Bieuville Margaux, Tissot Tazzio, Robert Alexandre, Henry Pierre-Yves, Pavard Samuel
Eco-Anthropologie (EA UMR 7206), MNHN, CNRS Université Paris-Diderot Paris France.
Agent, Interaction and complexity (AIC) research group Southampton University Southampton UK.
Evol Appl. 2023 Mar 1;16(3):609-624. doi: 10.1111/eva.13514. eCollection 2023 Mar.
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.
当前的致癌理论认为，肿瘤起源于细胞谱系，这些细胞谱系会依次积累（表观）突变，逐渐将健康细胞转变为致癌细胞。虽然这些模型得到了一些实证支持，但它们对物种内特定年龄的癌症发病率和物种间癌症患病率的预测能力较弱。值得注意的是，在人类和实验啮齿动物中，已发现老年时癌症发病率会下降（有时甚至降低）。此外，主要的肿瘤发生理论模型预测，大型和/或长寿物种的癌症风险应该增加，但这一观点并未得到实证数据的支持。在此，我们探讨细胞衰老能否解释这些不一致的实证模式这一假说。更确切地说，我们假设在死于癌症和死于（其他）与衰老相关的原因之间存在权衡。在细胞层面，这种生物体死亡组成部分之间的权衡将由衰老细胞的积累介导。在这个框架中，受损细胞可以要么经历凋亡，要么进入衰老状态。凋亡细胞会导致代偿性增殖，这与癌症风险增加相关，而衰老细胞的积累则会导致与衰老相关的死亡。为了检验我们的框架，我们构建了一个确定性模型，该模型首先描述细胞如何受损、经历凋亡或进入衰老状态。然后，我们将这些细胞动力学转化为一个复合的生物体生存指标，该指标还整合了生活史特征。我们解决了与我们的框架相关的四个不同问题：细胞衰老能否具有适应性，我们模型的预测是否反映了在哺乳动物物种中观察到的流行病学模式，物种大小对这些答案有何影响，以及去除衰老细胞会发生什么？重要的是，我们发现细胞衰老可以优化终身繁殖成功率。此外，我们发现生活史特征在塑造细胞权衡方面起着重要作用。总体而言，我们证明将细胞生物学知识与生态进化原理相结合对于解决部分癌症谜题至关重要。
