Molecular Classification of Central Nervous System Tumors in Developing Countries. - Fernandes, Igor Lima; Abdullaev, Zied; Quezado, Martha; Aldape, Kenneth; Bacchi, Carlos E. (Archives of Pathology & Laboratory Medicine, 2026)
Context.--In the past decade, central nervous system (CNS) tumor diagnosis has shifted toward molecular classification. Tools like DNA/RNA sequencing and methylation array analysis are now supportive tools, as reflected in the World Health Organization Classification of Tumours of the Central Nervous System, 5th edition. However, implementing these sophisticated and costly methods remains challenging for health care services in most developing countries. Objective.--To report the implementation and utility of methylation array-based classification in CNS tumor cases at a Brazilian pathology reference laboratory, and to explore practical challenges and opportunities for achieving diagnostic precision in resource-constrained environments. Design.--This study analyzed 319 CNS tumor cases that underwent methylation analysis. Cases were stratified into 6 categories: (1) Methylation Confirms or Narrows Initial Diagnosis; (2) Diagnosis Modified by Methylation; (3) Diagnosis Confirmed With Molecular Subclassification; (4) Specification of Initially Descriptive Diagnosis; (5) Emerging Entities; and (6) Unclassified/Inconclusive. We analyzed diagnostic impact, costs, and turnaround time. Results.--DNA methylation profiling was successfully completed in most cases, with preanalytical failures mainly due to insufficient DNA quantity or quality. Turnaround time varied with regional logistics. Classifier outputs yielded confident matches for most cases. However, 47 cases (14.7% of cohort) produced "no match" results due to low confidence scores (≤0.30) or divergent classifier outputs. Additional testing was performed when available. Conclusions.--DNA methylation profiling improves diagnostic accuracy and reclassifies a meaningful proportion of brain tumor cases. Broad implementation requires evidence of cost-effectiveness, streamlined workflows, and capacity building, particularly in low- and middle-income settings.