Cancer prevalence is remarkably low in turtles and is correlated with life history traits in birds, mammals, and squamates

Cancer rates vary widely across vertebrate groups. Identifying species with lower-than-expected cancer prevalence can help establish new models for unraveling the biological mechanisms underlying cancer resistance. Theoretical predictions suggest that cancer prevalence should be positively associated with body mass and longevity in animals. Yet, in mammals, the best studied vertebrates in terms of cancer, this prediction does not hold true: a phenomenon known as Peto’s paradox. Despite mounting work disentangling the biological basis of Peto’s paradox, it is still relatively unknown whether other major vertebrate groups behave similarly to mammals or might hold new keys to understanding cancer biology. Here, we present the largest dataset available so far on cancer prevalence across all major groups of tetrapod vertebrates: amphibians, birds, crocodilians, mammals, squamates (lizards and snakes), and turtles. We investigated cancer prevalence within and among these groups and its relationship with body mass and lifespan. This is the first study to analyze non-avian reptile groups separately. We found remarkably low cancer prevalence in birds, crocodilians, and turtles. Counter to previous studies, we found that body mass and lifespan are inversely related to cancer prevalence in mammals, although Peto’s paradox still holds true in this group. Conversely, we rejected Peto’s paradox in birds and squamates, as neoplasia prevalence was positively associated with body mass in these groups. The exceptionally low cancer prevalence in turtles and extensive variation in cancer prevalence amongst vertebrate families hold particular promise for identifying species with novel mechanisms of cancer resistance.

[1]  Dalia A. Conde,et al.  Slow and negligible senescence among testudines challenges evolutionary theories of senescence , 2022, Science.

[2]  David A. W. Miller,et al.  Diverse aging rates in ectothermic tetrapods provide insights for the evolution of aging and longevity , 2022, Science.

[3]  S. Harrison,et al.  A Multi-Institutional Collaboration to Understand Neoplasia, Treatment and Survival of Snakes , 2022, Animals : an open access journal from MDPI.

[4]  Dalia A. Conde,et al.  Cancer risk across mammals , 2021, Nature.

[5]  Vincent J. Lynch,et al.  Concurrent Evolution of Antiaging Gene Duplications and Cellular Phenotypes in Long-Lived Turtles , 2021, bioRxiv.

[6]  Vincent J. Lynch,et al.  Pervasive duplication of tumor suppressors in Afrotherians during the evolution of large bodies and reduced cancer risk , 2020, bioRxiv.

[7]  A. Boddy,et al.  Comparative Oncology: New Insights into an Ancient Disease , 2020, iScience.

[8]  Kshitiz,et al.  Comments on Boddy et al. 2020: Available data suggest positive relationship between placental invasion and malignancy , 2020, Evolution, medicine, and public health.

[9]  C. Maley,et al.  Lifetime cancer prevalence and life history traits in mammals , 2020, Evolution, medicine, and public health.

[10]  W. Jetz,et al.  Inferring the mammal tree: Species-level sets of phylogenies for questions in ecology, evolution, and conservation , 2019, PLoS biology.

[11]  P. Upchurch,et al.  The phylogenetic relationships of neosuchian crocodiles and their implications for the convergent evolution of the longirostrine condition , 2019, Zoological Journal of the Linnean Society.

[12]  K. Woolard,et al.  Cancer in wildlife: patterns of emergence , 2018, Nature Reviews Cancer.

[13]  Vincent J. Lynch,et al.  Insights on cancer resistance in vertebrates: reptiles as a parallel system to mammals , 2018, Nature Reviews Cancer.

[14]  João Pedro de Magalhães,et al.  Human Ageing Genomic Resources: new and updated databases , 2017, Nucleic Acids Res..

[15]  Caterina Penone,et al.  AmphiBIO, a global database for amphibian ecological traits , 2017, Scientific Data.

[16]  A. Møller,et al.  Life history, immunity, Peto's paradox and tumours in birds , 2017, Journal of evolutionary biology.

[17]  F. Thomas,et al.  Cancer Prevalence and Etiology in Wild and Captive Animals , 2017, Ecology and Evolution of Cancer.

[18]  J. Schiffman,et al.  Evolution of cancer suppression as revealed by mammalian comparative genomics. , 2017, Current opinion in genetics & development.

[19]  M. Hochberg,et al.  Cancer across the tree of life: cooperation and cheating in multicellularity , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[20]  R. Peto Quantitative implications of the approximate irrelevance of mammalian body size and lifespan to lifelong cancer risk , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[21]  R. A. Pyron,et al.  A phylogeny and revised classification of Squamata, including 4161 species of lizards and snakes , 2013, BMC Evolutionary Biology.

[22]  N. Galtier,et al.  The determinants of the molecular substitution process in turtles , 2013, Journal of evolutionary biology.

[23]  W. Jetz,et al.  The global diversity of birds in space and time , 2012, Nature.

[24]  H. Tuomisto An updated consumer’s guide to evenness and related indices , 2012 .

[25]  A. Pyron,et al.  A large-scale phylogeny of Amphibia including over 2800 species, and a revised classification of extant frogs, salamanders, and caecilians. , 2011, Molecular phylogenetics and evolution.

[26]  C. Maley,et al.  Peto's Paradox: evolution's prescription for cancer prevention. , 2011, Trends in ecology & evolution.

[27]  W. A. Cox,et al.  A Phylogenomic Study of Birds Reveals Their Evolutionary History , 2008, Science.

[28]  J. Sykes,et al.  REPTILE NEOPLASIA AT THE PHILADELPHIA ZOOLOGICAL GARDEN, 1901–2002 , 2006, Journal of zoo and wildlife medicine : official publication of the American Association of Zoo Veterinarians.

[29]  M. Garner,et al.  Reptile neoplasia: a retrospective study of case submissions to a specialty diagnostic service. , 2004, The veterinary clinics of North America. Exotic animal practice.

[30]  K. Strimmer,et al.  APE: Analyses of Phylogenetics and Evolution in R language , 2004, Bioinform..

[31]  E. Paradis,et al.  Analysis of comparative data using generalized estimating equations. , 2002, Journal of theoretical biology.

[32]  L. Nunney,et al.  Lineage selection and the evolution of multistage carcinogenesis , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[33]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

[34]  K. Benirschke,et al.  Nature and rate of neoplasia found in captive wild mammals, birds, and reptiles at necropsy. , 1977, Journal of the National Cancer Institute.

[35]  P. N. Lee,et al.  Cancer and ageing in mice and men. , 1975, British Journal of Cancer.

[36]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[37]  Robert C Thomson,et al.  Sparse supermatrices for phylogenetic inference: taxonomy, alignment, rogue taxa, and the phylogeny of living turtles. , 2010, Systematic biology.

[38]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[39]  Armand M. Leroi,et al.  Cancer selection , 2003, Nature Reviews Cancer.