CNS tumour methylation classifier
184 CNS tumour subclasses, from arrays or sequencing, running in your own laboratory.
How it works
Methylation-based classification of CNS tumours
Previously distributed under the MolecularNeuropathology banner, our flagship CNS tumour methylation classifier now runs on our own platform and as a licensed on-premise installation.
A well-annotated reference cohort
The classifier is trained on 7,495 methylation profiles covering 184 subclasses of CNS tumour. A machine-learning model compares each new case against that cohort and returns a score reflecting its resemblance to each class.
A calibrated confidence score
Every class receives a score between 0 and 1. A methylation subclass is only reported as a positive identification once its score passes a threshold of 0.9, so borderline cases are visible as borderline rather than presented as certainty.
Robust on difficult material
The cancer methylome combines somatically acquired alterations with features indicating the cell of origin. Methylation profiling is highly reproducible and often succeeds on small or degraded samples where other approaches do not.
Four-tier hierarchical output
Results are returned as methylation subclass, class, family and superfamily, alongside a copy number profile, quality-control metrics and an MGMT promoter methylation status prediction.
Specifications
Version 12.8
Coverage
- 184 subclasses
- 142 classes
- 75 families
- Reference cohort of 7,495 methylation profiles
Performance
- Four-tier hierarchical output
- Proposed evidence level annotation
- Confidence score for every call
In use
- Over 200,000 cases analysed to date
- More than 500 institutions worldwide
- On-premise version runs on standard laptops
- Installation guide included
- Proprietary CPT code for US reimbursement
- CE-IVD track
Workflow
From sample to report
- Sample collection: fresh frozen or FFPE, tumour content at least 70%
- DNA extraction
- Raw data generation
- Classification
- PDF and HTML report
Every report includes
- Quality control metrics
- Tumour classification with confidence score
- Copy number variation analysis
- MGMT promoter methylation status prediction
Supported platforms
Platform-agnostic: now compatible with sequencing data
The classifier is not tied to one instrument. One consistent model handles both array and sequencing input, so a laboratory can add or change technology without changing classifier and without re-validating against a separate model.
Methylation arrays
- Illumina Infinium MethylationEPIC v2
- Illumina Infinium MethylationEPIC v1
- Illumina HumanMethylation450 (450k)
Upload unprocessed IDAT files and the sample is classified automatically.
Sequencing
- Nanopore whole-genome sequencing
- Nanopore adaptive sampling
- Rapid-CNS²
- Whole-genome bisulfite sequencing (WGBS)
- EM-seq
- TAPS+
- Illumina 5-base
- biomodal 6-base
- Targeted methylation panels
Sequencing-derived methylation data is classified with the same model, with no ad-hoc per-platform variant.
Key publications
The science behind the classifier
Nature · 2018
Capper et al. DNA methylation-based classification of central nervous system tumours
The first demonstration that methylation profiling can classify CNS tumours, and the foundation this classifier is built on. The approach now informs guidance from the WHO, EANO and NCCN.
Cancer Cell · 2026
Sill et al. Advancing CNS tumour diagnostics with expanded DNA methylation-based classification
Describes the expanded reference cohort and class structure underlying version 12.8.
Nature Medicine · 2025
Patel et al. Prospective, multicentre validation of platform-agnostic methylation classification
The approach behind MNP-flex. Demonstrates that a single classifier delivers consistent results across diverse sequencing data as well as arrays, with molecular classification and copy number returned intraoperatively and validated across 301 samples.
Access and licensing
Two ways to use the CNS classifier
The classifier is available for research use on our RUO platform at app.epignostix.com, free for academic research and scientific use. Register there and log in once your account is approved.
For routine diagnostic use, the on-premise version is licensed for local installation: fully offline, with installation and validation support and complete documentation. Contact licensing@epignostix.com.
