Randomised phase 2 study (JADE) of the HBV capsid assembly modulator JNJ-56136379 with or without a nucleos(t)ide analogue in patients with chronic hepatitis B infection.

OBJECTIVE: We present the final analysis results of the phase 2 JADE study (ClinicalTrials.gov Identifier: NCT03361956). DESIGN: 232 patients with chronic hepatitis B (CHB) not currently treated at study start (NCT) at study start or virologically suppressed were randomised to receive 75 mg (part 1) or 250 mg (part 2) JNJ-56136379, a hepatitis B virus (HBV)-capsid assembly modulator, one time per day or placebo with nucleos(t)ide analogue (NA) (tenofovir disoproxil fumarate/entecavir) or JNJ-56136379 alone (NCT-only) for ≥24 and ≤48 weeks. RESULTS: In patients who are NCT hepatitis B e-antigen (HBeAg) positive, JNJ-56136379 75 mg+NA and 250 mg+NA showed limited mean (SE) hepatitis B surface antigen (HBsAg) declines (0.14 (0.10) and 0.41 (0.15), respectively) from baseline at Week 24 (primary endpoint; placebo+NA: 0.25 (0.11) log10 international unit (IU)/mL).In patients who are NCT HBeAg positive, mean (SE) HBV DNA declines at Week 24 were 5.53 (0.23) and 5.88 (0.34) for JNJ-56136379 75 mg+NA and 250 mg+NA, respectively, versus 5.21 (0.42) log10 IU/mL for placebo+NA. In NCT patients, mean (SE) HBV RNA declines were 2.96 (0.23) and 3.15 (0.33) versus 1.33 (0.32) log10 copies/mL, respectively.Patients with HBsAg declines had HBeAg and hepatitis B core-related antigen (HBcrAg) declines and some early on-treatment isolated alanine aminotransferase flares. Viral breakthrough occurred with JNJ-56136379 monotherapy with the emerging resistant-variant T33N, but not with JNJ-56136379+NA. JNJ-56136379 treatment beyond Week 24 had a generally small additional effect on viral markers.No study treatment-related serious adverse events or clinically significant changes in laboratory parameters occurred. CONCLUSIONS: In patients with non-cirrhotic CHB, JNJ-56136379+NA showed pronounced reductions in HBV DNA and HBV RNA, limited HBsAg or HBeAg declines in patients who are NCT HBeAg positive, and was well tolerated, but no clear benefit with regards to efficacy of JNJ-56136379 over NA was observed.

Safety, antiviral activity and pharmacokinetics of JNJ-64530440, a novel capsid assembly modulator, as 4 week monotherapy in treatment-naive patients with chronic hepatitis B virus infection.

OBJECTIVES: We investigated JNJ-64530440 (a hepatitis B virus capsid assembly modulator) safety, antiviral activity and pharmacokinetics in patients with chronic hepatitis B (CHB) (Phase 1b, NCT03439488). METHODS: Twenty treatment-naive, HBeAg-positive or -negative CHB patients were randomized 4|:|1 to JNJ-64530440 750 mg once or twice daily, or placebo for 28 days. RESULTS: All patients (mean age 43.8 years; 85% male; 70% White; 20% HBeAg positive) completed dosing/28 day follow-up. Mild-to-moderate treatment-emergent adverse events occurred in 3/4 (placebo), 6/8 (once-daily) and 4/8 (twice-daily) patients; mostly fatigue, increased alanine aminotransferase, decreased neutrophil count, and headache. Hepatitis B virus (HBV) DNA was substantially reduced; mean (range) changes from baseline at day 29 were: -3.2 (-2.4 to -3.9) (once-daily) and -3.3 (-2.6 to -4.1) (twice-daily) log10 IU/mL; placebo 0.1 (0.7 to -0.6) log10 IU/mL. HBV DNA levels were below the lower limit of quantification (LLOQ) in 5/8 (once-daily) and 3/8 (twice-daily) patients. For patients with detectable baseline HBV RNA, mean (SE) changes versus baseline in HBV RNA at day 29 were: -2.65 (0.81) (once-daily) and -2.94 (0.33) (twice-daily) log10 copies/mL. HBV RNA levels were 'target not detected' in 4/6 (once-daily) and 3/7 (twice-daily) patients. JNJ-64530440 pharmacokinetics in CHB patients were comparable with those in healthy volunteers. CONCLUSIONS: JNJ-64530440 750 mg once-daily or twice-daily for 28 days was well tolerated and achieved potent antiviral activity in CHB patients.

