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Updated: May 23, 2025
Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Different NGS identification methods of somatic mutation sites in solid tumors impact TMB results
Xueshu Chen1, Haixing Chen1, Mi Liu2
1Department of Molecular Pathology Laboratory, The Affiliated Cancer Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, China.
Background:
Tumor mutation burden (TMB) is a predictive biomarker for assessing the response of various tumor types to immune checkpoint inhibitors (ICI). TMB is quantified based on somatic mutations identified by next-generation sequencing (NGS) using targeted panel data. This study aimed to investigate whether different NGS methods will affect the results of TMB detection in solid tumors.
Materials And Methods:
In this study, a hybrid capture NGS method was performed to identify Tumor-only (TO) tissue and tumor tissue and white blood cells Tumor Control (TC). The accuracy and specificity of the two employed methods were evaluated by the identification and analysis of standard reference data. Based on the quality control of FFPE samples, 24 pathological and imaging confirmed solid tumor samples were compared to assess the differences between the two methods in identifying and incorporating the mutation sites and the effect on TMB detection.
Result:
The data identified 298 common genes in the detection range of TO and TC methods. The detection range of these genes primarily comprised exons and some introns. The coefficient of variation (CV%) between the detected variant and true mutation frequencies was < 10%, confirming their accuracy and specificity. Both methods detected increased mutations of TP53, CDKN2 A, KRAS, PTEN, EGFR, PIK3 CA, BRAF, BRCA2, FGFR2, and NRAS. The consistency rate of TMB was observed as 92% (22/24). The chi-square test indicated a significant difference in TMB results between TO and TC (χ2 = 16.667, p = 0.000, p < 0.001). Furthermore, Cohen's kappa analysis showed consistency in the TMB values detected by TO and TC methods, which were good and had high repeatability (kappa = 0.833, p = 0.000, p < 0.001). The Venn analysis revealed that the two methods identified and included different TMB sites, which in turn affected the TMB calculation results.
Conclusion:
This study revealed that different algorithms and design panels for mutation filtering affect the TMB test results. When the TMB result is near the 10 mut/Mb threshold, different methods may yield different results. Moreover, a single test result can affect clinical treatment decisions. Therefore, it is recommended to use TO or TC combined with other tests for evaluating somatic mutations.
Insights
Different next-generation sequencing (NGS) methods impact tumor mutation burden (TMB) detection in solid tumors. Results vary near the 10 mut/Mb threshold, influencing clinical decisions, so consider combined testing for somatic mutations.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Tumor mutation burden (TMB) is a key biomarker for predicting response to immune checkpoint inhibitors (ICI).
- Next-generation sequencing (NGS) using targeted panels is standard for TMB quantification.
- Variations in NGS methods may influence TMB detection accuracy in solid tumors.
Purpose of the Study:
- To investigate the impact of different NGS methods on TMB detection in solid tumors.
- To compare TMB results obtained from Tumor-only (TO) and Tumor Control (TC) analysis.
- To assess the clinical implications of method-dependent TMB variations.
Main Methods:
- Hybrid capture NGS was employed for both TO and TC analyses.
- Accuracy and specificity were validated using standard reference data.
- Twenty-four solid tumor samples (FFPE) were analyzed to compare mutation site identification and TMB calculation.
Main Results:
- Both TO and TC methods accurately detected mutations in 298 common genes with high specificity (CV% < 10%).
- A high consistency rate (92%) in TMB results was observed between the two methods.
- Significant differences in TMB results were noted (p < 0.001), with different mutation sites identified, impacting overall TMB calculation.
Conclusions:
- NGS algorithms and panel designs significantly affect TMB test outcomes.
- Discrepancies in TMB results near the 10 mut/Mb threshold can alter treatment decisions.
- Combined testing approaches (e.g., TO or TC with other methods) are recommended for comprehensive somatic mutation evaluation.
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