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Updated: Dec 27, 2025
Comparative Lesions Analysis Through a Targeted Sequencing Approach
Published on: November 5, 2019
Impact of panel design and cut-off on tumour mutational burden assessment in metastatic solid tumour samples
Joanne M Mankor1, Marthe S Paats2, Floris H Groenendijk3
1Department of Pulmonary Medicine, Erasmus MC, Rotterdam, The Netherlands.
Abstract:
Tumour mutational burden (TMB) has emerged as a promising biomarker to predict immune checkpoint inhibitors (ICIs) response in advanced solid cancers. However, harmonisation of TMB reporting by targeted gene panels is lacking, especially in metastatic tumour samples. To address this issue, we used data of 2841 whole-genome sequenced metastatic cancer biopsies to perform an in silico analysis of TMB determined by seven gene panels (FD1CDx, MSK-IMPACT™, Caris Molecular Intelligence, Tempus xT, Oncomine Tumour Mutation Load, NeoTYPE Discovery Profile and CANCERPLEX) compared to exome-based TMB as a golden standard. Misclassification rates declined from up to 30% to <1% when the cut-point for high TMB was increased. Receiver operating characteristic analysis demonstrated that, for correct classification, the cut-point for each gene panel may vary more than 20%. In conclusion, we here demonstrate that a major limitation for the use of gene panels is inter-assay variation and the need for dynamic thresholds to compare TMB outcomes.
Insights
Tumour mutational burden (TMB) is key for predicting response to immune checkpoint inhibitors (ICIs). Harmonizing TMB reporting across gene panels is crucial, as inter-assay variations necessitate dynamic thresholds for accurate classification.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Tumour mutational burden (TMB) is a predictive biomarker for immune checkpoint inhibitors (ICIs) in advanced cancers.
- Standardization of TMB reporting using targeted gene panels is lacking, particularly for metastatic samples.
Purpose of the Study:
- To evaluate the harmonization of TMB reporting across seven distinct gene panels.
- To compare in silico TMB results from gene panels against whole-genome sequencing (WGS) data as a gold standard.
Main Methods:
- In silico analysis of 2841 whole-genome sequenced metastatic cancer biopsies.
- Comparison of TMB values derived from seven commercial gene panels against exome-based TMB.
- Assessment of misclassification rates and use of receiver operating characteristic (ROC) analysis.
Main Results:
- Misclassification rates of high TMB decreased from 30% to under 1% with adjusted cut-points.
- Optimal cut-points for accurate classification varied by over 20% among different gene panels.
- Significant inter-assay variation was observed in TMB reporting.
Conclusions:
- Inter-assay variation among gene panels is a major limitation for TMB assessment.
- Dynamic, panel-specific thresholds are necessary for reliable comparison of TMB outcomes.
- Standardization efforts are needed to improve TMB's utility as a predictive biomarker.
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