Quantification of the Synergistic Inhibitory Effects of an Oncolytic Herpes Virus Plus Paclitaxel on Anaplastic Thyroid Cancer Cells

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-11-21 DOI:10.1155/cplx/3899849
Anna Park, Jong Hyuk Byun, Il Hyo Jung, Shingo Iwami, Kwang Su Kim
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Abstract

Conventional synergy theory explains the inhibitory effects of drug combinations at specific times. Determining the magnitude of inhibition is crucial for exploring the synergy effect. In the results of previous studies, the Chou–Talalay multiple drug effect analysis demonstrated that the combination of a mutant oncolytic herpes virus (G207) and the chemotherapeutic agent (paclitaxel) is the most effective strategy for treating anaplastic thyroid cancer, compared to other combinations such as G207 and NV1023 or paclitaxel and doxorubicin. However, the mechanism behind the synergy effect of G207 and paclitaxel remains unknown, and measuring the synergy effect over time is challenging and expensive. In this study, we formulated a mathematical model to quantify the synergy of G207, paclitaxel, and both over time using the dataset. We conducted a Bayesian estimation of tumor cell proliferation over 16 days using Markov chain Monte Carlo sampling. The Bliss independence was incorporated into the model to compare the observed and expected responses to combination therapy. The expected antitumor effect was significantly lower than the experimental data, suggesting a synergistic effect. Our result showed that the antitumor effect was influenced by the rate of inhibition of tumor growth and the absolute growth delay. Additionally, we found that combination therapy achieved an additional 24% antitumoral effect and a 12-day delay in cell growth. This modeling approach suggests the possibility of quantifying synergistic effects.

Abstract Image

肿瘤溶解性疱疹病毒与紫杉醇对无性甲状腺癌细胞协同抑制作用的定量分析
传统的协同作用理论解释了药物组合在特定时间的抑制作用。确定抑制作用的大小是探索协同效应的关键。在以往的研究结果中,Chou-Talalay 多药效应分析表明,与其他组合(如 G207 和 NV1023 或紫杉醇和多柔比星)相比,突变体溶瘤疱疹病毒(G207)和化疗药物(紫杉醇)的组合是治疗无性甲状腺癌最有效的策略。然而,G207 和紫杉醇的协同效应背后的机制仍不清楚,而且随着时间的推移测量协同效应具有挑战性且成本高昂。在本研究中,我们利用数据集建立了一个数学模型,以量化 G207、紫杉醇和两者随时间变化的协同效应。我们使用马尔科夫链蒙特卡洛抽样对 16 天内的肿瘤细胞增殖进行了贝叶斯估计。在模型中加入了布利斯独立性,以比较联合疗法的观察反应和预期反应。预期抗肿瘤效果明显低于实验数据,这表明存在协同效应。我们的研究结果表明,抗肿瘤效果受肿瘤生长抑制率和绝对生长延迟的影响。此外,我们还发现,联合疗法的抗肿瘤效果提高了 24%,细胞生长延迟了 12 天。这种建模方法为量化协同效应提供了可能。
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来源期刊
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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