Annexin-A2: Role and Regional Expression

Aus der Klinik für Neurochirurgie

der Albert-Ludwigs-Universität Freiburg

Annexin-A2: role and regional expression

in glioblastoma multiforme

INAUGURAL-DISSERTATION

Zur Erlangung des medizinischen Doktorgrades

der Medizinischen Fakultät der

Albert-Ludwigs-Universität Freiburg i. Br.

Vorgelegt 2017

von Ioannis Vasilikos

geboren in Chorlargos , Attiki , Griechenland

Dekanin: Prof. Dr. Kerstin Krieglstein

Erstgutachterin: PD Dr. Astrid Weyerbrock

Zweitgutachter: PD Dr. Rainer Claus

Jahr der Promotion: 2017

Erklärung nach §2 Abs.2 Nr. 5 und 6

Ich erkläre hiermit, dass ich die der Medizinischen Fakultät der Albert-Ludwigs-Universität Freiburg i. Br. Zur Promotion eingereichten Dissertation mit dem Titel „ Annexin-A2: role and regional expression in glioblastoma multiforme “ in der Klinik für Neurochirurgie der Albert- Ludwigs-Universität Freiburg i. Br. unter der Betreuung von PD. Dr. A. Weyerbrock ohne unzulässige Hilfe Dritter und ohne Benutzung anderer als der angegebenen Hilfsmittel angefertigt habe. Die aus anderen Quellen direkt oder indirekt entnommenen Daten und Konzepte sind unter Angaben der Quellen gekennzeichnet. Insbesondere habe ich hierfür nicht die entgeltliche Hilfe von Vermittlungs- bzw. Beratungsdiensten in Anspruch genommen. Niemand hat von mir unmittelbar oder mittelbar geldwertige Leistungen für Arbeiten erhalten, die im Zusammenhang mit dem Inhalt der vorgelegten Dissertation stehen. Ich habe diese Dissertation bisher weder im In- noch im Ausland in gleicher Form oder ähnlicher Form einer anderen Prüfungsbehörde vorgelegt. Weiterhin versichere ich, dass ich den beantragten Titel bisher noch nicht erworben habe.

to my wife and children

Table of Contents 1. INTRODUCTION ...... 11 1.1. GLIOBLASTOMA MULTIFORME ...... 11 1.2 MOLECULAR GENETICS AND CLASSIFICATION OF GLIOBLASTOMA ...... 13 1.3 BRAIN CANCER PROPAGATING CELLS ...... 18 1.4 THERAPY ...... 20 1.4.1 Standard treatment ...... 20 1.4.2 First generation of targeted molecular treatment ...... 21 1.5 CELL BIOLOGY OF ANNEXIN A2 ...... 22 1.5.1 Annexin protein family ...... 22 1.5.2 Functions of Annexin A2 ...... 24 1.5.3 The role of Annexin A2 in Cancer ...... 28 1.5.4 The role of ANXA2 in GBM ...... 29 1.5.5 Intratumor heterogeneity in human glioblastoma ...... 30 1.5.6 The importance of the peritumoral zone ...... 31 2. AIM ...... 31 3 MATERIAL & METHODS ...... 33 3.1 MATERIALS & CHEMICALS ...... 33 3.1.1 Chemicals ...... 33 3.1.2 Materials ...... 37 3.1.3 Media ...... 40 3.1.4 Specimens ...... 41 3.2 METHODS ...... 42 3.2.1 Classification of brain tumor samples...... 42 3.2.2 Glioma tissue collection ...... 43 3.2.3 MRI-navigated GBM tissue collection...... 44 3.2.4 Immunostaining...... 48 3.2.5 RNA extraction ...... 49 3.2.6 Quantitative Real-Time PCR ...... 50 3.2.7 Statistical Analysis of Quantitative Real-Time PCR ...... 50 4. RESULTS ...... 51 4.1 ANXA2 expression in high versus low-grade gliomas ...... 51 4.2 ANXA2 differential expression between mesenchymal and non-mesenchymal GBMs ...... 55 4.3 Regional expression of ANXA2 in mesenchymal and non-mesenchymal GBMs ...... 57 5. DISCUSSION ...... 62 6. SUMMARY ...... 66 ZUSAMMENFASSUNG ...... 67 REFERENCES ...... 68 DANKSAGUNG ...... 81 LEBENSLAUF ...... 82

