Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

• DOI: 10.1016/j.annonc.2021.09.016
• Publication Date: 2021-10-01T10:18:11Z
• Authors: D.M. Vega; L.M. Yee; L.M. McShane; P.M. Williams; L. Chen; T. Vilimas; D. Fabrizio; V. Funari; J. Newberg; L.K. Bruce; S.-J. Chen; J. Baden; J. Carl Barrett; P. Beer; M. Butler; J.-H. Cheng; J. Conroy; D. Cyanam; K. Eyring; E. Garcia; G. Green; V.R. Gregersen; M.D. Hellmann; L.A. Keefer; L. Lasiter; A.J. Lazar; M.-C. Li; L.E. MacConaill; K. Meier; H. Mellert; S. Pabla; A. Pallavajjalla; G. Pestano; R. Salgado; R. Samara; E.S. Sokol; P. Stafford; J. Budczies; A. Stenzinger; W. Tom; K.C. Valkenburg; X.Z. Wang; V. Weigman; M. Xie; Q. Xie; A. Zehir; C. Zhao; Y. Zhao; M.D. Stewart; J. Allen
• Keywords: Harmonization

•Estimation of TMB varies across different panels, with panel size, gene content and bioinformatics pipelines contributing to empirical variability.•Panel sizes greater than 667Kb are necessary maintain adequate PPA NPA for calling high versus low the range cutoffs used in practice.•Statistical calibration can achieve more consistent results panels allows comparison values various assays. BackgroundTumor mutational burden (TMB) measurements aid identifying patients who likely benefit from immunotherapy; however, there is variability assays factors this have not been comprehensively investigated. Identifying sources help facilitate comparability assays, which may broader adoption development clinical applications.Materials methodsTwenty-nine tumor samples 10 human-derived cell lines were processed distributed 16 laboratories; each their own calculate compare whole exome results. Additionally, theoretical positive percent agreement (PPA) negative (NPA) estimated. The impact filtering pathogenic germline variants on estimates was assessed. Calibration curves specific assay developed translation sequencing (WES) values.ResultsPanel >667 Kb cut-offs practice. Failure filter out when estimating resulted overestimating relative WES all Filtering potential at >0% population minor allele frequency strongest correlation TMB. Application a approach derived Cancer Genome Atlas data, tailored assay, reduced spread around as reflected lower root mean squared error (RMSE) 26/29 (90%) samples.ConclusionsEstimation content, variability. Statistical To promote reproducibility software tool made publicly available. Tumor applications. Twenty-nine values. Panel samples. Estimation