Validation of a next generation sequencing panel for detection of hotspot cancer mutations in a clinical laboratory

Pathol Res Pract. 2017 Feb;213(2):98-105. doi: 10.1016/j.prp.2016.11.016. Epub 2016 Dec 16.

Abstract

Recent advances in sequencing technologies have enabled us to scrutinize the versatile underlying mechanisms of cancer more precisely. However, adopting these new sophisticated technologies is challenging for clinical labs as it involves complex workflows, and requires validation for diagnostic purposes. The aim of this work is towards the analytical validation of a next generation sequencing (NGS) panel for cancer hotspot mutation analysis. Characterized formalin-fixed paraffin-embedded (FFPE) samples including biopsy specimens and cell-lines were examined by NGS methods utilizing the Ion Torrent™ Oncomine™ Focus DNA Assay and the PGM™ platform. Important parameters for somatic mutations including the threshold for differentiation of a positive and a negative result, coverage, sensitivity, specificity, and limit of detection (LoD) were analyzed. Variant calls with coverage of <100x were found to be inaccurate. The limit of detection for identifying hotspot mutations was determined to be 4.3%. The sensitivity and specificity of the method were 96.1% and 97.8% respectively. No statistically significant difference was found between different gene targets in terms of performance of hotspot frequency measurement for the subset tested. In every validation study, the number of samples, the manner of sample selection, and the number and type of variants play a role in the outcome. Therefore, these parameters should be assessed according to the clinical needs of each laboratory undertaking the validation.

Keywords: Cancer; Clinical laboratory; Next generation sequencing; Test validation.

Publication types

  • Validation Study

MeSH terms

  • DNA Mutational Analysis / methods*
  • DNA Mutational Analysis / standards
  • High-Throughput Nucleotide Sequencing / standards*
  • Humans
  • Mutation*
  • Reproducibility of Results
  • Sensitivity and Specificity