List of figures

FIGURE 1: MRI T1-WEIGHTED WITH CONTRAST AGENT (LEFT) AND F18-FLUORODEOXYGLYCOSE-POSITRON EMISSION TOMOGRAPHY (FDG-PET) (RIGHT), OVERLAY OF MRI AND FET-PET (MIDDLE)...... 11 FIGURE 2: KEY CHARACTERISTICS OF IDH-WILDTYPE AND IDH-MUTANT GLIOBLASTOMAS(81,82)...... 12 FIGURE 3: SEQUENTIAL GENETIC CHANGES OBSERVED IN THE PATHOGENESIS OF DIFFERENT SUBTYPES OF GLIOBLASTOMA. SOME CELLS IN THE NORMAL BRAIN UNDERGO GENETIC ALTERATIONS WHICH LEADS TO A POPULATION OF TUMOR–INITIATING CELLS (TICS) WHICH CAN THEN FURTHER ACCUMULATE GENETIC AND EPIGENETIC CHANGES AND BECOME BRAIN CANCER–PROPAGATING CELLS (BCPC). THE LATTER CELLS ARE RESPONSIBLE FOR THE FORMATION OF GLIOBLASTOMA. VERHAAK ET AL. (3) ...... 16 FIGURE 4: GENETIC ALTERATIONS IN GLIOBLASTOMA OCCUR FREQUENTLY IN THREE CELLULAR SIGNALING PATHWAYS. DNA ALTERATIONS AND COPY NUMBER CHANGES IN THE FOLLOWING SIGNALING PATHWAYS ARE INDICATED IN (A) RECEPTOR TYROSINE KINASE (RTK), RAS, AND PHOSPHOINOSITOL–3–KINASE (PI3K); (B) P53 TUMOR SUPPRESSOR; AND (C) RETINOBLASTOMA (RB) TUMOR SUPPRESSOR. ACTIVATING GENETIC ALTERATIONS ARE SHOWN IN RED. GENETIC ALTERATIONS THAT LEAD TO A LOSS OF FUNCTION ARE INDICATED IN BLUE. IN EACH PATHWAY, THE ALTERED COMPONENTS, THE TYPE OF ALTERATION, AND THE PERCENTAGE OF TUMORS CARRYING EACH ALTERATION ARE SHOWN. BLUE BOXES CONTAIN THE TOTAL PERCENTAGES OF GLIOBLASTOMAS WITH ALTERATIONS IN AT LEAST ONE KNOWN COMPONENT GENE OF THE DESIGNATED PATHWAY. EGFR INDICATES EPIDERMAL GROWTH FACTOR RECEPTOR; MET, MESENCHYMAL- EPITHELIAL TRANSITION FACTOR; PDGFRA, PLATELET-DERIVED GROWTH FACTOR RECEPTOR–A; PTEN, PHOSPHATASE AND TENSIN HOMOLOG. REPRINTED WITH PERMISSION FROM THE CANCER GENOME ATLAS RESEARCH NETWORK. COMPREHENSIVE GENOMIC CHARACTERIZATION DEFINES HUMAN GLIOBLASTOMA GENES AND CORE PATHWAYS. NATURE. 2008;455: 1061-1068. (26) ...... 18 FIGURE 5: POSSIBLE LINEAGE RELATIONS FOR THE ONTOGENY AND PRODUCTION OF BRAIN CANCER–PROPAGATING CELLS (BCPCS) AND GENERATION OF GLIOBLASTOMA MULTIFORME (GBM) TUMORS. ADAPTED WITH KIND PERMISSION OF SPRINGER SCIENCEBUSINESS MEDIA FROM FIGURE 2 IN HADJIPANAYIS CG, ET AL., INITIATING CELLS IN MALIGNANT GLIOMAS: BIOLOGY AND IMPLICATIONS FOR THERAPY. J MOL MED. 2009;87 :363-374.15 © SPRINGER ...... 20 FIGURE 6: CHROMOSOME 15 - NC_000015.10 (SOURCE :HTTP://WWW.NCBI.NLM.NIH.GOV/GENE/302) ...... 23 FIGURE 7: STRUCTURE OF THE ANXA2 PROTEIN. (SOURCE PROTEIN DATA BANK ARCHIVE-INFORMATION ABOUT THE 3D SHAPES OF PROTEINS HTTP://WWW.RCSB.ORG) ...... 24 FIGURE 8: EXPERIMENTAL MODEL OF PLASMIN REGULATION BY CELL SURFACE ANNEXIN A2 AND S100A10. THE HETEROTETRAMERIC COMPLEX CONSISTS OF TWO COPIES OF ANNEXIN A2 AND ONE COPY OF THE S100A10 DIMER. AIIT BINDS THE TISSUE-PLASMINOGEN ACTIVATOR TPA AND PLASMINOGEN AT THE CARBOXYL- TERMINAL LYSINE RESIDUE OF THE S100A10 SUBUNIT. THE ANNEXIN A2 SUBUNIT DOES NOT BIND TPA OR PLASMINOGEN BUT SERVES AS CELL SURFACE RECEPTOR FOR S100A10. THE UROKINASE-PLASMINOGEN ACTIVATOR IS BOUND TO ITS RECEPTOR (UPAR) AND FORMS THE UPA/UPAR COMPLEX THAT COLOCALIZES WITH AIIT. THE CO-LOCALIZATION OF THE PLASMINOGEN ACTIVATORS AND PLASMINOGEN BY AIIT RESULTS IN ACCELERATED CLEAVAGE OF PLASMINOGEN INTO PLASMIN. PLASMIN ACTIVATES PRO-MMPS (MATRIX METALLO-PROTEASES) INTO ACTIVE MMPS AND FURTHER ACTIVATES PRO-UPA INTO ACTIVE UPA (56,57). .... 26 FIGURE 9: A SCHEMATIC REPRESENTATION OF VARIOUS MEMBRANE-TRAFFICKING STEPS SHOWING THE INVOLVEMENT OF ANNEXINS. A | IN THE BIOSYNTHETIC PATHWAY, ANNEXIN A2 IN COMPLEX WITH S100A10 HAS BEEN SHOWN TO PARTICIPATE IN THE CA2+-EVOKED EXOCYTOSIS OF CHROMAFFIN GRANULES AND ENDOTHELIAL WEIBEL– PALADE BODIES. THE COMPLEX PROBABLY FUNCTIONS AT THE LEVEL OF THE PLASMA MEMBRANE, POSSIBLY BY LINKING THE LARGE SECRETORY VESICLES TO THE PLASMA MEMBRANE OR BY ORGANIZING PLASMA-MEMBRANE DOMAINS SO THAT EFFICIENT FUSION CAN TAKE PLACE. ANNEXIN A13B IS REQUIRED FOR THE BUDDING OF SPHINGOLIPID- AND CHOLESTEROL-RICH MEMBRANE DOMAINS AT THE TRANS-GOLGI NETWORK, AND THEREFORE THE DELIVERY OF SUCH MATERIAL TO THE APICAL PLASMA MEMBRANE IN POLARIZED EPITHELIAL CELLS. B | IN THE ENDOCYTIC PATHWAY, ANNEXIN A6 HAS BEEN PROPOSED TO BE INVOLVED IN CLATHRIN- COATED-PIT BUDDING EVENTS THAT DEPEND ON THE ACTIVITY OF A CYSTEINE PROTEASE THAT IS REQUIRED TO 6 MODULATE THE SPECTRIN MEMBRANE SKELETON. ANNEXIN A2, WHICH CAN ASSOCIATE WITH CAVEOLAE, HAS BEEN SHOWN TO FORM A LIPID–PROTEIN COMPLEX WITH ACYLATED CAVEOLIN AND CHOLESTERYL ESTERS THAT SEEMS TO BE INVOLVED IN THE INTERNALIZATION/TRANSPORT OF CHOLESTERYL ESTERS FROM CAVEOLAE TO INTERNAL MEMBRANES. ANNEXIN A2 IS ALSO FOUND ON EARLY ENDOSOMES, WHERE IT IS REQUIRED, IN COMPLEX WITH S100A10, TO MAINTAIN THE CORRECT MORPHOLOGY OF PERINUCLEAR RECYCLING ENDOSOMES. MOREOVER, ITS DEPLETION CAN INTERFERE WITH THE PROPER BIOGENESIS OF MULTIVESICULAR ENDOSOMES FROM EARLY ENDOSOMES. ANNEXIN A1 ALSO SEEMS TO FUNCTION IN MULTIVESICULAR ENDOSOME BIOGENESIS, MORE SPECIFICALLY, IN THE PROCESS OF INWARD VESICLE BUDDING...... 27 FIGURE 10: ROLES OF ANNEXIN A2 AND S100A10 IN TUMORIGENESIS. ANNEXIN A2 AND S100A10 MAY PROMOTE TUMORIGENESIS THROUGH SEVERAL MECHANISMS. ANNEXIN A2 CONTRIBUTES TO TUMORIGENESIS BY STABILIZING S100A10 LEVELS, PREVENTS CELL CYCLE ARREST, PROMOTES CELL PROLIFERATION AND PROTECTS CANCER CELLS FROM OXIDATIVE DAMAGE. S100A10 PARTICIPATES IN TUMORIGENESIS PRIMARILY BY PROMOTING PLASMIN GENERATION, WHICH CONTRIBUTES TO TAM INFILTRATION, ANGIOGENSIS, INVASIVENESS AND METASTASIS AND THE HYPERFIBRINOLYTIC STATE PRESENT IN APL...... 29 FIGURE 11: A: NETWORK REGION THAT INTEGRATES SEVERAL MOLECULAR SPECIES, DISEASE SUBTYPES AND LINEAGE MARKERS. THE FULL NETWORK, ORGANIZED INTO AROUND 500 SUB-NETWORKS CONTAINS 13400 VARIABLES AND MORE THAN 100,000 LINKS BOTH WITHIN AND BETWEEN DATA TYPES. FOR EXAMPLE, AROUND SIXTY DIFFERENT SUBNETWORKS CONTAINED CNA AND/OR LOH OF GENES CLOSELY LOCATED IN THE GENOME, AND ONE SUBNETWORK HARBORS METHYLATION PROBES LOCATED ON THE X CHROMOSOME LINKED TO PATIENT SEX. SUCH SUBNETWORKS OF CNA AND LOH VARIABLES WERE LARGELY EXPLAINED BY GENOMIC STRUCTURE, I.E. LINKING OF NEIGHBORING GENES. THE MODEL CONFIRMED THE EARLIER DISCOVERY OF THE CEBPB ASSOCIATION WITH MESENCHYMAL MARKERS [5], SINCE THE CEBPB MRNA LINKS TO THE MESENCHYMAL SUBTYPE VARIABLE. B: THE CLASSICAL SUBTYPE NODE. THE CLASSICAL SUBTYPE NODE IS ASSOCIATED TO THE COPY NUMBER, LOSS OF HETEROZYGOSITY, AND EXPRESSION OF THE CLOSELY-LOCATED GENES EGFR AND SEC61G. C: THE NETWORK SUGGESTS TESTABLE HYPOTHESES. ANXA2 IS POSITIVELY CONNECTED TO THE MESENCHYMAL SUBTYPE NODE AND NEGATIVELY CONNECTED TO A PROMOTER METHYLATION SITE (PROBE CG08081036). ANXA2 METHYLATION IS IN TURN ASSOCIATED WITH SURVIVAL VIA A SET OF OTHER METHYLATION EVENTS. (KLING, FERRARESE ET.AL 2016) ...... 32 FIGURE 12: FLOW CHART REPRESENTATION OF THE TCGA AND FREIBURG TUMOR BANK DATA SET ANALYSIS ...... 43 FIGURE 13: ZONE A (LIGHT BLUE): NON-ENHANCING PERITUMORAL AREA REFERRED TO AS EDEMA ZONE IN A T1- WEIGHTED MRI WITH GADOLINIUM CONTRAST...... 45 FIGURE 14: ZONE B (RED): GADOLINIUM CONTRAST-ENHANCING ZONE ...... 46 FIGURE 15: ZONE C (BLACK/GRAY): NON-ENHANCING/NECROTIC ZONE ...... 46 FIGURE 16: INTRAOPERATIVE SNAPSHOT FROM NEURONAVIGATION SYSTEM...... 47 FIGURE 17: SCHEMATIC ILLUSTRATION OF THE LOCALIZATION OF THE DIFFERENT GBM REGIONS CONSIDERED FOR SAMPLING (LEFT PANEL), AND REP- PRESENTATIVE MRI DATA USED TO COLLECT NAVIGATED BIOPSIES (RIGHT PANEL). THE EDEMA ZONE IS HIGHLIGHTED IN LIGHT BLUE, THE CONTRAST-ENHANCING ZONE IN RED, AND THE CORE IN BLACK (KLING, FERRARESE ET.AL 2016)...... 47 FIGURE 18: FLOWCHART REPRESENTATION OF ALL STEPS TAKEN FROM COLLECTION TO THE ANALYSIS OF THE TUMOR SAMPLES...... 49 FIGURE 19: ANXA2 EXPRESSION (RNASEQ) OF TCGA GBM AND LGG GRADE II AND III TUMOR SAMPLES. KS-TEST GBM AND LGG GRADE III P-VALUE: 2.0 • 10−35, GBM AND LGG GRADE II: 3.3 • 10−52, AND LGG GRADE III AND II: 5.2 • 10−7. (KLING, FERRARESE ET.AL 2016) ...... 52 FIGURE 20:IMMUNOSTAINING OF ANXA2 (RED) IN LGG, COUNTERSTAINED WITH DAPI (BLUE)...... 53 FIGURE 21: IMMUNOSTAINING OF ANXA2 (RED) IN GBM, COUNTERSTAINED WITH DAPI (BLUE)...... 54 FIGURE 22: ANXA2 EXPRESSION (AFFYMETRIX) OF TCGA MESENCHYMAL AND NON-MESENCHYMAL TUMOR SAMPLES. KS-TEST P-VALUE: 2.7 • 10−31. (KLING, FERRARESE ET.AL 2016) ...... 55 FIGURE 23: ANXA2 EXPRESSION (QPCR) OF UNIV. OF FREIBURG MESENCHYMAL AND NON-MESENCHYMAL TUMOR SAMPLES. KS-TEST P-VALUE: 7.6 • 10−5 (KLING, FERRARESE ET.AL 2016) ...... 56 FIGURE 24: EXEMPLARY BIOANALYZER RNA QUALITY CHECK ON MRI-GUIDED REGIONAL TUMOR SAMPLES. THE QUALITY OF THE RNA IS VISUALIZED BY A VIRTUAL ELECTROPHORESIS GEL (TOP), AND QUANTIFIED BY INDIVIDUAL ELECTROPHEROGRAMS (BOTTOM). ONLY THE SAMPLES WITH RIN>7.00 IN ALL 3 ...... 58 FIGURE 25: RELATIVE ANXA2 AND CHI3L1 EXPRESSION IN TUMOR REGIONAL SAMPLES MEASURED BY QUANTITATIVE REAL-TIME PCR. E: EDEMA ZONE, CE: GADOLINIUM-ENHANCED ZONE, C: CORE...... 59 FIGURE 26: BOX- PLOT GRAPH CORRELATING ANXA2 EXPRESSION WITH GBM REGIONS AND CHI3L1 EXPRESSION. THE GRAPH SHOWS THE SMALLEST AND LARGEST OBSERVATIONS (UPPER AND LOWER WHISKERS, RESPECTIVELY), THE INTERQUARTILE RANGE (BOX), AND THE MEDIAN (BLACK LINE); DATA POINTS ...... 61

List of tables

TABLE 1 : DISTRIBUTION OF FREQUENTLY MUTATED GENES ACROSS GBM SUBTYPES VERHAAK ET AL. (3) ...... 17 TABLE 2: SUMMARY OF THE NEWEST PHARMACEUTICAL AGENTS WITH THEIR MOLECULAR TARGETS AND MECHANISM OF ACTION (29)...... 22 TABLE 3: LIST OF CHEMICALS ...... 37 TABLE 4: LIST OF MATERIALS ...... 40 TABLE 5: LIST OF MEDIUMS ...... 40 TABLE 6: A COHORT OF 24 GBM SAMPLES (SUB-CLASSIFIED AS 9 MESENCHYMAL AND 15 NON-MESENCHYMAL, ACCORDING TO VERHAAK ET AL.) ANALYZED BY QUANTITATIVE REAL-TIME PCR ...... 41 TABLE 7: TISSUE SAMPLES QUALIFIED FOR THE REGIONAL EXPRESSION ANALYSIS GROUPED ACCORDING TO THEIR CHI3L1 EXPRESSION...... 41 TABLE 8: TISSUE SAMPLES USED FOR THE IMMUNOFLUORESCENCE STAINING OF ANXA2 ...... 42 TABLE 9: PRIMERS USED FOR QRT-PCR ...... 51

