Comprehensive circRNA Expression Profile and Construction of circRNAs-Related ceRNA Network in a Mouse Model of Autism.
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ABSTRACT:
SUBMITTER: Wang J
PROVIDER: S-EPMC7928284 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
2020-12-29 | GSE163904 | GEO
Project description:Comprehensive circRNA expression profile and construction of circRNAs-related ceRNA network in a mouse model of autism
| PRJNA688147 | ENA
Project description:Background and purposeAccumulating evidence suggests that circular RNAs (circRNAs) are involved in immune and inflammatory processes after acute ischemic stroke (AIS). However, the roles of circRNA-mediated competing endogenous RNA (ceRNA) in modulating immune inflammation of AIS have not yet been determined. This study aimed to construct a circRNA-mediated immune-related ceRNA network and identify novel circRNAs in AIS.MethodsMicroarray data were downloaded from the GEO database and further analysed by R software. Then, we constructed a circRNA-mediated ceRNA network based on interaction information from the bioinformatics database. A topological property analysis of the ceRNA network was conducted to screen novel circRNAs. Finally, we further applied quantitative real-time polymerase chain reaction (qRT-PCR) to two independent sets.ResultsWe constructed an AIS immune-related ceRNA (AISIRC) network containing immune-related genes (IRGs), miRNAs, and circRNAs. Additionally, we extracted the subnetwork from the AISIRC network and screened six immune-related circRNAs. After identification and validation, we finally confirmed that plasma levels of circPTP4A2 and circTLK2 were significantly increased in AIS patients compared with both healthy control subjects (HCs) and transient ischemic attack (TIA) patients. Logistic regression and receiver-operating characteristic (ROC) curve analyses demonstrated that these two circRNAs may function as predictive and discriminative biomarkers for AIS. We also confirmed that plasma levels of circPTP4A2 were elevated in TIA patients compared with HCs and might be an independent risk factor for predicting TIA. Longitudinal analysis of circRNA expression up to 90 days after AIS indicated that the ability of circPTP4A2 and circTLK2 to monitor AIS dynamics was highly desirable.ConclusionIn summary, the circRNA-mediated immune-related ceRNA network was successfully constructed, and two circulating circRNAs (circPTP4A2 and circTLK2) improved sensitivity for the diagnosis of AIS and could be considered diagnostic biomarkers.
| S-EPMC9304636 | biostudies-literature
Project description:Exosomes have been demonstrated to exert momentous roles in autism spectrum disorder (ASD). In this study, we aimed to make contribution to understanding pathogenesis of ASD and screen for the potential biomarkers associated with the occurrence and development of ASD.
2024-03-27 | GSE222046 | GEO
Project description:Purpose:Accumulating evidence has indicated that circRNAs are closely involved in tumorigenesis and progression of human cancers. However, the molecular mechanism underlying function of circRNAs in breast cancer has not been thoroughly elucidated. Currently, we aimed to characterize the circRNA-related competing endogenous RNA (ceRNA) regulatory network in breast cancer and to construct prognostic model. Materials and Methods:First, we constructed circRNA expression profiles for paired breast cancer in a Chinese population using a human circRNA microarray. Expression profiles of circRNAs, miRNAs, and mRNAs were retrieved from our circRNA dataset, the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We applied the limma and edgeR packages to identify differentially expressed RNAs. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules of mRNAs. Next, a ceRNA network was established based on circRNA-miRNA and miRNA-mRNA intersections. Both Cox regression analysis and ROC curve analysis were performed to generate prognostic model. Additionally, we performed Gene Set Enrichment Analysis (GSEA) on prognostic signatures. Results:Total of 59 circRNAs, 98 miRNAs and 3966 mRNAs were identified as differentially expressed RNAs. We first identified 38 miRNA-mRNA pairs and 38 circRNA-miRNA pairs to construct the circRNA-miRNA-mRNA regulatory network and then generated a prognostic model based on 7 signatures (MMD, SLC29A4, CREB5, FOS, ANKRD29, MYOCD, and PIGR), and patients with high-risk scores presented poor prognosis. Several cancer-related pathways were enriched, including the TGF-? pathway, the focal adhesion pathway, and the JAK-STAT signaling pathway, and 20 prognostic ceRNA regulatory networks were subsequently identified. Conclusion:In all, we screened a series of dysregulated circRNAs, miRNAs, and mRNAs, and constructed circRNA-related ceRNA network in breast cancer. Our findings may help to deepen the understanding of circRNA-related regulatory mechanisms. Moreover, we generated a prognostic model that provided new insight into postoperative management for breast cancer.
