As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services. Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource.

Patients presenting with repeat OM after MDT may still have favorable 3-year PMRFS and OS, which may justify exploring aggressive local treatments in this subpopulation. Further randomized trials in this space are needed.

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has demonstrated its ability to rapidly and continuously evolve, leading to the emergence of thousands of different sequence variants, many with distinctive phenotypic properties. Fortunately, the broad application of next generation sequencing (NGS) across the globe has produced a wealth of SARS-CoV-2 genome sequences, offering a comprehensive picture of how this virus is evolving so that accurate diagnostics, reliable therapeutics, and prophylactic vaccines against COVID-19 can be developed and maintained. The millions of SARS-CoV-2 sequences deposited into genomic sequencing databases, including GenBank, BV-BRC, and GISAID, are annotated with the dates and geographic locations of sample collection, and can be aligned to and compared with the Wuhan-Hu-1 reference genome to extract their constellation of nucleotide and amino acid substitutions. By aggregating these data into concise datasets, the spread of variants through space and time can be assessed. Variant tracking efforts have initially focused on the Spike protein due to its critical role in viral tropism and antibody neutralization. To identify emerging variants of concern as early as possible, we developed a computational pipeline to process the genomic data and assign risk scores based on both epidemiological and functional parameters. Epidemiological dynamics are used to identify variants exhibiting substantial growth over time and spread across geographical regions. Experimental data that quantify Spike protein regions targeted by adaptive immunity and critical for other virus characteristics are used to predict variants with consequential immunogenic and pathogenic impacts. The growth assessment and functional impact scores are combined to produce a Composite Score for any set of Spike substitutions detected. With this systematic method to routinely score and rank emerging variants, we have established an approach to identify threatening variants early and prioritize them for experimental evaluation.

There has been an increasing interest in patient-reported outcome (PRO) measures in both the clinical and research settings to improve the quality of life among patients and to identify when clinical intervention may be needed. The primary purpose of this prospective study was to validate an acute breast skin toxicity PRO measure across a broad sample of patient body types undergoing radiation therapy. Between August 2018 and September 2019, 134 women undergoing adjuvant breast radiotherapy (RT) consented to completing serial PRO measures both during and post-RT treatment and to having their skin assessed by trained trial radiation therapists. There was high patient compliance, with 124 patients (92.5%) returning to the clinic post-RT for at least one staff skin assessment. Rates of moist desquamation (MD) in the infra-mammary fold (IMF) by PRO were compared with skin assessments completed by trial radiation therapists. There was high sensitivity (86.5%) and good specificity (79.4%) between PRO and staff-reported presence of MD in the IMF, and there was a moderate correlation between the peak severity of the MD reported by PRO and assessed by staff (rho = 0.61, p < 0.001). This prospective study validates a new PRO measure to monitor the presence of MD in the IMF among women receiving breast RT.

Since the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, there has been international concern about the emergence of virus variants with mutations that increase transmissibility, enhance escape from the human immune response, or otherwise alter biologically important phenotypes. In late 2020, several variants of concern emerged globally, including the UK variant (B.1.1.7), the South Africa variant (B.1.351), Brazil variants (P.1 and P.2), and two related California variants of interest (B.1.429 and B.1.427). These variants are believed to have enhanced transmissibility. For the South Africa and Brazil variants, there is evidence that mutations in spike protein permit it to escape from some vaccines and therapeutic monoclonal antibodies. On the basis of our extensive genome sequencing program involving 20,453 coronavirus disease 2019 patient samples collected from March 2020 to February 2021, we report identification of all six of these SARS-CoV-2 variants among Houston Methodist Hospital (Houston, TX) patients residing in the greater metropolitan area. Although these variants are currently at relatively low frequency (aggregate of 1.1%) in the population, they are geographically widespread. Houston is the first city in the United States in which active circulation of all six current variants of concern has been documented by genome sequencing. As vaccine deployment accelerates, increased genomic surveillance of SARS-CoV-2 is essential to understanding the presence, frequency, and medical impact of consequential variants and their patterns and trajectory of dissemination.

