Results of a study, published in Annals of Oncology, demonstrated that the level of imprecision in the assessment of tumor mutational burden (TMB) increases as the number of genes sequenced in a targeted exome sequencing panel decreases.1,2
Emerging biomarkers of response to immune checkpoint inhibitor therapy include level of expression of programmed cell death-ligand 1 (PD-L1), level of microsatellite instability (MSI), and TMB level in tumor, with a status of “high” for each of these biomarkers associated with increased treatment response.
While whole-exome sequencing has been considered the “gold-standard” for assessment of tumor TMB, targeted exome sequencing panels that “extrapolate the total number of mutations in the coding sequence by analysis of a limited sequence” are typically used in clinical practice. Given that these targeted exome sequencing panels cover less than 5% of the coding sequence, their usefulness in the evaluation of TMB as a criterion for patient selection for immune checkpoint inhibitor therapy and enrollment in clinical trials has been debated.
As part of this study, a mathematical model of the coefficient of variation (CV), an assessment of the extent of variability in the data, was determined for tumor TMB as a function of gene panel size and the number of identified mutations. The study authors showed that the CV was inversely proportional to both the square root of the panel size and the square root of the TMB level. In other words, the larger the panel size and the greater the likelihood of a high TMB, the more precise the assessment of TMB.
For example, in the case of a tumor with 10 mutations/Mbp, the CV was determined to be 69% and 27% when the targeted exome sequencing panel size was 0.21 Mbp and 1.37 Mbp, respectively.
“The inherent imprecision of TMB estimates drastically increases for panel sizes <1 Mbp,” the study authors noted.
Furthermore, this mathematical relationship between CV in TMB and panel size and number of mutations remained valid when real-world whole-exome sequencing data from the Cancer Genome Atlas (TCGA) Pan-Cancer cohort was used to simulate results from 5 commercially-available targeted exome sequencing panels.
Interestingly, CV was 17% to 28% higher when evaluated in the real-world setting compared with the mathematical model. Also shown was that CV in TMB increased with increasing tumor heterogeneity.
While a bimodal distribution in TMB has been observed in certain cancers, such as colorectal cancer, endometrial cancer, and gastric cancers, the study author noted that “for most of the other cancer types including lung adenocarcinoma, lung squamous cell carcinoma and cutaneous melanoma, TMB is unimodally distributed with a dense point cloud of TMB scores scattering around the cut-point [separating TMB-low from TMB-high tumors]. For accurate classification of these tumors, TMB scores need to be determined by gene panels of a considerable size to obtain reliable results, ie with an acceptable CV.”
To partially account for the imprecision of TMB estimates using targeted exome sequencing panels, and to provide a better assessment of the likelihood of patient response to an immune checkpoint inhibitor therapy, the study authors proposed the introduction of a 3-tier TMB classification scheme which would include a “gray zone,” corresponding to an inability make a clinically meaningful assignment based on a single high/low TMB cut-point.
This 3-tier TMB classification scheme “would provide a safety margin in which clinicians could weigh in additional factors to their decision making (ie, comorbidities, other treatment options) [for those assigned to the gray zone],” the study authors opined.
- Budczies J, Allgäuer M, Litchfield K, et al. Optimizing panel-based tumor mutational burden (TMB) measurement [published online July 3, 2019]. Ann Oncol. doi: 10.1093/annonc/mdz205
- Yang W, Morris LGT, Chan TA. Panel-based estimates of tumor mutational burden: characterizing unknown unknowns [published online August 13, 2019]. Ann Oncol. doi: 10.1093/annonc/mdz234