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Why are the survival rates of patients with high TMB so amazing? What is the science behind it?
In cancer research and therapies, the “tumor mutation burden” (TMB) is considered a key genetic feature. Measurement of TMB has been achieved by next-generation sequencing techniques and has shown its predictive ability for immune checkpoint inhibitor (ICI) therapy in a variety of cancers. Recent studies have shown that high TMB may be associated with improved clinical efficacy, giving hope to many cancer patients.
High TMB not only predicted response to immunotherapy but also closely correlated with overall and disease-specific survival.
Studies suggest that survival in patients with high TMB is significantly higher than that in patients with low TMB. What kind of scientific principle lies behind this phenomenon? First, TMB represents the number of non-heritable mutations present per million base pairs. The latest research has found that when the number of mutations in tumor cells increases, the number of tumor-specific antigens (neoantigens) also increases, which may prompt the immune system to recognize tumor cells more effectively.
Immune checkpoint inhibitors (ICIs) improve patient survival, thanks to their enhanced immune system attack on tumor cells.
In addition to activating the immune system, the increase in TMB is closely correlated with the tumor response to ICIs. Among patients receiving ICI therapy, the corresponding response rate for patients with TMB levels ≥20 mutation/Mb was 58%, while the response rate for patients below this value was only 20%. These data highlight the importance of TMB as a potential predictive biomarker, especially in its use in determining which patients could benefit from ICI therapy.
Not only that, studies have shown that the survival rate of patients with intermediate TMB (5 to 20 mutations/Mb) is significantly lower than that of patients with high TMB, with progression-free survival and overall survival in some cases of high TMB not even yet The time point at which the end of the study was reached.
Progression-free survival can reach 12.8 months in patients with high TMB, a figure that demonstrates their superiority in treatment.
Of course, there are huge differences in TMB values between different types of cancer. For example, TMB values are usually higher for melanoma and non-small cell lung cancer, while TMB values are relatively low for leukemia and some pediatric tumors. This means that for different cancer types, it may be necessary to develop respective TMB categories to better predict survival and develop treatment plans.
The calculation method of TMB also affects its reliability. Currently, strategies based on whole-genome, whole-exome, and panel sequencing can be used to calculate TMB, and the advantages and disadvantages of these strategies affect the quality and accuracy of TMB data.
For example, for the high sensitivity of detection, certain panel sequencing strategies perform well in samples with lower tumor cell content.
In addition, the heterogeneity of the tumor as well as the source of the sample (in situ or metastatic tumor) also affects the calculation of TMB. In general, metastatic tumors are usually monoclonal and have lower overall gene diversity, which in turn may contribute to higher TMB values.
As research on TMB has deepened, scientists have begun to call for uniformity and regulation of TMB assessment standards to enhance its potential as a reliable biomarker. Various studies have also suggested that combining TMB with other biomarkers such as PD-L1 expression may improve the predictive power of patient prognosis.
This all means that the future of cancer research may be brighter with the introduction of TMB, but the challenges that come with it cannot be underestimated. As our understanding of the relationship between TMB and cancer continues to deepen, what new breakthroughs will lead our thinking about cancer treatment in the future?