Certain genetic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are of substantial concern because they may be more transmissible or detrimentally alter the pandemic course and disease features in individual patients. SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist health care system diagnosed from January 1 through May 31, 2021 are reported here. Prevalence of the B.1.1.7 (Alpha) variant increased rapidly and caused 63% to 90% of new cases in the latter half of May. Eleven B.1.1.7 genomes had an E484K replacement in spike protein, a change also identified in other SARS-CoV-2 lineages. Compared with noneB.1.1.7-infected patients, individuals with B.1.1.7 had a significantly lower cycle threshold (a proxy for higher virus load) and significantly higher hospitalization rate. Other variants [eg, B.1.429 and B.1.427 (Epsilon), P.1 (Gamma), P.2 (Zeta), and R.1] also increased rapidly, although the magnitude was less than that in B.1.1.7. Twenty-two patients infected with B.1.617.1 (Kappa) or B.1.617.2 (Delta) variants had a high rate of hospitalization. Breakthrough cases (n = 207) in fully vaccinated patients were caused by a heterogeneous array of virus genotypes, including many not currently designated variants of interest or concern. In the aggregate, this study delineates the trajectory of SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, TX, and heralds the arrival of B.1.617 variants in the metroplex.

Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. We demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low. This AMR metadata collection is freely available and maintained on the Bacterial and Viral Bioinformatics Center (BV-BRC) FTP site ftp://ftp.bvbrc.org/RELEASE_NOTES/PATRIC_genomes_AMR.txt.

AbstractGenetic variants of the SARS-CoV-2 virus are of substantial concern because they can detrimentally alter the pandemic course and disease features in individual patients. Here we report SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist healthcare system diagnosed from January 1, 2021 through May 31, 2021. The SARS-CoV-2 variant designated U.K. B.1.1.7 increased rapidly and caused 63%-90% of all new cases in the Houston area in the latter half of May. Eleven of the 3,276 B.1.1.7 genomes had an E484K change in spike protein. Compared with non-B.1.1.7 patients, individuals with B.1.1.7 had a significantly lower cycle threshold value (a proxy for higher virus load) and significantly higher rate of hospitalization. Other variants (e.g., B.1.429, B.1.427, P.1, P.2, and R.1) also increased rapidly, although the magnitude was less than for B.1.1.7. We identified 22 patients infected with B.1.617 “India” variants; these patients had a high rate of hospitalization. Vaccine breakthrough cases (n=207) were caused by a heterogeneous array of virus genotypes, including many that are not variants of interest or concern. In the aggregate, our study delineates the trajectory of concerning SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, and heralds the arrival and spread of B.1.617 variants in the metroplex.

Genetic variants of SARS-CoV-2 have repeatedly altered the course of the COVID-19 44 pandemic. Delta variants of concern are now the focus of intense international attention 45 because they are causing widespread COVID-19 disease globally and are associated 46 with vaccine breakthrough cases. We sequenced the genomes of 16,965 SARS-CoV-2 47 from samples acquired March 15, 2021 through September 20, 2021 in the Houston 48 Methodist hospital system. This sample represents 91% of all Methodist system COVID- 49 19 patients during the study period. Delta variants increased rapidly from late April 50 onward to cause 99.9% of all COVID-19 cases and spread throughout the Houston 51 metroplex. Compared to all other variants combined, Delta caused a significantly higher 52 rate of vaccine breakthrough cases (23.7% for Delta compared to 6.6% for all other 53 variants combined). Importantly, significantly fewer fully vaccinated individuals required 54 hospitalization. Individuals with vaccine breakthrough cases caused by Delta had a low 55 median PCR cycle threshold (Ct) value (a proxy for high virus load). This value was 56 closely similar to the median Ct value for unvaccinated patients with COVID-19 caused 57 by Delta variants, suggesting that fully vaccinated individuals can transmit SARS-CoV-2 58 to others. Patients infected with Alpha and Delta variants had several significant 59 differences. Our integrated analysis emphasizes that vaccines used in the United States 60 are highly effective in decreasing severe COVID-19 disease, hospitalizations, and 61 deaths. 62

