Similar Datasets
Project description:To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.
| S-EPMC6616370 | biostudies-literature
Project description:ExRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types Present Across Human Biofluids
| PRJNA510084 | ENA
Project description:Patients with high-grade gliomas and glioblastomas (GBMs) have poor survival despite optimal surgical and drug therapy. Minimally invasive diagnostic biomarkers would enable early diagnosis and tumor-specific treatments for 'personalized targeted' therapy, and would create the basis for response tracking in patients with GBM. Extracellular vesicles (EVs) isolated from cerebrospinal fluid and blood contain glioma-specific molecules, including tumor-derived EV RNAs that are detectable in small copy numbers in these biofluids. EV RNA mutations or expression changes are also detectable, the analysis of which gives rise to 'liquid biopsy' tumor profiling.
| S-EPMC5451268 | biostudies-literature
Project description:Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.
| S-EPMC6557167 | biostudies-literature
Project description:An integrative analysis of human biofluid data in the exRNA Atlas revealed the existence of distinct extracellular RNA cargo types. To determine whether different RNA isolation kits biased detection of certain exRNA cargo types, an integrative analysis was performed using pooled plasma and serum samples, where 10 different RNA isolation kits were applied.
2018-12-15 | GSE123865 | GEO
Project description:Extracellular vesicles (EVs) secreted in biological fluids contain several transcripts of the cell of origin, which may modify the functions and phenotype of proximal and distant cells. Cancer-derived EVs may promote a favorable microenvironment for cancer growth and invasion by acting on stroma and endothelial cells and may favor metastasis formation. The transcripts contained in cancer EVs may be exploited as biomarkers. Protein and extracellular RNA (exRNA) profiling in patient bio-fluids, such as blood and urine, was performed to identify molecular features with potential diagnostic and prognostic values. EVs are concentrated in saliva, and salivary EVs are particularly enriched in exRNAs. Several studies were focused on salivary EVs for the detection of biomarkers either of non-oral or oral cancers. The present paper provides an overview of the available studies on the diagnostic potential of exRNA profiling in salivary EVs.
| S-EPMC6679099 | biostudies-literature
Project description:To study in vivo CD8 T cell differentiation, we quantified the coexpression of multiple genes in single cells throughout immune responses. After in vitro activation, CD8 T cells rapidly express effector molecules and cease their expression when the antigen is removed. Gene behavior after in vivo activation, in contrast, was quite heterogeneous. Different mRNAs were induced at very different time points of the response, were transcribed during different time periods, and could decline or persist independently of the antigen load. Consequently, distinct gene coexpression patterns/different cell types were generated at the various phases of the immune responses. During primary stimulation, inflammatory molecules were induced and down-regulated shortly after activation, generating early cells that only mediated inflammation. Cytotoxic T cells were generated at the peak of the primary response, when individual cells simultaneously expressed multiple killer molecules, whereas memory cells lost killer capacity because they no longer coexpressed killer genes. Surprisingly, during secondary responses gene transcription became permanent. Secondary cells recovered after antigen elimination were more efficient killers than cytotoxic T cells present at the peak of the primary response. Thus, primary responses produced two transient effector types. However, after boosting, CD8 T cells differentiate into long-lived killer cells that persist in vivo in the absence of antigen.
| S-EPMC2118592 | biostudies-literature
Project description:Since extracellular vesicles (EVs) have emerged as a promising drug delivery system, diverse methods have been used to load them with active pharmaceutical ingredients (API) in preclinical and clinical studies. However, there is yet to be an engineered EV formulation approved for human use, a barrier driven in part by the intrinsic heterogeneity of EVs. API loading is rarely assessed in the context of single vesicle measurements of physicochemical properties but is likely administered in a heterogeneous fashion to the detriment of a consistent product. Here, we applied a suite of single-particle resolution methods to determine the loading of rhodamine 6G (R6G) surrogate cargo mimicking hydrophilic small molecule drugs across four common API loading methods: sonication, electroporation, freeze-thaw cycling and passive incubation. Loading efficiencies and alterations in the physical properties of EVs were assessed, as well as co-localization with common EV-associated tetraspanins (i.e., CD63, CD81 and CD9) for insight into EV subpopulations. Sonication had the highest loading efficiency, yet significantly decreased particle yield, while electroporation led to the greatest number of loaded API particles, albeit at a lower efficiency. Moreover, results were often inconsistent between repeated runs within a given method, demonstrating the difficulty in developing a rigorous loading method that consistently loaded EVs across their heterogeneous subpopulations. This work highlights the significance of how chosen quantification metrics can impact apparent conclusions and the importance of single-particle characterization of EV loading.
| S-EPMC11342351 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-01-03 | GSE230290 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-06-10 | E-GEOD-39528 | biostudies-arrayexpress