Rapid, reliable, and reproducible molecular sub-grouping of clinical medulloblastoma samples

Paul A. Northcott, David J.H. Shih, Marc Remke, Yoon Jae Cho, Marcel Kool, Cynthia Hawkins, Charles G. Eberhart, Adrian Dubuc, Toumy Guettouche, Yoslayma Cardentey, Eric Bouffet, Scott L. Pomeroy, Marco Marra, David Malkin, James T. Rutka, Andrey Korshunov, Stefan Pfister, Michael D. Taylor

Research output: Contribution to journalArticlepeer-review

299 Scopus citations

Abstract

The diagnosis of medulloblastoma likely encompasses several distinct entities, with recent evidence for the existence of at least four unique molecular subgroups that exhibit distinct genetic, transcriptional, demographic, and clinical features. Assignment of molecular subgroup through routine profiling of high-quality RNA on expression microarrays is likely impractical in the clinical setting. The planning and execution of medulloblastoma clinical trials that stratify by subgroup, or which are targeted to a specific subgroup requires technologies that can be economically, rapidly, reliably, and reproducibly applied to formalin-fixed paraffin embedded (FFPE) specimens. In the current study, we have developed an assay that accurately measures the expression level of 22 medulloblastoma subgroup-specific signature genes (CodeSet) using nanoString nCounter Technology. Comparison of the nanoString assay with Affymetrix expression array data on a training series of 101 medulloblastomas of known subgroup demonstrated a high concordance (Pearson correlation r = 0.86). The assay was validated on a second set of 130 non-overlapping medulloblastomas of known subgroup, correctly assigning 98% (127/130) of tumors to the appropriate subgroup. Reproducibility was demonstrated by repeating the assay in three independent laboratories in Canada, the United States, and Switzerland. Finally, the nanoString assay could confidently predict subgroup in 88% of recent FFPE cases, of which 100% had accurate subgroup assignment. We present an assay based on nanoString technology that is capable of rapidly, reliably, and reproducibly assigning clinical FFPE medulloblastoma samples to their molecular subgroup, and which is highly suited for future medulloblastoma clinical trials.

Original languageEnglish (US)
Pages (from-to)615-626
Number of pages12
JournalActa Neuropathologica
Volume123
Issue number4
DOIs
StatePublished - Apr 2012
Externally publishedYes

Keywords

  • Clinical trials
  • Medulloblastoma
  • Molecular classification
  • NanoString

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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