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Identification a lncRNA/circRNA-miRNA-mRNA ceRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis

ABSTRACT: Identification a lncRNA/circRNA-miRNA-mRNA ceRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis

PROVIDER: PRJNA945480 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR23886383_1.fastq.gz	Fastqsanger.gz
	SRR23886383_2.fastq.gz	Fastqsanger.gz
	SRR23886384_1.fastq.gz	Fastqsanger.gz
	SRR23886384_2.fastq.gz	Fastqsanger.gz
	SRR23886385_1.fastq.gz	Fastqsanger.gz

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Identification a lncRNA/circRNA-miRNA-mRNA ceRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis

Project description:The study was designed to explore the ceRNA network in Nasopharyngeal Carcinoma

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Comprehensive analysis of the whole coding and noncoding RNA transcriptome expression profiles and construction of the circRNA-lncRNA co-regulated ceRNA network in laryngeal squamous cell carcinoma [circRNA]

Project description:We explored the whole expression profiles of transcriptome included miRNA, circRNA, lncRNA and mRNA in 5 pairs of LSCC and matched non-LSCC tissues by microarray The LSCC-related competing endogenous RNA (ceRNA) networks were constructed based on these microarray data.

2020-07-10 | GSE117001 | GEO

CircRNA expression-profiling to predict prognosis in locoregionally advanced nasopharyngeal carcinoma

Project description:CircRNAs serve as prognostic biomarkers in various types of cancer. We aimed to identify a circRNA signature for individual relapse risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

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Identification of a lncRNA/circRNA-miRNA-mRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis.

Project description:Background: Accumulating evidence indicates that non-coding RNAs (ncRNA), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), can function as competitive endogenous RNAs (ceRNAs) by binding to microRNAs (miRNAs) and regulating host gene expression at the transcriptional or post-transcriptional level. Dysregulation in ceRNA network regulation has been implicated in the occurrence and development of cancer. However, the lncRNA/circRNA-miRNA-mRNA regulatory network is still lacking in nasopharyngeal carcinoma (NPC). Methods: Differentially expressed genes (DEGs) were obtained from our previous sequencing data and Gene Expression Omnibus (GEO). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were used to explore the biological functions of these common DEGs. Through a series of bioinformatic analyses, the lncRNA/circRNA-miRNA-mRNA network was established. In additional, the external data GSE102349 was used to test the prognostic value of the hub mRNAs through the Kaplan-Meier method. Results: We successfully constructed a lncRNA/circRNA-miRNA-mRNA network in NPC, consisting of 16 lncRNAs, 6 miRNAs, 3 circRNAs and 10 mRNAs and found that three genes (TOP2A, ZWINT, TTK) were significantly associated with overall survival time (OS) in patients. Conclusion: The regulatory network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving NPC, and provide novel candidate biomarkers for evaluating the prognosis of NPC.

| S-EPMC10905391 | biostudies-literature

Competitive Endogenous RNA Landscape in Epstein-Barr Virus Associated Nasopharyngeal Carcinoma

Project description:In this study, we investigated the role of microRNAs and circular RNAs in Nasopharyngeal Carcinoma (NPC) by constructing a circRNA-miRNA-mRNA co-expression network and performing differential expression analysis on mRNAs, miRNAs, and circRNAs. By comparing the expression profile of non-cancerous immortalized nasopharyngeal epithelial cell lines and NPC cell lines, we identified differentially expressed coding and non-coding RNAs. By leveraging coexpression and miRNA target prediction tools, we constructed a ceRNA network composed of mRNAs, miRNAs, and circRNAs.

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Differenatiation of ceRNA (circRNA, lncRNA and mRNA) expression in PBMCs (peripheral blood mononuclear cells)

Project description:To determine ceRNA transcribed during the PBMCs, we have employed whole genome microarray expression profiling as a discovery platform to identify ceRNA expression in PBMCs donated by T1DM (type 1 diabetes mellitus) patients and healthy volunteers.

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CircRNA sequencing analysis of PTMC with lateral lymph node metastases and related clinical value studies of circRNA.

Project description:High-throughput sequencing was used to detect the expression profile of circRNA in PTMC of lymph node metastasis in lateral cervical region, and RT-qPCR was used to detect the expression of circRNA in cancer tissues and normal tissues adjacent to cancer. The receiver operating characteristic (ROC) curve and the area under ROC curve (AUC) were used to evaluate whether CircRNAs could be used as a biomarker for the diagnosis of thyroid cancer. Bioinformatics was used to predict the PTMC-related ceRNA mechanism of lateral cervical lymph node metastasis.

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Project description:Purpose: We aimed to detected the circRNA expression profile and constructed a circRNA-based competing endogenous RNA (ceRNA) network in autism. Methods:Valproate acid was used to establish an in vivo model of autism in mice. circRNAs in autism group was identified by RNA sequencing. The expression of circRNAs were detected by real-time PCR. Module analysis was conducted followed by GO and KEGG pathway enrichment analysis. Results: A total of 1059 differentially expressed circRNAs (477 upregulated and 582 downregulated) in autism group. The expression of novel_circ_015779 and novel_circ_035247 were detected by real-time PCR. A ceRNA network based on altered circRNAs was established, with 9715 nodes and 150408 edges. The top three modules were all correlated with autism-related pathways involving ‘TGF-beta signaling pathway’, ‘Notch signaling pathway’, ‘MAPK signaling pathway’, ‘long term depression’, ‘thyroid hormone signaling pathway’, etc. Conclusions: The present study reveals a novel circRNA involved mechanisms in the pathogenesis of autism.

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