Preclinical Prediction of Resistance and Optimization of Sequential Therapy for ALK-positive Lung Cancer Using Next-generation ALK Inhibitors
Preclinical Prediction of Resistance and Optimization of Sequential Therapy for ALK-positive Lung Cancer Using Next-generation ALK Inhibitors
Semba, K.; Takei, Y.; Kuroiwa, H.; Arai, C.; Doi, Y.
AbstractBackground Anaplastic lymphoma kinase (ALK) gene rearrangements occur in approximately 5% of non-small cell lung cancers (NSCLCs). Although ALK tyrosine kinase inhibitors provide substantial clinical benefits, acquired resistance-conferring mutations frequently emerge, leading to disease progression. Preclinical prediction of these mutations might help guide the development of more effective sequential treatment strategies prior to clinical application. Objective To predict the emergence of resistance mutations to the investigational ALK inhibitors zotizalkib (TPX-0131), gilteritinib (ASP2215), and neladalkib (NVL-655) following resistance to first-line alectinib and assess the potential of these drugs as second-line therapies. Methods A polymerase chain reaction (PCR)-based mutagenesis system was used to introduce random mutations into ALK cDNA harboring representative alectinib-resistant mutations. Mutant libraries were expressed in Ba/F3 cells, which were exposed to each inhibitor. Drug-resistant clones were isolated, sequenced, and evaluated for drug sensitivity using viability assays and immunoblotting. Results Several resistance mutations against zotizalkib, gilteritinib, and neladalkib were identified. Sequential use of these agents effectively suppressed all predicted resistance patterns with G1202R or I1171N. Conclusions This PCR-based platform provides a valuable approach for anticipating resistance mutations and guiding the design of optimized sequential therapies. Zotizalkib, gilteritinib, and neladalkib might represent promising alternatives to lorlatinib as second-line treatments for ALK-positive NSCLC.