| S-EPMC7455596 | biostudies-literature
Project description:The morbidity and mortality of colorectal cancer (CRC) remained to be very high worldwide. Recently, circRNAs had been revealed to have a crucial role in cancer prognosis and progression. Numerous researches have shown that RNA sequencing technology and in silico method were widely used to identify pathogenic mechanisms and uncover promising targets for diagnosis and therapy. In this study, these methods were analyzed to obtain differentially expressed circRNAs (DECs). We identified upregulated 316 circRNAs and reduced 76 circRNAs in CRC samples, in comparison with those in normal tissues. In addition, a competitive endogenous network of circRNA-miRNA-mRNA was established to predict the mechanisms of circRNAs. Bioinformatics analysis revealed that these circRNAs participated in metabolism regulation and cell cycle progression. Of note, we observed the hub genes and miRNAs in this ceRNA network were associated with the survival time in CRC. We think this study could provide potential prognostic biomarkers and targets for CRC.
| S-EPMC7481959 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs) are now under hot discussion as novel promising biomarkers for patients with hepatocellular carcinoma (HCC). The purpose of our study is to identify several competing endogenous RNA (ceRNA) networks related to the prognosis and progression of HCC and to further investigate the mechanism of their influence on tumor progression.MethodsFirst, we obtained gene expression data related to liver cancer from The Cancer Genome Atlas (TCGA) database (http://www.portal.gdc.cancer.gov/), including microRNA (miRNA) sequence, RNA sequence, and clinical information. A co-expression network was constructed through the Weighted Correlation Network Analysis (WGCNA) software package in R software. The differentially expressed messenger RNAs (DEmRNAs) in the key module were analyzed with the Database for Annotation Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/summary.jsp) to perform functional enrichment analysis including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The data of miRNA expression and clinical information downloaded from TCGA were utilized for survival analysis to detach the prognostic value of the DEmiRNAs of the key module.ResultsThe 201 differentially expressed miRNAs (DEmiRNAs) and 3,783 DEmRNAs were preliminarily identified through differential expression analysis. The co-expression networks of DEmiRNAs and DEmRNAs were constructed with WGCNA. Further analysis confirmed four miRNAs in the most significant module (blue module) were associated with the overall survival (OS) of patients with liver cancer, including hsa-miR-92b-3p, hsa-miR-122-3p, hsa-miR-139-5p, and hsa-miR-7850-5p. DAVID was used for functional enrichment analysis of 286 co-expressed mRNAs. The GO analysis results showed that the top enriched GO terms were oxidation-reduction process, extracellular exosome, and iron ion binding. In KEGG pathway analysis, the top three enriched terms included metabolic pathways, fatty acid degradation, and valine, leucine, and isoleucine degradation. In addition, we intersected the miRNA-mRNA interaction prediction results with the differentially expressed and prognostic mRNAs. We found that hsa-miR-92b-3p can be related to CPEB3 and ACADL. By overlapping the data of predicted circRNAs by circBank and differentially expressed circRNAs of GSE94508, we screened has_circ_0077210 as the upstream regulatory molecule of hsa-miR-92b-3p. Hsa_circ_0077210/hsa-miR-92b-3p/cytoplasmic polyadenylation element binding protein-3 (CPEB3) and acyl-Coenzyme A dehydrogenase, long chain (ACADL) were validated in HCC tissue.ConclusionOur research provides a mechanistic elucidation of the unknown ceRNA regulatory network in HCC. Hsa_circ_0077210 might serve a momentous therapeutic role to restrain the occurrence and development of HCC.
