Daniel Kazdal1, Volker Endris2, Michael Allgäuer2, Mark Kriegsmann2, Jonas Leichsenring2, Anna-Lena Volckmar2, Alexander Harms1, Martina Kirchner2, Katharina Kriegsmann3, Olaf Neumann2, Regine Brandt2, Suranand B Talla2, Eugen Rempel2, Carolin Ploeger2, Moritz von Winterfeld2, Petros Christopoulos4, Diana M Merino5, Mark Stewart5, Jeff Allen5, Helge Bischoff4, Michael Meister6, Thomas Muley7, Felix Herth8, Roland Penzel2, Arne Warth9, Hauke Winter10, Stefan Fröhling11, Solange Peters12, Charles Swanton13, Michael Thomas4, Peter Schirmacher14, Jan Budczies2, Albrecht Stenzinger15. 1. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany. 2. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany. 3. Department of Hematology, Oncology and Rheumatology, University Hospital Heidelberg, Heidelberg, Germany. 4. Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany; Department of Thoracic Oncology, Thoraxklinik at the University Hospital Heidelberg, Heidelberg, Germany. 5. Friends of Cancer Research, Washington, DC. 6. Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany; Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany. 7. Translational Research Unit, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany. 8. Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany; Department of Pneumonology and Critical Care Medicine, Thoraxklinik at the University Hospital Heidelberg, Germany. 9. Institute of Pathology, Cytopathology, and Molecular Pathology UEGP MVZ Giessen/ Wetzlar/Limburg, Germany. 10. Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany; Department of Thoracic Surgery, Thoraxklinik at the University Hospital Heidelberg, Heidelberg, Germany. 11. Department of Translational Medical Oncology, National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), Partner Site, Heidelberg, Germany. 12. Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV) and Lausanne University, Lausanne, Switzerland. 13. Cancer Evolution and Genome Instability Translational Cancer Therapeutics Laboratory, Francis Crick Institute, London, United Kingdom. 14. Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany; German Cancer Consortium (DKTK), Partner Site, Heidelberg, Germany. 15. Translational Lung Research Center (TLRC) Heidelberg, German Center for Lung Research (DZL), Heidelberg, Germany; German Cancer Consortium (DKTK), Partner Site, Heidelberg, Germany. Electronic address: albrecht.stenzinger@med.uni-heidelberg.de.
Abstract
BACKGROUND: Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. METHODS: TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. RESULTS: On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. CONCLUSIONS: Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context.
BACKGROUND:Tumor mutational burden (TMB) is an emerging biomarker used to identify patients who are more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables such as tumor cell content and intratumor heterogeneity may play an important role in determining TMB. METHODS:TMB estimates were determined applying the TruSight Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multiregion sequencing (two to six samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in five patients. RESULTS: On average, a coding region of 1.28 Mbp was covered with a mean read depth of 609x. Manual validation of the mutation-calls confirmed a good performance, but revealed noticeable misclassification during germline filtering. Different regions within a tumor showed considerable spatial TMB variance in 30% (7 of 24) of the cases (maximum difference, 14.13 mut/Mbp). Lymph node-derived TMB was significantly lower (p = 0.016). In 13 cases, distinct mutational profiles were exclusive to different regions of a tumor, leading to higher values for simulated aggregated TMB. Combined, intratumor heterogeneity and the aggregated TMB could result in divergent TMB designation in 17% of the analyzed patients. TMB variation between primary tumor and distant metastases existed but was not profound. CONCLUSIONS: Our data show that, in addition to technical aspects such as germline filtering, the tumor content and spatially divergent mutational profiles within a tumor are relevant factors influencing TMB estimation, revealing limitations of single-sample-based TMB estimations in a clinical context.
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Authors: Katharina Kriegsmann; Christiane Zgorzelski; Thomas Muley; Petros Christopoulos; Michael Thomas; Hauke Winter; Martin Eichhorn; Florian Eichhorn; Moritz von Winterfeld; Esther Herpel; Benjamin Goeppert; Albrecht Stenzinger; Felix J F Herth; Arne Warth; Mark Kriegsmann Journal: BMC Cancer Date: 2021-05-01 Impact factor: 4.430