miFRame: analysis and visualization of miRNA sequencing data in neurological disorders

Background: While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians. Methods: We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments. Results: We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates

miRTrail - a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases

<p>Abstract</p> <p>Background</p> <p>Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs) gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer.</p> <p>Results</p> <p>Here, we present miRTrail, an integrative tool that allows for performing comprehensive analyses of interactions of genes and miRNAs based on expression profiles. The integrated analysis of mRNA and miRNA data should generate more robust and reliable results on deregulated pathogenic processes and may also offer novel insights into the regulatory interactions between miRNAs and genes. Our web-server excels in carrying out gene sets analysis, analysis of miRNA sets as well as the combination of both in a systems biology approach. To this end, miRTrail integrates information on 20.000 genes, almost 1.000 miRNAs, and roughly 280.000 putative interactions, for Homo sapiens and accordingly for Mus musculus and Danio rerio. The well-established, classical Chi-squared test is one of the central techniques of our tool for the joint consideration of miRNAs and their targets. For interactively visualizing obtained results, it relies on the network analyzers and viewers BiNA or Cytoscape-web, also enabling direct access to relevant literature. We demonstrated the potential of miRTrail by applying our tool to mRNA and miRNA data of malignant melanoma. MiRTrail identified several deregulated miRNAs that target deregulated mRNAs including miRNAs hsa-miR-23b and hsa-miR-223, which target the highest numbers of deregulated mRNAs and regulate the pathway "basal cell carcinoma". In addition, both miRNAs target genes like PTCH1 and RASA1 that are involved in many oncogenic processes.</p> <p>Conclusions</p> <p>The application on melanoma samples demonstrates that the miRTrail platform may open avenues for investigating the regulatory interactions between genes and miRNAs for a wide range of human diseases. Moreover, miRTrail cannot only be applied to microarray based expression profiles, but also to NGS-based transcriptomic data. The program is freely available as web-server at mirtrail.bioinf.uni-sb.de.</p

miRNAs and sports: tracking training status and potentially confounding diagnoses

Background: The dependency of miRNA abundance from physiological processes such as exercises remains partially understood. We set out to analyze the effect of physical exercises on miRNA profiles in blood and plasma of endurance and strength athletes in a systematic manner and correlated differentially abundant miRNAs in athletes to disease miRNAs biomarkers towards a better understanding of how physical exercise may confound disease diagnosis by miRNAs. Methods: We profiled blood and plasma of 29 athletes before and after exercise. With four samples analyzed for each individual we analyzed 116 full miRNomes. The study set-up enabled paired analyses of individuals. Affected miRNAs were investigated for known disease associations using network analysis. Results: MiRNA patterns in blood and plasma of endurance and strength athletes vary significantly with differences in blood outreaching variations in plasma. We found only moderate differences between the miRNA levels before training and the RNA levels after training as compared to the more obvious variations found between strength athletes and endurance athletes. We observed significant variations in the abundance of miR-140-3p that is a known circulating disease markers (raw and adjusted p value of 5 × 10−12 and 4 × 10−7). Similarly, the levels of miR-140-5p and miR-650, both of which have been reported as makers for a wide range of human pathologies significantly depend on the training mode. Among the most affected disease categories we found acute myocardial infarction. MiRNAs, which are up-regulated in endurance athletes inhibit VEGFA as shown by systems biology analysis of experimentally validated target genes. Conclusion: We provide evidence that the mode and the extent of training are important confounding factors for a miRNA based disease diagnosis

Autoantibody Signature Differentiates Wilms Tumor Patients from Neuroblastoma Patients

Several studies report autoantibody signatures in cancer. The majority of these studies analyzed adult tumors and compared the seroreactivity pattern of tumor patients with the pattern in healthy controls. Here, we compared the autoimmune response in patients with neuroblastoma and patients with Wilms tumor representing two different childhood tumors. We were able to differentiate untreated neuroblastoma patients from untreated Wilms tumor patients with an accuracy of 86.8%, a sensitivity of 87.0% and a specificity of 86.7%. The separation of treated neuroblastoma patients from treated Wilms tumor patients' yielded comparable results with an accuracy of 83.8%. We furthermore identified the antigens that contribute most to the differentiation between both tumor types. The analysis of these antigens revealed that neuroblastoma was considerably more immunogenic than Wilms tumor. The reported antigens have not been found to be relevant for comparative analyses between other tumors and controls. In summary, neuroblastoma appears as a highly immunogenic tumor as demonstrated by the extended number of antigens that separate this tumor from Wilms tumor

Amplified Host Defense by Toll-Like Receptor-Mediated Downregulation of the Glucocorticoid-Induced Leucine Zipper (GILZ) in Macrophages

Activation of toll-like receptors (TLRs) plays a pivotal role in the host defense against bacteria and results in the activation of NF-κB-mediated transcription of proinflammatory mediators. Glucocorticoid-induced leucine zipper (GILZ) is an anti-inflammatory mediator, which inhibits NF-κB activity in macrophages. Thus, we aimed to investigate the regulation and role of GILZ expression in primary human and murine macrophages upon TLR activation. Treatment with TLR agonists, e.g., Pam3CSK4 (TLR1/2) or LPS (TLR4) rapidly decreased GILZ mRNA and protein levels. In consequence, GILZ downregulation led to enhanced induction of pro-inflammatory mediators, increased phagocytic activity, and a higher capacity to kill intracellular bacteria (Salmonella enterica serovar typhimurium), as shown in GILZ knockout macrophages. Treatment with the TLR3 ligand polyinosinic: polycytidylic acid [Poly(I:C)] did not affect GILZ mRNA levels, although GILZ protein expression was decreased. This effect was paralleled by sensitization toward TLR1/2- and TLR4-agonists. A bioinformatics approach implicated more than 250 miRNAs as potential GILZ regulators. Microarray analysis revealed that the expression of several potentially GILZ-targeting miRNAs was increased after Poly(I:C) treatment in primary human macrophages. We tested the ability of 11 of these miRNAs to target GILZ by luciferase reporter gene assays. Within this small set, four miRNAs (hsa-miR-34b*,−222,−320d,−484) were confirmed as GILZ regulators, suggesting that GILZ downregulation upon TLR3 activation is a consequence of the synergistic actions of multiple miRNAs. In summary, our data show that GILZ downregulation promotes macrophage activation. GILZ downregulation occurs both via MyD88-dependent and -independent mechanisms and can involve decreased mRNA or protein stability and an attenuated translation

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS

miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments

<p>Abstract</p> <p>Background</p> <p>Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls.</p> <p>Methods</p> <p>We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls.</p> <p>Results</p> <p>Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%].</p> <p>Conclusion</p> <p>Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells.</p