Challenges of Tumor Mutational Burden as a Biomarker for Immunotherapy
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Challenges of Tumor Mutational Burden as a Biomarker for Immunotherapy
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Challenges of Tumor Mutational Burden as a Biomarker for Immunotherapy.
Immune checkpoint inhibitors (ICIs) are profoundly changing the treatment landscape for many cancers.
A cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitor and six programmed cell death protein pathway inhibitors (PD-1/PD-L1) have received regulatory approval from the U.S. Food and Drug Administration (FDA) for various malignancies.
Although some individuals can achieve durable complete remission, the overall response rates (RRs) of these drugs as monotherapy remain relatively low (15%-20%).
The heterogeneity in responses to ICIs underscores the necessity of identifying predictive biomarkers. Immunohistochemistry (IHC) testing for PD-L1 expression is one of the most straightforward predictive biomarkers.
Another biomarker that has recently gained widespread attention is tumor mutational burden (TMB), which measures the quantity of mutations in a tumor.
The more mutations present, the greater the number of neoantigens, and the higher the likelihood that one or more of these neoantigens will possess immunogenicity and trigger a T-cell response.
Many studies have reported a correlation between higher TMB and efficacy of ICIs, suggesting that TMB may serve as a promising predictive biomarker.
Definition and measurement of TMB
The conceptual definition of TMB is the total number of mutations present in tumor specimens. The actual definition of the type of genetic alteration considered for TMB varies according to the method.
Characterization of TMB was initially done with whole exome sequencing ( WES ), which essentially assumes that genetic alterations are limited to exons ( coding regions ). TMB calculations by WES included non-synonymous mutations in coding regions and excluded germline changes by subtracting matched normal samples.
A comprehensive genomic profiling assay ( FoundationOne ) of 324 genes ( equivalent to a 1.1MB coding genome ) developed by Foundation Medicine proved to be an accurate assessment of TMB by WES. Recently, the FDA approved the assay as an adjunct to the use of pembrolizumab in patients with TMB > 10 mutations/Mb.
The FoundationOne analysis also included synonymous mutations in its TMB and insertion-deletion markers ( Indels ) in intronic regions , which were not included in WES. Indels often generate a new DNA open reading frame, resulting in an entirely new peptide that may have a higher chance of encoding an immunogenic neoantigen.
Another FDA-approved NGS assay is MSK-IMPACT, which currently identifies somatic exonic mutations in 468 cancer-associated genes ( approximately 1.2 MB ).
TMB and Tumor Immune Response
Immune evasion is an important feature of tumors. T cells typically recognize neoantigens created by mutations and presented by major histocompatibility complex ( MHC ) proteins on the surface of cancer cells. To survive, tumors hijack proteins that normally serve as checkpoints to weaken the immune system’s ability to kill them.
By blocking immune checkpoint proteins, such as PD-1, PD-L1 and CTLA-4, the immune system can be reawakened.
Once activated, however, T cells must still be able to distinguish tumors from normal cells. The presence of immunogenic neoantigens on the surface of tumor cells facilitates the recognition of tumor cells.
Since neoantigens arise from mutations, the greater the number of mutations ( i.e., the higher the TMB ), the greater the likelihood that some neoantigens presented by MHC proteins will be immunogenic. On this basis, it is not surprising that high levels of TMB are associated with better outcomes after ICI treatment.
However, any attempt to dichotomize the predictive power of TMB is imperfect because, in theory, neoantigens recognized by T cells could originate in a low-mutation environment (albeit less likely); conversely, large numbers of mutations do not necessarily translate are immunogenic neoantigens.
Environmental and host factors affecting TMB as a biomarker for anticancer immunotherapy
Several different factors may cause alterations in the genome of tumor cells, the number of which can be quantified by TMB. Environmental factors ( e.g., UV light ) and DNA editing errors ( MSI ) lead to mutational patterns under different signatures. Each feature may affect not only the number of mutations but also the quality and immunogenicity of the neoantigens loaded as mutants.
Intrinsic properties of the host can also affect the presentation and recognition of neoantigens.
