Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2017 (2017), Article ID 9634172, 13 pages
Review Article

Contribution of the Microenvironmental Niche to Glioblastoma Heterogeneity

1Molecular Neurotherapeutics Laboratory, National Neuroscience Institute, Singapore
2Department of Physiology, National University of Singapore, Singapore
3National Heart Research Institute Singapore, National Heart Centre Singapore, Singapore
4Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore

Correspondence should be addressed to Ivy A. W. Ho; gs.moc.inn@oh_wa_yvi

Received 24 February 2017; Revised 20 April 2017; Accepted 30 April 2017; Published 28 May 2017

Academic Editor: Sara Piccirillo

Copyright © 2017 Ivy A. W. Ho and Winston S. N. Shim. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Glioblastoma is the most aggressive cancer of the brain. The dismal prognosis is largely attributed to the heterogeneous nature of the tumor, which in addition to intrinsic molecular and genetic changes is also influenced by the microenvironmental niche in which the glioma cells reside. The cancer stem cells (CSCs) hypothesis suggests that all cancers arise from CSCs that possess the ability to self-renew and initiate tumor formation. CSCs reside in specialized niches where interaction with the microenvironment regulates their stem cell behavior. The reciprocal interaction between glioma stem cells (GSCs) and cells from the microenvironment, such as endothelial cells, immune cells, and other parenchymal cells, may also promote angiogenesis, invasion, proliferation, and stemness of the GSCs and be likely to have an underappreciated role in their responsiveness to therapy. This crosstalk may also promote molecular transition of GSCs. Hence the inherent plasticity of GSCs can be seen as an adaptive response, changing according to the signaling cue from the niche. Given the association of GSCs with tumor recurrence and treatment sensitivity, understanding this bidirectional crosstalk between GSCs and its niche may provide a framework to identify more effective therapeutic targets and improve treatment outcome.

1. Introduction

Glioblastoma (GBM), World Health Organization (WHO) grade IV glioma, is the most aggressive primary brain tumor in adults and accounts for over 50% of the tumors of the brain [1]. Current standard therapy after initial diagnosis includes maximal surgical debulking followed by adjuvant temozolomide (TMZ) administration and radiation therapy [2, 3]. Unfortunately, recurrent cases of GBM that are highly resistant to radiation and chemotherapy are common and relapsed patients have a dismal survival of less than 15 months [1]. These recurring malignant gliomas are highly infiltrative and may stem from a subpopulation of glioma stem cells (GSCs) that shares some characteristics with neural stem and precursor cells [410], such as self-renewal capability.

Two hypotheses have been proposed on the origin of such tumor heterogeneity. Clonal evolution hypothesis suggests that most cancers arise from a single altered cell which facilitates tumor initiation and progression. As the tumor progresses, accumulated genomic instability results in the appearance of new genetic variants. Those variants with selective growth advantage expand to become the predominant subpopulation in the tumor. The presence of multiple subpopulations in a tumor thus supports the theory of tumor heterogeneity. On the other hand, cancer stem cells (CSCs) hypothesis suggests that intratumor heterogeneity arises from CSCs that possess the ability to self-renew and initiate tumor formation. CSCs give rise to phenotypically diverse cancer cells and reside in specialized niches where interaction with the microenvironment regulates their stem cell behavior. This behavior suggests a possible linkage between therapy outcome and genomic composition of the tumor. Recent experimental evidence supports the concept of CSCs plasticity and the ability of non-CSCs to dedifferentiate into CSCs [11]. This concept is further supported by lineage tracing and clonal analysis experiments that demonstrate the hierarchical organization of tumor in vivo [1214].

2. Molecular Heterogeneity of GBM

Advances in genomic sequencing and transcriptomic profiling reveal the existence of multiple molecular subtypes, namely, proneural, neural, classical, and mesenchymal, within a tumor, highlighting the heterogeneous nature of GBM [15, 16]. Each subtype is characterized by different transcriptional profile [1517] and varied response to radiotherapy and chemotherapy [1825]. The proneural GBM subtype can be further characterized as either isocitrate dehydrogenase-1 (IDH-1) wildtype or mutant. Mutation in IDH-1 results in remodeling of the glioma methylome, thus resulting in activation of gene expression characteristics of glioma CpG island methylator phenotype- (G-CIMP-) positive low grade tumor. Mutant IDH-1, which is G-CIMP-positive, has better prognosis and treatment response that is commonly seen in grade 2 and 3 tumor, thus representing secondary GBM [26, 27]. On the other hand, wildtype IDH-1, which is G-CIMP-negative, is characteristic of primary GBM that is more aggressive and less responsive to treatment than mutant IDH-1 [28]. The G-CIMP-negative GBM (IDH wildtype proneural, neural, classical, and mesenchymal) responds differently to standard therapeutic modality of temozolomide and radiation. IDH-1 wildtype proneural tumor is more amenable to standard treatment regimen than those presented with mesenchymal tumor subtype [18, 21, 29].

