The Mutation Patterns of MET Gene in Lung Cancer and Brain Tumors: Clinical and Therapeutic Implications.

[OBJECTIVES] MET aberrations are capable of triggering oncogenesis through multiple clinical significance genomic alterations. In non-small cell lung cancer, MET exon 14 skipping and MET amplification confer sensitivity to MET tyrosine kinase inhibitors. The MET gene is also one of the druggable genes in high-grade gliomas. However, a systematic comparison of MET variations between lung cancer and brain tumors is lacking.

[METHODS] We analyzed a large Chinese cohort of 30,355 lung cancer and 6004 brain tumor patients. Different MET mutation types were characterized, and somatic genomic mutational characteristics were examined across various MET mutation subgroups in both lung cancer and brain tumor cohorts. The impact of MET mutations on prognosis in these two cohorts was also assessed. The study cohort underwent comprehensive genomic profiling using targeted next-generation sequencing (NGS) panels.

[RESULTS] We found that clinically significant MET mutations exist in both lung and brain tumor cohorts, with the lung cancer group having a higher overall frequency (p < 0.001), but the frequency of different MET mutation types, mutation characteristics, tumor mutation burden, and co-mutated genes with high frequency all differ. MET alterations were significantly enriched in post-treatment brain tumors (8.5% vs. 4.8% in treatment-naïve, p < 0.001). MET mutations also have different prognostic effects in the two cancer types. MET alterations were not prognostic in lung cancer but were associated with significantly poorer survival in brain tumors (median OS: 19.9 vs. 62.9 months, p < 0.001), a finding that held in multivariate analysis.

[CONCLUSIONS] Our study demonstrated that the biological and clinical significance of MET alterations is highly context dependent. In lung cancer, MET serves primarily as a predictive biomarker for targeted therapy, whereas in brain tumors, it functions as a prognostic marker of genomic instability and aggressive disease. These findings advocate for context-specific clinical management strategies.