High-level gain of mesenchymal-epithelial transition factor (MET) copy number using next-generation sequencing as a predictive biomarker for MET inhibitor efficacy.

ABSTRACT: Background:In clinical oncology, targeted next-generation sequencing (NGS) has become an integral part of the routine molecular diagnostics repertoire. However, a consensus is yet to be agreed on the optimal mesenchymal-epithelial transition factor (MET) copy number (CN) cut-off value based on NGS data that could predict the MET-amplified non-small cell lung cancer (NSCLC) patients who could benefit from MET tyrosine kinase inhibitor (TKI) therapy. In this study, we aimed to identify the criteria to define MET amplification derived from NGS data. Methods:Sequencing data from matched plasma and tissue samples from 40 MET-amplified NSCLC patients were used to derive a normalization method, referred to as adjusted copy number (adCN). Clinical outcomes from an additional 18 MET TKI-treated NSCLC patients with solely MET-amplified cancers were analyzed to validate the adCN cut-offs. Results:AdCN, calculated as the absolute CN generated from NGS relative to the maximum mutant allele fraction (maxMAF) per sample, was demonstrated to have a high correlation with MET CN in tissue and plasma samples (R2=0.73). Using a cut-off value of 5.5 and 13, tertile stratification of adCN was able to distinguish patients with high-level MET amplification. The MET TKI-treated patients with adCN >13, categorized as high-level amplification, had significantly longer progression-free survival (PFS) than those with adCN <13 (P=0.009), suggesting that adCN positively correlated with the response to MET TKI. Conclusions:We derived a normalization method that could reflect the relative CN and distinguish MET-amplified NSCLC patients with high-level gene amplification who were sensitive to crizotinib, suggesting adCN could potentially serve as a predictive biomarker for MET TKI response.

SUBMITTER: Wu S 

PROVIDER: S-EPMC7327325 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature