Dataset Information

Identification of potential immune-related circRNA-miRNA-mRNA regulatory network in cutaneous squamous cell carcinoma.

ABSTRACT: Circulating RNAs (circRNAs) are involved in tumor development and progression by participating in immune regulation. Nevertheless, the circRNAs expression profiles and their roles on the immunomodulatory effects in cutaneous squamous cell carcinoma (cSCC) have rarely been studied. In our study, we identified the differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), mRNAs (DEmRNAs) in cSCC and established the circRNA competing endogenous RNAs (ceRNAs) network. Subsequently, the hub differentially expressed immune-related genes were identified and validated by immunochemistry as well as the GO and KEGG pathway analysis were performed. 54 differentially expressed circRNAs were identified and hub differentially expressed immune-related genes were identified and they were mostly associated with immune response in the progression of cSCC. Our results indicated that the potential immune-related circRNA-miRNA-mRNA network may assist in understanding the molecular mechanisms underlying the carcinogenesis and progression in cSCC. Moreover, the immune-related genes may provide an insight into the pathogenesis, molecular biomarkers, and potential therapeutic targets for cSCC patients.

SUBMITTER: Wei Y

PROVIDER: S-EPMC8569358 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Identification of potential immune-related circRNA-miRNA-mRNA regulatory network in cutaneous squamous cell carcinoma.

Wei Yuanfeng Y Yang Xi X Gao Limin L Yang Ju J Zheng Lingnan L Gao Ling L Zhou Xiaohan X Xiang Xiaoyu X Zhang Jie J Yi Cheng C

American journal of cancer research 20211015 10

Circulating RNAs (circRNAs) are involved in tumor development and progression by participating in immune regulation. Nevertheless, the circRNAs expression profiles and their roles on the immunomodulatory effects in cutaneous squamous cell carcinoma (cSCC) have rarely been studied. In our study, we identified the differentially expressed circRNAs (DEcircRNAs), miRNAs (DEmiRNAs), mRNAs (DEmRNAs) in cSCC and established the circRNA competing endogenous RNAs (ceRNAs) network. Subsequently, the hub d ...[more]

PMID: 34765295

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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.

Project description:Background Stroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce. Methods In this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS. Results A total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p. Conclusion Our study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.

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.

Project description: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.

Dataset Information

Identification of potential immune-related circRNA-miRNA-mRNA regulatory network in cutaneous squamous cell carcinoma.

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Identification of potential immune-related circRNA-miRNA-mRNA regulatory network in cutaneous squamous cell carcinoma.

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