Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

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 (R) 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 (R) (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.