A workflow for the creation of regulatory networks integrating miRNAs and lncRNAs associated with exposure to ionizing radiation using open source data and tools

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are involved in the modulation of the DNA-damage response (DDR) and upon exposure to ionizing radiation (IR), their expression fluctuates. In this study, we propose a workflow that enables the creation of regulatory networks by integrating transcriptomics data as well as regulatory data in order to better understand the interplay between genes, transcription factors (TFs), miRNAs, and lncRNAs in the cellular response to IR. We preprocessed and analyzed publicly available gene expression profiles and then applied our consensus and integration approach using open source data and tools. To exemplify the benefits of our proposed workflow, we identified a total of 32 differentially expressed transcripts corresponding to 20 unique differentially expressed genes (DEGs) and using these DEGs, we constructed a regulatory network consisting of 106 interactions and 100 nodes (11 DEGs, 78 miRNAs, 1 DEG acting as a TF, and 10 lncRNAs). Overrepresentation analyses (ORAs) furthermore linked our DEGs and miRNAs to annotations pertaining to the DDR and to IR. Our results show that MDM2 and E2F7 function as network hubs, and E2F7, miR-25-3p, let-7a-5p, and miR-497-5p are the four nodes with the highest betweenness centrality. In brief, our workflow, that is based on open source data and tools, and that generates a regulatory network, provides novel insights into the regulatory mechanisms involving miRNAs and lncRNAs in the cellular response to IR

A workflow for the creation of regulatory networks integrating miRNAs and lncRNAs associated with exposure to ionizing radiation using open source data and tools

MicroRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are involved in the modulation of the DNA-damage response (DDR) and upon exposure to ionizing radiation (IR), their expression fluctuates. In this study, we propose a workflow that enables the creation of regulatory networks by integrating transcriptomics data as well as regulatory data in order to better understand the interplay between genes, transcription factors (TFs), miRNAs, and lncRNAs in the cellular response to IR. We preprocessed and analyzed publicly available gene expression profiles and then applied our consensus and integration approach using open source data and tools. To exemplify the benefits of our proposed workflow, we identified a total of 32 differentially expressed transcripts corresponding to 20 unique differentially expressed genes (DEGs) and using these DEGs, we constructed a regulatory network consisting of 106 interactions and 100 nodes (11 DEGs, 78 miRNAs, 1 DEG acting as a TF, and 10 lncRNAs). Overrepresentation analyses (ORAs) furthermore linked our DEGs and miRNAs to annotations pertaining to the DDR and to IR. Our results show that MDM2 and E2F7 function as network hubs, and E2F7, miR-25-3p, let-7a-5p, and miR-497-5p are the four nodes with the highest betweenness centrality. In brief, our workflow, that is based on open source data and tools, and that generates a regulatory network, provides novel insights into the regulatory mechanisms involving miRNAs and lncRNAs in the cellular response to IR

Patient Recruitment System for Clinical Trials: Mixed Methods Study About Requirements at Ten University Hospitals

BackgroundClinical trials are the gold standard for advancing medical knowledge and improving patient outcomes. For their success, an appropriately sized cohort is required. However, patient recruitment remains one of the most challenging aspects of clinical trials. Information technology (IT) support systems—for instance, patient recruitment systems—may help overcome existing challenges and improve recruitment rates, when customized to the user needs and environment. ObjectiveThe goal of our study is to describe the status quo of patient recruitment processes and to identify user requirements for the development of a patient recruitment system. MethodsWe conducted a web-based survey with 56 participants as well as semistructured interviews with 33 participants from 10 German university hospitals. ResultsWe here report the recruitment procedures and challenges of 10 university hospitals. The recruitment process was influenced by diverse factors such as the ward, use of software, and the study inclusion criteria. Overall, clinical staff seemed more involved in patient identification, while the research staff focused on screening tasks. Ad hoc and planned screenings were common. Identifying eligible patients was still associated with significant manual efforts. The recruitment staff used Microsoft Office suite because tailored software were not available. To implement such software, data from disparate sources will need to be made available. We discussed concrete technical challenges concerning patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration, and we contributed to the support of developing a successful system. ConclusionsIdentifying eligible patients is still associated with significant manual efforts. To fully make use of the high potential of IT in patient recruitment, many technical and process challenges have to be solved first. We contribute and discuss concrete technical challenges for patient recruitment systems, including requirements for features, data, infrastructure, and workflow integration

MicroRNA Expression Changes during Interferon-Beta Treatment in the Peripheral Blood of Multiple Sclerosis Patients

MicroRNAs (miRNAs) are small non-coding RNA molecules acting as post-transcriptional regulators of gene expression. They are involved in many biological processes, and their dysregulation is implicated in various diseases, including multiple sclerosis (MS). Interferon-beta (IFN-beta) is widely used as a first-line immunomodulatory treatment of MS patients. Here, we present the first longitudinal study on the miRNA expression changes in response to IFN-beta therapy. Peripheral blood mononuclear cells (PBMC) were obtained before treatment initiation as well as after two days, four days, and one month, from patients with clinically isolated syndrome (CIS) and patients with relapsing-remitting MS (RRMS). We measured the expression of 651 mature miRNAs and about 19,000 mRNAs in parallel using real-time PCR arrays and Affymetrix microarrays. We observed that the up-regulation of IFN-beta-responsive genes is accompanied by a down-regulation of several miRNAs, including members of the mir-29 family. These differentially expressed miRNAs were found to be associated with apoptotic processes and IFN feedback loops. A network of miRNA-mRNA target interactions was constructed by integrating the information from different databases. Our results suggest that miRNA-mediated regulation plays an important role in the mechanisms of action of IFN-beta, not only in the treatment of MS but also in normal immune responses. miRNA expression levels in the blood may serve as a biomarker of the biological effects of IFN-beta therapy that may predict individual disease activity and progression