Methyl-CpG-binding domain sequencing reveals a prognostic methylation signature in neuroblastoma

Accurate assessment of neuroblastoma outcome prediction remains challenging. Therefore, this study aims at establishing novel prognostic tumor DNA methylation biomarkers. In total, 396 low- and high-risk primary tumors were analyzed, of which 87 were profiled using methyl-CpG-binding domain (MBD) sequencing for differential methylation analysis between prognostic patient groups. Subsequently, methylation-specific PCR (MSP) assays were developed for 78 top-ranking differentially methylated regions and tested on two independent cohorts of 132 and 177 samples, respectively. Further, a new statistical framework was used to identify a robust set of MSP assays of which the methylation score (i.e. the percentage of methylated assays) allows accurate outcome prediction. Survival analyses were performed on the individual target level, as well as on the combined multimarker signature. As a result of the differential DNA methylation assessment by MBD sequencing, 58 of the 78 MSP assays were designed in regions previously unexplored in neuroblastoma, and 36 are located in non-promoter or non-coding regions. In total, 5 individual MSP assays (located in CCDC177, NXPH1, lnc-MRPL3-2, lnc-TREX1-1 and one on a region from chromosome 8 with no further annotation) predict event-free survival and 4 additional assays (located in SPRED3, TNFAIP2, NPM2 and CYYR1) also predict overall survival. Furthermore, a robust 58-marker methylation signature predicting overall and event-free survival was established. In conclusion, this study encompasses the largest DNA methylation biomarker study in neuroblastoma so far. We identified and independently validated several novel prognostic biomarkers, as well as a prognostic 58-marker methylation signature

Application of Volcano Plots in Analyses of mRNA Differential Expressions with Microarrays

Volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log10(p-value) from the t test). We review the basic and an interactive use of the volcano plot, and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide an unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility to apply volcano plots to other fields beyond microarray.Comment: 8 figure

EGFR is required for Wnt9a-Fzd9b signalling specificity in haematopoietic stem cells.

Wnt signalling drives many processes in development, homeostasis and disease; however, the role and mechanism of individual ligand-receptor (Wnt-Frizzled (Fzd)) interactions in specific biological processes remain poorly understood. Wnt9a is specifically required for the amplification of blood progenitor cells during development. Using genetic studies in zebrafish and human embryonic stem cells, paired with in vitro cell biology and biochemistry, we determined that Wnt9a signals specifically through Fzd9b to elicit β-catenin-dependent Wnt signalling that regulates haematopoietic stem and progenitor cell emergence. We demonstrate that the epidermal growth factor receptor (EGFR) is required as a cofactor for Wnt9a-Fzd9b signalling. EGFR-mediated phosphorylation of one tyrosine residue on the Fzd9b intracellular tail in response to Wnt9a promotes internalization of the Wnt9a-Fzd9b-LRP signalosome and subsequent signal transduction. These findings provide mechanistic insights for specific Wnt-Fzd signals, which will be crucial for specific therapeutic targeting and regenerative medicine

Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance

The acquisition of language and speech is uniquely human, but how genetic changes might have adapted the nervous system to this capacity is not well understood. Two human-specific amino acid substitutions in the transcription factor forkhead box P2 (FOXP2) are outstanding mechanistic candidates, as they could have been positively selected during human evolution and as FOXP2 is the sole gene to date firmly linked to speech and language development. When these two substitutions are introduced into the endogenous Foxp2 gene of mice (Foxp2[superscript hum]), cortico-basal ganglia circuits are specifically affected. Here we demonstrate marked effects of this humanization of Foxp2 on learning and striatal neuroplasticity. Foxp2[superscript hum/hum] mice learn stimulus–response associations faster than their WT littermates in situations in which declarative (i.e., place-based) and procedural (i.e., response-based) forms of learning could compete during transitions toward proceduralization of action sequences. Striatal districts known to be differently related to these two modes of learning are affected differently in the Foxp2[superscript hum/hum] mice, as judged by measures of dopamine levels, gene expression patterns, and synaptic plasticity, including an NMDA receptor-dependent form of long-term depression. These findings raise the possibility that the humanized Foxp2 phenotype reflects a different tuning of corticostriatal systems involved in declarative and procedural learning, a capacity potentially contributing to adapting the human brain for speech and language acquisition.Nancy Lurie Marks Family FoundationSimons Foundation (Autism Research Initiative Grant 137593)National Institutes of Health (U.S.) (Grant R01 MH060379)Wellcome Trust (London, England) (Grant 075491/Z/04)Wellcome Trust (London, England) (Grant 080971)Fondation pour la recherche medicaleMax Planck Society for the Advancement of Scienc

