Methylation profiling analysis is a powerful new method of molecular analysis, that improves the classification of CNS tumors.
Perfect for classifying and analyzing benign and malignant CNS tumors including meningiomas and metastatic disease
Ideal for categorizing pediatric tumors of all types
Improved accuracy and reliability of CNS tumor classification using Bethesda classifier
Reports MGMT promoter methylation status and chromosome copy number, including 1p/19q co-deletion
Identifies key oncogene amplifications and key tumor suppressor deletions
Identifies new epigenetic subgroups of tumors
CNS cancer is the 10th leading cause of cancer-associated deaths for adults, and the leading cause in pediatric patients and young adults. The variety and complexity of histologic subtypes can lead to diagnostic errors.
A recent study of 1,602 CNS cases has demonstrated the value of DNA methylation analysis in the identification of errors in primary diagnosis and improvement of diagnostic accuracy. The benefits include increased diagnostic accuracy, improved patient management, and refinements in clinical trial design. [1]
A 2025 study published in Nature found that DNA Methylation classification provides significant added-value for CNS tumor diagnosis, particularly in pedatric cases. [2]
Protean’s methylation profiling analysis report provides the information you need in a clear and easy to understand format.
MGMT promoter methylation status
Chromosome copy number (including 1p/19q co-deletion)
Key oncogene amplifications
Key tumor suppressor deletions
Epigenetic subgroups of tumors
Methylation Profiling can be helpful for patients with:
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Helps CNS tumors meet molecular criteria for WHO 2021 CNS5 classification
Necessary for diagnosing specific methylation-defined tumor entities (e.g., H3 G34-mutant glioma, ETMR, or DGONC)
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Tumor histology is inconclusive
Conflicting interpretations among pathologists
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Pediatric tumors often have distinct methylation profiles
Essential for high-grade gliomas, medulloblastomas, and embryonal tumors
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Tumor shows atypical features not matching established WHO categories
Helpful for suspected rare tumor subtypes where traditional classification methods are insufficient, and for the discovery of new tumor entities
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Methylation profiling can help reclassify or identify new mutations, and guide further treatment
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Useful for the classification of metastatic brain tumors
Methylation profiling can also be helpful to:
Determine eligibility for clinical trials or targeted therapies
Confirm or refine a WHO CNS classification
Value of the Bethesda Classifier:
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Enhances Traditional Diagnosis: The classifier uses DNA methylation patterns to provide a molecular signature for CNS tumors, complementing traditional histopathological analysis and leading to more accurate diagnoses.
Identifies New Tumor Entities: In some instances, the classifier can identify new tumor entities or refine diagnoses by providing a more specific classification than morphology alone.
Resolves Ambiguous Cases: When traditional methods are inconclusive or lead to ambiguous diagnoses, methylation profiling can help clarify the tumor type.
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Guides Therapy Selection: The classifier's ability to provide a more refined diagnosis can influence treatment decisions, leading to more personalized and effective therapies.
Improved Treatment Plans: Studies have shown that integrating methylation profiling results can lead to significant changes in treatment decisions for a substantial proportion of patients.
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Supports Clinical Trials: The classifier's ability to identify more homogeneous tumor groups can facilitate the enrollment of appropriate patients in clinical trials, leading to more meaningful research findings.
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Growing Recognition and Use: DNA methylation profiling is increasingly recognized as a valuable diagnostic tool for CNS tumors, with ongoing efforts to expand its application.
Continued Refinement: Researchers are continuously working on improving the classifier and expanding its scope to include more tumor types and subtypes.
In Comparison with Heidelberg:
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Larger Reference Set: The Bethesda classifier is trained on a larger dataset, encompassing a broader range of tumor types and subtypes.
Hierarchical SVM Classifier: Uses a hierarchical Support Vector Machine (SVM) approach, potentially offering improved accuracy and robustness.
Active Development: The Bethesda classifier is actively developed and updated, incorporating new findings and tumor types.
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Relatively Newer: While robust, it's a relatively newer classifier compared to the Heidelberg classifier, and its long-term performance in various clinical settings is still being evaluated.
Specificity & Sensitivity for Bethesda Classifier
Ordering Process:
Complete the CNS test requisition form
Send the completed test requisition form via fax or Protean’s secure electronic portal
Ship tissue or slides with pathology report to Protean’s laboratory
Receive results within 5-10 business days
Sample Requirements:
FFPE tissue block or 20 unstained slides.
Overnight shipping required for tissue blocks.
Regular shipping for slides.
