Validation of Fragile X Screening in the Newborn Population Using a Fit-for-Purpose FMR1 PCR Assay System.

Newborn screening is designed for presymptomatic identification of serious conditions with effective early interventions. Clinical laboratories must perform prospective pilot studies to ensure that the analytical performance and workflow for a given screening test are appropriate. We assessed the potential to screen newborns for fragile X syndrome, a monogenic neurodevelopmental disorder, by establishing a customized, high-throughput PCR and analysis software system designed to detect fragile X mental retardation 1 gene repeat expansions from dried blood spots (DBSs). Assay precision, accuracy, sensitivity, and specificity were characterized across the categorical range of repeat expansions. The assay consistently resolved genotypes within three CGG repeats of reference values up to at least 137 repeats and within six repeats for larger expansions up to 200 repeats. Accuracy testing results were concordant with reference results. Full and premutation alleles were detected from subnanogram DNA inputs eluted from DBSs and from mixtures with down to 1% relative abundance of the respective expansion. Analysis of 963 deidentified newborn DBS samples identified 957 normal and 6 premutation specimens, consistent with previously published prevalence estimates. These studies demonstrate that the assay system can support high-throughput newborn screening programs.

Multilaboratory Assessment of a New Reference Material for Quality Assurance of Cell-Free Tumor DNA Measurements.

We conducted a multilaboratory assessment to determine the suitability of a new commercially available reference material with 40 cancer variants in a background of wild-type DNA at four different variant allele frequencies (VAFs): 2%, 0.50%, 0.125%, and 0%. The variants include single nucleotides, insertions, deletions, and two structural variations selected for their clinical importance and to challenge the performance of next-generation sequencing (NGS) methods. Fragmented DNA was formulated to simulate the size distribution of circulating wild-type and tumor DNA in a synthetic plasma matrix. DNA was extracted from these samples and characterized with different methods and multiple laboratories. The various extraction methods had differences in yield, perhaps because of differences in chemistry. Digital PCR assays were used to measure VAFs to compare results from different NGS methods. Comparable VAFs were observed across the different NGS methods. This multilaboratory assessment demonstrates that the new reference material is an appropriate tool to determine the analytical parameters of different measurement methods and to ensure their quality assurance.

An Integrated Next-Generation Sequencing System for Analyzing DNA Mutations, Gene Fusions, and RNA Expression in Lung Cancer.

We developed and characterized a next-generation sequencing (NGS) technology for streamlined analysis of DNA and RNA using low-input, low-quality cancer specimens. A single-workflow, targeted NGS panel for non-small cell lung cancer (NSCLC) was designed covering 135 RNA and 55 DNA disease-relevant targets. This multiomic panel was used to assess 219 formalin-fixed paraffin-embedded NSCLC surgical resections and core needle biopsies. Mutations and expression phenotypes were identified consistent with previous large-scale genomic studies, including mutually exclusive DNA and RNA oncogenic driver events. Evaluation of a second cohort of low cell count fine-needle aspirate smears from the BATTLE-2 trial yielded 97% agreement with an independent, validated NGS panel that was used with matched surgical specimens. Collectively, our data indicate that broad, clinically actionable insights that previously required independent assays, workflows, and analyses to assess both DNA and RNA can be conjoined in a first-tier, highly multiplexed NGS test, thereby providing faster, simpler, and more economical results.

Design, Optimization, and Multisite Evaluation of a Targeted Next-Generation Sequencing Assay System for Chimeric RNAs from Gene Fusions and Exon-Skipping Events in Non-Small Cell Lung Cancer.

Lung cancer accounts for approximately 14% of all newly diagnosed cancers and is the leading cause of cancer-related deaths. Chimeric RNA resulting from gene fusions (RNA fusions) and other RNA splicing errors are driver events and clinically addressable targets for non-small cell lung cancer (NSCLC). The reliable assessment of these RNA markers by next-generation sequencing requires integrated reagents, protocols, and interpretive software that can harmonize procedures and ensure consistent results across laboratories. We describe the development and verification of a system for targeted RNA sequencing for the analysis of challenging, low-input solid tumor biopsies that includes reagents for nucleic acid quantification and library preparation, run controls, and companion bioinformatics software. Assay development reconciled sequence discrepancies in public databases, created predictive formalin-fixed, paraffin-embedded RNA qualification metrics, and eliminated read misidentification attributable to index hopping events on the next-generation sequencing flow cell. The optimized and standardized system was analytically verified internally and in a multiphase study conducted at five independent laboratories. The results show accurate, reproducible, and sensitive detection of RNA fusions, alternative splicing events, and other expression markers of NSCLC. This comprehensive approach, combining sample quantification, quality control, library preparation, and interpretive bioinformatics software, may accelerate the routine implementation of targeted RNA sequencing of formalin-fixed, paraffin-embedded samples relevant to NSCLC.

