Quantifying assays: inhibition of signalling pathways of cancer.

IF 0.8 4区 数学 Q4 BIOLOGY Mathematical Medicine and Biology-A Journal of the Ima Pub Date : 2023-09-15 DOI:10.1093/imammb/dqad005
Roumen Anguelov, G Manjunath, Avulundiah E Phiri, Trevor T Nyakudya, Priyesh Bipath, June C Serem, Yvette N Hlophe
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Abstract

Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell's viability, cell division and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired inhibition qualities often show great variability across experiments, and it is imperative to diminish the effects of such variability while inferences are drawn. In this paper, we propose the study of experimental data through the lenses of a mathematical model depicting the inhibition mechanism and the activation-inhibition dynamics. The method is exemplified through assay data obtained from an experimental study of the inhibition of the chemokine receptor 4 (CXCR4) and chemokine ligand 12 (CXCL12) signalling pathway of melanoma cells. The quantitative analysis is conducted as a two step process: (i) deriving theoretically from the model the cell viability as a function of time depending on several parameters; (ii) estimating the values of the parameters by using the experimental data. The cell viability is obtained as a function of concentration of the inhibitor and time, thus providing a comprehensive characterization of the potential therapeutic effect of the considered inhibitor, e.g. $IC_{50}$ can be computed for any time point.

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量化试验:抑制癌症信号通路。
抑制信号通路涉及控制癌细胞的存活、分裂和死亡等细胞过程。为了解受试药物的分子结构是否具有理想的抑制效果而制定的检测方案往往在不同实验中表现出很大的差异性,因此在进行推断时必须减少这种差异性的影响。在本文中,我们提出通过描述抑制机制和活化-抑制动态的数学模型来研究实验数据。该方法通过对抑制黑色素瘤细胞趋化因子受体 4(CXCR4)和趋化因子配体 12(CXCL12)信号通路的实验研究中获得的检测数据进行举例说明。定量分析分两步进行:(i) 根据模型从理论上推导出细胞存活率与多个参数有关的时间函数;(ii) 利用实验数据估算参数值。细胞存活率是抑制剂浓度和时间的函数,因此可以全面描述所考虑抑制剂的潜在治疗效果,例如可以计算任何时间点的 $IC_{50}$。
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
期刊最新文献
A generalized order mixture model for tracing connectivity of white matter fascicles complexity in brain from diffusion MRI. A dynamical model of TGF-β activation in asthmatic airways. Quantifying assays: inhibition of signalling pathways of cancer. Discrete and continuum models for the coevolutionary dynamics between CD8+ cytotoxic T lymphocytes and tumour cells. COVID-19 immunotherapy: a mathematical model.
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