Comprehensive NGS profiling to enable detection of ALK gene rearrangements and MET amplifications in non-small cell lung cancer

Introduction Next-generation sequencing (NGS) is currently widely used for biomarker studies and molecular profiling to identify concurrent alterations that can lead to the better characterization of a tumor's molecular landscape. However, further evaluation of technical aspects related to the detection of gene rearrangements and copy number alterations is warranted.Methods There were 12 ALK rearrangement-positive tumor specimens from patients with non-small cell lung cancer (NSCLC) previously detected via fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and an RNA-based NGS assay, and 26 MET high gene copy number (GCN) cases detected by FISH, selected for this retrospective study. All 38 pre-characterized cases were reassessed utilizing the PGDx (TM) elio (TM) tissue complete assay, a 505 gene targeted NGS panel, to evaluate concordance with these conventional diagnostic techniques.Results The detection of ALK rearrangements using the DNA-based NGS assay demonstrated excellent sensitivity with the added benefit of characterizing gene fusion partners and genomic breakpoints. MET copy number alterations were also detected; however, some discordances were observed likely attributed to differences in algorithm, reporting thresholds and gene copy number state. TMB was also assessed by the assay and correlated to the presence of NSCLC driver alterations and was found to be significantly lower in cases with NGS-confirmed canonical driver mutations compared with those without (p=0.0019).Discussion Overall, this study validates NGS as an accurate approach for detecting structural variants while also highlighting the need for further optimization to enable harmonization across methodologies for amplifications.

Automated summary

This article introduces the application of next-generation sequencing (NGS) in tumor research and the need for technical optimization for the detection of structural variations.