12% of the patients showing more than 20 mutations/mb. the authors identified a tumor mutational burden greater than or equal to 10 mutations/mb as the optimal cut-off to benefit from combination immunotherapy. however, in other cancer types, high tmb status has been classified as >20 mutations/mb. issues and future directions one approved biomarker of ici therapy is pd-l1 expression, but the predictive power of this biomarker is affected by factors such as assay interpretation and lack of standard methods. tmb is also affected by these factors in addition to accessibility issues. biological factors like specimen type and cancer type as well as technical factors like sequencing technology can affect evaluation of tmb. thus, it is necessary to harmonize evaluation methods and there are still so many factors that can complicate this task. for example, gene fusions and post-translational changes in proteins contribute to tumor behaviour and consequently response to therapy while these factors are not considered in tmb estimation. in addition, currently all mutations have the same weight in tmb calculation, while they can have very different effects on proteins and pathways activity. furthermore, there is still no good answer to the question of how mutations in genes that are known to influence ici therapy should be treated in tmb evaluation. it is also important to note that tmb is highly variable across cancer types and subtypes and different studies are being conducted to find distinct tmb thresholds. some studies argue that to have better prediction of response to ici therapy, tmb should be used as a complementary marker with other biomarkers such as pd-l1. other studies have shown that a combination of tmb and neoantigen load can be used as a biomarker to predict survival in patients with melanoma who received adaptive t cell transfer therapy. since tmb is a relatively new biomarker, there is still a need to perform more studies and many labs are being focused on different aspects of this biomarker.