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Gene Expression Profiles Associated with Treatment Response in Oligodendrogliomas

Departments of ¹ Neurology, ² Bioinformatics, ³ Pathology, ⁴ Medical Oncology, and ⁵ Cell Biology and Genetics, Cancer Genomics Center, Erasmus Medical Center, Rotterdam, the Netherlands

Requests for reprints: Pim J. French, Department Neurology, Josephine Nefkens Institute, Erasmus Medical Center, Room Be462a, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands. Phone: 31-10-408-8333; Fax: 31-10-408-8365; E-mail: p.french{at}erasmusmc.nl.

Oligodendrogliomas are a specific subtype of brain tumor of which the majority responds favorably to chemotherapy. In this study, we made use of expression profiling to identify chemosensitive oligodendroglial tumors. Correlation of expression profiles to loss of heterozygosity on 1p and 19q, common chromosomal aberrations associated with response to treatment, identified 376, 64, and 60 differentially expressed probe sets associated with loss of 1p, 19q or 1p, and 19q, respectively. Correlation of expression profiles to the tumors' response to treatment identified 16 differentially expressed probe sets. Because transcripts associated with chemotherapeutic response were identified independent of common chromosomal aberrations, expression profiling may be used as an alternative approach to the tumors' 1p status to identify chemosensitive oligodendroglial tumors. Finally, we correlated expression profiles to survival of the patient after diagnosis and identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed between long and short survivors indicates that the genetic background of the tumor is an important factor in determining the prognosis of the patient. Furthermore, these transcripts can help identify patient subgroups that are associated with favorable prognosis. Our study is the first to correlate gene expression with chromosomal aberrations and clinical performance (response to treatment and survival) in oligodendrogliomas. The differentially expressed transcripts can help identify patient subgroups with good prognosis and those that will benefit from chemotherapeutic treatments. (Cancer Res 2005; 65(24): 11335-44)

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