Yin Yang Gene Expression Ratio Signature for Lung Cancer Prognosis

Many studies have established gene expression-based prognostic signatures for lung cancer. All of these signatures were built from training data sets by learning the correlation of gene expression with the patients'' survival time. They require all new sample data to be normalized to the training data, ultimately resulting in common problems of low reproducibility and impracticality. To overcome these problems, we propose a new signature model which does not involve data training. We hypothesize that the imbalance of two opposing effects in lung cancer cells, represented by Yin and Yang genes, determines a patient’s prognosis. We selected the Yin and Yang genes by comparing expression data from normal lung and lung cancer tissue samples using both unsupervised clustering and pathways analyses. We calculated the Yin and Yang gene expression mean ratio (YMR) as patient risk scores. Thirty-one Yin and thirty-two Yang genes were identified and selected for the signature development. In normal lung tissues, the YMR is less than 1.0; in lung cancer cases, the YMR is greater than 1.0. The YMR was tested for lung cancer prognosis prediction in four independent data sets and it significantly stratified patients into high- and low-risk survival groups (p = 0.02, HR = 2.72; p = 0.01, HR = 2.70; p = 0.007, HR = 2.73; p = 0.005, HR = 2.63). It also showed prediction of the chemotherapy outcomes for stage II & III. In multivariate analysis, the YMR risk factor was more successful at predicting clinical outcomes than other commonly used clinical factors, with the exception of tumor stage. The YMR can be measured in an individual patient in the clinic independent of gene expression platform. This study provided a novel insight into the biology of lung cancer and shed light on the clinical applicability.     

Drosophila Heparan Sulfate 6-O-Endosulfatase Sulf1 Facilitates Wingless (Wg) Protein Degradation

Heparan sulfate proteoglycans regulate various physiological and developmental processes through interactions with a number of protein ligands. Heparan sulfate (HS)-ligand binding depends on the amount and patterns of sulfate groups on HS, which are controlled by various HS sulfotransferases in the Golgi apparatus as well as extracellular 6-O-endosulfatases called “Sulfs.” Sulfs are a family of secreted molecules that specifically remove 6-O-sulfate groups within the highly sulfated regions on HS. Vertebrate Sulfs promote Wnt signaling, whereas the only Drosophila homologue of Sulfs, Sulf1, negatively regulates Wingless (Wg) signaling. To understand the molecular mechanism for the negative regulation of Wg signaling by Sulf1, we studied the effects of Sulf1 on HS-Wg interaction and Wg stability. Sulf1 overexpression strongly inhibited the binding of Wg to Dally, a potential target heparan sulfate proteoglycan of Sulf1. This effect of Drosophila Sulf1 on the HS-Wg interaction is similar to that of vertebrate Sulfs. Using in vitro, in vivo, and ex vivo systems, we show that Sulf1 reduces extracellular Wg protein levels, at least partly by facilitating Wg degradation. In addition, expression of human Sulf1 in the Drosophila wing disc lowers the levels of extracellular Wg protein, as observed for Drosophila Sulf1. Our study demonstrates that vertebrate and Drosophila Sulfs have an intrinsically similar activity and that the function of Sulfs in the fate of Wnt/Wg ligands is context-dependent.     

A conceptual and practical guide to the behavioural evaluation of animal models of the symptomatology and therapy of schizophrenia

Schizophrenia is a chronic debilitating brain disorder characterized by a complex set of perceptual and behavioural symptoms that severely disrupt and undermine the patient’s psychological well-being and quality of life. Since the exact disease mechanisms remain essentially unknown, holistic animal models are indispensable tools for any serious investigation into the neurobiology of schizophrenia, including the search for remedies, prevention of the disease and possible biological markers. This review provides some practical advice to those confronted with the task of evaluating their animal models for relevance to schizophrenia, a task that inevitably involves behavioural tests with animals. To a novice, this challenge not only is a technical one but also entails attention to interpretative issues concerning validity and translational power. Here, we attempt to offer some guidance to help overcome these obstacles by drawing on our experience of diverse animal models of schizophrenia based on genetics, strain difference, brain lesions, pharmacological induction and early life developmental manipulations. The review pays equal emphasis to the general (theoretical) considerations of experimental design and the illustration of the problems related to critical test parameters and the data analysis of selected exemplar behavioural tests. Finally, the individual differences of behavioural expression in relevant tests observed in wild-type animals might offer an alternative approach in order to explore the mechanism of schizophrenia-related behavioural dysfunction at the molecular, cellular and structural levels, all of which are of more immediate relevance to cell and tissue research.     

