Regulatory evaluation of antiviral drug resistance in the era of next-generation sequencing

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.

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).

Impact of hepatitis C virus polymorphisms on direct-acting antiviral treatment efficacy: Regulatory analyses and perspectives

Several highly effective, interferon-free, direct-acting antiviral (DAA)-based regimens are available for the treatment of chronic hepatitis C virus (HCV) infection. Despite impressive efficacy overall, a small proportion of patients in registrational trials experienced treatment failure, which in some cases was associated with the detection of HCV resistance-associated substitutions (RASs) at baseline. In this article, we describe methods and key findings from independent regulatory analyses investigating the impact of baseline nonstructural (NS) 3 Q80K and NS5A RASs on the efficacy of current United States Food and Drug Administration (FDA)-approved regimens for patients with HCV genotype (GT) 1 or GT3 infection. These analyses focused on clinical trials that included patients who were previously naïve to the DAA class(es) in their investigational regimen and characterized the impact of baseline RASs that were enriched in the viral population as natural or transmitted polymorphisms (i.e., not drug-selected RASs). We used a consistent approach to optimize comparability of results across different DAA regimens and patient populations, including the use of a 15% sensitivity cutoff for next-generation sequencing results and standardized lists of NS5A RASs. These analyses confirmed that detection of NS3 Q80K or NS5A baseline RASs was associated with reduced treatment efficacy for multiple DAA regimens, but their impact was often minimized with the use of an intensified treatment regimen, such as a longer treatment duration and/or addition of ribavirin. We discuss the drug resistance-related considerations that contributed to pretreatment resistance testing and treatment recommendations in drug labeling for FDA-approved DAA regimens.

CONCLUSION

Independent regulatory analyses confirmed that baseline HCV RASs can reduce the efficacy of certain DAA-based regimens in selected patient groups. However, highly effective treatment options are available for patients with or without baseline RASs. (Hepatology 2018;67:2430-2448).

MinVar: A rapid and versatile tool for HIV-1 drug resistance genotyping by deep sequencing

Genotypic monitoring of drug-resistance mutations (DRMs) in HIV-1 infected individuals is strongly recommended to guide selection of the initial antiretroviral therapy (ART) and changes of drug regimens. Traditionally, mutations conferring drug resistance are detected by population sequencing of the reverse transcribed viral RNA encoding the HIV-1 enzymes target by ART, followed by manual analysis and interpretation of Sanger sequencing traces. This process is labor intensive, relies on subjective interpretation from the operator, and offers limited sensitivity as only mutations above 20% frequency can be reliably detected. Here we present MinVar, a pipeline for the analysis of deep sequencing data, which allows reliable and automated detection of DRMs down to 5%. We evaluated MinVar with data from amplicon sequencing of defined mixtures of molecular virus clones with known DRM and plasma samples of viremic HIV-1 infected individuals and we compared it to VirVarSeq, another virus variant detection tool exclusively working on Illumina deep sequencing data. MinVar was designed to be compatible with a diverse range of sequencing platforms and allows the detection of DRMs and insertions/deletions from deep sequencing data without the need to perform additional bioinformatics analysis, a prerequisite to a widespread implementation of HIV-1 genotyping using deep sequencing in routine diagnostic settings.