Identification of a Potentially Functional circRNA-miRNA-mRNA Regulatory Network in Melanocytes for Investigating Pathogenesis of Vitiligo.
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ABSTRACT:
SUBMITTER: Li L
PROVIDER: S-EPMC8098995 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundCircular RNAs (circRNAs) have received considerable attention in human cancer research. However, many circRNAs remain to be detected. In our study, we determined novel circRNAs and investigated their effects on bladder cancer (BCa).MethodsMicroarray dataset GSE92675 was downloaded from Gene Expression Omnibus (GEO). Then, we combined computational biology with quantitative real-time polymerase chain reaction (qRT-PCR) to select related circRNAs in BCa. The selected circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory subnetwork was determined by Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.ResultsThe regulatory network constructed from the microarray dataset (GSE92675) contained 49 differentially expressed circRNAs (DECs). GO and KEGG analyses showed that the MAPK and PI3K-AKT signaling pathways were statistically significant. On the basis of qRT-PCR and the degree value calculated by the cytoHubba plugin of Cytoscape, hsa_circ_0011385 was finally confirmed. The subnetwork around hsa_circ_0011385 was constructed. In addition, we created a protein-protein interaction (PPI) network composed of 67 nodes and 274 edges after removing independent nodes. GO and KEGG analyses showed that hubgenes were involved in cell cycle activities. Moreover, they could be regulated by miRNAs and play an eventful role in BCa pathogenesis.ConclusionsWe proposed a novel circRNA-miRNA-mRNA network related to BCa pathogenesis. This network might be a new molecular biomarker and could be used to develop potential treatment strategies for BCa.
| S-EPMC6990554 | biostudies-literature
Project description:BACKGROUND As all we know, gastric cancer (GC) is a highly aggressive disease. Recently, circular RNA (circRNA) was found to play a vital role in regulation of GC. Some circRNAs could regulate messenger RNA (mRNA) expression by functioning as a microRNA (miRNA) sponge. Nevertheless, the circRNA-miRNA-mRNA regulatory network involved GC rarely has been explored and researched. MATERIAL AND METHODS All the differentially expressed circRNAs, miRNAs, and mRNA were derived from Gene Expression Omnibus (GEO) microarray data (GSE78092, GSE89143, GSE93415, and GSE54129). GC level 3 miRNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Furthermore, a circRNA-miRNA-mRNA regulatory network was constructed by Cytoscape (version 3.6.1). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway revealed the functions and signaling pathways associated with these target genes. Hub genes of protein-protein interaction (PPI) network were identified by STRING database and cytoHubba. RESULTS The regulatory network consists of 3 circRNAs, 22 miRNAs, and 128 mRNAs. Only 3 miRNAs of the network were consistent with the expression of TCGA and were associated with some clinical features. The results of the functional analysis of 128 mRNAs showed that GO analysis and KEGG pathways of inclusion criteria were 49 and 24, respectively. PPI network and Cytoscape showed that the top 10 hub genes were MYC, CTGF, TGFBR2, TGFBR1, SERPINE1, KRAS, ZEB1, THBS1, CDK6, and TNS1; 4 of which were verified by GEPIA based on TCGA. Highly expressed SERPINE1 had a poor OS (over survival) and DFS (disease-free survival), and TGFBR1 expression increased along with the increase of clinical stages. CONCLUSIONS This study looked at a circRNA-miRNA-mRNA regulatory network associated with GC and explored the potential functions of mRNA in the network, then identified a new molecular marker for prediction, prognosis, and therapeutic targets for clinical patients.
| S-EPMC6880644 | biostudies-literature
Project description:The pathogenesis of nonalcoholic steatohepatitis (NASH) is still unclear, where involvement of circRNA is considered for its active role as "miRNA sponge". Therefore, we aimed to investigate the circRNA expression pattern in NASH and further construct the circRNA-miRNA-mRNA network for in-depth mechanism exploration. Briefly, NASH mice model was established by Methionine and choline deficiency (MCD) diet feeding. Liver circRNA and mRNA profile was initially screened by microarray and ensuing qRT-PCR verification was carried out. The overlapped predicted miRNAs as downstream targets of circRNAs and upstream regulators of mRNAs were verified by qRT-PCR and final circRNA-miRNA-mRNA network was constructed. Gene Ontology (GO) and KEGG pathway analysis were further applied to enrich the huge mRNA microarray data. To sum up, there were 69 up and 63 down regulated circRNAs as well as 2760 up and 2465 down regulated mRNAs in NASH group, comparing with control group. Randomly selected 13 of 14 mRNAs and 2 of 8 circRNAs were successfully verified by qRT-PCR. Through predicted overlapped miRNA verification, four circRNA-miRNA-mRNA pathways were constructed, including circRNA_002581-miR-122-Slc1a5, circRNA_002581- miR-122-Plp2, circRNA_002581-miR-122-Cpeb1 and circRNA_007585-miR-326- UCP2. GO and KEGG pathway analysis also enriched specific mRNAs. Therefore, circRNA profile may serve as candidate for NASH diagnosis and circRNA-miRNA -mRNA pathway may provide novel mechanism for NASH.
