A transcriptome-based classifier to determine molecular subtypes in medulloblastoma

PLoS Comput Biol. 2020 Oct 29;16(10):e1008263. doi: 10.1371/journal.pcbi.1008263. eCollection 2020 Oct.

Abstract

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data. We have developed a GPL-3 licensed R package and a Shiny Application to enable users to quickly and robustly classify medulloblastoma samples using transcriptomic data. The classifier utilizes a large composite microarray dataset (15 individual datasets), an individual microarray study, and an RNA-Seq dataset, using gene ratios instead of gene expression measures as features for the model. Discriminating features were identified using the limma R package and samples were classified using an unweighted mean of normalized scores. We utilized two training datasets and applied the classifier in 15 separate datasets. We observed a minimum accuracy of 85.71% in the smallest dataset and a maximum of 100% accuracy in four datasets with an overall median accuracy of 97.8% across the 15 datasets, with the majority of misclassification occurring between the heterogeneous Group 3 and Group 4 subtypes. We anticipate this medulloblastoma transcriptomic subtype classifier will be broadly applicable to the cancer research and clinical communities.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cerebellar Neoplasms* / classification
  • Cerebellar Neoplasms* / genetics
  • Cerebellar Neoplasms* / metabolism
  • Databases, Genetic
  • Gene Expression Profiling / methods*
  • Genomics
  • Humans
  • Medulloblastoma* / classification
  • Medulloblastoma* / genetics
  • Medulloblastoma* / metabolism
  • Oligonucleotide Array Sequence Analysis
  • Software*
  • Transcriptome / genetics*