Abbreviations

AP1 Activator Protein 1 B27 B 27 Supplements Gibco c-Met Hepatocyte Growth Factor Receptor cDNA Converse Deoxyribonucleic acid ChIP Chromatin immunoprecipitation DNA Deoxyribonucleic acid DMEM Dulbecco’s Modified Eagle’s Medium DNMT1 DNA methyltransferase 1 DNMT3a/b DNA methyltransferase 3a/b EDTA Ethylenediamine tetraacetic acid EGF Epidermal Growth Factor EGFR Epidermal Growth Factor Receptor FGF Fibroblast Growth Factor FGFR Fibroblast Growth Factor Receptor GBM Glioblastoma multiforme HCl Hydrochloric acid HDAC Histone Deacetylase HIF Hypoxia-inducible factor HGF Hepatocyte Growth Factor HSP Heat Shock Protein IDH Isocitrate dehydrogenase IP Immunoprecipitation LIF Leukemia inhibitory factor mRNA Messenger RNA mTOR Mechanistic Target of Rapamycin N2 N 2 Supplements Gibco NaCl Sodium chloride NaDeoxycholate Sodium deoxycholate PCR Polymerase Chain Reaction PDGFR Platelet-derived Growth Factor Receptor PI3K Phosphoinositide-3 kinase PKC Protein kinase C PMSF Phenylmethylsulfonyl fluoride q-RT-PCR Quantitative Real-Time PCR RNA Ribonucleic acid SDS Sodium dodecyl sulfate TAE Tris Acetate EDTA TBS Tris Buffered Saline VEGFR Vascular Endothelial Growth Factor Receptor WHO World Health Organization

1. Introduction

1.1. Glioblastoma multiforme

Glioblastoma multiforme is the most common primary brain tumor. The current World Health

Organization (WHO) classification system distinguishes between primary (de novo) and secondary

(WHO grade II and III which transform into grade IV) glioblastomas. WHO grade III and IV are referred to as high grade gliomas (HGGs) representing 60-75% of all gliomas (1). HGGs occur predominantly in the fifth and sixth decade of life. Patients with GBM have a uniformly poor prognosis with a median survival of 16 months (2)

Figure 1: MRI T1-weighted with contrast agent (left) and F18-fluorodeoxyglycose-positron emission tomography (FDG-PET) (right), overlay of MRI and FET-PET (middle). The etiology of GBM is mostly unknown and poorly understood (3). Only 5% of all glioma cases are familial, mostly in connection with syndromes like Cowden’s disease, Li-Fraumeni syndrome

11 and neurofibromatosis (4). Among environmental factors only ionizing radiation is a proven risk factor for the development of GBM.

The updated 2016 version of WHO classification divides glioblastomas using molecular criteria, specifically mutations of IDH. About 90% of cases present the IDH/wildtype mutation which predominates in patients over 55 years of age and is most frequently defined as primary or de novo glioblastoma. The other group (about 10% of cases) presents the IDH-mutation and corresponds to so-called secondary glioblastoma, with a history of prior lower grade diffuse glioma, preferentially arising in younger patients. (5).

Figure 2: Key characteristics of IDH-wildtype and IDH-mutant glioblastomas(81,82).

1.2 Molecular genetics and classification of glioblastoma

Large-scale gene expression profile studies in glioblastoma have demonstrated that transcriptional profiles reflect the underlying tumor biology and can be used to predict tumor classification (e.g. being a surrogate for pathological grading), patient outcome and treatment response. Each tumor is unique in its expression profile and therefore in its biology suggesting that oncological treatment needs to become more personalized. It is possible to cluster the profiles of glioblastoma patients into molecular subtypes defined by combinations of genes that are over- or under-expressed within each group (3). The exciting aspect of defining subgroups within a tumor entity is the possibility that patients within a given group may exhibit similar responses to defined therapies and that by defining the common biology within each group, it is possible to better select specific therapies tailored to the group and test them in clinical trials. This is a major advance because past results of clinical trials may have overlooked successful therapeutic agents because the populations of tested patients were too heterogeneous at the molecular level.

An integrated genomic analysis of 200 GBM samples identified clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR and NF1 (3). Verhaak and colleagues in 2010 expanded previous glioblastoma classification studies by associating known subtypes with specific alterations of NF1 and PDGFRA/IDH1 and by identifying two additional subtypes, one of which is characterized by EGFR abnormalities and wild type TP53. In addition, the subtypes have shown specific differentiation characteristics that suggested a link to different cells of origin. Taken together, these data provide a framework for investigation of targeted therapies (3).

13 According to Verhaak and colleagues (2010), the first subtype has a profile characteristic of highly proliferative cells and was labeled “classical.” Hallmarks of this group are amplification of chromosome 7, loss of chromosome 10 (93%) and frequent focal losses on chromosome 9p21.3

(95%). These chromosomal events lead to amplification of EGFR (in 50% of cases with gene rearrangements) and loss of PTEN and CDKN2A. Alterations of TP53, NF1, PDGFRA, or IDH1 are nearly absent. Classical GBM demonstrates responsiveness to radiation and chemotherapy, most likely because the p53-mediated DNA damage response axis is maintained in this group. Such tumors may also be responsive to Mdm2 inhibitors, the negative regulator of p53. At the gene expression level, the classical subtype demonstrates elevated expression of the neural precursor and stem cell marker NES, and the Notch (NOTCH3, JAG1, and LFNG) and Sonic hedgehog (SMO,

GAS1, and GLI2) signaling pathways.

The second subtype is defined by an expression profile associated with mesenchymal characteristics and angiogenesis and overexpresses CHI3L1 and MET as well as astrocytic markers

CD44 and MERTK and genes in the TNF super family and NFκB pathways (5, 6). This group, called “mesenchymal,” has frequent inactivation of the NF1 (37%), TP53 (32%), and PTEN (32%) genes. These tumors demonstrate response to aggressive chemoradiation therapies and might in addition be responsive to Ras, PI3K, and angiogenesis inhibitors. The process of activating the mesenchymal gene expression signature has been referred to as mesenchymal transformation (7,

8) or mesenchymal differentiation (9). Computational mRNA profiling data analysis has shown genes that modulate mesenchymal transformation in GBM in previous studies. Transcription factors CEBPβ and STAT3 are correlated with mesenchymal differentiation (7) while WWTR1

(a.k.a. TAZ) is found to be an inducer of mesenchymal tumors through recruitment of the WWTR1-

TEAD2 complex to mesenchymal gene promoters (9). Integration of expression, copy number alterations, and mutation data finds amplified and overexpressed RHPN2 involved in the

14 mesenchymal transformation (8). Additionally, microRNA miR-128 and miR-504 expression has been shown to negatively correlate with mesenchymal marker gene expression in GBM (10).

A third subtype, termed “proneural,” has an expression profile reminiscent of gene activation in neuronal development. This includes a high level of expression of oligodendrocytic (PDGFRA,

OLIG2, TCF3, and NKX2-2) and proneural (SOX, DCX, DLL3, ASCL1, and TCF4) development genes. In this group, patients are younger, and overexpression or amplification/mutation of the gene encoding platelet-derived growth factor receptor– (PDGFRA) and mutations of IDH1 (30%) are signature genetic alterations. Frequent mutations in TP53 (54%) and PIK3CA/PIK3R1 (19%) genes are also observed, whereas amplification of chromosome 7 and loss on chromosome 10 are less frequent than in the classical subtype (50%). The finding of IDH1/2 mutations in lower grade gliomas also suggests that secondary glioblastoma might belong to this subtype. This subtype may be most responsive to inhibitors of the hypoxia-inducible factor (HIF), PI3K, and PDGFRA pathways. Survival in the proneural subtype is slightly better than in the other three tumor subtypes, yet these tumors are the least responsive to standard chemoradiation.

The fourth subtype, called “neural,” is less well defined and has gene expression signatures that are most similar to those found in normal brain tissue with activation of neuronal markers such as

NEFL, GABRA1, SYT1, and SLC12A5. These tumors demonstrate a low degree of infiltration by normal cells, excluding bias in the expression analyses. Nevertheless, their expression signature is suggestive of cells with a differentiated phenotype.

Worth of notice is that all subgroups commonly show inactivation of the p53 and retinoblastoma

(Rb) tumor suppressor pathways and activation of the receptor tyrosine kinase (RTK) pathways

(26) (Fig. 3).

Figure 3: “Sequential Genetic Changes Observed in the Pathogenesis of Different Subtypes of Glioblastoma. Some cells in the normal brain undergo genetic alterations which lead to a population of tumor–initiating cells (TICs) which can then further accumulate genetic and epigenetic changes and become brain cancer–propagating cells (BCPC). The latter cells are responsible for the formation of glioblastoma”. Verhaak et al. (3)

Table 1 : “Distribution of Frequently Mutated Genes across GBM Subtypes. Verhaak et al.” (3)

Figure 4: “Genetic Alterations in Glioblastoma Occur Frequently in three Cellular Signaling Pathways. DNA alterations and copy number changes in the following signaling pathways are indicated in (a) receptor tyrosine kinase (RTK), RAS, and phosphoinositol– 3–kinase (PI3K); (b) p53 tumor suppressor; and (c) retinoblastoma (Rb) tumor suppressor. Activating genetic alterations are shown in red. Genetic alterations that lead to a loss of function are indicated in blue. In each pathway, the altered components, the type of alteration, and the percentage of tumors carrying each alteration are shown. Blue boxes contain the total percentages of glioblastomas with alterations in at least one known component gene of the designated pathway. EGFR indicates epidermal growth factor receptor; MET, mesenchymal- epithelial transition factor; PDGFRA, platelet-derived growth factor receptor–A; PTEN, phosphatase and tensin homolog. Reprinted with permission from The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008; 455: 1061-1068.” (26)

1.3 Brain Cancer Propagating Cells

18 A subset of cancer cells, variably termed cancer-propagating cells (CPCs) or cancer stem-like cells, may underlie the growth of different types of cancer and be responsible for their resistance to therapy. (27, 28).

Brain-CPCs are believed to originate from tumor-initiating cells which are present in the early stages of tumor development and have not acquired full tumorigenic capacity (Fig.5). It is unclear whether the growth of primary brain tumors is driven exclusively by CPCs or by all tumor cells.

Since tumors are comprised of a heterogeneous group of cells including differentiated tumor cells,

CPCs and progenitor-like cancer cells, targeting each of these tumor cell types may be necessary for a more efficient treatment of primary brain tumors.

Hadjipanayis, et al (Fig.5) suggested in 2009 a linear ontogeny model for the CPCs and GBM genesis. According to this theoretical model, neural stem cells during the physiological central nervous system differentiation process undergo an amplification step producing transit-amplifying cells, which lead to the genesis of neural/glial progenitor cells. Those cells are able to produce either neural or glial cell lineages but not both. During this process mutations driving GBM-genesis produce tumor initiating cells (TIC). TICs are believed to be stem-like in behavior based on their ability to self-renew, proliferate, and generate BCPCs, differentiated tumor or cancer-like progenitor cells within the tumor mass.

