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Standardized benchmarking approaches are required to assess the accuracy of variants called from sequence data. Although variant-calling tools and the metrics used to assess their performance continue to improve, important challenges remain. Here, as part of the Global Alliance for Genomics and Health (GA4GH), we present a benchmarking framework for variant calling. We provide guidance on how to match variant calls with different representations, define standard performance metrics, and stratify performance by variant type and genome context. We describe limitations of high-confidence calls and regions that can be used as truth sets (for example, single-nucleotide variant concordance of two methods is 99.7% inside versus 76.5% outside high-confidence regions). Our web-based app enables comparison of variant calls against truth sets to obtain a standardized performance report. Our approach has been piloted in the PrecisionFDA variant-calling challenges to identify the best-in-class variant-calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and evaluating the results.A new standard allows the accuracy of variant calls to be assessed and compared across different technologies, variant types and genomic regions.

Accurately calling indels with next-generation sequencing (NGS) data is critical for clinical application. The precisionFDA team collaborated with the U.S. Food and Drug Administration’s (FDA’s) National Center for Toxicological Research (NCTR) and successfully completed the NCTR Indel Calling from Oncopanel Sequencing Data Challenge, to evaluate the performance of indel calling pipelines. Top performers were selected based on precision, recall, and F1-score. The performance of many other pipelines was close to the top performers, which produced a top cluster of performers. The performance was significantly higher in high confidence regions and coding regions, and significantly lower in low complexity regions. Oncopanel capture and other issues may have occurred that affected the recall rate. Indels with higher variant allele frequency (VAF) may generally be called with higher confidence. Many of the indel calling pipelines had good performance. Some of them performed generally well across all three oncopanels, while others were better for a specific oncopanel. The performance of indel calling can further be improved by restricting the calls within high confidence intervals (HCIs) and coding regions, and by excluding low complexity regions (LCR) regions. Certain VAF cut-offs could be applied according to the applications.

In the version of this article initially published online, two pairs of headings were switched with each other in Table 4: “Recall (PCR free)” was switched with “Recall (with PCR),” and “Precision (PCR free)” was switched with “Precision (with PCR).” The error has been corrected in the print, PDF and HTML versions of this article.

Background Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. Results To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. Conclusions Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.

Cancer is a genetic disease caused by genomic instability. In many cancers, this instability is manifested by chromosomal reconfigurations and karyotypic complexity. These features are particular hallmarks of the epithelial cancers that are some of the malignancies most resistant to long term control by current chemotherapeutic agents. We have asked whether we could use karyotypic complexity and instability as determinants for the screening of potential anticancer compounds. Using a panel of well characterized cancer cell lines, we have been able to identify specific groups of chemical compounds that are more cytotoxic toward the relatively more karyotypically complex and unstable panel members. Thus, we delineate an approach for the identification of \"lead compounds\" for anticancer drug discovery complementary to those that are focused at the outset on a given gene or pathway.

Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines.

Previously, we have demonstrated that interleukin‐4 receptor α (IL‐4Rα) is overexpressed on a variety of human cancers and can serve as target for IL‐4 immunotoxin comprised of IL‐4 and a mutated Pseudomonas exotoxin. However, its expression and association with grade and clinical stage of bladder cancer has not been studied. IL‐4Rα expression was examined in human bladder cancer cell lines, mouse xenografts, and biopsy specimens at mRNA and protein levels by real‐time RT‐PCR and IHC/ISH techniques. We also examined the effect of IL‐4 on proliferation and invasion of bladder carcinoma cell lines. For tissue microarray (TMA) results, we analyzed the precision data using exact binomial proportion with exact two‐sided P‐values. We used Cochran–Armitage Statistics with exact two‐sided P‐values to examine the trend analysis of IL‐4Rα over grade or stage of the bladder cancer specimens. The influence of age and gender covariates was also analyzed using multiple logistic regression models. IL‐4Rα is overexpressed in five bladder cancer cell lines, while normal bladder and human umbilical vein cell lines (HUVEC) expressed at low levels. Two other chains of IL‐4 receptor complex, IL‐2RγC and IL‐13Rα1, were absent or weakly expressed. IL‐4 modestly inhibited the cell proliferation, but enhanced cell invasion of bladder cancer cell lines in a concentration‐dependent manner. Bladder cancer xenografts in immunodeficient mice also maintained IL‐4Rα overexpression in vivo. Analysis of tumor biopsy specimens in TMAs revealed significantly higher IL‐4Rα immunostaining (≥2+) in Grade 2 (85%) and Grade 3 (97%) compared to Grade 1 tumors (0%) (P ≤ 0.0001). Similarly, 9% stage I tumors were positive for IL‐4Rα (≥2+) compared to 84% stage II (P ≤ 0.0001) and 100% stages III–IV tumors (P ≤ 0.0001). IL‐13Rα1 was also expressed in tumor tissues but at low levels and it did not show any correlation with the grade and stage of disease. However, the IL‐2RγC was not expressed. Ten normal bladder specimens demonstrated ≤1+ staining for IL‐4Rα and IL‐13Rα1 and no staining for IL‐2RγC. These results demonstrate that IL‐4Rα is overexpressed in human bladder cancer, which correlates with advanced grade and stage of the disease. Thus, IL‐4Rα may be a bladder tumor‐associated protein and a prognostic biomarker. This study identifies a novel role of the interleukin‐4 receptor α (IL‐4R α) chain as a bladder cancer–associated protein, which characterizes tumor aggressiveness in bladder cancer and its potential as a prognostic biomarker. Investigational new IL‐4R α‐directed therapy either alone or in combination with other anticancer drugs can be additional therapeutic options for advanced grade or stage bladder cancer patients.

