Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression

Abstract The intrinsic risk of cancer increases with body size and longevity; however, big long‐lived species do not exhibit this increase, a contradiction named Peto's paradox. Five hypotheses potentially resolving this paradox were modeled using the multistage model of carcinogenesis. The fiv...

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Published in:Evolutionary Applications
Main Author: Nunney, Leonard
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2020
Subjects:
Online Access:http://dx.doi.org/10.1111/eva.12993
https://onlinelibrary.wiley.com/doi/pdf/10.1111/eva.12993
https://onlinelibrary.wiley.com/doi/full-xml/10.1111/eva.12993
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spelling crwiley:10.1111/eva.12993 2024-09-15T18:00:03+00:00 Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression Nunney, Leonard 2020 http://dx.doi.org/10.1111/eva.12993 https://onlinelibrary.wiley.com/doi/pdf/10.1111/eva.12993 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/eva.12993 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Evolutionary Applications volume 13, issue 7, page 1581-1592 ISSN 1752-4571 1752-4571 journal-article 2020 crwiley https://doi.org/10.1111/eva.12993 2024-08-09T04:19:38Z Abstract The intrinsic risk of cancer increases with body size and longevity; however, big long‐lived species do not exhibit this increase, a contradiction named Peto's paradox. Five hypotheses potentially resolving this paradox were modeled using the multistage model of carcinogenesis. The five hypotheses were based on (1) intrinsic changes in metabolic rate with body size; adaptive increase in immune policing of (2) cancer cells or (3) cells with driver mutations; or adaptive increase in cancer suppression via (4) decreased somatic mutation rate, or (5) increased genetic control. Parameter changes needed to stabilize cancer risk in three types of cancer were estimated for tissues scaled from mouse size and longevity to human and blue whale levels. The metabolic rate hypothesis alone was rejected due to a conflict between the required interspecific effect with the observed intraspecific effect of size on cancer risk, but some metabolic change was optionally incorporated in the other models. Necessary parameter changes in immune policing and somatic mutation rate far exceeded values observed; however, natural selection increasing the genetic suppression of cancer was generally consistent with data. Such adaptive increases in genetic control of cancers in large and/or long‐lived animals raise the possibility that nonmodel animals will reveal novel anticancer mechanisms. Article in Journal/Newspaper Blue whale Wiley Online Library Evolutionary Applications 13 7 1581 1592
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description Abstract The intrinsic risk of cancer increases with body size and longevity; however, big long‐lived species do not exhibit this increase, a contradiction named Peto's paradox. Five hypotheses potentially resolving this paradox were modeled using the multistage model of carcinogenesis. The five hypotheses were based on (1) intrinsic changes in metabolic rate with body size; adaptive increase in immune policing of (2) cancer cells or (3) cells with driver mutations; or adaptive increase in cancer suppression via (4) decreased somatic mutation rate, or (5) increased genetic control. Parameter changes needed to stabilize cancer risk in three types of cancer were estimated for tissues scaled from mouse size and longevity to human and blue whale levels. The metabolic rate hypothesis alone was rejected due to a conflict between the required interspecific effect with the observed intraspecific effect of size on cancer risk, but some metabolic change was optionally incorporated in the other models. Necessary parameter changes in immune policing and somatic mutation rate far exceeded values observed; however, natural selection increasing the genetic suppression of cancer was generally consistent with data. Such adaptive increases in genetic control of cancers in large and/or long‐lived animals raise the possibility that nonmodel animals will reveal novel anticancer mechanisms.
format Article in Journal/Newspaper
author Nunney, Leonard
spellingShingle Nunney, Leonard
Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
author_facet Nunney, Leonard
author_sort Nunney, Leonard
title Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
title_short Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
title_full Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
title_fullStr Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
title_full_unstemmed Resolving Peto’s paradox: Modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
title_sort resolving peto’s paradox: modeling the potential effects of size‐related metabolic changes, and of the evolution of immune policing and cancer suppression
publisher Wiley
publishDate 2020
url http://dx.doi.org/10.1111/eva.12993
https://onlinelibrary.wiley.com/doi/pdf/10.1111/eva.12993
https://onlinelibrary.wiley.com/doi/full-xml/10.1111/eva.12993
genre Blue whale
genre_facet Blue whale
op_source Evolutionary Applications
volume 13, issue 7, page 1581-1592
ISSN 1752-4571 1752-4571
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1111/eva.12993
container_title Evolutionary Applications
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