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Single Droplet Digital Polymerase Chain Reaction for Comprehensive and Simultaneous Detection of Mutations in Hotspot Regions
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Key differences between 13 KRAS mutation detection technologies and their relevance for clinical practice.

James L Sherwood1, Helen Brown1, Alessandro Rettino2

  • 1Precision Medicine and Genomics, Innovative Medicines and Early Development Biotech, AstraZeneca, Cambridge, UK.

ESMO Open
|October 12, 2017
PubMed
Summary

This study compared 13 KRAS mutation detection technologies, finding significant performance differences in sensitivity and turnaround time. Next-generation sequencing (NGS) showed the highest accuracy, while some qPCR and MALDI-TOF assays also performed well.

Keywords:
EGFR mutationMALDITOFNGSNSCLCddPCRplatform comparisonqPCR

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Area of Science:

  • Molecular Diagnostics
  • Oncology
  • Biotechnology

Background:

  • KRAS mutations are critical biomarkers in various cancers, necessitating accurate and efficient detection methods.
  • Clinical practice relies on diverse technologies for KRAS mutation analysis, with varying performance characteristics.

Purpose of the Study:

  • To comprehensively assess and compare the performance of 13 distinct KRAS mutation detection technologies available in clinical settings.
  • To evaluate assay sensitivity, accuracy, and turnaround time for clinically relevant KRAS mutations.

Main Methods:

  • Utilized five KRAS-mutant cell lines with five specific mutations (p.G12C, p.G12D, p.G12V, p.G13D, p.Q61H).
  • Created cell line admixtures with mutant KRAS allele frequencies ranging from 0.5% to 20%.
  • Tested 13 assays including quantitative PCR (qPCR), MALDI-TOF, next-generation sequencing (NGS), digital PCR, and Sanger sequencing.

Main Results:

  • Successful genotyping varied significantly, from 0% for Sanger sequencing to 100% for one NGS assay.
  • One NGS assay detected mutations down to 0.5% allele frequency.
  • qPCR and MALDI-TOF assays demonstrated high accuracy (96% and 92% respectively) at higher allele frequencies.
  • Turnaround times ranged from ~2 hours to 2 weeks, with expertise requirements varying from minimal to high.

Conclusions:

  • This parallel assessment using cell line DNA provides crucial data for laboratories implementing KRAS testing.
  • Significant performance differences exist among available technologies, impacting clinical decision-making.
  • Findings are relevant for selecting appropriate molecular diagnostic tools and may inform applications for other biomarkers.