The accuracy of survival time prediction for patients with glioma is improved by measuring mitotic spindle checkpoint gene expression

PLoS One. 2011;6(10):e25631. doi: 10.1371/journal.pone.0025631. Epub 2011 Oct 12.

Abstract

Identification of gene expression changes that improve prediction of survival time across all glioma grades would be clinically useful. Four Affymetrix GeneChip datasets from the literature, containing data from 771 glioma samples representing all WHO grades and eight normal brain samples, were used in an ANOVA model to screen for transcript changes that correlated with grade. Observations were confirmed and extended using qPCR assays on RNA derived from 38 additional glioma samples and eight normal samples for which survival data were available. RNA levels of eight major mitotic spindle assembly checkpoint (SAC) genes (BUB1, BUB1B, BUB3, CENPE, MAD1L1, MAD2L1, CDC20, TTK) significantly correlated with glioma grade and six also significantly correlated with survival time. In particular, the level of BUB1B expression was highly correlated with survival time (p<0.0001), and significantly outperformed all other measured parameters, including two standards; WHO grade and MIB-1 (Ki-67) labeling index. Measurement of the expression levels of a small set of SAC genes may complement histological grade and other clinical parameters for predicting survival time.

Publication types

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

MeSH terms

  • Cell Cycle Proteins / genetics
  • Cell Cycle Proteins / metabolism
  • Cell Line, Tumor
  • Databases, Genetic
  • Gene Expression Regulation, Neoplastic*
  • Glioma / genetics*
  • Glioma / mortality
  • Glioma / pathology*
  • Humans
  • Kaplan-Meier Estimate
  • M Phase Cell Cycle Checkpoints / genetics*
  • Models, Genetic
  • Multivariate Analysis
  • Neoplasm Grading
  • Oligonucleotide Array Sequence Analysis
  • Polymerase Chain Reaction
  • Prognosis
  • Reproducibility of Results
  • Statistics, Nonparametric
  • Time Factors
  • World Health Organization

Substances

  • Cell Cycle Proteins