Medgenome’s CNS Tumour Methylation Classifier – A Breakthrough In Brain Tumour Diagnostics

Introduction

Brain tumours are known to be the trickiest to diagnose accurately – for decades now, doctors have relied on examination of the morphology of the tumour using various staining and immunohistochemical techniques. Despite years of experience, these tumours continue to defy accurate classification as distinct types appear similar under the microscope. Accurate diagnosis sheds light on the behaviour of the tumour and is vital to the patient’s treatment journey.

The development of sequencing technologies has further enabled an examination of the tumour at the genetic level, but the same problem persists. Methylation profiling of central nervous system (CNS) tumours, in conjunction with traditional immunohistochemical and genetic evaluations, forms a comprehensive test for accurate diagnostics (WHO guidelines for classification of CNS tumours 2021, 5^th ed.)¹.

What Is Methylation Profiling?

DNA methylation is an epigenetic modification, an additional layer on the base sequence that can cause the silencing or overexpression of genes, modifying their functioning irrespective of any base mutations. This pattern of methylation changes when a normal cell becomes cancerous and is specific to every tumour and reflects its origin². If we can read the pattern of methylation, we can often tell what kind of tumour it is and where it came from, even if it’s hard to tell just by looking at it under the microscope.

In methylation profiling, scientists extract DNA from a small piece of tumour tissue (often preserved in paraffin blocks from surgery). They then measure hundreds of thousands of methylation sites across the genome and compare them to a massive reference database using a classification algorithm. If the tumour’s “methylation fingerprint” matches a known tumour type, the classifier gives a score that helps pathologists confirm the diagnosis³.

Medgenome’s CNS Tumour Methylation Classification Test: Closing the Diagnostic Gap

India’s first genome-wide methylation-based classification test for CNS tumours, Medgenome’s CNS Tumour Methylation Classification test (utilising the Heidelberg Epignostix GmbH⁴ and NCI’s Bethesda v2.0⁵ classifiers), can identify the precise type and subtype of the CNS tumours.

This test can either confirm the initial diagnosis and further refine it, or provide a new diagnosis altogether. In either scenario, the clarity provided by this test can help make correct treatment decisions based on the prognosis and grade of the identified subtype.

• • Wu et.al.⁶, observed that the classifier was able to refine diagnosis in 13.3% of 1045 surgical samples and establish a new diagnosis in an additional 17.9% cases.
  • Karimi et.al.⁷, resolved uncertain diagnoses in 46% tumours using methylation profiling. As a direct consequence, 15% patients were directly impacted by avoiding unnecessary or insufficient treatment.
  • Filippidou et.al.,⁸ adapted the clinical management of 40% of children and adolescents based on the methylation results. In two patients, the change in methylation diagnosis was accompanied by the identification of ALK and NTRK biomarkers, resulting in a good response with targeted treatment.This test offers a comprehensive molecular assessment that complements histopathology and empowers clinicians with clarity in even the most ambiguous CNS tumour cases.

• Distinguishes morphologically similar tumours
• Resolves histologically inconclusive cases
• Improves tumour subtyping accuracy
• Reduces chances of overtreatment
• Identifies rare or novel tumour types
• Increases diagnostic specificity across overlapping molecular profiles
• Enables personalised treatment and precise trial matching

Conclusion: The Future of CNS Tumour Diagnosis Is Here

This test is not just a diagnostic tool—it’s a clinical advantage. It gives neurosurgeons, oncologists and pathologists the confidence to make evidence-based decisions, even in complex or ambiguous clinical presentations of CNS tumours.

References

1. https://pmc.ncbi.nlm.nih.gov/articles/PMC8328013/
2. https://pmc.ncbi.nlm.nih.gov/articles/PMC7409375/
3. https://www.nature.com/articles/nature26000
4. https://www.medrxiv.org/content/10.1101/2025.05.28.25328344v1
5. https://methylscape.ccr.cancer.gov/
6. https://pmc.ncbi.nlm.nih.gov/articles/PMC8598573/
7. https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-019-0766-2#Sec2
8. https://www.sciencedirect.com/science/article/pii/S2772610X24000588