Tumor mutational burden (TMB) is an emerging biomarker that has gained considerable attention in recent years as a predictor of response to immunotherapy. TMB is defined as the number of somatic mutations per megabase (Mb) of the genome within a tumor. It is widely believed that tumors with higher TMB have a higher likelihood of producing neoantigens, which are foreign antigens that are generated as a result of somatic mutations and are presented on the surface of tumor cells. These neoantigens can be recognized by the immune system as foreign and trigger an immune response, making tumors with high TMB more susceptible to immune checkpoint inhibitor therapy.
Immune checkpoint inhibitors (ICI) are a class of drugs that target immune checkpoint proteins, such as programmed cell death protein 1 (PD-1) and its ligand (PD-L1), which are involved in regulating the immune response. By inhibiting these proteins, ICIs can enhance the immune response against cancer cells, leading to tumor cell death. However, not all patients respond to ICI therapy, and a significant proportion of patients experience adverse events. This highlights the need for biomarkers to identify patients who are most likely to benefit from ICI therapy.
TMB has been evaluated as a potential biomarker for response to ICI therapy in several clinical trials across different cancer types, including melanoma, non-small cell lung cancer (NSCLC), and bladder cancer. In a landmark study published in 2015, Rizvi et al. demonstrated that NSCLC patients with higher TMB had a higher response rate to PD-1 blockade with pembrolizumab (Keytruda) compared to those with lower TMB. The study also showed that patients with high TMB had a longer progression-free survival (PFS) and overall survival (OS) compared to those with low TMB.
Since then, several other studies have confirmed the association between TMB and response to ICI therapy. For instance, in a phase II trial of pembrolizumab in patients with advanced bladder cancer, patients with high TMB had a higher response rate and longer PFS compared to those with low TMB. Similarly, in a phase III trial of nivolumab (Opdivo) in patients with melanoma, TMB was found to be a predictive biomarker for response to ICI therapy.
Despite these promising results, there are still several challenges associated with the use of TMB as a biomarker for ICI therapy. One of the major challenges is the lack of standardization in TMB assessment. There are several methods for measuring TMB, including whole-exome sequencing (WES), targeted sequencing, and gene panels, each with its own advantages and limitations. As a result, there is a need for standardized and validated methods for TMB assessment to ensure consistency across different studies and clinical settings.
Another challenge is the lack of a clear threshold for defining high TMB. Different studies have used different cutoffs for defining high TMB, ranging from 6 to 20 mutations/Mb, making it difficult to compare results across studies. Additionally, TMB may not be a reliable biomarker in all cancer types, as some tumors may have low TMB but still respond to ICI therapy, while others may have high TMB but not respond.
In conclusion, TMB is a promising biomarker for predicting response to ICI therapy. Several clinical trials have demonstrated that patients with high TMB have a higher response rate and longer survival compared to those with low TMB. However, there are still several challenges associated with the use of TMB as a biomarker, including the lack of standardization in TMB assessment and the lack of a clear threshold for defining high TMB. As more data become available, TMB may become a valuable tool for identifying patients who are most likely to benefit from ICI therapy.
