Dataset Information

Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.

ABSTRACT: MicroRNAs (miRNAs) are small, noncoding regulatory molecules. They are involved in many essential biological processes and act by suppressing gene expression. The present work reports an integrative analysis of miRNA-mRNA and miRNA-miRNA interactions and their regulatory patterns using high-throughput miRNA and mRNA datasets. Aberrantly expressed miRNA and mRNA profiles were obtained based on fold change analysis, and qRT-PCR was used for further validation of deregulated miRNAs. miRNAs and target mRNAs were found to show various expression patterns. miRNA-miRNA interactions and clustered/homologous miRNAs were also found to contribute to the flexible and selective regulatory network. Interacting miRNAs (e.g., miRNA-103a and miR-103b) showed more pronounced differences in expression, which suggests the potential "restricted interaction" in the miRNA world. miRNAs from the same gene clusters (e.g., miR-23b gene cluster) or gene families (e.g., miR-10 gene family) always showed the same types of deregulation patterns, although they sometimes differed in expression levels. These clustered and homologous miRNAs may have close functional relationships, which may indicate collaborative interactions between miRNAs. The integrative analysis of miRNA-mRNA based on biological characteristics of miRNA will further enrich miRNA study.

SUBMITTER: Guo L

PROVIDER: S-EPMC3945032 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.

Guo Li L Zhao Yang Y Yang Sheng S Zhang Hui H Chen Feng F

BioMed research international 20140212

MicroRNAs (miRNAs) are small, noncoding regulatory molecules. They are involved in many essential biological processes and act by suppressing gene expression. The present work reports an integrative analysis of miRNA-mRNA and miRNA-miRNA interactions and their regulatory patterns using high-throughput miRNA and mRNA datasets. Aberrantly expressed miRNA and mRNA profiles were obtained based on fold change analysis, and qRT-PCR was used for further validation of deregulated miRNAs. miRNAs and targ ...[more]

PMID: 24689063

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Project description:Gastric cancer (GC) is one of the most common types of malignant cancer and is associated with poor prognosis. Although the prognosis of patients with GC is associated with grade, stage and lymph node metastases, these traditional clinical features are inadequate to predict the outcome of GC. Therefore, there has been an increased focus on identifying novel molecular biomarkers for early diagnosis and prognosis, in order to improve outcomes in GC. In the present study, an integrative analysis of microRNA (miRNA) expression profiles, mRNA expression profiles and clinical characteristics was performed in a large cohort of patients with GC in order to identify an integrative prognostic model for improving postoperative risk classification. An integrative mRNA/miRNA signature (IMMIS), comprised of three miRNAs and one mRNA, was identified from a large number of differentially expressed miRNAs and mRNAs using univariate and multivariate Cox regression analysis. The prognostic value of the IMMIS was validated in the discovery cohort, testing cohort and The Cancer Genome Atlas (TCGA) cohort. The present results suggested that the identified signature had a reliable predictive performance and could classify the patients into high- and low-risk groups with significantly different overall survival times. In the discovery cohort, the hazard ratio (HR) was 2.805 with a 95% CI=1.722-4.567 (P<0.001). The median overall survival time as 1.49 vs. 3.85 years. In the testing cohort, the HR was 1.625 with a 95% CI=1.004-2.638 (P=0.039) and the median overall survival time was 2.17 vs. 4.62 years. In the TCGA cohort, the HR was 2.139 with a 95% CI=1.519-3.012 (P<0.001) and the median overall survival time was 1.53 vs. 4.62 years. The IMMIS constituted a reliable independent prognostic factor compared with clinical covariates, including age, sex, grade and stage, as indicated by multivariate and stratified analyses. Furthermore, comparative analysis revealed that the predictive value of the IMMIS was superior to the mRNA-based signature alone. The present results suggested the potential value of the IMMIS as a promising novel biomarker for improving the clinical management of patients with GC.

Dataset Information

Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.

Publications

Integrative analysis of miRNA-mRNA and miRNA-miRNA interactions.

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