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Multicenter Evaluation of the Fully Automated PCR-Based Idylla EGFR Mutation Assay on Formalin-Fixed, Paraffin-Embedded Tissue of Human Lung Cancer


Abstract

Before initiating treatment of advanced non-small-cell lung cancer with tyrosine kinase inhibitors (eg, erlotinib, gefitinib, osimertinib, and afatinib), which inhibit the catalytic activity of epidermal growth factor receptor (EGFR), clinical guidelines require determining the EGFR mutational status for activating (EGFR exons 18, 19, 20, or 21) and resistance (EGFR exon 20) mutations. The EGFR resistance mutation T790M should be monitored at cancer progression. The Idylla EGFR Mutation Assay, performed on the Idylla molecular diagnostics platform, is a fully automated (<2.5 hours turnaround time) sample-to-result molecular test to qualitatively detect 51 EGFR oncogene point mutations, deletions, or insertions. In a 15-center evaluation, Idylla results on 449 archived formalin-fixed, paraffin-embedded tissue sections, originating from non-small-cell lung cancer biopsies and resection specimens, were compared with data obtained earlier with routine reference methods, including next-generation sequencing, Sanger sequencing, pyrosequencing, mass spectrometry, and PCR-based assays. When results were discordant, a third method of analysis was performed, when possible, to confirm test results. After confirmation testing and excluding invalids/errors and discordant results by design, a concordance of 97.6% was obtained between Idylla and routine test results. Even with <10 mm$^{2}$ of tissue area, a valid Idylla result was obtained in 98.9% of the cases. The Idylla EGFR Mutation Assay enables sensitive detection of most relevant EGFR mutations in concordance with current guidelines, with minimal molecular expertise or infrastructure.

Abstract

Before initiating treatment of advanced non-small-cell lung cancer with tyrosine kinase inhibitors (eg, erlotinib, gefitinib, osimertinib, and afatinib), which inhibit the catalytic activity of epidermal growth factor receptor (EGFR), clinical guidelines require determining the EGFR mutational status for activating (EGFR exons 18, 19, 20, or 21) and resistance (EGFR exon 20) mutations. The EGFR resistance mutation T790M should be monitored at cancer progression. The Idylla EGFR Mutation Assay, performed on the Idylla molecular diagnostics platform, is a fully automated (<2.5 hours turnaround time) sample-to-result molecular test to qualitatively detect 51 EGFR oncogene point mutations, deletions, or insertions. In a 15-center evaluation, Idylla results on 449 archived formalin-fixed, paraffin-embedded tissue sections, originating from non-small-cell lung cancer biopsies and resection specimens, were compared with data obtained earlier with routine reference methods, including next-generation sequencing, Sanger sequencing, pyrosequencing, mass spectrometry, and PCR-based assays. When results were discordant, a third method of analysis was performed, when possible, to confirm test results. After confirmation testing and excluding invalids/errors and discordant results by design, a concordance of 97.6% was obtained between Idylla and routine test results. Even with <10 mm$^{2}$ of tissue area, a valid Idylla result was obtained in 98.9% of the cases. The Idylla EGFR Mutation Assay enables sensitive detection of most relevant EGFR mutations in concordance with current guidelines, with minimal molecular expertise or infrastructure.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Health Sciences > Pathology and Forensic Medicine
Life Sciences > Molecular Medicine
Language:English
Date:November 2019
Deposited On:13 Jan 2020 10:46
Last Modified:29 Jul 2020 12:24
Publisher:American Society for Investigative Pathology
ISSN:1525-1578
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.jmoldx.2019.06.010
PubMed ID:31445213

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