Molecular classification of thyroid lesions by combined testing for miRNA gene expression and somatic gene alterations.

Multiple molecular markers contribute to the pathogenesis of thyroid cancer and can provide valuable information to improve disease diagnosis and patient management. We performed a comprehensive evaluation of miRNA gene expression in diverse thyroid lesions (n = 534) and developed predictive models for the classification of thyroid nodules, alone or in combination with genotyping. Expression profiling by reverse transcription-quantitative polymerase chain reaction in surgical specimens (n = 257) identified specific miRNAs differentially expressed in 17 histopathological categories. Eight supervised machine learning algorithms were trained to discriminate benign from malignant lesions and evaluated for accuracy and robustness. The selected models showed invariant area under the receiver operating characteristic curve (AUC) in cross-validation (0.89), optimal AUC (0.94) in an independent set of preoperative thyroid nodule aspirates (n = 235), and classified 92% of benign lesions as low risk/negative and 92% of malignant lesions as high risk/positive. Surgical and preoperative specimens were further tested for the presence of 17 validated oncogenic gene alterations in the BRAF, RAS, RET or PAX8 genes. The miRNA-based classifiers complemented and significantly improved the diagnostic performance of the 17-mutation panel (p < 0.001 for McNemar's tests). In a subset of resected tissues (n = 54) and in an independent set of thyroid nodules with indeterminate cytology (n = 42), the optimized ThyraMIR Thyroid miRNA Classifier increased diagnostic sensitivity by 30-39% and correctly classified 100% of benign nodules negative by the 17-mutation panel. In contrast, testing with broad targeted next-generation sequencing panels decreased diagnostic specificity by detecting additional mutations of unknown clinical significance in 19-39% of benign lesions. Our results demonstrate that, independent of mutational status, miRNA expression profiles are strongly associated with altered molecular pathways underlying thyroid tumorigenesis. Combined testing for miRNA gene expression and well-established somatic gene alterations is a novel diagnostic strategy that can improve the preoperative diagnosis and surgical management of patients with indeterminate thyroid nodules.

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies.

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench ("wet bench") and data analyses conducted using bioinformatics pipelines ("dry bench"). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible "tag" PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.

Computational Analysis Reveals a Key Regulator of Cryptococcal Virulence and Determinant of Host Response.

UNLABELLED: Cryptococcus neoformans is a ubiquitous, opportunistic fungal pathogen that kills over 600,000 people annually. Here, we report integrated computational and experimental investigations of the role and mechanisms of transcriptional regulation in cryptococcal infection. Major cryptococcal virulence traits include melanin production and the development of a large polysaccharide capsule upon host entry; shed capsule polysaccharides also impair host defenses. We found that both transcription and translation are required for capsule growth and that Usv101 is a master regulator of pathogenesis, regulating melanin production, capsule growth, and capsule shedding. It does this by directly regulating genes encoding glycoactive enzymes and genes encoding three other transcription factors that are essential for capsule growth: GAT201, RIM101, and SP1. Murine infection with cryptococci lacking Usv101 significantly alters the kinetics and pathogenesis of disease, with extended survival and, unexpectedly, death by pneumonia rather than meningitis. Our approaches and findings will inform studies of other pathogenic microbes. IMPORTANCE: Cryptococcus neoformans causes fatal meningitis in immunocompromised individuals, mainly HIV positive, killing over 600,000 each year. A unique feature of this yeast, which makes it particularly virulent, is its polysaccharide capsule; this structure impedes host efforts to combat infection. Capsule size and structure respond to environmental conditions, such as those encountered in an infected host. We have combined computational and experimental tools to elucidate capsule regulation, which we show primarily occurs at the transcriptional level. We also demonstrate that loss of a novel transcription factor alters virulence factor expression and host cell interactions, changing the lethal condition from meningitis to pneumonia with an exacerbated host response. We further demonstrate the relevant targets of regulation and kinetically map key regulatory and host interactions. Our work elucidates mechanisms of capsule regulation, provides methods and resources to the research community, and demonstrates an altered pathogenic outcome that resembles some human conditions.

Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation.

Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying transcription factors (TFs) involved in a specific process and used it to map regulation of the key virulence factor of a deadly fungus-its capsule. The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, midlevel, and "foreman" TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. These resources and analyses provide the first integrated, systems-level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to laboratories focused on specific physiological processes.

Identification of the galactosyltransferase of Cryptococcus neoformans involved in the biosynthesis of basidiomycete-type glycosylinositolphosphoceramide.

The pathogenic fungus Cryptococcus neoformans synthesizes a complex family of glycosylinositolphosphoceramide (GIPC) structures. These glycosphingolipids (GSLs) consist of mannosylinositolphosphoceramide (MIPC) extended by ß1-6-linked galactose, a unique structure that has to date only been identified in basidiomycetes. Further extension by up to five mannose residues and a branching xylose has been described. In this study, we identified and determined the gene structure of the enzyme Ggt1, which catalyzes the transfer of a galactose residue to MIPC. Deletion of the gene in C. neoformans resulted in complete loss of GIPCs containing galactose, a phenotype that could be restored by the episomal expression of Ggt1 in the deletion mutant. The entire annotated open reading frame, encoding a C-terminal GT31 galactosyltransferase domain and a large N-terminal domain of unknown function, was required for complementation. Notably, this gene does not encode a predicted signal sequence or transmembrane domain. The demonstration that Ggt1 is responsible for the transfer of a galactose residue to a GSL thus raises questions regarding the topology of this biosynthetic pathway and the function of the N-terminal domain. Phylogenetic analysis of the GGT1 gene shows conservation in hetero- and homobasidiomycetes but no homologs in ascomycetes or outside of the fungal kingdom.

Mapping functional transcription factor networks from gene expression data.

A critical step in understanding how a genome functions is determining which transcription factors (TFs) regulate each gene. Accordingly, extensive effort has been devoted to mapping TF networks. In Saccharomyces cerevisiae, protein-DNA interactions have been identified for most TFs by ChIP-chip, and expression profiling has been done on strains deleted for most TFs. These studies revealed that there is little overlap between the genes whose promoters are bound by a TF and those whose expression changes when the TF is deleted, leaving us without a definitive TF network for any eukaryote and without an efficient method for mapping functional TF networks. This paper describes NetProphet, a novel algorithm that improves the efficiency of network mapping from gene expression data. NetProphet exploits a fundamental observation about the nature of TF networks: The response to disrupting or overexpressing a TF is strongest on its direct targets and dissipates rapidly as it propagates through the network. Using S. cerevisiae data, we show that NetProphet can predict thousands of direct, functional regulatory interactions, using only gene expression data. The targets that NetProphet predicts for a TF are at least as likely to have sites matching the TF's binding specificity as the targets implicated by ChIP. Unlike most ChIP targets, the NetProphet targets also show evidence of functional regulation. This suggests a surprising conclusion: The best way to begin mapping direct, functional TF-promoter interactions may not be by measuring binding. We also show that NetProphet yields new insights into the functions of several yeast TFs, including a well-studied TF, Cbf1, and a completely unstudied TF, Eds1.

Reduced DICER1 elicits an interferon response in endometrial cancer cells.

