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J Pharmacol Toxicol Methods. 2018 Jul - Aug;92:57-66. doi: 10.1016/j.vascn.2018.03.001. Epub 2018 Mar 14.

A spontaneous metastatic mathematical model in mice for screening anti-metastatic agents.

Author information

1
Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, PR China; Center for ADR Monitoring of Jiangsu, Nanjing 210002, Jiangsu, PR China.
2
Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, PR China.
3
School of Science, Tianjin University of Technology and Education, Tianjin 300222, PR China.
4
Department of Medical Oncology, Cancer Hospital, Fudan University, Shanghai 200433, PR China.
5
Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, PR China; Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine (TCM) Prevention and Treatment of Tumor, Nanjing 210023, PR China.
6
Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, PR China; Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine (TCM) Prevention and Treatment of Tumor, Nanjing 210023, PR China. Electronic address: chenwx@njucm.edu.cn.
7
Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing 210023, PR China; Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine (TCM) Prevention and Treatment of Tumor, Nanjing 210023, PR China. Electronic address: profyinlu@163.com.

Abstract

PURPOSE:

A computational model based on clinical data from pancreatic cancer patients has been successfully created and used for predicting tumor sizes in primary and metastasis sites and survival time from kinetics of tumor cells, such as growth rate, metastasis rate and mutation rate, etc. Whether this computational model could be fitted or necessary modification of some parameters for fitting in mice is unknown. Here, we developed a computational model in mice for spontaneous metastasis to simulate the process of tumor metastasis based on the mathematical frameworks.

METHODS:

The spontaneous melanoma metastasis model in mice was used for assessing the fitting accuracy between the mathematical model and the experimental data and evaluating the efficacy of anticancer agents, as well as the invasion assay.

RESULTS:

According to the modified model, most of parameters including growth rate, mutation rate and metastasis rate, which were used to describe the whole metastatic course in mice were calculated based on the experimental analysis. Furthermore, only measurement of the growth rate of cancer in the primary site was required to predict the survival time. Our predicted results of the overall survival (OS) extension of mice were close to the clinical outcomes after treated with four clinical intervention strategies of CVD, Paclitaxel, Dartmouth and Temozolomide. And predictive efficacy of anticancer drug using the model matches well the factual experimental data in mice.

CONCLUSIONS:

The mathematical model is more economical and efficient for evaluating the tumor metastasis and could be used to screen the anti-cancer and anti-metastatic medicine by shortening the periods of assessment of OS extension in preclinical trials.

KEYWORDS:

Anti-cancer drug assessing; Clinical intervention strategies; Mathematical model; Overall survival time; Spontaneous metastasis model

PMID:
29550466
DOI:
10.1016/j.vascn.2018.03.001
[Indexed for MEDLINE]

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