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Benchmarking whole exome sequencing in the German network for personalized medicine

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Item Type:Article
Title:Benchmarking whole exome sequencing in the German network for personalized medicine
Creators Name:Menzel, M., Martis-Thiele, M., Goldschmid, H., Ott, A., Romanovsky, E., Siemanowski-Hrach, J., Seillier, L., Brüchle, N.O., Maurer, A., Lehmann, K.V., Begemann, M., Elbracht, M., Meyer, R., Dintner, S., Claus, R., Meier-Kolthoff, J.P, Blanc, E., Möbs, M., Joosten, M., Benary, M., Basitta, P., Hölscher, F., Tischler, V., Groß, T., Kutz, O., Prause, R., William, D., Horny, Kai, Goering, W., Sivalingam, S., Borkhardt, A., Blank, C., Junk, S.V., Yasin, L., Moskalev, E.A., Carta, M.G., Ferrazzi, F., Tögel, L., Wolter, S., Adam, E., Matysiak, U., Rosenthal, T., Dönitz, J., Lehmann, U., Schmidt, G., Bartels, S., Hofmann, W., Hirsch, S., Dikow, N., Göbel, K., Banan, R., Hamelmann, S., Fink, A., Ball, M., Neumann, O., Rehker, J., Kloth, M., Murtagh, J., Hartmann, N., Jurmeister, P., Mock, A., Kumbrink, J., Jung, A., Mayr, E.M., Jacob, A., Trautmann, M., Kirmse, S., Falkenberg, K., Ruckert, C., Hirsch, D., Immel, A., Dietmaier, W., Haack, T., Marienfeld, R., Fürstberger, A., Niewöhner, J., Gerstenmaier, U., Eberhardt, T., Greif, P.A., Appenzeller, S., Maurus, K., Doll, J., Jelting, Y., Jonigk, D., Märkl, B., Beule, D., Horst, D., Wulf, A.L., Aust, D., Werner, M., Reuter-Jessen, K., Ströbel, P., Auber, B., Sahm, F., Merkelbach-Bruse, S., Siebolts, U., Roth, W., Lassmann, S., Klauschen, F., Gaisa, N.T., Weichert, W., Evert, M., Armeanu-Ebinger, S., Ossowski, S., Schroeder, C., Schaaf, C.P., Malek, N., Schirmacher, P., Kazdal, D., Pfarr, N., Budczies, J. and Stenzinger, A.
Abstract: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. Somatic and germline variants, copy-number alterations (CNAs), and complex biomarkers were investigated. Somatic variant calling was performed in 494 diagnostically relevant cancer genes. The raw data were collected and 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 % while the positive predictive value (PPV) was 89 % in relation to 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 the clinically relevant variants. CNA calls were concordant for 82 % of genomic regions. Homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI) status were concordant for 94 %, 93 %, and 93 % of calls, respectively. Variability of CNAs and complex biomarkers did not decrease considerably after harmonization of the bioinformatic processing and was hence attributed mainly to wet-lab differences. CONCLUSION: Continuous optimization of bioinformatic workflows and participating in round robin tests are recommended.
Keywords:Whole Exome Sequencing, Molecular Pathology, Multi-Centric Inter-Laboratory Test, Clinical Exome, Precision Oncology
Source:European Journal of Cancer
ISSN:0959-8049
Publisher:Elsevier
Volume:211
Page Range:114306
Date:November 2024
Official Publication:https://doi.org/10.1016/j.ejca.2024.114306
PubMed:View item in PubMed

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