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Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia.

ABSTRACT: BACKGROUND:Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML is still rarely reported. METHOD:We obtained transcriptome data of AML and normal samples from The Cancer Genome Atlas (TCGA), Genotype-tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases, and identified differentially expressed (DE) mRNAs, lncRNAs, and circRNAs. Then, the targeting relationships among lncRNA-miRNA, circRNA-miRNA, and miRNA-mRNA were predicted, and the survival related hub mRNAs were further screened by univariate and multivariate Cox proportional hazard regression. Finally, the AML prognostic circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. RESULTS:We identified prognostic 6 hub mRNAs (TM6SF1, ZMAT1, MANSC1, PYCARD, SLC38A1, and LRRC4) through Cox regression model, and divided the AML samples into high and low risk groups according to the risk score obtained by multivariate Cox regression. Survival analysis verified that the survival rate of the high-risk group was significantly reduced (p < 0.0001). The prognostic ceRNA network of 6 circRNAs, 32 lncRNAs, 8 miRNAs, and 6 mRNAs was established according to the targeting relationship between 6 hub mRNAs and other RNAs. CONCLUSION:In this study, ceRNA network jointly participated by circRNAs and lncRNAs was established for the first time. It comprehensively elucidated the post-transcriptional regulatory mechanism of AML, and identified novel AML prognostic biomarkers, which has important guiding significance for the clinical diagnosis, treatment, and further scientific research of AML.

SUBMITTER: Cheng Y

PROVIDER: S-EPMC7465400 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia.

Cheng Yaqi Y Su Yaru Y Wang Shoubi S Liu Yurun Y Jin Lin L Wan Qi Q Liu Ying Y Li Chaoyang C Sang Xuan X Yang Liu L Liu Chang C Wang Zhichong Z

Genes 20200731 8

<h4>Background</h4>Acute myeloid leukemia (AML) is one of the most common malignant and aggressive hematologic tumors, and its pathogenesis is associated with abnormal post-transcriptional regulation. Unbalanced competitive endogenous RNA (ceRNA) promotes tumorigenesis and progression, and greatly contributes to tumor risk classification and prognosis. However, the comprehensive analysis of the circular RNA (circRNA)-long non-coding RNA (lncRNA)-miRNA-mRNA ceRNA network in the prognosis of AML i ...[more]

PMID: 32751923

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Project description:IntroductionCircRNA is closely correlated with a wide variety of processes of acute myeloid leukemia (AML), whereas the novel circRNAs, their molecular mechanism and the specific function they played in AML should be explored in depth.MethodsThe microarray chip data of AML patients and normal samples in the Gene Expression Omnibus (GEO) database were selected to differentially expressed (DE) circRNA, miRNA, and mRNA genes. The miRNA gene was the intersection of the circRNA target gene predicted using CSCD and the miRNA gene screened from AML patients, while the mRNA gene was the intersection of the target gene mRNA of miRNA predicted using miRanda and miRTarBase software and the mRNA gene screened from AML patients. The hub mRNAs related to survival were further screened through Cox proportional hazard regression. CircRNA/miRNA/mRNA interaction network was constructed by using Cytoscape software.10 circRNAs and 6 miRNAs in bone marrow mononuclear cells (BMMNCs) of AML patients (n=43) and healthy controls (n=35) were determined by RT-qPCR. Correlations between them were analyzed by Pearson correlation coefficient.Results10 circRNAs, 6 miRNAs, and 33 mRNAs were identified. Subsequently, the network of circRNAs, miRNAs, and hub genes was built using Cystoscope. Four key circRNAs, seven hub genes and their regulatory pathways were identified. The result of RT-qPCRs showed that hsa_circ_0009581 and hsa_circ_0005273 were significantly upregulated in AML patients while hsa_circ_0000497 and hsa_circ_0001947 were significantly downregulated. Hsa-miR-150-5p was significantly downregulated; hsa-miR-454-3p was upregulated in AML patients. Hsa_circ_0009581 and hsa-miR-150-5p; hsa_ circ_0001947 and hsa-miR-454-3p were inversely correlated using Pearson's correlation coefficient.ConclusionThis study suggests that differentially expressed circRNAs take on a critical significance to AML development and may be the effective therapeutic targets. We suppose that hsa_circ_0009581 promotes leukemia development through hsa-miR-150-5p and hsa_circ_0001947 through hsa-miR-454-3p. hsa_circ_0001947 and hsa_circ_0009581 may provide new directions in the pathogenesis of AML.

Project description:Accumulating evidence has indicated that noncoding RNAs are involved in intervertebral disc degeneration (IDD); however, the competing endogenous RNA (ceRNA)‑mediated regulatory mechanisms in IDD remain rarely reported. The present study aimed to comprehensively investigate the alterations in expression levels of circular RNA (circRNA), long noncoding RNA (lncRNA), microRNA (miRNA/miR) and mRNA in the nucleus pulposus (NP) of patients with IDD. In addition, crucial lncRNA/circRNA‑miRNA‑mRNA ceRNA interaction axes were screened using the GSE67567 microarray dataset obtained from the Gene Expression Omnibus database. After data preprocessing, differentially expressed circRNAs (DECs), lncRNAs (DELs), miRNAs (DEMs) or genes (DEGs) between IDD and normal controls were identified using the Linear Models for Microarray data method. A protein‑protein interaction (PPI) network was constructed for DEGs based on protein databases, followed by module analysis. The ceRNA network was constructed based on the interaction between miRNAs and mRNAs, and lncRNAs/circRNAs and miRNAs. The underlying functions of mRNAs were predicted using the Database for Annotation, Visualization and Integrated Discovery database. The present study identified 636 DECs, 115 DELs, 84 DEMs and 1,040 DEGs between patients with IDD and control individuals. PPI network analysis demonstrated that Fos proto‑oncogene, AP‑1 transcription factor subunit (FOS), mitogen‑activated protein kinase 1 (MAPK1), hypoxia inducible factor 1 subunit α (HIF1A) and transforming growth factor β1 (TGFB1) were hub genes and enriched in modules. Metastasis‑associated lung adenocarcinoma transcript 1 (MALAT1)/hsa_circRNA_102348‑hsa‑miR‑185‑5p‑TGFB1/FOS, MALAT1‑hsa‑miR‑155‑5p‑HIF1A, hsa_circRNA_102399‑hsa‑miR‑302a‑3p‑HIF1A, MALAT1‑hsa‑miR‑519d‑3p‑MAPK1 and hsa_circRNA_100086‑hsa‑miR‑509‑3p‑MAPK1 ceRNA axes were obtained by constructing the ceRNA networks. In conclusion, these identified ceRNA interaction axes may be crucial targets for the treatment of IDD.

Dataset Information

Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia.

Publications

Identification of circRNA-lncRNA-miRNA-mRNA Competitive Endogenous RNA Network as Novel Prognostic Markers for Acute Myeloid Leukemia.

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