Modeling multi-mutation and drug resistance: analysis of some case studies.

Q1 Mathematics
Mitra Shojania Feizabadi
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引用次数: 24

Abstract

Background: Drug-induced resistance is one the major obstacles that may lead to therapeutic failure during cancer treatment. Different genetic alterations occur when tumor cells divide. Among new generations of tumor cells, some may express intrinsic resistance to a specific chemotherapeutic agent. Also, some tumor cells may carry a gene that can develop resistance induced by the therapeutic drug. The methods by which the therapeutic approaches need to be revised in the occurrence of drug induced resistance is still being explored. Previously, we introduced a model that expresses only intrinsic drug resistance in a conjoint normal-tumor cell setting. The focus of this work is to expand our previously reported model to include terms that can express both intrinsic drug resistance and drug-induced resistance. Additionally, we assess the response of the cell population as a function of time under different treatment strategies and discuss the outcomes.

Methods: The model introduced is expressed in the format of coupled differential equations which describe the growth pattern of the cells. The dynamic of the cell populations is simulated under different treatment cases. All computational simulations were executed using Mathematica v7.0.

Results: The outcome of the simulations clearly demonstrates that while some therapeutic strategies can overcome or control the intrinsic drug resistance, they may not be effective, and are even to some extent damaging, if the administered drug creates resistance by itself.

Conclusion: In the present study, the evolution of the cells in a conjoint setting, when the system expresses both intrinsic and induced resistance, is mathematically modeled. Followed by a set of computer simulations, the different growing patterns that can be created based on choices of therapy were examined. The model can still be improved by considering other factors including, but not limited to, the nature of the cancer growth, the level of toxicity that the body can tolerate, or the strength of the patient's immune system.

Abstract Image

Abstract Image

多突变和耐药性建模:一些案例分析。
背景:在癌症治疗过程中,药物耐药是可能导致治疗失败的主要障碍之一。当肿瘤细胞分裂时,会发生不同的基因改变。在新一代的肿瘤细胞中,有些可能对特定的化疗药物表现出内在的耐药性。此外,一些肿瘤细胞可能携带一种基因,这种基因可以产生治疗药物诱导的耐药性。在药物诱导耐药的发生中,需要修改的治疗方法仍在探索中。在此之前,我们介绍了一个在正常肿瘤细胞联合环境中仅表达内在耐药性的模型。这项工作的重点是扩展我们之前报道的模型,包括可以表达内在耐药性和药物诱导耐药性的术语。此外,我们评估了不同治疗策略下细胞群的反应作为时间的函数,并讨论了结果。方法:引入的模型以描述细胞生长模式的耦合微分方程的形式表示。模拟了不同处理条件下细胞群的动态变化。所有计算模拟均使用Mathematica v7.0进行。结果:模拟结果清楚地表明,虽然一些治疗策略可以克服或控制内在耐药性,但如果所给药物本身产生耐药性,它们可能无效,甚至在一定程度上具有破坏性。结论:在本研究中,当系统同时表达固有和诱导抗性时,细胞在联合环境中的进化被数学建模。接着是一组计算机模拟,研究了基于治疗选择而产生的不同生长模式。该模型仍然可以通过考虑其他因素来改进,包括但不限于,癌症生长的性质,身体可以忍受的毒性水平,或患者免疫系统的强度。
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
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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