DNA methylation-based classification of central nervous system tumours

Abstract

Summary Accurate pathological diagnosis is crucial for optimal management of cancer patients. For the ~100 known central nervous system (CNS) tumour entities, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumour types. We herein present the development of a comprehensive approach for DNA methylation-based CNS tumour classification across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that availability of this method may have substantial impact on diagnostic precision compared with standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility we have designed a free online classifier tool (www.molecularneuropathology.org) requiring no additional onsite data processing. Our results provide a blueprint for the generation of machine learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

cIMPACT-NOW update 3: recommended diagnostic criteria for “Diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma, WHO grade IV”

“…Whole genome DNA methylation profiling represents a robust and reproducible method for precisely segregating tumor types that have similar histogenesis, genetic signatures and clinical behaviors [5, 6]. IDH-wildtype diffuse astrocytic gliomas of WHO grade II or III with genetic features suggesting aggressive clinical behavior ( EGFR amplification, +7/−10, TERT promoter mutation) have been shown to cluster tightly with IDH-wildtype glioblastoma based on DNA methylation profiling[6, 10, 26].…”

“…IDH-wildtype diffuse astrocytic gliomas of WHO grade II or III with genetic features suggesting aggressive clinical behavior ( EGFR amplification, +7/−10, TERT promoter mutation) have been shown to cluster tightly with IDH-wildtype glioblastoma based on DNA methylation profiling[6, 10, 26]. Other forms of gliomas with indolent clinical features do not cluster together with these tumors, indicating a high degree of specificity for this signature[5]. While the literature indicates this method is superior for classification purposes and could have a role in grading, it currently lacks widespread clinical implementation due to regulatory challenges and prevailing practice patterns that test primarily for mutations and copy number alterations, as well as a reluctance due to uncertainties in reimbursement.…”

Practical implementation of DNA methylation and copy-number-based CNS tumor diagnostics: the Heidelberg experience

“…Consequently, the potential of methylation-based characterization has been expanded to other CNS tumor entities and the overarching concept and feasibility has just been published [6]. …”

Satisfying your neuro-oncologist: a fast approach to routine molecular glioma diagnostics

“…4 For methylome analysis, 500 ng DNA were bisulfite converted and tested using the Infinium Methylation EPIC Microarray (Illumina), and data were analyzed by Brain Tumor Methylation Classifier v11b4. 2 …”

“…Both techniques provide sufficient stratification based on published diagnostic cutoffs. 2,4 (C–E) Turnaround times (TaT) calculated from diagnostic reports and plotted as histograms, counting from the day of surgery. DNA extraction follows overnight proteinase K tissue dissection.…”