Molecular markers of risk of subsequent invasive breast cancer in women with ductal carcinoma in situ: protocol for a population-based cohort study

INTRODUCTION: Ductal carcinoma in situ (DCIS) of the breast is a non-obligate precursor of invasive breast cancer (IBC). Many DCIS patients are either undertreated or overtreated. The overarching goal of the study described here is to facilitate detection of patients with DCIS at risk of IBC development. Here, we propose to use risk factor data and formalin-fixed paraffin-embedded (FFPE) DCIS tissue from a large, ethnically diverse, population-based cohort of 8175 women with a first diagnosis of DCIS and followed for subsequent IBC to: identify/validate miRNA expression changes in DCIS tissue associated with risk of subsequent IBC; evaluate ipsilateral IBC risk in association with two previously identified marker sets (triple immunopositivity for p16, COX-2, Ki67; Oncotype DX Breast DCIS score); examine the association of risk factor data with IBC risk. METHODS AND ANALYSIS: We are conducting a series of case-control studies nested within the cohort. Cases are women with DCIS who developed subsequent IBC; controls (2/case) are matched to cases on calendar year of and age at DCIS diagnosis. We project 485 cases/970 controls in the aim focused on risk factors. We estimate obtaining FFPE tissue for 320 cases/640 controls for the aim focused on miRNAs; of these, 173 cases/346 controls will be included in the aim focused on p16, COX-2 and Ki67 immunopositivity, and of the latter, 156 case-control pairs will be included in the aim focused on the Oncotype DX Breast DCIS score®. Multivariate conditional logistic regression will be used for statistical analyses. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Institutional Review Boards of Albert Einstein College of Medicine (IRB 2014-3611), Kaiser Permanente Colorado, Kaiser Permanente Hawaii, Henry Ford Health System, Mayo Clinic, Marshfield Clinic Research Institute and Hackensack Meridian Health, and from Lifespan Research Protection Office. The study results will be presented at meetings and published in peer-reviewed journals

Genomic and Transcriptomic Differentiation of Independent Invasions of the Pacific Oyster Crassostrea gigas

Upon colonizing new habitats, invasive species face a series of new selection pressures as a result of changing abiotic conditions and novel biotic interactions with native species. These new selection pressures can be accommodated by different mechanisms that act on different levels and across different time scales: (1) By changing transcriptomic profiles, species can react by plasticity within individual physiological limitations. (2) Invasive populations can adapt by fixing beneficial genetic variants in response to the newly encountered selection pressures. Here, we compare the genomic and transcriptomic landscapes of two independent invasions of the Pacific Oyster (Crassostrea gigas) into the North Sea. In detail, we combine ddRAD sequencing on the genomic level with RNAseq on the transcriptomic level to reveal outlier loci (SNPs) indicative of adaptation, as well as transcriptomic profiles from a translocation experiment to show immediate physiological reactions between two populations characterizing the two independent invasions. Generally, we found low physical congruence between differentially regulated genes and outlier loci, indicating that different genes are involved on the different time scales. Functionally matching outlier loci and differentially expressed genes were however found for spliceosomal modification of mRNA and particularly for transposon activation, indicating that these variation creating processes might be connected across eco-physiological and evolutionary time scales. By contrasting and identifying functional congruence between population outlier loci and population specific transcriptomic profiles, we can thus reveal a glimpse at the traits and processes characterizing specific mechanisms involved in successful invasions

