Gene clusters based on OLIG2 and CD276 could distinguish molecular profiling in glioblastoma

Abstract

Background The molecular profiling of glioblastoma (GBM) based on transcriptomic analysis could provide precise treatment and prognosis. However, current subtyping (classic, mesenchymal, neural, proneural) is time-consuming and cost-intensive hindering its clinical application. A simple and efficient method for classification was imperative. Methods In this study, to simplify GBM subtyping more efficiently, we applied a random forest algorithm to conduct 26 genes as a cluster featured with hub genes, OLIG2 and CD276. Functional enrichment analysis and Protein–protein interaction were performed using the genes in this gene cluster. The classification efficiency of the gene cluster was validated by WGCNA and LASSO algorithms, and tested in GSE84010 and Gravandeel’s GBM datasets. Results The gene cluster (n = 26) could distinguish mesenchymal and proneural excellently (AUC = 0.92), which could be validated by multiple algorithms (WGCNA, LASSO) and datasets (GSE84010 and Gravandeel’s GBM dataset). The gene cluster could be functionally enriched in DNA elements and T cell associated pathways. Additionally, five genes in the signature could predict the prognosis well (p = 0.0051 for training cohort, p = 0.065 for test cohort). Conclusions Our study proved the accuracy and efficiency of random forest classifier for GBM subtyping, which could provide a convenient and efficient method for subtyping Proneural and Mesenchymal GBM.

mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses

“…), this review aimed to conduct a comprehensive, systematic literature review to identify all relevant studies that have significantly reported genes related to overall survival in GBM patients. However, some impact reports on this topic might have been missed due to limitations in the search strategy [ 265 – 266 ]. In the study future, given the well-established heterogeneity of GBM, the assessment of the prognostic value of specific genes must be conducted with consideration for GBM molecular subtypes, to ensure a comprehensive understanding of their impact, and would pave the way for precision medicine [ 266 ].…”

“…However, some impact reports on this topic might have been missed due to limitations in the search strategy [265][266]. In the study future, given the well-established heterogeneity of GBM, the assessment of the prognostic value of specific genes must be conducted with consideration for GBM molecular subtypes, to ensure a comprehensive understanding of their impact, and would pave the way for precision medicine [266].…”

TNFAIP8 in Mesenchymal Glioblastoma Correlates with Metabolic Dysfunction and Poor Prognosis

“…Speci c molecular events in gliomas like EGFR ampli cation, MYB alteration, MAPK pathway alteration, have shown their signi cance according to WHO CNS5 (1). Our previous analysis found GBM with Olig2 or CD276 could share totally different prognosis, and a gene cluster featured with hub genes of Olig2 and CD276 could distinguish molecular subtypes in GBM (4). Interestingly, tumor necrosis factor-α-induced protein 8 (TNFAIP8) was superiorly de ned as one of the independent factors for prognosis in GBM, which favored mesenchymal subtype (4).…”