EGFR突变的肺癌中药物代谢动力学过程和不同的给药方案对厄洛替尼获得性耐药的动力学的作用 # j$ u6 a! A8 ~* OEffects of Pharmacokinetic Processes and Varied Dosing Schedules on the Dynamics of Acquired Resistance to Erlotinib in EGFR-Mutant Lung Cancer 5 @3 S0 Y0 Y& C% }中文摘要: 4 U( u2 N2 l+ Y) O% ^) x 引言：厄洛替尼（Tarceva）是一种表皮生长因子受体（EGFR）酪氨酸激酶抑制剂，可以有效治疗EGFR突变的非小细胞肺癌。但是，在EGFR内第二个突变位点（T790M）所导致的获得性耐药的产生仍然是成功治疗的一个障碍。 方法：我们使用数学模型和现有的临床试验的数据来预测不同的药物代谢动力学参数（代谢快vs 代谢慢）和给药方案（低剂量vs高剂量；补服和不补服漏服药物）是如何影响不同类型的肿瘤细胞群产生由T790M介导的耐药。 结果：我们发现高剂量冲击治疗和低剂量持续治疗都可以最大程度的抑制耐药的产生，无论是之前出现的耐药还是之后出现的耐药。在药物代谢较快的患者耐药的可能性高于药物代谢较慢的患者，提示可能存在有一种机制（到目前还未发现）影响患者产生获得性耐药。在因为药物毒性而需要调整药物剂量时，在使用标准每日剂量（150 mg/d）和100 mg/d与150 mg/d交替使用的患者之间观察到疗效和耐药动力学之间差异很小。漏服药物后会更快导致耐药，即使在尝试补服药物之后也是如此。 结论：对于现有的和新的激酶抑制剂，可以使用这一新的框架来合理快速地设计最优的给药策略，以便将获得性耐药的产生降低到最小程度。 $ X6 p8 n$ ` w英文摘要: ( g; U: y" N, ~" l Introduction: Erlotinib (Tarceva) is an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, which effectively targets EGFR-mutant driven non–small-cell lung cancer. However, the evolution of acquired resistance because of a second-site mutation (T790M) within EGFR remains an obstacle to successful treatment. Methods: We used mathematical modeling and available clinical trial data to predict how different pharmacokinetic parameters (fast versus slow metabolism) and dosing schedules (low dose versus high dose; missed doses with and without make-up doses) might affect the evolution of T790M-mediated resistance in mixed populations of tumor cells. Results: We found that high-dose pulses with low-dose continuous therapy impede the development of resistance to the maximum extent, both pre- and post-emergence of resistance. The probability of resistance is greater in fast versus slow drug metabolizers, suggesting a potential mechanism, unappreciated to date, influencing acquired resistance in patients. In case of required dose modifications because of toxicity, little difference is observed in terms of efficacy and resistance dynamics between the standard daily dose (150 mg/d) and 150 mg/d alternating with 100 mg/d. Missed doses are expected to lead to resistance faster, even if make-up doses are attempted. Conclusions: For existing and new kinase inhibitors, this novel framework can be used to rationally and rapidly design optimal dosing strategies to minimize the development of acquired resistance.
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