The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we compare the performance of the ARTIC V3 and V4 primer sets with a matched set of 663 SARS-CoV-2 clinical samples sequenced with an Illumina NovaSeq 6000 instrument. We observe general improvements in sequencing depth and quality, and improved resolution of the SNP causing the D950N variation in the spike protein. Importantly, we also find nearly universal presence of spike protein substitution G142D in Delta-lineage samples. Due to the prior release and widespread use of the ARTIC V3 primers during the initial surge of the Delta variant, it is likely that the G142D amino acid substitution is substantially underrepresented among early Delta variant genomes deposited in public repositories. In addition to the improved performance of the ARTIC V4 primer set, this study also illustrates the importance of the primer scheme in downstream analyses. IMPORTANCE ARTIC Network primers are commonly used by laboratories worldwide to amplify and sequence SARS-CoV-2 present in clinical samples. As new variants have evolved and spread, it was found that the V3 primer set poorly amplified several key mutations. In this report, we compare the results of sequencing a matched set of samples with the V3 and V4 primer sets. We find that adoption of the ARTIC V4 primer set is critical for accurate sequencing of the SARS-CoV-2 spike region. The absence of metadata describing the primer scheme used will negatively impact the downstream use of publicly available SARS-Cov-2 sequencing reads and assembled genomes.

A high cancer burden exists among indigenous populations worldwide. Providing equitable delivery of cancer services can be challenging in Canada and Greenland given their geography. We sought to describe geographic access to radiotherapy for indigenous populations in Canada and Greenland. We used geospatial analyses to calculate distance and travel-time from indigenous communities in Canada and Greenland to the nearest radiotherapy center. In Canada, we calculated the proportion of indigenous communities and populations residing within a 1 and 2-hour drive of a radiotherapy center, and compared the proportion of indigenous versus non-indigenous populations residing within each drive-time area. We also calculated the potential distance and travel-time saved if radiotherapy was available in northern Canada (Yellowknife and Iqaluit), and Greenland (Nuuk). This took into consideration several assumptions, including that the new radiotherapy centers here would be similarly utilized and could offer all the same types of treatments available as in the current referral tertiary centers. We also assumed that patients would choose to receive radiotherapy within their own respective regions. Median one-way travel from indigenous communities to nearest radiotherapy center in Canada was 268 km (3 hours by plane or road), and 4,111 km (6 hours by plane) in Greenland. In Canada, 84% and 68% of indigenous communities were outside a 1 and 2-hour drive from a radiotherapy center, respectively. Only 2% of the total population in Canada resided outside a 2-hour drive from a radiotherapy center. However, indigenous peoples were 336 times more likely to live more than a 2-hour drive away, compared to non-indigenous peoples. Nearly 3 million km and 4,000 hours of travel could be saved for 1,000 patients with newly diagnosed cancers over a 10-year period in Canada, and 7 million km and 10,000 hours for 1,020 patients in Greenland, if radiotherapy was available in Yellowknife, Iqaluit, and Nuuk. Disparities in geographic access to radiotherapy exist between indigenous and non-indigenous peoples in Canada. Geospatial analyses can help highlight inequities in access to inform radiotherapy service planning, such as in Canada and Greenland where geography is an important potential barrier. Future work should involve a detailed economic evaluation involving the current costs associated with travelling, versus the implementation of local radiotherapy units.

TPS6592 Background: Treatment for HPV positive(+) oropharyngeal squamous cell carcinoma (OSCC) is highly effective but associated with significant short and long term treatment related morbidity. We hypothesize that decreasing the regions of elective nodal irradiation (ENI) in the neck will lead to less toxicity and better quality of life/functional outcomes while maintaining high disease control rates in patients with favourable prognosis HPV+ OSCC. Methods: HN.10 is a Canadian Cancer Trials Group phase II trial with a primary objective to evaluate the efficacy of primary definitive radiotherapy (RT) or chemoradiotherapy (CRT) utilizing volume reduced ENI as measured by 2-year event-free survival (EFS) in patients with low-risk HPV+ OPSCC. Secondary objectives include to evaluate overall survival, local control, regional control, locoregional control, out-of-field regional control, distant metastasis free survival, early and late toxicities of treatment, subjective swallowing functions, quality of life, utilization of healthcare resources, work productivity, and prognostic biomarkers. An imaging and biospecimen bank will be compiled as part of trial conduct. Key eligibility criteria include: pathologically proven diagnosis of HPV+ OPSCC; HPV association determined locally by either p16 immunohistochemistry or direct detection of HPV DNA sequences (e.g. by PCR or in situ hybridization) performed on a core needle or surgical biopsy specimen of the primary tumour or involved cervical lymph node; clinical stage T1-3 N0-1 M0 (UICC/AJCC 8th Ed.); fit for radiotherapy +/-chemoradiotherapy. Statistical Design: The primary endpoint is 2-year EFS. Assuming 2-year EFS to be 91% (Ha) for low-risk HPV-related OPSCC with standard treatment, and that the experimental treatment will be considered as ineffective if the 2-year EFS is ≤ 85% (H0), with one-sided alpha of 0.1, a sample size of 100 patients will have 80% power to detect a 6% difference of 2-year EFS. With 3 years of accrual and 2 years of follow-up, the total duration of this study will be 5 years. A total of 304.7 person-years of follow-up is needed for the final analysis. The null hypothesis (H0) will be rejected when the observed survival rate is 88.85% or higher (i.e. if there are 18 or fewer EFS events observed). Conduct to Date: Study activation February 20, 2019. Enrollment as of January 29 2020: 23. Clinical trial information: NCT03822897 .