| S-EPMC5341813 | biostudies-literature
Project description:The growing evidence suggests that circular RNAs (circRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of circRNAs in lung adenocarcinoma (LUAD) remains unclear. This study clarified the potentially regulatory network and functional mechanism of circRNAs in LUAD. The expression data of circRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) were obtained from the Gene Expression Omnibus (GEO) database. Relying on GSE101586, GSE101684, and GSE112214, we identified differentially expressed circRNAs (DEcircRNAs). Depending on GSE135918 and GSE32863, we screened out differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs), respectively. Then, a novel competing endogenous RNA (ceRNA) regulatory network related to LUAD was constructed. We also revealed biological processes and signal pathways regulated by these DEcircRNAs. Based on gene expression data and survival information of LUAD patients in The Cancer Genome Atlas (TCGA) and GEO, we implemented survival analysis to select DEmRNAs related to prognosis and build a novel circRNA-miRNA-mRNA hub regulatory network. Meanwhile, quantitative real-time PCR (qRT-PCR) was utilized to validate DEcircRNAs in the ceRNA hub regulatory network. As a result, a total of 8 DEcircRNAs, 19 DEmiRNAs, and 85 DEmRNAs were identified. The novel ceRNA regulatory network included 5 circRNAs, 8 miRNAs, and 22 mRNAs. The final ceRNA hub regulatory network contained two circRNAs, two miRNAs, and two mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the five DEcircRNAs may affect LUAD onset and progression through Wnt signaling pathway and Hippo signaling pathway. All in all, this study revealed the regulatory network and functional mechanism of circRNA-related ceRNAs in LUAD.
| S-EPMC8292838 | biostudies-literature
Project description:Circular RNA (circRNA) abnormal expression and regulation are involved in the occurrence and development of a variety of tumors. However, the role of circRNAs still remains unknown in gastrointestinal stromal tumors (GISTs). In the present study, the differential circRNA expression profile of GISTs was screened by human circRNAs chip and verified by qRT-PCR. The circRNA-miRNA-mRNA regulatory network was constructed using the cytoHubba plugin based on the Cytoscape software. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore circRNA functions. Six significantly differential circRNAs were also verified in 20 pairs of GISTs and adjacent tissues by qRT-PCR. The result showed that a total of 543 differentially expressed circRNAs were identified in GISTs, of which 242 were up-regulated and 301 were down-regulated. Additionally, the circRNA-miRNA-mRNA network contained six circRNAs, 30 miRNAs, and 308 mRNAs, and the targeted mRNAs were associated with "regulation of biological process," "intracellular organelle," "protein binding," and enriched in Wnt signaling pathway. Furthermore, qRT-PCR demonstrated that hsa_circRNA_061346, hsa_circRNA_103114, and hsa_circRNA_103870 were significantly up-regulated in GISTs (n = 20), and hsa_ circRNA_405324, hsa_circRNA_406821, and hsa_circRNA_000361 were dramatically down-regulated in GISTs (n = 20). In addition, all of these circRNAs were shown to have high diagnostic values, and most of them were significantly associated with tumor size, mitotic figure, and malignant degrees in GISTs (P < 0.05). Therefore, we concluded that circRNAs were abnormally expressed in GISTs, and the circRNA-miRNA-mRNA regulatory network plays an important role in the occurrence and development of GISTs. Also, the identified six candidate circRNAs might be critical circRNAs and may present as potential diagnostic biomarkers for GISTs.
| S-EPMC7271966 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs) have received increasing attention in cancer development. However, a substantial number of circRNAs still require characterization. The purpose of this study is to uncover novel circRNAs and their molecular mechanism in bladder cancer (BCa).MethodsA combinative strategy of extensive data mining and computational biology was employed to identify BCa-related circRNAs and explore their potential mechanisms of action.ResultsThree differentially expressed circRNAs (has_circ_0023642, has_circ_0047322, has_circ_0041151) were obtained from the microarray dataset (GSE92675). Four miRNAs (miR-616, miR-515-5p, miR-647, miR-1178) with potential binding sites with these three circRNAs were identified. Pathway analysis demonstrated that all four miRNAs were closely associated with some cancer-related pathways. Survival analysis indicated that these miRNAs might potentially play a role in tumor-suppressive functions in BCa. Subsequently, 181 overlapping genes were identified from 472 up-regulated genes in BCa (TCGA database), and 10,017 predicted target genes of the four miRNAs obtained. A circRNA-miRNA-mRNA network was constructed on the identified three circRNAs, four miRNAs, and 181 overlapping genes. Besides, six hub genes (CENPA, HIST1H2BJ, HIST1H2BO, HIST1H3H, HIST1H3B, HIST1H3F) were identified from establishing a protein-protein interaction (PPI) network on the same overlapping genes. Furthermore, a circRNA-miRNA-hub gene sub-network was built to delineate the links among the differential circRNAs, miRNA, and hub genes.ConclusionsOur study provided significant insights into the molecular mechanisms that regulate the progression of BCa from the circRNA-miRNA-mRNA network view.
