What question did this study set out to answer?

This research aims to find an optimal cut-off for MET gene copy number associated with patient outcomes in non-small-cell lung cancer.

May 10, 2026Open Access

Exploratory Identification of Gene Copy Number Cut-Off for NGS-Based MET Amplification Assessment and Clinical Relevance to MET Inhibitor Outcomes in Non-Small-Cell Lung Cancer

Key Points

This research aims to find an optimal cut-off for MET gene copy number associated with patient outcomes in non-small-cell lung cancer.
Conducted a multiple-site joint study using tumor tissue and next-generation sequencing analysis.
Utilized five NGS panels and fluorescence in situ hybridization as a reference to detect MET gene copy number.
Analyzed receiver operating characteristic curves to determine optimal cut-off values.
The optimal MET gene copy number cut-off was established at 6.55, with a corresponding accuracy of 85.7%.
In the validation cohort, NGS analysis showed an accuracy rate of 79.3%.
Patients with MET gene copy number ≥ 6.55 experienced a longer median progression-free survival (hazard ratio = 0.42; p = 0.03) compared to those with lower values.

Abstract

Introduction: MET amplification is a critical oncogenic driver and a major mechanism of acquired resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in non-small-cell lung cancer (NSCLC). Currently, next-generation sequencing (NGS)-based assays are increasingly used in clinical practice. However, they lack a unified standard for defining MET amplification across multiple NGS platforms with a potential actionable threshold. Methods: This was a multiple-site joint study to optimize the cut-off value for MET amplification using tumor tissue and NGS analysis. In the training cohort, five NGS panels were used to detect MET gene copy number (GCN), and fluorescence in situ hybridization (FISH) was used as a reference. Receiver operating characteristic (ROC) curve analysis was used to identify the optimal cutoff with 100% specificity and 66.7% sensitivity. The results were validated in an independent cohort to explore the correlation between MET amplification and efficacy of MET inhibitors in patients with NSCLC. Results: In the training cohort (n=21), the optimal MET GCN cut-off was determined to be 6.55, yielding an area under the curve of 0.9, corresponding to an accuracy of 85.7%. MET polysomy, identified using FISH (n=2), was also detected using NGS. All five NGS panels demonstrated good concordance with FISH, with accuracies ranging from 75.0% to 85.7%. In the validation cohort (n=29), NGS analysis demonstrated a good performance, with an accuracy rate of 79.3%. Patients with MET GCN ≥ 6.55 had a significantly longer median progression free survival than those with MET GCN < 6.55 (hazard ratio = 0.42; p = 0.03). Conclusion: In this study, an exploratory cut-off of 6.55 for MET GCN by NGS was associated with MET amplification and longer progression-free survival in patients receiving targeted therapy. However, given the retrospective design and limited sample size, these findings should be regarded as exploratory and require validation in larger, prospective cohorts before broader clinical application. Keywords: MET amplification, next-generation of sequencing, gene copy number, non-small-cell lung cancer, targeted therapy

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