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How does TMB reveal the secrets of tumors and make immunotherapy more effective?
With the advancement of science and technology, tumor mutation burden (TMB) has become an important indicator in cancer research and treatment. Studies have shown that TMB is closely related to immunotherapy response in various cancers. Through next-generation sequencing technology, TMB can accurately calculate the number of mutations in tumor tissues, which provides a new perspective for clinical treatment.
High TMB and DNA damage repair mutations are strongly associated with clinical benefit from immune checkpoint inhibitor therapy.
TMB is defined as the number of non-genetic mutations per million bases, a number that reveals the variability of tumor cells. According to a 2019 study, patients with high TMB showed significant clinical responses and had higher survival rates after receiving immune checkpoint inhibitor (ICI) treatment. Compared with patients with low TMB or intermediate TMB, patients with high TMB had significantly longer survival.
The biomarker value of TMB
TMB, as a predictive biomarker, has received increasing attention. Especially in various cancers, the higher the TMB value, the higher the response rate of patients when receiving immune checkpoint inhibitor treatment.
An analysis of ICIs showed that the response rate of patients with TMB greater than 20 mutations/Mb was 58%, while the response rate dropped to 20% with TMB less than 20 mutations/Mb.
In addition, studies have shown that patients with different cancer types have differences in the predictive role of TMB. For example, in lung cancer patients, the median TMB is 7.2 mutations/Mb, while in other cancers, the definition of high TMB may be higher. This makes understanding cancer types and their molecular signatures increasingly important.
Key indicators of patient prognosis
TMB is not only an indicator of treatment response, but also an important reference for patient prognosis. One study found that patients with higher TMB had a median progression-free survival of 12.8 months without immunotherapy treatment, compared with only 3.3 months for patients with low TMB.
The overall survival of these two groups of patients also showed significant differences, showing that TMB is an independent and reliable prognostic indicator in a variety of cancers.
The variability and calculation method of TMB
Currently, TMB values vary significantly among different cancer types. TMB levels are highest in melanoma and non-small cell lung cancer, while certain leukemias and pediatric tumors show lower TMB values. This requires clinically developing different TMB boundaries for different cancer types to more accurately predict patients' survival chances.
About 70% of melanoma patients are found to have high TMB, and the value can even reach more than 400 mutations/Mb.
As for the calculation methods of TMB, it currently mainly includes different methods such as whole genome sequencing, whole exome sequencing and targeted panels. Each method has its advantages and disadvantages. In clinical applications, targeted gene panels are widely used due to their accuracy and rapidity.
Future challenges and prospects
Although TMB has shown good predictive ability in cancer immunotherapy, its standardization and quantification still face challenges. Different sequencing technologies and bioinformatics pipelines will affect the calculation results of TMB. Therefore, unified assessment methods and guiding principles remain an important direction for future research.
Further research shows that TMB alone may not be able to independently predict a patient's immunotherapy response. Combining it with other biomarkers (such as PD-L1 expression) to improve prediction accuracy will be the current research focus of the scientific community. Whether TMB can become a standard indicator for the treatment of more cancer types is worthy of our in-depth consideration?