The existence of different molecular subtypes within a tumor [30] and at single cell level [31, 32] was demonstrated using genome wide gene expression analysis. Using fluorescence-guided multiple sampling approach, Sottoriva and colleagues showed that GBM tumor fragments harvested from spatially distinct location within the tumor can be classified into different molecular subtypes based on their gene expression profile [30]. Patel and colleagues revealed that all GBM contain heterogeneous mixtures of tumor cells using single cell transcriptomic analysis on 430 cells harvested from five GBM patients. They demonstrated that, regardless of the dominant subtype of the tumor, all tumors contain some cells having molecular characteristics that conform to the proneural subtype according to the Cancer Genome Atlas (TCGA) classification scheme [31], supporting the notion that all GBM subclasses evolve from the proneural subclasses [33]. Importantly, the group demonstrated that increased heterogeneity of the tumor correlates with poorer survival [31]. Using large-scale clonal analysis of glioma-initiating cells harvested from primary GBM, Segerman et al. further revealed the widespread and extensive heterogeneity that correspond to response to radiation and chemotherapy [32]. Resistant clones were associated with the mesenchymal cell state, which is consistent with previous reports in GBM and other carcinomas in which mesenchymal phenotype is associated with increased therapeutic resistance [3436]. Given that all tumors contain a portion of proneural cells regardless of their dominant subclasses [31], it is conceivable that the clinical outcome of GBM tumor is greatly influenced by subtype of cells that coexist within that tumor environment.

It is now established that an epithelial-mesenchymal-like transition (EMT), termed as proneural-mesenchymal transition (PMT), exists in GBM [16, 35, 37]. Analysis performed on paired GBM specimens prior to radiotherapy and at the time of recurrence suggested that there is a shift of the glioma cells from the proneural to the mesenchymal phenotype [16]. In addition, transcription factors that play important role in EMT, such as twist family BHLH transcription factor-1 (TWIST-1), zinc finger E-box binding homeobox-1 (ZEB-1)/ZEB-2, and snail family transcriptional repressor-1 (SNAIL-1)/SNAIL-2, were found to be altered in GBM [38, 39] as the proneural cells undergo transformation to mesenchymal subtype. Downregulation of proneural-specific markers and upregulation of mesenchymal-specific markers were also observed in irradiated proneural glioma cells [35]. Furthermore, elevated levels of mesenchymal markers expression were observed in mouse xenograft model treated with bevacizumab, a monoclonal antibody against vascular endothelial growth factor (VEGF) [37]. The shift from proneural to mesenchymal phenotype may account for the enhanced aggressiveness observed in patients with recurrent glioma that have acquired resistance to bevacizumab [37]. This evidence collectively points to an intimate involvement of microenvironmental flow of signals in contributing to PMT, suggesting that targeting the microenvironmental niche is critical for controlling GBM.

3. Microenvironment and Tumor Heterogeneity

Heterogeneity among tumor cells not only arises within a single tumor as a result of molecular and genetic changes but also is affected by different microenvironments within different regions of the tumor [4042]. GBM are highly vascularized, and often GSCs that are in the perivascular niches are observed to interact with endothelial cells (ECs) [43, 44]. Interactions between GSCs and their environment through autocrine or paracrine factors promote invasion and growth of GSCs and likely affect their response to therapy [45]. Likewise, GSCs exist in a particular niche will cross-influence the stemness of other GSCs. Understanding this bidirectional crosstalk between GSCs and its niches is critical to deciphering the regulatory role of the microenvironment on GSCs tumor initiation, invasion, therapeutic resistance, and heterogeneity.

3.1. Perivascular Environment

The perivascular niche of brain tumor is critical to the maintenance of CSC state of the tumor. GSCs are often found to adhere to vascular structures where physical interaction with ECs occurs [44, 46, 47]. The physical proximity of GSCs to ECs is a key driver of tumor progression [44] and interaction between tumor cells and ECs/pericytes has been reported to influence GBM malignancy [46]. ECs promote GSCs survival through secretion of soluble factors such as transforming growth factor-β (TGF-β) and platelet derived growth factor (PDGF), which in turn increase expression of stemness-related genes such as SRY-box-2 (Sox-2), oligodendrocyte lineage transcription factor-2 (Olig-2), Bmi-1, and CD133 in GSCs [4]. On the other hand, GSCs promote ECs angiogenesis through expression of proangiogenic factors such as VEGF.

