Dataset Information

Analysis of circular RNA-associated competing endogenous RNA network in breast cancer.

ABSTRACT: As the most common type of cancer in female patients, the morbidity and mortality rates of breast cancer (BC) are high, and its incidence is gradually increasing worldwide. However, the underlying molecular and genetic mechanisms involved in the etiopathogenesis of BC remain unclear. Circular RNAs (circRNAs) are a novel type of non-coding RNAs that have been verified to serve a crucial role in tumorigenesis. However, the majority of functions and mechanisms of circRNAs remain unknown. The present study identified 47 differentially expressed circRNAs in a dataset from Gene Expression Omnibus. Using the cancer-specific circRNA database, the potential microRNA (miRNA) response elements, RNA-binding proteins and open reading frames of the candidate circRNAs were predicted. Combing the predictions of miRNAs and target mRNAs, a competing endogenous RNA network was constructed, which may serve as the theoretical basis for further research. Furthermore, the analyses conducted using Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways indicated that candidate circRNAs may serve a role in transcriptional regulation. Moreover, 20 BC tissue specimens and their paired adjacent normal tissue specimens were used to evaluate the expression levels of the screened circRNAs. Thus, the analyses of the raw microarray data conducted in the present study offer perspectives on the exploration of mechanisms associated with BC tumorigenesis with regard to the circRNA-miRNA-mRNA network.

SUBMITTER: Wang X

PROVIDER: S-EPMC6960389 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Analysis of circular RNA-associated competing endogenous RNA network in breast cancer.

Wang Xuekang X Dong Yanhan Y Wu Qiong Q Lu Tong T Wang Yuanyong Y Liu Wenchao W Liu Chengyu C Xu Wenhua W

Oncology letters 20200102 2

As the most common type of cancer in female patients, the morbidity and mortality rates of breast cancer (BC) are high, and its incidence is gradually increasing worldwide. However, the underlying molecular and genetic mechanisms involved in the etiopathogenesis of BC remain unclear. Circular RNAs (circRNAs) are a novel type of non-coding RNAs that have been verified to serve a crucial role in tumorigenesis. However, the majority of functions and mechanisms of circRNAs remain unknown. The presen ...[more]

PMID: 32002039

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Project description:Background: Genetic characteristics remain underutilized for establishing prognostic models for colorectal cancer (CRC). We explored the underlying regulatory mechanisms of circular RNAs (circRNAs) that act as competing endogenous RNAs (ceRNAs) and constructed a gene-based nomogram to predict overall survival (OS) in patients with CRC. Methods: We obtained circRNA expression profiling data from the Gene Expression Omnibus (GEO) database. MicroRNA (miRNA) and mRNA expression profiles, with associated clinical data, were obtained from The Cancer Genome Atlas (TCGA). A ceRNA network was established using Cytoscape. Interactions between differential genes were analyzed, and hub genes were identified using the cytoHubba application. The R package "clusterProfiler" was used to evaluate the Gene Ontology (GO) annotations of the differentially expressed mRNAs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Database-extracted patients were randomized into a training and validation cohorts. A prognostic model was developed using the training set based on multivariate Cox analyses and was then assessed in the validation set. The accuracy of the model was evaluated using discrimination and calibration plots. Results: Thirteen circRNAs, 62 miRNAs, and 301 mRNAs were used to construct the ceRNA network; 10 hub genes were identified via the PPI network. Next, a circRNA- miRNA hub of gene-regulatory modules was established based on four differentially expressed circRNAs, eight differentially expressed miRNAs, and nine differentially expressed mRNAs (DEmRNAs). GO and KEGG pathway analyses indicated the possible association of DEmRNAs with CRC onset and progression. Multivariate analyses revealed that age, tumor stage, and CXCR5 expression were independent risk factors for OS. A CXCR5-based model was developed to predict the OS of patients with CRC in our training set. Our nomogram showed relatively good accuracy, with C-indices of 0.757 and 0.702 in the training and validation sets, respectively. The areas under the curve of the nomograms predicting 3- and 5-years OS were 0.749 and 0.805 in the training set and 0.706 and 0.779 in the validation set, respectively. Conclusions: Our data suggested that the hsa_circ_00001666/has-mir-1229/CXCR5 axis plays an important role in the pathogenesis of CRC, thereby identifying a potential therapeutic target. The proposed CXCR5-based nomogram may also assist surgeons in devising personalized treatments for patients with this disease.

Project description:Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function and application of circRNAs in lung adenocarcinoma (LUAD) are still unknown. In this study, we constructed a circRNA-associated competitive endogenous RNA (ceRNA) network to investigate the regulatory mechanism of LUAD procession and further constructed a prognostic signature to predict overall survival for LUAD patients. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network. Based on the TargetScan prediction tool and Pearson correlation coefficient, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs, and 49 DEmRNAs. GO and KEGG enrichment indicated that the ceRNA network might be involved in the regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate Cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using the LASSO method in the TCGA-LUAD training cohort. By applying the signature, patients could be categorized into the high-risk or low-risk subgroups with significant survival differences (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009). The prognostic performance was confirmed in an independent GEO cohort (GSE42127, HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004). Multivariate Cox regression analysis proved that the three-gene signature was an independent prognostic factor. Combining the three-gene signature with clinical characters, a nomogram was constructed. The primary and external verification C-indexes were 0.717 and 0.716, respectively. The calibration curves for the probability of 3- and 5-year OS showed significant agreement between nomogram predictions and actual observations. Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and further constructed a useful prognostic signature to guide personalized treatment of LUAD patients.

