Open Access

Michael Menzel, Mihaela Martis-Thiele, Hannah Goldschmid, Alexander Ott, Eva Romanovsky, Janna Siemanowski-Hrach, Lancelot Seillier, Nadina Ortiz Brüchle, Angela Maurer, Kjong-Van Lehmann, Matthias Begemann, Miriam Elbracht, Robert Meyer, Sebastian Dintner, Rainer Claus, Jan Meier-Kolthoff, Eric Blanc, Markus Möbs, Maria Joosten, Manuela Benary, Patrick Basitta, Florian Hölscher, Verena Tischler, Thomas Groß, Oliver Kutz, Rebecca Prause, Doreen William, Kai Horny, Wolfgang Goering, Sugirthan Sivalingam, Arndt Borkhardt, Cornelia Blank, Stefanie Junk, Layal Yasin, Evgeny A. Moskalev, Maria Giulia Carta, Fulvia Ferrazzi, Lars Tögel, Steffen Wolter, Eugen Adam, Uta Matysiak, Tessa Rosenthal, Jürgen Dönitz, Ulrich Lehmann, Gunnar Schmidt, Stephan Bartels, Winfried Hofmann, Steffen Hirsch, Nicola Dikow, Kirsten Göbel, Rouzbeh Banan, Stefan Hamelmann, Annette Fink, Markus Ball, Olaf Neumann, Jan Rehker, Michael Kloth, Justin Murtagh, Nils Hartmann, Phillip Jurmeister, Andreas Mock, Jörg Kumbrink, Andreas Jung, Eva-Maria Mayr, Anne Jacob, Marcel Trautmann, Santina Kirmse, Kim Falkenberg, Christian Ruckert, Daniela Hirsch, Alexander Immel, Wolfgang Dietmaier, Tobias Haack, Ralf Marienfeld, Axel Fürstberger, Jakob Niewöhner, Uwe Gerstenmaier, Timo Eberhardt, Phillip Greif, Silke Appenzeller, Katja Maurus, Julia Doll, Yvonne Jelting, Danny Jonigk, Bruno Märkl, Dieter Beule, David Horst, Anna-Lena Wulf, Daniela Aust, Martin Werner, Kirsten Reuter-Jessen, Philipp Ströbel, Bernd Auber, Felix Sahm, Sabine Merkelbach-Bruse, Udo Siebolts, Wilfried Roth, Silke Lassmann, Frederick Klauschen, Nadine T. Gaisa, Wilko Weichert, Matthias Evert, Sorin Armeanu-Ebinger, Stephan Ossowski, Christopher Schroeder, Christian P. Schaaf, Nisar Malek, Peter Schirmacher, Daniel Kazdal, Nicole Pfarr, Jan Budczies, Albrecht Stenzinger

• Introduction Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. Methods To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics investigating somatic and germline variants, copy-number alteration (CNA), and different complex biomarkers. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. In addition, all raw data were re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. Results The mean positive percentage agreement (PPA) of somatic variant calling was 76% and positive predictive value (PPV) 89% compared a consensus list ofIntroduction Whole Exome Sequencing (WES) has emerged as an efficient tool in clinical cancer diagnostics to broaden the scope from panel-based diagnostics to screening of all genes and enabling robust determination of complex biomarkers in a single analysis. Methods To assess concordance, six formalin-fixed paraffin-embedded (FFPE) tissue specimens and four commercial reference standards were analyzed by WES as matched tumor-normal DNA at 21 NGS centers in Germany, each employing local wet-lab and bioinformatics investigating somatic and germline variants, copy-number alteration (CNA), and different complex biomarkers. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. In addition, all raw data were re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. Results The mean positive percentage agreement (PPA) of somatic variant calling was 76% and positive predictive value (PPV) 89% compared a consensus list of variants found by at least five centers. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 88% for all and 97% for clinically relevant variants. CNA calls were concordant for 82% of genomic regions. Calls of homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94%, 93%, and 93% respectively. Variability of CNAs and complex biomarkers did not increase considerably using the central pipeline and was hence attributed to wet-lab differences. Conclusion Continuous optimization of bioinformatic workflows and participating in round robin tests are recommend.…