JNJ-56136379, an HBV Capsid Assembly Modulator, Is Well-Tolerated and Has Antiviral Activity in a Phase 1 Study of Patients With Chronic Infection.

BACKGROUND & AIMS: JNJ-56136379 (JNJ-6379), a capsid assembly modulator that blocks hepatitis B virus (HBV) replication, was well tolerated and demonstrated dose-proportional pharmacokinetics in healthy participants in part 1 of its first clinical trial. In part 2, we have evaluated the safety, pharmacokinetics, and antiviral activity of multiple doses of JNJ-6379 in patients with chronic HBV infection. METHODS: We performed a double-blind study of 57 treatment-naïve patients with HB e antigen-positive or -negative (74%) chronic HBV infection without cirrhosis. Patients were randomly assigned to groups given JNJ-6379 at 25 mg (100 mg loading dose), 75 mg, 150 mg, or 250 mg or placebo daily for 4 weeks with an 8-week follow-up period. RESULTS: Twenty-three (56%) of 41 patients given JNJ-6379 had at least 1 adverse event (AE) during treatment, compared with 10 (63%) of 16 patients given placebo. No serious AEs were reported during the treatment period. Three patients (7%) given JNJ-6379 vs none given placebo had grade 3 AEs; of these, 1 patient (150 mg) also had an isolated grade 4 increase in the level of alanine aminotransferase that led to treatment discontinuation. JNJ-6379 exposure increased with dose, with time-linear pharmacokinetics. HBV-DNA and HBV-RNA decreased from baseline in patients receiving all doses of JNJ-6379, independently of viral genotype and HB e antigen status. On day 29, 13 (32%) of 41 patients had levels of HBV DNA below the lower limit of quantification. No clinically significant changes in levels of HB surface antigen were observed. CONCLUSIONS: In a phase 1 study of treatment-naïve patients with chronic HBV infection, all doses tested of JNJ-6379 were well tolerated, showed dose-dependent pharmacokinetics, and had potent antiviral activity in patients with CHB. The findings support a phase 2a study to evaluate JNJ-6379 ± nucleos(t)ide analogs in patients with chronic HBV infection, which is under way. ClinicalTrials.gov identifier: NCT02662712.

Mean HBsAg decline at week 24 of PEG-IFN-based treatment predicts subsequent rate of HBsAg clearance - suggesting a valuable endpoint for early development HBV trials.

Earlier identification of potentially efficacious treatments in early development trials requires on-treatment response markers. We hypothesized that mean week 12 or 24 HBsAg decline could be a useful marker for subsequent off-treatment sustained HBsAg clearance at the treatment arm level in HBV trials. We used individual patient data from the studies HBV 9901 (peginterferon [PEG-IFN] versus PEG-IFN+lamivudine for HBeAg-positive CHB), PARC (PEG-IFN±ribavirin for HBeAg-negative CHB) and published data from 0149 (PEG-IFN±tenofovir for HBeAg-positive and HBeAg-negative CHB) and LIRA-B (PEG-IFN for HBeAg-positive CHB) to define the relationship between mean week HBsAg decline and HBsAg loss at 6 months post-treatment. A within-study comparison of HBsAg decline at weeks 12 and 24 between patients with or without HBsAg clearance was used to make projections beyond the observed HBsAg data. Across trials, a more pronounced mean HBsAg decline at week 24 was associated with higher rates of subsequent HBsAg loss. Mean HBsAg decline data at week 24 for patients with or without HBsAg clearance from HBV 9901 (4.3 vs 0.5), PARC (4.8 vs 0.3) and 0149 (PEG-IFN+TDF arm; 4.6 vs 0.6) were used to extrapolate this relationship beyond observed rates of HBsAg. An additional mean 1 log10 decline at week 24 versus a comparator arm is expected to translate into a 20%-30% increase in subsequent HBsAg loss during off-treatment follow-up. Observations were similar for week 12 data, but the relationship was less strong. Mean week 24 HBsAg decline predicts subsequent HBsAg loss and could be a valuable and useful early endpoint in HBV-treatment trials.

