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Updated: Feb 5, 2026

Evaluation of Exon Inclusion Induced by Splice Switching Antisense Oligonucleotides in SMA Patient Fibroblasts
Published on: May 11, 2018
Optimization of Routine Testing for MET Exon 14 Splice Site Mutations in NSCLC Patients
Clotilde Descarpentries1, Frédéric Leprêtre2, Fabienne Escande1
1Department of Biochemistry and Molecular Biology, Hormonology Metabolism Nutrition Oncology, CHU Lille, Lille, France.
Introduction:
Genomic alterations affecting splice sites of MNNG HOS transforming gene (MET) exon 14 were recently identified in NSCLC patients. Objective responses to MET tyrosine kinase inhibitors have been reported in these patients. Thus, detection of MET exon 14 splice site mutations represents a major challenge. So far, most of these alterations were found by full-exome sequencing or large capture-based next-generation sequencing (NGS) panels, which are not suitable for routine diagnosis.
Methods:
Aiming to provide a molecular testing method applicable in routine practice, we first developed a fragment-length analysis for detecting deletions in introns flanking MET exon 14. Second, we designed an optimized targeted NGS panel called CLAPv1, covering the MET exon 14 and flanking regions in addition to the main molecular targets usually covered in genomic testing. In patients with MET exon 14 mutations, MET gene amplification, gene copy number and MET receptor expression were also determined.
Results:
Among 1514 formalin-fixed paraffin-embedded NSCLC samples, nonoptimized NGS allowed detection of MET exon 14 mutations in only 0.3% of the patients, and fragment length analysis detected deletions in 1.1% of the patients. Combined, the optimized CLAPv1 panel and fragment-length analysis implemented for routine molecular testing revealed MET exon 14 alterations in 2.2% of 365 additional NSCLC patients. MET gene amplification or high gene copy number was observed in 6 of 30 patients (20%) harboring MET exon 14 mutations.
Conclusions:
These results show that optimized targeted NGS and fragment-length analysis improve detection of MET alterations in routine practice.
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