Project description:The dataset was used to study the effect of 2 hours of western classical music concert performance on the peripheral blood microRNA transcriptome in professional musicians.
Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
Project description:The goal of this study is to identify circulating microRNAs with prognostic value in a large cohort of comatose survivors of out-of-hospital cardiac arrest. We performed RNA-Seq for short RNAs in plasma, collected 48 hours after return of spontaneous circulation, of 50 cardiac arrest patients including 25 good neurological outcome at 6 months (cerebral performance category 1) and 25 poor neurological outcome including death at 6 months (cerebral performance category score 5). The sequencing generated on average 18.5 million reads per sample. After mapping the reads and counting to relevant entries in miRBase 20, we found 236 microRNAs detected in all 50 samples with TPM above or equals to 1. 11 microRNAs were differentially expressed between 2 groups with False Discovery Rate (FDR) < 5%.
Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
Project description:This data is part of a miRNA platform comparison study. We compared the performance characteristics of four commercial miRNA array technologies and found that all platforms performed well in separate measures of performance. The Ambion and Agilent platforms were more accurate, whereas the Illumina and Exiqon platforms were more specific. Furthermore, the data analysis approach had a large impact on the performance, predominantly by improving precision. Performance of four (4) commercially available miRNA platforms was evaluated using 7 placenta samples spiked with synthetic microRNA spikes (in Latin-square design) absent in placenta. Platforms were primarily evaluated for accuracy and specificity.
Project description:We report performance of six different protocols for small RNAseq library preparation and of a method utilizing sequencing of probes targeting microRNAs (HTG EdgeSeq). Recently, small RNA sequencing (small RNA-seq) has been introduced as a method for quantifying circulating microRNAs (miRNAs) and enabling their global profiling without prior knowledge of target sequences. Despite its great promise, small RNA-seq has not delivered the expected outcomes, particularly due to ligation and PCR bias introduced within the workflow. In this study, we assessed the performance of all existing approaches to the small RNA-seq of miRNAs in plasma samples: original two adapter ligation approach; single adapter ligation with subsequent circularization; polyadenylation; use of randomized adapters; and use of unique molecular identifiers (UMI). Using comprehensive set of metrics, we evaluated each protocol in terms of yield, precision, accuracy, sensitivity, and ability to detect isomiRs. Moreover, we assessed performance of targeted RNA-seq method utilizing hybridization probes across relevant metrics and together with RT-qPCR we used it as a reference for accuracy evaluation. The best results were delivered by targeted RNA-seq outperforming other methods in all relevant parameters. The protocols using randomized adapters or UMIs showed consistent good performance across all of the assessed metrics. In contrast, the polyadenylation approach generated a high percentage of discarded reads and impeded the analysis of isomiRs. The single adapter ligation with subsequent circularization failed to prevent ligation bias and the traditional two adapter ligation approach achieved the worse scores in the majority of tested metrics. To sum, we provide a comprehensive comparison that can serve as a guide for new users interested in analysis of circulating miRNAs and as a reference for further comparative studies.