Comparison of Targeted RNA-Sequencing Platforms for Oncogenic Fusion Detection in Non-Small-Cell Lung Cancer. Academic Article uri icon

Overview

abstract

  • Oncogenic fusion detection is an essential part of clinical diagnosis and management of non-small-cell lung carcinoma. Numerous methods are available for detection of oncogenic fusions in the clinical laboratory, although RNA sequencing has rapidly gained prominence. Accordingly, however, multiple different RNA-sequencing assays exist, with diverse methods and varying performance characteristics. Here, a single-institutional clinical experience with a testing algorithm for non-small-cell lung carcinoma that uses amplicon-based DNA/RNA sequencing, followed by reflex hybridization-capture-based RNA sequencing if the initial testing is negative for oncogenic drivers, is reported. A total of 1211 non-small-cell lung carcinoma specimens were received for molecular testing, and 120 (approximately 10%) were reflexed for hybridization-capture-based RNA sequencing. Of the 120 cases tested, oncogenic fusions were identified in 9 and included clinically actionable fusions involving ALK, BRAF, NRG1, NTRK3, ROS1, and RET. None of these fusions was detected by the amplicon-based assay. Review of the 20,900 non-small-cell lung cancer cases in the American Association for Cancer Research Project Genie version 15.1 publicly available database (registration required) revealed that of the 1081 cases harboring fusions, 893 (82.6%) could theoretically be detected by the amplicon-based assay. Overall, this study shows that the addition of reflex hybridization-capture-based RNA sequencing could improve detection of rare and novel oncogenic fusions, maximizing patient eligibility for appropriate targeted therapies or clinical trials.

publication date

  • March 21, 2025

Research

keywords

  • Carcinoma, Non-Small-Cell Lung
  • Lung Neoplasms
  • Oncogene Fusion
  • Oncogene Proteins, Fusion
  • Sequence Analysis, RNA

Identity

Scopus Document Identifier

  • 105002741815

Digital Object Identifier (DOI)

  • 10.1016/j.jmoldx.2025.02.007

PubMed ID

  • 40122160

Additional Document Info

volume

  • 27

issue

  • 6