Antiviral Activity, Safety, and Pharmacokinetics of Capsid Assembly Modulator NVR 3-778 in Patients with Chronic HBV Infection.

BACKGROUND & AIMS: NVR 3-778 is a first-in-class hepatitis B virus (HBV) capsid assembly modulator that can inhibit HBV replication. We performed a proof-of-concept study to examine the safety, pharmacokinetics, and antiviral activity of NVR 3-778 in patients with chronic HBV infection. METHODS: We performed a phase 1 study in 73 hepatitis B envelope antigen (HBeAg)-positive patients with chronic HBV infection without cirrhosis. In a 2-part study (part 1 in New Zealand and part 2 in Hong Kong, Singapore, Taiwan, Korea, and the United States), patients were randomly assigned to groups that were given oral NVR 3-778 (100 mg, 200 mg, or 400 mg daily or 600 mg or 1000 mg twice daily) or placebo for 4 weeks. Additional groups received combination treatment with pegylated interferon (pegIFN) and NVR 3-778 (600 mg twice daily) or pegIFN with placebo. RESULTS: Reductions in serum levels of HBV DNA and HBV RNA were observed in patients receiving ≥1200 mg/d NVR 3-778. The largest mean reduction in HBV DNA was observed in the group given NVR 3-778 plus pegIFN (1.97 log10 IU/mL), compared with the groups given NVR 3-778 or pegIFN alone (1.43 log10 IU/mL and 1.06 log10 IU/mL, respectively). The mean reduction in HBV RNA was also greatest in the group given NVR 3-778 plus pegIFN (2.09 log10 copies/mL), compared with the groups given NVR 3-778 or pegIFN alone (1.42 log10 copies/mL and 0.89 log10 copies/mL, respectively). There was no significant mean reduction in HBsAg during the 4-week treatment period. There were no discontinuations and no pattern of dose-related adverse effects with NVR 3-778. CONCLUSIONS: In a phase 1 study of HBeAg-positive patients with chronic HBV infection without cirrhosis, NVR 3-778 was well tolerated and demonstrated antiviral activity. The agent reduced serum levels of HBV DNA and HBV RNA, to the greatest extent in combination with pegIFN. The observed reductions in HBV RNA confirmed the novel mechanism of NVR 3-778. Clinicaltrials.gov no. NCT02112799 (single-center) and NCT02401737 (multicenter).

Virology analysis of chronic hepatitis B virus-infected patients treated for 28 days with JNJ-56136379 monotherapy.

Four weeks of once-daily oral JNJ-56136379 (JNJ-6379; 25, 75, 150 or 250 mg), a class-N capsid assembly modulator (CAM-N), was well tolerated with potent antiviral activity in treatment-naïve, chronic hepatitis B e antigen-positive and hepatitis B e antigen-negative patients (NCT02662712). Hepatitis B virus (HBV) genome sequence analysis, using HBV DNA next-generation sequence technology, was performed, and impact of substitutions on efficacy was assessed. Analyses focused on HBV core protein amino acid positions associated with JNJ-6379 and/or other CAMs in vitro resistance, and those within the CAM-binding pocket. 31/57 patients had ≥ 1 polymorphism at any of the core amino acid positions of interest, most frequently at positions 38 (32%), 105 (23%) and 109 (14%). None of these polymorphisms are known to reduce JNJ-6379 in vitro activity (fold change [FC] in 50% effective concentration <3.0). Two JNJ-6379-treated patients carried a Y118F baseline core polymorphism known to reduce JNJ-6379 activity in vitro (FC = 6.6) and had HBV DNA declines of 2.77 (75 mg) and 2.19 log10 IU/mL (150 mg) at the end of treatment. One 75 mg JNJ-6379-treated patient had an emerging T109S substitution (FC = 1.8; HBV DNA decline 3.18 log10 IU/mL). A 25 mg JNJ-6379-treated patient had on-treatment enrichment of Y118F variant (HBV DNA decline 2.13 log10 IU/mL). In conclusion, baseline polymorphisms and enrichment of substitutions reducing JNJ-6379 in vitro activity were rare, with no consistent impact on virological response during a 4-week phase 1b study. Emergence of resistance to longer treatments of JNJ-6379 will be evaluated in phase 2 studies.

