Blocking NS3-NS4B interaction inhibits dengue virus in non-human primates.

Dengue is a major health threat and the number of symptomatic infections caused by the four dengue serotypes is estimated to be 96 million1 with annually around 10,000 deaths2. However, no antiviral drugs are available for the treatment or prophylaxis of dengue. We recently described the interaction between non-structural proteins NS3 and NS4B as a promising target for the development of pan-serotype dengue virus (DENV) inhibitors3. Here we present JNJ-1802-a highly potent DENV inhibitor that blocks the NS3-NS4B interaction within the viral replication complex. JNJ-1802 exerts picomolar to low nanomolar in vitro antiviral activity, a high barrier to resistance and potent in vivo efficacy in mice against infection with any of the four DENV serotypes. Finally, we demonstrate that the small-molecule inhibitor JNJ-1802 is highly effective against viral infection with DENV-1 or DENV-2 in non-human primates. JNJ-1802 has successfully completed a phase I first-in-human clinical study in healthy volunteers and was found to be safe and well tolerated4. These findings support the further clinical development of JNJ-1802, a first-in-class antiviral agent against dengue, which is now progressing in clinical studies for the prevention and treatment of dengue.

A pan-serotype dengue virus inhibitor targeting the NS3-NS4B interaction.

Dengue virus causes approximately 96 million symptomatic infections annually, manifesting as dengue fever or occasionally as severe dengue1,2. There are no antiviral agents available to prevent or treat dengue. Here, we describe a highly potent dengue virus inhibitor (JNJ-A07) that exerts nanomolar to picomolar activity against a panel of 21 clinical isolates that represent the natural genetic diversity of known genotypes and serotypes. The molecule has a high barrier to resistance and prevents the formation of the viral replication complex by blocking the interaction between two viral proteins (NS3 and NS4B), thus revealing a previously undescribed mechanism of antiviral action. JNJ-A07 has a favourable pharmacokinetic profile that results in outstanding efficacy against dengue virus infection in mouse infection models. Delaying start of treatment until peak viraemia results in a rapid and significant reduction in viral load. An analogue is currently in further development.

Analyzing magnetic bead QuantiGene® Plex 2.0 gene expression data in high throughput mode using QGprofiler.

BACKGROUND: The QuantiGene® Plex 2.0 platform (ThermoFisher Scientific) combines bDNA with the Luminex/xMAP magnetic bead capturing technology to assess differential gene expression in a compound exposure setting. This technology allows multiplexing in a single well of a 96 or 384 multi-well plate and can thus be used in high throughput drug discovery mode. Data interpretation follows a three-step normalization/transformation flow in which raw median fluorescent gene signals are transformed to fold change values with the use of proper housekeeping genes and negative controls. Clear instructions on how to assess the data quality and tools to perform this analysis in high throughput mode are, however, currently lacking. RESULTS: In this paper we introduce QGprofiler, an open source R based shiny application. QGprofiler allows for proper QuantiGene® Plex 2.0 assay optimization, choice of housekeeping genes and data pre-processing up to fold change, including appropriate QC metrics. In addition, QGprofiler allows for an Akaike information criterion based dose response fold change model selection and has a built-in tool to detect the cytotoxic potential of compounds evaluated in a high throughput screening campaign. CONCLUSION: QGprofiler is a user friendly, open source available R based shiny application, which is developed to support drug discovery campaigns. In this context, entire compound libraries/series can be tested in dose response against a gene signature of choice in search for new disease relevant chemical entities. QGprofiler is available at: https://qgprofiler.openanalytics.eu/app/QGprofiler.

Integrating High-Dimensional Transcriptomics and Image Analysis Tools into Early Safety Screening: Proof of Concept for a New Early Drug Development Strategy.

During drug discovery and development, the early identification of adverse effects is expected to reduce costly late-stage failures of candidate drugs. As risk/safety assessment takes place rather late during the development process and due to the limited ability of animal models to predict the human situation, modern unbiased high-dimensional biology readouts are sought, such as molecular signatures predictive for in vivo response using high-throughput cell-based assays. In this theoretical proof of concept, we provide findings of an in-depth exploration of a single chemical core structure. Via transcriptional profiling, we identified a subset of close analogues that commonly downregulate multiple tubulin genes across cellular contexts, suggesting possible spindle poison effects. Confirmation via a qualified toxicity assay (in vitro micronucleus test) and the identification of a characteristic aggregate-formation phenotype via exploratory high-content imaging validated the initial findings. SAR analysis triggered the synthesis of a new set of compounds and allowed us to extend the series showing the genotoxic effect. We demonstrate the potential to flag toxicity issues by utilizing data from exploratory experiments that are typically generated for target evaluation purposes during early drug discovery. We share our thoughts on how this approach may be incorporated into drug development strategies.

