Towards accurate indel calling for oncopanel sequencing through an international pipeline competition at precisionFDA.

Accurately calling indels with next-generation sequencing (NGS) data is critical for clinical application. The precisionFDA team collaborated with the U.S.

Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project.

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.

The impact of misclassification errors on the performance of biomarkers based on next-generation sequencing, a simulation study.

The development of next-generation sequencing (NGS) opens opportunities for new applications such as liquid biopsy, in which tumor mutation genotypes can be determined by sequencing circulating tumor DNA after blood draws. However, with highly diluted samples like those obtained with liquid biopsy, NGS invariably introduces a certain level of misclassification, even with improved technology. Recently, there has been a high demand to use mutation genotypes as biomarkers for predicting prognosis and treatment selection.

US FDA public meeting: identification of concepts and terminology for multicomponent biomarkers.

The US FDA convened a virtual public workshop with the goals of obtaining feedback on the terminology needed for effective communication of multicomponent biomarkers and discussing the diverse use of biomarkers observed across the FDA and identifying common issues. The workshop included keynote and background presentations addressing the stated goals, followed by a series of case studies highlighting FDA-wide and external experience regarding the use of multicomponent biomarkers, which provided context for panel discussions focused on common themes, challenges and preferred terminology. The final panel discussion integrated the main concepts from the keynote, background presentations and case studies, laying a preliminary foundation to build consensus around the use and terminology of multicomponent biomarkers.

Assessing reproducibility of inherited variants detected with short-read whole genome sequencing.

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.

A targeted simulation-extrapolation method for evaluating biomarkers based on new technologies in precision medicine.

New technologies for novel biomarkers have transformed the field of precision medicine. However, in applications such as liquid biopsy for early tumor detection, the misclassification rates of next generation sequencing and other technologies have become an unavoidable feature of biomarker development. Because initial experiments are usually confined to specific technology choices and application settings, a statistical method that can project the performance metrics of other scenarios with different misclassification rates would be very helpful for planning further biomarker development and future trials.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers.

Author Correction: Best practices for benchmarking germline small-variant calls in human genomes.

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.

Best practices for benchmarking germline small-variant calls in human genomes.

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.

Identification, characterization, and targeting of IL-4 receptor by IL-4-Pseudomonas exotoxin in mouse models of anaplastic thyroid cancer.

Thyroid cancer is a rapidly increasing endocrine cancer. Since interleukin-4 receptor (IL-4R) is overexpressed in human solid cancer, we examined expression of IL-4R in 50 cases of anaplastic thyroid cancer (ATC), 37 well-differentiated papillary cancer (WDPC), 35 well-differentiated follicular cancer of thyroid (WDFC), and 37 normal thyroid specimens by immunohistochemistry (IHC) and in-situ hybridization (ISH) techniques. We demonstrated that IL-4Rα was overexpressed in 36/50 (72%) ATC, 20/35 (57%) WDFC, and 11/37 (30%) WDPC tumors.

Overall conceptual framework for studying the genetics of autoimmune diseases following vaccination: a regulatory perspective.

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.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

Background: Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model.

Results: We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays.

In silico analysis of autoimmune diseases and genetic relationships to vaccination against infectious diseases.

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.

Interleukin-4 receptor alpha overexpression in human bladder cancer correlates with the pathological grade and stage of the disease.

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.

Gene markers of cellular aging in human multipotent stromal cells in culture.

Introduction: Human multipotent stromal cells (MSCs) isolated from bone marrow or other tissue sources have great potential to treat a wide range of injuries and disorders in the field of regenerative medicine and tissue engineering. In particular, MSCs have inherent characteristics to suppress the immune system and are being studied in clinical studies to prevent graft-versus-host disease. MSCs can be expanded in vitro and have potential for differentiation into multiple cell lineages.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods.

Targeting angiogenesis via a c-Myc/hypoxia-inducible factor-1alpha-dependent pathway in multiple myeloma.

Bone marrow angiogenesis is associated with multiple myeloma (MM) progression. Here, we report high constitutive hypoxia-inducible factor-1alpha (Hif-1alpha) expression in MM cells, which is associated with oncogenic c-Myc. A drug screen for anti-MM agents that decrease Hif-1alpha and c-Myc levels identified a variety of compounds, including bortezomib, lenalidomide, enzastaurin, and adaphostin.

