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Immune Determinants of the Association between Tumor Mutational Burden and Immunotherapy Response across Cancer Types
Neelam Sinha1, Sanju Sinha1, Cristina Valero2,3
1Cancer Data Science Lab, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, Maryland.
Abstract:
The FDA has recently approved a high tumor mutational burden (TMB-high) biomarker, defined by ≥10 mutations/Mb, for the treatment of solid tumors with pembrolizumab, an immune checkpoint inhibitor (ICI) that targets PD1. However, recent studies have shown that this TMB-high biomarker is only able to stratify ICI responders in a subset of cancer types, and the mechanisms underlying this observation have remained unknown. The tumor immune microenvironment (TME) may modulate the stratification power of TMB (termed TMB power), determining if it will be predictive of ICI response in a given cancer type. To systematically study this hypothesis, we inferred the levels of 31 immune-related factors characteristic of the TME of different cancer types in The Cancer Genome Atlas. Integration of this information with TMB and response data of 2,277 patients treated with anti-PD1 identified key immune factors that determine TMB power across 14 different cancer types. We find that high levels of M1 macrophages and low resting dendritic cells in the TME characterized cancer types with high TMB power. A model based on these two immune factors strongly predicted TMB power in a given cancer type during cross-validation and testing (Spearman Rho = 0.76 and 1, respectively). Using this model, we predicted the TMB power in nine additional cancer types, including rare cancers, for which TMB and ICI response data are not yet publicly available. Our analysis indicates that TMB-high may be highly predictive of ICI response in cervical squamous cell carcinoma, suggesting that such a study should be prioritized.
Significance:
This study uncovers immune-related factors that may modulate the relationship between high tumor mutational burden and ICI response, which can help prioritize cancer types for clinical trials.
Insights
High tumor mutational burden (TMB) predicts immune checkpoint inhibitor response in some cancers. This study identifies M1 macrophages and resting dendritic cells as key factors influencing TMB predictive power, aiding trial prioritization.
Area of Science:
- Immunology
- Oncology
- Genomics
Background:
- The FDA-approved high tumor mutational burden (TMB-high) biomarker (≥10 mutations/Mb) predicts response to immune checkpoint inhibitors (ICIs) like pembrolizumab in solid tumors.
- However, TMB-high's predictive ability varies across cancer types, with underlying mechanisms remaining unclear.
- The tumor immune microenvironment (TME) is hypothesized to modulate TMB's predictive power (TMB power).
Purpose of the Study:
- To systematically investigate how TME factors influence TMB power in predicting ICI response.
- To identify specific immune-related factors within the TME that determine TMB power across diverse cancer types.
- To develop a predictive model for TMB power and apply it to prioritize cancer types for future clinical trials.
Main Methods:
- Inferred TME immune-related factors for various cancer types using The Cancer Genome Atlas (TCGA) data.
- Integrated TME data with TMB and anti-PD1 response data from 2,277 patients across 14 cancer types.
- Developed and validated a predictive model for TMB power using key immune factors.
Main Results:
- Identified high M1 macrophage and low resting dendritic cell levels in the TME as characteristic of cancer types with high TMB power.
- A model incorporating these two factors accurately predicted TMB power (Spearman Rho = 0.76 cross-validation, 1 testing).
- Predicted TMB power in nine additional cancer types, suggesting high potential in cervical squamous cell carcinoma.
Conclusions:
- Specific TME compositions, particularly M1 macrophages and resting dendritic cells, significantly modulate TMB's predictive capacity for ICI response.
- The developed model offers a tool to predict TMB power and guide the selection of cancer types for ICI clinical trials.
- Cervical squamous cell carcinoma emerges as a priority for further investigation regarding TMB-high biomarker utility in ICI therapy.
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