Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Abstract

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

Tumor Mutational Burden Determined by Panel Sequencing Predicts Survival After Immunotherapy in Patients With Advanced Gastric Cancer

“…In a previous study on patients with metastatic gastric cancer treated with pembrolizumab, circulating tumor DNA mutation load was slightly, albeit not significantly correlated with objective response and predicted PFS (12). Like PD-L1 expression, the thresholds to define high TMB vary depending on the technique used and tumor type (13,24). Factors that influence TMB include tumor type, pre-analytic variables, the method used (whole exome vs. panel sequencing), and bioinformatics (20,24).…”

“…Although several studies evaluated TMB in gastric cancer, most studies proposed cut-off points for TMB and their relevance to survival (21)(22)(23), and only two studies included patients treated with ICB, in which TMB was measured by whole exome sequencing (18) and custom-designed large-sized panels (14). Moreover, despite efforts to standardize the TMB from multiple different genomic profiling panels (24), the cutoff value for TMB is not consistent and the associations with other biomarkers have not been fully defined in gastric cancer. For the use in daily clinical practice, a smaller and standardized panel should be developed and needs to be validated in clinical trials (17).…”

Molecular profiling for precision cancer therapies

“…TMB can be assessed either on tumor samples or using ctDNA from blood samples [130,131]. However, the cutoff values and the size and content of the genomic footprint required for TMB analysis are still not clear [132], and harmonization initiatives are underway to standardize the approach to interpreting tumor mutation for therapeutic uses (e.g., Friends of Cancer TMB initiative Quality Assurance Initiative Pathology) [133]. TMB is not predictive of response to anti-PD-1/PD-L1 agents across all cancers, as a few tumor types, such as Merkel cell carcinomas, are quite responsive to IO agents despite having a relatively low TMB [134,135].…”

Prevalence and mutational determinants of high tumor mutation burden in breast cancer

“…[25][26][27] There are multiple ongoing initiatives to standardize TMB assessment, and further work is necessary to establish the best cutoff for using TMB as a predictive biomarker of response to immunotherapy. 49,50…”