Introduction

BACKGROUND: Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped. METHODS: We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci. RESULTS: We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing. CONCLUSIONS: NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

Publications

  1. Microsatellite instability detection by next generation sequencing.
    Cite this
    Salipante SJ, Scroggins SM, Hampel HL, Turner EH, Pritchard CC, 2014-09-01 - Clinical chemistry

Credits

  1. Stephen J Salipante
    Developer

    Department of Laboratory Medicine, University of Washington, United States of America

  2. Sheena M Scroggins
    Developer

    Department of Laboratory Medicine, University of Washington, United States of America

  3. Heather L Hampel
    Developer

    Department of Internal Medicine, Division of Human Genetics

  4. Emily H Turner
    Developer

    Department of Laboratory Medicine, University of Washington, United States of America

  5. Colin C Pritchard
    Investigator

    Department of Laboratory Medicine, University of Washington, United States of America

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Summary
AccessionBT000580
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesPerl
User InterfaceTerminal Command Line
Download Count0
Submitted ByColin C Pritchard