue regards the reconstitution, at the target site and from its neighbors, of missed storm surges with a multiple linear regression (MLR). MLR analysis can be considered conclusive if available observations at neighboring sites are informative enough and the reconstitution results meet some criteria during the cross-validation process. A total of 35 harbors located on the French (Atlantic and English Channel) and British coasts are used as a whole region with the La Rochelle site as a target site. The Peaks-Over-Threshold frequency model is used. The results are compared to those of an existing model based on the index flood method. The use of HI in the developed RFM increases the representativeness of the outlier in the sample. Fitting results at the right tail of the distribution appear more adequate and the 100-year return level is about 30 cm higher. The 100-year return level in the initial fitting has a return period of about 30 years in the updated fitting. © 2018, Springer Science+Business Media B.V., part of Springer Nature