Validation of OncoPanel: A Targeted Next-Generation Sequencing Assay for the Detection of Somatic Variants in Cancer. Academic Article uri icon

Overview

abstract

  • CONTEXT: - The analysis of somatic mutations across multiple genes in cancer specimens may be used to aid clinical decision making. The analytical validation of targeted next-generation sequencing panels is important to assess accuracy and limitations. OBJECTIVE: - To report the development and validation of OncoPanel, a custom targeted next-generation sequencing assay for cancer. DESIGN: - OncoPanel was designed for the detection of single-nucleotide variants, insertions and deletions, copy number alterations, and structural variants across 282 genes with evidence as drivers of cancer biology. We implemented a validation strategy using formalin-fixed, paraffin-embedded, fresh or frozen samples compared with results obtained by clinically validated orthogonal technologies. RESULTS: - OncoPanel achieved 98% sensitivity and 100% specificity for the detection of single-nucleotide variants, and 84% sensitivity and 100% specificity for the detection of insertions and deletions compared with single-gene assays and mass spectrometry-based genotyping. Copy number detection achieved 86% sensitivity and 98% specificity compared with array comparative genomic hybridization. The sensitivity of structural variant detection was 74% compared with karyotype, fluorescence in situ hybridization, and polymerase chain reaction. Sensitivity was affected by inconsistency in the detection of FLT3 and NPM1 alterations and IGH rearrangements due to design limitations. Limit of detection studies demonstrated 98.4% concordance across triplicate runs for variants with allele fraction greater than 0.1 and at least 50× coverage. CONCLUSIONS: - The analytical validation of OncoPanel demonstrates the ability of targeted next-generation sequencing to detect multiple types of genetic alterations across a panel of genes implicated in cancer biology.

publication date

  • March 3, 2017

Research

keywords

  • Genetic Variation
  • High-Throughput Nucleotide Sequencing
  • Neoplasms

Identity

Scopus Document Identifier

  • 85020162020

Digital Object Identifier (DOI)

  • 10.5858/arpa.2016-0527-OA

PubMed ID

  • 28557599

Additional Document Info

volume

  • 141

issue

  • 6