ArticleIET systems biology2016
Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis.
Article in IET systems biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Potential role of microRNAs as biomarkers in human glioblastoma: a mini systematic review from 2015 to 2020.Molecular biology reports · 2021Pooled it
- Functions and mechanisms of miR-650 in human diseases.Frontiers in molecular biosciences · 2026Review
- LncRNA H19 acts as a ceRNA to promote glioblastoma malignancy by sponging miR-19b-3p and upregulating SERPINE1.Cancer cell international · 2025Article
- Microrna-1224-5p Is a Potential Prognostic and Therapeutic Biomarker in Glioblastoma: Integrating Bioinformatics and Clinical Analyses.Current medical science · 2022Article
- Article
- NF-κB-mediated miR-650 plays oncogenic roles and activates AKT/ERK/NF-κB pathways by targeting RERG in glioma cells.Cellular oncology (Dordrecht, Netherlands) · 2020Article
- Investigation of miRNA and mRNA Co-expression Network in Ependymoma.Frontiers in bioengineering and biotechnology · 2020Article
- MicroRNA-181 inhibits glioblastoma cell growth by directly targeting CCL8.Oncology letters · 2019Article
- Mining conditions specific hub genes from RNA-Seq gene-expression data via biclustering and their application to drug discovery.IET systems biology · 2019Article
- MicroRNA-1231 exerts a tumor suppressor role through regulating the EGFR/PI3K/AKT axis in glioma.Journal of neuro-oncology · 2018Article
- MicroRNA-141-3p promotes glioma cell growth and temozolomide resistance by directly targeting p53.Oncotarget · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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