Practical implementation of DNA methylation and copy-number-based CNS tumor diagnostics: the Heidelberg experience.

Capper D1,2,3,4, Stichel D5,6, Sahm F5,6, Jones DTW7,8, Schrimpf D5,6, Sill M7,9, Schmid S10, Hovestadt V11,12, Reuss DE5,6, Koelsche C5,6,13, Reinhardt A5,6, Wefers AK5,6, Huang K5,6, Sievers P5,6, Ebrahimi A5,6, Schöler A10,14, Teichmann D10, Koch A10, Hänggi D15, Unterberg A16, Platten M17,18, Wick W19,20, Witt O7,21,22, Milde T7,21,22, Korshunov A5,6, Pfister SM7,9,21, von Deimling A23,24.

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Abstract

Recently, we described a machine learning approach for classification of central nervous system tumors based on the analysis of genome-wide DNA methylation patterns [6]. Here, we report on DNA methylation-based central nervous system (CNS) tumor diagnostics conducted in our institution between the years 2015 and 2018. In this period, more than 1000 tumors from the neurosurgical departments in Heidelberg and Mannheim and more than 1000 tumors referred from external institutions were subjected to DNA methylation analysis for diagnostic purposes. We describe our current approach to the integrated diagnosis of CNS tumors with a focus on constellations with conflicts between morphological and molecular genetic findings. We further describe the benefit of integrating DNA copy-number alterations into diagnostic considerations and provide a catalog of copy-number changes for individual DNA methylation classes. We also point to several pitfalls accompanying the diagnostic implementation of DNA methylation profiling and give practical suggestions for recurring diagnostic scenarios.