| S-EPMC7844515 | biostudies-literature
Project description:BackgroundAbdominal aortic aneurysm (AAA) is a progressive cardiovascular disease, which is a permanent and localized dilatation of the abdominal aorta with potentially fatal consequence of aortic rupture. Dysregulation of circRNAs is correlated with the development of various pathological events in cardiovascular diseases. However, the function of circRNAs in abdominal aortic aneurysm (AAA) is unknown and remains to be explored. This study is aimed at determining the regulatory mechanisms of circRNAs in AAAs. This study was aimed at exploring the underlying molecular mechanisms of abdominal aortic aneurysms based on the competing endogenous RNA (ceRNA) regulatory hypothesis of circRNA, miRNA, and mRNA.MethodsThe expression profiles of circRNAs (GSE144431), miRNAs (GSE62179), and mRNAs (GSE7084, GSE57691, and GSE47472) in human tissue sample from the aneurysm group and normal group were obtained from the Gene Expression Omnibus database, respectively. The circRNA-miRNA-mRNA network was constructed by using Cytoscape 3.7.2 software; then, the protein-protein interaction (PPI) network was constructed by using the STRING database, and the hub genes were identified by using the cytoHubba plug-in. The circRNA-miRNA-hub gene regulatory subnetwork was formed to understand the regulatory axis of hub genes in AAAs.ResultsThe present study identified 40 differentially expressed circRNAs (DECs) in the GSE144431, 90 differentially expressed miRNAs (DEmiRs) in the GSE62179, and 168 differentially expressed mRNAs (DEGs) with the same direction regulation (130 downregulated and 38 upregulated) in the GSE7084, GSE57691, and GSE47472 datasets identified regarding AAAs. The miRNA response elements (MREs) of three DECs were then predicted. Four overlapping miRNAs were obtained by intersecting the predicted miRNA and DEmiRs. Then, 17 overlapping mRNAs were obtained by intersecting the predicted target mRNAs of 4 miRNAs with 168 DEGs. Furthermore, the circRNA-miRNA-mRNA network was constructed through 3 circRNAs, 4 miRNAs, and 17 mRNAs, and three hub genes (SOD2, CCR7, and PGRMC1) were identified. Simultaneously, functional enrichment and pathway analysis were performed within genes in the circRNA-miRNA-mRNA network. Three of them (SOD2, CCR7, and PGRMC1) were suggested to be crucial based on functional enrichment, protein-protein interaction, and ceRNA network analysis. Furthermore, the expression of SOD2 and CCR7 may be regulated by hsa_circ_0011449/hsa_circ_0081968/hsa-let-7f-5p; the expression of PGRMC1 may be regulated by hsa_circ_0011449/hsa_circ_0081968-hsa-let-7f-5p/hsa-let-7e-5p.ConclusionIn conclusion, the ceRNA interaction axis we identified may be an important target for the treatment of abdominal aortic aneurysms. This study provided further understanding of the potential pathogenesis from the perspective of the circRNA-related competitive endogenous RNA network in AAAs.
| S-EPMC8589483 | biostudies-literature
Project description:This study was to identify important circRNA-miRNA-mRNA (ceRNAs) regulatory mechanisms in hepatocellular carcinoma (HCC). The circRNA dataset GSE97332 and miRNA dataset GSE57555 were used for analyses. Functional enrichment analysis for miRNA and target gene was conducted using cluster Profiler. Survival analysis was conducted through R package Survival. The ceRNAs and drug-gene interaction networks were constructed. The ceRNAs network contained five miRNAs including hsa-miR-25-3p, hsa-miR-3692-5p, hsa-miR-4270, hsa-miR-331-3p, and hsa-miR-125a-3p. Among the network, hsa-miR-25-3p targeted the most genes, hsa-miR-3692-5p and hsa-miR-4270 were targeted by more circRNAs than other miRNAs, hsa-circ-0034326 and hsa-circ-0011950 interacted with three miRNAs. Furthermore, target genes, including NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were obtained in drug-gene interaction network. Survival analysis showed NRAS, ITGA5, SLC7A1, SEC14L2, SLC12A5, and SMAD2 were significantly associated with prognosis of HCC. NRAS, ITGA5, and SMAD2 were significantly enriched in proteoglycans in cancer. Moreover, hsa-circ-0034326 and hsa-circ-0011950 might function as ceRNAs to play key roles in HCC. Furthermore, miR-25-3p, miR-3692-5p, and miR-4270 might be significant for HCC development. NRAS, ITGA5, SEC14L2, SLC12A5, and SMAD2 might be prognostic factors for HCC patients via proteoglycans in cancer pathway. Taken together, the findings will provide novel insight into pathogenesis, selection of therapeutic targets and prognostic factors for HCC.
