FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki.

Database (Oxford). 2016;2016

Authors: Abugessaisa I, Shimoji H, Sahin S, Kondo A, Harshbarger J, Lizio M, Hayashizaki Y, Carninci P, FANTOM consortium, Forrest A, Kasukawa T, Kawaji H

Abstract
The Functional Annotation of the Mammalian Genome project (FANTOM5) mapped transcription start sites (TSSs) and measured their activities in a diverse range of biological samples. The FANTOM5 project generated a large data set; including detailed information about the profiled samples, the uncovered TSSs at high base-pair resolution on the genome, their transcriptional initiation activities, and further information of transcriptional regulation. Data sets to explore transcriptome in individual cellular states encoded in the mammalian genomes have been enriched by a series of additional analysis, based on the raw experimental data, along with the progress of the research activities. To make the heterogeneous data set accessible and useful for investigators, we developed a web-based database called Semantic catalog of Samples, Transcription initiation And Regulators (SSTAR). SSTAR utilizes the open source wiki software MediaWiki along with the Semantic MediaWiki (SMW) extension, which provides flexibility to model, store, and display a series of data sets produced during the course of the FANTOM5 project. Our use of SMW demonstrates the utility of the framework for dissemination of large-scale analysis results. SSTAR is a case study in handling biological data generated from a large-scale research project in terms of maintenance and growth alongside research activities.Database URL: http://fantom.gsc.riken.jp/5/sstar/.

PMID: 27402679 [PubMed - in process]

Publication, Discovery and Interoperability of Clinical Decision Support Systems: a Linked Data Approach.

J Biomed Inform. 2016 Jul 8;

Authors: Marco-Ruiz L, Pedrinaci C, Maldonado JA, Panziera L, Chen R, Gustav Bellika J

Abstract
BACKGROUND: The high costs involved in the development of Clinical Decision Support Systems (CDSS) make it necessary to share their functionality across different systems and organizations. Service Oriented Architectures (SOA) have been proposed to allow reusing CDSS by encapsulating them in a Web service. However, strong barriers in sharing CDS functionality are still present as a consequence of lack of expressiveness of services' interfaces. Linked Services are the evolution of the Semantic Web Services paradigm to process Linked Data. They aim to provide semantic descriptions over SOA implementations to overcome the limitations derived from the syntactic nature of Web services technologies.
OBJECTIVE: To facilitate the publication, discovery and interoperability of CDS services by evolving them into Linked Services that expose their interfaces as Linked Data.
MATERIALS AND METHODS: We developed methods and models to enhance CDS SOA as Linked Services that define a rich semantic layer based on machine interpretable ontologies that powers their interoperability and reuse. These ontologies provided unambiguous descriptions of CDS services properties to expose them to the Web of Data.
RESULTS: We developed models compliant with Linked Data principles to create a semantic representation of the components that compose CDS services. To evaluate our approach we implemented a set of CDS Linked Services using a Web service definition ontology. The definitions of Web services were linked to the models developed in order to attach unambiguous semantics to the service components. All models were bound to SNOMED-CT and public ontologies (e.g. Dublin Core) in order to count on a lingua franca to explore them. Discovery and analysis of CDS services based on machine interpretable models was performed reasoning over the ontologies built.
DISCUSSION: Linked Services can be used effectively to expose CDS services to the Web of Data by building on current CDS standards. This allows building shared Linked Knowledge Bases to provide machine interpretable semantics to the CDS service description alleviating the challenges on interoperability and reuse. Linked Services allow for building 'digital libraries' of distributed CDS services that can be hosted and maintained in different organizations.

PMID: 27401856 [PubMed - as supplied by publisher]

Enhanced reproducibility of SADI web service workflows with Galaxy and Docker.

Gigascience. 2015;4:59

Authors: Aranguren ME, Wilkinson MD

Abstract
BACKGROUND: Semantic Web technologies have been widely applied in the life sciences, for example by data providers such as OpenLifeData and through web services frameworks such as SADI. The recently reported OpenLifeData2SADI project offers access to the vast OpenLifeData data store through SADI services.
FINDINGS: This article describes how to merge data retrieved from OpenLifeData2SADI with other SADI services using the Galaxy bioinformatics analysis platform, thus making this semantic data more amenable to complex analyses. This is demonstrated using a working example, which is made distributable and reproducible through a Docker image that includes SADI tools, along with the data and workflows that constitute the demonstration.
CONCLUSIONS: The combination of Galaxy and Docker offers a solution for faithfully reproducing and sharing complex data retrieval and analysis workflows based on the SADI Semantic web service design patterns.

