Tumor mutational burden (TMB), defi ned as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the effi cacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMBhigh tumor subgroup. Unmet needs include prospective validation of TMB cutoffs in relationship to tumor type and patient outcomes. Furthermore, standardization and harmonization of TMB measurement across test platforms are important to the successful implementation of TMB in clinical practice.Signifi cance: Evaluation of TMB as a predictive biomarker creates the need to harmonize panel-based TMB estimation and standardize its reporting. TMB can improve the predictive accuracy for immunotherapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors. Responses were observed across tumor types, and microsatellite instability-high (MSI-H) status did not account for all of the increased clinical benefi t in the TMB-high subgroup ( 24 ).On the basis of these data, the FDA approved pembrolizumab monotherapy for the subgroup of solid-tumor patients with TMB ≥10 mut/Mb who are treatment-refractory and lack satisfactory alternative treatment options. Although data from KEYNOTE-158 demonstrated a role for TMB in selection of patients for cancer treatment, important issues remain,
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