Expression profiling of primary glioma samples

Background: Signaling by receptor tyrosine kinases (RTK) is frequently dysregulated in gliomas. Inter-individual variability in the causes for dysregulated RTK signaling may have hampered the efficacy of targeted therapies. Using gene expression modules around key regulators in the RAS-RAF-MEK-MAPK cascade and in the phosphatidylinositol 3-kinase-AKT pathways, we developed a “RMPA” clustering scheme to distinguish gliomas with varying extents of RTK signaling. Results: We identified gene modules consistently co-expressed with NF1 (NF1-M), Sprouty (SPRY-M) and PTEN (PTEN-M) in gliomas. Their signatures enabled robust clustering of adult diffuse gliomas of WHO grades II-IV into RMPAhigh and RMPAlow phenotypes in a morphology-independent manner. In five independent data sets from three continents containing more than 1500 adult diffuse gliomas, RMPAhigh gliomas were associated with poor prognosis while RMPAlow gliomas were not. The RMPAhigh and RMPAlow glioma subtypes showed distinct levels of the activities of RAS-RAF-MEK-MAPK cascade and PI3K-AKT pathway and harbored unique sets of genomic alterations in the RTK signaling-related genes. The RMPAhigh gliomas contained large numbers of immature vessel cells and tumor associated macrophages and both cell types expressed high levels of pro-angiogenic RTKs including MET, VEGFR1, KDR, EPHB4 and NRP1. Conclusion: Inter-glioma variability in RTK signaling activities can be defined using the RMPA clustering scheme. The combined signatures of NF1-M, SPRY-M and PTEN-M reflect RTK signaling activity both in the glioma cells and in the glioma microenvironment. Our data show that RTK signaling in the glioma microenvironment may play a pivotal role in glioma progression. Transcriptome data from 22 fresh gliomas (2 astrocytoma II, 1 oligodendrocytoma II, 7 oligoastrocytoma II, 4 anaplastic oligoastrocytoma III and 8 GBM) were obtained using Affymetrix Human Gene 1.0 ST Array. Unsupervised hierarchical clustering of the expression data for the SPRY-M, NF1-M and PTEN-M was performed on these transcriptome data to identify samples with RMPAhigh or RMPAlow signature.