Detalle Publicación

Multiplex RNA-based detection of clinically relevant MET alterations in advanced non-small cell lung cancer

Autores: Aguado, C.; Teixido, C.; Roman, R.; Reyes, R.; Gimenez-Capitan, A.; Marin, E.; Cabrera, C.; Vinolas, N.; Castillo, S.; Munoz, S.; Arcocha, A.; Lopez-Vilaro, L; Sullivan, I.; Aldeguer, E.; Rodriguez, S.; Moya, I.; Viteri, S.; Cardona, A. F.; Palmero, R.; Sainz, C.; Mesa-Guzman, M; Lozano Escario, María Dolores; Aguilar-Hernandez, A; Martinez-Bueno, A.; Gonzalez-Cao, M.; Gonzalvo, E.; Leenders, W. P. J.; Rosell, R.; Montuenga Badía, Luis; Prat, A.; Molina-Vila, M. A.; Reguart, N. (Autor de correspondencia)
Título de la revista: MOLECULAR ONCOLOGY
ISSN: 1574-7891
Volumen: 15
Número: 2
Páginas: 350 - 363
Fecha de publicación: 2021
Resumen:
MET inhibitors have shown activity in non-small-cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping (MET Delta ex14). 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 Delta ex14 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 Delta ex14, 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.