A random effects model for the identification of differential splicing (REIDS) using exon and HTA arrays.

BACKGROUND: Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events do occur which have been linked to genetic disorders, such as several types of cancer and neurodegenerative diseases (Fan et al., Theor Biol Med Model 3:19, 2006). Therefore, understanding the mechanism of alternative splicing and identifying the difference in splicing events between diseased and healthy tissue is crucial in biomedical research with the potential of applications in personalized medicine as well as in drug development. RESULTS: We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events. Based on a set of scores, an exon score and an array score, a decision regarding alternative splicing can be made. The model enables the ability to distinguish a differential expressed gene from a differential spliced exon. The proposed model was applied to three case studies concerning both exon and HTA arrays. CONCLUSION: The REIDS model provides a work flow for the identification of alternative splicing events relying on the established linear mixed model. The model can be applied to different types of arrays.

A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery.

Identification of the minimum effective dose for normally distributed data using a Bayesian variable selection approach.

The identification of the minimum effective dose is of high importance in the drug development process. In early stage screening experiments, establishing the minimum effective dose can be translated into a model selection based on information criteria. The presented alternative, Bayesian variable selection approach, allows for selection of the minimum effective dose, while taking into account model uncertainty. The performance of Bayesian variable selection is compared with the generalized order restricted information criterion on two dose-response experiments and through the simulations study. Which method has performed better depends on the complexity of the underlying model and the effect size relative to noise.

VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering.

MOTIVATION: In virology, massively parallel sequencing (MPS) opens many opportunities for studying viral quasi-species, e.g. in HIV-1- and HCV-infected patients. This is essential for understanding pathways to resistance, which can substantially improve treatment. Although MPS platforms allow in-depth characterization of sequence variation, their measurements still involve substantial technical noise. For Illumina sequencing, single base substitutions are the main error source and impede powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores (Qs) that are useful for differentiating errors from the real low-frequency mutations. RESULTS: A variant calling tool, Q-cpileup, is proposed, which exploits the Qs of nucleotides in a filtering strategy to increase specificity. The tool is imbedded in an open-source pipeline, VirVarSeq, which allows variant calling starting from fastq files. Using both plasmid mixtures and clinical samples, we show that Q-cpileup is able to reduce the number of false-positive findings. The filtering strategy is adaptive and provides an optimized threshold for individual samples in each sequencing run. Additionally, linkage information is kept between single-nucleotide polymorphisms as variants are called at the codon level. This enables virologists to have an immediate biological interpretation of the reported variants with respect to their antiviral drug responses. A comparison with existing SNP caller tools reveals that calling variants at the codon level with Q-cpileup results in an outstanding sensitivity while maintaining a good specificity for variants with frequencies down to 0.5%. AVAILABILITY: The VirVarSeq is available, together with a user's guide and test data, at sourceforge: http://sourceforge.net/projects/virtools/?source=directory.

High MIG (CXCL9) plasma levels favours response to peginterferon and ribavirin in HCV-infected patients regardless of DPP4 activity.