PMID: 26640691 [PubMed - indexed for MEDLINE]

Investigation of 7-dehydrocholesterol reductase pathway to elucidate off-target prenatal effects of pharmaceuticals: a systematic review.

Pharmacogenomics J. 2016 Jul 12;

Authors: Boland MR, Tatonetti NP

Abstract
Mendelian diseases contain important biological information regarding developmental effects of gene mutations that can guide drug discovery and toxicity efforts. In this review, we focus on Smith-Lemli-Opitz syndrome (SLOS), a rare Mendelian disease characterized by compound heterozygous mutations in 7-dehydrocholesterol reductase (DHCR7) resulting in severe fetal deformities. We present a compilation of SLOS-inducing DHCR7 mutations and the geographic distribution of those mutations in healthy and diseased populations. We observed that several mutations thought to be disease causing occur in healthy populations, indicating an incomplete understanding of the condition and highlighting new research opportunities. We describe the functional environment around DHCR7, including pharmacological DHCR7 inhibitors and cholesterol and vitamin D synthesis. Using PubMed, we investigated the fetal outcomes following prenatal exposure to DHCR7 modulators. First-trimester exposure to DHCR7 inhibitors resulted in outcomes similar to those of known teratogens (50 vs 48% born-healthy). DHCR7 activity should be considered during drug development and prenatal toxicity assessment.The Pharmacogenomics Journal advance online publication, 12 July 2016; doi:10.1038/tpj.2016.48.

PMID: 27401223 [PubMed - as supplied by publisher]

Lithium-responsive genes and gene networks in bipolar disorder patient-derived lymphoblastoid cell lines.

Pharmacogenomics J. 2016 Jul 12;

Authors: Breen MS, White CH, Shekhtman T, Lin K, Looney D, Woelk CH, Kelsoe JR

Abstract
Lithium (Li) is the mainstay mood stabilizer for the treatment of bipolar disorder (BD), although its mode of action is not yet fully understood nor is it effective in every patient. We sought to elucidate the mechanism of action of Li and to identify surrogate outcome markers that can be used to better understand its therapeutic effects in BD patients classified as good (responders) and poor responders (nonresponders) to Li treatment. To accomplish these goals, RNA-sequencing gene expression profiles of lymphoblastoid cell lines (LCLs) were compared between BD Li responders and nonresponders with healthy controls before and after treatment. Several Li-responsive gene coexpression networks were discovered indicating widespread effects of Li on diverse cellular signaling systems including apoptosis and defense response pathways, protein processing and response to endoplasmic reticulum stress. Individual gene markers were also identified, differing in response to Li between BD responders and nonresponders, involved in processes of cell cycle and nucleotide excision repair that may explain part of the heterogeneity in clinical response to treatment. Results further indicated a Li gene expression signature similar to that observed with clonidine treatment, an α2-adrenoceptor agonist. These findings provide a detailed mechanism of Li in LCLs and highlight putative surrogate outcome markers that may permit for advanced treatment decisions to be made and for facilitating recovery in BD patients.The Pharmacogenomics Journal advance online publication, 12 July 2016; doi:10.1038/tpj.2016.50.

PMID: 27401222 [PubMed - as supplied by publisher]

Genotype-guided versus standard vitamin K antagonist dosing algorithms in patients initiating anticoagulation. A systematic review and meta-analysis.

Thromb Haemost. 2015 Oct;114(4):768-77

Authors: Belley-Cote EP, Hanif H, D'Aragon F, Eikelboom JW, Anderson JL, Borgman M, Jonas DE, Kimmel SE, Manolopoulos VG, Baranova E, Maitland-van der Zee AH, Pirmohamed M, Whitlock RP

