Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non–small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial.

The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti–PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff.

In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab.

Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy.