Evolutionary dynamics of acid resistance in tumors: A mathematical model.

IF 2.6 4区 工程技术 Q1 Mathematics
Prithvi Anickode, Fabio Augusto Milner
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引用次数: 0

Abstract

Acidosis in tumors arises from reprogrammed metabolism and compromised vasculature, creating a harsh, acidic microenvironment that drives the evolutionary selection of acid-resistant cell phenotypes. A mathematical model was proposed to integrate phenotypic evolution, microenvironmental acidification, and tumor density dynamics. Three key mechanisms were incorporated in it: frequency-dependent selection favoring acid-resistant cells below a critical pH, stress-induced phenotypic switching, and a positive feedback loop where resistant cells produce excess acid that intensifies selection pressure. The well-posedness of the model was established. Through numerical simulations across biologically relevant parameter regimes, we identified two therapeutically targetable parameters: the baseline acid clearance rate (a proxy for vascular perfusion) and a protection factor (representing acid-resistance "machinery" effectiveness) as critical bifurcation parameters for resistance evolution. The model exhibits qualitatively distinct dynamics depending on phenotypic plasticity levels. In low-plasticity tumors, both parameters exhibit sharp bifurcations with strong parameter interactions: clearance and protection effects are context-dependent, with therapeutic interventions effective only within specific parameter ranges. In high-plasticity tumors, both parameters produce continuous, monotonic responses with independent, additive effects. These regime-dependent dynamics suggest that treatment strategies should adapt to tumor plasticity: in the former, targeting perfusion alone is typically sufficient, though sequential therapy may be required if the perfusion rate approaches or exceeds the bifurcation threshold, whereas in the latter, treatment might benefit from combination therapies addressing both parameters simultaneously. These findings suggest that a low-dimensional model can identify therapeutically targetable parameters governing resistance evolution, suggesting interventions that may prevent or reverse the harmful effect of acid-resistant phenotypes, which are associated with chemotherapy failure, immune evasion, and metastatic progression.

肿瘤中耐酸的进化动力学:一个数学模型。
肿瘤中的酸中毒源于代谢重编程和脉管系统受损,创造了一个严酷的酸性微环境,推动了耐酸细胞表型的进化选择。提出了一个综合表型进化、微环境酸化和肿瘤密度动态的数学模型。其中包含三个关键机制:频率依赖性选择有利于低于临界pH值的耐酸细胞,压力诱导的表型转换,以及一个正反馈回路,其中耐酸细胞产生过量的酸,从而加剧了选择压力。建立了模型的适定性。通过跨生物学相关参数体系的数值模拟,我们确定了两个治疗可靶向参数:基线酸清除率(血管灌注的代理)和保护因子(代表耐酸“机械”有效性)作为耐药性进化的关键分支参数。该模型表现出依赖于表型可塑性水平的定性不同的动力学。在低可塑性肿瘤中,这两个参数表现出明显的分叉,具有很强的参数相互作用:清除和保护作用依赖于环境,治疗干预仅在特定参数范围内有效。在高塑性肿瘤中,这两个参数产生连续的单调响应,具有独立的加性效应。这些方案依赖的动力学表明,治疗策略应适应肿瘤的可塑性:在前者中,单独靶向灌注通常是足够的,尽管如果灌注率接近或超过分岔阈值可能需要序贯治疗,而在后者中,治疗可能受益于同时处理这两个参数的联合治疗。这些发现表明,低维模型可以识别控制耐药进化的治疗可靶向参数,表明干预措施可以预防或逆转与化疗失败、免疫逃避和转移进展相关的耐酸表型的有害影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Mathematical Biosciences and Engineering
Mathematical Biosciences and Engineering 工程技术-数学跨学科应用
CiteScore
3.90
自引率
7.70%
发文量
586
审稿时长
>12 weeks
期刊介绍: Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing. MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).
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