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Updated: Dec 3, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
The Challenges of Tumor Mutational Burden as an Immunotherapy Biomarker
Denis L Jardim1, Aaron Goodman2, Debora de Melo Gagliato3
1Centro de Oncologia Hospital Sírio Libanês-São Paulo, São Paulo, Brazil.
Abstract:
Tumor mutational burden (TMB) reflects cancer mutation quantity. Mutations are processed to neo-antigens and presented by major histocompatibility complex (MHC) proteins to T cells. To evade immune eradication, cancers exploit checkpoints that dampen T cell reactivity. Immune checkpoint inhibitors (ICIs) have transformed cancer treatment by enabling T cell reactivation; however, response biomarkers are required, as most patients do not benefit. Higher TMB results in more neo-antigens, increasing chances for T cell recognition, and clinically correlates with better ICI outcomes. Nevertheless, TMB is an imperfect response biomarker. A composite predictor that also includes critical variables, such as MHC and T cell receptor repertoire, is needed.
Insights
Tumor mutational burden (TMB) indicates cancer mutation levels and can predict responses to immune checkpoint inhibitors (ICIs). However, TMB alone is insufficient, necessitating composite biomarkers for better patient stratification.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Tumor mutational burden (TMB) quantifies cancer mutations, which can be processed into neo-antigens.
- Neo-antigens presented by major histocompatibility complex (MHC) proteins engage T cells.
- Cancer immune evasion occurs via checkpoints that suppress T cell activity.
Purpose of the Study:
- To evaluate the predictive value of TMB for immune checkpoint inhibitor (ICI) therapy outcomes.
- To identify the limitations of TMB as a sole biomarker for ICI response.
- To advocate for the development of composite biomarkers.
Main Methods:
- Analysis of TMB in relation to neo-antigen formation and T cell recognition.
- Correlation of TMB levels with clinical outcomes in patients treated with ICIs.
- Review of mechanisms of cancer immune evasion and T cell regulation.
Main Results:
- Higher TMB generally correlates with increased neo-antigens and improved ICI outcomes.
- TMB is an imperfect predictor, as many patients do not benefit from ICIs.
- Existing biomarkers do not fully capture the complexity of anti-tumor immunity.
Conclusions:
- While TMB is a valuable biomarker, it is insufficient for predicting ICI response.
- A composite biomarker incorporating TMB, MHC, and T cell receptor repertoire is needed.
- Improved biomarkers are crucial for patient selection and optimizing cancer immunotherapy.
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