Benchmarking whole exome sequencing in the German Network for Personalized Medicine

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 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