Abstract
Variability in vitamin K antagonist (VKA) dosing is partially explained by genetic polymorphisms. We performed a meta-analysis to determine whether genotype-guided VKA dosing algorithms decrease a composite of death, thromboembolic events and major bleeding (primary outcome) and improve time in therapeutic range (TTR). We searched MEDLINE, EMBASE, CENTRAL, trial registries and conference proceedings for randomised trials comparing genotype-guided and standard (non genotype-guided) VKA dosing algorithms in adults initiating anticoagulation. Data were pooled using a random effects model. Of the 12 included studies (3,217 patients), six reported all components of the primary outcome of mortality, thromboembolic events and major bleeding (2,223 patients, 87 events). Our meta-analysis found no significant difference between groups for the primary outcome (relative risk 0.85, 95% confidence interval [CI] 0.54-1.34; heterogeneity Χ(²)=4.46, p=0.35, I(²)=10%). Based on 10 studies (2,767 patients), TTR was significantly higher in the genotype-guided group (mean difference (MD) 4.31%; 95% CI 0.35, 8.26; heterogeneity Χ(²)=43.31, p<0.001, I(²)=79%). Pre-specified exploratory analyses demonstrated that TTR was significantly higher when genotype-guided dosing was compared with fixed VKA dosing (6 trials, 997 patients: MD 8.41%; 95% CI 3.50,13.31; heterogeneity Χ(²)=15.18, p=0.01, I(²)=67%) but not when compared with clinical algorithm-guided dosing (4 trials, 1,770 patients: MD -0.29%; 95% CI -2.48,1.90; heterogeneity Χ(²)=1.53, p=0.68, I(²)=0%; p for interaction=0.002). In conclusion, genotype-guided compared with standard VKA dosing algorithms were not found to decrease a composite of death, thromboembolism and major bleeding, but did result in improved TTR. An improvement in TTR was observed in comparison with fixed VKA dosing algorithms, but not with clinical algorithms.

PMID: 26158747 [PubMed - indexed for MEDLINE]

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens.

PLoS Comput Biol. 2016 Jul;12(7):e1005013

Authors: Chasman D, Walters KB, Lopes TJ, Eisfeld AJ, Kawaoka Y, Roy S

Abstract
Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection.

PMID: 27403523 [PubMed - as supplied by publisher]

Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks.

Biomed Res Int. 2016;2016:6186281

Authors: Lin S, Yin YA, Jiang X, Sahni N, Yi S

Abstract
The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative "OMICs" arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine.

PMID: 27403431 [PubMed - in process]

Graphics processing units in bioinformatics, computational biology and systems biology.

Brief Bioinform. 2016 Jul 8;

Authors: Nobile MS, Cazzaniga P, Tangherloni A, Besozzi D

Abstract
Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools.

PMID: 27402792 [PubMed - as supplied by publisher]

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

J Integr Bioinform. 2016;13(1):284

Authors: Almeida D, Azevedo V, Silva A, Baumbach J

Abstract
Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

PMID: 27402693 [PubMed - in process]

The Notch meeting: an odyssey from structure to function.

Development. 2016 Feb 15;143(4):547-53

Authors: Chitnis A, Balle-Cuif L

Abstract
The Notch signaling pathway plays fundamental roles in diverse developmental processes. Studies of the basic biology of Notch function have provided insights into how its dysfunction contributes to multi-systemic diseases and cancer. In addition, our understanding of Notch signaling in maintaining stem/progenitor cell populations is revealing new avenues for rekindling regeneration. The Notch IX meeting, which was held in Athens, Greece in October 2015, brought together scientists working on different model systems and studying Notch signaling in various contexts. Here, we provide a summary of the key points that were presented at the meeting. Although we focus on the molecular mechanisms that determine Notch signaling and its role in development, we also cover talks describing roles for Notch in adulthood. Together, the talks revealed how interactions between adjacent cells mediated by Notch regulate development and physiology at multiple levels.

PMID: 26884393 [PubMed - indexed for MEDLINE]

Slowing Down of Recovery as Generic Risk Marker for Acute Severity Transitions in Chronic Diseases.

Crit Care Med. 2016 Mar;44(3):601-6

Authors: Olde Rikkert MG, Dakos V, Buchman TG, Boer Rd, Glass L, Cramer AO, Levin S, van Nes E, Sugihara G, Ferrari MD, Tolner EA, van de Leemput I, Lagro J, Melis R, Scheffer M

Abstract
OBJECTIVE: We propose a novel paradigm to predict acute attacks and exacerbations in chronic episodic disorders such as asthma, cardiac arrhythmias, migraine, epilepsy, and depression. A better generic understanding of acute transitions in chronic dynamic diseases is increasingly important in critical care medicine because of the higher prevalence and incidence of these chronic diseases in our aging societies.
DATA SOURCES: PubMed, Medline, and Web of Science.
STUDY SELECTION: We selected studies from biology and medicine providing evidence of slowing down after a perturbation as a warning signal for critical transitions.
DATA EXTRACTION: Recent work in ecology, climate, and systems biology has shown that slowing down of recovery upon perturbations can indicate loss of resilience across complex, nonlinear biologic systems that are approaching a tipping point. This observation is supported by the empiric studies in pathophysiology and controlled laboratory experiments with other living systems, which can flip from one state of clinical balance to a contrasting one. We discuss examples of such evidence in bodily functions such as blood pressure, heart rate, mood, and respiratory regulation when a tipping point for a transition is near.
CONCLUSIONS: We hypothesize that in a range of chronic episodic diseases, indicators of critical slowing down, such as rising variance and temporal correlation, may be used to assess the risk of attacks, exacerbations, and even mortality. Identification of such early warning signals over a range of diseases will enhance the understanding of why, how, and when attacks and exacerbations will strike and may thus improve disease management in critical care medicine.