Direct interaction between ECs and GSCs also activates key stemness pathways such as nitric oxide- (NO-) cyclic GMP pathway [48] and Notch signaling [49]. In the brain tumor microenvironment, NO is synthesized by nitric oxide synthase (NOS). There are three isoforms of NOS, neuronal NOS (NOS-1 or nNOS), inducible NOS (NOS-2 or iNOS), and endothelial NOS (NOS-3 or eNOS). nNOS and eNOS, which are constitutive and calcium-dependent, produce small amount of NO for very short period of time when activated. By contrast, iNOS is calcium-independent and generates high concentration of NO that last for longer intervals when activated. All three NOS isoforms are highly expressed in high grade glioma in comparison to the lower grade tumors [5054], with the exception of iNOS, which is also highly expressed in GSCs [55]. The cell autonomous increase in iNOS expression in GSCs results in enhanced neurosphere formation and tumorigenic potential and correlates with poor patient survival [55]. Interestingly, NO production in the tumor microenvironment may also be regulated by interaction between the glioma cells and ECs. This reciprocal production of NO by the glioma cells (nNOS) and ECs (eNOS) may represent another way of direct crosstalk between cells in the microenvironment that facilitate tumorigenesis [56, 57]. iNOS-induced tumorigenesis can be abrogated by the expression of the NO consuming enzyme flavohemoglobin [55]. Indeed, when iNOS was targeted using either small molecular inhibitor or shRNA, there was a significant loss in tumorigenesis in both human and murine glioma cells [55], demonstrating that GSCs-derived iNOS may be a potential therapeutic target. In addition to NO signaling, Notch signaling between cells of the microenvironment also promotes GSCs-mediated tumorigenesis. Notch-1 and Notch-2 are expressed on GSCs, while their ligands, Delta-like-4 (DL-4) and Jagged-1, are expressed on the ECs [49]. Abrogating Notch signaling through targeted knockdown of DL-4 or Jagged-1 in brain microvascular endothelial cells has been shown to reduce tumor angiogenesis and tumor growth [49]. On the other hand, using a PDGF-driven glioma model, Charles and colleagues found that eNOS maintain GSCs phenotype and enhanced tumorigenesis via activation of Notch signaling [56]. However, Notch signaling was suppressed when eNOS expression was blocked and thus reduced tumor growth and prolonged survival of tumor bearing mice [56]. In addition to Notch and NO, PDGF also induces stemness associated genes in patient-derived neurosphere lines via inhibitor of differentiation (ID) [58], which functions to maintain GBM mesenchymal subclass and promote adherence of GSCs to the perivascular niche [59]. Inactivation of ID protein resulted in loss of GSCs contact with the ECs and loss of self-renewal [60]. Thus, it appears that ID, NO, PDGF, and Notch individually enhance the self-renewal capacity of GSCs. But together, the PDGF-ID-NO-Notch signaling axes not only maintain and promote GSCs phenotype but also enhance tumor angiogenesis [61].

GSCs are not passive recipient in the microenvironment; in fact, they play active participatory role such as stimulating angiogenesis through expression of angiogenic factors such as VEGF [43, 62]. Recent studies have suggested that GSCs may differentiate into ECs [63, 64] and pericytes [14]. Ricci-Vitiani and coworkers found that a percentage of ECs within GBM contain somatic mutations identical to the tumor cells, suggesting neoplastic origin of the vascular endothelium [63, 64]. However, large-scale analysis of patient-derived brain tumors suggested that tumor-derived endothelial cells are rare events [65]. By contrast, GSCs differentiation into pericytes was shown to promote vessel maturation. Using lineage tracing of GSCs from 21 GBM xenografts, Cheng and colleagues demonstrated that GSCs give rise to pericytes in vivo in part through EC-derived TGF-β signaling [14]. Importantly, tumor vessels with few pericytes coverage appeared to be more sensitive to radiation and chemotherapy treatment [66, 67]. On the other hand, high pericyte coverage stabilizes vessels and promotes perfusion and thus promotes tumor growth [68]. The results from Cheng et al.’s studies further demonstrated that depletion of GSCs-derived pericytes results in inhibition of tumor growth, thus suggesting a possible utility of targeting GSCs-derived pericytes for treating GBM.

