Weill Cornell Graduate School of Medical Sciences, New York, NY 10021, USA.
Sci Transl Med. 2011 Jul 6;3(90):90ra59. doi: 10.1126/scitranslmed.3002356.
Non-small cell lung cancers (NSCLCs) that harbor mutations within the epidermal growth factor receptor (EGFR) gene are sensitive to the tyrosine kinase inhibitors (TKIs) gefitinib and erlotinib. Unfortunately, all patients treated with these drugs will acquire resistance, most commonly as a result of a secondary mutation within EGFR (T790M). Because both drugs were developed to target wild-type EGFR, we hypothesized that current dosing schedules were not optimized for mutant EGFR or to prevent resistance. To investigate this further, we developed isogenic TKI-sensitive and TKI-resistant pairs of cell lines that mimic the behavior of human tumors. We determined that the drug-sensitive and drug-resistant EGFR-mutant cells exhibited differential growth kinetics, with the drug-resistant cells showing slower growth. We incorporated these data into evolutionary mathematical cancer models with constraints derived from clinical data sets. This modeling predicted alternative therapeutic strategies that could prolong the clinical benefit of TKIs against EGFR-mutant NSCLCs by delaying the development of resistance.
非小细胞肺癌 (NSCLC) 中存在表皮生长因子受体 (EGFR) 基因突变的患者对酪氨酸激酶抑制剂 (TKI) 吉非替尼和厄洛替尼敏感。不幸的是，所有接受这些药物治疗的患者都会产生耐药性，最常见的原因是 EGFR 内的继发突变 (T790M)。由于这两种药物都是针对野生型 EGFR 开发的，我们假设目前的给药方案没有针对突变型 EGFR 进行优化，也没有预防耐药性。为了进一步研究这一点，我们开发了模拟人类肿瘤行为的同源 TKI 敏感和 TKI 耐药细胞系对。我们确定，药物敏感和药物耐药的 EGFR 突变细胞表现出不同的生长动力学，耐药细胞的生长速度较慢。我们将这些数据纳入到具有从临床数据集推导而来的约束条件的进化数学癌症模型中。该模型预测了替代治疗策略，可以通过延迟耐药的发展来延长 TKI 针对 EGFR 突变型 NSCLC 的临床获益。
