Dataset Information

Construct a circRNA/miRNA/mRNA regulatory network to explore potential pathogenesis and therapy options of clear cell renal cell carcinoma.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) is the most representative subtype of renal cancer. CircRNA acts as a kind of ceRNA to play a role in regulating microRNA (miRNA) in many cancers. However, the potential pathogenesis role of the regulatory network among circRNA/miRNA/mRNA is not clear and has not been fully explored. CircRNA expression profile data were obtained from GEO datasets, and the differentially expressed circRNAs (DECs) were identified through utilizing R package (Limma) firstly. Secondly, miRNAs that were regulated by these circRNAs were predicted by using Cancer-specific circRNA database and Circular RNA Interactome. Thirdly, some related genes were identified by intersecting targeted genes, which was predicted by a web tool (miRWalk) and differentially expressed genes, which was obtained from TCGA datasets. Function enrichment was analyzed, and a PPI network was constructed by Cytoscape software and DAVID web set. Subsequently, ten hub-genes were screened from the network, and the overall survival time in patients of ccRCC with abnormal expression of these hub-genes were completed by GEPIA web set. In the last, a circRNA/miRNA/mRNA regulatory network was constructed, and potential compounds and drug which may have the function of anti ccRCC were forecasted by taking advantage of CMap and PharmGKB datasets. Six DECs (hsa_circ_0029340, hsa_circ_0039238, hsa_circ_0031594, hsa_circ_0084927, hsa_circ_0035442, hsa_circ_0025135) were obtained and six miRNAs (miR-1205, miR-657, miR-587, miR-637, miR-1278, miR-548p) which are regulated by three circRNAs (hsa_circ_0084927, hsa_circ_0035442, hsa_circ_0025135) were also predicted. Then 497 overlapped genes regulated by these six miRNAs above had been predicted, and function enrichment analysis revealed these genes are mainly linked with some regulation functions of cancers. Ten hub-genes (PTGER3, ADCY2, APLN, CXCL5, GRM4, MCHR1, NPY5R, CXCR4, ACKR3, MTNR1B) have been screened from a PPI network. PTGER3, ADCY2, CXCL5, GRM4 and APLN were identified to have a significant effect on the overall survival time of patients with ccRCC. Furthermore, one compound (josamycin) and four kinds of drugs (capecitabine, hmg-coa reductase inhibitors, ace Inhibitors and bevacizumab) were confirmed as potential therapeutic options for ccRCC by CMap analysis and pharmacogenomics analysis. This study implies the potential pathogenesis of the regulatory network among circRNA/miRNA/mRNA and provides some potential therapeutic options for ccRCC.

SUBMITTER: Bai S

PROVIDER: S-EPMC7423896 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Construct a circRNA/miRNA/mRNA regulatory network to explore potential pathogenesis and therapy options of clear cell renal cell carcinoma.

Bai Shuheng S Wu YinYing Y Yan Yanli Y Shao Shuai S Zhang Jiangzhou J Liu Jiaxin J Hui Beina B Liu Rui R Ma Hailin H Zhang Xiaozhi X Ren Juan J

Scientific reports 20200812 1

Clear cell renal cell carcinoma (ccRCC) is the most representative subtype of renal cancer. CircRNA acts as a kind of ceRNA to play a role in regulating microRNA (miRNA) in many cancers. However, the potential pathogenesis role of the regulatory network among circRNA/miRNA/mRNA is not clear and has not been fully explored. CircRNA expression profile data were obtained from GEO datasets, and the differentially expressed circRNAs (DECs) were identified through utilizing R package (Limma) firstly. ...[more]