GSCs not only interact with ECs in the perivascular niche but also interact with the extracellular matrix (ECM). Abnormal ECM remodeling affects ECs, immune cells, and tumor angiogenesis, which influences GBM progression and invasion. ECM components, such as laminin, integrin, vitronectin, and fibronectin, have been shown to associate with tumor grade and patient survival. The laminin family of proteins consists of five laminin α chains, four laminins β chains, and three laminins chains. These , , and subunits form heterotrimers to promote downstream signaling including promotion of cell adhesion and migration, regulation of cell proliferation, differentiation, and survival [69, 70]. Among them, α2 and α4 laminins are primarily expressed in mesenchymal cells. Specifically, laminin α2 expression is higher in classical and mesenchymal subtypes than neural and proneural subtypes and correlates with poorer survival. Lathia et al. demonstrated that laminin α2, which is expressed in non-GSCs and ECs, plays a role in GSCs maintenance. Targeted knockdown of laminin α2 using shRNAs decreased the clonogenic and proliferative capacity of GSCs. Further, depletion of laminin α2 results in increased tumor latency in mice [71]. Laminin α4 is also expressed in glioma and other tumor cells, especially after EMT, and contributes to tumor invasion and recurrence [7278]. The laminin receptor, integrin α6β1, regulates tumor cells survival and promotes EC growth in GBM [79] and is required for GSCs maintenance [80, 81]. In the perivascular niche, integrins mediate the interaction between tumor cells and ECs, thus maintaining the function of the niche. Similar to laminin, alteration in integrin expression is associated with tumor malignancy [82]. In fact, prosurvival integrin-mediated signaling following radiation and chemotherapy occurs at the ECM. Integrins are heterodimeric cell adhesion molecules formed by dimerization of 18 α-subunits and 8 β-subunits. Integrins αvβ3, αvβ5, α5β1, α3, and α6 are expressed in GBM [8386]. In particular, αvβ3 and αvβ5 are enriched in highly vascularized GBM; as a result, targeting these integrins with cilengitide was evaluated in clinical trials. Unfortunately, results from recent CENTRIC trial did not demonstrate improved outcomes for patient treated with cilengitide in combination with temozolomide and chemoradiotherapy [83]. Despite the setback, integrin remains a potential target because GSCs also express high levels of α3 and α6 [85]. Overexpression of integrin α3 has been shown to promote GBM invasion via the ERK1/2 signaling in human astrocytoma and GBM patient-derived xenograft mouse model [84]. On the other hand, integrin α5β1, which is expressed in mesenchymal GBM and is associated with increased invasion, negatively regulates the p53 pathway to modulate prosurvival molecule survivin in GSCs and mouse xenograft model [86].

Another molecule that is highly expressed in the ECM at the perivascular niche is cadherins, which mediate cell-cell interactions in multiple processes including tumor invasion [8789]. Cadherins mediate cell adhesion through interaction with β-catenin, protein kinase C, cdc42, and Numb. N-cadherin is expressed in normal stem cell niche and is required for maintenance of progenitor state [90]. On the other hand, E-cadherin is downregulated in GBM and is associated with poor prognosis [91]. Alteration in cadherin expression is found to associate with a change in tumor phenotype and growth. For example, inhibiting VEGF pathway induces a switch from angiogenic to invasive phenotype, which is followed by a switch in cadherin subtype. Specifically, cadherin 11 is highly expressed in mesenchymal GBM subclasses and is associated with enhanced GBM migration and tumor growth in vivo [92].

In summary, bidirectional crosstalk between GSCs and the microenvironment in the perivascular niche enhances stem cells phenotype of GSCs and promotes glioma cell invasion, proliferation, and resistance to therapy. GSCs promote ECs recruitment and induced expression of angiogenic factors to support angiogenesis. Thus, deciphering the molecular mechanisms involved in the interaction between GSCs and the perivascular environment could well reveal insights into the complicated nature of glioma tumorigenesis.

3.2. Hypoxic Environment

Hypoxia is a hallmark of GBM [45, 9396]. Hypoxia stimulates the expression of the transcription factor hypoxia-inducible factors (HIF), which results in downstream activation of proangiogenesis factors such as angiopoietins, TGF-β, PDGF/PDGF-R, and VEGF/VEGF-R [97]. In addition to triggering multiple signaling pathways that affect GSCs self-renewal, proliferation, cell invasion, and survival [98], hypoxia also influences therapeutic resistance of GBM and enhances genetic instability of tumor cells. The low oxygen content in the tumor tissues not only attenuates expression of DNA mismatch repair genes but also inhibits free radicals generated from radiation treatment and thus impedes therapeutic efficacy and encourages rapid development of drug resistance phenomenon [99]. Furthermore, HIF-1 activates the multidrug resistance-1 (MDR-1) gene, which encodes P-glycoprotein (P-gp) ATP binding cassette transporters, in response to hypoxia. Activated P-gp acts as a drug efflux pump to remove intracellular concentration of chemotherapeutic drug and hence renders treatment ineffective.

