Clinical Application of Picodroplet Digital PCR Technology for Rapid Detection of EGFR T790M in Next-Generation Sequencing Libraries and DNA from Limited Tumor Samples Academic Article uri icon

Overview

MeSH Major

  • High-Throughput Nucleotide Sequencing
  • Mutation
  • Neoplasms
  • Polymerase Chain Reaction
  • Receptor, Epidermal Growth Factor

abstract

  • Although next-generation sequencing (NGS) is a robust technology for comprehensive assessment of EGFR-mutant lung adenocarcinomas with acquired resistance to tyrosine kinase inhibitors, it may not provide sufficiently rapid and sensitive detection of the EGFR T790M mutation, the most clinically relevant resistance biomarker. Here, we describe a digital PCR (dPCR) assay for rapid T790M detection on aliquots of NGS libraries prepared for comprehensive profiling, fully maximizing broad genomic analysis on limited samples. Tumor DNAs from patients with EGFR-mutant lung adenocarcinomas and acquired resistance to epidermal growth factor receptor inhibitors were prepared for Memorial Sloan-Kettering-Integrated Mutation Profiling of Actionable Cancer Targets sequencing, a hybrid capture-based assay interrogating 410 cancer-related genes. Precapture library aliquots were used for rapid EGFR T790M testing by dPCR, and results were compared with NGS and locked nucleic acid-PCR Sanger sequencing (reference high sensitivity method). Seventy resistance samples showed 99% concordance with the reference high sensitivity method in accuracy studies. Input as low as 2.5 ng provided a sensitivity of 1% and improved further with increasing DNA input. dPCR on libraries required less DNA and showed better performance than direct genomic DNA. dPCR on NGS libraries is a robust and rapid approach to EGFR T790M testing, allowing most economical utilization of limited material for comprehensive assessment. The same assay can also be performed directly on any limited DNA source and cell-free DNA.

publication date

  • November 2016

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1016/j.jmoldx.2016.07.004

PubMed ID

  • 27631691

Additional Document Info

start page

  • 903

end page

  • 911

volume

  • 18

number

  • 6