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Monitoring the Cancer-Immunity Cycle and Exploring Tumor Microenvironment Dynamics
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Cancer-immune coevolution dictated by antigenic mutation accumulation.

Long Wang1,2, Christo Morison2, Weini Huang1,2

  • 1Group of Theoretical Biology, Innovation Center for Evolutionary Synthetic Biology School of Life Sciences, Sun Yat-sen University, Guangzhou, China.

Elife
|October 10, 2025
PubMed
Summary
This summary is machine-generated.

Cancer cells and immune cells coevolve, with cancer cells developing escape mechanisms. Our model reveals how these interactions influence tumor progression and can be detected through genetic sequencing data.

Keywords:
cancer biologycancer–immune interactioneffector cellsevolutionary biologymutation accumulationnonesingle-cell mutation burden distributionsite frequency spectrumstochastic modelling

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Area of Science:

  • Immunology
  • Computational Biology
  • Cancer Research

Background:

  • The immune system is a critical defense against cancer.
  • Cancer cells can evade immune detection and suppression.
  • Understanding tumor-immune dynamics is vital for cancer treatment.

Purpose of the Study:

  • To model the coevolutionary dynamics between cancer and immune cells.
  • To investigate how interactions influence tumor progression and immune evasion.
  • To identify genetic signatures of these dynamics.

Main Methods:

  • Developed an individual-based model of mutation accumulation in cancer cells.
  • Explicitly modeled stochastic interactions between cancer and effector immune cells.
  • Analyzed sequencing-derived summary statistics for signatures of selection.

Main Results:

  • Model parameters governing cancer-effector cell interactions determine tumor outcomes (suppression vs. evasion).
  • Stochastic effects are crucial for population dynamics of small cell groups.
  • Genetic signatures, like mutational burden distribution, indicate coevolutionary dynamics.

Conclusions:

  • Cancer-immune coevolution significantly impacts tumor progression and treatment response.
  • Genetic sequencing data can reveal underlying tumor-immune interactions.
  • The model provides insights into tumor evolution and potential therapeutic targets.