Institution: | 1. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany;2. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
German Cancer Research Center (DKFZ), Heidelberg, Germany;3. Institute of Pathology, Technical University of Munich, Munich, Germany
German Cancer Consortium (DKTK), Munich partner site, Germany;4. German Cancer Research Center (DKFZ), Heidelberg, Germany
National Center for Tumor Diseases (NCT) Dresden, Dresden, Germany;5. German Cancer Research Center (DKFZ), Heidelberg, Germany;6. Department of Thoracic Surgery, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany;7. Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany
Department of Pneumology and Critical Care Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany;8. Translational Lung Research Center Heidelberg (TLRC-H), Heidelberg, Germany
Department of Thoracic Oncology, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany;9. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
German Cancer Consortium (DKTK), Heidelberg partner site, Germany |
Abstract: | Assessment of Tumor Mutational Burden (TMB) for response stratification of cancer patients treated with immune checkpoint inhibitors is emerging as a new biomarker. Commonly defined as the total number of exonic somatic mutations, TMB approximates the amount of neoantigens that potentially are recognized by the immune system. While whole exome sequencing (WES) is an unbiased approach to quantify TMB, implementation in diagnostics is hampered by tissue availability as well as time and cost constrains. Conversely, panel-based targeted sequencing is nowadays widely used in routine molecular diagnostics, but only very limited data are available on its performance for TMB estimation. Here, we evaluated three commercially available larger gene panels with covered genomic regions of 0.39 Megabase pairs (Mbp), 0.53 Mbp and 1.7 Mbp using i) in silico analysis of TCGA (The Cancer Genome Atlas) data and ii) wet-lab sequencing of a total of 92 formalin-fixed and paraffin-embedded (FFPE) cancer samples grouped in three independent cohorts (non-small cell lung cancer, NSCLC; colorectal cancer, CRC; and mixed cancer types) for which matching WES data were available. We observed a strong correlation of the panel data with WES mutation counts especially for the gene panel >1Mbp. Sensitivity and specificity related to TMB cutpoints for checkpoint inhibitor response in NSCLC determined by wet-lab experiments well reflected the in silico data. Additionally, we highlight potential pitfalls in bioinformatics pipelines and provide recommendations for variant filtering. In summary, our study is a valuable data source for researchers working in the field of immuno-oncology as well as for diagnostic laboratories planning TMB testing. |