BACKGROUND & AIMS: Sustained virological response (SVR) following peginterferon (pegIFN) and ribavirin (RBV) treatment in hepatitis C virus (HCV)-infected patients has been linked with the IL28B genotype and lower peripheral levels of the CXCR3-binding chemokine IP-10 (CXCL10). To further improve the understanding of these biomarkers we investigated plasma levels of the other CXCR3-binding chemokines and activity of the dipeptidyl peptidase IV (DPP4, CD26) protease, which cleaves IP-10, in relation to treatment response. METHODS: African-American and Caucasian HCV genotype 1-infected patients (n = 401) were treated with pegIFN/RBV for 48 weeks (ViraHep-C cohort). Pretreatment plasma levels of MIG (CXCL9), I-TAC (CXCL11) and the type III interferon IL29 were investigated by Luminex and DPP4 activity by using a luciferase assay. RESULTS: Patients achieving SVR had higher baseline MIG plasma levels and lower DPP4 activity than non-SVR patients. MIG was higher in Caucasians, IL28B CC (rs1297860) genotype carriers and patients with higher ALT levels. MIG correlated with IP-10 in SVR patients, but not in non-SVRs. A high DPP4 activity correlated with higher IP-10 levels, while DPP4 activity was not associated with MIG or I-TAC levels. CONCLUSIONS: The associations of MIG with SVR status and IL28B genotype imply that higher MIG plasma levels could reflect a beneficial immunological state for response to pegIFN/RBV treatment. The correlation between MIG and IP-10 observed only in SVR patients may contribute to a better treatment response, whereas this MIG/IP-10 balance might be disrupted in non-SVR patients because of the increased DPP4 cleavage of IP-10 into a dysfunctional form.

Gait characteristics and spatio-temporal variables of climbing in bonobos (Pan paniscus).

Although much is known about the terrestrial locomotion of great apes, their arboreal locomotion has been studied less extensively. This study investigates arboreal locomotion in bonobos (Pan paniscus), focusing on the gait characteristics and spatio-temporal variables associated with locomotion on a pole. These features are compared across different substrate inclinations (0°, 30°, 45°, 60°, and 90°), and horizontal quadrupedal walking is compared between an arboreal and a terrestrial substrate. Our results show greater variation in footfall patterns with increasing incline, resulting in more lateral gait sequences. During climbing on arboreal inclines, smaller steps and strides but higher stride frequencies and duty factors are found compared to horizontal arboreal walking. This may facilitate better balance control and dynamic stability on the arboreal substrate. We found no gradual change in spatio-temporal variables with increasing incline; instead, the results for all inclines were clustered together. Bonobos take larger strides at lower stride frequencies and lower duty factors on a horizontal arboreal substrate than on a flat terrestrial substrate. We suggest that these changes are the result of the better grip of the grasping feet on an arboreal substrate. Speed modulation of the spatio-temporal variables is similar across substrate inclinations and between substrate types, suggesting a comparable underlying motor control. Finally, we contrast these variables of arboreal inclined climbing with those of terrestrial bipedal locomotion, and briefly discuss the results with respect to the origin of habitual bipedalism. Am. J. Primatol. 78:1165-1177, 2016. © 2016 Wiley Periodicals, Inc.

ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering.

BACKGROUND: Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second best base calls for identifying and quantifying viral variants. ViVaMBC is optimized to call variants at the codon level (nucleotide triplets) which enables immediate biological interpretation of the variants with respect to their antiviral drug responses. RESULTS: Using mixtures of HCV plasmids we show that our method accurately estimates frequencies down to 0.5%. The estimates are unbiased when average coverages of 25,000 are reached. A comparison with the SNP-callers V-Phaser2, ShoRAH, and LoFreq shows that ViVaMBC has a superb sensitivity and specificity for variants with frequencies above 0.4%. Unlike the competitors, ViVaMBC reports a higher number of false-positive findings with frequencies below 0.4% which might partially originate from picking up artificial variants introduced by errors in the sample and library preparation step. CONCLUSIONS: ViVaMBC is the first method to call viral variants directly at the codon level. The strength of the approach lies in modeling the error probabilities based on the quality scores. Although the use of second best base calls appeared very promising in our data exploration phase, their utility was limited. They provided a slight increase in sensitivity, which however does not warrant the additional computational cost of running the offline base caller. Apparently a lot of information is already contained in the quality scores enabling the model based clustering procedure to adjust the majority of the sequencing errors. Overall the sensitivity of ViVaMBC is such that technical constraints like PCR errors start to form the bottleneck for low frequency variant detection.

