MicroRNA-122 modulates the rhythmic expression profile of the circadian deadenylase Nocturnin in mouse liver.

Nocturnin is a circadian clock-regulated deadenylase thought to control mRNA expression post-transcriptionally through poly(A) tail removal. The expression of Nocturnin is robustly rhythmic in liver at both the mRNA and protein levels, and mice lacking Nocturnin are resistant to diet-induced obesity and hepatic steatosis. Here we report that Nocturnin expression is regulated by microRNA-122 (miR-122), a liver specific miRNA. We found that the 3'-untranslated region (3'-UTR) of Nocturnin mRNA harbors one putative recognition site for miR-122, and this site is conserved among mammals. Using a luciferase reporter construct with wild-type or mutant Nocturnin 3'-UTR sequence, we demonstrated that overexpression of miR-122 can down-regulate luciferase activity levels and that this effect is dependent on the presence of the putative miR-122 recognition site. Additionally, the use of an antisense oligonucleotide to knock down miR-122 in vivo resulted in significant up-regulation of both Nocturnin mRNA and protein expression in mouse liver during the night, resulting in Nocturnin rhythms with increased amplitude. Together, these data demonstrate that the normal rhythmic profile of Nocturnin expression in liver is shaped in part by miR-122. Previous studies have implicated Nocturnin and miR-122 as important post-transcriptional regulators of both lipid metabolism and circadian clock controlled gene expression in the liver. Therefore, the demonstration that miR-122 plays a role in regulating Nocturnin expression suggests that this may be an important intersection between hepatic metabolic and circadian control.

Substrate metabolism, nutrient balance and obesity development in children and adolescents: a target for intervention?

Obesity results from the organism's inability to maintain energy balance over a long term. Childhood obesity and its related factors and pathological consequences tend to persist into adulthood. A cluster of factors, including high energy density in the diet (high fat intake), low energy expenditure, and disturbed substrate oxidation, favour the increase in fat mass. Oxidation of three major macronutrients and their roles in the regulation of energy balance, particularly in children and adolescents, are discussed. Total glucose oxidation is not different between obese and lean children; exogenous glucose utilization is higher whereas endogenous glucose utilization is lower in obese compared with lean children. Carbohydrate composition of the diet determines carbohydrate oxidation regardless of fat content of the diet. Both exogenous and endogenous fat oxidation are higher in obese than in lean subjects. The influence of high fat intake on accumulation of fat mass is operative rather over a long term. Several future directions are addressed, such that a combination of increased physical activity and modification in diet composition, in terms of energy density and glycemic index, is recommended for children and adolescents.

CD44 attenuates activation of the hippo signaling pathway and is a prime therapeutic target for glioblastoma.

Glioblastoma multiforme (GBM) is the most aggressive brain tumor that, by virtue of its resistance to chemotherapy and radiotherapy, is currently incurable. Identification of molecules whose targeting may eliminate GBM cells and/or sensitize glioblastoma cells to cytotoxic drugs is therefore urgently needed. CD44 is a major cell surface hyaluronan receptor and cancer stem cell marker that has been implicated in the progression of a variety of cancer types. However, the major downstream signaling pathways that mediate its protumor effects and the role of CD44 in the progression and chemoresponse of GBM have not been established. Here we show that CD44 is upregulated in GBM and that its depletion blocks GBM growth and sensitizes GBM cells to cytotoxic drugs in vivo. Consistent with this observation, CD44 antagonists potently inhibit glioma growth in preclinical mouse models. We provide the first evidence that CD44 functions upstream of the mammalian Hippo signaling pathway and that CD44 promotes tumor cell resistance to reactive oxygen species-induced and cytotoxic agent-induced stress by attenuating activation of the Hippo signaling pathway. Together, our results identify CD44 as a prime therapeutic target for GBM, establish potent antiglioma efficacy of CD44 antagonists, uncover a novel CD44 signaling pathway, and provide a first mechanistic explanation as to how upregulation of CD44 may constitute a key event in leading to cancer cell resistance to stresses of different origins. Finally, our results provide a rational explanation for the observation that functional inhibition of CD44 augments the efficacy of chemotherapy and radiation therapy.

Target organ damage: how to detect it and how to treat it?

The early detection of cardiac organ damage in clinical practice is primordial for cardiovascular risk profiling of patients with hypertension. In this respect the determination of microalbuminuria is very appealing because it increasingly appears to be the most cost-effective means to identify cardiovascular and renal complications. Considering the treatment of patients with target organ damage, blockers of the renin-angiotensin system have a key position as they are very effective in regressing left ventricular hypertrophy, lowering urinary albumin excretion and delaying the progression of nephropathy. In high-risk patients with atherosclerosis, the use of a blocker of the renin-angiotensin system is also appealing, and it appears increasingly judicious to combine such a blocker with a calcium antagonist whenever required to control blood pressure.

