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Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.

ABSTRACT: Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor in adults. Patients with this disease have a poor prognosis. The objective of this study is to identify survival-related individual genes (or miRNAs) and miRNA -mRNA pairs in GBM using a multi-step approach. First, the weighted gene co-expression network analysis and survival analysis are applied to identify survival-related modules from mRNA and miRNA expression profiles, respectively. Subsequently, the role of individual genes (or miRNAs) within these modules in GBM prognosis are highlighted using survival analysis. Finally, the integration analysis of miRNA and mRNA expression as well as miRNA target prediction is used to identify survival-related miRNA -mRNA regulatory network. In this study, five genes and two miRNA modules that significantly correlated to patient's survival. In addition, many individual genes (or miRNAs) assigned to these modules were found to be closely linked with survival. For instance, increased expression of neuropilin-1 gene (a member of module turquoise) indicated poor prognosis for patients and a group of miRNA -mRNA regulatory networks that comprised 38 survival-related miRNA -mRNA pairs. These findings provide a new insight into the underlying molecular regulatory mechanisms of GBM.

SUBMITTER: Bing ZT

PROVIDER: S-EPMC8687286 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.

Bing Zhi-Tong ZT Yang Guang-Hui GH Xiong Jie J Guo Ling L Yang Lei L

IET systems biology 20161201 6

Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor in adults. Patients with this disease have a poor prognosis. The objective of this study is to identify survival-related individual genes (or miRNAs) and miRNA -mRNA pairs in GBM using a multi-step approach. First, the weighted gene co-expression network analysis and survival analysis are applied to identify survival-related modules from mRNA and miRNA expression profiles, respectively. Subsequently, the ...[more]

PMID: 27879479

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Project description:Background: Glioblastoma multiforme (GBM), the most common and aggressive human malignant brain tumor, is notorious for its limited treatment options and poor prognosis. MicroRNAs (miRNAs) are found to be involved in tumorigenesis of GBM. However, a comprehensive miRNA-mRNA regulatory network has still not been established. Methods: A miRNA microarray dataset (GSE90603) was obtained from GEO database. Then, we employed GEO2R tool to perform differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The GBM mRNA dataset were downloaded from TCGA database for identifying differentially expressed genes (DEGs). Next, GO annotation and KEGG pathway enrichment analysis was conducted. PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes was further evaluated. Results: Total 33 DE-miRNAs, consisting of 10 upregulated DE-miRNAs and 23 downregulated DE-miRNAs, were screened. SP1 was predicted to potentially regulate most of screened DE-miRNAs. Three thousand and twenty seven and 3,879 predicted target genes were obtained for upregulated and downregulated DE-miRNAs, respectively. Subsequently, 1,715 upregulated DEGs and 1,259 downregulated DEGs were identified. Then, 149 and 295 potential downregulated and upregulated genes commonly appeared in target genes of DE-miRNAs and DEGs were selected for GO annotation and KEGG pathway enrichment analysis. The downregulated genes were significantly enriched in cGMP-PKG signaling pathway and calcium signaling pathway whereas the upregulated genes were enriched in pathways in cancer and PI3K-Akt signaling pathway. Construction and analysis of PPI network showed that STXBP1 and TP53 were recognized as hub genes with the highest connectivity degrees. Expression analytic result of the top 20 hub genes in GBM using GEPIA database was generally identical with previous differential expression analysis for TCGA data. EGFR, PPP3CB, and MYO5A expression was significantly associated with patients' OS. Conclusions: In this study, we established a potential GBM-related miRNA-mRNA regulatory network, which explores a comprehensive understanding of the molecular mechanisms and provides key clues in seeking novel therapeutic targets for GBM. In the future, more experiments need to be performed to validate our current findings.

Project description:BackgroundHepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is a life-threatening disease with a high mortality rate; the systemic inflammatory response plays a vital role in disease progression. We aimed to determine if a miRNA-mRNA co-regulatory network exists in the peripheral blood mononuclear cells (PBMCs) of HBV-ACLF patients, which might be important for prognosis.MethodsIn patients with HBV-ACLF meeting COSSH-ACLF criteria, age, liver cirrhosis and INR were independent risk factors for 28-day and 90-day poor prognosis. COSSH-ACLFs was a superior prognostic model. mir-6840-3p-JADE2 may promote the progression of ACLF and lead to poor prognosis. Meanwhile, mir-6840-3p and mir-6861-3p can be used as markers of short-term poor prognosis. Finally, ALSS treatment is not only the blood material exchange of patients, but also changes part of the immune state of patients. Among them, cytokine cytokine receptor interaction may play an important role in determining the therapeutic effect.MethodsTranscriptome-wide microRNA (miRNA) and mRNA microarrays were used to define the miRNA and mRNA expression profiles of the PBMCs of HBV-ACLF patients in a discovery cohort. The targets of the miRNAs were predicted. We built a miRNA-mRNA regulatory network through bioinformatics analysis, and used quantitative real-time polymerase chain reaction (qRT-PCR) to assess the importance of candidate miRNAs and mRNAs. We also assessed the direct and transcriptional regulatory effects of miRNAs on target mRNAs using a dual-luciferase reporter assay.ResultsThe miRNA/mRNA PBMC expression profiles of the discovery cohort, of whom eight survived and eight died, revealed a prognostic interactive network involving 38 miRNAs and 313 mRNAs; this was constructed by identifying the target genes of the miRNAs. We validated the expression data in another cohort, of whom 43 survived and 35 died; miR-6840-3p, miR-6861-3p, JADE2, and NR3C2 were of particular interest. The levels of miR-6840-3p and miR-6861-3p were significantly increased in the PBMCs of the patients who died, and thus predicted prognosis (areas under the curve values = 0.665 and 0.700, respectively). The dual-luciferase reporter assay indicated that miR-6840-3p directly targeted JADE2.ConclusionWe identified a prognostic miRNA-mRNA co-regulatory network in the PBMCs of HBV-ACLF patients. miR-6840-3p-JADE2 is a potential miRNA-mRNA pair contributing to a poor prognosis.

