Spatial and temporal heterogeneity of panel-based tumor mutational burden in pulmonary adenocarcinoma: separating biology from technical artifacts
Authors listDaniel Kazdal Volker Endris Michael Allgäuer Mark Kriegsmann Jonas Leichsenring Anna-Lena Volckmar Alexander Harms Martina Kirchner Katharina Kriegsmann Olaf Neumann Regine Brandt Suranand B Talla Eugen Rempel Carolin Ploeger Moritz von Winterfeld Petros Christopoulos Diana M Merino Mark Stewart Jeff Allen Helge Bischoff Michael Meister Thomas Muley Felix Herth Roland Penzel Arne Warth Hauke Winter Stefan Fröhling Solange Peters Charles Swanton Michael Thomas Peter Schirmacher Jan Budczies Albrecht Stenzinger
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INTRODUCTION: Tumor mutational burden (TMB) is an emerging biomarker used to identify patients more likely to benefit from immuno-oncology therapy. Aside from various unsettled technical aspects, biological variables like tumor cell content and intratumor heterogeneity (ITH) may play an important role in determining TMB. METHODS: TMB estimates were determined applying the TruSightTM Oncology 500 targeted sequencing panel. Spatial and temporal heterogeneity was analyzed by multi-region sequencing (2-6 samples) of 24 pulmonary adenocarcinomas and by sequencing a set of matched primary tumors, locoregional lymph node metastases, and distant metastases in 5 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% (7/24) of the cases (max 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, ITH 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 demonstrate that, in addition to technical aspects like 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.
Journal Journal of Thoracic Oncology
Issue number 11