ReviewBMC cancer2015
Can Peto's paradox be used as the null hypothesis to identify the role of evolution in natural resistance to cancer? A critical review.
Review in BMC cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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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.
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Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Peto's paradox's relevance is off the scale.Aging · 2025Article
- Analysis of Cancer-Resisting Evolutionary Adaptations in Wild Animals and Applications for Human Oncology.Journal of molecular evolution · 2024Review
- Cell size, body size and Peto's paradox.BMC ecology and evolution · 2022Review
- A phylogenetic review of cancer resistance highlights evolutionary solutions to Peto's Paradox.Genetics and molecular biology · 2022Article
- What Animal Cancers teach us about Human Biology.Theranostics · 2021Review
- TERT promoter alterations could provide a solution for Peto's paradox in rodents.Scientific reports · 2020Article
- Article
- Turning natural adaptations to oncogenic factors into an ally in the war against cancer.Evolutionary applications · 2018Article
- Importance of metabolic rate to the relationship between the number of genes in a functional category and body size in Peto's paradox for cancer.Royal Society open science · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCarcinogenesis affects not only humans but almost all metazoan species. Understanding the rules driving the occurrence of cancers in the wild is currently expected to provide crucial insights into identifying how some species may have evolved efficient cancer resistance mechanisms. Recently the absence of correlation across species between cancer prevalence and body size (coined as Peto's paradox) has attracted a lot of attention. Indeed, the disparity between this null hypothesis, where every cell is assumed to have an identical probability to undergo malignant transformation, and empirical observations is particularly important to understand, due to the fact that it could facilitate the identification of animal species that are more resistant to carcinogenesis than expected. Moreover it would open up ways to identify the selective pressures that may be involved in cancer resistance. However, Peto's paradox relies on several questionable assumptions, complicating the interpretation of the divergence between expected and observed cancer incidences. DISCUSSIONS: Here we review and challenge the different hypotheses on which this paradox relies on with the aim of identifying how this null hypothesis could be better estimated in order to provide a standard protocol to study the deviation between theoretical/theoretically predicted and observed cancer incidence. We show that due to the disproportion and restricted nature of available data on animal cancers, applying Peto's hypotheses at species level could result in erroneous conclusions, and actually assume the existence of a paradox. Instead of using species level comparisons, we propose an organ level approach to be a more accurate test of Peto's assumptions. SUMMARY: The accuracy of Peto's paradox assumptions are rarely valid and/or quantifiable, suggesting the need to reconsider the use of Peto's paradox as a null hypothesis in identifying the influence of natural selection on cancer resistance mechanisms.
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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 OpenQuestion graph.