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Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Investigating glioblastoma chemoresistance: a meta-analysis of microRNA signatures and gene networks
Mohammad Hamza Bajwa1, Sufiyan Sufiyan1, Wajiha Amin1
1Section of Neurosurgery and Center of Oncological Research in Surgery, The Aga Khan University, Karachi, Pakistan.
Background:
Chemoresistance 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.
Methods:
Meta-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.
Results:
Significantly 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.
Conclusions:
miR 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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