SynthesisJournal of neuro-oncology2025
Investigating glioblastoma chemoresistance: a meta-analysis of microRNA signatures and gene networks.
Synthesis in Journal of neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundChemoresistance is a significant issue in glioblastoma (GBM) treatment due to recurrence, poor survival and limited salvage options. Non-invasive biomarkers can identify early chemoresistance. These cohorts may benefit from initiating early chemotherapy or second-line drugs at an earlier timeline.
methodsMeta-analysis of identified miR through systematic review was conducted through data mining and miR-target interaction compilation in validated miR databases. We curated a list of gene targets that underwent pathway enrichment analysis using the EnrichR tool. Network analysis of pathways and protein-protein interactions was conducted using the Metascape bioinformatics tool with several ontology sources.
resultsSignificantly upregulated miR validated in chemoresistant GBM were miR-221, -222, -132, and - 125b. 33 miR are identified in the high expression category. 18 miR were low expression responders in TMZ-resistant GBM. MiR-21 and miR-10b are the most replicated miR for bevacizumab response assessment with a low expression in Avastin-resistant GBM. 5 miR with high expression and 11 miR with low expression were identified; two combined micro-RNA signatures predicted cohorts likely to respond well to bevacizumab therapy. MiRs upregulated in TMZ resistance showed 400 predicted mRNA targets and 411 genes in downregulated miR. For bevacizumab response, upregulated miR yielded 38 genes and 82 in downregulated miR. An integrated, mechanistic model linking these miR to downstream targets and pathways is presented.
conclusionsmiR evaluation of GBM chemo-resistance requires insights into molecular subtypes and key signatures associated with TMZ/BVZ treatment failure. Evaluating a compiled signature's efficacy in improving progression-free and overall survival can highlight the impact of miR in GBM response evaluation. Our meta-analysis provides a template for understanding the key pathways and targets involved in miR-regulation of chemo-resistant GBM and potential applications of our signature in clinical practice.
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Registered trials
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