Tyczynska Weh Malgorzata, Kumar Pragya, Marusyk Viktoriya, Marusyk Andriy, Basanta David
Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612.
Cancer Biology Ph.D. Program, Department of Molecular Biosciences, University of South Florida, Tampa, FL 33612.
Proc Natl Acad Sci U S A. 2025 Jul;122(26):e2427070122. doi: 10.1073/pnas.2427070122. Epub 2025 Jun 26.
Darwinian evolution results from an interplay between stochastic diversification of heritable phenotypes, impacting the chance of survival and reproduction, and fitness-based selection. The ability of populations to evolve and adapt to environmental changes depends on rates of mutational diversification and the distribution of fitness effects of random mutations. In turn, the distribution of fitness effects of stochastic mutations can be expected to depend on the adaptive state of a population. To systematically study the impact of the interplay between the adaptive state of a population on the ability of asexual populations to adapt, we used a spatial agent-based model of a neoplastic population adapting to a selection pressure of continuous exposure to targeted therapy. We found favorable mutations were overrepresented at the extinction bottleneck but depleted at the adaptive peak. The model-based predictions were tested using an experimental cancer model of an evolution of resistance to a targeted therapy. Consistent with the model's prediction, we found that enhancement of the mutation rate was highly beneficial under therapy but moderately detrimental under the baseline conditions. Our results highlight the importance of considering population fitness in evaluating the fitness distribution of random mutations and support the potential therapeutic utility of restricting mutational variability.
达尔文式进化源于可遗传表型的随机多样化、影响生存和繁殖机会以及基于适应性的选择之间的相互作用。种群进化和适应环境变化的能力取决于突变多样化的速率以及随机突变的适应性效应分布。反过来,随机突变的适应性效应分布预计取决于种群的适应状态。为了系统地研究种群适应状态之间的相互作用对无性繁殖种群适应能力的影响,我们使用了一个基于空间主体的肿瘤种群模型,该模型适应持续接受靶向治疗的选择压力。我们发现有利突变在灭绝瓶颈处过度代表,但在适应峰值处减少。使用对靶向治疗产生抗性进化的实验性癌症模型对基于模型的预测进行了测试。与模型预测一致,我们发现提高突变率在治疗下非常有益,但在基线条件下有适度的不利影响。我们的结果强调了在评估随机突变的适应性分布时考虑种群适应性的重要性,并支持限制突变变异性的潜在治疗效用。