ProKinO: An Ontology for Integrative Analysis of Protein Kinases in Cancer

Protein kinases are a large and diverse family of enzymes that are genomically altered in many human cancers. Targeted cancer genome sequencing efforts have unveiled the mutational profiles of protein kinase genes from many different cancer types. While mutational data on protein kinases is currently catalogued in various databases, integration of mutation data with other forms of data on protein kinases such as sequence, structure, function and pathway is necessary to identify and characterize key cancer causing mutations. Integrative analysis of protein kinase data, however, is a challenge because of the disparate nature of protein kinase data sources and data formats., where the mutations are spread over 82 distinct kinases. We also provide examples of how ontology-based data analysis can be used to generate testable hypotheses regarding cancer mutations.

A Classifier-based approach to identify genetic similarities between diseases

Motivation: Genome-wide association studies are commonly used to identify possible associations between genetic variations and diseases. These studies mainly focus on identifying individual single nucleotide polymorphisms (SNPs) potentially linked with one disease of interest. In this work, we introduce a novel methodology that identifies similarities between diseases using information from a large number of SNPs. We separate the diseases for which we have individual genotype data into one reference disease and several query diseases. We train a classifier that distinguishes between individuals that have the reference disease and a set of control individuals. This classifier is then used to classify the individuals that have the query diseases. We can then rank query diseases according to the average classification of the individuals in each disease set, and identify which of the query diseases are more similar to the reference disease. We repeat these classification and comparison steps so that each disease is used once as reference disease

Financial Time series: motif discovery and analysis using VALMOD

Motif discovery and analysis in time series data-sets have a wide-range of applications from genomics to finance. In consequence, development and critical evaluation of these algorithms is required with the focus not just detection but rather evaluation and interpretation of overall significance. Our focus here is the specific algorithm, VALMOD, but algorithms in wide use for motif discovery are summarised and briefly compared, as well as typical evaluation methods with strengths. Additionally, Taxonomy diagrams for motif discovery and evaluation techniques are constructed to illustrate the relationship between different approaches as well as inter-dependencies. Finally evaluation measures based upon results obtained from VALMOD analysis of a GBP-USD foreign exchange (F/X) rate data-set are presented, in illustration

Evidence for the role of EPHX2 gene variants in anorexia nervosa.

Anorexia nervosa (AN) and related eating disorders are complex, multifactorial neuropsychiatric conditions with likely rare and common genetic and environmental determinants. To identify genetic variants associated with AN, we pursued a series of sequencing and genotyping studies focusing on the coding regions and upstream sequence of 152 candidate genes in a total of 1205 AN cases and 1948 controls. We identified individual variant associations in the Estrogen Receptor-ß (ESR2) gene, as well as a set of rare and common variants in the Epoxide Hydrolase 2 (EPHX2) gene, in an initial sequencing study of 261 early-onset severe AN cases and 73 controls (P=0.0004). The association of EPHX2 variants was further delineated in: (1) a pooling-based replication study involving an additional 500 AN patients and 500 controls (replication set P=0.00000016); (2) single-locus studies in a cohort of 386 previously genotyped broadly defined AN cases and 295 female population controls from the Bogalusa Heart Study (BHS) and a cohort of 58 individuals with self-reported eating disturbances and 851 controls (combined smallest single locus P<0.01). As EPHX2 is known to influence cholesterol metabolism, and AN is often associated with elevated cholesterol levels, we also investigated the association of EPHX2 variants and longitudinal body mass index (BMI) and cholesterol in BHS female and male subjects (N=229) and found evidence for a modifying effect of a subset of variants on the relationship between cholesterol and BMI (P<0.01). These findings suggest a novel association of gene variants within EPHX2 to susceptibility to AN and provide a foundation for future study of this important yet poorly understood condition

Reshaping Antibody Diversity

SummarySome species mount a robust antibody response despite having limited genome-encoded combinatorial diversity potential. Cows are unusual in having exceptionally long CDR H3 loops and few V regions, but the mechanism for creating diversity is not understood. Deep sequencing reveals that ultralong CDR H3s contain a remarkable complexity of cysteines, suggesting that disulfide-bonded minidomains may arise during repertoire development. Indeed, crystal structures of two cow antibodies reveal that these CDR H3s form a very unusual architecture composed of a β strand “stalk” that supports a structurally diverse, disulfide-bonded “knob” domain. Diversity arises from somatic hypermutation of an ultralong DH with a severe codon bias toward mutation to cysteine. These unusual antibodies can be elicited to recognize defined antigens through the knob domain. Thus, the bovine immune system produces an antibody repertoire composed of ultralong CDR H3s that fold into a diversity of minidomains generated through combinations of somatically generated disulfides

Comparing Effect of Safranal and Diazepam in Reducing Preoperative Anxiety and Improving Vital Symptoms

