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Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

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Related Experiment Video

Updated: Aug 6, 2025

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

Persistence is key: Refining immunotherapy response prediction.

Michelle Leung¹, Nicholas McGranahan²

¹Cancer Genome Evolution Research Group, University College London Cancer Institute, London, UK; Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, University College London Cancer Institute, London, UK; Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.

|March 15, 2023

Summary

This summary is machine-generated.

Persistent mutation burden, a refined measure of tumor mutation burden (TMB), shows improved prediction of patient response to immune checkpoint blockade (ICB) therapy compared to standard TMB. This finding enhances immunotherapy outcome prediction.

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Last Updated: Aug 6, 2025

Predictive Immune Modeling of Solid Tumors

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Published on: February 25, 2020

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Published on: June 29, 2021

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Published on: September 15, 2023

Area of Science:

Oncology
Immunotherapy
Genomics

Background:

Tumor mutation burden (TMB) is an established biomarker for predicting response to immune checkpoint blockade (ICB) therapy.
However, TMB's predictive accuracy is limited, necessitating improved metrics for patient stratification.

Purpose of the Study:

To evaluate persistent mutation burden as a novel, more accurate predictor of ICB therapy response.
To compare the efficacy of persistent mutation burden against conventional TMB in predicting treatment outcomes.

Main Methods:

Analysis of genomic data to quantify tumor mutation burden.
Development and application of a novel metric: persistent mutation burden.
Correlation of mutation burden metrics with patient responses to ICB therapy.

Main Results:

Persistent mutation burden demonstrated superior predictive performance for ICB therapy outcomes compared to overall TMB.
The study identified a specific subset of TMB that more reliably indicates treatment success.

Conclusions:

Persistent mutation burden represents a refined and more effective biomarker for predicting patient response to ICB.
This improved metric can aid in better patient selection for immunotherapy, optimizing treatment strategies.