GSCs are enriched in the hypoxic regions of GBM tumor and are characterized by reduced oxygen tension and activation of HIF-1 and HIF-2 [100]. HIF-1α is highly expressed in GBM in particular in hypoxic cells forming pseudopalisades around regions of necrosis and invading cells [101]. However, the degree of hypoxia differentially influences the expression of HIF-1α and HIF-2α. Severe hypoxic conditions result in upregulation of both HIFs in GSCs, while HIF-1α expression is also observed in nonstem cells and neural stem cells in addition to GSCs in mild hypoxia [99]. Both HIF-1α and HIF-2α are required for GSCs maintenance because targeted knockdown of either HIFs impaired GSCs self-renewal [47, 102]. Whereas HIF-2α promotes GSCs phenotype, HIF-1α is required for GSCs maintenance. HIF-2α upregulates a number of GSCs genes responsible for induction of a pluripotent state such as Kruppel-like factor-4 (Klf-4) [103], Sox-2, and Oct-4 [47, 104, 105]. Furthermore, HIF-2α also activates c-Myc [97, 98], a stem cells regulator, suggesting its role in regulating undifferentiated phenotype of CSCs in the hypoxic niche. Exposure to long-term hypoxia induced a phenotypic shift towards a stem-like state [106] that is accompanied by upregulation of Oct-4, Nanog, Sox-2, c-Myc, and nestin, all of which play roles in reprogramming [106108]. In fact, this phenotype shift is observed in GBM patients who underwent bevacizumab treatment. Bevacizumab treatment, which targets VEGF, initially normalizes the vessels integrity and permeability [109]. However, prolong treatment of bevacizumab beyond the normalization phase induces hypoxia which recruits bone marrow-derived myeloid cells to glioma tissues [110, 111]. Furthermore, comparison of GBM patient tumor samples obtained before and after bevacizumab treatment showed increased intratumoral hypoxia [112] and upregulated level of c-Met expression [113]. Hypoxia has been shown to induce c-Met expression [114]. Along the same line, c-Met transcription is activated by HIF-1α, which results in enhanced cell invasion upon activation by hepatocyte growth factor (HGF) [115]. Thus, the upregulated level of c-Met observed in bevacizumab-treated tumor may be a response to hypoxia as a result of prolong anti-VEGF therapy. In contrast to this study, Bergers and team observed elevated concentration of phosphorylated c-Met expression at the invasive edge of mouse tumors that are not hypoxic, rather than at the tumor core which is hypoxic [116], suggesting that invasive phenotype is not solely driven by higher oxygen tension. Together, these findings illustrate the plasticity of the microenvironment in shaping tumor invasiveness through the same signaling pathway.

Hypoxic regions in GBM are spatially heterogeneous, with some regions having higher degree of severity than others, indicating that individual tumor cells may respond to a range of oxygen tension in the microenvironment. These localized hypoxic regions promote a malignant phenotype clinically and may contribute to the heterogeneity of the tumor [100]. The heterogeneous hypoxic zone also contributes to heterogeneity in metabolic reprogramming. Indeed, glycolytic enzymes and glucose transporters such as Glut-1 and Glut-3 as well as lactate exporters and pH regulators such as monocarboxylate transporters (MCTs) and carbonic anhydrases are induced by hypoxia [117119]. HIFs also promote the expression of metabolites such as hexokinase, aldolase, and carbonic anhydrase which could in turn stimulate glycolytic flux and increase lactate buildup in the extracellular space [117, 118, 120]. Importantly, these metabolic enzymes and transcriptional regulators converge into multiple pathways that encourage tumor growth. The heterogeneous nature of the metabolic microenvironment can be driven by activation of phosphoinositide 3-kinase (PI3K)/Akt, Myc, or p53, which orchestrate glycolysis [121123], glutaminolysis, and lipid synthesis [124, 125] pathways [126, 127].

GBM displays the Warburg effect, which is a preference to utilize aerobic glycolysis for energy instead of oxidative phosphorylation. Overexpression of metabolic enzymes such as hexokinase 2 (HK2) that is required for metabolic reprogramming has been shown in GBM, but not in low grade brain tumor [128]. In addition to pyruvate dehydrogenase kinase 1 or Glut1/4 [128130], GBM also expresses UDP-Glc and UDP-glucuronic acid (UDP-GlcA) and crucial substrates of glycosaminoglycan (GAG) synthesis, during hypoxia [131]. Upregulation of UDP-GlcA suggests reshaping of the tumor microenvironment through altered GAG synthesis [132] during hypoxia. Notwithstanding, metabolic needs of tumor cells are dynamic and may depend on the severity of hypoxia [133135], exposure to cytokines, or extracellular matrix proteins [136]. Metabolic symbiosis between hypoxic and aerobic tumor cells was recently reported in which metabolic substrates such as lactate produced in hypoxic cells are taken up by normoxic cancer cells and used as fuel [137139]. This symbiotic microenvironment may promote subtype switching.

