Pitfalls in Detecting MET Exon 14 Skipping Variants by DNA- and RNA-Based Next-Generation Sequencing Technologies in a Large Real-World Cohort and Results of the First Multinational External Quality Assessment Schemes
Résumé fourni par la source
MET exon 14 skipping mutations in non-small-cell lung cancer (NSCLC) are important biomarkers for targeted therapy, making accurate detection essential. This study analyzed 379 NSCLCs with mutations in MET exon 14 and adjacent splice sites using DNA- and RNA-based next-generation sequencing (NGS). The 379 samples contained 171 distinct mutations around MET exon 14, highlighting the diversity; 114 mutations were analyzed with a DNA- and an RNA-based NGS assay. Two large deletions and one synonymous splice variant causing exon 14 skipping were only detected by RNA-based NGS. Seven single-nucleotide variations in MET exon 14 did not induce skipping. A total of 57 variants could not be analyzed by RNA-based NGS because of insufficient material or RNA quality; among them, 18 were previously reported as skipping mutations, 30 were splice-site insertions/deletions, and 9 remained unclassified. Additionally, data from the first multinational external quality assessment schemes for MET exon 14 skipping mutation testing in formalin-fixed, paraffin-embedded tissue and liquid biopsies, organized by the lead panel institute and Quality in Pathology GmbH, are presented. High success rates (98%) for tissue are shown, whereas liquid biopsy tests had lower rates (37.5% in 2022, and 63% in 2024), primarily because of low allelic fractions and intronic deletions. This study highlights the importance of analyzing both DNA and RNA, urging improvements in sensitivity, coverage, and bioinformatics.
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Contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Pitfalls in Detecting MET Exon 14 Skipping Variants by DNA- and RNA-Based Next-Generation Sequencing Technologies in a Large Real-World Cohort and Results of the First Multinational External Quality Assessment Schemes
- Date Crossref
- 01/08/2026
- Éditeur
- Elsevier BV
- Type
- journal-article
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