Spatial and Temporal Heterogeneity of Panel-Based Tumor Mutational Burden in Pulmonary Adenocarcinoma: Separating Biology From Technical Artifacts.

医学 计算生物学 肿瘤异质性 癌症研究
作者
Daniel Kazdal,Volker Endris,Michael Allgäuer,Mark Kriegsmann,Jonas Leichsenring,Anna-Lena Volckmar,Alexander Harms,Martina Kirchner,Katharina Kriegsmann,Olaf Neumann,Regine Brandt,Suranand Babu Talla,Eugen Rempel,Carolin Ploeger,Moritz von Winterfeld,Petros Christopoulos,Diana M. Merino,Mark Stewart,Jeff Allen,Helge Bischoff,Michael Meister,Thomas Muley,Felix J.F. Herth,Roland Penzel,Arne Warth,Hauke Winter,Stefan Fröhling,Solange Peters,Charles Swanton,Michael Thomas,Peter Schirmacher,Jan Budczies,Albrecht Stenzinger
出处
期刊:Journal of Thoracic Oncology [Elsevier]
卷期号:14 (11): 1935-1947 被引量:35
标识
DOI:10.1016/j.jtho.2019.07.006
摘要

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.
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