Dataset Information

Identification of an lncRNA?miRNA?mRNA interaction mechanism in breast cancer based on bioinformatic analysis.

ABSTRACT: Non?coding RNAs serve important roles in regulating the expression of certain genes and are involved in the principal biological processes of breast cancer. The majority of studies have focused on defining the regulatory functions of long non?coding RNAs (lncRNAs) and microRNAs (miRNAs/miRs), and few studies have investigated how lncRNAs and miRNAs are transcriptionally regulated. In the present study, based on the breast invasive carcinoma dataset from The Cancer Genome Atlas at cBioPortal, and using a bioinformatics computational approach, an lncRNA?miRNA?mRNA network was constructed. The network consisted of 601 nodes and 706 edges, which represented the complex web of regulatory effects between lncRNAs, miRNAs and target genes. The results of the present study demonstrated that miR?510 was the most potent miRNA controller and regulator of numerous target genes. In addition, it was observed that the lncRNAs PVT1, CCAT1 and linc00861 exhibited possible interactions with clinical biomarkers, including receptor tyrosine?protein kinase erbB?2, estrogen receptor and progesterone receptor, demonstrated using RNA?protein interaction prediction software. The network of lncRNA?miRNA?mRNA interactions will facilitate further experimental studies and may be used to refine biomarker predictions for developing novel therapeutic approaches in breast cancer.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5647044 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Identification of an lncRNA‑miRNA‑mRNA interaction mechanism in breast cancer based on bioinformatic analysis.

Zhang Yuhan Y Li Yongfeng Y Wang Qing Q Zhang Xiping X Wang Dajin D Tang Hong Chao HC Meng Xuli X Ding Xianfeng X

Molecular medicine reports 20170821 4

Non‑coding RNAs serve important roles in regulating the expression of certain genes and are involved in the principal biological processes of breast cancer. The majority of studies have focused on defining the regulatory functions of long non‑coding RNAs (lncRNAs) and microRNAs (miRNAs/miRs), and few studies have investigated how lncRNAs and miRNAs are transcriptionally regulated. In the present study, based on the breast invasive carcinoma dataset from The Cancer Genome Atlas at cBioPortal, and ...[more]

PMID: 28849135

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Project description:Background: Colorectal cancer (CRC) is currently the fourth most common cancer worldwide. The roles of exosomal competing endogenous RNAs (ceRNAs) in CRC remain unclear. In this study, we constructed an exosomal ceRNA network to identify the core ceRNAs and investigate the diagnostic biomarkers in CRC. Methods and Patients: Serum exosomes were isolated from four CRC patients and two healthy donors by ultracentrifugation, and then subjected to RNA isolation, sequencing and microarray. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were performed to identify functional enrichment implications of differentially expressed exosomal mRNAs. TargetScan and miRanda were used for identifying the miRNA-mRNA and miRNA-LncRNA interactions. The predicted lncRNAs and mRNAs were intersected with the differentially expressed genes, for which the screening criterion was fold change >1.5 in the microarray. Differentially expressed exosomal miRNAs were identified in the GSE71008 dataset, and differentially expressed mRNAs (DEmRNAs) were further summarized from The Cancer Genome Atlas (TCGA) database. Results: A total of 1186 exosomal DEmRNAs, 2088 exosomal DElncRNAs and 29 exosomal miRNAs were detected in CRC patients compared to the healthy donors. Functional enrichment analysis suggested that exosomal DEmRNAs might participate in pathways related to carcinogenesis and development of cancer. An exosomal ceRNA regulatory network of CRC was constructed based on 40 lncRNAs, two miRNAs, and five mRNAs. Exosomal miR-150-5p and miR-10b-5p expression levels were increased in healthy donors compared with CRC patients in the GSE71008 dataset, and five DEmRNAs (TOMM70A, RBM48, BEND3, RHOBTB1, and ADAMTS2) were significantly upregulated in TCGA database. Two potential exosomal regulatory axes of lncRNA G016261-miR-150-5p-RBM48 and lncRNA XLOC_011677-miR-10b-5p-BEND3 were identified from the network. Conclusion: The current study revealed potential molecular biological regulation pathways and diagnostic biomarkers through the exosomal ceRNA regulatory network.

Project description:Recently, rapid advances in bioinformatics analysis have expanded our understanding of the transcriptome to a genome-wide level. miRNA-mRNA-lncRNA interactions have been shown to play critical regulatory role in cancer biology. In this study, we discussed the use of an integrated systematic approach to explore new facets of the oestrogen receptor (ER)-regulated transcriptome. The identification of RNAs that are related to the expression status of the ER may be useful in clinical therapy and prognosis. We used a network modelling strategy. First, microarray expression profiling of mRNA, lncRNA and miRNA was performed in MCF-7 (ER-positive) and MDA-MB-231 cells (ER- negative). A co-expression network was then built using co-expression relationships of the differentially expressed mRNAs and lncRNAs. Finally, the selected miRNA-mRNA network was added to the network. The key miRNA-mRNA-lncRNA interaction can be inferred from the network. The mRNA and non-coding RNA expression profiles of the cells with different ER phenotypes were distinct. Among the aberrantly expressed miRNAs, the expression levels of miR-19a-3p, miR-19b-3p and miR-130a-3p were much lower in the MCF-7 cells, whereas that of miR-148b-3p was much higher. In a cluster of miR-17-92, the expression levels of six of seven miRNAs were lower in the MCF-7 cells, in addition to miR-20b in the miR-106a-363 cluster. However, the levels of all the miRNAs in the miR-106a-25 cluster were higher in the MCF-7 cells. In the co-expression networking, CD74 and FMNL2 gene which is involved in the immune response and metastasis, respectively, had a stronger correlation with ER. Among the aberrantly expressed lncRNAs, lncRNA-DLEU1 was highly expressed in the MCF-7 cells. A statistical analysis revealed that there was a co-expression relationship between ESR1 and lncRNA-DLEU1. In addition, miR-19a and lncRNA-DLEU1 are both located on the human chromosome 13q. We speculate that miR-19a might be co-expressed with lncRNA-DLEU1 to co-regulate the expression of ESR1, which influences the occurrence and development of breast cancer cells with different levels of ER expression. Our findings reveal that the status of ER is mainly due to the differences in the mRNA and ncRNA profile between the breast cancer cell lines, and highlight the importance of studying the miRNA-mRNA-lncRNA interactions to completely illustrate the intricate transcriptome.

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Dataset Information

Identification of an lncRNA?miRNA?mRNA interaction mechanism in breast cancer based on bioinformatic analysis.

Publications

Identification of an lncRNA‑miRNA‑mRNA interaction mechanism in breast cancer based on bioinformatic analysis.

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