The influence of resolution on the predictive power of spatial heterogeneity measures as biomarkers of liver fibrosis.

Spatial heterogeneity of cells in liver biopsies can be used as biomarker for disease severity of patients. This heterogeneity can be quantified by non-parametric statistics of point pattern data, which make use of an aggregation of the point locations. The method and scale of aggregation are usually chosen ad hoc, despite values of the aforementioned statistics being heavily dependent on them. Moreover, in the context of measuring heterogeneity, increasing spatial resolution will not endlessly provide more accuracy. The question then becomes how changes in resolution influence heterogeneity indicators, and subsequently how they influence their predictive abilities. In this paper, cell level data of liver biopsy tissue taken from chronic Hepatitis B patients is used to analyze this issue. Firstly, Morisita-Horn indices, Shannon indices and Getis-Ord statistics were evaluated as heterogeneity indicators of different types of cells, using multiple resolutions. Secondly, the effect of resolution on the predictive performance of the indices in an ordinal regression model was investigated, as well as their importance in the model. A simulation study was subsequently performed to validate the aforementioned methods. In general, for specific heterogeneity indicators, a downward trend in predictive performance could be observed. While for local measures of heterogeneity a smaller grid-size is outperforming, global measures have a better performance with medium-sized grids. In addition, the use of both local and global measures of heterogeneity is recommended to improve the predictive performance.

Measures of spatial heterogeneity in the liver tissue micro-environment as predictive factors for fibrosis score.

The organization and interaction between hepatocytes and other hepatic non-parenchymal cells plays a pivotal role in maintaining normal liver function and structure. Although spatial heterogeneity within the tumor micro-environment has been proven to be a fundamental feature in cancer progression, the role of liver tissue topology and micro-environmental factors in the context of liver damage in chronic infection has not been widely studied yet. We obtained images from 110 core needle biopsies from a cohort of chronic hepatitis B patients with different fibrosis stages according to METAVIR score. The tissue sections were immunofluorescently stained and imaged to determine the locations of CD45 positive immune cells and HBsAg-negative and HBsAg-positive hepatocytes within the tissue. We applied several descriptive techniques adopted from ecology, including Getis-Ord, the Shannon Index and the Morisita-Horn Index, to quantify the extent to which immune cells and different types of liver cells co-localize in the tissue biopsies. Additionally, we modeled the spatial distribution of the different cell types using a joint log-Gaussian Cox process and proposed several features to quantify spatial heterogeneity. We then related these measures to the patient fibrosis stage by using a linear discriminant analysis approach. Our analysis revealed that the co-localization of HBsAg-negative hepatocytes with immune cells and the co-localization of HBsAg-positive hepatocytes with immune cells are equally important factors for explaining the METAVIR score in chronic hepatitis B patients. Moreover, we found that if we allow for an error of 1 on the METAVIR score, we are able to reach an accuracy of around 80%. With this study we demonstrate how methods adopted from ecology and applied to the liver tissue micro-environment can be used to quantify heterogeneity and how these approaches can be valuable in biomarker analyses for liver topology.

A single, oral dose of the TLR7 agonist JNJ-64794964 induces transcriptomic and phenotypic changes in peripheral immune cells in healthy adults.

BACKGROUND: Chronic hepatitis B (CHB) is responsible for major disease burden worldwide. However, the number of available therapies is limited; cure remains an elusive goal. JNJ-64794964 (JNJ-4964) is an oral toll-like receptor-7 (TLR7) agonist being evaluated for the treatment of CHB. Here, we investigated the capacity of JNJ-4964 to induce transcriptomic and immune cell changes in peripheral blood in healthy volunteers. METHODS: Peripheral blood was collected in the JNJ-4964 first-in-human phase 1 trial at multiple time points to assess transcriptomics and changes in frequency and phenotype of peripheral-blood mononuclear cells. Correlation of changes to JNJ-4964 exposure (Cmax) and changes in cytokine levels (C-X-C motif chemokine ligand 10 [CXCL10] and interferon alpha [IFN-α]) were evaluated. RESULTS: Fifty-nine genes, mainly interferon-stimulated genes, were up-regulated between 6 hours and 5 days after JNJ-4964 administration. JNJ-4964 increased frequencies of CD69, CD134, CD137, and/or CD253-expressing natural killer (NK) cells, indicative of NK cell activation. These changes correlated with Cmax, increase of CXCL10, and induction of IFN-α and were observed at IFN-α levels that are associated with no/acceptable flu-like adverse events. JNJ-4964 administration resulted in increased frequencies of CD86-expressing B cells, indicative of B-cell activation. These changes were predominantly observed at high IFN-α levels, which are associated with flu-like adverse events. CONCLUSIONS: JNJ-4964 administration led to changes in transcriptional profiles and immune cell activation phenotype, particularly for NK cells and B cells. Together, these changes could represent a set of biomarkers for the characterization of the immune response in CHB patients receiving TLR7 agonists.

Sustained Liver HBsAg Loss and Clonal T- and B-Cell Expansion upon Therapeutic DNA Vaccination Require Low HBsAg Levels.

BACKGROUND: Suppression of HBV DNA, inhibition of HBV surface (HBsAg) production and therapeutic vaccination to reverse HBV-specific T-cell exhaustion in chronic HBV patients are likely required to achieve a functional cure. In the AAV-HBV mouse model, therapeutic vaccination can be effective in clearing HBV when HBsAg levels are low. Using a single-cell approach, we investigated the liver immune environment with different levels of HBsAg and sustained HBsAg loss through treatment with a GalNAc-HBV-siRNA followed by therapeutic vaccination. METHODS: AAV-HBV-transduced C57BL/6 mice were treated with GalNAc-HBV-siRNA to lower HBsAg levels and then vaccinated using a DNA vaccine. We used single-cell RNA and V(D)J sequencing to understand liver immune microenvironment changes. RESULTS: GalNAc-HBV-siRNA, followed by therapeutic vaccination, achieved sustained HBsAg loss in all mice. This was accompanied by CD4 follicular helper T-cell induction, polyclonal activation of CD8 T cells and clonal expansion of plasma cells that were responsible for antibody production. CONCLUSIONS: This study provides novel insights into liver immune changes at the single-cell level, highlighting the correlation between induced reduction of HBsAg levels and clonal expansion of CD4, CD8 T cells and plasma cells in the liver upon HBV siRNA and subsequent therapeutic vaccination.

Single-cell immune profiling reveals markers of emergency myelopoiesis that distinguish severe from mild respiratory syncytial virus disease in infants.

Whereas most infants infected with respiratory syncytial virus (RSV) show no or only mild symptoms, an estimated 3 million children under five are hospitalized annually due to RSV disease. This study aimed to investigate biological mechanisms and associated biomarkers underlying RSV disease heterogeneity in young infants, enabling the potential to objectively categorize RSV-infected infants according to their medical needs. Immunophenotypic and functional profiling demonstrated the emergence of immature and progenitor-like neutrophils, proliferative monocytes (HLA-DRLow , Ki67+), impaired antigen-presenting function, downregulation of T cell response and low abundance of HLA-DRLow B cells in severe RSV disease. HLA-DRLow monocytes were found as a hallmark of RSV-infected infants requiring hospitalization. Complementary transcriptomics identified genes associated with disease severity and pointed to the emergency myelopoiesis response. These results shed new light on mechanisms underlying the pathogenesis and development of severe RSV disease and identified potential new candidate biomarkers for patient stratification.

Therapeutic efficacy of a respiratory syncytial virus fusion inhibitor.

Respiratory syncytial virus is a major cause of acute lower respiratory tract infection in young children, immunocompromised adults, and the elderly. Intervention with small-molecule antivirals specific for respiratory syncytial virus presents an important therapeutic opportunity, but no such compounds are approved today. Here we report the structure of JNJ-53718678 bound to respiratory syncytial virus fusion (F) protein in its prefusion conformation, and we show that the potent nanomolar activity of JNJ-53718678, as well as the preliminary structure-activity relationship and the pharmaceutical optimization strategy of the series, are consistent with the binding mode of JNJ-53718678 and other respiratory syncytial virus fusion inhibitors. Oral treatment of neonatal lambs with JNJ-53718678, or with an equally active close analog, efficiently inhibits established acute lower respiratory tract infection in the animals, even when treatment is delayed until external signs of respiratory syncytial virus illness have become visible. Together, these data suggest that JNJ-53718678 is a promising candidate for further development as a potential therapeutic in patients at risk to develop respiratory syncytial virus acute lower respiratory tract infection.Respiratory syncytial virus causes lung infections in children, immunocompromised adults, and in the elderly. Here the authors show that a chemical inhibitor to a viral fusion protein is effective in reducing viral titre and ameliorating infection in rodents and neonatal lambs.