Metabolism Microenvironment-Derived Regulation of HIF Signaling Drives Transcriptional Heterogeneity in Glioblastoma Multiforme Dieter Henrik Heiland 1,10 , Annette Gaebelein 1,10 , Melanie B € orries 2,3 , Jakob W€ orner 4 , Nils Pompe 4 , Pamela Franco 1,10 , Sabrina Heynckes 1,10 , Mark Bartholomae 5,10 , Darren  O. hAilín 1,10,11 , Maria Stella Carro 1,10 , Marco Prinz 6,7,10 , Stefan Weber 4 , Irina Mader 8,9,10 , Daniel Delev 1,10 , and Oliver Schnell 1,10 Abstract The evolving and highly heterogeneous nature of malignant brain tumors underlies their limited response to therapy and poor prognosis. In addition to genetic alterations, highly dynamic processes, such as transcriptional and metabolic reprogramming, play an important role in the development of tumor heteroge- neity. The current study reports an adaptive mechanism in which the metabolic environment of malignant glioma drives transcrip- tional reprogramming. Multiregional analysis of a glioblastoma patient biopsy revealed a metabolic landscape marked by varying stages of hypoxia and creatine enrichment. Creatine treatment and metabolism was further shown to promote a synergistic effect through upregulation of the glycine cleavage system and chemical regulation of prolyl-hydroxylase domain. Consequently, creatine maintained a reduction of reactive oxygen species and change of the a-ketoglutarate/succinate ratio, leading to an inhibition of HIF signaling in primary tumor cell lines. These effects shifted the transcriptional pattern toward a proneural subtype and reduced the rate of cell migration and invasion in vitro. Implications: Transcriptional subclasses of glioblastoma multi- forme are heterogeneously distributed within the same tumor. This study uncovered a regulatory function of the tumor microenviron- ment by metabolism-driven transcriptional reprogramming in infil- trating glioma cells. Mol Cancer Res; 16(4); 655–68. Ó2018 AACR. Introduction Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults, with an annual inci- dence of 3 to 4 cases per 100,000 people in Europe (1, 2) and the United states (3). In spite of the best available treatment, the prognosis for patients with GBM is poor, with a median survival of 14 to 16 months (4–8). During the past decade, technical advances in high-throughput analysis led to the classification of GBM based on their mutational, transcription- al, or epigenetic profiles. Several recent profiling studies have found that the proneural and mesenchymal expression pheno- types were the only classifications that could be consistently validated (9–12). Although these classifications provide useful insight into the broad transcriptional identity of a GBM tumor, genetic classifications based on single biopsies are biased by tumor heterogeneity, which is a hallmark of the malignant and resistant character of GBM. Heterogeneity is defined by different cell subpopulations with- in the same tumor harboring distinct genetic or gene expression profiles (13, 14). At present, few studies have uncovered the mutational heterogeneity of GBM and explored the clonal archi- tecture of glioma (15). However, the mutational architecture of a tumor is relatively stable by nature (15). In contrast to these stable heterogenic clusters, Patel and colleagues investigated the tran- scriptional heterogeneity in GBM and described a highly incon- sistent expression profile of different cells within the same tumor. Most notably, the expression subtypes characterized by Verhaak and colleagues were found to be heterogeneously distributed within the same tumor specimen (14, 16–19). Metabolism is recognized as one of the most dynamic factors within GBM tumors and their surrounding environment and serves as a potential mediator of transcriptional identity (20). Metabolic reprogramming in normal brain conditions has been shown to play an important role in neural differentiation and 1 Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg im Breisgau, Germany. 2 Institute of Molecular Medicine and Cell Research, Albert-Ludwigs-University, Freiburg im Breisgau, Germany. 3 German Cancer Consortium (DKTK), Freiburg and German Cancer Research Center (DKFZ), Heidelberg, Germany. 4 Institute of Physical Chemistry, Faculty of Chemistry and Pharmacy, University of Freiburg, Freiburg im Breisgau, Germany. 5 Department of Nuclear Medicine, Medical Center - University of Freiburg, Freiburg im Breisgau, Germany. 6 Institute of Neuropathology, Medical Center - University of Freiburg, Freiburg im Breisgau, Germany. 7 BIOSS Centre for Biological Signalling Studies, University of Freiburg, Freiburg im Breisgau, Germany. 8 Department of Neuroradiology, Medical Center - University of Freiburg, Freiburg im Breisgau, Germany. 9 Clinic for Neuropediatrics and Neurorehabilitation, Epilepsy Center for Children and Adolescents, Sch€ on Klinik, Vogtareuth, Germany. 10 Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany. 11 Faculty of Biology, University of Freiburg, Freiburg im Breisgau, Germany. Note: Supplementary data for this article are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/). D.H. Heiland and A. Gaebelein contributed equally to this article. Corresponding Author: Dieter Henrik Heiland, Department of Neurosurgery, University of Freiburg, Breisacher Straße 64, Freiburg 79106, Germany. Phone: 49-761-2705-0010; Fax: 49-761-2705-0010; E-mail: dieter.henrik.heiland@uniklinik-freiburg.de doi: 10.1158/1541-7786.MCR-17-0680 Ó2018 American Association for Cancer Research. Molecular Cancer Research www.aacrjournals.org 655 Downloaded from http://aacrjournals.org/mcr/article-pdf/16/4/655/2311979/655.pdf by guest on 14 June 2022