The Advantage of Targeted Next-Generation Sequencing over qPCR in Testing for Druggable EGFR Variants in Non-Small-Cell Lung Cancer

Real-world application of targeted next-generation sequencing for identifying molecular variants in Asian non-small-cell lung cancer

BACKGROUND

The advent of novel therapeutic agents has advanced biomarker characterization in non-small-cell lung cancer (NSCLC), driving increased adoption of next-generation sequencing (NGS) technologies for molecular testing. However, comprehensive data addressing the clinical utility of different NGS platforms for NSCLC remains limited.

METHODS

This retrospective study analyzed real-world data from 478 Taiwanese NSCLC patients over five years, using the Oncomine Focus Assay (OFA) to assess genetic alterations. The evaluation focused on assay accuracy, limit of detection (LoD), sequencing performance, and the genetic landscape of NSCLC.

RESULTS

The OFA achieved an NGS success rate of 80.5% (385/478), with tumor cell percentage, specimen source and FFPE block age identified as key factors affecting success. Quality metrics demonstrated robust sequencing performance, including 97.0 ± 9.6% on-target alignment, 94.7 ± 6.4% uniformity, and ≥ 500 × coverage for 98.0 ± 6.6% of amplicons. Among the 385 patients analyzed, 86.8% (334/385) were found to harbor pathogenic or likely pathogenic variants, of which 78.4% (262/334) were SNVs/Indels, 41.6% (139/334) were CNVs, 2.7% (9/334) were exon skipping alterations, and 10.2% (34/334) were gene fusions. Actionable driver mutations included EGFR mutations (46.2%, 178/385), KRAS mutations (9.4%, 36/385), ERBB2 mutations (6.8%, 26/385), ALK fusions (4.4%, 17/385), MET exon 14 skipping (2.3%, 9/385), BRAF mutations (2.3%, 9/385), ROS1 and RET fusions (1.8%, 7/385 each), and NTRK1 fusions (0.5%, 2/385). Notably, KRAS G12 C mutation was detected in 2.8% (11/385) of cases.

CONCLUSIONS

This study demonstrates the robust performance of the OFA in identifying clinically relevant genetic alterations in NSCLC. The findings support its clinical utility in precision oncology and provide valuable insights into the genetic landscape of Asian NSCLC, enhancing personalized treatment strategies for lung cancer patients.

Research Trends and Development Dynamics of qPCR-based Biomarkers: A Comprehensive Bibliometric Analysis

Quantitative polymerase chain reaction (qPCR) is a vital molecular technique for biomarker detection; however, its clinical application is impeded by the scarcity of robust biomarkers and the inherent limitations of the technology. This study conducted a bibliometric analysis of 4063 qPCR-based biomarker studies sourced from the Web of Science (WOS) database, employing VOSviewer and CiteSpace to generate multi-dimensional structural insights into this field. The results reveal a growing trend in research within this domain, with gene expression analysis playing a central role in the identification of potential biomarkers. Among these, cancer-related biomarkers are the most prominent, while research on biomarkers for other diseases remains limited. Liquid biopsy biomarkers, including microRNA (miRNA), circulating free DNA (cfDNA), and circulating tumor DNA (ctDNA), are increasingly being explored. The integration of bioinformatics, omics analysis, and high-throughput technologies with qPCR is accelerating biomarker discovery. Furthermore, large-scale parallel sequencing is emerging as a potential alternative to relative quantification and microarray techniques. Nevertheless, qPCR remains essential for validating specific biomarkers, and further standardization of its protocols is necessary to enhance reliability. This study provides a systematic analysis of qPCR-based biomarker research and underscores the need for future technological integration and standardization to facilitate broader clinical applications.