Integration of omics data in the diagnosis and therapy of glioblastoma.

Abstract

Since the 2016 update of the WHO Classification of Tumors of the Central Nervous System, omics data have been officially integrated into the diagnostic process for glioblastoma, the most prevalent and aggressive primary malignant brain tumor in adults. This review will examine the current and future integration of omics data in both the diagnosis and therapy of glioblastomas. The current clinical use of omics data primarily focuses on genomics for determining the IDH- and H3-wildtype status of the tumor, and on epigenomics, such as assessing MGMT promoter methylation status as a prognostic and predictive biomarker. However, it can be anticipated that the usage and importance of omics data will likely increase in the future. This work highlights how omics technologies have significantly enhanced our understanding of glioblastoma, particularly of its extensive heterogeneity. This enhanced understanding has not only improved diagnostic accuracy but has also facilitated the identification of new predictive and/or prognostic biomarkers. It is likely that the ongoing integration of omics data will transform many aspects of the diagnostic process, including sample acquisition. Additionally, omics data will be integrated into future glioblastoma treatment procedures, with possible applications ranging from identifying potential therapeutic targets to selecting individual treatment plans. The implications of the ongoing integration of omics data for clinical routine, future classification systems, and trial design are also discussed in this review, outlining the pivotal role omics data play in shaping future glioblastoma diagnosis and treatment.