Clinical and genomic analysis of non-small cell lung cancer (NSCLC) patients with MET exon14 skipping (METex14) mutations and responses to anti-MET therapy.

9613 Background: MET is a validated oncogene for molecular targeted therapy in non-small-cell lung cancer (NSCLC), and METex14 mutations result in MET overexpression. Studies with MET-targeting therapies have demonstrated high objective response rates and prolonged disease control. There are few clinical and genomic analyses of patients with METex14-positive NSCLC in the community setting. We herein characterize key clinical and genomic findings for patients harboring METex14 mutations. Methods: Sarah Cannon provides clinical research to partnering medical oncology practices who order broad-based NGS, from both tissue and blood, as a part of standard of care. Genospace, a clinico-genomic software tool, was used for identification of patients for clinical trials and analysis of clinical and genomic data. Results: Of 6521 lung cancer patients with NGS results, 66 (1.01%) harbored METex14 mutations (45.5% from blood and 54.5% from in tissue). The mean age at diagnosis was 75.7 and 21.2% developed brain metastases. Of the 66 patients with METex14 mutations, 69.5% are current/former smokers. Nineteen percent of former/current smokers and 7.6% of never smokers had PD-L1 scores of > 50%, respectively. The majority of METex14-positive patients either received standard of care (66.7%) or were unable to take (19.7%) 1st-line therapy. Patients who received chemotherapy (Chemo), immunotherapy (IO), and Chemo/IO in the first and second line settings responded to SOC treatment, and patients receiving anti-MET therapy benefited from therapy even after front-line SOC (table). Genomic analysis revealed the most common co-occurring mutations to be EGFR, MET, NF1, KRAS, and BRCA2 (Freq = 8.7%, 8.7%, 8.7%, and 7.6%, respectively). Conclusions: Genospace enables real-time patient identification of METex14-positive NSCLC cases and analysis of these cases indicates that anti-MET therapy may be effective at any line of treatment. Genospace’s clinico-genomic database was used to analyze treatment history, clinical correlates, and co-occurring mutations that may reveal novel treatment combination strategies or resistance mechanisms. [Table: see text]