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Identification of Survival-Associated miRNA Signatures in Glioblastoma Using Next-Generation Sequencing

Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Glioblastoma (GBM) is the most aggressive primary brain tumor in adults and is characterized by pronounced molecular heterogeneity, contributing to poor prognosis and limited therapeutic responsiveness. Distinct clinical subgroups, including short-term survivors (GBM-STS) and long-term survivors (GBM-LTS), differ substantially in disease progression and outcome; however, reliable biomarkers for prognostic stratification remain insufficiently defined. This study aimed to identify microRNA (miRNA) expression patterns capable of distinguishing GBM-STS from GBM-LTS patients. Methods: miRNA expression profiling was performed on glioblastoma tissue samples using next-generation sequencing (NGS). Differentially expressed miRNAs between GBM-STS and GBM-LTS groups were subjected to Gene Ontology (GO) Biological Process enrichment analysis to identify dysregulated pathways associated with their predicted target genes. Selected candidate miRNAs were further validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Results: Functional enrichment analysis revealed significant overrepresentation of pathways related to neurogenesis, neuronal differentiation, and neuron projection development, supporting the involvement of neural developmental programs in glioblastoma progression and invasion. NGS and RT-qPCR analyses demonstrated significant downregulation of hsa-miR-133a-3p, and significant upregulation of hsa-miR-424-5p and has-miR-216a-5p in GBM-STS tissues compared with GBM-LTS and control samples. Conclusions: Our findings demonstrate that distinct miRNA expression profiles are associated with survival-related glioblastoma subgroups and may contribute to differences in tumor aggressiveness. Hsa-miR-424-5p, has-miR-216a-5p, and hsamiR-133a-3p may represent promising candidate biomarkers for prognostic stratification in glioblastoma.
Language: English
Subfield: Cancer Research
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W7222962397
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