Comprehensive analysis of circRNA expression profiles and circRNA‐associated competing endogenous RNA networks in the development of mouse thymus

Abstract Background As one of the novel molecules, circRNA has been identified closely involved in the pathogenesis of many diseases. However, the function of circRNA in acute myeloid leukemia (AML) still remains unknown. Methods In the current study, the RNA expression profiles were obtained from Gene Expression Omnibus (GEO) datasets. The differentially expressed RNAs were identified using R software and the competing endogenous RNA (ceRNA) network was constructed using Cytoscape. Functional and pathway enrichment analyses were performed to identify the candidate circRNA-mediated aberrant signaling pathways. The hub genes were identified by MCODE and CytoHubba plugins of Cytoscape, and then a subnetwork regulatory module was established. Results A total of 27 circRNA-miRNA pairs and 208 miRNA-mRNA pairs, including 12 circRNAs, 24 miRNAs and 112 mRNAs were included in the ceRNA network. Subsequently, a subnetwork, including 4 circRNAs, 5 miRNAs and 6 mRNAs, was established based on related circRNA-miRNA-mRNA regulatory modules. Conclusions In summary, this work analyzes the characteristics of circRNA as competing endogenous RNA in AML pathogenesis, which would provide hints for developing novel prognostic, diagnostic and therapeutic strategy for AML.

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Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽

10.1186/s12885-021-08173-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ping Yan ◽

Zuotian Huang ◽

Tong Mou ◽

Yunhai Luo ◽

Yanyao Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Malignant Tumors ◽

Expression Profiles ◽

Clinical Information ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

High Rate ◽

Competing Endogenous Rna ◽

Tissue Samples ◽

Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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A Comprehensive Analysis of Human Gene Expression Profiles Identifies Stromal Immunoglobulin κ C as a Compatible Prognostic Marker in Human Solid Tumors

Clinical Cancer Research ◽

10.1158/1078-0432.ccr-11-2210 ◽

2012 ◽

Vol 18 (9) ◽

pp. 2695-2703 ◽

Cited By ~ 127

Author(s):

Marcus Schmidt ◽

Birte Hellwig ◽

Seddik Hammad ◽

Amnah Othman ◽

Miriam Lohr ◽

...

Keyword(s):

Gene Expression ◽

Solid Tumors ◽

Prognostic Marker ◽

Human Gene ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Comprehensive Analysis ◽

Human Gene Expression ◽

Human Solid Tumors

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Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines

Oncogene ◽

10.1038/sj.onc.1205829 ◽

2002 ◽

Vol 21 (42) ◽

pp. 6549-6556 ◽

Cited By ~ 39

Author(s):

Jiafu Ji ◽

Xin Chen ◽

Suet Yi Leung ◽

Jen-Tsan A Chi ◽

Kent Man Chu ◽

...

Keyword(s):

Gene Expression ◽

Gastric Cancer ◽

Cell Lines ◽

Cancer Cell ◽

Gastric Cancer Cell ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Comprehensive Analysis ◽

Human Gastric Cancer ◽

Gastric Cancer Cell Lines

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Comprehensive Analysis of Differential Expression Profiles of Long Non-coding RNAs with Associated Co-expression and Competing Endogenous RNA Networks in the Hippocampus of Patients with Alzheimer's Disease

Current Alzheimer Research ◽

10.2174/1567205018666211202143449 ◽

2021 ◽

Vol 18 ◽

Author(s):

Jian-Jun Zhang ◽

Ze-Xuan-Zhu ◽

Guang-Min-Xu ◽

Peng Su ◽

Qian Lei ◽

...

Keyword(s):

Gene Expression ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Expression Profiles ◽

Gene Expression Omnibus ◽

Competing Endogenous Rna ◽

Pathogenic Genes ◽

Non Coding Rna ◽

Using Data ◽

Trans Regulation

Background: Alzheimer's disease (AD) is still one of the major threats to human health. Although a satisfactory treatment for AD has not yet been discovered, it is necessary to continue to search for novel approaches to deal with this insidious and debilitating disease. Although numerous studies have shown that long non-coding RNA (lncRNA) occupy a significant role in a variety of diseases, their roles in AD remain unclear. Objectives: Using data analysis to explore the role of lncRNA in the course of AD, to further our understanding of AD, and to look forward to finding a new breakthrough for the treatment of AD. Methods: We downloaded and screened expression data of the hippocampal regions of patients with AD from the Gene Expression Omnibus database. We generated lncRNA-miRNA-mRNA networks based on the competing endogenous RNA (ceRNA) hypothesis, and according to gene expression level, we constructed a coding-noncoding co-expression (CNC) network and then executed cis- and trans-regulation analyses. Results: Through comprehensive and systematic analyses, we found that lncRNAs MALAT1, OIP5-AS1, LINC00657, and lnc-NUMB-1 regulated the expression of the key AD pathogenic genes APP, PSEN1, BACE1; and that these lncRNAs may promote the distribution of β-amyloid (Aβ protein) in the brain through exosomes. In addition, lncRNAs were found to adjust viral transcriptional expression, thereby further supporting viral pathogenesis for AD. Conclusions: The lncRNAs MALAT1, OIP5-AS1, LINC00657, and lnc-NUMB-1 that are present in the hippocampus of AD patients exert an important influence on the development of this disease.

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