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Updated: Jul 2, 2025
Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical
Célia Dupain1, Tom Gutman2, Elodie Girard2
1Department of Drug Development and Innovation (D3i), Institut Curie, Paris, France.
Background:
High tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests.
Results:
FFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm. Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as "true TMB high." Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10-3927] versus 8.2 mut/Mb [2.5-897], p < 0.001).
Conclusions:
We herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.
Insights
A new Institut Curie (IC) algorithm for calculating tumor mutational burden (TMB) was developed and validated. This method allows for TMB assessment using various next-generation sequencing panels and sample types.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- High tumor mutational burden (TMB) is a predictor of immune checkpoint inhibitor (ICI) efficacy.
- Pembrolizumab (anti-PD-1) is FDA-approved for high TMB tumors, with TMB determined by FoundationOne®CDx.
- Alternative methods for TMB calculation require investigation.
Purpose of the Study:
- To develop and validate a novel TMB calculation method at Institut Curie (IC).
- To compare the IC algorithm with the FoundationOne® (FO) algorithm for TMB assessment.
- To establish optimal variant allele frequency (VAF) cut-offs for TMB evaluation on different sample types.
Main Methods:
- Next-generation sequencing (NGS) panel used for sequencing tumor samples.
- Development of an in-house TMB calculation algorithm (IC algorithm).
- Comparison of IC algorithm with the FoundationOne® (FO) algorithm.
Main Results:
- An optimal 10% VAF cut-off for FFPE samples and 5% for frozen samples was established for the IC algorithm.
- The IC algorithm identified significant differences in median TMB between MSS/POLE WT and MSI/POLE-mutated tumors.
- The FO algorithm yielded higher TMB values on FFPE samples compared to the IC algorithm (40 mut/Mb vs. 8.2 mut/Mb).
Conclusions:
- A customizable TMB calculation method and bioinformatics tool were developed.
- The IC algorithm is adaptable to different NGS panels and sample types.
- Direct retrieval of TMB values from the FO algorithm using the IC algorithm and NGS panel was not achieved.
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