An accurate DNA and RNA based targeted sequencing assay for clinical detection of gene fusions in solid tumors

Gang Ji1,2,3, Qianlan Yao1,2,3, Min Ren1,2,3

  • 1Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.

Scientific Reports
|February 28, 2025
PubMed

Insights

A novel DNA and RNA next-generation sequencing (NGS) assay accurately detects gene fusions in solid tumors. This integrated approach improves tumor diagnosis and targeted therapy selection.

Area of Science:

  • Oncology
  • Molecular Diagnostics
  • Genomics

Background:

  • Gene fusions are critical molecular biomarkers for cancer diagnosis, classification, and targeted therapy.
  • Accurate detection of gene fusions remains a significant challenge in clinical practice.

Purpose of the Study:

  • To develop and validate a custom-designed, integrated DNA and RNA-based next-generation sequencing (NGS) assay for identifying gene fusions in solid tumors.
  • To assess the assay's performance, including accuracy, sensitivity, and reproducibility.

Main Methods:

  • Development of a targeted NGS assay covering 16 genes relevant to targeted therapy.
  • Validation using commercial fusion standards and clinical solid tumor samples.
  • Assessment of limit of detection using dilution experiments and reproducibility studies.

Main Results:

  • The assay accurately identified all 10 fusion types in reference standards and 29 fusions (16 forms) in 60 clinical samples.
  • A TPM3::NTRK1 fusion was newly identified, highlighting potential for discovering missed fusions.
  • Stable detection limits were established at 5% mutational abundance for DNA and 250-400 copies/100 ng for RNA.
  • High intra-assay and inter-assay reproducibility was demonstrated.

Conclusions:

  • The integrated DNA and RNA-based NGS assay demonstrates excellent performance for detecting gene fusions in formalin-fixed, paraffin-embedded solid tumors.
  • The assay's complementary DNA and RNA results facilitate precise cancer diagnosis and treatment selection.
  • This approach enhances the clinical utility of molecular biomarkers for personalized oncology.