Variant classification in precision oncology

Jonas Leichsenring, Peter Horak, Simon Kreutzfeldt, Christoph Heining, Petros Christopoulos, Anna Lena Volckmar, Olaf Neumann, Martina Kirchner, Carolin Ploeger, Jan Budczies, Christoph E. Heilig, Barbara Hutter, Martina Fröhlich, Sebastian Uhrig, Daniel Kazdal, Michael Allgäuer, Alexander Harms, Eugen Rempel, Ulrich Lehmann, Michael ThomasNicole Pfarr, Ninel Azoitei, Irina Bonzheim, Ralf Marienfeld, Peter Möller, Martin Werner, Falko Fend, Melanie Boerries, Nikolas von Bubnoff, Silke Lassmann, Thomas Longerich, Michael Bitzer, Thomas Seufferlein, Nisar Malek, Wilko Weichert, Peter Schirmacher, Roland Penzel, Volker Endris, Benedikt Brors, Frederick Klauschen, Hanno Glimm, Stefan Fröhling, Albrecht Stenzinger*

*Corresponding author for this work
24 Citations (Scopus)


Next-generation sequencing has become a cornerstone of therapy guidance in cancer precision medicine and an indispensable research tool in translational oncology. Its rapidly increasing use during the last decade has expanded the options for targeted tumor therapies, and molecular tumor boards have grown accordingly. However, with increasing detection of genetic alterations, their interpretation has become more complex and error-prone, potentially introducing biases and reducing benefits in clinical practice. To facilitate interdisciplinary discussions of genetic alterations for treatment stratification between pathologists, oncologists, bioinformaticians, genetic counselors and medical scientists in specialized molecular tumor boards, several systems for the classification of variants detected by large-scale sequencing have been proposed. We review three recent and commonly applied classifications and discuss their individual strengths and weaknesses. Comparison of the classifications underlines the need for a clinically useful and universally applicable variant reporting system, which will be instrumental for efficient decision making based on sequencing analysis in oncology. Integrating these data, we propose a generalizable classification concept featuring a conservative and a more progressive scheme, which can be readily applied in a clinical setting.

Original languageEnglish
JournalInternational Journal of Cancer
Issue number11
Pages (from-to)2996-3010
Number of pages15
Publication statusPublished - 01.12.2019


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