In GBM, IDH-1 wildtype proneural subclasses are characterized by having high glutamate level [140]. On the other hand, aldehyde dehydrogenase-1A3 (ALDH-1A3), an isozyme of ALDH-1 in the glycolysis and gluconeogenesis pathway, is elevated in mesenchymal subclasses [35] through the activation of the transcription factor FoxD1 [141]. Blocking ALDH-1 activity with inhibitor diethylaminobenzaldehyde (DEAB) or a novel class of imidazo pyridine derivatives reduced mesenchymal tumor cells growth and inhibited xenograft growth in glioma bearing mouse brains [35, 141]. Using a collection of seventeen patient-derived GSCs, Marziali and colleagues found that the proneural-like GSCs express metabolites such as N-acetylaspartate (NAA) and -aminobutyric acid (GABA), which is involved in the production of neurotransmitters. Conversely, mesenchymal-like GSCs lack NAA and GABA but have high levels of high mobile lipids indicative of an astroglial-like metabolism [142], thus demonstrating the differential metabolic programming in different molecular subclasses. Interestingly, Marin-Valencia and team suggested that GBM can utilize both glycolysis and mitochondrial glucose oxidation as their energy source as revealed by carbon-13 nuclear magnetic resonance spectroscopy of GBM xenograft in vivo [143]. Along the same vein, Janiszewska et al. found that the oncofetal insulin-like growth factor 2 mRNA-binding protein 2 (IMP2, IGFBP2), which plays a role in oxidative phosphorylation, is a key regulator in proneural GSCs and correlates with poor prognosis [144]. Unlike mesenchymal GSCs, inhibition of oxidative phosphorylation, but not glycolysis, abolishes GBM cells clonogenicity in proneural GSCs, suggesting that mesenchymal and proneural GSCs preferentially utilize different pathways for fuel [143]. How the metabolic pattern differs between different molecular subtypes remains unclear, but it is highly probable that intricate crosstalk between the microenvironment and the tumor may influence the metabolic profile of the tumor.

Several oncogene driven pathways converge to drive changes in metabolic programming. A key to understanding the therapeutic significance of metabolic changes in the tumor is to integrate information obtained through omics profiling via genomics, epigenetics, and transcriptomics as well as metabolomics of different stages of tumor, so as to decipher critical enzymatic players at a systems level for possible therapeutic targets.

3.3. Inflammatory Environment

Vascular abnormalities in GBM can result in disruption of the blood-brain barrier (BBB). BBB is composed of astrocytes, endothelial cells, and pericytes that tightly regulate the transfer of molecules between the blood and the brain. Intact BBB ensures that the brain is immune-privilege [145]. Disruption of the BBB, arising from either loss of vessels integrity or displacement of astrocytes by glioma cells, allows the influx of circulating immune cells. Monocytes [146], neutrophils [147], and myeloid-derived suppressor cells (MDSC) [148, 149] are commonly found within the tumor microenvironment [150153]. These cells form another component of the heterogeneous tumor microenvironment, where crosstalk among the various members promote angiogenesis, convey immune-suppressive functions, and promote tumor growth and progression.

In the tumor microenvironment, tumor associated macrophages (TAMs) are commonly found in the vicinity of GSCs and correlate with the density of GSCs perhaps owing to the higher level of chemoattractants such as VEGF [146, 154]. The percentage of TAMs infiltration into a tumor is positively correlated with the tumor grade [155]. TAMs can be defined into either type 1 macrophages (M1)/Th1 (type 1 T helper cells) or type 2 macrophages (M)/Th2. Classically activated M1 macrophages stimulate antitumor response by production of proinflammatory cytokines, presenting antigens to adaptive immune cells and phagocytosing tumor cells. On the other hand, the alternatively activated M2 macrophages express immunosuppressive cytokines, intracellular signal transducer, and activator of transcription 3 (STAT3) and scavenger receptors such as CD163, CD204, and CD206 and promote tumor supportive CD4+ regulatory T cells [156159]. GSCs secrete soluble factors, such as periostin, that recruit and support the growth of macrophages through integrin αvβ3 [160]. Conversely, molecules produced by TAMs, such as TGF-β, stromal-derived factor-1 (SDF-1), and NO, maintain and promote GSCs [161164]. TGF-β plays dual role in the tumor microenvironment. On the one hand, TGF-β released from TAMs induces matrix-metalloproteinase-2 (MMP-2) and MMP-9 expression from GBM to augment GC invasion [111, 165167]. On the other hand, TGF-β released from GSCs actively suppresses M1 macrophages, inhibits phagocytosis, and induces polarization of microglial and macrophages into the immunosuppressive M2 phenotype and thus enhances the capacity of TAMs to inhibit T cell proliferation, thereby promoting tumor progression [164, 168].