Identification of in vitro and in vivo disconnects using transcriptomic data.

BACKGROUND: Integrating transcriptomic experiments within drug development is increasingly advocated for the early detection of toxicity. This is partly to reduce costs related to drug failures in the late, and expensive phases of clinical trials. Such an approach has proven useful both in the study of toxicology and carcinogenicity. However, general lack of translation of in vitro findings to in vivo systems remains one of the bottle necks in drug development. This paper proposes a method for identifying disconnected genes between in vitro and in vivo toxicogenomic rat experiments. The analytical framework is based on the joint modeling of dose-dependent in vitro and in vivo data using a fractional polynomial framework and biclustering algorithm. RESULTS: Most disconnected genes identified belonged to known pathways, such as drug metabolism and oxidative stress due to reactive metabolites, bilirubin increase, glutathion depletion and phospholipidosis. We also identified compounds that were likely to induce disconnect in gene expression between in vitro and in vivo toxicogenomic rat experiments. These compounds include: sulindac and diclofenac (both linked to liver damage), naphtyl isothiocyanate (linked to hepatoxocity), indomethacin and naproxen (linked to gastrointestinal problem and damage of intestines). CONCLUSION: The results confirmed that there are important discrepancies between in vitro and in vivo toxicogenomic experiments. However, the contribution of this paper is to provide a tool to identify genes that are disconnected between the two systems. Pathway analysis of disconnected genes may improve our understanding of uncertainties in the mechanism of actions of drug candidates in humans, especially concerning the early detection of toxicity.

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.

Gene filtering in the analysis of Illumina microarray experiments.

Illumina bead arrays are microarrays that contain a random number of technical replicates (beads) for every probe (bead type) within the same array. Typically around 30 beads are placed at random positions on the array surface, which opens unique opportunities for quality control. Most preprocessing methods for Illumina bead arrays are ported from the Affymetrix microarray platform and ignore the availability of the technical replicates. The large number of beads for a particular bead type on the same array, however, should be highly correlated, otherwise they just measure noise and can be removed from the downstream analysis. Hence, filtering bead types can be considered as an important step of the preprocessing procedure for Illumina platform. This paper proposes a filtering method for Illumina bead arrays, which builds upon the mixed model framework. Bead types are called informative/non-informative (I/NI) based on a trade-off between within and between array variabilities. The method is illustrated on a publicly available Illumina Spike-in data set (Dunning et al., 2008) and we also show that filtering results in a more powerful analysis of differentially expressed genes.

cn.FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate.

Cost-effective oligonucleotide genotyping arrays like the Affymetrix SNP 6.0 are still the predominant technique to measure DNA copy number variations (CNVs). However, CNV detection methods for microarrays overestimate both the number and the size of CNV regions and, consequently, suffer from a high false discovery rate (FDR). A high FDR means that many CNVs are wrongly detected and therefore not associated with a disease in a clinical study, though correction for multiple testing takes them into account and thereby decreases the study's discovery power. For controlling the FDR, we propose a probabilistic latent variable model, 'cn.FARMS', which is optimized by a Bayesian maximum a posteriori approach. cn.FARMS controls the FDR through the information gain of the posterior over the prior. The prior represents the null hypothesis of copy number 2 for all samples from which the posterior can only deviate by strong and consistent signals in the data. On HapMap data, cn.FARMS clearly outperformed the two most prevalent methods with respect to sensitivity and FDR. The software cn.FARMS is publicly available as a R package at http://www.bioinf.jku.at/software/cnfarms/cnfarms.html.

Viral sequence analysis of chronic hepatitis B patients treated with the capsid assembly modulator JNJ-56136379 in the JADE phase 2a study.

