Abstract
BackgroundGlioblastoma (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.MethodsUsing 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.ResultsThe integrative Glioblastoma Subtype (iGlioSub) classifier shows better performance (mean AUC = 95.9%) stratifying patients than gene expression (mean AUC = 91.9%) and DNAm-based classifiers (AUC = 93.6%). Also, to expand the understanding of the molecular differences between the GBM subtypes, this study shows that each subtype presents unique DNAm patterns and gene pathway activation.ConclusionsThe iGlioSub classifier provides the basis to design cost-effective strategies to stratify GBM patients in routine pathology laboratories for clinical trials, which will significantly accelerate the discovery of more efficient GBM subtype-specific treatment approaches.
Highlights
Despite aggressive multimodal treatments, the median survival of glioblastoma (GBM)patients is 15 months, with only 5 % survival beyond 5 years [1]
Unsupervised hierarchical clustering analysis and tSNE representation using subtype-specific differentially expressed genes (DEG) or differentially methylated sites (DMS) showed a modest overall performance in segregating the cases according to the annotated GBM subtype, even when combining DEG and DMS
The initial Random Forest (RF)-based signatures were reduced by applying nearest shrunken centroid (NSC) approaches
Summary
The median survival of glioblastoma (GBM)patients is 15 months, with only 5 % survival beyond 5 years [1]. GBM molecular features are gaining more attention, given their critical role in clinical decision-making. Hypermethylation of the MGMT gene promoter region is the best-known prognostic factor for a favorable response to Temozolomide [11]. Other factors such as ZNF7 expression levels, or transcriptional profiling of the tumor microenvironment, have emerged as potential prognostic markers for GBM [12, 13]. Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Due to the costs of high-throughput profiling techniques, GBM molecular subtyping is not currently employed in clinical settings
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