| S-EPMC7953168 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs), a new class of regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. The aim of this study was to identify circRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis.MethodsCircRNA (GSE101684, GSE101586), miRNA (GSE135918), and mRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNAs (DECs), miRNAs (DEMs), and mRNAs (DEGs) in LUAD. Circinteractome and StarBase were used to predict miRNAs and mRNAs, respectively. A circRNA-miRNA-mRNA-ceRNA network was constructed. Patient survival was analyzed using UALCAN, and a sub-network was established. Real-time quantitative PCR (qRT-PCR) was used to verify the expressed of DECs between LUAD tissues and paired adjacent normal tissues.ResultsHsa_circ_0072088 was identified as a differentially expressed (upregulated) circRNA in the two datasets. Intersection analysis identified hsa-miR-532-3p and hsa-miR-942 as the two miRNAs with the highest potential for binding to hsa_circ_0072088. Differential expression analysis and target gene prediction were performed to build a ceRNA network of hsa_circ_0072088 using Circinteractome/StarBase 3.0. Intersection analysis showed that TMEM52, IL24, POF1B, KIF1A, NHS, LBH, HIST2H2BE, ABCC3, PYCR1, CD79A, IGF2BP3, ANKRD17, GTSE1, MKI67, CLSPN, PLAU, LUC7L, MAGIX, GPATCH4, and ABAT were potential downstream mRNAs. The association between the expression level of 20 DEGs and LUAD patient survival was analyzed using UALCAN and GEPIA, which showed that IGF2BP3, MKI67, CD79A, and ABAT were related to patient survival. Hsa_circ_0072088 was verified upregulated by qRT-PCR.ConclusionThe circRNA hsa_circ_0072088, the DEMs (hsa-miR-532-3p and hsa-miR-942-5p), and the DEGs (IGF2BP3, MKI67, CD79A, and ABAT) may serve as prognostic markers in LUAD.
| S-EPMC8197624 | biostudies-literature
Project description:ObjectiveEsophageal cancer (ESCC) is reported to be the eighth most common malignant tumors worldwide with high mortality. However, the functions of majority circRNAs in ESCC requires to be further explored.MethodsThis study identified differently expressed circRNAs in 3 paired ESCC using RNA-sequencing method. The interactions among circRNAs, miRNAs, and mRNAs were predicted using bioinformatics analysis.ResultsIn this study, using RNA-sequencing method and integrated bioinformatics analysis, 418 overexpressed circRNAs and 637 reduced circRNAs in ESCC sample were identified. Based on the mechanism that circRNAs could play as ceRNAs to modulate targets expression, circRNA-miRNA and circRNA-miRNA-mRNA networks were constructed in this study. Based on the network analysis, 7 circRNAs, including circ_0002255, circ_0000530, circ_0001904, circ_0001005, circ_0000513, circ_0000075, and circ_0001121, were identified as key circRNAs in ESCC. We found that circ_0002255 was related to the regulation of substrate adhesion-dependent cell spreading. circ_0001121 was involved in regulating nucleocytoplasmic transport. circ_0000513 played a key role in regulating Adherens junction, B cell receptor signaling pathway. Meanwhile, we observed circ_0000075 was involved in regulating zinc II ion transport, transition metal ion homeostasis, and angiogenesis.ConclusionWe thought this study could provide novel biomarkers for the prognosis of ESCC.
| S-EPMC7474783 | biostudies-literature
Project description:BackgroundAberrant gene expression occurs in almost all diseases including constrictive pericarditis (CP). However, the dysregulation of genes underlying the CP remains unclear. This study aims to investigate the potential molecular mechanisms underlying CP and screen hub genes critical for the pathogenesis of CP.MethodsDifferentially expressed mRNAs, miRNAs, lncRNAs and circRNAs in pericardial tissues were screened using RNA-seq in CP patients and controls. Furthermore, functional annotation analysis and protein-protein interaction (PPI) network were carried out to investigate the potential key pathways and identify hub genes in CP. Subsequently, a ceRNA network was established and the key circRNAs were determined by Gene Set Enrichment Analysis (GSEA). Finally, the corresponding RNA-seq results were confirmed and validated with a quantitative real time-PCR (qRT-PCR).ResultsFunctional annotation analysis revealed that differentially expressed mRNAs (DEMs) mainly participated in inflammatory response related pathways and the 10 top genes with the highest degree in PPI network were considered as the hub genes. In addition, a total of 377 regulatory relationships among the differentially expressed genes (DEGs) could be constructed, from which a subsequent ceRNA network was also established, while the circRNAs were further validated with qRT-PCR and the key biological pathways were identified using GSEA as well.ConclusionsThe genes determined to have altered expression levels in CP may participate in a number of biological signaling processes leading to inflammation and fibrosis frequently encountered in CP, and, therefore, our novel findings may provide an insight into the pathogenesis, molecular biomarkers, and potential therapeutic targets in CP.
| S-EPMC7214901 | biostudies-literature