Evidence map›Paper›PMID 41071591›Full record

ArticleeLife2025

Cancer-immune coevolution dictated by antigenic mutation accumulation.

Long Wang, Christo Morison, Weini Huang

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. A pediatric low-grade sinonasal mesenchymal tumor harboring a novel CHD9::BEND2 fusion.Virchows Archiv : an international journal of pathology · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Long WangGroup of Theoretical Biology, Innovation Center for Evolutionary Synthetic Biology School of Life Sciences, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-6937-2481
Christo MorisonSchool of Mathematical Sciences, Queen Mary University of London, London, United Kingdom.ORCID https://orcid.org/0000-0002-9350-7833
Weini HuangGroup of Theoretical Biology, Innovation Center for Evolutionary Synthetic Biology School of Life Sciences, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-9016-2665

Funding

European Commission 10.3030/955708
6 · The paper itself

Abstract

The immune system is one of the first lines of defence against cancer. When effector cells attempt to suppress tumour, cancer cells can evolve methods of escape or inhibition. Knowledge of this coevolutionary system can help to understand tumour-immune dynamics both during tumourigenesis and during immunotherapy treatments. Here, we present an individual-based model of mutation accumulation, where random mutations in cancer cells trigger specialised immune responses. Unlike previous research, we explicitly model interactions between cancer and effector cells and incorporate stochastic effects, which are important for the expansion and extinction of small populations. We find that the parameters governing interactions between the cancer and effector cells induce different outcomes of tumour progress, such as suppression and evasion. While it is hard to measure the cancer-immune dynamics directly, genetic information of the cancer may indicate the presence of such interactions. Our model demonstrates signatures of selection in sequencing-derived summary statistics, such as the single-cell mutational burden distribution. Thus, bulk and single-cell sequencing may provide information about the coevolutionary dynamics.

Indexed as

Antigens, NeoplasmMutationMutation AccumulationNeoplasmsHumansAntigens, Neoplasmcancer biologycancer–immune interactioneffector cellsevolutionary biologymutation accumulationnonesingle-cell mutation burden distributionsite frequency spectrumstochastic modelling

Identifiers

PMID41071591
PMCPMC12513721

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.