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// Biljana Stangeland 1, 2 , Awais A. Mughal 1 , Zanina Grieg 1, 4 , Cecilie Jonsgar Sandberg 1 , Mrinal Joel 1, 4, 5 , Ståle Nygård 3 , Torstein Meling 1 , Wayne Murrell 1 , Einar O. Vik Mo 1 , Iver A. Langmoen 1, 2, 4 1 Vilhelm Magnus Laboratory for Neurosurgical Research, Institute for Surgical Research and Department of Neurosurgery, Oslo University Hospital, Oslo, Norway 2 SFI-CAST Biomedical Innovation Center, Oslo University Hospital, Oslo, Norway 3 Bioinformatics Core Facility, Institute for Medical Informatics, Oslo University Hospital and University of Oslo, Oslo, Norway 4 Norwegian Center for Stem Cell Research, Department of Immunology and Transfusion Medicine, Oslo University Hospital, Oslo, Norway 5 Laboratory of Neural Development and Optical Recording (NDEVOR), Department of Physiology, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway Correspondence to: Biljana Stangeland, e-mail: Biljana.Stangeland@labmed.uio.no Keywords: glioblastoma, GBM, glioblastoma stem cells, GSCs, therapeutic targeting Received: February 13, 2015 Accepted: July 10, 2015 Published: July 20, 2015 ABSTRACT Glioblastoma (GBM) is both the most common and the most lethal primary brain tumor. It is thought that GBM stem cells (GSCs) are critically important in resistance to therapy. Therefore, there is a strong rationale to target these cells in order to develop new molecular therapies. To identify molecular targets in GSCs, we compared gene expression in GSCs to that in neural stem cells (NSCs) from the adult human brain, using microarrays. Bioinformatic filtering identified 20 genes ( PBK/TOPK, CENPA, KIF15, DEPDC1, CDC6, DLG7/DLGAP5/HURP, KIF18A, EZH2, HMMR/RHAMM/CD168, NOL4, MPP6, MDM1, RAPGEF4, RHBDD1, FNDC3B, FILIP1L, MCC, ATXN7L4/ATXN7L1, P2RY5/LPAR6 and FAM118A ) that were consistently expressed in GSC cultures and consistently not expressed in NSC cultures. The expression of these genes was confirmed in clinical samples (TCGA and REMBRANDT). The first nine genes were highly co-expressed in all GBM subtypes and were part of the same protein-protein interaction network. Furthermore, their combined up-regulation correlated negatively with patient survival in the mesenchymal GBM subtype. Using targeted proteomics and the COGNOSCENTE database we linked these genes to GBM signalling pathways. Nine genes: PBK, CENPA, KIF15, DEPDC1, CDC6, DLG7, KIF18A, EZH2 and HMMR should be further explored as targets for treatment of GBM.
Stangeland et al. (Mon,) studied this question.