PMID: 32788609

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Project description:BackgroundCircular RNAs (circRNAs) are a new class of noncoding RNAs that have gained increased attention in human tumor research. However, the identification and function of circRNAs are largely unknown in the context of gastric cancer (GC). This study aims to identify novel circRNAs and determine their action networks in GC.MethodsA comprehensive strategy of data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology were conducted to discover novel circRNAs and to explore their potential mechanisms in GC. Promising therapeutic drugs for GC were determined by connectivity map (CMap) analysis.ResultsSix overlapped differentially expressed circRNAs (DECs) were screened from selected microarray and RNA-Seq datasets of GC, and the six DECs were then validated by sanger sequencing and RNase R treatment. Subsequent RT-qPCR analysis of GC samples confirmed decreased expressions of the six DECs (hsa_circ_0000390, hsa_circ_0000615, hsa_circ_0001438, hsa_circ_0002190, hsa_circ_0002449 and hsa_circ_0003120), all of which accumulated preferentially in the cytoplasm. MiRNA binding sites and AGO2 occupation of the six circRNAs were predicted using online databases, and circRNA-miRNA interactions including the six circRNAs and 33 miRNAs were determined. Then, 5320 target genes of the above 33 miRNAs and 1492 differently expressed genes (DEGs) from The Cancer Genome Atlas (TCGA) database were identified. After intersecting the miRNA target genes and the 889 downregulated DEGs, 320 overlapped target genes were acquired. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that these target genes were related to two critical tumor-associated signaling pathways. A protein-protein interaction network with the 320 target genes was constructed using STRING, and fifteen hubgenes (ATF3, BTG2, DUSP1, EGR1, FGF2, FOSB, GNAO1, GNAI1, GNAZ, GNG7, ITPR1, ITPKB, JUND, NR4A3, PRKCB) in the network were identified. Finally, bioactive chemicals (including vorinostat, trichostatin A and astemizole) based on the fifteen hubgenes were identifed as therapeutic agents for GC through the CMap analysis.ConclusionsThis study provides a novel insight for further exploration of the pathogenesis and therapy of GC from the circRNA-miRNA-mRNA network perspective.

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.

Project description:BackgroundOsteosarcoma is a common malignant primary bone tumor in adolescents and children. Numerous studies have shown that circRNAs were involved in the proliferation and invasion of various tumors. However, the role of circRNAs in osteosarcoma remains unclear. Here, we aimed to explore the regulatory network among circRNA-miRNA-mRNA in osteosarcoma.MethodsThe circRNA (GSE140256), microRNA (GSE28423), and mRNA (GSE99671) expression profiles of osteosarcoma were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs, miRNAs and mRNAs were identified. CircRNA-miRNA interactions and miRNA-mRNA interactions were determined by Circular RNA Interactome (CircInteractome) database and microRNA Data Integration Portal (mirDIP) database, respectively. Then, we constructed a regulatory network. Function enrichment analysis of miRNA and mRNA was performed by DIANA-miRPath v3.0 and Metascape database, respectively. mRNAs with significant prognostic value were identified based on expression profiles from The Cancer Genome Atlas (TCGA) database, and we constructed a subnetwork for them. To make the most of the network, we used the CLUE database to predict potential drugs for the treatment of osteosarcoma based on mRNA expression in the network. And we used the STITCH database to analyze and validate the interactions among these drugs and mRNAs, and to further screen for potential drugs.ResultsA total of 9 circRNAs, 19 miRNAs, 67 mRNAs, 54 pairs of circRNA-miRNA interactions and 110 pairs of miRNA-mRNA interactions were identified. A circRNA-miRNA-mRNA network was constructed. Function enrichment analysis indicated that these miRNAs and mRNAs in the network were involved in the process of tumorigenesis and immune response. Among these mRNAs, STC2 and RASGRP2 with significantly prognostic value were identified, and we constructed a subnetwork for them. Based on mRNA expression in the network, three potential drugs, quinacridine, thalidomide and zonisamide, were screened for the treatment of osteosarcoma. Among them, quinacridine and thalidomide have been proved to have anti-tumor effects in previous studies, while zonisamide has not been reported. And a corresponding drug-protein interaction network was constructed.ConclusionOverall, we constructed a circRNA-miRNA-mRNA regulatory network to investigate the possible mechanism in osteosarcoma, and predicted that quinacridine, thalidomide and zonisamide could be potential drugs for the treatment of osteosarcoma.

Dataset Information

Construct a circRNA/miRNA/mRNA regulatory network to explore potential pathogenesis and therapy options of clear cell renal cell carcinoma.

Publications

Construct a circRNA/miRNA/mRNA regulatory network to explore potential pathogenesis and therapy options of clear cell renal cell carcinoma.

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