Figure 5: “Possible Lineage Relations for the Ontogeny and Production of Brain Cancer–Propagating Cells (BCPCs) and Generation of Glioblastoma Multiforme (GBM) Tumors.”(27)

1.4 Therapy

1.4.1 Standard treatment

Hallmarks of the GBM therapy are complete tumor resection followed by concurrent temozolomide-/radiotherapy and a subsequent adjuvant temozolomide therapy as described by

Stupp et.al in 2005 (30).

The surgical resection aims to eliminate or reduce the mass effect of the tumor relieving the clinical symptoms and additionally allowing tissue collection from the tumor for further histological and molecular profiling. A complete or near total resection of a glioma confers a significant survival benefit to the patients (31). Sanai et al. observed that the extent of resection is one of the most important factors influencing survival in high- and low-grade gliomas (32).

The chemoradiation therapy following surgical resection, as described by Stupp et.al in 2005, is

20 the standard of care for younger patients with glioblastoma, but with advancing age the benefits may be outweighed by risks of toxicity and side effects (30). Single modality therapy is often better tolerated and is a common approach in older patients and those with a low functional status. In such patients, subgroup analyses from randomized trials support the role of methylguanyl methyltransferase (MGMT) methylation status in helping to select between radiation and temozolomide (60). Temolozomide-induced cell damage is repaired by the DNA repairing enzymes including methylguanyl methyltransferase (MGMT). It is now commonly recognized that silencing of the MGMT gene promoter by methylation is associated with better tumor response to combination treatment with radiation and temozolomide (25, 29). Nonetheless, despite the use of combined modality treatment, most patients eventually relapse.

1.4.2 First generation of targeted molecular treatment

The abnormalities in cellular signal transduction pathways identified in malignant gliomas have already led to the design of a first generation of targeted molecular drugs to inhibit these pathways in the clinical setting. A summary of those treatments is listed in Table 3.

Table 2: “Summary of the newest pharmaceutical agents with their molecular targets and mechanism of action” (29).

1.5 Cell Biology of Annexin A2

1.5.1 Annexin protein family

The annexins are an evolutionarily ancient and conserved family of Ca2+-regulated phospholipid- binding proteins. Annexin proteins, which have existed for over 500 million years, typically possess two main structural domains. The core domain, usually 30 to 35 kDa in mass, contains four

22 α-helical “annexin” repeats that bind Ca2+ and form a convex face that can associate with membrane phospholipid. The more hydrophilic amino-terminal “tail” or “interaction” domains are essentially unique to each family member and allow the annexins to bind to a wide variety of protein ligands. The term “annexinopathy,” first coined in 1999 (13) and expanded in more recent reviews (14-18), describes the mechanistic role played by the annexins in human disease.

Among the 12 annexins (annexins A1 to A11 and A13) expressed in humans, annexin A2

(ANXA2) is one of the most extensively studied, especially with respect to mammalian biology and human disease (19). A 36-kDa protein produced by endothelial cells, monocytes, macrophages, dendritic cells, trophoblast cells, epithelial cells, tumor cells and many others, ANXA2 can exist as a free monomer in the cytoplasm, in association with intracellular membranes or tethered to the external face of the plasma membrane (20,21). Human ANXA2 is the product of the ANXA2 gene composed of 13 exons distributed over 40 kb of genomic DNA on chromosome 15 (15q21) (22).

Versions of ANXA2 protein among mammalian species are ~98% identical at the amino acid level.

Figure 6: Chromosome 15 - NC_000015.10 (source :http://www.ncbi.nlm.nih.gov/gene/302)

Figure 7: “Structure of the ANXA2 protein.” (source Protein Data Bank archive-information about the 3D shapes of proteins http://www.rcsb.org)

1.5.2 Functions of Annexin A2

Annexin A2 acts as a scaffold protein that links the actin cytoskeleton to various membrane microdomains or recruits factors for actin-remodeling events. It can bundle pre-formed F-actin filaments and regulates the growth of newly formed filaments (23).

The annexin cell surface heterotetramer form (AIIt) may play an important role in exocytosis not only by forming and stabilizing lipid microdomains in the plasma membrane but also by organizing the exocytotic machinery in the chromaffin cells (21). Through its ability to bind actin, AIIt also

24 participates in the formation of membrane cytoskeletal complexes which control lipid raft assembly and the formation of functional exocytotic sites (24).

ANXA2 is also involved in endocytosis mediated by its Ca2+-dependent binding to actin. ANXA2 could potentially serve as a link between the actin cytoskeleton and clathrin-coated vesicles.

Moreover, ANXA2 can also link different domains of early endosomes via calcium-independent cholesterol binding (Fig.10) (55). However, Valapala and Viswanatha (2011) have described Ca2+- dependent cell surface trafficking of ANXA2 independent of clathrin (33).

In response to external stimuli, ANXA2 is capable of promoting epithelial cell polarity by regulating cell-cell adhesion through the formation of adherent junctions (transmembrane anchors composed of cadherins and integrins). Since ANXA2 regulates actin dynamics and weakly interacts with PtdIns (34, 35, 36) P3, it is plausible to consider ANXA2 an important modulator of cell-cell adhesion. In fact, ANXA2 recruits and regulates the activation of Rho and Rac1 GTPases

(137, 138), both of which are essential for initiating actin cytoskeleton reorganization during cell- cell adhesion (37, 38). Additionally, it interacts with AHNAK and recruits it to cholesterol-rich microdomains essential for regulation of the actin cytoskeleton (39).

ANXA2 is one of several proteins found in mRNP (ribonucleoprotein) complexes and may function as a nuclear scaffold protein for recruitment of other proteins. Immunoprecipitation of

ANXA2 from UV-irradiated cultured cells revealed its association with RNA as a part of RNP complex. Subsequently, studies have shown that ANXA2 is found in the nucleus in association with Z-DNA (40), and as a part of primer recognition complex stimulating DNA polymerase-α activity. ANXA2 specifically binds to oncogenic c-myc mRNA and regulates its translation, as expression of ANXA2 is associated with enhanced levels of c-myc protein (41).

Annexin A2 can exist in the cells as a monomer or a heterotetramer in complex with S100A10.

Interestingly, in cell types such as endothelial, epithelial, and MDCK cells, most of ANXA2is

25 present on the cell surface as the heterotetrameric form AIIt. Rigorous scientific analysis suggests that ANXA2 plays an important role in regulating plasmin activity even though it does not act as a direct plasminogen receptor. ANXA2 rather stabilizes and recruits S100A10 to the cell surface where it serves as a docking site for plasminogen and the tissue plasminogen activator (tPA) (Fig.

8).

Figure 8: “Experimental model of plasmin regulation by cell surface annexin A2 and S100A10. The heterotetrameric complex consists of two copies of annexin A2 and one copy of the S100A10 dimer. AIIt binds the tissue-plasminogen activator tPA and plasminogen at the carboxyl-terminal lysine residue of the S100A10 subunit. The annexin A2 subunit does not bind tPA or plasminogen but serves as cell surface receptor for S100A10. The urokinase-plasminogen activator is bound to its receptor (uPAR) and forms the uPA/uPAR complex that colocalizes with AIIt. The co-localization of the plasminogen activators and plasminogen by AIIt results in accelerated cleavage of plasminogen into plasmin. Plasmin activates pro-MMPs (matrix metallo-proteases) into active MMPs and further activates pro-uPA into active uPA” (56,57). Among other functions, ANXA2 is involved in DNA synthesis and cell proliferation. Chiang et al. in 1999 used a transient co-transfection assay to regulate ANXA2 expression in human HeLa, 293 and 293T cells and measured the effects of ANXA2 downregulation on DNA synthesis and

26 proliferation. Transfection of cells with an antisense ANXA2 vector results in inhibition of cell division and proliferation with concomitant reduction in ANXA2 message and protein levels.

Cellular DNA synthesis was significantly reduced in antisense transfected cells. (42).

Figure 9: “A schematic representation of various membrane-trafficking steps showing the involvement of annexins in the biosynthetic pathway, annexin A2 in complex with S100A10 has been shown to participate in the Ca2+-evoked exocytosis of chromaffin granules and endothelial Weibel–Palade bodies. The complex probably functions at the level of the plasma membrane, possibly by linking the large secretory vesicles to the plasma membrane or by organizing plasma-membrane domains so that efficient fusion can take place. Annexin A13b is required for the budding of sphingolipid- and cholesterol-rich membrane domains at the trans-Golgi network, and therefore the delivery of such material to the apical plasma membrane in polarized epithelial cells. b | In the endocytic pathway, annexin A6 has been proposed to be involved in clathrin-coated-pit budding events that depend on the activity of a cysteine protease that is required to modulate the spectrin membrane skeleton. Annexin A2, which can associate with caveolae, has been shown to form a lipid–protein complex with acylated caveolin and cholesteryl esters that seems to be involved in the internalization/transport of cholesteryl esters from caveolae to internal membranes. Annexin A2 is also found on early endosomes, where it is required, in complex with S100A10, to maintain the correct morphology of perinuclear recycling endosomes. Moreover, its depletion can interfere with the proper biogenesis of multivesicular endosomes from early endosomes. Annexin A1 also seems to function in multivesicular endosome biogenesis, more specifically, in the process of inward vesicle budding”(20).

27 1.5.3 The role of Annexin A2 in Cancer

ANXA2 is aberrantly expressed in a wide spectrum of cancers and exerts profound effects on tumor cell adhesion, proliferation, apoptosis, invasion and metastasis as well as tumor neovascularization via different modes of action (44).

High expression of ANXA2 is associated with poor prognosis in a wide range of solid tumors (43) including breast and pancreas cancer. ANXA2 downregulation, however, has been shown in prostate and head and neck cancer (44). Singh et al. confirmed in 2007 that ANXA2 is a high affinity binding protein required for mediating the growth stimulatory effects of gastrin and progastrin peptides on intestinal epithelial and colon cancer cells suggesting an involvement of

ANXA2 in the regulation of tumor cell proliferation (61). Zheng et al. in 2011 showed that phosphorylation of ANXA2 promotes epithelial to mesenchymal transition of pancreatic ductal adenocarcinoma (62). ANXA2 was almost undetectable in normal liver and chronic hepatitis tissues while it is strongly expressed in hepatocellular cancer (63-66). A selective overexpression of ANXA2 was also detected in invasive breast cancers (67). Sharma et al. in 2010 showed

ANXA2-induced cell migration and neoangiogenesis via tPA-dependent plasmin generation when localized on the cell surface (68). In metastatic renal cell and breast cancer tissues ANXA2 expression was significantly higher in comparison to the primary carcinoma tissues supporting the theory that ANXA2 may be a key player in migration and invasion (69). Figure 10 summarizes the known roles of ANXA2 in tumorigenesis.