Background Near universal administration of vaccines mandates intense pharmacovigilance for vaccine safety and a stringently low tolerance for adverse events. Reports of autoimmune diseases (AID) following vaccination have been challenging to evaluate given the high rates of vaccination, background incidence of autoimmunity, and low incidence and variable times for onset of AID after vaccinations. In order to identify biologically plausible pathways to adverse autoimmune events of vaccine-related AID, we used a systems biology approach to create a matrix of innate and adaptive immune mechanisms active in specific diseases, responses to vaccine antigens, adjuvants, preservatives and stabilizers, for the most common vaccine-associated AID found in the Vaccine Adverse Event Reporting System. Results This report focuses on Guillain-Barre Syndrome (GBS), Rheumatoid Arthritis (RA), Systemic Lupus Erythematosus (SLE), and Idiopathic (or immune) Thrombocytopenic Purpura (ITP). Multiple curated databases and automated text mining of PubMed literature identified 667 genes associated with RA, 448 with SLE, 49 with ITP and 73 with GBS. While all data sources provided valuable and unique gene associations, text mining using natural language processing (NLP) algorithms provided the most information but required curation to remove incorrect associations. Six genes were associated with all four AIDs. Thirty-three pathways were shared by the four AIDs. Classification of genes into twelve immune system related categories identified more “ Th17 T-cell subtype ” genes in RA than the other AIDs, and more “ Chemokine plus Receptors ” genes associated with RA than SLE. Gene networks were visualized and clustered into interconnected modules with specific gene clusters for each AID, including one in RA with ten C-X-C motif chemokines. The intersection of genes associated with GBS, GBS peptide auto-antigens, influenza A infection, and influenza vaccination created a subnetwork of genes that inferred a possible role for the MAPK signaling pathway in influenza vaccine related GBS. Conclusions Results showing unique and common gene sets, pathways, immune system categories and functional clusters of genes in four autoimmune diseases suggest it is possible to develop molecular classifications of autoimmune and inflammatory events. Combining this information with cellular and other disease responses should greatly aid in the assessment of potential immune-mediated adverse events following vaccination.

The US Vaccine Adverse Event Reporting System contains case reports of autoimmune diseases (ADs) occurring following vaccinations. ADs are rare and occur in unvaccinated people, making the potential association between vaccines and ADs challenging to evaluate. Developing mechanistic pathways that link genes, immune mediators, vaccine components and ADs would be helpful for hypothesis generation, enhancing theories of biologic plausibility and grouping rare autoimmune adverse events to increase the ability to detect and evaluate safety signals. Here, we propose a conceptual framework for investigating the genetics of ADs as safety signals following vaccination, potentially contributing to the identification of relevant biomarkers. We also discuss a study design that incorporates genetic information into postmarket clinical evaluation of autoimmune adverse events following vaccination.

Previously, we have demonstrated that Interleukin-4 (IL-4) receptor alpha (IL-4Rα) is overexpressed in bladder cancer biopsy specimens and its expression level correlates with the grade and stage of disease. Based on these observations, it is proposed that IL-4Rα is a prognostic biomarker for bladder cancer. To target IL-4Rα, we have developed a recombinant chimeric fusion immunotoxin, which consists of circularly permuted IL-4 and truncated Pseudomonas exotoxin (IL-4-PE) [1]. Here we demonstrate that IL-4-PE is highly cytotoxic to eight bladder cancer cell lines in vitro. The cytotoxicity by IL-4-PE was mediated in a concentration dependent manner and this cytotoxicity was receptor specific as excess IL-4 inhibited cytotoxicity mediated by IL-4-PE. IL-4-PE immunotoxin also killed bladder cancer colonies in a concentration dependent manner in a clonogenic assay. We developed three subcutaneous tumor models in athymic nude mice using three different bladder cancer cell lines (UM-UC-3, SW780 and 5637), which are sensitive to IL-4-PE at a variable degree. These mice were treated with 50 μg/kg, 100 μg/kg of IL-4-PE immunotoxin or vehicle-control intratumorally and monitored for tumor growth and survival. IL-4-PE effectively caused regression of tumors by 70% in all three tumor models compared to vehicle control mice. Responding animals showed complete regression of tumors in 58% of mice at the highest dose in UM-UC-3 tumor model and 54% in SW780 tumor model. Overall, all responding animals showed >8 week longer survival compared to control mice. IL-4-PE immunotoxin at both doses did not show any visible toxicity when administrated intratumorally. Similar safety profile has been observed in the clinic when IL-4-PE was administered intratumorally in glioma trial [2]. Taken together our results demonstrate that IL-4Rα in bladder cancer is a prognostic biomarker and in addition it provides an excellent target for immunotherapy. Additional studies are ongoing to target IL-4Rα with other immunotherapeutic approaches such as cancer vaccines and adoptive cell transfer immunotherapy.