Publications
ESMO OpenOct 2024 |
9
103870
DOI:
10.1016/j.esmoop.2024.103870

131P Benchmarking whole exome sequencing in the German network for personalized medicine

Menzel, M.; Martis-Thiele, M.; Goldschmid, H.; Ott, A.; Romanovsky, E.; Siemanowski-Hrach, J.; Seillier, L.; Brüchle, N. Ortiz; Maurer, A.; Lehmann, K-V.; Ossowski, S.; Schroeder, C.; Schaaf, C.; Malek, N.; Schirmacher, P.; Kazdal, D.; Pfarr, N.; Budczies, J.; Stenzinger, A.
Product Used
NGS
Abstract
Background 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. In addition, all raw data were re-analyzed with a central bioinformatic pipeline to separate wet- and dry-lab variability. Results The positive percentage agreement (PPA) of somatic variant calling was 76% of variants compared to a five-center consensus calling. Variant filtering was identified as the main cause for divergent variant calls. Adjusting filter criteria and re-analysis increased the PPA to 98%. Copy-number alteration (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. Agreement of CNAs and complex biomarkers did not increase considerably using the central pipeline and the origin of variability was hence attributed to wet-lab differences. Conclusions In conclusion, continuous optimization of bioinformatic workflows and participating in round robin tests are recommend.
Product Used
NGS

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