Long non-coding RNA and circular RNA and coding RNA profiling of plasma exosomes of osteosarcoma by RNA seq
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE218526 | GEO | 2023/05/27
REPOSITORIES: GEO
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2024-10-25 | GSE272078 | GEO
Project description:Cardiac myxoma (CM) is an important aetiology of stroke in young adults, and its diagnosis is difficult in patients having stroke because of the lack of diagnostic biomarkers. Tumour-derived exosomes play a crucial role in tumour growth, metastasis, and immune regulation, and monitor disease development. We established an RNA-sequencing dataset for long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) in the plasma and tumour-derived exosomes from four patients with cardiac myxoma-related ischaemic stroke (CM-IS) and six patients with cardiac myxoma without ischaemic stroke (non-IS CM). Clean data (15.48 Gb) were obtained for lncRNAs and mRNAs. Moreover, 5,533 lncRNAs, 1,331 known miRNAs, and 412 new miRNAs were identified. Finally, gene expression profiles and differentially expressed genes were analysed in 20 samples. In the plasma samples, 74 miRNAs, 12 lncRNAs, and 693 mRNAs were identified. Tumour-derived tissue samples contained 61 miRNAs, 67 lncRNAs, and 433 mRNAs. This dataset provides a significant resource for relevant researchers to explore the potential dysregulated lncRNAs, miRNAs, and mRNAs of plasma and tumour-derived exosomes in CM-IS versus CM without stroke.
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Project description:Objective: The diagnostic roles of long non-coding RNAs (lncRNAs) in clear cell renal cell carcinoma (ccRCC) are still not well defined. We aimed to identify differentially expressed lncRNAs and mRNAs in plasma of ccRCC patients and health controls systematically. Methods: Expression profile of lncRNAs and mRNAs in plasma from ccRCC patients and healthy controls was analyzed by microarray assay. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway based approaches were used to investigate biological functions and signaling pathways affected by the differentially expressed mRNAs. SOCS2-AS1 was selected for validation using Real-Time PCR. The differentially expressed genes were further compared with E-MTAB-1830 datasets by Venn and NetworkAnalyst website. The expression level and overall survival (OS) of differentially expressed mRNAs were analyzed in GEPIA and ULCAN website. Results: Compared with healthy controls, a total of 3,664 differentially expressed lncRNAs were revealed by heatmap and volcano-plot, including up-regulation in 1,511 and down-regulation in 2,153 (fold change ≥ 2 and P < 0.05), respectively. And differential expression was noticed in 2,268 mRNAs, including up-regulation in 932 mRNAs and down-regulation in 1,336 mRNAs, respectively (fold change ≥ 2 and P < 0.05). Pathways analysis based on deregulated mRNAs were mainly involved in melanogenesis and Hippo signaling pathway (P < 0.05). The expression of SOCS2-AS1 was down in ccRCC plasma and tissues, as well as in cell lines, which was the same as the results of lncRNA microarray. Compared with the E-MTAB-1830 gene expression profiles, we identified 18 lncRNAs, and 87 mRNAs were differently expressed in both plasma and neoplastic tissues of ccRCC. Ten mRNAs (EPB41L4B, CCND1, GGT1, CGNL1, CYSLTR1, PLAUR, UGT3A1, PROM2, MUC12, and PCK1) were correlated with the overall survival (OS) rate in ccRCC patients based on the GEPIA and ULCAN website.Conclusions: We first reported differentially expressed lncRNAs in ccRCC patient and healthy control systemically. Combined with the published dataset, we identified several differentially expressed lncRNAs and mRNAs which might to be diagnostic or prognostic markers. The biological functions of those lncRNAs and mRNAs should be further validated. Taken together, this study provided the basis for future treatment of ccRCC and novel insights into cancer biology.
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Project description:Purpose: This study aimed to explore the differential expression profiles of exosomal lncRNAs and evaluated their potential utility in the accurate diagnosis of LAA stroke. Methods: LncRNA profiles of exosomes in large artery atherosclerosis stroke and controls were generated by high-throughput sequencing. The sequence reads that passed quality filters were analyzed at the transcript isoform level with Hisat2, Trapnell, STAR. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results: A total of 1020 differentially expressed lncRNAs were identified in LAA stroke patients. GO and KEGG pathway analyses indicated that their target genes are involved in atherosclerosis-related pathways, including inflammation, cell adhesion, and cell migration. 8 exosomal lncRNAs were confirmed with qRT–PCR.The result showed that the expression trend of differential expressed lncRNAs in validation was consistent with RNA-seq.Conclusion: Our study showed the differential expression of lncRNAs in plasma exosomes and presented related diagnostic potential for LAA stroke for the first time. The results suggested that exosomal lncRNA could be potential diagnostic tools in LAA stroke. Circular RNAs (circRNAs), novel endogenous noncoding RNAs, play diverse roles in ischemic stroke. Recently, the abundance and stability of circRNAs in exosomes have been identified. However, a comprehensive analysis of exosomal circRNAs in large artery atherosclerotic (LAA) stroke has not yet been reported. We performed RNA sequencing (RNA-Seq) to comprehensively identify differentially expressed exosomal circRNAs in five paired LAA and normal controls. RNA-Seq identified a total of 462 circRNAs in peripheral exosomes; there were 25 differentially expressed circRNAs among them. Additionally, circRNA competing endogenous RNA (ceRNA) network and translatable analysis revealed the potential functions of the exosomal circRNAs in LAA progression. Two ceRNA pathways involving 5 circRNAs, 2 miRNAs, and 3 mRNAs were confirmed by qRT-PCR. In the validation cohort, receiver operating characteristic (ROC) curve analysis identified two circRNAs as possible novel biomarkers, and a logistic model combining two and four circRNAs increased the area under the curve compared with the individual circRNAs.
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