#6024. iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes

April 2026publication date
Proposal available till 15-05-2025
4 total number of authors per manuscript6020 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Computational Mathematics;
Computational Theory and Mathematics;
Computer Science Applications;
Genetics;
Biochemistry;
Molecular Biology;
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Abstract:
Background: Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Advancements in multi-omics profiling combined with computational algorithms have unraveled the existence of three GBM molecular subtypes (Classical, Mesenchymal, and Proneural) with clinical relevance. However, due to the costs of high-throughput profiling techniques, GBM molecular subtyping is not currently employed in clinical settings. Methods: Using Random Forest and Nearest Shrunken Centroid algorithms, we constructed transcriptomic, epigenomic, and integrative GBM subtype-specific classifiers. We included gene expression and DNA methylation (DNAm) profiles from 304 GBM patients profiled in the Cancer Genome Atlas (TCGA), the Human Glioblastoma Cell Culture resource (HGCC), and other publicly available databases.
Keywords:
Cancer; DNA methylation; Epigenetics; Gene expression; Glioblastoma; iGlioSub; Integrative classifier; Machine learning; Molecular subtypes

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