Figure 10: “Roles of annexin A2 and S100A10 in tumorigenesis. Annexin A2 and S100A10 may promote tumorigenesis through several mechanisms. Annexin A2 contributes to tumorigenesis by stabilizing S100A10 levels, prevents cell cycle arrest, promotes cell proliferation and protects cancer cells from oxidative damage. S100A10 participates in tumorigenesis primarily by promoting plasmin generation, which contributes to TAM infiltration, angiogensis, invasiveness and metastasis and the hyperfibrinolytic state present in APL” (86).

1.5.4 The role of ANXA2 in GBM

Knockdown of ANXA2 has been associated with decreased cell migration and proliferation in glioma models including human cell lines U87MG, U373MG and cell lines derived from rodent gliomas (45, 46). Another study showed significantly higher expression levels of ANXA2 in glioma samples than in normal brain samples. ANXA2 expression correlated with the grade and survival of patients with gliomas. Multivariate analysis further revealed that ANXA2 was an independent prognostic marker for glioma. After ANXA2 expression was suppressed using short interfering RNA, U87 cells had decreased migratory and invasive capabilities in vitro.

Consequently, ANXA2 is considered a candidate biomarker for glioma grade stratification (47).

In a preliminary analysis carried out by our group, we sought to determine the regulatory origins

29 of GBM molecular subtypes by a new analytical approach. Adapting a novel statistical method based on sparse inverse covariance selection, we combined several forms of data from GBM tumors, including mRNA and miRNA expression, copy number aberrations (CNA), DNA methylation, point mutations, and clinical information (48). The key goal of the analysis was to associate the molecular subtypes of GBM to the genome and epigenome. The fitted model identified twenty cases of possible genetic or epigenetic regulators of genes closely linked to the classical, mesenchymal, and proneural subtypes (Figure 11). We chose to follow up on ANXA2 which was one of six genes in the network linked to its promoter methylation and the mesenchymal subtype, and the only identified subtype regulator for which promoter methylation was also linked to survival (Figure 11 C). Silencing of ANXA2 in GBM-derived cancer stem cell-like cultures suppressed mesenchymal signature genes and induced a gene expression profile similar to that of the less aggressive G-CIMP subgroup of GBM. ANXA2 abrogation in GBM-derived cells also reduced cell proliferation and invasiveness, which are aggressive features of mesenchymal GBMs.

These findings suggest an important role of ANXA2 as a modulator of aggressive GBM.

1.5.5 Intratumor heterogeneity in human glioblastoma

Snuderl et al in 2011 showed intratumoral heterogeneity of GBM using FISH that at the level of tyrosine kinases EGFR, PDGFRA, and MET (70). Szerlip et al. in 2012 verified distinct cellular populations within the same GBM with a common response to growth factors (71). Piccirilo et al. in 2012 identified phenotypically distinct tumor-initiating cell populations in the tumor mass and margin by fluorescence-guided intratumoral sampling (72). Barajas et al. in 2010 and Sottoriva et al. in 2013 demonstrated that GBM exhibits a landscape of intratumorally heterogeneous mutations across the whole genome at the copy number level. Other publications reported the presence of two 30 types of CSCs within different regions of the same human GBM. Cytogenetic and molecular analysis showed that these two types of CSCs bear quite diverse tumorigenic potential and distinct genetic anomalies and yet, derive from common ancestor cells (73).

1.5.6 The importance of the peritumoral zone

Current operative strategies pursue a gross total resection of the tumor as defined by the T1

Gadolinium high-enhancing region. Multiple studies support that up to 85% of recurrences are localized at the resection margin leading to the hypothesis that residual cancer cells reside in this area (76, 77, 78). Fluorescence-guided surgery with 5-aminolevulinic avid (ALA) and combined metabolic PET- and MRI-guided surgical resections (Pirotte et al. 2006) increased the rate of complete resections and extended patient survival, strenghtening the hypothesis that the so-called

“edema zone” may be the primary location of residual tumor cells (74,75).

2. Aim

With the present study, we aim to confirm the aberrant overexpression of ANXA2 in high-grade gliomas and to investigate the further the role of ANXA2 in determining the characteristic invasive properties of mesenchymal GBMs.

Data obtained from glioma cell lines experiments, which implicate ANXA2 in proliferation and migration, combined with those from studies that highlight an elevated intratumoral molecular heterogeneity in gliomas, prompted us to investigate ANXA2 expression in areas of the tumor characterized by different histopathological features. We hypothesize that if ANXA2 is indeed a modulator of migration and invasion in GBM, it might be preferentially overexpressed at the periphery of the tumor, where malignant cells require those properties to be able to infiltrate the normal non-transformed brain tissue (46, 49, 50, 51).

Figure 11: “A: Network region that integrates several molecular species, disease subtypes and lineage markers. The full network, organized into around 500 sub-networks contains 13400 variables and more than 100,000 links both within and between data types. For example, around sixty different subnetworks contained CNA and/or LOH of genes closely located in the genome, and one subnetwork harbors methylation probes located on the X chromosome linked to patient sex. Such subnetworks of CNA and LOH variables were largely explained by genomic structure, i.e. linking of neighboring genes. The model confirmed the earlier discovery of the CEBPB association with mesenchymal markers [5], since the CEBPB mRNA links to the mesenchymal subtype variable. B: The classical subtype node. The classical subtype node is associated to the copy number, loss of heterozygosity, and expression of the closely-located genes EGFR and SEC61G. C: The network suggests testable hypotheses. ANXA2 is positively connected to the mesenchymal subtype node and negatively connected to a promoter methylation site (probe cg08081036). ANXA2 methylation is in turn associated with survival via a set of other methylation events.” (87)

32 3 Material & Methods

3.1 Materials & Chemicals

3.1.1 Chemicals

Chemicals Company

16% Paraformaldehyde aqueous EM Sciences (Hatfield, solution USA)

Sigma (Taufkirchen, 2-Mercaptoethanol Germany)

Sigma (Taufkirchen, 2-Propanol Germany)

Zymo Research (Freiburg, 5-Hydroxymethylcytosine Germany)

Zymo Research (Freiburg, 5-Methylcytosine Germany)

7900HT System Fast 96 Well Spectral Life Technologies Calibration KIT (Carlsbad, USA)

Millipore (Darmstadt, Accutase Germany)

Life Technologies ACK Lysing Buffer (Carlsbad, USA)

Sigma (Taufkirchen, Acrylamide/Bis-Acrylamide, 30% Germany)

Adenosine 5′-triphosphate disodium Sigma (Taufkirchen, salt hydrate Germany)

Sigma (Taufkirchen, Agarose Germany)

Sigma (Taufkirchen, Albumine bovine Germany)

33 Sigma (Taufkirchen, Alcian Blue Germany)

Sigma (Taufkirchen, Ampicillin sodium salt Germany)

Life Technologies B-27 Supplement (Carlsbad, USA)

Bio-Rad Protein Assay Dye Reagent Concentrate Bio Rad (Hercules, USA)

Cell Dissociation Solution Non- Sigma (Taufkirchen, enzymatic Germany)

Clarity Western ECL Substrate Bio Rad (Hercules, USA)

Competent cells one shot ccdB Survival Life Technologies 2T1R (Carlsbad, USA)

Sigma (Taufkirchen, DAPI Germany)

Invitrogen (Carlsbad, DMEM medium USA)

Sigma (Taufkirchen, DMSO Germany)

Sigma (Taufkirchen, EDTA 0,5M Germany)

Sigma (Taufkirchen, Ethanol Germany)

Fetal Bovine Serum (FBS) (cell Life Technologies culture) (Carlsbad, USA)

Fugene Promega (Madison, USA)

Invitrogen (Carlsbad, GlutaMAX™-I Supplement USA)

Sigma (Taufkirchen, Glycerol Germany)

34 Qiagen (Venlo, HotStarTaq Master Mix Kit Netherlands)

Qiagen (Venlo, HotStarTaq Plus DNA Polymerase Netherlands)

Qiagen (Venlo, HotStarTaq Plus Master Mix Kit Netherlands)

Sigma (Taufkirchen, Methanol Germany)

Sigma (Taufkirchen, Milk Powder Germany)

Life Technologies N-2 Supplement (Carlsbad, USA)

Sigma (Taufkirchen, Sodium Chloride Germany)

Life Technologies Neurobasal-A Medium (Carlsbad, USA)

Life Technologies OneShot Stbl3 competent cells (Carlsbad, USA)

Sigma (Taufkirchen, Phenol Germany)

Sigma (Taufkirchen, Phosphatase Inhibitor Cocktail Germany)

Sigma (Taufkirchen, Phenylmethylsulfonylchlorid Germany)

Precision Plus Protein Dual Color Bio Rad (Hercules, USA)

Precision Plus Protein Marker WesternC Standards Bio Rad (Hercules, USA)

Precision Plus Protein WesternC Pack Bio Rad (Hercules, USA)

Thermo Scientific Protease inhibitors cocktail (Waltham, USA)

35 Santa Cruz (Heidelberg, Protein A/G plus-agarose beads Germany)

Sigma (Taufkirchen, Puromycin dihydrochloride Germany)

Thermo Scientific RNA 6000 Ladder (Waltham, USA)

Thermo Scientific RNA 6000 Nano Kit (Waltham, USA)

Thermo Scientific Rnase ZAP (Waltham, USA)

Carl Roth (Karlsruhe, SDS Ultrapure Germany)

Life Technologies SOC Medium (Carlsbad, USA)

Sigma (Taufkirchen, Sodium acetate Germany)

Sigma (Taufkirchen, Sodium bicarbonate Germany)

SuperScript III RNase Rev. Life Technologies Transcriptase (Carlsbad, USA)

Life Technologies SYBR Green Master Mix (Carlsbad, USA)

Life Technologies Synth-a-Freeze (Carlsbad, USA)

Life Technologies Taqman PCR Master Mix (Carlsbad, USA)

Sigma (Taufkirchen, TEMED Germany)

Applichem (Darmstadt, Tris Base Ultrapur Germany)

Sigma (Taufkirchen, Tris-EDTA Buffer Solution Germany)

36 Sigma (Taufkirchen, Triton X-100 Germany)

Sigma (Taufkirchen, Tween 20 Germany)

Life Technologies Ultra Pure X-gal 100mg (Carlsbad, USA)

Life Technologies Ultrapure 20x SSC (Carlsbad, USA)

