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: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.

Project description:BackgroundExosomes play important roles in angiogenesis, drug resistance, and metastasis of colorectal cancer (CRC), but the underlying mechanism has seldom been reported. Herein, our study aimed to reveal an exosomal miRNA-mRNA network involved in CRC by performing bioinformatical analysis.MethodsThe mRNA and miRNA data of colon adenocarcinoma and rectal adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and exosomal miRNAs data were downloaded from the GEO dataset GSE39833. The differential expression analysis was performed using "limma" and "edgeR". Target mRNAs of miRNAs were predicted using FunRich 3.1.3, miRNAtap and multiMiR. The candidate mRNAs and exosomal miRNAs were obtained by intersecting two groups of differentially expressed miRNAs and intersection of the differential expressed mRNAs and the target mRNAs, respectively. Key mRNAs and exosomal miRNAs were identified by the least absolute shrinkage and selection operator regression analysis, and used to construct the exosomal miRNA-mRNA network. The network verified was by receiver operating characteristic curve, GEPIA and LinkedOmics. Functional enrichment analysis was also performed for studied miRNAs and mRNAs.ResultsA total of 6568 differentially expressed mRNAs and 531 differentially expressed miRNAs from TCGA data, and 166 differentially expressed exosomal miRNAs in GSE39833 dataset were identified. Next, 16 key mRNAs and five key exosomal miRNAs were identified from the 5284 candidate mRNAs and 61 candidate exosomal miRNAs, respectively. The exosomal miRNA-mRNA network with high connectivity contained 13 hub mRNAs (CBFB, CDH3, ETV4, FOXQ1, FUT1, GCNT2, GRIN2D, KIAA1549, KRT80, LZTS1, SLC39A10, SPTBN2, and ZSWIM4) and five hub exosomal miRNAs (hsa-miR-126, hsa-miR-139, hsa-miR-141, hsa-miR-29c, and hsa-miR-423). The functional annotation revealed that these hub mRNAs were mainly involved in the regulation of B cell receptor signaling pathway and glycosphingolipid biosynthesis related pathways. All hub mRNAs and hub exosomal miRNAs exhibited high diagnosis value for CRC. Furthermore, the association of the hub mRNAs with overall survival, stages, and MSI phenotype of CRC revealed their important roles in CRC progression.ConclusionThis study constructed an exosomal miRNA-mRNA network which may play crucial roles in the carcinogenesis and progression of CRC, thus providing potential diagnostic biomarkers and therapeutic targets for CRC.

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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