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Abstract
Background
The Mesenchymal epithelial transition factor (MET) gene encodes a receptor tyrosine kinase with pleiotropic functions in cancer. MET exon 14 skipping alterations and high-level MET amplification are oncogenic and targetable genetic changes in patients with non-small-cell lung cancer (NSCLC). Resistance to tyrosine kinase inhibitors (TKIs) has been a major challenge for targeted therapies that impairs their clinical efficacies.
Methods
Eighty-six NSCLC patients were categorized into three cohorts based on the time of detecting MET tyrosine kinase domain (TKD) mutations (cohort 1: at baseline; cohort 2: after MET-TKI treatment; cohort 3: after EGFR-TKI treatment). Baseline and paired TKI treatment samples were analyzed by targeted next-generation sequencing.
Results
MET TKD mutations were highly prevalent in METex14-positive NSCLC patients after MET-TKI treatment, including L1195V, D1228N/H/Y/E, Y1230C/H/N/S, and a double-mutant within codons D1228 and M1229. Missense mutations in MET TKD were also identified at baseline and in post-EGFR-TKI treatment samples, which showed different distribution patterns than those in post-MET-TKI treatment samples. Remarkably, H1094Y and L1195F, absent from MET-TKI-treated patients, were the predominant type of MET TKD mutations in patients after EGFR-TKI treatment. D1228H, which was not found in treatment-naïve patients, also accounted for 14.3% of all MET TKD mutations in EGFR-TKI-treated samples. Two patients with baseline EGFR-sensitizing mutations who acquired MET-V1092I or MET-H1094Y after first-line EGFR-TKI treatment experienced an overall improvement in their clinical symptoms, followed by targeted therapy with MET-TKIs.
Conclusions
MET TKD mutations were identified in both baseline and patients treated with TKIs. MET-H1094Y might play an oncogenic role in NSCLC and may confer acquired resistance to EGFR-TKIs. Preliminary data indicates that EGFR-mutated NSCLC patients who acquired MET-V1092I or MET-H1094Y may benefit from combinatorial therapy with EGFR-TKI and MET-TKI, providing insights into personalized medical treatment.
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