Dataset Information

MiRNA-mRNA Associated With Survival in Endometrial Cancer.

ABSTRACT: Although various factors may contribute to its initiation and progression, the etiology and prognostic factors of endometrial carcinoma (EC) remains not fully understood. We sought to understand the role of changes in transcriptome during the progress of EC by exploring public datasets. The aberrant expression characteristics of EC based on RNA-Seq and miRNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed. Kaplan-Meier analysis was performed to assess the relationship between differently expressed genes (DEGs) and patient survival. As a result, 320 out of 4,613 differently expressed mRNAs (DE mRNAs) and 68 out of 531 differently expressed miRNAs (DE miRNAs) with a significantly poorer survival were determined. We predicted eight paired DE miRNAs and DE mRNAs through TargetScan. Patients with three out of the eight paired low rate of miRNA/mRNA (miR-497/EMX1, miR-23c/DMBX1, and miR-670/KCNS1) expression had a significantly poorer survival. Furthermore, the simultaneous presence of these selected low miRNA/mRNA pairs occurred in most patients and resulted in a significantly poorer survival rate. Luciferase reporter assay identified that EMX1 was a direct target of miR-497. Both low expression of miR-497 and overexpression of EMX1 were significantly associated with more advanced clinicopathologic characteristics (stage, tumor status, grade, and histology) besides survival (all P values < 0.05). Multivariate analysis also demonstrated that miR-497 remained an independent prognostic variable for overall survival. In summary, we identified that a series of DE mRNAs and miRNAs, including eight paired DE miRNAs and mRNAs, were associated with survival in EC. Clinical evaluation of downregulated miR-497 and paired upregulated EMX1 confirmed the value of our prediction analysis. The simultaneous presence of low rate of these selected low miRNA/mRNA pairs (miR-497/EMX1, miR-23c/DMBX1, and miR-670/KCNS1) might have a better prediction value. Therefore, further studies are required to validate these findings.

SUBMITTER: Xu X

PROVIDER: S-EPMC6710979 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

miRNA-mRNA Associated With Survival in Endometrial Cancer.

Xu Xiaofeng X Liu Tao T Wang Yijin Y Fu Jian J Yang Qian Q Wu Jun J Zhou Huaijun H

Frontiers in genetics 20190820

Although various factors may contribute to its initiation and progression, the etiology and prognostic factors of endometrial carcinoma (EC) remains not fully understood. We sought to understand the role of changes in transcriptome during the progress of EC by exploring public datasets. The aberrant expression characteristics of EC based on RNA-Seq and miRNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed. Kaplan-Meier analysis was performed to assess the relationship between differen ...[more]

PMID: 31481972

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Project description:Chronic obstructive pulmonary disease (COPD) is characterized by expiratory airflow limitation and symptoms such as shortness of breath. Although many studies have demonstrated dysregulated microRNA (miRNA) and gene (mRNA) expression in the pathogenesis of COPD, how miRNAs and mRNAs systematically interact and contribute to COPD development is still not clear. To gain a deeper understanding of the gene regulatory network underlying COPD pathogenesis, we used Sparse Multiple Canonical Correlation Network (SmCCNet) to integrate whole blood miRNA and RNA-sequencing data from 404 participants in the COPDGene study to identify novel miRNA-mRNA networks associated with COPD-related phenotypes including lung function and emphysema. We hypothesized that phenotype-directed interpretable miRNA-mRNA networks from SmCCNet would assist in the discovery of novel biomarkers that traditional single biomarker discovery methods (such as differential expression) might fail to discover. Additionally, we investigated whether adjusting -omics and clinical phenotypes data for covariates prior to integration would increase the statistical power for network identification. Our study demonstrated that partial covariate adjustment for age, sex, race, and CT scanner model (in the quantitative emphysema networks) improved network identification when compared with no covariate adjustment. However, further adjustment for current smoking status and relative white blood cell (WBC) proportions sometimes weakened the power for identifying lung function and emphysema networks, a phenomenon which may be due to the correlation of smoking status and WBC counts with the COPD-related phenotypes. With partial covariate adjustment, we found six miRNA-mRNA networks associated with COPD-related phenotypes. One network consists of 2 miRNAs and 28 mRNAs which had a 0.33 correlation (p = 5.40E-12) to forced expiratory volume in 1 s (FEV1) percent predicted. We also found a network of 5 miRNAs and 81 mRNAs that had a 0.45 correlation (p = 8.80E-22) to percent emphysema. The miRNA-mRNA networks associated with COPD traits provide a systems view of COPD pathogenesis and complements biomarker identification with individual miRNA or mRNA expression data.

Project description:Background: Ovarian cancer (OC) is the most lethal malignancy in the female reproductive system. Growing evidences demonstrates that competing endogenous RNA (ceRNA) network play crucial roles in the occurrence and progression of tumors. Therefore, we aimed to explore and identify novel mRNA-miRNA-lncRNA ceRNA networks associated with prognosis of OC. Methods: The differentially expressed gene (DEGs) of four expression profiles datasets (GSE5438, GSE40595, GSE38666 and GSE26712) were collected from Gene Expression Omnibus (GEO) database and analyzed with NetworkAnalyst. Intersection of DEGs were further employed for Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis. Protein-protein interaction (PPI) network and hub genes of DEGs were also identified. The expression levels and survival analysis of the hub genes in OC and their upstream miRNAs and lncRNAs were performed by various bioinformatics databases. More importantly, ceRNA networks were constructed based on mRNA-miRNA-lncRNA in OC. Results: A total of 178 DEGs including 38 upregulated and 140 downregulated genes from intersected DEGs of four expression profiles were identified in OC. Functional enrichment analysis suggested that the commonly DEGs were enriched in regulating enzyme inhibitor activity, glycosaminoglycan and G protein-coupled receptor binding, cell morphogenesis, and involved in pathways including metabolic process, proteoglycans in cancer. Top 10 hub genes with higher connectivity degree were selected for subsequent expression and prognosis analysis. After take expression levels and prognostic roles of hub genes and their upstream miRNAs and lncRNAs in OC into consideration, 2 mRNAs (TACC3 and CXCR4), 2 miRNAs (hsa-miR-425-5p and hsa-miR-146a-5p) and 3 lncRNAs (FUT8-AS1, LINC00665 and LINC01535) were significantly associated with the poor prognosis of OC. The mRNA-miRNA-lncRNA networks (TACC3-hsa-miR-425-5p-FUT8-AS1 and CXCR4-hsa-miR-146a-5p-LINC00665/LINC01535) were eventually constructed in OC based on ceRNA mechanism. Conclusion: We successfully constructed novel ceRNA network associated with the prognosis of ovarian cancer, which may provide a new strategy for early diagnosis and therapeutic intervention of OC.

Dataset Information

MiRNA-mRNA Associated With Survival in Endometrial Cancer.

Publications

miRNA-mRNA Associated With Survival in Endometrial Cancer.

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