Optimising fusion detection through sequential DNA and RNA molecular profiling of non-small cell lung cancer

David A Moore1, Sarah Benafif2, Benjamin Poskitt3

  • 1CRUK Lung Cancer Centre of Excellence, UCL Cancer Institute, UCL, London, United Kingdom; Department of Cellular Pathology, University College London Hospitals NHS Foundation Trust, London, United Kingdom.

Abstract

Insights

A new sequential testing approach for non-small cell lung cancer (NSCLC) improves detection of actionable driver fusions. This method prioritizes patients negative for driver mutations on DNA next-generation sequencing (NGS) for RNA panel testing, enhancing targeted therapy identification.

Area of Science:

  • Oncology
  • Molecular Diagnostics
  • Genomics

Background:

  • Non-small cell lung cancer (NSCLC) management increasingly relies on targeted therapies for driver fusions.
  • Current fusion panel testing is costly and requires ample, high-quality biopsy material.
  • Driver events in NSCLC are typically mutually exclusive, allowing for sequential testing strategies.

Purpose of the Study:

  • To evaluate a novel, cost-effective molecular testing pathway for NSCLC.
  • To identify patients with actionable driver fusions by prioritizing those negative for driver mutations via DNA-NGS.
  • To improve the detection rate of fusion-driven NSCLC amenable to targeted therapy.

Main Methods:

  • A sequential diagnostic pathway was implemented over 18 months for non-squamous NSCLC patients.
  • Initial testing involved DNA-NGS and ALK/ROS1 immunohistochemistry +/- FISH.
  • Patients negative for driver mutations were recalled for RNA panel testing if sufficient tissue remained.

Main Results:

  • 61% of successfully DNA-NGS tested samples harbored driver mutations.
  • Among samples negative for driver mutations, 24% (17/72) had detectable fusions (ALK, ROS, MET, RET, FGFR, EGFR).
  • The combined DNA and RNA panel approach detected a driver event in 66% of patients.

Conclusions:

  • Sequential DNA and RNA-based molecular profiling enhances the detection of fusion-driven NSCLC.
  • Optimizing tissue handling and diagnostic pathways is crucial to reduce failure rates in gene fusion analysis.
  • Improved detection rates facilitate treatment with next-generation small molecule inhibitors.