Doi Yuta, Tagaya Hiroaki, Noge Ayaka, Semba Kentaro
Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo, 162-8480, Japan.
Translational Research Center, Fukushima Medical University, Hikarigaoka, Fukushima, 960-1295, Japan.
Target Oncol. 2022 Nov;17(6):695-707. doi: 10.1007/s11523-022-00919-5. Epub 2022 Oct 6.
Chromosomal aberrations involving the anaplastic lymphoma kinase (ALK) gene have been observed in approximately 4% of patients with non-small cell lung cancer (NSCLC). Although these patients clinically benefit from treatment with various ALK tyrosine kinase inhibitors (ALK-TKIs), none of these can inhibit the development of resistance mutations. Considering inevitable drug resistance and the variety of available ALK-TKIs, it is necessary to predict the pattern of drug-resistance mutations to determine the optimal treatment strategy.
We aimed to establish a polymerase chain reaction (PCR)-based system to predict the development of resistance mutations against ALK-TKIs and identify therapeutic strategies using the upcoming ALK-TKIs repotrectinib (TPX-0005) and ensartinib (X-396) following recurrence on first-line alectinib treatment for ALK-positive NSCLC.
An error-prone PCR-based method for predicting drug resistance mutations was established and the half-maximal inhibitory concentration (IC) values of the predicted ALK mutations were evaluated in a Ba/F3 cell-based assay.
We predicted several resistance mutations against repotrectinib and ensartinib, and demonstrated that the next-generation ALK-TKI TPX-0131, was active against repotrectinib-resistant mutations and that the FLT3 inhibitor gilteritinib was active against ensartinib-resistant mutations.
We developed a PCR-based system for predicting drug resistance mutations. When this system was applied to repotrectinib and ensartinib, the results suggested that these drugs can be used for the second-line treatment of ALK-positive NSCLC. Predicting resistance mutations against TKIs will provide useful information to aid in the development of effective therapeutic strategies.
在大约4%的非小细胞肺癌(NSCLC)患者中观察到涉及间变性淋巴瘤激酶(ALK)基因的染色体畸变。尽管这些患者从各种ALK酪氨酸激酶抑制剂(ALK-TKIs)治疗中临床获益,但这些药物均无法抑制耐药突变的发生。考虑到不可避免的耐药性以及可用的ALK-TKIs种类繁多,预测耐药突变模式以确定最佳治疗策略很有必要。
我们旨在建立一种基于聚合酶链反应(PCR)的系统,以预测对ALK-TKIs耐药突变的发生,并确定在一线使用阿来替尼治疗ALK阳性NSCLC复发后,使用即将上市的ALK-TKIs瑞波替尼(TPX-0005)和恩扎替尼(X-396)的治疗策略。
建立了一种基于易错PCR的预测耐药突变的方法,并在基于Ba/F3细胞的试验中评估预测的ALK突变的半数最大抑制浓度(IC)值。
我们预测了几种针对瑞波替尼和恩扎替尼的耐药突变,并证明下一代ALK-TKI TPX-0131对瑞波替尼耐药突变有活性,FLT3抑制剂吉列替尼对恩扎替尼耐药突变有活性。
我们开发了一种基于PCR的预测耐药突变的系统。当该系统应用于瑞波替尼和恩扎替尼时,结果表明这些药物可用于ALK阳性NSCLC的二线治疗。预测针对TKIs的耐药突变将为制定有效的治疗策略提供有用信息。