Population pharmacokinetics of imatinib in CML and GIST patients under long-term treatment

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastro-intestinal stromal tumour (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occur in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after latest dose, were measured in 59 patients receiving Glivec® at diverse regimens, using a validated chromatographic method (HPLC-UV) developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one- compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T appears to affect the disposition of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen ! This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help to individualise the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Decoding decisions in healthy subjects and auditory discrimination in comatose patients through single-trial topographic EEG analyses

Neuroimaging studies analyzing neurophysiological signals are typically based on comparing averages of peri-stimulus epochs across experimental conditions. This approach can however be problematic in the case of high-level cognitive tasks, where response variability across trials is expected to be high and in cases where subjects cannot be considered part of a group. The main goal of this thesis has been to address this issue by developing a novel approach for analyzing electroencephalography (EEG) responses at the single-trial level. This approach takes advantage of the spatial distribution of the electric field on the scalp (topography) and exploits repetitions across trials for quantifying the degree of discrimination between experimental conditions through a classification scheme. In the first part of this thesis, I developed and validated this new method (Tzovara et al., 2012a,b). Its general applicability was demonstrated with three separate datasets, two in the visual modality and one in the auditory. This development allowed then to target two new lines of research, one in basic and one in clinical neuroscience, which represent the second and third part of this thesis respectively. For the second part of this thesis (Tzovara et al., 2012c), I employed the developed method for assessing the timing of exploratory decision-making. Using single-trial topographic EEG activity during presentation of a choice's payoff, I could predict the subjects' subsequent decisions. This prediction was due to a topographic difference which appeared on average at ~516ms after the presentation of payoff and was subject-specific. These results exploit for the first time the temporal correlates of individual subjects' decisions and additionally show that the underlying neural generators start differentiating their responses already ~880ms before the button press. Finally, in the third part of this project, I focused on a clinical study with the goal of assessing the degree of intact neural functions in comatose patients. Auditory EEG responses were assessed through a classical mismatch negativity paradigm, during the very early phase of coma, which is currently under-investigated. By taking advantage of the decoding method developed in the first part of the thesis, I could quantify the degree of auditory discrimination at the single patient level (Tzovara et al., in press). Our results showed for the first time that even patients who do not survive the coma can discriminate sounds at the neural level, during the first hours after coma onset. Importantly, an improvement in auditory discrimination during the first 48hours of coma was predictive of awakening and survival, with 100% positive predictive value. - L'analyse des signaux électrophysiologiques en neuroimagerie se base typiquement sur la comparaison des réponses neurophysiologiques à différentes conditions expérimentales qui sont moyennées après plusieurs répétitions d'une tâche. Pourtant, cette approche peut être problématique dans le cas des fonctions cognitives de haut niveau, où la variabilité des réponses entre les essais peut être très élevéeou dans le cas où des sujets individuels ne peuvent pas être considérés comme partie d'un groupe. Le but principal de cette thèse est d'investiguer cette problématique en développant une nouvelle approche pour l'analyse des réponses d'électroencephalographie (EEG) au niveau de chaque essai. Cette approche se base sur la modélisation de la distribution du champ électrique sur le crâne (topographie) et profite des répétitions parmi les essais afin de quantifier, à l'aide d'un schéma de classification, le degré de discrimination entre des conditions expérimentales. Dans la première partie de cette thèse, j'ai développé et validé cette nouvelle méthode (Tzovara et al., 2012a,b). Son applicabilité générale a été démontrée avec trois ensembles de données, deux dans le domaine visuel et un dans l'auditif. Ce développement a permis de cibler deux nouvelles lignes de recherche, la première dans le domaine des neurosciences cognitives et l'autre dans le domaine des neurosciences cliniques, représentant respectivement la deuxième et troisième partie de ce projet. En particulier, pour la partie cognitive, j'ai appliqué cette méthode pour évaluer l'information temporelle de la prise des décisions (Tzovara et al., 2012c). En se basant sur l'activité topographique de l'EEG au niveau de chaque essai pendant la présentation de la récompense liée à un choix, on a pu prédire les décisions suivantes des sujets (en termes d'exploration/exploitation). Cette prédiction s'appuie sur une différence topographique qui apparaît en moyenne ~516ms après la présentation de la récompense. Ces résultats exploitent pour la première fois, les corrélés temporels des décisions au niveau de chaque sujet séparément et montrent que les générateurs neuronaux de ces décisions commencent à différentier leurs réponses déjà depuis ~880ms avant que les sujets appuient sur le bouton. Finalement, pour la dernière partie de ce projet, je me suis focalisée sur une étude Clinique afin d'évaluer le degré des fonctions neuronales intactes chez les patients comateux. Des réponses EEG auditives ont été examinées avec un paradigme classique de mismatch negativity, pendant la phase précoce du coma qui est actuellement sous-investiguée. En utilisant la méthode de décodage développée dans la première partie de la thèse, j'ai pu quantifier le degré de discrimination auditive au niveau de chaque patient (Tzovara et al., in press). Nos résultats montrent pour la première fois que même des patients comateux qui ne vont pas survivre peuvent discriminer des sons au niveau neuronal, lors de la phase aigue du coma. De plus, une amélioration dans la discrimination auditive pendant les premières 48heures du coma a été observée seulement chez des patients qui se sont réveillés par la suite (100% de valeur prédictive pour un réveil).