BACKGROUND & AIMS: In the monotherapy arms of the phase 2 JADE study (ClinicalTrials.gov Identifier: NCT03361956) evaluating the safety and efficacy of JNJ-56136379 (capsid assembly modulator-class E) with/without nucleos(t)ide analogue (NA), viral breakthroughs (VBT) were observed, leading to JNJ-56136379 monotherapy discontinuation. We present the viral sequencing analysis of JNJ-56136379±NA-treated hepatitis B virus (HBV)-infected patients. METHODS: The HBV full genome was sequenced using next generation sequencing. Baseline amino acid (aa) polymorphisms were defined as changes versus the universal HBV reference sequence (sequence read frequency >15%). Emerging mutations were defined as aa changes versus baseline sequence (frequency <1% at baseline and ≥15% post-baseline). RESULTS: 6/28 JNJ-56136379 75 mg monotherapy arm patients experienced VBT; all 6 had emerging JNJ-56136379-resistant variants T33N (n = 5; fold change [FC] = 85) or F23Y (n = 1; FC = 5.2). 1/32 JNJ-56136379 250 mg arm patients (genotype-E) had <1 log10 IU/mL decline in HBV DNA at Week 4, experienced VBT at Week 8, and carried the I105T baseline polymorphism (FC = 7.9), but had no emerging variants. Eight additional monotherapy-treated patients had shallow second phases of their HBV DNA profile and emerging T33N (n = 7) or F23Y (n = 1) variants. NA initiation (switch [75 mg arm]; add-on [250 mg arm]) in all monotherapy patients with VBT resulted in HBV DNA decline in all patients. No VBT was observed during JNJ-56136379+NA combination therapy. CONCLUSIONS: JNJ-56136379 monotherapy resulted in VBT and was associated with the selection of JNJ-56136379-resistant variants. Efficacy of NA treatment (de novo combination or rescue therapy for VBT) was not impacted, confirming the lack of cross-resistance between these drug classes. CLINICAL TRIAL NUMBER: NCT03361956.

Automated Spot Counting in Microbiology.

Biological samples are routinely analyzed for microbe concentration. The samples are diluted, loaded onto established host cell cultures, and incubated. If infectious agents are present in the samples, they form circular spots that do not contain the host cells. Each spot is assumed to be originated from a single microbial unit such as a bacterial colony forming unit or viral plaque forming unit. The undiluted sample concentration is estimated by counting the spots and back-calculating. Counting the number of spots by trained technicians is currently the gold standard but it is laborious, subjective, and hard to scale. This paper presents a new automated algorithm for spot counting, Localized and Sequential Thresholding (LoST). Validation studies showed that LoST performance was comparable with manual counting and outperformed several existing tools on images with overlapping spots. The LoST algorithm employs sequential thresholding through a two-stage segmentation and borrows information across all images from the same dilution series to fine-tune the count and identify right censoring. The algorithm increases the efficiency of the spot counting and the quality of the downstream analysis, especially when coupled with an appropriate statistical serial dilution model to enhance the undiluted sample concentration estimation procedure.

The use of semiparametric mixed models to analyze PamChip(R) peptide array data: an application to an oncology experiment.

MOTIVATION: Phosphorylation by protein kinases is a central theme in biological systems. Aberrant protein kinase activity has been implicated in a variety of human diseases (e.g. cancer). Therefore, modulation of kinase activity represents an attractive therapeutic approach for the treatment of human illnesses. Thus, identification of signature peptides is crucial for protein kinase targeting and can be achieved by using PamChip(®) microarray technology. We propose a flexible semiparametric mixed model for analyzing PamChip(®) data. This approach enables the estimation of the phosphorylation rate (Velocity) as a function of time together with pointwise confidence intervals. RESULTS: Using a publicly available dataset, we show that our model is capable of adequately fitting the kinase activity profiles and provides velocity estimates over time. Moreover, it allows to test for differences in the velocity of kinase inhibition between responding and non-responding cell lines. This can be done at individual time point as well as for the entire velocity profile. CONTACT: pushpike@med.kuleuven.be SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.