Epigallocatechin Gallate Modulates Microglia Phenotype to Suppress Pro-Inflammatory Signalling Cues and Inhibit Phagocytosis

Microglia are crucial players in the pathogenesis of late onset Alzheimer’s Disease (AD), with evidence for both deleterious and beneficial effects. Identifying interventions to modulate microglial responsiveness, to promote Amyloid β (Aβ) clearance, disrupt plaque formation, or to dampen excessive inflammation has therapeutic potential. Bioavailable flavonoids, such as the flavan 3-ols, are of interest due to their antioxidant, metal chelating, signalling and anti-inflammatory potential. Primary microglia were treated with a series of structurally related flavanol 3-ols to assess effects on phagocytosis, cytokine release and transcriptional responses by RNA sequencing. Data indicated that the extent of hydroxylation and the presence of the galloyl moiety were strong determinants of flavan 3-ol activity. Epigallocatechin gallate (EGCG) was the most effective flavan-3-ol tested and strongly inhibited phagocytosis of Aβ independent of any metal chelating properties, suggesting a more direct modulation of microglia responsiveness. EGCG was broadly anti-inflammatory, reducing cytokine release and downregulating transcription, particularly of components of the microglia extracellular matrix such as MMP3 and SerpinB2. Collectively, this brings new insight into the actions of flavonoids on microglial responsiveness with potential implications for the therapeutic use of EGCG and structurally related flavanol-3-ols in AD

Group A Streptococcal S Protein Utilizes Red Blood Cells as Immune Camouflage and Is a Critical Determinant for Immune Evasion.

Group A Streptococcus (GAS) is a human-specific pathogen that evades the host immune response through the elaboration of multiple virulence factors. Although many of these factors have been studied, numerous proteins encoded by the GAS genome are of unknown function. Herein, we characterize a biomimetic red blood cell (RBC)-captured protein of unknown function-annotated subsequently as S protein-in GAS pathophysiology. S protein maintains the hydrophobic properties of GAS, and its absence reduces survival in human blood. S protein facilitates GAS coating with lysed RBCs to promote molecular mimicry, which increases virulence in vitro and in vivo. Proteomic profiling reveals that the removal of S protein from GAS alters cellular and extracellular protein landscapes and is accompanied by a decrease in the abundance of several key GAS virulence determinants. In vivo, the absence of S protein results in a striking attenuation of virulence and promotes a robust immune response and immunological memory

Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data

Background: Long non-coding RNAs (lncRNAs) are typically expressed at low levels and are inherently highly variable. This is a fundamental challenge for differential expression (DE) analysis. In this study, the performance of 25 pipelines for testing DE in RNA-seq data is comprehensively evaluated, with a particular focus on lncRNAs and low-abundance mRNAs. Fifteen performance metrics are used to evaluate DE tools and normalization methods using simulations and analyses of six diverse RNA-seq datasets. Results: Gene expression data are simulated using non-parametric procedures in such a way that realistic levels of expression and variability are preserved in the simulated data. Throughout the assessment, results for mRNA and lncRNA were tracked separately. All the pipelines exhibit inferior performance for lncRNAs compared to mRNAs across all simulated scenarios and benchmark RNA-seq datasets. The substandard performance of DE tools for lncRNAs applies also to low-abundance mRNAs. No single tool uniformly outperformed the others. Variability, number of samples, and fraction of DE genes markedly influenced DE tool performance. Conclusions: Overall, linear modeling with empirical Bayes moderation (limma) and a non-parametric approach (SAMSeq) showed good control of the false discovery rate and reasonable sensitivity. Of note, for achieving a sensitivity of at least 50%, more than 80 samples are required when studying expression levels in realistic settings such as in clinical cancer research. About half of the methods showed a substantial excess of false discoveries, making these methods unreliable for DE analysis and jeopardizing reproducible science. The detailed results of our study can be consulted through a user-friendly web application, giving guidance on selection of the optimal DE tool (http://statapps.ugent.be/tools/AppDGE/)