PMID: 26765499 [PubMed - indexed for MEDLINE]

Biomarkers in Sporadic and Familial Alzheimer's Disease.

J Alzheimers Dis. 2015;47(2):291-317

Authors: Lista S, O'Bryant SE, Blennow K, Dubois B, Hugon J, Zetterberg H, Hampel H

Abstract
Most forms of Alzheimer's disease (AD) are sporadic (sAD) or inherited in a non-Mendelian fashion, and less than 1% of cases are autosomal-dominant. Forms of sAD do not exhibit familial aggregation and are characterized by complex genetic and environmental interactions. Recently, the expansion of genomic methodologies, in association with substantially larger combined cohorts, has resulted in various genome-wide association studies that have identified several novel genetic associations of AD. Currently, the most effective methods for establishing the diagnosis of AD are defined by multi-modal pathways, starting with clinical and neuropsychological assessment, cerebrospinal fluid (CSF) analysis, and brain-imaging procedures, all of which have significant cost- and access-to-care barriers. Consequently, research efforts have focused on the development and validation of non-invasive and generalizable blood-based biomarkers. Among the modalities conceptualized by the systems biology paradigm and utilized in the "exploratory biomarker discovery arena", proteome analysis has received the most attention. However, metabolomics, lipidomics, transcriptomics, and epigenomics have recently become key modalities in the search for AD biomarkers. Interestingly, biomarker changes for familial AD (fAD), in many but not all cases, seem similar to those for sAD. The integration of neurogenetics with systems biology/physiology-based strategies and high-throughput technologies for molecular profiling is expected to help identify the causes, mechanisms, and biomarkers associated with the various forms of AD. Moreover, in order to hypothesize the dynamic trajectories of biomarkers through disease stages and elucidate the mechanisms of biomarker alterations, updated and more sophisticated theoretical models have been proposed for both sAD and fAD.

PMID: 26401553 [PubMed - indexed for MEDLINE]

Silica distinctively affects cell wall features and lignocellulosic saccharification with large enhancement on biomass production in rice.

Plant Sci. 2015 Oct;239:84-91

Authors: Zhang J, Zou W, Li Y, Feng Y, Zhang H, Wu Z, Tu Y, Wang Y, Cai X, Peng L

Abstract
Rice is a typical silicon-accumulating crop with enormous biomass residues for biofuels. Silica is a cell wall component, but its effect on the plant cell wall and biomass production remains largely unknown. In this study, a systems biology approach was performed using 42 distinct rice cell wall mutants. We found that silica levels are significantly positively correlated with three major wall polymers, indicating that silica is associated with the cell wall network. Silicon-supplied hydroculture analysis demonstrated that silica distinctively affects cell wall composition and major wall polymer features, including cellulose crystallinity (CrI), arabinose substitution degree (reverse Xyl/Ara) of xylans, and sinapyl alcohol (S) proportion in three typical rice mutants. Notably, the silicon supplement exhibited dual effects on biomass enzymatic digestibility in the mutant and wild type (NPB) after pre-treatments with 1% NaOH and 1% H2SO4. In addition, silicon supply largely enhanced plant height, mechanical strength and straw biomass production, suggesting that silica rescues mutant growth defects. Hence, this study provides potential approaches for silicon applications in biomass process and bioenergy rice breeding.

PMID: 26398793 [PubMed - indexed for MEDLINE]

BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

Database (Oxford). 2016;2016

Authors: Rinaldi F, Ellendorff TR, Madan S, Clematide S, van der Lek A, Mevissen T, Fluck J

Abstract
Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text.

PMID: 27402677 [PubMed - in process]

Extracting Information from Electronic Medical Records to Identify the Obesity Status of a Patient Based on Comorbidities and Bodyweight Measures.

