Dissection of transcriptomic and epigenetic heterogeneity of grade 4 gliomas: implications for prognosis - Chang Zeng; Xiao Song; Zhou Zhang; Qinyun Cai; Jiajun Cai; Craig Horbinski; Bo Hu; Shi-Yuan Cheng; Wei Zhang (Acta Neuropathologica Communications, 2023)
Abstract Background Grade 4 glioma is the most aggressive and currently incurable brain tumor with a median survival of one year in adult patients. Elucidating novel transcriptomic and epigenetic contributors to the molecular heterogeneity underlying its aggressiveness may lead to improved clinical outcomes. Methods To identify grade 4 glioma -associated 5-hydroxymethylcytosine (5hmC) and transcriptomic features as well as their cross-talks, genome-wide 5hmC and transcriptomic profiles of tissue samples from 61 patients with grade 4 gliomas and 9 normal controls were obtained for differential and co-regulation/co-modification analyses. Prognostic models on overall survival based on transcriptomic features and the 5hmC modifications summarized over genic regions (promoters, gene bodies) and brain-derived histone marks were developed using machine learning algorithms. Results Despite global reduction, the majority of differential 5hmC features showed higher modification levels in grade 4 gliomas as compared to normal controls. In addition, the bi-directional correlations between 5hmC modifications over promoter regions or gene bodies and gene expression were greatly disturbed in grade 4 gliomas regardless of IDH1 mutation status. Phenotype-associated co-regulated 5hmC–5hmC modules and 5hmC–mRNA modules not only are enriched with different molecular pathways that are indicative of the pathogenesis of grade 4 gliomas, but also are of prognostic significance comparable to IDH1 mutation status. Lastly, the best-performing 5hmC model can predict patient survival at a much higher accuracy (c-index = 74%) when compared to conventional prognostic factor IDH1 (c-index = 57%), capturing the molecular characteristics of tumors that are independent of IDH1 mutation status and gene expression-based molecular subtypes. Conclusions The 5hmC-based prognostic model could offer a robust tool to predict survival in patients with grade 4 gliomas, potentially outperforming existing prognostic factors such as IDH1 mutations. The crosstalk between 5hmC and gene expression revealed another layer of complexity underlying the molecular heterogeneity in grade 4 gliomas, offering opportunities for identifying novel therapeutic targets.