Oncoprotein DEK as a tissue and urinary biomarker for bladder cancer

<p>Abstract</p> <p>Background</p> <p>Bladder cancer is a significant healthcare problem in the United States of America with a high recurrence rate. Early detection of bladder cancer is essential for removing the tumor with preservation of the bladder, avoiding metastasis and hence improving prognosis and long-term survival. The objective of this study was to analyze the presence of DEK protein in voided urine of bladder cancer patients as a urine-based bladder cancer diagnostic test.</p> <p>Methods</p> <p>We examined the expression of DEK protein by western blot in 38 paired transitional cell carcinoma (TCC) bladder tumor tissues and adjacent normal tissue. The presence of DEK protein in voided urine was analyzed by western blot in 42 urine samples collected from patients with active TCC, other malignant urogenital disease and healthy individuals.</p> <p>Results</p> <p>The DEK protein is expressed in 33 of 38 bladder tumor tissues with no expression in adjacent normal tissue. Based on our sample size, DEK protein is expressed in 100% of tumors of low malignant potential, 92% of tumors of low grade and in 71% of tumors of high grade. Next, we analyzed 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals for DEK protein expression by western blot analysis. We are the first to show that the DEK protein is present in the urine of bladder cancer patients. Approximately 84% of TCC patient urine specimens were positive for urine DEK.</p> <p>Conclusion</p> <p>Based on our pilot study of 38 bladder tumor tissue and 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals; DEK protein is expressed in bladder tumor tissue and voided urine of bladder cancer patients. The presence of DEK protein in voided urine is potentially a suitable biomarker for bladder cancer and that the screening for the presence of DEK protein in urine can be explored as a noninvasive diagnostic test for bladder cancer.</p

Preventing intrusive memories after trauma via a brief intervention involving Tetris computer game play in the emergency department: a proof-of-concept randomized controlled trial.

After psychological trauma, recurrent intrusive visual memories may be distressing and disruptive. Preventive interventions post trauma are lacking. Here we test a behavioural intervention after real-life trauma derived from cognitive neuroscience. We hypothesized that intrusive memories would be significantly reduced in number by an intervention involving a computer game with high visuospatial demands (Tetris), via disrupting consolidation of sensory elements of trauma memory. The Tetris-based intervention (trauma memory reminder cue plus c. 20 min game play) vs attention-placebo control (written activity log for same duration) were both delivered in an emergency department within 6 h of a motor vehicle accident. The randomized controlled trial compared the impact on the number of intrusive trauma memories in the subsequent week (primary outcome). Results vindicated the efficacy of the Tetris-based intervention compared with the control condition: there were fewer intrusive memories overall, and time-series analyses showed that intrusion incidence declined more quickly. There were convergent findings on a measure of clinical post-trauma intrusion symptoms at 1 week, but not on other symptom clusters or at 1 month. Results of this proof-of-concept study suggest that a larger trial, powered to detect differences at 1 month, is warranted. Participants found the intervention easy, helpful and minimally distressing. By translating emerging neuroscientific insights and experimental research into the real world, we offer a promising new low-intensity psychiatric intervention that could prevent debilitating intrusive memories following trauma

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain

Expression Profiling of a Genetic Animal Model of Depression Reveals Novel Molecular Pathways Underlying Depressive-Like Behaviours

The Flinders model is a validated genetic rat model of depression that exhibits a number of behavioural, neurochemical and pharmacological features consistent with those observed in human depression.In this study we have used genome-wide microarray expression profiling of the hippocampus and prefrontal/frontal cortex of Flinders Depression Sensitive (FSL) and control Flinders Depression Resistant (FRL) lines to understand molecular basis for the differences between the two lines. We profiled two independent cohorts of Flinders animals derived from the same colony six months apart, each cohort statistically powered to allow independent as well as combined analysis. Using this approach, we were able to validate using real-time-PCR a core set of gene expression differences that showed statistical significance in each of the temporally distinct cohorts, representing consistently maintained features of the model. Small but statistically significant increases were confirmed for cholinergic (chrm2, chrna7) and serotonergic receptors (Htr1a, Htr2a) in FSL rats consistent with known neurochemical changes in the model. Much larger gene changes were validated in a number of novel genes as exemplified by TMEM176A, which showed 35-fold enrichment in the cortex and 30-fold enrichment in hippocampus of FRL animals relative to FSL.These data provide significant insights into the molecular differences underlying the Flinders model, and have potential relevance to broader depression research

