Multiplex RNA‐based detection of clinically relevant MET alterations in advanced non‐small cell lung cancer. Issue 2 (7th December 2020) - Aguado, Cristina; Teixido, Cristina; Román, Ruth; Reyes, Roxana; Giménez‐Capitán, Ana; Marin, Elba; Cabrera, Carlos; Viñolas, Nuria; Castillo, Sergi; Muñoz, Silvia; Arcocha, Ainara; López‐Vilaró, Laura; et al.
Abstract : MET inhibitors have shown activity in non‐small‐cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping ( METΔex14) . However, patient stratification is imperfect, and thus, response rates have varied widely. Here, we studied MET alterations in 474 advanced NSCLC patients by nCounter, an RNA‐based technique, together with next‐generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and reverse transcriptase polymerase chain reaction (RT–PCR), exploring correlation with clinical benefit. Of the 474 samples analyzed, 422 (89%) yielded valid results by nCounter, which identified 13 patients (3%) with MET Δex14 and 15 patients (3.5%) with very‐high MET mRNA expression. These two subgroups were mutually exclusive, displayed distinct phenotypes and did not generally coexist with other drivers. For MET Δex14, 3/8 (37.5%) samples positive by nCounter tested negative by NGS. Regarding patients with very‐high MET mRNA, 92% had MET amplification by FISH and/or NGS. However, FISH failed to identify three patients (30%) with very‐high MET RNA expression, among which one received MET tyrosine kinase inhibitor treatment deriving clinical benefit. Our results indicate that quantitative mRNA‐based techniques can improve the selection of patients for MET‐targeted therapies. Abstract : We studied MET alterations in 474 advanced non‐small‐cell lung cancer (NSCLC) patients by nCounter, an RNA‐based technique. We identified 3% with MET Δex14 mRNA and 3.5% with very‐high MET mRNA expression, a surrogate of MET amplification. MET alterations identified by nCounter correlated with clinical benefit from MET inhibitors. Quantitative mRNA‐based techniques can improve the selection of patients for MET‐targeted therapies.