Computational analysis uncovers druggable targets and regulatory lncRNAs in invasive glioblastoma, highlighting candidate repurposed compounds to suppress recurrence.
Introduction Glioblastoma (GBM) recurrence is driven by residual disease that infiltrates beyond the resection margin, a region poorly characterised at the molecular level. Fluorescence-guided surgery using 5-aminolevulinic acid (5ALA) identifies metabolically active invasive tumour populations and provides an opportunity to interrogate the biology underpinning local invasion and recurrence. Methods Spatially resolved bulk RNA-seq data derived from 5ALA-defined GBM regions were analysed to identify genes enriched at the invasive margin. Differential expression within intra-tumour regions were integrated with protein-protein interaction analysis and patient survival. Protein-coding genes associated with adverse overall and disease-free survival were prioritised for structure-based drug repurposing using binding pocket identification and molecular docking against FDA-approved and experimental libraries. In parallel, 16 invasive-specific lncRNAs were identified and curated, and literature-informed Boolean network modelling is being used to explore their regulatory roles within invasion-associated gene networks. Results This integrative pipeline identified an invasive- specific gene signature enriched in 5ALA+ tumour populations. Six genes upregulated in 5ALA+ regions relative to other intra-tumour regions demonstrated invasive-margin specificity and consistent associations with survival and were prioritised for structure-based drug repurposing. Molecular docking identified a focused set of clinically relevant candidate compounds, including fosphenytoin, flecainide, droperidol, lemborexant, and safinamide, which are currently being progressed to wet-lab validation in GBM 2D/3D models. In parallel, 16 lncRNAs uniquely enriched at the invasive margin were identified and selected for Boolean network modelling to explore their potential regulatory roles within invasion-associated gene networks. Conclusion This work establishes a multi-layered computational framework linking invasive-margin biology with therapeutic prioritisation and regulatory network modelling. By targeting both protein-coding candidates and lncRNA driven regulatory dynamics, this approach aims to advance strategies directed at residual GBM cells responsible for tumour recurrence.
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Shah et al. (2026) studied this question.
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