Project description:BackgroundDuring asthma progression, the intricate molecular networks, including microRNA (miRNA) transcriptional regulation in airway epithelium, remain largely undefined. The abnormal expression of miRNAs in asthmatic airway epithelium is a recent and fast-growing area in developing diagnostic and therapeutic targets for asthma.Material and methodsAnalyses were conducted to compare airway epithelial miRNAs and gene expression between patients with asthma and healthy subjects from three datasets (two for miRNAs expression profiles and one for gene expression profile). The interactions network between differentially expressed (DE)-miRNAs and mRNAs was further identified for functional analysis. To verify the involvement and functions of all the identified miRNAs in asthma, we constructed two cellular models of asthma. The most promising causal miRNA candidate, miR-1246, was examined in an in vitro system to explore its targets and roles in asthma pathophysiology.ResultsThrough integrative analysis, we obtained six miRNAs with 31 validated target genes in airway epithelium associated with asthma. Next, we confirmed that these miRNAs were all associated with asthma progression by in vitro functional experiments. They may participate in eosinophilic inflammation (miR-92b-3p, miR-1246, miR-197-3p, and miR-124-5p) or remodeling (miR-197-3p, miR-193a-5p, miR-1246, and miR-92b-3p). Additionally, some other non-screened valuable miRNAs were also examined and identified (miR-21-5p and miR-19b-3p), and some detected in blood correlated with the disease status. Furthermore, we found that miR-1246 could directly target POSTN and influence epithelial-to-mesenchymal transition and fibrosis in airway epithelial cells.ConclusionWe constructed a preliminary epithelial regulatory network in asthma based on six identified miRNAs and their valuable target genes. Candidate factors in the biological miRNA-mRNA network in airway epithelium may provide further information on the pathogenesis of asthma. Strikingly, among all screened miRNAs, miR-1246, which could interact with POSTN may have multifunctional effects in the course of asthma and be a promising agent for asthma treatment and molecular subtyping.

Project description:BackgroundGlioblastoma (GBM) is an intracranial brain tumor characterized by a high final lethality rate and recurrence rate, and limited available therapies. With the development of high-throughput sequencing technology, the genomic and transcriptomic features of GBM have been fully characterized. Therefore, our study aimed to identify its underlying genetic mechanisms, thus facilitating the development of novel therapies for GBM.MethodsBased on the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases, differential expression of RNAs in GBM and control group was analyzed. After constructing the long noncoding RNA (lncRNA)-miRNA-mRNA regulatory network of GBM, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were performed to analyze related key nodes and the lncRNAs interacting with them. Further univariate Cox regression was conducted to explore independent factors, and then multivariate Cox regression was performed to construct risk prediction models.ResultsWe first constructed the lncRNA-miRNA-mRNA regulatory network of GBM and two effective prediction models that included 2 mRNAs [transcription factor 12 (TCF12) and discoidin, CUB and LCCL domain containing 2 (DCBLD2)] and 5 lncRNAs (C10orf25, LINC00343, HOXA transcript antisense RNA, myeloid-specific 1 (HOTAIRM1), FGF12 antisense RNA 2 (FGF12-AS2) and H19). Additionally, we identified several key molecules [TCF12, integrin β3 (ITGB3), high mobility group AT-hook 2 (HMGA2), C10orf25 and LINC00336] closely associated with GBM prognosis. C10orf25/miR-218/DCBLD2 may be an important regulatory pathway in GBM.ConclusionsKey molecules (TCF12, ITGB3, HMGA2, C10orf25, LINC00336 and H19) that are independent prognostic factors may be possible biomarkers to further optimize GBM prognosis. Two effective prognostic risk models that include 2 mRNAs (TCF12 and DCBLD2) and 5 lncRNAs (C10orf25, LINC00343, HOTAIRM1, FGF12-AS2 and H19) were constructed. C10orf25/miR-218/DCBLD2 may be an important regulatory pathway associated with the pathogenesis of GBM. Our findings contribute to further understanding the pathogenesis of GBM and finding possible candidate genes for prognostic and therapeutic usage with GBM.

Dataset Information

Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.

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Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.

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