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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
Comprehensive multi-omics approach reveals critical genes and immunometabolic networks in glioblastoma
Zhaohui Yi1, Min Song, Lirong Liang
1Department of Neurosurgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Background:
Glioblastoma multiforme (GBM) is the most aggressive primary brain tumor, with a 5-year survival rate of 4%-7% and median survival of 12-18 months despite treatment advances. Its complex genetic profile and immunosuppressive microenvironment underscore the urgent need to identify novel therapeutic targets.
Methods:
We conducted an integrative multi-omics study combining bioinformatics, transcriptomics, proteomics, and Mendelian Randomization (MR). Differential gene expression analysis was performed between GBM and normal tissues, followed by intersecting differentially expressed genes with expression quantitative trait loci and protein quantitative trait loci (pQTL) datasets. Overlapping genes were employed as instrumental variables in MR analyses with GBM as the outcome. Findings were validated using the Summary-data-based Mendelian Randomization method and pQTL data from the UKB-PPP cohort. Two-step MR analyses explored the mediating effects of immune cells, cerebrospinal fluid metabolites, and plasma metabolites. Additionally, in vitro experiments and drug-gene interaction analyses validated biological functions and therapeutic potential.
Result:
LGALS9 and SELL exhibited significant causal associations with elevated GBM risk. Two-step MR analyses elucidated their mechanisms: LGALS9 promotes GBM via CD3 on CD39 + resting regulatory T cells (mediating 7% of the effect), while SELL acts through cerebrospinal fluid metabolite X-22162 (mediating 16% of the effect). In vitro studies confirmed that LGALS9 and SELL enhance GBM cell proliferation, migration, and invasion, with drug analyses and molecular docking identifying promising compounds, such as meclofenamate, targeting SELL.
Conclusion:
This pioneering study integrates multi-omics data with MR methodology in GBM research, providing robust evidence for the causal roles of LGALS9 and SELL and clarifying their mechanistic pathways. Validated through functional experiments and druggability assessments, these findings highlight actionable therapeutic targets and prognostic biomarkers for advancing GBM treatment.
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