The correlation between crizotinib efficacy and molecular heterogeneity by next-generation sequencing in non-small cell lung cancer

Tangfeng Lv, Qian Zou, Zhengbo Song, Hongbing Liu, Qiming Wang, Yong Song


Background: Non-small cell lung cancer (NSCLC) patients with EML4-ALK fusion exhibited various durations of response to crizotinib. Molecular heterogeneity is also one of the factors associated with resistance to crizotinib. This study investigated the relevance of molecular heterogeneity to the clinical efficacy of crizotinib using next-generation sequencing (NGS).
Methods: A total of 52 ALK-positive advanced NSCLC patients were enrolled. The genetic variation was revealed by NGS. We identified different ALK fusion types, allelic fraction (AF) and additional coexisting mutations (ACMs) and evaluated the correlation between the above three factors and clinical response to crizotinib.
Results: Among the group that was detected with ALK+ fusion by immunohistochemistry (IHC), patients detected as ALK− fusion by the NGS method were associated with a shorter progression-free survival (PFS) compared with ALK+ patients by NGS. Moreover, for different ALK fusion types, the median PFS of variant 1/2/3 and other uncommon variants were 305, 557, 242 and 370 days, respectively. Although there was no statistically significant difference (P=0.201), patients with ALK variant 2 appeared to display a longer PFS than other types of variants in this study. There was no significant difference in the relationship between ALK fusion AF and PFS (P=0.639). Additionally, there was no correlation between ACMs and PFS in the three groups (IHC+, IHC+/NGS−, and IHC+/NGS+, P=0.738, 0.801 and 0.550). We analysed the relationship between TP53/FAT3 and PFS in the IHC+/NGS+ group, and there was no statistically significant difference (P=0.712/0.631).
Conclusions: It is necessary to use multiple methods together to detect ALK fusion, and we can continue to carry out the study of the correlation between the different contents of heterogeneity of gene mutations and TKI effects using the NGS method.