Evidence map›Paper›PMID 40569384›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

The adaptive state determines the impact of mutations on evolving populations.

Malgorzata Tyczynska Weh, Pragya Kumar, Viktoriya Marusyk, Andriy Marusyk, David Basanta

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Cancer Evolvability Determines Therapy Outcomes.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. 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

5 authors.

Malgorzata Tyczynska WehDepartment of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612.
Pragya KumarCancer Biology Ph.D. Program, Department of Molecular Biosciences, University of South Florida, Tampa, FL 33612.
Viktoriya MarusykDepartment of Tumor Microenvironment and Metastasis, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612.
Andriy Marusyk *Department of Tumor Microenvironment and Metastasis, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612.ORCID 0000-0002-0087-9575
David Basanta *Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612.ORCID 0000-0002-8527-0776

Funding

The Delta Ecology of NSCLC TreatmentU54CA274507 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI Alexander Robertson Allan Anderson, ROBERT A GATENBY · 2023 to 2026
$9.4M
NCI NIH HHS U54 CA274507
6 · The paper itself

Abstract

Darwinian evolution results from an interplay between stochastic diversification of heritable phenotypes, impacting the chance of survival and reproduction, and fitness-based selection. The ability of populations to evolve and adapt to environmental changes depends on rates of mutational diversification and the distribution of fitness effects of random mutations. In turn, the distribution of fitness effects of stochastic mutations can be expected to depend on the adaptive state of a population. To systematically study the impact of the interplay between the adaptive state of a population on the ability of asexual populations to adapt, we used a spatial agent-based model of a neoplastic population adapting to a selection pressure of continuous exposure to targeted therapy. We found favorable mutations were overrepresented at the extinction bottleneck but depleted at the adaptive peak. The model-based predictions were tested using an experimental cancer model of an evolution of resistance to a targeted therapy. Consistent with the model's prediction, we found that enhancement of the mutation rate was highly beneficial under therapy but moderately detrimental under the baseline conditions. Our results highlight the importance of considering population fitness in evaluating the fitness distribution of random mutations and support the potential therapeutic utility of restricting mutational variability.

Indexed as

Adaptation, PhysiologicalEvolution, MolecularModels, GeneticMutationGenetic FitnessHumansMutation RateNeoplasmsSelection, Geneticagent-based modelingcancerevolution

Identifiers

PMID40569384
PMCPMC12232665

What OpenQuestion holds

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Registered trials

None linked

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.