A growing number of studies are using machine learning models to accurately predict antimicrobial resistance (AMR) phenotypes from bacterial sequence data. Although these studies are showing promise, the models are typically trained using features derived from comprehensive sets of AMR genes or whole genome sequences and may not be suitable for use when genomes are incomplete. In this study, we explore the possibility of predicting AMR phenotypes using incomplete genome sequence data. Models were built from small sets of randomly-selected core genes after removing the AMR genes. For Klebsiella pneumoniae, Mycobacterium tuberculosis, Salmonella enterica, and Staphylococcus aureus, we report that it is possible to classify susceptible and resistant phenotypes with average F1 scores ranging from 0.80-0.89 with as few as 100 conserved non-AMR genes, with very major error rates ranging from 0.11-0.23 and major error rates ranging from 0.10-0.20. Models built from core genes have predictive power in cases where the primary AMR mechanisms result from SNPs or horizontal gene transfer. By randomly sampling non-overlapping sets of core genes, we show that F1 scores and error rates are stable and have little variance between replicates. Although these small core gene models have lower accuracies and higher error rates than models built from the corresponding assembled genomes, the results suggest that sufficient variation exists in the core non-AMR genes of a species for predicting AMR phenotypes.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

BACKGROUND:Patients receiving chemoradiotherapy for head and neck cancer (HNC) are often malnourished. We assessed the utility of nutritional risk index (NRI) in HNC patients undergoing chemoradiotherapy. METHODS:A population-based retrospective review of HNC patients treated with curative chemoradiation was performed. Demographics, anthropometrics, overall survival (OS), and the composite treatment complication rate (G-tube dependence, radiation incompletion, 90-day mortality, and unplanned hospitalization) were collected. RESULTS:Two hundred ninety-two patients were identified. Average pretreatment and posttreatment NRI were 110 (SD 3) and 99 (SD 12), respectively (P < .01). Pretreatment NRI risk category, age, ECOG status, and tumor subsites were associated with OS on multivariate analysis. Pretreatment NRI risk category was associated with risk of treatment related complications. CONCLUSIONS:There was a significant decrease between pretreatment and posttreatment NRI in HNC patients receiving chemoradiation. Pretreatment NRI risk category may predict OS and composite treatment complications. Investigation of NRI as a prognostic factor is warranted.

Background Recent advances in high-volume sequencing technology and mining of genomes from metagenomic samples call for rapid and reliable genome quality evaluation. The current release of the PATRIC database contains over 220,000 genomes, and current metagenomic technology supports assemblies of many draft-quality genomes from a single sample, most of which will be novel. Description We have added two quality assessment tools to the PATRIC annotation pipeline. EvalCon uses supervised machine learning to calculate an annotation consistency score. EvalG implements a variant of the CheckM algorithm to estimate contamination and completeness of an annotated genome.We report on the performance of these tools and the potential utility of the consistency score. Additionally, we provide contamination, completeness, and consistency measures for all genomes in PATRIC and in a recent set of metagenomic assemblies. Conclusion EvalG and EvalCon facilitate the rapid quality control and exploration of PATRIC-annotated draft genomes.

