Differential expression and prognostic significance of SOX genes in pediatric medulloblastoma and ependymoma identified by microarray analysis.

The objective of this study was to identify differentially expressed and prognostically important genes in pediatric medulloblastoma and pediatric ependymoma by Affymetrix microarray analysis. Among the most discriminative genes, three members of the SOX transcription factor family were differentially expressed. Both SOX4 and SOX11 were significantly overexpressed in medulloblastoma (median, 11-fold and 5-fold, respectively) compared with ependymoma and normal cerebellum. SOX9 had greater expression in ependymoma (median, 16-fold) compared with normal cerebellum and medulloblastoma (p<0.001 for all comparisons). The differential expression of the SOX genes was confirmed at the protein level by immunohistochemical analysis. Survival analysis of the most discriminative probe sets for each subgroup showed that 35 and 13 probe sets were predictive of survival in patients with medulloblastoma and ependymoma, respectively. There was a trend toward better survival with increasing SOX4 expression in medulloblastoma. SOX9 expression was predictive for favorable outcome in ependymoma. The mRNA levels of BCAT1, a mediator of amino acid breakdown, were higher (median, 15-fold) in medulloblastoma patients with metastases compared with those without metastasized disease (p<0.01). However, the correlation between BCAT1 expression and metastatic medulloblastoma could not be confirmed at the protein level. The potential prognostic effect of the genes associated with outcome should be evaluated in ongoing studies using larger groups of patients. Furthermore, our findings support further analysis of the functional properties of the selected genes, especially SOX4 and BCAT1 for medulloblastoma and SOX9 for ependymoma, to evaluate the use of these genes as potential tumor markers, prognostic markers, and drug targets in pediatric brain tumors.

• View at Publisher
• View at Scopus
• View at Web of Science