Aim: Preoperative anxiety is an unpleasant manner created by fear of surgery. The aim of the present study was to compare the effects of diazepam pill with Safranal in reducing preoperative anxiety and improving vital symptoms. Material and Methods: In this double blind randomized clinical trial, 54 patients who were candidates of urology surgery (varicocele) in 15th Khordad Hospital, Gonabad, Iran, were selected by purposive sampling method, using a randomized numbers table; they were divided into intervention (n=29) and control group (n=25). The patients in intervention group received 15mg Safranal and the patients in control group received 5mg oral diazepam 3 hours before surgery. The State-Trait Anxiety Inventory (STAI) questionnaire was completed by the patients prior to the intervention and just at the entrance to the surgery room, and the vital symptoms of the patient were evaluated. The data were analyzed by SPSS 11.5 software, using of Chi-square and independent sample t-test. Findings: After intervention, the trait anxiety in the Safranal group was significantly lower than diazepam group (p=0.007) and before the intervention (p=0.002). Also, diastolic blood pressure decreased significantly in the Safranal group compared with the diazepam group (p=0.049). Conclusion: Saffranal consumption before surgery is more effective than diazepam consumption in reducing the trait anxiety, but it does not affect state anxiety. Also, compared to diazepam, Saffranal consumption leads to a more reduction in diastolic blood pressure, while it does not affect systolic blood pressure and heart rate

Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis

Non-homologous end-joining pathway associated with occurrence of myocardial infarction: gene set analysis of genome-wide association study data

<p>Purpose: DNA repair deficiencies have been postulated to play a role in the development and progression of cardiovascular disease (CVD). The hypothesis is that DNA damage accumulating with age may induce cell death, which promotes formation of unstable plaques. Defects in DNA repair mechanisms may therefore increase the risk of CVD events. We examined whether the joints effect of common genetic variants in 5 DNA repair pathways may influence the risk of CVD events.</p> <p>Methods: The PLINK set-based test was used to examine the association to myocardial infarction (MI) of the DNA repair pathway in GWAS data of 866 subjects of the GENetic DEterminants of Restenosis (GENDER) study and 5,244 subjects of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) study. We included the main DNA repair pathways (base excision repair, nucleotide excision repair, mismatch repair, homologous recombination and non-homologous end-joining (NHEJ)) in the analysis.</p> <p>Results: The NHEJ pathway was associated with the occurrence of MI in both GENDER (P = 0.0083) and PROSPER (P = 0.014). This association was mainly driven by genetic variation in the MRE11A gene (PGENDER = 0.0001 and PPROSPER = 0.002). The homologous recombination pathway was associated with MI in GENDER only (P = 0.011), for the other pathways no associations were observed.</p> <p>Conclusion: This is the first study analyzing the joint effect of common genetic variation in DNA repair pathways and the risk of CVD events, demonstrating an association between the NHEJ pathway and MI in 2 different cohorts.</p&gt

Arena3D: visualizing time-driven phenotypic differences in biological systems

<p>Abstract</p> <p>Background</p> <p>Elucidating the genotype-phenotype connection is one of the big challenges of modern molecular biology. To fully understand this connection, it is necessary to consider the underlying networks and the time factor. In this context of data deluge and heterogeneous information, visualization plays an essential role in interpreting complex and dynamic topologies. Thus, software that is able to bring the network, phenotypic and temporal information together is needed. Arena3D has been previously introduced as a tool that facilitates link discovery between processes. It uses a layered display to separate different levels of information while emphasizing the connections between them. We present novel developments of the tool for the visualization and analysis of dynamic genotype-phenotype landscapes.</p> <p>Results</p> <p>Version 2.0 introduces novel features that allow handling time course data in a phenotypic context. Gene expression levels or other measures can be loaded and visualized at different time points and phenotypic comparison is facilitated through clustering and correlation display or highlighting of impacting changes through time. Similarity scoring allows the identification of global patterns in dynamic heterogeneous data. In this paper we demonstrate the utility of the tool on two distinct biological problems of different scales. First, we analyze a medium scale dataset that looks at perturbation effects of the pluripotency regulator Nanog in murine embryonic stem cells. Dynamic cluster analysis suggests alternative indirect links between Nanog and other proteins in the core stem cell network. Moreover, recurrent correlations from the epigenetic to the translational level are identified. Second, we investigate a large scale dataset consisting of genome-wide knockdown screens for human genes essential in the mitotic process. Here, a potential new role for the gene <it>lsm14a </it>in cytokinesis is suggested. We also show how phenotypic patterning allows for extensive comparison and identification of high impact knockdown targets.</p> <p>Conclusions</p> <p>We present a new visualization approach for perturbation screens with multiple phenotypic outcomes. The novel functionality implemented in Arena3D enables effective understanding and comparison of temporal patterns within morphological layers, to help with the system-wide analysis of dynamic processes. Arena3D is available free of charge for academics as a downloadable standalone application from: <url>http://arena3d.org/</url>.</p