Gliomas are the most frequent primary brain tumors in adults. Despite multimodality treatment strategies, the survival of patients with a diffuse glioma remains poor. There has been an increasing use of molecular markers to assist diagnosis and predict prognosis and response to therapy. Although several prognostic and predictive response markers have been identified, considerable research still needs to be done to improve on these. Therefore, the identification of novel predictive response markers and therapeutic targets are desperately needed for this dismal disease.

In this thesis, we describe prognostic and identify novel predictive markers in randomized clinical trials. We determined the gene expression profiles of samples of anaplastic oligodendrogliomas and oligoastrocytomas from the EORTC 26951 study and samples of recurrent glioblastomas of the BELOB study to evaluate the treatment responses within defined intrinsic glioma subtypes (IGSs). IGSs are molecularly similar tumors that have been previously identified by unsupervised gene expression analysis. We found that IGSs can be used to assess the molecular heterogeneity within clinical trials. In addition, we confirmed that IGS subtypes are prognostic for survival and predictive. Tumors assigned to IGS-9 showed benefit from adjuvant PCV chemotherapy. In the BELOB study, we found that tumors assigned to IGS-18 (classical GBMs) showed a trend towards benefit from Beva+CCNU treatment. Expression of FMO4 and OSBPL3 were particularly associated with treatment response. Intrinsic subtypes can therefore be used to assess the molecular heterogeneity within clinical trials and may be used as a prognostic and predictive marker.

Another method to profile gliomas is based on DNA methylation. We performed genome-wide methylation profiling on material from EORTC 26951 and assessed CIMP and MGMT-STP27 status. We have shown that survival in patients with CIMP+ or MGMT-STP27 methylated tumors was improved compared to CIMP- and/or MGMT-STP27 unmethylated tumors. Importantly, the MGMT-STP27 status was predictive for response to adjuvant PCV chemotherapy in these tumors. MGMT-STP27 may therefore be used to identify AODs and AOAs with improved prognosis and identify patients that are likely to benefit from adjuvant PCV chemotherapy.
We also performed functional analysis on different mutations on the EGFR gene and infrequently mutated genes in oligodendrogliomas. We have shown that different mutations within a single gene (EGFR) can have different molecular consequences and have different binding partners for EGFRvIII, EGFRL858 and EGFRwildtype. As these mutations have different functions, each mutation may need its own unique treatment. Functional analysis on infrequently mutated genes showed that the function of many of ‘low frequency’ genes, differs from its wildtype counterpart. This differential effect suggests that these genes can contribute to the disease and therefore may offer new therapeutic targets for oligodendrogliomas.

Additional Metadata
Keywords Glioma, predictive response markers, expression profiling
Promotor P.A.E. Sillevis Smitt (Peter) , P.J. French (Pim)
Publisher Erasmus University Rotterdam
ISBN 978-94-6169-831-5
Persistent URL
Erdem-Eraslan, L. (2016, March 15). Identification of Predictive Response Markers and Novel Treatment Targets for Gliomas. Erasmus University Rotterdam. Retrieved from