The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other 'omic' data analyses. In response to mounting concern over antimicrobial resistance (AMR), the PATRIC team has been developing new tools that help researchers understand AMR and its genetic determinants. To support comparative analyses, we have added AMR phenotype data to over 15000 genomes in the PATRIC database, often assembling genomes from reads in public archives and collecting their associated AMR panel data from the literature to augment the collection. We have also been using this collection of AMR metadata to build machine learning-based classifiers that can predict the AMR phenotypes and the genomic regions associated with resistance for genomes being submitted to the annotation service. Likewise, we have undertaken a large AMR protein annotation effort by manually curating data from the literature and public repositories. This collection of 7370 AMR reference proteins, which contains many protein annotations (functional roles) that are unique to PATRIC and RAST, has been manually curated so that it projects stably across genomes. The collection currently projects to 1610744 proteins in the PATRIC database. Finally, the PATRIC Web site has been expanded to enable AMR-based custom page views so that researchers can easily explore AMR data and design experiments based on whole genomes or individual genes.

Purpose: Randomized data assessing the longitudinal quality of life (QoL) impact of stereotactic ablative radiation therapy (SABR) in the oligometastatic setting are lacking. Methods and Materials: We enrolled patients who had a controlled primary malignancy with 1 to 5 metastatic lesions, with good performance status and life expectancy >6 months. We randomized in a 1:2 ratio between standard of care (SOC) treatment (SOC arm) and SOC plus SABR to all metastatic lesions (SABR arm). QoL was measured using the Functional Assessment of Cancer Therapy-General. QoL changes over time and between groups were assessed with linear mixed modeling. Results: Ninety-nine patients were randomized. Median age was 68 years (range, 43-89), and 60% were male. The most common primary tumor types were breast (n = 18), lung (n = 18), colorectal (n = 18), and prostate (n = 16). Most patients (n = 92) had 1 to 3 metastases. Median follow-up was 26 months. Because of the previously reported inferior survival of the SOC arm, the time for attrition in QoL respondents to <10% of subjects was shorter in the SOC versus SABR arm (30 vs 42 months). In the whole cohort, QoL declined over time after randomization: There were significant declines in total Functional Assessment of Cancer Therapy-General score over time compared with baseline (P<.001) owing to declines in physical and functional subscales (both P<.001), with no declines in social and emotional subscales. However, the magnitudes of decline were small, and clinically meaningful changes were not seen at most time points. Comparison between arms showed no differences in QoL between the SABR and SOC arms in total score (P = .42) or in the physical (P = .98), functional (P = .59), emotional (P = .82), or social (P = .17) subscales. Conclusions: For patients with oligometastases, average QoL declines slowly over time regardless of treatment approach, although the changes are small in magnitude. The use of SABR, compared with SOC, was not associated with a QoL detriment. (C) 2019 Elsevier Inc. All rights reserved.

Objectives/HypothesisTo assess for potential urban and rural disparities in head and neck cancer (HNC) outcomes within a single‐payer healthcare system.Study DesignA large retrospective population‐based cohort analysis of consecutive HNC patients treated in British Columbia, Canada between 2001 and 2010 was conducted.MethodsAll patients diagnosed with HNC from 2001 to 2010 and referred to any one of five British Columbia Cancer Agency centers for management were reviewed. Based on census data, patients were classified into: 1) rural, 2) small urban, 3) moderate urban, and 4) large urban areas. Kaplan‐Meier methods and Cox regression models were used to correlate site of residence with overall survival (OS), controlling for prognostic factors that included sociodemographic and other tumor and treatment‐related characteristics.ResultsWe identified 3,036 patients; the median age was 64 years, 26% were women, and 32% had Eastern Cooperative Oncology Group (ECOG) 0 or 1. The majority resided in large urban areas (55%) followed by rural (22%), moderate urban (13%), and small urban (10%). In regression analyses, smoking (hazard ratio [HR]: 2.10, 95% confidence interval [CI]: 1.28‐3.45, P < .001), ECOG 2 + (HR: 3.44, 95% CI: 2.26‐5.22, P < .001), oral cavity (HR: 1.54, 95% CI: 1.03‐2.32, P = .04) and hypopharyngeal tumors (HR: 2.31, 95% CI: 1.42‐3.77, P = .00), and large tumor size (HR: 1.69, 95% CI: 1.08‐2.64, P = .02) were correlated with inferior OS, but site of residence was not. When stratified by type of treatment, OS remained similar irrespective of urban or rural residence.ConclusionsUrban–rural differences in HNC survival outcomes were not observed.Level of Evidence2c. Laryngoscope, 128:852–858, 2018