For example, MHC diversity defines the extent of neoantigen presentation, while TCR clustering can define neoantigen recognition. Epigenetic regulation, such as histone modifications and DNA methylation , may also affect the host’s ability to mount an effective immune response.
Applications and challenges of TMB as a biomarker
The role of TMB as a prognostic marker in patients with early immunotherapy
Clinically, there was a significant correlation between TMB and the objective response to PD-1/PD-L1 inhibitors.
Among 151 patients with advanced solid tumors treated with ICIs, RRs were 5% ( <5 mutations/Mb ) for patients with low TMB levels, 25% ( 6-19 mutations/Mb ) for patients with intermediate TMB levels, and RRs for patients with TMB RRs were 45% in patients with high levels ( >20-49 mutations/Mb ) and 65% in individuals with very high TMB ( >50 mutations/Mb ).
It is also relevant to compare squamous cells to other histologies.
Squamous cell tumors had higher TMB than non-squamous cell carcinomas, with cutaneous squamous cell tumors having the highest TMB, with 41% showing very high TMB ( >50 mutations/Mb ).
Among patients with squamous cell carcinoma receiving immunotherapy, higher TMB ( >12 mutations/Mb ) was associated with a significantly better prognosis, with the highest clinical benefit from ICI in cutaneous squamous cell carcinoma.
Low TMB does not preclude response to ICIs
ICIs can be effective even with low TMB, although in a small percentage of patients ( 5% ). For example, Kaposi’s sarcoma is a virus-associated malignancy that responds to ICIs. In fact, 6 of 9 patients ( 67% ) who received anti-PD-1 monotherapy achieved a complete or partial response; all patients had low TMB and were PD-L1 negative.
Merkel cell carcinoma is another interesting example, where the RRs of ICI therapy in advanced patients were approximately 56%. Merkel cell carcinomas may be associated with UV light or Merkel cell polyomavirus infection, while Merkel cell carcinomas caused by UV light show high levels of TMB, Merkel cell tumors with Merkel cell polyomavirus show low levels of TMB, but the viral antigen itself Immunogenic.
TMB as part of a composite biomarker to predict prognosis in ICI
Developing accurate predictors of ICI response requires a deep understanding of the complexities of immune response and drug resistance and the integration of multiple variables into a composite biomarker that may include expression of TMB, PD-L1, PD-1 and Other checkpoints, and consider the expression of cells, tumor molecular characteristics, neoantigen immunogenicity and other characteristics. This integrated conceptual model is called the “Cancer Immune Map.”
One of the seven parameter categories of the Cancer Immunogram is tumor foreignness. Although TMB has its limitations in defining the quality of neoantigens, it can be considered as a proxy for foreignness. Additional parameters of the cancer immune map include biomarkers related to immune infiltration and metabolism, lack of inhibitors, checkpoint status, and tumor sensitivity to immune effectors.
A key aspect of this model is to frame the tumor immune system as dynamic, changing as the disease progresses. Thus, in this complex system, biomarkers can be added or removed as the disease progresses.
Summary
Multiple lines of evidence suggest that higher TMB is associated with better outcomes after ICI treatment. Although the FDA has approved the use of the anti-PD-1 antibody pembrolizumab in solid tumors with TMB >10 mutations/Mb, and a blood test to evaluate TMB is being developed, many challenges remain for the further development of TMB as a clinical biomarker.
For example, the predictive value of TMB for immunotherapy combined with targeted agents or chemotherapy has not been established.
Furthermore, it is critical to recognize that a small proportion ( 5% ) of patients with low TMB respond well to ICIs, whereas more than 50% of patients with high TMB do not respond.
This reflects the complexity of the immune system and the need to incorporate multiple other variables into a composite biomarker in order to more accurately predict ICI outcome and fully realize the potential benefits of immunotherapy.
references:
1. The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker . Cancer Cell. 2020 Oct 14;S1535-6108(20)30495-5.
Challenges of Tumor Mutational Burden as a Biomarker for Immunotherapy
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