Life Technologies UltraPure™ 10X TBE Buffer (Carlsbad, USA)

Table 3: List of Chemicals

3.1.2 Materials Materials Company

10 cm culture plates BD (Franklin Lakes, USA)

100 ml bottle Schott (Mainz, Germany)

10 ml disposable pipets BD (Franklin Lakes, USA)

12 well plate BD (Franklin Lakes, USA)

15 cm culture plates BD (Franklin Lakes, USA)

15 ml tubes VWR (Radnor, USA)

24 well plates steril Nunc VWR (Radnor, USA)

25 ml disposable pipettes VWR (Radnor, USA)

2 ml disposable pipettes Corning (Corning, USA)

4-20% resolving gel Bio Rad (Hercules, USA)

50 ml disposable pipettes BD (Franklin Lakes, USA)

50 ml Falcon tubes BD (Franklin Lakes, USA)

5 ml disposable pipettes BD (Franklin Lakes, USA)

37 6 cm culture plates, easy grip BD (Franklin Lakes, USA)

6 well plates BD (Franklin Lakes, USA)

Thermo Scientific (Waltham, 6-Well HydroCell USA)

Agilent RNA 6000 Nano Kit Agilent (Santa Clara, USA)

Agilent RNA 6000 Nano Reagents Part 1 Agilent (Santa Clara, USA)

All Prep DNA/RNA Mini Kit Qiagen (Venlo, Netherlands)

Amersham Hybond -ECL GE Health care (Freiburg, Nitrocellulose membrane(0.45µm) Germany)

Falcon cell culture flasks VWR (Radnor, USA)

Beaker, 1000ml VWR (Radnor, USA)

Beaker, 100ml VWR (Radnor, USA)

Beaker, 2000ml VWR (Radnor, USA)

Beaker, 250ml VWR (Radnor, USA)

Beaker, 600ml VWR (Radnor, USA)

Cell lifter Corning (Corning, USA)

Cell Scraper 25 cm handle / 1.8 cm blade VWR (Radnor, USA)

Sigma (Taufkirchen, Cell scraping Germany)

Cell strainer 100µm Nylon 50pcs BD (Franklin Lakes, USA)

Carl Roth (Karlsruhe, Cell counter Germany)

Cryo-babies, labels for Eppis 33x13mm VWR (Radnor, USA)

Thermo Scientific (Waltham, Cryobox USA)

38 cover slips round 12mm Dunn (Asbach, Germany)

cover slips round 30mm VWR (Radnor, USA)

Epoch Biolabs (Sugar Land, DNA Miniprep Kit USA)

single-use scalpel VWR (Radnor, USA)

Medipha GmbH (Geislingen single-use forceps an der Steige, Germany)

Endo free Maxi Kit (10) Qiagen (Venlo, Netherlands)

epTIPS 0,1-10µl LMS (Brigachtal, Germany)

epTIPS 2-200 µl LMS (Brigachtal, Germany)

epTIPS 50-1000µl LMS (Brigachtal, Germany)

epTIPS Reload 0,1 - 10µl LMS (Brigachtal, Germany)

epTIPS Reload 2-200µl LMS (Brigachtal, Germany)

epTIPS Reload 50-1000µl LMS (Brigachtal, Germany)

MaxiPrep Kit Qiagen (Venlo, Netherlands)

Carl Roth (Karlsruhe, graduated cylinder, 1000ml Germany)

Carl Roth (Karlsruhe, graduated cylinder, 100ml Germany)

Carl Roth (Karlsruhe, graduated cylinder, 2000ml Germany)

Carl Roth (Karlsruhe, graduated cylinder, 250ml Germany)

Carl Roth (Karlsruhe, graduated cylinder, 500ml Germany)

Miniprep Kit Qiagen (Venlo, Netherlands)

miRNeasy Mini Kit Qiagen (Venlo, Netherlands)

39 Motor mixer VWR (Radnor, USA)

Parafilm VWR (Radnor, USA)

cell counting chamber, Neubauer VWR (Radnor, USA) improved Table 4: List of Materials 3.1.3 Media

CSC Medium Neurobasal 50ml B27 1X N2 1X Glutamax 1X FGF 0.01ug/ml EGF 0.04ug/ml LIF 0.004ug/ml Heparin PN Medium Neurobasal 37,5 ml DNEM 12.5 ml EGF 0.01ug/ml FGF 0.04ug/ml AD Medium DNEM FBS 10%

Table 5: List of Mediums

40 3.1.4 Specimens Samples Sub-classification according to Verhaak et al. BT504 Mesenchymal BT203 Mesenchymal BT219 Mesenchymal BT222 Mesenchymal BT305 Mesenchymal BT392 Mesenchymal BT307 Mesenchymal BT408 Mesenchymal BT411 Mesenchymal BT523 Non- mesenchymal BT278 Non- mesenchymal BT105 Non- mesenchymal BT089 Non- mesenchymal BT122 Non- mesenchymal BT332 Non- mesenchymal BT556 Non- mesenchymal BT093 Non- mesenchymal BT494 Non- mesenchymal BT112 Non- mesenchymal BT056 Non- mesenchymal BT209 Non- mesenchymal BT300 Non- mesenchymal BT232 Non- mesenchymal BT111 Non- mesenchymal Table 6: a cohort of 24 GBM samples (sub-classified as 9 mesenchymal and 15 non-mesenchymal, according to Verhaak et al.) analyzed by quantitative real-time PCR

Sample BT530 BT504 BT440 BT402 BT405 BT422 BT479 BT532 BT473 BT482 BT501 BT503 BT393

Table 7: Tissue samples qualified for the regional expression analysis grouped according to their CHI3L1 expression. Grey background: represents the samples 5with high expression of CHI3L1.

Sample WHO Grade Classification NP1269/11 II Mixed oligoastrocytoma NP155/11 III Anaplastic oligoastroglioma NP242/11 III Anaplastic oligoastrocytoma NP1268/12 III Anaplastic oligoastrocytoma NP1553/10 III Anaplastic astrocytoma NP437/10 IV Glioblastoma NP726/11 IV Glioblastoma NP849/11 IV Glioblastoma NP1033/11 IV Glioblastoma

Table 8: Tissue samples used for the Immunofluorescence staining of ANXA2

3.2 Methods

3.2.1 Classification of brain tumor samples.

The classification of brain tumor samples was performed by using 510 genes out of the 840 classifier genes used by Verhaak et al. (3). Out of 661 randomly selected gliomas from the TCGA

Bank 529 have been classified as mesenchymal or non-mesenchymal tumors (54). The expression levels for the genes used to classify the TCGA data set were converted into z-scores. The combined matrix was used to classify each glioma sample based on a k-nearest neighbors (k=10) and voting procedure, in which a subtype was assigned based on the majority subtype among the 10 TCGA samples with highest correlation coefficients for these genes with respect to the tumor sample. All data manipulations were performed in R (R Core Team, 2012) and MATLAB (The MathWorks,

Inc., Natick, MA, United States).

Figure 12: flow chart representation of the TCGA and Freiburg tumor bank data set analysis

3.2.2 Glioma tissue collection

The tumor samples have been collected from a selected pathological area during surgical resection.

Identification of the sampling area was performed by the presurgical gadolinium-enhanced T1- weighted MRI in combination with macroscopical intraoperative identification of the pathology and intraoperative quick-biopsy verification. These samples are all included in the gadolinium- enhanced area. All biopsy specimens were collected upon patient’s approval by an experienced neurosurgeon, subsequently snap-frozen in liquid nitrogen and stored at −80◦C. The local ethics

43 committee of the University of Freiburg approved data evaluation, imaging procedures and experimental design (protocol 100020/09 and 5565/15). The experiments were carried out in accordance with the guidelines. Written informed consent was obtained from all patients.

3.2.3 MRI-navigated GBM tissue collection.

Before surgery, standard gadolinium-enhanced T1-weighted MRI 3D datasets were acquired. According to the MRI data, three tumor regions were identified for sampling: A) a non- enhancing peritumoral area referred as edema zone, B) a contrast-enhancing area within the contrast-enhancing rim of the tumor C) a non-enhancing intratumoral area, referred to as core

(figures 13-17). During surgical resection of the tumor, pre-originated MRI coordinates were used to accurately track the sampling positions. All biopsy specimens were collected upon patient’s approval by an experienced neurosurgeon, subsequently snap-frozen in liquid nitrogen and stored at −80◦C. The local ethics committee of the University of Freiburg approved data evaluation, imaging procedures and experimental design (protocol 100020/09 and 5565/15). The experiments were carried out in accordance with the guidelines. Written informed consent was obtained from all patients.

Figure 13: Zone A (light blue): non-enhancing peritumoral area referred to as edema zone in a T1-weighted MRI with Gadolinium contrast.

Figure 14: Zone B (Red): Gadolinium contrast-enhancing zone

Figure 15: Zone C (black/gray): non-enhancing/necrotic zone

Figure 16: Intraoperative snapshot from neuronavigation system.

Figure 17: Schematic illustration of the localization of the different GBM regions considered for sampling (left panel), and rep- presentative MRI data used to collect navigated biopsies (right panel). The edema zone is highlighted in light blue, the contrast- enhancing zone in red, and the core in black (Kling, Ferrarese et.al 2016).

3.2.4 Immunostaining.

Immunostaining was performed on the tissue samples listed on table 6 from the Freiburg University intraoperative-biopsies-glioma Database using antibodies against: ANXA2 (mouse monoclonal,

BD Biosciences), and DAPI for nuclei counterstaining. Tissue samples were placed on slides and fixed with 3% formaldehyde for 10 minutes at room temperature. Afterwards the slides were incubated in permeabilizing solution (HEPES, Sucrose, NaCl, MgCl2, 0.5% Triton X-100) for 20 minutes at 4°C and subsequently blocked in PBS 2% BSA for 30 minutes at 37 °C. The slides were then washed with PBS three times for five minutes. The primary antibody was diluted in blocking buffer (2% BSA, PBS) and incubated for 90 minutes at 37 °C. After 3 washes (5 minutes) in PBS the secondary antibodies were diluted in blocking buffer and added to the coverslips for 45 minutes at 37 °C. After another 3 wash cycles a counterstaining with DAPI for 20 minutes followed. After another wash in water the coverslips were fixed on a glass plate. Pictures were acquired using an

Axiovert Microscope (Zeiss) or a FSL confocal microscope (Olympus). The collected images were then analyzed with Adobe Photoshop CS5 (Adobe) to evaluate ANXA2 staining positivity.