Target Molecular Size and Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis Analysis of the ATP-and Pyrophosphate-Dependent Proton Pumps from Maize Root Tonoplast.

Tonoplast-enriched membranes were prepared from maize (Zea mays L. cv LG 11) primary roots, using sucrose nonlinear gradients. The functional molecular size of the tonoplast ATP-and PPi-dependent proton pumps were analyzed by radiation inactivation. Glucose-6-phosphate dehydrogenase (G6PDH) was added as an internal standard. Frozen samples (-196 degrees C) of the membranes were irradiated with (60)Co for different periods of time. After thawing the samples, the activities of G6PDH, ATPase, and PPase were tested. By applying target theory, the functional sizes of the ATPase and PPase in situ were found to be around 540 and 160 kilodaltons, respectively. The two activities were solubilized and separated by gel filtration chromatography. The different polypeptides copurifying with the two pumps were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Two bands (around 59 and 65 kilodaltons) were associated with the ATPase activity, whereas a double band (around 40 kilodaltons) was recovered with the PPase activity.

Developing methodologies to allow the robust prediction dynamic context dominated by perturbations

El principal objectiu del projecte era desenvolupar millores conceptuals i metodològiques que permetessin una millor predicció dels canvis en la distribució de les espècies (a una escala de paisatge) derivats de canvis ambientals en un context dominat per pertorbacions. En un primer estudi, vàrem comparar l'eficàcia de diferents models dinàmics per a predir la distribució de l'hortolà (Emberiza hortulana). Els nostres resultats indiquen que un model híbrid que combini canvis en la qualitat de l'hàbitat, derivats de canvis en el paisatge, amb un model poblacional espacialment explícit és una aproximació adequada per abordar canvis en la distribució d'espècies en contextos de dinàmica ambiental elevada i una capacitat de dispersió limitada de l'espècie objectiu. En un segon estudi abordarem la calibració mitjançant dades de seguiment de models de distribució dinàmics per a 12 espècies amb preferència per hàbitats oberts. Entre les conclusions extretes destaquem: (1) la necessitat de que les dades de seguiment abarquin aquelles àrees on es produeixen els canvis de qualitat; (2) el biaix que es produeix en la estimació dels paràmetres del model d'ocupació quan la hipòtesi de canvi de paisatge o el model de qualitat d'hàbitat són incorrectes. En el darrer treball estudiarem el possible impacte en 67 espècies d’ocells de diferents règims d’incendis, definits a partir de combinacions de nivells de canvi climàtic (portant a un augment esperat de la mida i freqüència d’incendis forestals), i eficiència d’extinció per part dels bombers. Segons els resultats dels nostres models, la combinació de factors antropogènics del regim d’incendis, tals com l’abandonament rural i l’extinció, poden ser més determinants per als canvis de distribució que els efectes derivats del canvi climàtic. Els productes generats inclouen tres publicacions científiques, una pàgina web amb resultats del projecte i una llibreria per a l'entorn estadístic R.

Brain tissue properties differentiate between motor and limbic basal ganglia circuits.

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high-resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome.

Human synthetic lethal inference as potential anti-cancer target gene detection

Background: Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results: In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes) in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates.Conclusions: Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Comparative gene prediction in human and mouse

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.

Early investigational drugs that target epidermal growth factor receptors for the treatment of head and neck cancer.

INTRODUCTION: Squamous-cell carcinoma of the head and neck (SCCHN) remains a challenging clinical problem, due to the persistent high rate of local and distant failures and the occurrence of secondary primaries. For locally advanced SCCHN, a combination of chemotherapy (CT), radiation or surgery is often used, but there are limitations, which may reduce compliance. Molecular targeted therapies, namely anti-EGFR treatments, are in development with the aim of improving clinical outcomes and mitigating treatment-related toxicities. AREAS COVERED: This review provides an overview of early investigational drugs that target EGFR for the treatment of SCCHN and discusses the ongoing trials in this domain. EXPERT OPINION: Targeted therapies are increasingly used in oncology, especially in SCCHN. Cetuximab has demonstrated a significant improvement in the treatment outcome, both as a curative treatment in combination with radiation therapy and as a palliative treatment in combination with CT; however, it failed to show any benefit in combination with concomitant chemoradiotherapy. Presently, there are many new agents, including monoclonal antibodies and small-molecule tyrosine kinase inhibitors, which are either currently under investigation for or which warrant further investigation for treating SCCHN. The discovery of predictive factors that help to identify patients most likely to respond to EGFR inhibitors as well as patient-customized therapies would help to improve patient outcomes in the future.