Molecular diagnostic tools for the World Health Organization (WHO) 2021 classification of gliomas, glioneuronal and neuronal tumors; an EANO guideline

Abstract

In the 5th edition of the WHO CNS tumor classification (CNS5, 2021), multiple molecular characteristics became essential diagnostic criteria for many additional CNS tumor types. For those tumors, an integrated, "histomolecular" diagnosis is required. A variety of approaches exists for determining the status of the underlying molecular markers. The present guideline focuses on the methods that can be used for assessment of the currently most informative diagnostic and prognostic molecular markers for the diagnosis of gliomas, glioneuronal and neuronal tumors. The main characteristics of the molecular methods are systematically discussed, followed by recommendations and information on available evidence levels for diagnostic measures. The recommendations cover DNA and RNA next-generation-sequencing, methylome profiling, and select assays for single/limited target analyses, including immunohistochemistry. Additionally, because of its importance as a predictive marker in IDH-wildtype glioblastomas, tools for the analysis of MGMT promoter methylation status are covered. A structured overview of the different assays with their characteristics, especially their advantages and limitations, is provided, and requirements for input material and reporting of results are clarified. General aspects of molecular diagnostic testing regarding clinical relevance, accessibility, cost, implementation, regulatory, and ethical aspects are discussed as well. Finally, we provide an outlook on new developments in the landscape of molecular testing technologies in neuro-oncology.

Keywords: WHO classification; glioma; glioneuronal tumors; molecular classification; molecular diagnostics; neuronal tumors.

Figure 1.

Overview of major molecular diagnostic technologies. The technologies discussed in this guideline are depicted with focus on the high-throughput, more recently established methods. For simplicity, turnaround times represent a scenario in which the protocol is instantly initiated for a given sample, not accounting for other timeframes in typical routine workflows, for example, once-weekly methylation runs, or other platforms with the need to collect samples over several days for generating reasonable batch sizes. Exact cost, material input, timelines, but also width of analysis results depend on the local setting: While DNA methylation arrays are highly standardized, DNA and RNA NGS platforms can be designed at different scale, from very narrow target regions to a whole exome/genome or transcriptome, respectively. Figure generated with BioRender.

Figure 2.

CpGs interrogated in commonly used MGMT promoter methylation assays. The physical location of sites in the CpG island (green) interrogated by commonly used MGMT methylation assays are shown (CpGs, numbered 1–98, genome build GRCh37/hg19). The differentially methylated regions 1 and 2 (DMR1 and 2) are marked in blue. The CpGs from the original MSP assay commonly examined by qualitative and quantitative MSP assays are marked in red (MSP1, CpGs 76–80 and 84–87);^,, CpGs analyzed in a quantitative MSP assay (MSP2, CpGs 76–80 and 88–90) used in large clinical trials are marked in yellow. Two sets of CpGs used commonly for pyrosequencing, PSQ1 (CpGs 74–78) and PSQ2 (CpGs 76–79), are marked in purple and pink, respectively.^, The locations of the CpGs (31, 84) selected from the BeadChip array analyzed by the MGMT-STP27 procedure, are marked in black. Figure by Pierre Bady.