Modeling of senescent cell dynamics predicts a late‐life decrease in cancer incidence. (1st March 2023)

• Record Type: Journal Article
• Authors: Bieuville, Margaux; Tissot, Tazzio; Robert, Alexandre; Henry, Pierre‐Yves; Pavard, Samuel
• Is Part Of: Evolutionary applications. Volume 16:Number 3(2023)
• Page Start: 609
• Page End: 624
• Publication Date: 2023-03-01
• Subjects: ageing -- cancer -- demography -- evolution -- life‐history traits -- Peto's paradox -- senescent cells; Evolution (Biology) -- Periodicals; Genetics -- Periodicals; Natural selection -- Periodicals; Ecology -- Periodicals; 576.8
• DOI: 10.1111/eva.13514
• Languages: English
• ISSNs: 1752-4571

Abstract

Abstract: Current oncogenic theories state that tumors arise from cell lineages that sequentially accumulate (epi)mutations, progressively turning healthy cells into carcinogenic ones. While those models found some empirical support, they are little predictive of intraspecies age‐specific cancer incidence and of interspecies cancer prevalence. Notably, in humans and lab rodents, a deceleration (and sometimes decline) of cancer incidence rate has been found at old ages. Additionally, dominant theoretical models of oncogenesis predict that cancer risk should increase in large and/or long‐lived species, which is not supported by empirical data. Here, we explore the hypothesis that cellular senescence could explain those incongruent empirical patterns. More precisely, we hypothesize that there is a trade‐off between dying of cancer and of (other) ageing‐related causes. This trade‐off between organismal mortality components would be mediated, at the cellular scale, by the accumulation of senescent cells. In this framework, damaged cells can either undergo apoptosis or enter senescence. Apoptotic cells lead to compensatory proliferation, associated with an excess risk of cancer, whereas senescent cell accumulation leads to ageing‐related mortality. To test our framework, we build a deterministic model that first describes how cells get damaged, undergo apoptosis, or enter senescence. We then translate those cellular dynamics into a compound organismal survival metric also integrating life‐history traits. We address four different questions linked to our framework: can cellular senescence be adaptive, do the predictions of our model reflect epidemiological patterns observed among mammal species, what is the effect of species sizes on those answers, and what happens when senescent cells are removed? Importantly, we find that cellular senescence can optimize lifetime reproductive success. Moreover, we find that life‐history traits play an important role in shaping the cellular trade‐offs. Overall, we demonstrate that integrating cellular biology knowledge with eco‐evolutionary principles is crucial to solve parts of the cancer puzzle.