Project description:Purpose:This study was aimed to develop a lncRNA-associated competing endogenous RNA (ceRNA) network to provide further understanding of the ceRNA regulatory mechanism and pathogenesis in colorectal cancer (CRC). Patients and methods:Expression profiles of mRNAs, lncRNAs, and miRNAs, and clinical information for CRC patients were obtained from The Cancer Genome Atlas. The differentially expressed mRNAs, lncRNAs, and miRNAs (referred to as "DEmRNAs", "DElncRNAs", and "DEmiRNAs", respectively) were screened out between 539 CRC samples and 11 normal samples. The interactions between DElncRNAs and DEmiRNAs were predicted by miRcode. The DEmRNAs targeted by the DEmiRNAs were retrieved according to TargetScan, miRTar-Base, and miRDB. The lncRNA-miRNA-mRNA ceRNA network was constructed based on the DEmiRNA-DElncRNA and DEmiRNA-DEmRNA interactions. Functional enrichment analysis revealed the biological processes and pathways of DEmRNAs involved in the development of CRC. Key lncRNAs were further analyzed for their associations with overall survival and clinical features of CRC patients. Results:A total of 1,767 DEmRNAs, 608 DElncRNAs, and 283 DEmiRNAs were identified as CRC-specific RNAs. Three hundred eighty-two DEmiRNA-DElncRNA interactions and 68 DEmiRNA-DEmRNA interactions were recognized according to the relevant databases. The lncRNA-miRNA-mRNA ceRNA network was constructed using 25 DEmiRNAs, 52 DEmRNAs, and 64 DElncRNAs. Two DElncRNAs, five DEmiRNAs, and six DEmRNAs were demonstrated to be related to the prognosis of CRC patients. Four DElncRNAs were found to be associated with clinical features. Twenty-eight Gene Ontology terms and 10 Kyoto Encyclopedia of Genes and Genomes pathways were found to be significantly enriched by the DEmRNAs in the ceRNA network. Conclusion:Our results showed cancer-specific mRNA, lncRNA, and miRNA expression patterns and enabled us to construct an lncRNA-associated ceRNA network that provided new insights into the molecular mechanisms of CRC. Key RNA transcripts related to the overall survival and clinical features were also found with promising potential as biomarkers for diagnosis, survival prediction, and classification of CRC.

Project description:Gastric cancer (GC) is a common type of cancer, and identification of novel diagnostic biomarkers associated with this disease is important. The present study aimed to identify novel diagnostic biomarkers associated with the prognosis of GC, using an integrated bioinformatics approach. Differentially expressed long non-coding RNAs (lncRNAs) associated with GC were identified using Gene Expression Omnibus datasets (GSE58828, GSE72305 and GSE99416) and The Cancer Genome Atlas database. A competing endogenous RNA network that incorporated five lncRNAs [long intergenic non-protein coding RNA 501 (LINC00501), LINC00365, SOX21 antisense divergent transcript 1 (SOX21-AS1), GK intronic transcript 1 (GK-IT1) and DLEU7 antisense RNA 1 (DLEU7-AS1)], 29 microRNAs and 114 mRNAs was constructed. Gene Ontology and protein-protein interaction network analyses revealed that these lncRNAs may be involved in 'biological regulation', 'metabolic process', 'cell communication', 'developmental process', 'cell proliferation', 'reproduction' and the 'cell cycle'. The results of receiver operating characteristic curve analysis demonstrated that LINC00501 (AUC=0.819), LINC00365 (AUC=0.580), SOX21-AS1 (AUC=0.736), GK-IT1 (AUC=0.823) and DLEU7-AS1 (AUC=0.932) had the potential to become valuable diagnostic biomarkers for GC. Associations with clinicopathological characteristics demonstrated that LINC00501 expression was significantly associated with sex (P=0.015) and tumor grade (P=0.022). Furthermore, LINC00365 expression was significantly associated with lymph node metastasis (P=0.025). Gene set enrichment analysis revealed that LINC00501, LINC00365 and SOX21-AS1 were enriched in signaling pathways associated with GC. Reverse transcription-quantitative PCR analysis demonstrated that LINC00501 expression (P=0.043) was significantly upregulated in GC tissues, whereas the expression levels of LINC00365 (P=0.033) and SOX21-AS1 (P=0.037) were significantly downregulated in GC tissues. Taken together, the results of the present study suggest that LINC00501, LINC00365, SOX21-AS1, GK-IT1 and DLEU7-AS1 may be used as novel diagnostic biomarkers for GC, and may be functionally associated with GC development and progression.

Project description:Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Dataset Information

Analysis of circular RNA-associated competing endogenous RNA network in breast cancer.

Publications

Analysis of circular RNA-associated competing endogenous RNA network in breast cancer.

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