Memorial sloan kettering-integrated mutation profiling of actionable cancer targets (MSK-IMPACT): A hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology Academic Article uri icon

Overview

MeSH Major

  • DNA Mutational Analysis
  • High-Throughput Nucleotide Sequencing
  • Neoplasms

abstract

  • The identification of specific genetic alterations as key oncogenic drivers and the development of targeted therapies are together transforming clinical oncology and creating a pressing need for increased breadth and throughput of clinical genotyping. Next-generation sequencing assays allow the efficient and unbiased detection of clinically actionable mutations. To enable precision oncology in patients with solid tumors, we developed Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a hybridization capture-based next-generation sequencing assay for targeted deep sequencing of all exons and selected introns of 341 key cancer genes in formalin-fixed, paraffin-embedded tumors. Barcoded libraries from patient-matched tumor and normal samples were captured, sequenced, and subjected to a custom analysis pipeline to identify somatic mutations. Sensitivity, specificity, reproducibility of MSK-IMPACT were assessed through extensive analytical validation. We tested 284 tumor samples with previously known point mutations and insertions/deletions in 47 exons of 19 cancer genes. All known variants were accurately detected, and there was high reproducibility of inter- and intrarun replicates. The detection limit for low-frequency variants was approximately 2% for hotspot mutations and 5% for nonhotspot mutations. Copy number alterations and structural rearrangements were also reliably detected. MSK-IMPACT profiles oncogenic DNA alterations in clinical solid tumor samples with high accuracy and sensitivity. Paired analysis of tumors and patient-matched normal samples enables unambiguous detection of somatic mutations to guide treatment decisions.

publication date

  • January 2015

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1016/j.jmoldx.2014.12.006

PubMed ID

  • 25801821

Additional Document Info

start page

  • 251

end page

  • 64

volume

  • 17

number

  • 3