Characterization of Non–Small-Cell Lung Cancers With MET Exon 14 Skipping Alterations Detected in Tissue or Liquid: Clinicogenomics and Real-World Treatment Patterns

MET exon 14 (METex14) skipping alterations are oncogenic drivers in non-small-cell lung cancer (NSCLC). We present a comprehensive overview of METex14 samples from 1,592 patients with NSCLC, associated clinicogenomic characteristics, potential mechanisms of acquired resistance, treatment patterns, and outcomes to MET inhibitors.Hybrid capture-based comprehensive genomic profiling (CGP) was performed on samples from 69,219 patients with NSCLC. For treatment patterns and outcomes analysis, patients with advanced METex14-altered NSCLC were selected from the Flatiron Health-Foundation Medicine clinicogenomic database, a nationwide deidentified electronic health record-derived database linked to Foundation Medicine CGP for patients treated between January 2011 and March 2020.A total of 1,592 patients with NSCLC (2.3%) were identified with 1,599 METex14 alterations spanning multiple functional sites (1,458 of 60,244 tissue samples and 134 of 8,975 liquid samples). Low tumor mutational burden and high programmed death ligand 1 expression were enriched in METex14-altered samples. MDM2, CDK4, and MET coamplifications and TP53 mutations were present in 34%, 19%, 11%, and 42% of tissue samples, respectively. Comparing tissue and liquid cohorts, coalteration frequency and acquired resistance mechanisms, including multiple MET mutations, EGFR, ERBB2, KRAS, and PI3K pathway alterations, were generally similar. Positive percent agreement with the tissue was 100% for METex14 pairs collected within 1 year (n = 7). Treatment patterns showed increasing adoption of MET inhibitors in METex14-altered NSCLC after receipt of CGP results; the real-world response rate to MET inhibitors was 45%, and time to treatment discontinuation was 4.4 months.Diverse METex14 alterations were present in 2%-3% of NSCLC cases. Tissue and liquid comparisons showed high concordance and similar coalteration profiles. Characterizing common co-occurring alterations and immunotherapy biomarkers, including those present before or acquired after treatment, may be critical for predicting responses to MET inhibitors and informing rational combination strategies.