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

David Capper(Heidelberg University), Damian Stichel(Heidelberg University), Felix Sahm(Heidelberg University), David Jones(National Center for Tumor Diseases), Daniel Schrimpf(Heidelberg University), Martin Sill(National Center for Tumor Diseases), Simone Schmid(Charité - Universitätsmedizin Berlin), Volker Hovestadt(Center for Cancer Research), David Reuß(University Hospital Heidelberg), Christian Koelsche(University Hospital Heidelberg), Annekathrin Reinhardt(University Hospital Heidelberg), Annika K. Wefers(German Cancer Research Center), Kristin Huang(Heidelberg University), Philipp Sievers(Heidelberg University), Azadeh Ebrahimi(Heidelberg University), Anne Schöler(Humboldt-Universität zu Berlin), Daniel Teichmann(Freie Universität Berlin), Arend Koch(Humboldt-Universität zu Berlin), Daniel Hänggi(University Hospital Heidelberg), Andreas Unterberg(University Hospital Heidelberg), Michael Platten(University Hospital Heidelberg), Wolfgang Wick(Heidelberg University), Olaf Witt(German Cancer Research Center), Till Milde(Hopp Children's Cancer Center Heidelberg), Andrey Korshunov(German Cancer Research Center), Stefan M. Pfister(Heidelberg University), Andreas von Deimling(Heidelberg University)
Acta Neuropathologica
July 2, 2018
Cited by 587Open Access
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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.


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