Mechanistic framework to link root growth models with weather and soil physical properties, including example applications to soybean growth in Brazil

Background and aimsRoot elongation is generally limited by a combination of mechanical impedance and water stress in most arable soils. However, dynamic changes of soil penetration resistance with soil water content are rarely included in models for predicting root growth. Better modelling frameworks are needed to understand root growth interactions between plant genotype, soil management, and climate. Aim of paper is to describe a new model of root elongation in relation to soil physical characteristics like penetration resistance, matric potential, and hypoxia.MethodsA new diagrammatic framework is proposed to illustrate the interaction between root elongation, soil management, and climatic conditions. The new model was written in Matlab®, using the root architecture model RootBox and a model that solves the 1D Richards equations for water flux in soil. Inputs: root architectural parameters for Soybean; soil hydraulic properties; root water uptake function in relation to matric flux potential; root elongation rate as a function of soil physical characteristics. Simulation scenarios: (a) compact soil layer at 16 to 20 cm; (b) test against a field experiment in Brazil during contrasting drought and normal rainfall seasons.Results(a) Soil compaction substantially slowed root growth into and below the compact layer. (b) Simulated root length density was very similar to field measurements, which was influenced greatly by drought. The main factor slowing root elongation in the simulations was evaluated using a stress reduction function.ConclusionThe proposed framework offers a way to explore the interaction between soil physical properties, weather and root growth. It may be applied to most root elongation models, and offers the potential to evaluate likely factors limiting root growth in different soils and tillage regimes

A general method for controlling and resolving rotational orientation of molecules in molecule-surface collisions

Theoretical Chemistr

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

RationaleIdentification of biomarkers that establish diagnosis or treatment response is critical to the advancement of research and management of patients with depression.ObjectiveOur goal was to identify biomarkers that can potentially assess fluoxetine response and risk to poor treatment outcome.MethodsWe measured behavior, gene expression, and the levels of 36 neurobiochemical analytes across a panel of genetically diverse mouse inbred lines after chronic treatment with water or fluoxetine.ResultsGlyoxylase 1 (GLO1) and guanine nucleotide-binding protein 1 (GNB1) mostly account for baseline anxiety-like and depressive-like behavior, indicating a common biological link between depression and anxiety. Fluoxetine-induced biochemical alterations discriminated positive responders, while baseline neurobiochemical differences differentiated negative responders (p < 0.006). Results show that glial fibrillary acidic protein, S100 beta protein, GLO1, and histone deacetylase 5 contributed most to fluoxetine response. These proteins are linked within a cellular growth/proliferation pathway, suggesting the involvement of cellular genesis in fluoxetine response. Furthermore, a candidate genetic locus that associates with baseline depressive-like behavior contains a gene that encodes for cellular proliferation/adhesion molecule (Cadm1), supporting a genetic basis for the role of neuro/gliogenesis in depression.ConclusionWe provided a comprehensive analysis of behavioral, neurobiochemical, and transcriptome data across 30 mouse inbred strains that has not been accomplished before. We identified biomarkers that influence fluoxetine response, which, altogether, implicate the importance of cellular genesis in fluoxetine treatment. More broadly, this approach can be used to assess a wide range of drug response phenotypes that are challenging to address in human samples.Electronic supplementary materialThe online version of this article (doi:10.1007/s00213-011-2574-z) contains supplementary material, which is available to authorized users