Tumor containment: a more general mathematical analysis.

IF 2.3 4区 数学 Q2 BIOLOGY Journal of Mathematical Biology Pub Date : 2024-03-06 DOI:10.1007/s00285-024-02062-3
Frank Ernesto Alvarez, Yannick Viossat
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Abstract

Clinical and pre-clinical data suggest that treating some tumors at a mild, patient-specific dose might delay resistance to treatment and increase survival time. A recent mathematical model with sensitive and resistant tumor cells identified conditions under which a treatment aiming at tumor containment rather than eradication is indeed optimal. This model however neglected mutations from sensitive to resistant cells, and assumed that the growth-rate of sensitive cells is non-increasing in the size of the resistant population. The latter is not true in standard models of chemotherapy. This article shows how to dispense with this assumption and allow for mutations from sensitive to resistant cells. This is achieved by a novel mathematical analysis comparing tumor sizes across treatments not as a function of time, but as a function of the resistant population size.

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肿瘤遏制:更普遍的数学分析。
临床和临床前数据表明,以温和的、针对患者的剂量治疗某些肿瘤可能会延缓耐药性,延长生存时间。最近,一个包含敏感和耐药肿瘤细胞的数学模型确定了在哪些条件下,以遏制而非根除肿瘤为目标的治疗确实是最佳的。然而,该模型忽略了从敏感细胞到耐药细胞的突变,并假设敏感细胞的生长速度不会随着耐药细胞群的增加而增加。而后者在标准化疗模型中并不存在。本文展示了如何摒弃这一假设,允许敏感细胞向耐药细胞突变。这是通过一种新颖的数学分析来实现的,这种分析不是将不同疗法的肿瘤大小作为时间函数,而是作为耐药群体大小的函数进行比较。
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来源期刊
CiteScore
3.30
自引率
5.30%
发文量
120
审稿时长
6 months
期刊介绍: The Journal of Mathematical Biology focuses on mathematical biology - work that uses mathematical approaches to gain biological understanding or explain biological phenomena. Areas of biology covered include, but are not restricted to, cell biology, physiology, development, neurobiology, genetics and population genetics, population biology, ecology, behavioural biology, evolution, epidemiology, immunology, molecular biology, biofluids, DNA and protein structure and function. All mathematical approaches including computational and visualization approaches are appropriate.
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