- Robust home brew fragment sizing assay for detection of MET exon 14 skipping mutation in non–small cell lung cancer patients in resource constrained community hospitals
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Anurag Mehta, Shrinidhi Nathany, Aanchal Chopra, Sakshi Mattoo, Dushyant Kumar, Manoj Kumar Panigrahi
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J Pathol Transl Med. 2021;55(5):324-329. Published online September 2, 2021
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DOI: https://doi.org/10.4132/jptm.2021.07.15
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 Abstract
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- Background
A mutation/deletion involving donor or acceptor sites for exon 14 results in splicing out of exon 14 of the mesenchymal epithelial transition (MET) gene and is known as “MET exon 14 skipping” (ΔMET14). The two recent approvals with substantial objective responses and improved progression-free survival to MET inhibitors namely capmatinib and tepotinib necessitate the identification of this alteration upfront. We herein describe our experience of ΔMET14 detection by an mRNA-based assay using polymerase chain reaction followed by fragment sizing.
Methods
This is a home brew assay which was developed with the concept that the transcripts from true ΔMET14 will be shorter by ~140 bases than their wild type counterparts. The cases which were called MET exon 14 skipping positive on next-generation sequencing (NGS) were subjected to this assay, along with 13 healthy controls in order to establish the validity for true negatives.
Results
Thirteen cases of ΔMET14 mutation were detected on NGS using RNA-based sequencing. Considering NGS as a gold standard, the sizing assay using both gel and capillary electrophoresis that showed 100% specificity for both with concordance rates of 84.6% and 88.2% with NGS, respectively, were obtained.
Conclusions
Owing to the cost-effective nature and easy to use procedures, this assay will prove beneficial for small- and medium-sized laboratories where skilled technical personnel and NGS platforms are unavailable.
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Citations
Citations to this article as recorded by  - MET: A narrative review of exon 14 skipping mutation in non-small-cell lung carcinoma
Shrinidhi Nathany, Ullas Batra
Cancer Research, Statistics, and Treatment.2022; 5(2): 284. CrossRef
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