| S-EPMC8687197 | biostudies-literature
Project description:BackgroundNumerous studies have identified that circular RNAs (circRNAs) can serve as competing endogenous RNAs (ceRNAs) to regulate tumor progression. However, there are still a large number of circRNAs to be deciphered.ObjectiveThe purpose of this study was to reveal novel circRNAs and their potential role in lung adenocarcinoma (LUAD).MethodsTo unveil LUAD-related circRNAs, microRNA (miRNAs), and messenger RNA (mRNA) and elucidate their possible molecular mechanisms, we employed a strategy combining extensive data mining and bioinformatics methods. According to the results of bioinformatics workflow analysis, a novel circRNA-miRNA-mRNA network was constructed.ResultsTen circRNAs with different expressions were acquired from four Gene Expression Omnibus (GEO) microarray datasets. Seven Prognostic-related differential miRNAs of LUAD were gained from The Cancer Genome Atlas (TCGA). Simultaneously, the miRNA reaction components corresponding to the ten circRNAs were predicted. Two circRNA-miRNA interactions including two circRNAs (hsa_circ_0008234 and hsa_circ_0002360) and two miRNAs (hsa-miR-490-3p and hsa-miR-1293) were identified above. Then, target genes of the two miRNAs and differently expressed genes (DEGs) from TCGA on LUAD were collected. Three hub-genes (ADCY9, NMUR1, SYT1) were determined according to prognosis in patients with LUAD ulteriorly.Conclusionshsa_circ_0008234/hsa-miR-490-3p/SYT1 and hsa_circ_0002360/hsa-miR-1293/ (ADCY9, NMUR1) networks were established, and identified molecules may be involved in pathogenesis and prognosis in patients with LUAD.
| S-EPMC9141977 | biostudies-literature
Project description:The pathogenesis of gastric cancer (GC) is still not fully understood. We aimed to find the potential regulatory network for ceRNA (circRNA-miRNA-immune-related mRNA) to uncover the pathological molecular mechanisms of GC. The expression profiles of circRNA, miRNA, and mRNA in gastric tissue from GC patients were downloaded from the Gene Expression Omnibus (GEO) datasets. Differentially expressed circRNAs, miRNAs, and immune-related mRNAs were filtered, followed by the construction of the ceRNA (circRNA-miRNA-immune-related mRNA) network. Functional annotation and protein-protein interaction (PPI) analysis of immune-related mRNAs in the network were performed. Expression validation of circRNAs and immune-related mRNAs was performed in the new GEO and TCGA datasets and in-vitro experiment. A total of 144 differentially expressed circRNAs, 216 differentially expressed miRNAs, and 2,392 differentially expressed mRNAs were identified in GC. Some regulatory pairs of circRNA-miRNA-immune-related mRNA were obtained, including hsa_circ_0050102-hsa-miR-4537-NRAS-Tgd cells, hsa_circ_0001013-hsa-miR-485-3p-MAP2K1-Tgd cells, hsa_circ_0003763-hsa-miR-145-5p-FGF10-StromaScore, hsa_circ_0001789-hsa-miR-1269b-MET-adipocytes, hsa_circ_0040573-hsa-miR-3686-RAC1-Tgd cells, and hsa_circ_0006089-hsa-miR-5584-3p-LYN-neurons. Interestingly, FGF10, MET, NRAS, RAC1, MAP2K1, and LYN had potential diagnostic value for GC patients. In the KEGG analysis, some signaling pathways were identified, such as Rap1 and Ras signaling pathways (involved NRAS and FGF10), Fc gamma R-mediated phagocytosis and cAMP signaling pathway (involved RAC1), proteoglycans in cancer (involved MET), T-cell receptor signaling pathway (involved MAP2K1), and chemokine signaling pathway (involved LYN). The expression validation of hsa_circ_0003763, hsa_circ_0004928, hsa_circ_0040573, FGF10, MET, NRAS, RAC1, MAP2K1, and LYN was consistent with the integrated analysis. In conclusion, the identified ceRNA (circRNA-miRNA-immune-related mRNA) regulatory network may be associated with the development of GC.
| S-EPMC8907717 | biostudies-literature