JTO Clinical and Research Reports (Feb 2022)

Performance of an RNA-Based Next-Generation Sequencing Assay for Combined Detection of Clinically Actionable Fusions and Hotspot Mutations in NSCLC

  • Patrice Desmeules, MD, MSc,
  • Dominique K. Boudreau, MSc,
  • Nathalie Bastien, PhD,
  • Marie-Chloé Boulanger, PhD,
  • Yohan Bossé, PhD,
  • Philippe Joubert, MD, PhD,
  • Christian Couture, MD, MSc

Journal volume & issue
Vol. 3, no. 2
p. 100276

Abstract

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Introduction: With its expanding list of approved and emerging therapeutic indications, NSCLC is the exemplar tumor type requiring upfront assessment of several biomarkers to guide clinical management. Next-generation sequencing allows identification of different types of molecular alterations, each with specific analytical challenges. Library preparation using parallel DNA and RNA workflows can overcome most of them, but it increases complexity of laboratory operations, turnaround time, and costs. We describe the performance characteristics of a 15-gene RNA panel on the basis of anchored multiplex polymerase chain reaction for combined detection of clinically relevant oncogenic fusion transcripts and hotspot small variants. Methods: Formalin-fixed, paraffin-embedded NSCLC clinical samples (N = 58) were used along cell lines and commercial controls to validate the assay’s analytical performance, followed by an exploratory prospective cohort (N = 87). Results: The raw assay sensitivity for hotspot mutations and fusions was 83% and 93%, respectively, reaching 100% after filtering for key assay metrics. Those include quantity and quality of input of nucleic acid and sequencing metric from primers on housekeeping genes included in the assay. In the prospective cohort, driver alterations were identified in most cases (≥58%). Conclusions: This ultrafocused RNA–next-generation sequencing assay offers an advantageous option with single unified workflow for simultaneous detection of clinically relevant hotspot mutations and fusions in NSCLC, focusing on actionable gene targets.

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