48 3.2.5 RNA extraction RNA extraction from the collected samples was performed using the RNeasy mini-kit according to the manufacturer’s instructions (Qiagen). A concentration and contamination analysis of the extracted RNA was performed with the Nanodrop-Spectrograph (Thermo Scientific): samples with

260/280 and 260/230 ratios below 2.00 were discarded. An RNA-integrity evaluation was performed using the 2100 Bioanalyzer (Agilent): samples in which at least one of the MRI-guided biopsies showed an RNA integrity number (RIN) inferior to 7.00, were discarded (83,84). The flowchart represented in (Fig. 18) summarizes the key steps of the experimental procedure.

Figure 18: Flowchart representation of all steps taken from collection to the analysis of the tumor samples.

3.2.6 Quantitative Real-Time PCR

RNA was prepared using the RNAeasy kit or the AllPrep DNA/RNA Protein Mini Kit (Qiagen) and used for first strand cDNA synthesis using random primers and SuperscriptIII reverse transcriptase (Invitrogen). Quantitative real-time PCR (qRT-PCR) was performed using the following pre-validated TaqMan Assays (Applied Biosystems); ANXA2: Hs00743063 s1,

18srRNA: Hs99999901. Quantitative RT-PCR with SYBR green (Applied Biosystems) and primers listed in Table 7 were used to validate a panel of mesenchymal genes. The results were analyzed by the SDS software (Applied Biosystems). Statistical analyses were performed by

Microsoft Excel 2015. Average cDNA quantities in relation to a standard amplified gene

(Housekeeper-gene 18s) were calculated using the measured and SDS calculated ct-value1s.

3.2.7 Statistical Analysis of Quantitative Real-Time PCR

All qRT-PCR results were analyzed using Microsoft Excel 2015 (Welch’s t-test), the significance level was defined as p-value < 0.05. Regional samples were classified as expressing high or low

CHI3L1 setting a relative expression threshold value of 9.99E-0,5.

Gene Primer Sequence FOS Fwd CGGGCTTCAACGCAGACTA Rev GGTCCGTGCAGAAGTCCTG CD44 Fwd GCAACTGAGACAGCAACCAAG Rev GCCATTTGTGTTGTTGTGTGAA CHI3L1 Fwd AGATGCCCTTGACCGCTTC Rev CCGTACAGCGTCACATCATTC WWTR1 Fwd CGGGATTTGTCAGCCAAG Rev GAGGCCGGATTCATCTTCTGG METTL7B Fwd GAGTACTGAGACCGGGAGGT Rev GTGGGCTCGAAAACTTGCTG EMP3 Fwd TGGTCTCAGCCCTTCACATC

50 Rev TCGTACCAGAGATTCAGGGAC EFEMP2 Fwd TGAAGTGCATCAACCACTACG Rev TCCTGATCGTCGGGCTCATA CD97 Fwd CCTGTCCGGCACCTCATAG Rev CCATAGTGACGTTCTTGTCCC PTRF Fwd TGAGCCTCCTGGACAAAATC Rev AGCTTGCTCACCGTATTGCT C1R Fwd ATGTCCCAAGGGAACAAGATGC Rev CTCCCCTAATTTGCTCCGGG SERPINE1 Fwd AGTCCCAGAGAGGGAGGTGT Rev TCTTCTTGACAGCGCTCTTG ACTN1 Fwd CACCAACCCCTACACAACCAT Rev TGCTTGCGTAGCCTCTCATTG MVP Fwd GGGCTTGGTGCTGTTTGATG Rev CGCCTTTAGATGGAGGGCA Table 9: Primers used for qRT-PCR

4. Results

4.1 ANXA2 expression in high versus low-grade gliomas

In order to confirm the increased ANXA2 expression in high-grade gliomas, we initially performed an in-silico analysis of ANXA2 expression in a cohort of 661 gliomas (174 WHO-grade IV; 252

WHO-grade III; 235 WHO-grade II) from The Cancer Genome Atlas (TCGA) collection, for which the WHO-grade was known. Figure 19 shows the expression of ANXA2 (extrapolated from

RNAseq data) of gliomas of WHO-grade II, III and IV. ANXA2 expression significantly correlates with the tumor grade and is markedly overexpressed in GBM.

Figure 19: ANXA2 expression (RNAseq) of TCGA GBM and LGG grade II and III tumor samples. KS-test GBM and LGG grade III p- value: 2.0 • 10−35, GBM and LGG grade II: 3.3 • 10−52, and LGG grade III and II: 5.2 • 10−7. (87) The association between ANXA2 expression and GBM was validated further at the protein level by immunofluorescence staining. The analysis of 6 GBM and 6 LGG biopsies collected at Freiburg

University using an ANXA2 mouse monoclonal antibody to label ANXA2 protein, highlighted its presence exclusively in the GBM samples (Fig. 20-21). Of note, a WHO-grade III anaplastic astrocytoma resulted positive for ANXA2 staining; however, the histopathological report of this biopsy highlighted signs of endothelial proliferation and necrosis which might suggest increased malignancy at least in some areas of the tumor in spite the histological classification as a grade III tumor. From the in silico RNAseq analysis of ANXA2 expression and from the immunofluorescence

52 ANXA2 staining, we confirmed that ANXA2 is overexpressed in glioblastoma multiforme.

Figure 20:Immunostaining of ANXA2 (red) in LGG, counterstained with DAPI (blue).

Figure 21: Immunostaining of ANXA2 (red) in GBM, counterstained with DAPI (blue).

54 4.2 ANXA2 differential expression between mesenchymal and non-mesenchymal GBMs

In consideration of the fact that ANXA2 has been previously associated to tumor aggressiveness in GBM (45,46,47), we investigated whether ANXA2 was differentially expressed between mesenchymal and non-mesenchymal GBMs. Preliminary in silico analysis of ANXA2 expression based on Affymetrix data in a cohort of 529 gliomas from TCGA database either sub-classified as mesenchymal (164) or as non-mesenchymal (365), showed a significant correlation between higher levels of ANXA2 expression and mesenchymal tumors (Fig.22).

Figure 22: ANXA2 expression (Affymetrix) of TCGA mesenchymal and non-mesenchymal tumor samples. KS-test p-value: 2.7 • 10−31. (87)

Given that the majority of mesenchymal gliomas included in the in silico analysis were GBMs while non-mesenchymal gliomas consisted of a more heterogeneous group of GBMs and lower- grade tumors, we sought to validate ANXA2 association to the mesenchymal signature restricted to GBMs. Thus, we analyzed by quantitative real-time PCR a cohort of 24 GBM samples (sub- classified as 9 mesenchymal and 15 non-mesenchymal, according to Verhaak et al.) from our in- house tumor bank at the Freiburg University. This analysis confirmed that among GBMs, ANXA2 is overexpressed in mesenchymal tumors compared to non- mesenchymal ones (Fig. 23).

Figure 23: ANXA2 expression (qPCR) of Univ. of Freiburg mesenchymal and non-mesenchymal tumor samples. KS-test p-value: 7.6 • 10−5 (87)

4.3 Regional expression of ANXA2 in mesenchymal and non-mesenchymal GBMs

Taken together, these results support our initial hypothesis that ANXA2 is typically overexpressed in mesenchymal GBMs compared to the other GBM subtypes.

GBMs typically present an elevated degree of intratumoral heterogeneity (70-73). It has also been observed that the peritumoral zone, commonly defined as the area outside the Gadolinium- enhancing ring on MRIs, is infiltrated by invading tumor cells and in more than 85% of the cases represents the zone of origin for a recurrence (74-78). Having established the association between

ANXA2 expression and mesenchymal GBMs, which manifest the most motile and invasive tumor subtype among all the GBM sub-classes, we speculated that ANXA2 might be overexpressed in tumor cells infiltrating the edema zone especially in mesenchymal tumors.

Thus, we sought to test whether ANXA2 was differentially expressed in different areas of GBM and in particular, whether it was overexpressed at the invasive periphery of the tumor compared to the tumor center.

To achieve this goal, we collected matching GBM tissue samples from the core of the tumor, from the Gadolinium-enhancing rim and from the peritumoral zone, by using an intraoperative navigational system, as described in the Methods section (Figure 13-17). At first, RNA yield and purity was assessed by spectrophotometric analysis; subsequently, RNA quality was evaluated by measuring its RIN (RNA Integrity Number) with a bioanalyzer (Figure 24); eventually, quantitative real-time PCR analysis was performed to evaluate the expressions levels of ANXA2 on those samples for which all the matching regions met the selection criteria.

In addition to the housekeeping gene 18S and our gene of interest, ANXA2, we measured the expression of the mesenchymal marker gene CHI3L1 to subdivide the GBM samples in mesenchymal and non-mesenchymal.

Figure 24: Exemplary bioanalyzer RNA quality check on MRI-guided regional tumor samples. The quality of the RNA is visualized by a virtual electrophoresis gel (top), and quantified by individual electropherograms (bottom). Only the samples with RIN>7.00 in all 3

Figure 25: Relative ANXA2 and CHI3L1 expression in tumor regional samples measured by quantitative real-time PCR. E: Edema zone, CE: Gadolinium-enhanced zone, C: core.

The regional samples were subdivided in two separate groups: one characterized by high CHI3L1 expression levels, and one with low CHI3L1 expression; interestingly, ANXA2 expression matched that of CHI3L1 in both groups (Figure 25). Between these two grossly distinct groups, ANXA2 expression is significantly more prominent in the mesenchymal one, but within the groups, it seems to be relatively uniform across the different regions, from the core to the periphery of the tumor

(edema zone). However, it is worth noticing that even though ANXA2 overall expression level is high in tumors of the mesenchymal subgroup, the peritumoral zone (edema zone) shows a lower expression of ANXA2 compared to the contrast-enhancing zone and the core of the matching GBM

(Figure 26).

Taken together these results confirm our previous observation that ANXA2 is specifically overexpressed in mesenchymal GBMs, but it fails to highlight any intratumoral expression gradient. These data suggest that at least at the gene expression level, ANXA2 is not preferentially overexpressed in any specific region of the tumor and that infiltrating cells of the tumor invasive front in the peritumoral zone appear not to be depending on ANXA2 gene activation to exert their role in moving out of the tumor mass and colonize new areas of the brain.

Figure 26: Box- plot graph correlating ANXA2 expression with GBM regions and CHI3L1 expression. The graph shows the smallest and largest observations (upper and lower whiskers, respectively), the interquartile range (box), and the median (black line); data points

5. Discussion

The progression of a GBM depends on invasive growth marked by mesenchymal cell features. It therefore remains a critical priority to expand our knowledge on how the mesenchymal features are modulated. In our group’s preliminary work, we applied augmented Sparse Inverse Covariance

Selection (aSICS) as a novel integrative modeling method to identify regulators of GBM subtypes.

