ArticleBMC bioinformatics2014
Differential expression of microRNAs as predictors of glioblastoma phenotypes.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 21 citations in OpenAlex.
- Modulation of miRNA Signature in Human Adipose Tissue After 3 Months of ω-3PUFA Supplementation.Cells · 2026Article
- Three Unrelated Children With Childhood Apraxia of Speech: Exome Sequencing and Functional Gene Analysis Imply a Role of Laminin-511 in Early Neurodevelopment.Case reports in genetics · 2026Article
- Epigenetic Alterations in Glioblastoma Multiforme as Novel Therapeutic Targets: A Scoping Review.International journal of molecular sciences · 2025Article
- Genome-Wide Association Study of Gallstone Disease Identifies Novel Candidate Genomic Variants in a Latino Community of Southwest USA.Journal of racial and ethnic health disparities · 2025Article
- Differential expression of microRNAs in xenografted Lewis lung carcinomas subjected to intermittent hypoxia: a next-generation sequence analysis.Translational cancer research · 2020Article
- Knockdown of lncRNA PVT1 Inhibits Glioma Progression by Regulating miR-424 Expression.Oncology research · 2019Article
- MiR-21, miR-34a, miR-125b, miR-181d and miR-648 levels inversely correlate with MGMT and TP53 expression in primary glioblastoma patients.Archives of medical science : AMS · 2019Article
- Density-Dependent Regulation of Glioma Cell Proliferation and Invasion Mediated by miR-9.Cancer microenvironment : official journal of the International Cancer Microenvironment Society · 2016Article
- An integrated network of microRNA and gene expression in ovarian cancer.BMC bioinformatics · 2015Article
- MicroRNA profiling in intraocular medulloepitheliomas.PloS one · 2015Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundGlioblastoma is the most aggressive primary central nervous tumor and carries a very poor prognosis. Invasion precludes effective treatment and virtually assures tumor recurrence. In the current study, we applied analytical and bioinformatics approaches to identify a set of microRNAs (miRs) from several different human glioblastoma cell lines that exhibit significant differential expression between migratory (edge) and migration-restricted (core) cell populations. The hypothesis of the study is that differential expression of miRs provides an epigenetic mechanism to drive cell migration and invasion.
resultsOur research data comprise gene expression values for a set of 805 human miRs collected from matched pairs of migratory and migration-restricted cell populations from seven different glioblastoma cell lines. We identified 62 down-regulated and 2 up-regulated miRs that exhibit significant differential expression in the migratory (edge) cell population compared to matched migration-restricted (core) cells. We then conducted target prediction and pathway enrichment analysis with these miRs to investigate potential associated gene and pathway targets. Several miRs in the list appear to directly target apoptosis related genes. The analysis identifies a set of genes that are predicted by 3 different algorithms, further emphasizing the potential validity of these miRs to promote glioblastoma.
conclusionsThe results of this study identify a set of miRs with potential for decreased expression in invasive glioblastoma cells. The verification of these miRs and their associated targeted proteins provides new insights for further investigation into therapeutic interventions. The methodological approaches employed here could be applied to the study of other diseases to provide biomedical researchers and clinicians with increased opportunities for therapeutic interventions.
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