DNA Methylation Profiling in Central Nervous System Tumors

DNA methylation profiling has emerged as a cornerstone of modern neuro-oncology, enabling epigenetic characterisation of central nervous system (CNS) tumours with a precision that transcends conventional histopathology. By interrogating patterns of cytosine methylation across the genome, this approach reveals molecular subclasses within morphologically similar tumour entities and refines diagnostic accuracy. Beyond diagnosis, methylation profiles inform prognosis, reveal therapeutic targets and uncover cancer predisposition syndromes. Integration with copy number analysis and targeted gene sequencing has established a multi-omic framework that guides clinical decision-making, from neurosurgical resection strategies to the selection of targeted therapies. The global rollout of array-based and sequencing-based workflows has standardised epigenetic tumour classification, streamlining diagnostic pathways and reducing inter-centre variability. As a result, methylation profiling is reshaping CNS tumour taxonomy, driving the adoption of epigenetic criteria in the WHO classification and supporting personalised patient management worldwide.

Research from Nature Portfolio

Recent studies have demonstrated the feasibility of ultra-rapid epigenetic diagnosis during surgery. By applying nanopore sequencing to native tumour DNA, a sparse methylation signature can be generated intraoperatively and analysed through a transfer-learned neural network. This workflow delivers a reliable molecular subclassification within an hour, informing surgeons in real time and minimising the risk of neurological damage. Parallel advances in paediatric neuro-oncology have leveraged integrated DNA methylation and targeted gene panel sequencing in population-based cohorts. In these efforts, half of all patients received refined methylation-based diagnoses, nearly half harboured actionable genetic alterations and a subset presented identifiable cancer predisposition syndromes. Notably, discordances between histological grade and methylation class were linked to improved outcomes in certain high-grade gliomas, underscoring the prognostic relevance of epigenetic stratification.

DNA Methylation Profiling in Central Nervous System Tumors publication trend

The graph below shows the total number of articles in dna methylation profiling in central nervous system tumors across all publications each year (not limited to Nature Index journals).

Technical terms

DNA methylation profiling: Genome-wide measurement of cytosine methylation levels used to classify tumour subtypes.

Nanopore sequencing: A real-time sequencing technique that reads nucleotide modifications directly from native DNA fragments.

Copy number variation: Gains or losses of genomic regions assessed alongside methylation to refine tumour characterisation.

Multi-omic integration: Combined analysis of methylation, genetic mutations and copy number alterations for enhanced diagnostic precision.

Neural network classifier: A machine learning model trained to assign tumour samples to epigenetic subclasses based on methylation signatures.

References

1. Ultra-fast deep-learned CNS tumour classification during surgery. Nature (2023).
2. Multiomic neuropathology improves diagnostic accuracy in pediatric neuro-oncology. Nature Medicine (2023).
3. Glioneuronal tumor with ATRX alteration, kinase fusion and anaplastic features (GTAKA): a molecularly distinct brain tumor type with recurrent NTRK gene fusions. Acta Neuropathologica (2023).
4. Pediatric-type high-grade neuroepithelial tumors with CIC gene fusion share a common DNA methylation signature. npj Precision Oncology (2023).
5. EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics. Acta Neuropathologica Communications (2024).
6. Practical implementation of DNA methylation and copy-number-based CNS tumor diagnostics: the Heidelberg experience. Acta Neuropathologica (2018).
7. The central nervous system tumor methylation classifier changes neuro-oncology practice for challenging brain tumor diagnoses and directly impacts patient care. Clinical Epigenetics (2019).
8. Impact of the methylation classifier and ancillary methods on CNS tumor diagnostics. Neuro-Oncology (2021).
9. A Summary of the Inaugural WHO Classification of Pediatric Tumors: Transitioning from the Optical into the Molecular EraInaugural WHO Classification of Pediatric Tumors: A Summary. Cancer Discovery (2021).