摘要
Previous study has shown that dopamine D1 receptor(D1DR)agonists,fenoldopam(FEN)and l-stepholidine(l-SPD),have inhibitory effects on breast cancer lung metastasis.To quantitatively describe and predict the pharmacodynamic(PD)properties of FEN and l-SPD and to explore the PD model structure of cancer metastasis treating drugs,we used the data of lung metastasis in 4T1 breast cancer mice under the treatment of either FEN or l-SPD,and established a PD model.The PD model assumed an exponential growth for both primary tumor and metastasis.The primary tumor emitted cells to form metastases,and the cell emitting rate was proportional to power form of the primary tumor weight.The total number of lung metastasis was set as the target value.D1DR agonists inhibited metastasis by inhibiting cell emitting rate instead of the growth rate of primary tumor or metastasis.The model results showed that the decrease in the number of lung metastases was roughly proportional to the square of the drug dose.The values of PD coefficient reflected the inhibitory ability of the drugs,and that of l-SPD(0.274 kg/mg)was greater than that of FEN(0.0393 kg/mg).This PD model can quantitatively describe the effects of FEN and l-SPD on the progression of lung metastasis in 4T1 primary breast cancer mice and can predict the time course of drug efficacy at multiple doses,providing a reference for PD model structure of other drugs for cancer metastasis indication.
在本实验室之前的研究中,我们证明了多巴胺D1受体(dopamineD1receptor,D1DR)激动剂非诺多泮(fenoldopam,FEN)和左旋千金藤啶碱(l-stepholidine,l-SPD)具有抑制乳腺癌肺转移的作用。为了定量描述FEN和l-SPD的药效学性质并预测其药物作用,以及探索治疗癌症转移药物的药效动力学(pharmacodynamics,PD)模型结构,本研究利用FEN和l-SPD治疗乳腺癌肺脏转移的数据,建立了以转移灶总数为目标量的PD模型。该模型假设乳腺原位肿瘤与肺脏转移灶均以指数生长,原位瘤发射细胞以形成远端转移灶,且原位细胞发射速率与原位瘤肿瘤的幂成正比;D1DR激动剂通过抑制原位肿瘤细胞的发射速率来抑制转移发生,且药物并不影响原位瘤或转移灶的生长速率。模型结果表明,肺脏转移灶数量的降低大致与药物剂量的平方成正比,且l-SPD的药效系数(0.274kg/mg)大于FEN(0.0393kg/mg)。此PD模型能够定量描述FEN和l-SPD对乳腺癌肺转移疾病进展的影响,并且能够预测多个剂量下药物药效的时间过程。该研究对抗肿瘤转移药物的PD模型结构提供参考。
基金
Natural Science Foundation of Beijing(Grant No.7192100).
作者简介
Corresponding author:周田彦,Tel.:+86-10-82801717,E-mail:tianyanzhou@bjmu.edu.cn