J Med Syst. 2016 Aug;40(8):191

Authors: Figueroa RL, Flores CA

Abstract
Obesity is a chronic disease with an increasing impact on the world's population. In this work, we present a method of identifying obesity automatically using text mining techniques and information related to body weight measures and obesity comorbidities. We used a dataset of 3015 de-identified medical records that contain labels for two classification problems. The first classification problem distinguishes between obesity, overweight, normal weight, and underweight. The second classification problem differentiates between obesity types: super obesity, morbid obesity, severe obesity and moderate obesity. We used a Bag of Words approach to represent the records together with unigram and bigram representations of the features. We implemented two approaches: a hierarchical method and a nonhierarchical one. We used Support Vector Machine and Naïve Bayes together with ten-fold cross validation to evaluate and compare performances. Our results indicate that the hierarchical approach does not work as well as the nonhierarchical one. In general, our results show that Support Vector Machine obtains better performances than Naïve Bayes for both classification problems. We also observed that bigram representation improves performance compared with unigram representation.

PMID: 27402260 [PubMed - in process]

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"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

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Drug repurposing of minocycline against dengue virus infection.

Biochem Biophys Res Commun. 2016 Jul 7;

Authors: Leela SL, Srisawat C, Sreekanth GP, Noisakran S, Yenchitsomanus PT, Limjindaporn T

Abstract
Dengue virus infection is one of the most common arthropod-borne viral diseases. A complex interplay between host and viral factors contributes to the severity of infection. The antiviral effects of three antibiotics, lomefloxacin, netilmicin, and minocycline, were examined in this study, and minocycline was found to be a promising drug. This antiviral effect was confirmed in all four serotypes of the virus. The effects of minocycline at various stages of the viral life cycle, such as during viral RNA synthesis, intracellular envelope protein expression, and the production of infectious virions, were examined and found to be significantly reduced by minocycline treatment. Minocycline also modulated host factors, including the phosphorylation of extracellular signal-regulated kinase1/2 (ERK1/2). The transcription of antiviral genes, including 2'-5'-oligoadenylate synthetase 1 (OAS1), 2'-5'-oligoadenylate synthetase 3 (OAS3), and interferon α (IFNA), was upregulated by minocycline treatment. Therefore, the antiviral activity of minocycline may have a potential clinical use against Dengue virus infection.

PMID: 27396621 [PubMed - as supplied by publisher]

Pharmacoethnicity in Paclitaxel-Induced Sensory Peripheral Neuropathy.

Clin Cancer Res. 2015 Oct 1;21(19):4337-46

Authors: Komatsu M, Wheeler HE, Chung S, Low SK, Wing C, Delaney SM, Gorsic LK, Takahashi A, Kubo M, Kroetz DL, Zhang W, Nakamura Y, Dolan ME

Abstract
PURPOSE: Paclitaxel is used worldwide in the treatment of breast, lung, ovarian, and other cancers. Sensory peripheral neuropathy is an associated adverse effect that cannot be predicted, prevented, or mitigated. To better understand the contribution of germline genetic variation to paclitaxel-induced peripheral neuropathy, we undertook an integrative approach that combines genome-wide association study (GWAS) data generated from HapMap lymphoblastoid cell lines (LCL) and Asian patients.
METHODS: GWAS was performed with paclitaxel-induced cytotoxicity generated in 363 LCLs and with paclitaxel-induced neuropathy from 145 Asian patients. A gene-based approach was used to identify overlapping genes and compare with a European clinical cohort of paclitaxel-induced neuropathy. Neurons derived from human-induced pluripotent stem cells were used for functional validation of candidate genes.
RESULTS: SNPs near AIPL1 were significantly associated with paclitaxel-induced cytotoxicity in Asian LCLs (P < 10(-6)). Decreased expression of AIPL1 resulted in decreased sensitivity of neurons to paclitaxel by inducing neurite morphologic changes as measured by increased relative total outgrowth, number of processes and mean process length. Using a gene-based analysis, there were 32 genes that overlapped between Asian LCL cytotoxicity and Asian patient neuropathy (P < 0.05), including BCR. Upon BCR knockdown, there was an increase in neuronal sensitivity to paclitaxel as measured by neurite morphologic characteristics.
CONCLUSIONS: We identified genetic variants associated with Asian paclitaxel-induced cytotoxicity and functionally validated the AIPL1 and BCR in a neuronal cell model. Furthermore, the integrative pharmacogenomics approach of LCL/patient GWAS may help prioritize target genes associated with chemotherapeutic-induced peripheral neuropathy.

PMID: 26015512 [PubMed - indexed for MEDLINE]