Chromosomal instability is associated with higher expression of genes implicated in epithelial-mesenchymal transition, cancer invasiveness, and metastasis and with lower expression of genes involved in cell cycle checkpoints, DNA repair, and chromatin maintenance.

Chromosomal instability-a hallmark of epithelial cancers-is an ongoing process that results in aneuploidy and karyotypic heterogeneity of a cancer cell population. Previously, we stratified cancer cell lines in the NCI-60 drug discovery panel based on their karyotypic complexity and heterogeneity. Using this stratification in conjunction with drug response data for the cell lines allowed us to identify classes of chemical compounds whose growth-inhibitory activity correlates with karyotypic complexity and chromosomal instability.

Challenges in DNA microarray studies from the regulatory perspective.

Genomic classifiers using DNA microarrays are becoming powerful tools in the medical community with the potential to revolutionize the diagnosis and treatment of disease. However, despite the tremendous interest in using these classifiers in diagnosis and the management of disease, few genomic classifiers have made it into clinical practice. Some of the major challenges for the development and validation of genomic classifiers will be discussed in this article together with some of their difficulties.

Detailed DNA methylation profiles of the E-cadherin promoter in the NCI-60 cancer cells.

E-cadherin (E-cad) is a transmembrane adhesion glycoprotein, the expression of which is often reduced in invasive or metastatic tumors. To assess E-cad's distribution among different types of cancer cells, we used bisulfite-sequencing for detailed, base-by-base measurement of CpG methylation in E-cad's promoter region in the NCI-60 cell lines. The mean methylation levels of the cell lines were distributed bimodally, with values pushed toward either the high or low end of the methylation scale.

Women participating in a dietary intervention trial maintain dietary changes without much effect on household members.

This study examined whether subjects who participated in a 12-mo intervention would maintain their diets 1 yr after the study ended and whether the diets of household members were affected. Premenopausal women, who had at least one first-degree relative with breast cancer (n = 122), were randomized to one of four diets: control, low fat (15% of energy), high fruit and vegetable (FV, nine servings per day), and combination low fat, high FV. Study subjects and one household member were asked to complete the Block '95 food-frequency questionnaire (FFQ) at baseline, 1 yr, and 2 yr.

Integrating data on DNA copy number with gene expression levels and drug sensitivities in the NCI-60 cell line panel.

Chromosome rearrangement, a hallmark of cancer, has profound effects on carcinogenesis and tumor phenotype. We used a panel of 60 human cancer cell lines (the NCI-60) as a model system to identify relationships among DNA copy number, mRNA expression level, and drug sensitivity. For each of 64 cancer-relevant genes, we calculated all 4,096 possible Pearson's correlation coefficients relating DNA copy number (assessed by comparative genomic hybridization using bacterial artificial chromosome microarrays) and mRNA expression level (determined using both cDNA and Affymetrix oligonucleotide microarrays).

Karyotypic "state" as a potential determinant for anticancer drug discovery.

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.

Predicting drug sensitivity and resistance: profiling ABC transporter genes in cancer cells.

For analysis of multidrug resistance, a major barrier to effective cancer chemotherapy, we profiled mRNA expression of the 48 known human ABC transporters in 60 diverse cancer cell lines (the NCI-60) used by the National Cancer Institute to screen for anticancer activity. The use of real-time RT-PCR avoided artifacts commonly encountered with microarray technologies. By correlating the results with the growth inhibitory profiles of 1,429 candidate anticancer drugs tested against the cells, we identified which transporters are more likely than others to confer resistance to which agents.

Levels of 5-hydroxymethyl-2'-deoxyuridine in DNA from women participating in an intervention trial of low-fat and low-energy diets.

Oxidative DNA damage in blood appears to be useful as a marker of systemic oxidative stress levels. Dietary factors such as fat and energy intakes have been indicated to affect oxidative stress levels, and this may be an important mechanism by which diet can modulate cancer risk. The primary objective of this study was to investigate the effects of dietary intervention in premenopausal women on the levels of one type of oxidative DNA damage: 5-hydroxymethyl-2'-deoxyuridine.