Rapid EGFR Mutation Detection Using the Idylla Platform: Single-Institution Experience of 1200 Cases Analyzed by an In-House Developed Pipeline and Comparison with Concurrent Next-Generation Sequencing Results. Academic Article uri icon

Overview

abstract

  • Mutations in the epidermal growth factor receptor (EGFR) are the most common targetable alterations in lung adenocarcinoma. To facilitate rapid testing, the Idylla EGFR assay was incorporated as a screening method before next-generation sequencing (NGS). Validation and experience using an in-house developed analysis pipeline, enhanced with a manual review algorithm is described. Results are compared with corresponding NGS results. In all, 1249 samples were studied. Validation demonstrated 98.57% (69/70) concordance with the reference methods. The limit of detection varied from 2% to 5% variant allele frequency for total EGFR quantitation cycle between 20 and 23. Of the 1179 clinical cases, 23.41% were EGFR-positive by Idylla. Concurrent NGS was successfully performed on 94.9% (799/842) requests. Concordance of Idylla with NGS was 98.62% (788/799) and 98.50% (787/799) using our in-house and Idylla analysis pipelines, respectively. Discordances involved missed mutations by both assays associated with low tumor/low input. Incorporating a manual review algorithm to supplement automated calls improved accuracy from 98.62% to 99.37% and sensitivity from 94.68% to 97.58%. Overall reporting time, from receipt of material to official clinical report, ranged from 1 to 3 days. Therefore, Idylla EGFR testing enables rapid and sensitive screening without compromising subsequent comprehensive NGS, when required. Automated calling, enhanced with a manual review algorithm, reduces false-negative calls associated with low tumor/low input samples.

publication date

  • December 18, 2020

Research

keywords

  • DNA Mutational Analysis
  • Mutation

Identity

PubMed Central ID

  • PMC7919857

Scopus Document Identifier

  • 85101031542

Digital Object Identifier (DOI)

  • 10.1016/j.jmoldx.2020.11.009

PubMed ID

  • 33346146

Additional Document Info

volume

  • 23

issue

  • 3