ReviewNature reviews. Cancer2025
Modelling the ageing dependence of cancer evolutionary trajectories.
Review in Nature reviews. Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Resolving translational challenges in cancer biology through yeast experimental evolution.Cancer metastasis reviews · 2026Review
- Article
- Ageing, immune fitness and cancer.Nature reviews. Cancer · 2025Review
- The evolution of cancer and ageing: a history of constraint.Nature reviews. Cancer · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Ageing is the single most important prognostic factor for cancer development. Despite this knowledge, experimental models of cancer have historically omitted incorporating the impact of age on cancer initiation, progression and treatment outcomes. Ageing interacts with other lifestyle factors, including cigarette smoking, obesity and physical activity, but these intersections are rarely studied in experimental models. Given that cancer-related mortality rates increase with age, there is a growing emphasis on modelling ageing-associated mutational and microenvironmental changes in cancer research. In this Review, we provide guidance on the technological advancements and experimental strategies that have increased our ability to model how ageing impacts various stages of cancer evolution, from mutation-driven clonal expansions, to pre-malignant lesions, and then to progression to more malignant phenotypes and metastasis, and responses to therapies. We discuss the benefits and limitations of methods and models used. The wider adoption of age-appropriate models of cancer will enable the development of improved approaches for the detection, prevention and therapeutic intervention of human cancers.
Indexed as
Identifiers
40640377What Socratic holds
Registered trials
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 Socratic graph.