CoRAL: predicting non-coding RNAs from small RNA-sequencing data

The surprising observation that virtually the entire human genome is transcribed means we know little about the function of many emerging classes of RNAs, except their astounding diversities. Traditional RNA function prediction methods rely on sequence or alignment information, which are limited in their abilities to classify the various collections of non-coding RNAs (ncRNAs). To address this, we developed Classification of RNAs by Analysis of Length (CoRAL), a machine learning-based approach for classification of RNA molecules. CoRAL uses biologically interpretable features including fragment length and cleavage specificity to distinguish between different ncRNA populations. We evaluated CoRAL using genome-wide small RNA sequencing data sets from four human tissue types and were able to classify six different types of RNAs with ∼80% cross-validation accuracy. Analysis by CoRAL revealed that microRNAs, small nucleolar and transposon-derived RNAs are highly discernible and consistent across all human tissue types assessed, whereas long intergenic ncRNAs, small cytoplasmic RNAs and small nuclear RNAs show less consistent patterns. The ability to reliably annotate loci across tissue types demonstrates the potential of CoRAL to characterize ncRNAs using small RNA sequencing data in less well-characterized organisms.     

Variants in GATA4 are a rare cause of familial and sporadic congenital diaphragmatic hernia

Congenital diaphragmatic hernia (CDH) is characterized by incomplete formation of the diaphragm occurring as either an isolated defect or in association with other anomalies. Genetic factors including aneuploidies and copy number variants are important in the pathogenesis of many cases of CDH, but few single genes have been definitively implicated in human CDH. In this study, we used whole exome sequencing (WES) to identify a paternally inherited novel missense GATA4 variant (c.754C>T; p.R252W) in a familial case of CDH with incomplete penetrance. Phenotypic characterization of the family included magnetic resonance imaging of the chest and abdomen demonstrating asymptomatic defects in the diaphragm in the two “unaffected” missense variant carriers. Screening 96 additional CDH patients identified a de novo heterozygous GATA4 variant (c.848G>A; p.R283H) in a non-isolated CDH patient. In summary, GATA4 is implicated in both familial and sporadic CDH, and our data suggests that WES may be a powerful tool to discover rare variants for CDH.     

Impact of mercury on denitrification and denitrifying microbial communities in nitrate enrichments of subsurface sediments

The contamination of groundwater with mercury (Hg) is an increasing problem worldwide. Yet, little is known about the interactions of Hg with microorganisms and their processes in subsurface environments. We tested the impact of Hg on denitrification in nitrate reducing enrichment cultures derived from subsurface sediments from the Oak Ridge Integrated Field Research Challenge site, where nitrate is a major contaminant and where bioremediation efforts are in progress. We observed an inverse relationship between Hg concentrations and onset and rates of denitrification in nitrate enrichment cultures containing between 53 and 1.1 μM of inorganic Hg; higher Hg concentrations increasingly extended the time to onset of denitrification and inhibited denitrification rates. Microbial community complexity, as indicated by terminal restriction fragment length polymorphism (tRFLP) analysis of the 16S rRNA genes, declined with increasing Hg concentrations; at the 312 nM Hg treatment, a single tRFLP peak was detected representing a culture of Bradyrhizobium sp. that possessed the merA gene indicating a potential for Hg reduction. A culture identified as Bradyrhizobium sp. strain FRC01 with an identical 16S rRNA sequence to that of the enriched peak in the tRFLP patterns, reduced Hg(II) to Hg(0) and carried merA whose amino acid sequence has 97 % identity to merA from the Proteobacteria and Firmicutes. This study demonstrates that in subsurface sediment incubations, Hg may inhibit denitrification and that inhibition may be alleviated when Hg resistant denitrifying Bradyrhizobium spp. detoxify Hg by its reduction to the volatile elemental form.     

Strategic use of conformational bias and structure based design to identify potent JAK3 inhibitors with improved selectivity against the JAK family and the kinome

Using a structure based design approach we have identified a series of indazole substituted pyrrolopyrazines, which are potent inhibitors of JAK3. Intramolecular electronic repulsion was used as a strategy to induce a strong conformational bias within the ligand. Compounds bearing this conformation participated in a favorable hydrophobic interaction with a cysteine residue in the JAK3 binding pocket, which imparted high selectivity versus the kinome and improved selectivity within the JAK family.     

Turnover of nonessential fatty acids in cardiolipin from the rat heart

Cardiolipin (CL) is a unique phospholipid (PL) found in the mitochondria of mammalian cells. CL remodeling is accompanied by turnover of its fatty acid acyl groups. Abnormalities in CL remodeling have been found in Barth's syndrome, diabetes, and obesity. The objective of this study was to determine nonessential fatty acid turnover in CL and phosphatidylethanolamine (PE) in the rat heart in vivo. Sprague-Dawley rats were fed either a regular chow or a high-fat diet for 15 weeks, and consumed 6% deuterium-enriched drinking water as a tracer for 14 days. CL and PE were extracted from cardiac tissue and isolated by TLC. Fatty acids from CL, PE, and plasma were analyzed by GC/MS for deuterium incorporation. Results showed oleate and vaccenate turnover were the highest in CL whereas palmitate and stearate turnover were low. Among the nonessential fatty acids in PE, turnover of stearate and vaccenate were the highest. The high turnover rate in vaccenate was unexpected, because vaccenate previously had no known metabolic or physiologic function. In conclusion, the similarly high turnover rates of both oleate and vaccenate readily suggest that remodeling is an important functional aspect of PL metabolism in CL.