GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data.

BACKGROUND: The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats-normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently. RESULTS: We developed the GeneTonic software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. GeneTonic is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. GeneTonic is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility. CONCLUSION: GeneTonic is distributed as an R package in the Bioconductor project ( https://bioconductor.org/packages/GeneTonic/ ) under the MIT license. Offering both bird's-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, GeneTonic aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.

ideal: an R/Bioconductor package for interactive differential expression analysis.

BACKGROUND: RNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking. RESULTS: We developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpretation. ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility. CONCLUSION: ideal is distributed as an R package in the Bioconductor project ( http://bioconductor.org/packages/ideal/ ), and provides a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, empowering researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.

Time-saving polyp detection in colon capsule endoscopy: evaluation of a novel software algorithm.

BACKGROUND: Colon capsule endoscopy (CCE) is a reliable method to detect colonic polyps in the well-prepared colon. As CCE evaluation can be time consuming, a new software algorithm might aid in reducing evaluation time. OBJECTIVES: The aim of the study was to evaluate whether it is feasible to reliably detect colon polyps in CCE videos with a new software algorithm the "collage mode" (Rapid 8 Software, Covidien/Medtronic®). METHODS: Twenty-nine CCE videos were randomly presented to three experienced and to three inexperienced investigators. Videos were evaluated by applying the collage mode. Investigation time was documented and the results (≥one polyp vs. no polyp) were compared with the findings of two highly experienced central readers who read the CCE videos in the standard mode beforehand. RESULTS: It took a median time of 9.8, 3.5, and 7.5 vs. 4.3, 4.6 and 12.5 min for experienced vs. inexperienced investigators to review the CCE videos. For detecting ≥one polyp vs. no polyp, sensitivity of 93.3%, 73.3%, and 93.3% was observed for the experienced and sensitivity of 46.7%, 33.3%, and 93.3% for the inexperienced CCE readers. CONCLUSION: Collage mode might allow for a quick review of CCE videos with a high polyp detection rate for experienced CCE readers. Future prospective studies should include CCE collage mode for rapid polyp detection to further prove the feasibility of practical colon polyp detection by CCE and possibly support the role of CCE as a screening tool in CRC prevention.

Histone deacetylase 10 promotes autophagy-mediated cell survival.

Tumor cells activate autophagy in response to chemotherapy-induced DNA damage as a survival program to cope with metabolic stress. Here, we provide in vitro and in vivo evidence that histone deacetylase (HDAC)10 promotes autophagy-mediated survival in neuroblastoma cells. We show that both knockdown and inhibition of HDAC10 effectively disrupted autophagy associated with sensitization to cytotoxic drug treatment in a panel of highly malignant V-MYC myelocytomatosis viral-related oncogene, neuroblastoma derived-amplified neuroblastoma cell lines, in contrast to nontransformed cells. HDAC10 depletion in neuroblastoma cells interrupted autophagic flux and induced accumulation of autophagosomes, lysosomes, and a prominent substrate of the autophagic degradation pathway, p62/sequestosome 1. Enforced HDAC10 expression protected neuroblastoma cells against doxorubicin treatment through interaction with heat shock protein 70 family proteins, causing their deacetylation. Conversely, heat shock protein 70/heat shock cognate 70 was acetylated in HDAC10-depleted cells. HDAC10 expression levels in high-risk neuroblastomas correlated with autophagy in gene-set analysis and predicted treatment success in patients with advanced stage 4 neuroblastomas. Our results demonstrate that HDAC10 protects cancer cells from cytotoxic agents by mediating autophagy and identify this HDAC isozyme as a druggable regulator of advanced-stage tumor cell survival. Moreover, these results propose a promising way to considerably improve treatment response in the neuroblastoma patient subgroup with the poorest outcome.

Histone deacetylase 8 in neuroblastoma tumorigenesis.

PURPOSE: The effects of pan-histone deacetylase (HDAC) inhibitors on cancer cells have shown that HDACs are involved in fundamental tumor biological processes such as cell cycle control, differentiation, and apoptosis. However, because of the unselective nature of these compounds, little is known about the contribution of individual HDAC family members to tumorigenesis and progression. The purpose of this study was to evaluate the role of individual HDACs in neuroblastoma tumorigenesis. EXPERIMENTAL DESIGN: We have investigated the mRNA expression of all HDAC1-11 family members in a large cohort of primary neuroblastoma samples covering the full spectrum of the disease. HDACs associated with disease stage and survival were subsequently functionally evaluated in cell culture models. RESULTS: Only HDAC8 expression was significantly correlated with advanced disease and metastasis and down-regulated in stage 4S neuroblastoma associated with spontaneous regression. High HDAC8 expression was associated with poor prognostic markers and poor overall and event-free survival. The knockdown of HDAC8 resulted in the inhibition of proliferation, reduced clonogenic growth, cell cycle arrest, and differentiation in cultured neuroblastoma cells. The treatment of neuroblastoma cell lines as well as short-term-culture neuroblastoma cells with an HDAC8-selective small-molecule inhibitor inhibited cell proliferation and clone formation, induced differentiation, and thus reproduced the HDAC8 knockdown phenotype. Global histone 4 acetylation was not affected by HDAC8 knockdown or by selective inhibitor treatment. CONCLUSIONS: Our data point toward an important role of HDAC8 in neuroblastoma pathogenesis and identify this HDAC family member as a specific drug target for the differentiation therapy of neuroblastoma.

Common miRNA Patterns of Alzheimer's Disease and Parkinson's Disease and Their Putative Impact on Commensal Gut Microbiota.

With the rise of Next-Generation-Sequencing (NGS) methods, Micro-RNAs (miRNAs) have achieved an important position in the research landscape and have been found to present valuable diagnostic tools in various diseases such as multiple sclerosis or lung cancer. There is also emerging evidence that miRNAs play an important role in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease (AD) or Parkinson's disease (PD). Apparently, these diseases come along with changes in miRNA expression patterns which led to attempts from researchers to use these small RNA species from several body fluids for a better diagnosis and in order to observe disease progression. Additionally, it became evident that microbial commensals might play an important role for pathology development and were shown to have a significantly different composition in patients suffering from neurodegeneration compared with healthy controls. As it could recently be shown that secreted miRNAs are able to enter microbial organisms, it is conceivable that the host's miRNA might affect the gut microbial ecosystem. As such, miRNAs may inherit a central role in shaping the "diseased microbiome" and thereby mutually act on the characteristics of these neurodegenerative diseases. We have therefore (1) compiled a list of miRNAs known to be associated with AD and/or PD, (2) performed an in silico target screen for binding sites of these miRNA on human gut metagenome sequences and (3) evaluated the hit list for interesting matches potentially relevant to the etiology of AD and or PD. The examination of protein identifiers connected to bacterial secretion system, lipopolysaccharide biosynthesis and biofilm formation revealed an overlap of 37 bacterial proteins that were targeted by human miRNAs. The identified links of miRNAs to the biological processes of bacteria connected to AD and PD have yet to be validated via in vivo experiments. However, our results show a promising new approach for understanding aspects of these neurodegenerative diseases in light of the regulation of the microbiome.