Clinicopathological characteristics of Non-Small Cell Lung Cancer (NSCLC) patients with c-MET exon 14 skipping mutation, MET overexpression and amplification

Abstract

Purpose MET exon 14 skipping is one of the rare mutations in non-small cell lung cancer (NSCLC), involving its pathogenesis and progression. The performances of several MET inhibitors in clinical trials have been validated based on NGS, immunohistochemistry (IHC), and gene copy number assessments. Thus, a detailed understanding of the relationship between these markers and prognosis is required. Methods This study has recruited patients (n = 17) with MET exon 14 skipping mutation and initially screened genes (n = 10) by polymerase chain reaction (PCR) from 257 specimens of NSCLC, including small biopsies and surgical resection. Further, the IHC analysis detected MET overexpression and recorded the score using the MetMAb trial (rial ( recruited patients (n = 17) with MET exstainings). Finally, the fluorescence in situ hybridization (FISH) resulted in the MET amplification with a MET copy number initially screened genes (n = 10) by p. Results PCR results indicated strong MET staining ( 3+) in more than 50% of tumor cells. Among the recruited 17 cases of MET exon 14 skipping, 9 cases presented MET amplification, and 10 cases with MET overexpression. These attributes were not correlated to the clinicopathological characteristics and overall survival. In addition, 4 cases showed gene amplification, and 3 cases presented polyploidy condition. The correlation analysis showed a significant relationship between MET amplification and MET overexpression (Pearson’s r2 = 0.4657, P < 0.005). Conclusion Together, these findings indicated a significant correlation between MET overexpression and MET amplification in NSCLC patients but no correlation to prognosis.

Retrospective Analysis to Optimize the Detection of MET Exon 14 Skipping Mutations in Non-Small Cell Lung Cancer

“…It has been found that patients with the MET exon 14 ( MET ex14) skipping alteration have a significantly poor prognosis, making the identification of this mutation crucial for an accurate diagnosis and personalized treatment strategies [ 3 , 4 ]. Therefore, efficient biomarker detection methods are necessary for this mutation identification.…”