Application of molecular classification of central nervous system tumors using DNA methylation profiling: A single-center experience

Abstract

Molecular classification using DNA methylation profiling had a great impact on the diagnosis and classification of central nervous system (CNS) tumors; however, nationwide data remain limited. Methods: We uploaded IDAT files from archived samples from the Illumina Infinium Human MethylationEPIC BeadChip array at our institution to the methylation classifier on the webpage of the German Cancer Center to obtain the molecular classification and copy number plot. Results: Sixty-one samples from 53 patients were collected. Twenty-eight samples (46%) showed calibrated scores of ≥0.9. Among them, one case suggested a diagnostic change (level of usefulness A), four were diagnosed according to the revised WHO classification (level of usefulness B), 18 obtained prognostic information from molecular classification or copy number analysis (level of usefulness C), and five supported a pathological diagnosis (level of usefulness D). Thirteen cases with calibrated scores <0.9 but ≥0.5 presented a level of usefulness of A in one case, B in one case, C in five cases, and D in six cases. Multivariate analysis showed a statistical significance in the diagnosis of medulloblastomas with a higher calibrated score (odds ratio; 12.56, p=0.004). Conclusion: Methylation classifiers can support pathological diagnosis, thereby providing additional valuable information for predicting the prognosis of childhood CNS tumors. In Japan, prospective clinical studies are underway.