DICER1 is essential for the generation of mature miRNAs and other short noncoding RNAs. Several lines of investigation implicate DICER1 as a tumor suppressor. Reduced DICER1 levels and changes in miRNA abundance have been associated with aggressive tumor phenotypes. The global effects of reduced DICER1 on mRNA transcript abundance in tumor cells remain largely unknown. We used short hairpin RNA to stably knock down DICER1 in endometrial cancer cell lines to begin to determine how reduced DICER1 activity contributes to tumor phenotypes. DICER1 knockdown did not affect cell proliferation but caused enhanced cell migration and growth in soft agar. miRNA and mRNA profiling in KLE cells revealed overall decreases in miRNA levels and changes in the relative abundance of many mRNAs. One of the most striking changes in mRNA levels was the upregulation of IFN-stimulated genes (ISG), the majority of which lack known miRNA target sequences. IFNß, a key upstream regulator of the IFN response, was significantly increased in DICER1 knockdowns in the AN3CA, Ishikawa, and KLE endometrial cancer cell lines and in the normal endometrial cell line EM-E6/E7/TERT. IFNß secreted in media from KLE and EM-E6/E7/TERT shDcr cells was sufficient to activate an IFN response in HT29 cells. The reduced miRNA processing in DICER1 knockdowns was associated with increases in pre-miRNAs in the cytoplasm. Our findings suggest that elevated pre-miRNA levels trigger the IFN response to double-stranded RNA. We thus report a novel effect of reduced DICER1 function in cancer cells.

Toward an integrated model of capsule regulation in Cryptococcus neoformans.

Cryptococcus neoformans is an opportunistic fungal pathogen that causes serious human disease in immunocompromised populations. Its polysaccharide capsule is a key virulence factor which is regulated in response to growth conditions, becoming enlarged in the context of infection. We used microarray analysis of cells stimulated to form capsule over a range of growth conditions to identify a transcriptional signature associated with capsule enlargement. The signature contains 880 genes, is enriched for genes encoding known capsule regulators, and includes many uncharacterized sequences. One uncharacterized sequence encodes a novel regulator of capsule and of fungal virulence. This factor is a homolog of the yeast protein Ada2, a member of the Spt-Ada-Gcn5 Acetyltransferase (SAGA) complex that regulates transcription of stress response genes via histone acetylation. Consistent with this homology, the C. neoformans null mutant exhibits reduced histone H3 lysine 9 acetylation. It is also defective in response to a variety of stress conditions, demonstrating phenotypes that overlap with, but are not identical to, those of other fungi with altered SAGA complexes. The mutant also exhibits significant defects in sexual development and virulence. To establish the role of Ada2 in the broader network of capsule regulation we performed RNA-Seq on strains lacking either Ada2 or one of two other capsule regulators: Cir1 and Nrg1. Analysis of the results suggested that Ada2 functions downstream of both Cir1 and Nrg1 via components of the high osmolarity glycerol (HOG) pathway. To identify direct targets of Ada2, we performed ChIP-Seq analysis of histone acetylation in the Ada2 null mutant. These studies supported the role of Ada2 in the direct regulation of capsule and mating responses and suggested that it may also play a direct role in regulating capsule-independent antiphagocytic virulence factors. These results validate our experimental approach to dissecting capsule regulation and provide multiple targets for future investigation.

Emerging themes in cryptococcal capsule synthesis.

Cryptococcus neoformans, a basidiomycete yeast and opportunistic pathogen, expends significant biosynthetic effort on construction of a polysaccharide capsule with a radius that may be many times that of the cell. Beyond posing a stimulating challenge in terms of defining biosynthetic pathways, the capsule is required for this yeast to cause fatal disease. This combination has focused the attention of researchers on this system. Here we briefly review two aspects of the rapidly advancing field of capsule synthesis: the extensive variation that occurs in capsule polymers and the regulation of capsule biosynthesis.

Benchmarking regulatory network reconstruction with GRENDEL.

MOTIVATION: Over the past decade, the prospect of inferring networks of gene regulation from high-throughput experimental data has received a great deal of attention. In contrast to the massive effort that has gone into automated deconvolution of biological networks, relatively little effort has been invested in benchmarking the proposed algorithms. The rate at which new network inference methods are being proposed far outpaces our ability to objectively evaluate and compare them. This is largely due to a lack of fully understood biological networks to use as gold standards. RESULTS: We have developed the most realistic system to date that generates synthetic regulatory networks for benchmarking reconstruction algorithms. The improved biological realism of our benchmark leads to conclusions about the relative accuracies of reconstruction algorithms that are significantly different from those obtained with A-BIOCHEM, an established in silico benchmark. AVAILABILITY: The synthetic benchmark utility and the specific benchmark networks that were used in our analyses are available at http://mblab.wustl.edu/software/grendel/.