MDSCs are a heterogeneous population of immature myeloid progenitors that mediate immune suppression and support glioma growth, invasion, vascularization, and expansion of regulatory T cells via various molecules. It is believed that MDSCs interact with gliomas and GSCs [169]; however, the exact mechanisms of crosstalk remain undefined. Using CD133 and Sox2, Otvos and colleagues found significant amount of MDSCs located directly adjacent to GSCs [149], suggesting possible interaction between GSCs and MDSCs in the tumor microenvironment. Although the mechanism of crosstalk is not clear, what we do know is that glioma cells recruit immature myeloid cells to promote their differentiation into MDSCs either through direct cell-cell contact or the release of soluble factors or exosomes. MDSCs primed with GSCs conditioned media were found to have elevated ratio of CD4-positive to CD8-positive T cells and decreased interferon-γ (IFN-γ) production, suggesting that soluble factors secreted by GSCs exerted an immunosuppressive phenotype in MDSCs [149]. Using a cytokine screen performed on GSCs and nonstem tumor cells conditioned media, Otvos et al. found significantly higher level of migratory inhibitory factor (MIF) in GSCs conditioned media. MIF regulate arginase-1 production through a C-X-C-chemokine receptor-2 (CXCR-2)-dependent manner [149]. Arginase-1 plays a role in MDSCs-induced immunosuppression by depleting L-arginine essential for growth and differentiation of T cells, resulting in T cell dysfunction [170]. The group further demonstrated that blocking MIF using shRNA reduced arginase-1 production. Furthermore, depleting MIF in immunocompetent mouse glioma using shRNAs increased tumor latency and proportion of cytotoxic T cells but decreased [170]. Similarly, Domenis et al. also demonstrated that exosomes released by GSCs promoted immunosuppressive phenotype in monocytes and stimulated production of arginase-1 and interleukin-10 (IL-10) by monocytic-MDSCs [169]. Together, these studies demonstrated that MDSCs interact with GSCs to modulate glioma aggressiveness by immunosuppressing monocytes and other T cell populations.

It is interesting to note that each molecular subtype has different frequency and types of immune infiltrates. Higher frequency of TAMs was detected in mesenchymal subtypes in comparison to other GBM subtypes [171]. In fact mesenchymal subtype GBM is mainly infiltrated with microglia, whereas proneural and neural subtypes contain similar frequency of MDSCs, microglia, and macrophages, while classical subtype has a higher percentage of MDSCs [152]. However, implications of the different percentage and type of immune cells in response to therapy remain unknown. Interestingly, PMT signaling pathways are found to be upregulated in TAMs, indicating a role of the immune cells in influencing GBM heterogeneity [152, 172] and modulating mesenchymal differentiation [34].

Triggering PMT in tumor cells in the perivascular niche not only induces stem cells phenotypes but also maintains the stemness of cancer cells. One of the molecules that is crucial in PMT is osteopontin, which is secreted by immune cells under inflammatory conditions and promotes GSCs phenotype by activating CD44 [173]. Higher level of osteopontin expression is found in mesenchymal GBM when compared with other GBM subtypes. This finding is consistent with the preclinical finding that osteopontin expression is higher in murine microglia than in macrophages in GL261 mouse glioma model [174]. Whereas mesenchymal GBM also express CD44 at high level, CD44 expression in proneural tumors is confined to the perivascular niche [173]. Moreover, CD44 expression correlates with hypoxia-induced gene signatures and poor survival [173]. An elegant study by Bhat et al. showed that subtype switching from proneural to mesenchymal can be driven by paracrine factors such as tumor necrosis factor-α (TNF-α), which in turn activates transcription factor nuclear factor-κB (NF-κB) to drive mesenchymal transition [34]. Another study identified the transcriptional coactivator with PDZ-binding motif (TAZ) as a key mediator of mesenchymal phenotype in GBM [175]. Silencing of TAZ in mesenchymal GBM decreased expression of mesenchymal markers; on the other hand, overexpression of TAZ in proneural GSCs induced mesenchymal markers expression [175]. Together with STAT3 and CCAAT-enhancer-binding proteins-β (CEBP-β), CD44 and NF-κB activation portends poor survival in GBM patients [34]. Importantly, these transcription factors also play important role in inflammatory response, further reinforcing the concept that crosstalk between paracrine factors and inflammation-associated transcription factors drives mesenchymal transition [34, 35, 176].

It remains unclear what factors are responsible for mediating the interaction between GSCs, ECs, and TAMs. Given the complexity of the glioma inflammatory niche, elucidating the molecular mechanism involved in various interactions is critical to address several key questions: do TAMs acquire dissimilar function when interacting with different microenvironment generated by the various molecular subclasses? Does combining TAMs targeted therapy with standard treatment regimen give better treatment response than GSCs-targeted therapy, irrespective of the molecular subclasses? More importantly, is subtype-specific therapy essential for personalized medicine? These are some of the questions that remain to be addressed; TAMs remain a promising target for the design of therapeutic intervention.