Details for slides: 5 micron thick sections, unstained & unbaked, 25 mm² (if less than this size, please provide additional slides), H&E optional
The Protean MAPS® System
Methylation Profiling is part of Protean’s full molecular analysis system for CNS tumors.
Protean MAPS® includes Methylation, pathology review, IHC, rapid IDH1/2 mutation testing, NGS profiling and complex fusion analysis
Order Methylation Testing
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Sources
[1] Clinical utility of whole-genome DNA methylation profiling as a primary molecular diagnostic assay for central nervous system tumors—A prospective study and guidelines for clinical testing
Neuro-Oncology Advances, Volume 5, Issue 1, January-December 2023, vdad076, Publication Date June 26 2023 https://doi.org/10.1093/noajnl/vdad076
[2] Diagnostic impact of DNA methylation classification in adult and pediatric CNS tumors
Nature, Scientific Reports volume 15, Article number: 2857 (2025) https://www.nature.com/articles/s41598-025-87079-4
[3] DNA methylation profiling as a model for discovery and precision diagnostics in neuro-oncology
Neuro-oncology, 2021 November 2 https://read.qxmd.com/read/34725697/dna-methylation-profiling-as-a-model-for-discovery-and-precision-diagnostics-in-neuro-oncology
[4] DNA Methylation Profiling: An Emerging Paradigm for Cancer Diagnosis
Annual Review of Pathology: Mechanisms of Disease Vol. 17:295-321 (Volume publication date January 2022) https://doi.org/10.1146/annurev-pathol-042220-022304
Academic Papers
Wang, J.Z., Patil, V., Landry, A.P. et al. Molecular classification to refine surgical and radiotherapeutic decision-making in meningioma. Nat Med (2024). https://doi.org/10.1038/s41591-024-03167-4
Sievers, P., Bielle, F., Göbel, K. et al. Identification of a putative molecular subtype of adult-type diffuse astrocytoma with recurrent MAPK pathway alterations. Acta Neuropathol 148, 7 (2024). https://doi.org/10.1007/s00401-024-02766-2
Manita Kanathanavanich, Shunsuke Koga, Sara Lynn Stone, Jacquelyn Roth, Zied Abdullaev, Donald M O’Rourke, Stephen Bagley, Robert M Kurtz, Michelle Alonso-Basanta, Kenneth Aldape, MacLean P Nasrallah, Guang Yang, CTDSP2::GLI1 fusion in glioblastoma: A diagnostic challenge through tumor heterogeneity, Journal of Neuropathology & Experimental Neurology, 2024;, nlae073, https://academic.oup.com/jnen/article-abstract/83/12/1076/7710048
Yeo, K. K., Macrae, C. B., Gampel, B., Ahrendsen, J. T., Lidov, H., Wright, K. D., Chi, S., Fehnel, K., Baird, L., Clymer, J., Aldape, K., & Alexandrescu, S. (2024). Clinical utility of DNA methylation profiling for choroid plexus tumors. Neuro-oncology advances, 6(1), vdae097. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11221062/
Briceno, N., Vera, E., Komlodi-Pasztor, E., Abdullaev, Z., Choi, A., Grajkowska, E., Kunst, T., Levine, J., Lindsley, M., Fernandez, K., Reyes, J., Boris, L., Burton, E., Panzer, M., Polskin, L., Penas-Prado, M., Pillai, T., Theeler, B. J., Wu, J., Wall, K., … Gilbert, M. R. (2024). Long-term survivors of glioblastoma: Tumor molecular, clinical, and imaging findings. Neuro-oncology advances, 6(1), vdae019. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10901543/
van der Meulen, M., Ramos, R. C., Voisin, M. R., Patil, V., Wei, Q., Singh, O., Climans, S. A., Kalidindi, N., Or, R., Aldape, K., Diamandis, P., Munoz, D. G., Zadeh, G., & Mason, W. P. (2024). Differences in methylation profiles between long-term survivors and short-term survivors of IDH-wild-type glioblastoma. Neuro-oncology advances, 6(1), vdae001. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10838123/
Himstead, A. S., Perez-Rosendahl, M., Fote, G. M., Zhang, A., Kim, M. G., Floriolli, D., Quezado, M., Aldape, K., Pratt, D., Abdullaev, Z., Monuki, E. S., Hsu, F. P. K., & Yong, W. H. (2022). Pigmented ependymoma, a tumor with predilection for the middle-aged adult: case report with methylation classification and review of 16 literature cases. Free neuropathology, 3, 3-16. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240947/
