TMB represents the total number of mutations per coding area of a tumor genome. It is usually calculated through genomic sequencing of tumor DNA. The value of TMB has been found to correlate with the efficacy of some anti-PD1/PD-L1 immunotherapies in certain tumor types.
NovoPM™ 2.0-TMB Algorithm
- TMB is calculated based on the coding DNA sequence (CDS) regions included in the NovoPM™ 2.0 panel (approximately 1.4 Mb).
- Somatic mutations are identified by VarScan2.
- The following mutations are excluded from the calculation of TMB:
- Germline mutations
- Low frequency mutations (Threshold: SNV 1.5%; InDel 3%)
- Known driver mutations (EGFR, MET, BRAF, PIK3CA, NF1, KRAS, and NOTCH family)
- Synonymous mutations
- Repeat regions
The NovoPM™ 2.0-TMB algorithm was validated with the lung adenocarcinoma (LUAD) WES dataset and lung squamous cell carcinoma (LUSC) WES dataset from The Cancer Genome Atlas (TCGA). Both showed highly linear correlations between mutation counts calculated from whole exome sequencing and NovoPM™ 2.0-TMB (Figure 1A and Figure 1B; R²=0.90 and 0.77, respectively). In addition to the validation with public data, we also validated the NovoPM™ 2.0-TMB algorithm with in-house WES data from 15 lung cancer samples and the results showed strong linear correlation (Figure 1C; R²=0.98).
Figure 1. NovoPM™ 2.0‒TMB shows strong linear correlation with WES‒TMB for two TCGA lung cancer dataset (A and B) and a Novogene in-house dataset from FFPE samples (C. Germline mutations, synonymous mutations and repeat regions are excluded in both WES and NovoPM™ 2.0).