LncRNA expression signatures for stroke mice
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ABSTRACT:
PROVIDER: PRJNA671676 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To identify the overall impact of permanent ischemia injury on lncRNAs, we profile differentially expressed lncRNAs using microarray analysis in mouse brains subjected to permenant focal ischemia via electrocoagulation. At 24h after dMCAO injury, the animals were executed for microarray analysis of lncRNA expression.
2022-10-10 | GSE160030 | GEO
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Project description:L1CAM-positive extracellular vesicles (L1EV) are an emerging biomarker that may better reflect ongoing neuronal damage than other blood-based biomarkers. The physiological roles and regulation of L1EVs and their small RNA cargoes following stroke is unknown. We sought to characterize L1EV small RNAs following stroke and assess L1EV RNA signatures for diagnosing stroke using weighted gene co-expression network analysis and random forest (RF) machine learning algorithms. Interestingly, small RNA sequencing of plasma L1EVs from patients with stroke and control patients (n = 28) identified micro(mi)RNAs known to be enriched in the brain. Weighted gene co-expression network analysis (WGCNA) revealed small RNA transcript modules correlated to diagnosis, initial NIH stroke scale, and age. L1EV-derived RNA signatures associated with the diagnosis of AIS were derived from WGCNA and RF classification. These small RNA signatures demonstrated a high degree of accuracy in the diagnosis of AIS with an area under the curve (AUC) of the signatures ranging from 0.833- 0.932. Further work is necessary to understand the role of small RNA L1EV cargoes in the response to brain injury, however, this study supports the utility of L1EV small RNA signatures as a biomarker of stroke.
2024-06-28 | GSE269195 | GEO
Project description:Microglial activation after stroke may lead to development of inflammation-induced brain damage. Here we uncover a ribosome-based mechanism/check point involved in control of the innate immune response and microglial activation orchestrated by RNA binding protein SRSF3. Using an in vivo model-system for analysis of the dynamic translational state of microglial ribosomes with mRNAs as input and newly synthesized peptides as an output, we found a marked dissociation of microglia mRNA and protein signatures following ischemic stroke. Highly up-regulated and ribosomes associated mRNAs were not translated 24hrs after stroke resulting in two distinct microglial molecular signatures, a highly specialized pro-inflammatory mRNA and immunomodulatory/homeostatic protein signatures. We found that this is due to specific translational suppression of highly expressed mRNAs through a 3'UTR-mediated mechanism involving the RNA binding protein SRSF3. This discovery suggests avenues for therapeutic modulation of innate immune response in resident microglia after stroke.
2024-04-30 | GSE232244 | GEO
Project description:Differential Expression Data from Mice 24hrs after stroke
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Project description:Our team has constructed a prediction model based on the expression level of lncRNA (lncRNA-UCID、NEAT1、ciRS-7) to predict the chronicization of radiation-induced acute intestinal injury (RAII) and verified the predictive efficacy of the system in retrospective studies. This clinical study intends to further prospectively verify the accuracy of this prediction model in rectal cancer patients. In this study, we plan to enroll 200 patients diagnosed with locally advanced rectal cancer by pathology and MRI, who undergo neoadjuvant chemoradiotherapy (NCRT) and total mesorectal excision (TME) and develop RAII during NCRT or within 1 month. We will follow up the occurrence and progression of radiation-induced intestinal injury within 1 year after TME. Expression levels of lncRNA will be detected in pathological tissue after TME and applied to the prediction model to predict the chronicization of RAII. Based on the clinical diagnosis of chronic radiation-induced intestinal injury, the area under curve (AUC), accuracy, precision, specificity, and sensitivity of this prediction model in predicting the chronicization of RAII will be evaluated. The main outcome hypothesis is that the AUC of chronicization of RAII predicted by the prediction model based on the expression level of lncRNA is more than 0.8.
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Project description:Stroke remains a major leading cause of death and disability worldwide. Despite continuous advances, the identification of key molecular signatures of ischemic stroke within the hyper-acute phase of the disease is still of primary interest for a real translational research on stroke diagnosis, prognosis and treatment. High-throughput - omics technologies are enabling large-scale studies on stroke pathology at different molecular levels. Data integration resulting from these -omics approaches is becoming crucial to unravel the interactions among all different molecular elements and highly contribute to interpret all findings in a complex biological context. Here, we have used advanced data integration methods for multi-level joint analysis of transcriptomics and proteomics datasets depicted from the mouse brain 2h after cerebral ischemia. By modeling network-like correlation structures, we identified a set of differentially expressed genes and proteins by ischemia with a relevant association in stroke pathology. The ischemia-induced deregulation of 10 of these inter-correlated elements was successfully verified in a new cohort of ischemic mice, and changes in their expression pattern were also evaluated at a later time-point after cerebral ischemia. Of those, CLDN20, GADD45G, RGS2, BAG5 and CTNND2 were highlighted and evaluated as potential blood biomarkers of cerebral ischemia in blood samples from ischemic and sham-control mice and from ischemic strokes and other patients presenting stroke-mimicking conditions. Our findings indicated that CTNND2 and GADD45G levels in blood within the first hours after ischemic stroke might be potentially useful to discriminate ischemic strokes from mimics and to predict patients’ poor outcome after stroke, respectively. In summary, we have here used for the first time an integrative approach to elucidate by means of biostatistical tools key elements of the initial stages of the stroke pathophysiology, highlighting new outstanding proteins that might be further considered as blood biomarkers of ischemic stroke.
2020-09-02 | PXD016538 | Pride
Project description:Development of gene expression signatures for lncRNA MRPL23-AS1
| PRJNA563063 | ENA
Project description:Our study reveals that ischemic stroke can influence the expression of LncRNAs and mRNAs in the peripheral blood at both the acute and subacute stages
2019-02-27 | GSE122709 | GEO