Our model implied that a number of methylation events, independently of IDH1 mutation, contribute to a mesenchymal/proneural axis in GBM. Our preliminary cell line experiments indicated that ANXA2 is a key regulator of mesenchymal transformation and demonstrated its importance for viability, invasiveness and maintaining a mesenchymal gene signature.

In this work, the analysis of TCGA GBM samples validates that ANXA2 is typically overexpressed in mesenchymal GBMs compared to lower grade gliomas and to non-mesenchymal GBMs. This was verified by analyzing GBM samples collected at the Medical Center at the University of

Freiburg. ANXA2 has been previously implicated in other cancer types as a key player in invasion and migration, especially in metastatic disease where nesting of tumor cells among various physiological tissue types is the foundation of dissemination (67, 68, 69). A possible explanation for our results is that mesenchymal GBMs exploit ANXA2 overexpression in order to improve invasive capabilities of their cell populations. ANXA2 expression levels are elevated in all GBMs but are significantly higher in mesenchymal ones suggesting that ANXA2 levels correlate with their aggressive tumor expansion profile. Interestingly, the immunostaining of one sample (BT102) which had been previously histopathologically evaluated as a Grade III anaplastic astrocytoma, unexpectedly stained positive for ANXA2. A thorough histopathological re-evaluation of this sample revealed signs of endothelial proliferation and necrosis, indicating an increased malignancy

62 at least in some areas of the tumor. This observation supports our hypothesis that ANXA2 overexpression may possibly emerge in association with the malignant progression of a glioma, and that this process develops heterogeneously within a single tumor, making the histopathological classification based on single biopsies even more challenging. In consideration of these results, it seems important to acquire a better knowledge of the molecular and genetic mechanisms which orchestrate ANXA2 overexpression in GBM.

Ontogenetically, Sottoriva et al. in 2013 suggested a “space-and-time” evolutionary model to explain intratumoral heterogeneity in GBMs. They suggested that GBM cells adapt gradually their genetic instability according to their location within the tumor, presenting a mosaic of expression alterations based on their environmental demands. For example, among the cells that lay within the

Gadolinium contrast-enhancing area, those able to divide more quickly and to migrate more easily in the nutrient-rich surrounding normal tissue, will have a selection advantage over the tumor cells which do not possess these qualities. Conversely, the cells belonging to the core of the tumor do not contribute to the tumor expansion pattern and thus will not adopt the same behavior. Parker et al. in 2016 showed that promoter methylation status of the DNA repair enzyme O6-methylguanine

DNA methyltransferase (MGMT), the most important clinical marker yet, is inhomogeneous expressed in various areas of the tumour mass at the epigenetic, genetic and transcriptional level

(85).

Following these assumptions and combining them with our current data, we explored whether

ANXA2 belongs to those proteins that are topotropically expressed in GBMs. Since up to 85% of tumor recurrences arise from cell populations hidden in the peritumoral area which is not radically resected, we hypothesized that ANXA2 is overexpressed in the invasive tumor cells of this area compared to the cells located in the tumor center.

63 Contrary to our expectations, ANXA2 showed no differential expression in the tumor-infiltrated edema zone or in the Gadolinium-enhancing tumor periphery compared to the core of the tumor.

However, in accordance with the literature and with our previous observations, for each tested region we detected an overexpression of ANXA2 in mesenchymal tumors (with high CHI3L1 expression) compared to the non-mesenchymal ones (with low CHI3L1 expression), the latter being characterized by almost uniformly low levels of ANXA2 expression.

Various glioblastoma invasion markers have been recently proposed. Zhou et al. in 2015 proposed

CD151-a3β1 integrin complexes as an invasion marker (81). These adhesion molecules, form tight protein complexes and synergize with EGF/EGFR to accelerate tumor cell motility and invasion.

Fan et al. showed in 2016 that adenylate cyclase-associated protein 1 (CAP1), a protein related to the regulation of actin filaments and the Ras/cAMP pathway, is upregulated in high grade gliomas and strongly associated with their invasiveness (82). Investigating the expression of actin in gliomas Ohtaki et al. showed recently, that alpha cardiac muscle 1 (ACTC1), which is 1 of 6 actin families implicated in cell motility, may serve as a novel independent invasion marker in glioblastoma (83). A regional expression analysis of the aforementioned markers has not yet been reported in the literature. However, Toussaint et al. in 2012 showed that galectin-1 plays a key role in GBM invasion and is preferentially expressed in the peritumoral zone (80).

Counterintuitively, in mesenchymal tumors ANXA2 expression is relatively constant in the core and the Gadolinium-enhancing zone, but comparatively reduced in the peritumoral zone (edema zone). Although it is possible that ANXA2 is downregulated in the peritumoral zone compared to the main tumor, our findings could also be explained by the fact that the size of the actual tumor cell population within this area is remarkably lower than the one in the tumor body. In fact, the highly heterogenous peritumoral edema zone is characterized by neoplastic cells in various ontogenic phases of tumorigenesis infiltrating non-transformed brain tissue (79). Gill´s et al. 2014

64 analysis of the peritumoral cell populations of 69 glioblastoma patients who underwent MRI- localized intraoperative biopsies, showed that tumor cells in this region are highly intermixed with non-transformed normal brain cells and cells from the inflammatory compartment (84). Thus, the actual ANXA2 expression of this tumor region might be masked by the cumulative effect resulting from the relatively low number of ANXA2-expressing tumor cells intermixed with normal brain cells lacking ANXA2. In this case, ANXA2 expression level of the tumor cells in the peritumoral zone may be similar to the expression in the cells belonging to the Gadolinium-enhancing zone and to the core. Thus, the typical aggressive invasive behavior of malignant cells at the invasive front of the tumor is most likely not caused by an upregulated expression of ANXA2. An alternative explanation about how ANXA2 may contribute to the invasive pattern of GBM is that upregulation of ANXA2 would be regulated at the protein level, making it available to exert its function only where it is required (i.e., the invasive peritumoral zone).

Theoretically, the isolation of the tumor cells from the edema zone would allow analyzing with more precision their expression profile and proteome in order to elucidate their invasive and migratory properties. Learning more about the regulatory mechanisms of ANXA2 and more generally about the mechanisms underlying tumor aggressiveness, might provide additional useful therapeutic tools that could help to restrain tumors in the area of their genesis. Targeting key players of invasion offers the opportunity to inhibit the invasive phenotype of GBM and turning it into a more localized disease, thus preventing multifocal growth and distant relapses. Our future experiments will be focused on the exploration of this experimental strategy evaluating other already suggested invasion markers in the regional peritumoral environment.

65 6. Summary

In a preliminary work of our group we used a novel data-driven network modeling technique

(augmented sparse inverse covariance selection, aSICS) to define separate genomic, epigenetic, and transcriptional regulators of glioblastoma subtypes. Our model identified Annexin A2

(ANXA2) as a methylation-controlled positive regulator of the mesenchymal subtype (87).

We analyzed glioma-samples from the TCGA and Freiburg glioma bank and we confirmed that

ANXA2 expression correlates with tumor grade and is characteristically high in mesenchymal

GBMs (87).

Our MRI-localized regional analysis of ANXA2 expression in GBM confirmed its association with the mesenchymal molecular signature but failed to highlight any specific intratumoral variety in expression. The role played by ANXA2 in invasion might suggest its activity occurs primarily in the tumor invasive front. However, this could not be confirmed when assessing ANXA2 expression in different areas of the tumor including the peritumoral edema zone. Reduced ANXA2 expression in the edema zone compared to contrast-enhancing zone and core of mesenchymal tumors might be related to the particularly heterogeneous nature of this region in which ANXA2-expressing neoplastic cells are intermixed with the non-transformed brain cells not expressing ANXA2. Future experiments have to confirm if ANXA2 possibly exerts its role in invasion by differential protein activation in tumor cells in the peritumoral edema.

66 Zusammenfassung

In einer vorherigen Analyse unserer Gruppe konnten wir eine neuartige, datengesteuerte

Netzwerkmodellierungstechnik (erweiterte spärliche inverse Kovarianzauswahl, aSICS) implementieren, um separate genomische, epigenetische und transkriptionelle Regulatoren von

Glioblastom-Subtypen zu definieren. Mit diesem Modell konnte Annexin A2 (ANXA2) als

Methylierungs-kontrollierter positiver Regulator des mesenchymalen Subtyps von Glioblastomen

(GBM) identifiziert werden (87).

Nach Analyse von Gliom-Proben aus der TCGA- und der Freiburger Gliomdatenbank konnten wir bestätigen, dass die ANXA2-Expression mit dem Tumorgrad korreliert und im mesenchymalen

Subtyp stark exprimiert wird.

Unsere MRT-lokalisierte regionale Analyse der ANXA2-Expression in GBM bestätigte ihre

Assoziation mit der mesenchymalen molekularen Signatur. Sie konnte aber keine spezifische intratumorale Variation in der Expression nachweisen. Die Rolle, die ANXA2 bei der Invasion spielt, könnte darauf hindeuten, dass seine Aktivität vor allem im Bereich der Tumorinvasion von

Bedeutung ist. Allerdings konnte dies bei der Beurteilung der ANXA2-Expression in verschiedenen Tumorarealen, einschließlich der peritumoralen Ödemzone, nicht bestätigt werden.

Eine reduzierte ANXA2-Expression in der Ödemzone im Vergleich zur Kontrastmittel- anreichernden Zone und dem Tumorzentrum mesenchymaler Tumore könnte mit der Heterogenität dieser Regionen zusammenhängen, in der ANXA2-exprimierende neoplastische Zellen mit den nicht-transformierten Hirnzellen, welche kein ANXA2 exprimieren, vermischt sind. Zukünftige

Experimente müssen bestätigen, ob ANXA2 eine Rolle bei der Invasion durch eine differentielle

Proteinaktivierung in Tumorzellen im peritumoralen Ödem spielt.

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Danksagung

Ich danke meiner Doktormutter PD Dr. Astrid Weyerbrock für die Überlassung des Themas, die hervorragende Betreuung, sowie die mühevolle Arbeit des Korrekturlesens.

Dr. Roberto Ferrarese danke ich besonders für die Themastellung, die hervorragende Betreuung und seine ständige Diskussions- und Hilfsbereitschaft.

Besonderen Dank auch an die gesamte Arbeitsgruppe besonders Herr. Darren Ó hailin, für die freundschaftliche Arbeitsatmosphäre, viele wertvolle Anregungen und stete Hilfsbereitschaft, die wesentlich zum Gelingen dieser Arbeit beigetragen haben.

Bei meiner Familie möchte ich mich ganz besonders herzlich bedanken für die uneingeschränkte, liebevolle und vielseitige Unterstützung während meines Studiums, ohne die diese Arbeit so nicht möglich gewesen wäre.