Dataset Information

Identification of the Key Factors Related to Bladder Cancer by lncRNA-miRNA-mRNA Three-Layer Network.

ABSTRACT: Bladder cancer is the most common malignant tumor of the urinary system, and it has high incidence, high degree of malignancy, and easy recurrence after surgery. The etiology and pathogenesis of bladder cancer are not fully understood, but more and more studies have shown that its development may be regulated by some core molecules. To identify key molecules in bladder cancer, we constructed a three-layer network by merging lncRNA-miRNA regulatory network, miRNA-mRNA regulatory network, and lncRNA-mRNA coexpression network, and further analyzed the topology attributes of the network including the degree, betweenness centrality and closeness centrality of nodes. We found that miRNA-93 and miRNA-195 are controllers for a three-layer network and regulators of numerous target genes associated with bladder cancer. Functional enrichment analysis of their target mRNAs revealed that miRNA-93 and miRNA-195 may be closely related to bladder cancer by disturbing the homeostasis of the cell cycle or HTLV-I infection. In addition, since E2F1 and E2F2 are enriched in various KEGG signaling pathways, we conclude that they are important target genes of miRNA-93, and participate in the apoptotic process by forming a complex with a certain protein or transcription factor activity, sequence-specific DNA binding in bladder cancer. Similarly, AKT3 is an important target gene of miRNA-195, its expression is associated with PI3K-Akt-mTOR signaling pathway and AMPK-mTOR signaling pathway. Therefore, we speculate that AKT3 may participate in proliferation and apoptosis of bladder cancer cells through these pathways, and ultimately affect the biological behavior of tumor cells. Furthermore, through survival analysis, we found that miRNA-195 and miRNA-93 are associated with poor prognosis of bladder cancer. And the Kaplan-Meier curve showed that 24 mRNAs and nine lncRNAs are closely related to overall survival of bladder cancer.

SUBMITTER: Wang X

PROVIDER: S-EPMC6997565 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of the Key Factors Related to Bladder Cancer by lncRNA-miRNA-mRNA Three-Layer Network.

Wang Xiaxia X Ding Yanrui Y Wang Jie J Wu Yanyan Y

Frontiers in genetics 20200128

Bladder cancer is the most common malignant tumor of the urinary system, and it has high incidence, high degree of malignancy, and easy recurrence after surgery. The etiology and pathogenesis of bladder cancer are not fully understood, but more and more studies have shown that its development may be regulated by some core molecules. To identify key molecules in bladder cancer, we constructed a three-layer network by merging lncRNA-miRNA regulatory network, miRNA-mRNA regulatory network, and lncR ...[more]

PMID: 32047516

Similar Datasets

Project description:Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.

Project description:BackgroundNon-coding RNAs are competing endogenous RNAs in the occurrence and development of tumorigenesis; numerous microRNAs are aberrantly expressed in colon cancer tissues and play significant roles in oncogenesis development and metastasis. However, large clinical and RNA data are lacking to further confirm the exact role of these RNAs in tumors. This study aimed to ascertain differential RNA expression between colon cancer and normal colon tissues.Materials and methodsRNA sequencing and clinical data of patients with colon cancer were procured from The Cancer Genome Atlas database; differentially expressed long non-coding RNA, differentially expressed messenger RNAs, and differentially expressed microRNAs were achieved using the limma package in edgeR to generate competing endogenous RNAs networks. Then, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with ggplot2 package, the Kaplan-Meier survival method was used to predict survival in patients with colon cancer.ResultsIn total, 1174 differentially expressed long non-coding RNAs, 2068 differentially expressed messenger RNAs, and 239 differentially expressed microRNAs were generated between 480 colon cancer and 41 normal colon tissue samples. Three competing endogenous RNA networks were established. Gene Ontology analysis indicated that the genes of the up-regulated microRNA network were involved in negative regulation of transcription, DNA-template, and those of down-regulated microRNA network were involved in transforming growth factor β receptor signaling pathways, response to hypoxia, cell migration, while Kyoto Encyclopedia of Genes and Genomes analyses of these networks turned out to be negative. Three long non-coding RNAs (AP004609.1, ARHGEF26-AS1, and LINC00491), 3 microRNAs (miRNA-141, miRNA-216a, and miRNA-193b) and 3 RNAs (ULBP2, PHLPP2, and TPM2) were detected to be associated with prognosis by the Kaplan-Meier survival analysis. Additionally, univariate and multivariate Cox regression analyses showed that the microRNA-216a of the competing endogenous RNA might be an independent prognostic factor in colon cancer.ConclusionsThis study constructed the non-coding RNA-related competing endogenous RNA networks in colon cancer and sheds lights on underlying biomarkers for colon cancer cohorts.

Project description:Cytogenetically normal acute myeloid leukemia (CN-AML) is a heterogeneous disease with different prognoses. Researches on prognostic biomarkers and therapy targets of CN-AML are still ongoing. Instead of protein-coding genes, more and more researches were focused on the non-coding RNAs especially long non-coding RNAs (lncRNAs) which may play an important role in the development of AML. Although a large number of lncRNAs have been found, our knowledge of their functions and pathological process is still in its infancy. The purpose of this research is to identify the key lncRNAs and explore their functions in CN-AML by reconstructing the lncRNA-miRNA-mRNA network based on the competitive endogenous RNA (ceRNA) theory. We reconstructed a global triple network based on the ceRNA theory using the data from National Center for Biotechnology Information Gene Expression Omnibus and published literature. According to the topological algorithm, we identified the key lncRNAs which had both the higher node degrees and the higher numbers of lncRNA-miRNA pairs and total pairs in the ceRNA network. Meanwhile, Gene Ontology (GO) and pathway analysis were performed using databases such as DAVID, KOBAS and Cytoscape plug-in ClueGO respectively. The lncRNA-miRNA-mRNA network was composed of 90 lncRNAs,33mRNAs,26 miRNAs and 259 edges in the lncRNA upregulated group, and 18 lncRNAs,11 mRNAs,6 miRNAs and 45 edges in the lncRNA downregulated group. The functional assay showed that 53 pathways and 108 GO terms were enriched. Three lncRNAs (XIST, TUG1, GABPB1-AS1) could possibly be selected as key lncRNAs which may play an important role in the development of CN-AML. Particularly, GABPB1-AS1 was highly expressed in CN-AML by both bioinformatic analysis and experimental verification in AML cell line (THP-1) with quantitative real-time polymerase chain reaction. In addition, GABPB1-AS1 was also negatively correlated with overall survival of AML patients. The lncRNA-miRNA-mRNA network revealed key lncRNAs and their functions in CN-AML. Particularly, lncRNA GABPB1-AS1 was firstly proposed in AML. We believe that GABPB1-AS1 is expected to become a candidate prognostic biomarker or a potential therapeutic target.

Project description:Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, "Extracellular-receptor interaction", "Focal adhesion", and "microRNAs in cancer" were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.

Dataset Information

Identification of the Key Factors Related to Bladder Cancer by lncRNA-miRNA-mRNA Three-Layer Network.

Publications

Identification of the Key Factors Related to Bladder Cancer by lncRNA-miRNA-mRNA Three-Layer Network.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets