Background. Dengue is the most common arboviral infection of humans. There are currently no specific treatments for dengue. Balapiravir is a prodrug of a nucleoside analogue (called R1479) and an inhibitor of hepatitis C virus replication in vivo.Methods. We conducted in vitro experiments to determine the potency of balapiravir against dengue viruses and then an exploratory, dose-escalating, randomized placebo-controlled trial in adult male patients with dengue with <48 hours of fever.Results. The clinical and laboratory adverse event profile in patients receiving balapiravir at doses of 1500 mg (n = 10) or 3000 mg (n = 22) orally for 5 days was similar to that of patients receiving placebo (n = 32), indicating balapiravir was well tolerated. However, twice daily assessment of viremia and daily assessment of NS1 antigenemia indicated balapiravir did not measurably alter the kinetics of these virological markers, nor did it reduce the fever clearance time. The kinetics of plasma cytokine concentrations and the whole blood transcriptional profile were also not attenuated by balapiravir treatment.Conclusions. Although this trial, the first of its kind in dengue, does not support balapiravir as a candidate drug, it does establish a framework for antiviral treatment trials in dengue and provides the field with a clinically evaluated benchmark molecule.Clinical Trials Registration. NCT01096576.

MotivationGene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions.ResultsThe ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA’s gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists’ feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes.Availability and ImplementationEGSEA is available as an R package at http://www.bioconductor.org/packages/EGSEA/. The gene sets collections are available in the R package EGSEAdata from http://www.bioconductor.org/packages/EGSEAdata/.Supplementary information Supplementary data are available at Bioinformatics online.

Interleukin-3 (IL-3) is an activated T cell product that bridges innate and adaptive immunity and contributes to several immunopathologies. Here, we report the crystal structure of the IL-3 receptor α chain (IL3Rα) in complex with the anti-leukemia antibody CSL362 that reveals the N-terminal domain (NTD), a domain also present in the granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-5, and IL-13 receptors, adopting unique "open" and classical "closed" conformations. Although extensive mutational analyses of the NTD epitope of CSL362 show minor overlap with the IL-3 binding site, CSL362 only inhibits IL-3 binding to the closed conformation, indicating alternative mechanisms for blocking IL-3 signaling. Significantly, whereas "open-like" IL3Rα mutants can simultaneously bind IL-3 and CSL362, CSL362 still prevents the assembly of a higher-order IL-3 receptor-signaling complex. The discovery of open forms of cytokine receptors provides the framework for development of potent antibodies that can achieve a "double hit" cytokine receptor blockade.

Motivation: Gene set enrichment (GSE) analysis allows researchers to efficiently extract biological insight from long lists of differentially expressed genes by interrogating them at a systems level. In recent years, there has been a proliferation of GSE analysis methods and hence it has become increasingly difficult for researchers to select an optimal GSE tool based on their particular dataset. Moreover, the majority of GSE analysis methods do not allow researchers to simultaneously compare gene set level results between multiple experimental conditions. Results: The ensemble of genes set enrichment analyses (EGSEA) is a method developed for RNA-sequencing data that combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets. EGSEA's gene set database contains around 25 000 gene sets from sixteen collections. It has multiple visualization capabilities that allow researchers to view gene sets at various levels of granularity. EGSEA has been tested on simulated data and on a number of human and mouse datasets and, based on biologists' feedback, consistently outperforms the individual tools that have been combined. Our evaluation demonstrates the superiority of the ensemble approach for GSE analysis, and its utility to effectively and efficiently extrapolate biological functions and potential involvement in disease processes from lists of differentially regulated genes. Availability and Implementation: EGSEA is available as an R package at http://www.bioconductor. org/packages/EGSEA/. The gene sets collections are available in the R package EGSEAdata from

To date, the major target of biologic therapeutics in systemic lupus erythematosus (SLE) has been the B cell, which produces pathogenic autoantibodies. Recently, targeting type I IFN, which is elaborated by plasmacytoid dendritic cells (pDCs) in response to endosomal TLR7 and TLR9 stimulation by SLE immune complexes, has shown promising results. pDCs express high levels of the IL-3Rα chain (CD123), suggesting an alternative potential targeting strategy. We have developed an anti-CD123 monoclonal antibody, CSL362, and show here that it affects key cell types and cytokines that contribute to SLE. CSL362 potently depletes pDCs via antibody-dependent cell-mediated cytotoxicity, markedly reducing TLR7, TLR9, and SLE serum-induced IFN-α production and IFN-α-upregulated gene expression. The antibody also inhibits TLR7- and TLR9-induced plasmablast expansion by reducing IFN-α and IL-6 production. These effects are more pronounced than with IFN-α blockade alone, possibly because pDC depletion reduces production of other IFN subtypes, such as type III, as well as non-IFN proinflammatory cytokines, such as IL-6. In addition, CSL362 depletes basophils and inhibits IL-3 signaling. These effects were confirmed in cells derived from a heterogeneous population of SLE donors, various IFN-dependent autoimmune diseases, and healthy controls. We also demonstrate in vivo activity of CSL362 following its s.c. administration to cynomolgus monkeys. This spectrum of effects provides a preclinical rationale for the therapeutic evaluation of CSL362 in SLE.