Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model.
Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model.
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DOI：
10.3390/cells10082009
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发表时间：
2021-08-06
期刊：
影响因子：
6
通讯作者：
Shahriyari L
中科院分区：
文献类型：
--
作者：
Le T;Su S;Shahriyari L
骨肉瘤是一种罕见的癌症，预后很差。然而，就我们所知，目前还没有数学模型来研究化疗对骨肉瘤微环境的影响。在这项研究中，我们开发了一个数据驱动的数学模型来分析在存在最常见的化疗药物的情况下，免疫模式不同的三组骨肉瘤中重要参与者的动力学。结果表明，治疗的开始时间和最佳剂量取决于肿瘤的独特生长速度，这意味着个性化用药的必要性。此外，开发的模型可以被其他人扩展以建立可以推荐特定个体的最佳剂量的模型。由于所有肿瘤都是独一无二的，它们对相同的治疗可能会有不同的反应。因此，有必要单独研究他们的特点，以找到他们的最佳治疗方案。我们建立了最常见的化疗药物与具有独特免疫特征的三组肿瘤的骨肉瘤微环境之间相互作用的数学模型。然后，我们研究了不同治疗方案和不同治疗开始时间的化疗对每个簇中免疫细胞和癌细胞行为的影响。值得注意的是，我们建议了每个簇中肿瘤的最佳药物剂量。结果表明，树突状细胞和HMGB1的丰度在给药时增加，在不给药时减少。辅助性T细胞、细胞毒细胞和干扰素的数量在治疗期间增长，而癌细胞和其他免疫细胞的数量在治疗期间减少。根据该模型，MAP方案在杀癌方面做得很好，而且比阿霉素和顺铂联合或单独使用甲氨蝶呤更有效。结果还表明，在决定治疗细节时，考虑肿瘤的独特生长率是重要的，因为快速生长的肿瘤需要早期开始治疗和高剂量。
Osteosarcoma is a rare type of cancer with poor prognoses. However, to the best of our knowledge, there are no mathematical models that study the impact of chemotherapy treatments on the osteosarcoma microenvironment. In this study, we developed a data driven mathematical model to analyze the dynamics of the important players in three groups of osteosarcoma tumors with distinct immune patterns in the presence of the most common chemotherapy drugs. The results indicate that the treatments’ start times and optimal dosages depend on the unique growth rate of the tumor, which implies the necessity of personalized medicine. Furthermore, the developed model can be extended by others to build models that can recommend individual-specific optimal dosages. Since all tumors are unique, they may respond differently to the same treatments. Therefore, it is necessary to study their characteristics individually to find their best treatment options. We built a mathematical model for the interactions between the most common chemotherapy drugs and the osteosarcoma microenvironments of three clusters of tumors with unique immune profiles. We then investigated the effects of chemotherapy with different treatment regimens and various treatment start times on the behaviors of immune and cancer cells in each cluster. Saliently, we suggest the optimal drug dosages for the tumors in each cluster. The results show that abundances of dendritic cells and HMGB1 increase when drugs are given and decrease when drugs are absent. Populations of helper T cells, cytotoxic cells, and IFN- grow, and populations of cancer cells and other immune cells shrink during treatment. According to the model, the MAP regimen does a good job at killing cancer, and is more effective than doxorubicin and cisplatin combined or methotrexate alone. The results also indicate that it is important to consider the tumor’s unique growth rate when deciding the treatment details, as fast growing tumors need early treatment start times and high dosages.
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DOI：
10.1084/jem.20050915
发表时间：
2005-12-19
期刊：
The Journal of experimental medicine
影响因子：
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作者：
Casares N;Pequignot MO;Tesniere A;Ghiringhelli F;Roux S;Chaput N;Schmitt E;Hamai A;Hervas-Stubbs S;Obeid M;Coutant F;Métivier D;Pichard E;Aucouturier P;Pierron G;Garrido C;Zitvogel L;Kroemer G
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8.8
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发表时间：
2014-11-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
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DOI：
10.1002/wsbm.1461
发表时间：
2019-07-17
影响因子：
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作者：
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