4. Concluding Remarks

The inherent plasticity of GSCs thus suggests that its response to environmental cue is an adaptive response. Given the correlation of GSCs with tumor recurrence and response to treatment, further understating of GSCs biology and its surrounding niche may provide a framework to identify more effective treatment interventions (Figure 1).

Figure 1: Tumor microenvironment and its effect on GSCs. Dialogues between tumor cells and other cell types in the microenvironment create vascular niches that regulate tumor growth. The perivascular niche contains cells such as ECs, pericytes, astrocytes, macrophages, and microglial. Each component of the perivascular niche interacts with GSCs to promote glioma cells growth and proliferation, maintain GSCs stemness, and control vascular integrity. GBM contains areas of pseudopalisading necrosis that is the core of the hypoxic niche. Hypoxia upregulates HIFs that induce the expression of oncogenes and transcription factors such as c-Myc and STAT3 involved in stem cells maintenance and expansion. Hypoxia also contributes to metabolic programming and recruitment of macrophages and microglial. These cells form the inflammatory niche, where TAMs secrete soluble factors such as TGF-β and IL-6 that expand GSCs population and promote glioma invasion. Interaction between GSCs and the various players in the microenvironment orchestrate tumor cells responds to therapeutic interventions, thus contributing to the heterogeneity of the tumor.

Targeting the tumor microenvironment represents a promising approach to prevent tumor progression. However, several key questions remain unanswered. Although different molecular subtypes exhibit varying degree of hypoxia and immune cell infiltration, it is still not clear whether there are differences in the composition of the distinct tumor niches. Patient stratification for molecular therapies using tissues obtained from single surgical site may not present accurate information, as evidenced by the significant differences between samples obtained from different regions from the same tumor mass. Given that the tumor cells are genetically and epigenetically diverse, it is conceivable that the interaction between the tumor cells and the microenvironment is niche type specific to better accommodate the needs of the GSC. This heterogeneity in the niche will affect tumor cells response to therapies. Furthermore, the tumor microenvironment is dynamic. Changes in oxygenation, which in turn affects hypoxic conditions and metabolic states, neovascularization, and tumor invasiveness, will alter receptivity of the niches to accommodate more aggressive GBM growth. On the other hand, therapies may convert a tumor niche into a benign type or even eliminate it. For example, radiation therapy may convert the perivascular niche into hypoxic niche that promotes mesenchymal tumor growth. Conversely, short-term anti-VEGF therapy may convert a hypoxic niche into the perivascular niche that normalizes the vasculature and hence facilitates drug delivery. However, it is difficult to target specific niches for therapy; hence deciphering common shared pathways among various niches is the most efficient approach in designing therapeutic strategies. Thus, a more structured modulation of the glioma microenvironmental niche may complement the conventional treatments to achieve more effective control of the malignancy of GSC-driven GBM.

Conflicts of Interest

The authors declare no conflicts of interest.


The authors wish to thank Ms. Nurashikin Bte Abdul Halim for the illustration. Ivy A. W. Ho is supported by the Singapore Ministry of Health’s National Medical Research Council under its Translational and Clinical Research (TCR) Flagship Program-Tier 1 (NMRC/TCR/016-NNI/2-16), the NCC Research Fund and Oncology ACP, and the National Neuroscience Institute. Winston S. N. Shim is supported by GOH Foundation Grant/Duke-NUS Medical School (GCR/2013/010 and GCR/2013/011).


  1. Q. Ostrom, M. L. Cohen, A. Ondracek, A. Sloan, and J. Barnholtz-Sloan, “Gene markers in brain tumors: what the epileptologist should know,” Epilepsia, vol. 54, supplement 9, pp. 25–29, 2013. View at Google Scholar
  2. R. Stupp, W. P. Mason, M. J. van den Bent et al., “Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma,” The New England Journal of Medicine, vol. 352, no. 10, pp. 987–996, 2005. View at Publisher · View at Google Scholar
  3. D. R. Johnson and B. P. O'Neill, “Glioblastoma survival in the United States before and during the temozolomide era,” Journal of Neuro-Oncology, vol. 107, pp. 359–364, 2012. View at Publisher · View at Google Scholar · View at Scopus
  4. G.-N. Yan, L. Yang, Y.-F. Lv et al., “Endothelial cells promote stem-like phenotype of glioma cells through activating the Hedgehog pathway,” The Journal of Pathology, vol. 234, no. 1, pp. 11–22, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. M. Jackson, F. Hassiotou, and A. Nowak, “Glioblastoma stem-like cells: at the root of tumor recurrence and a therapeutic target,” Carcinogenesis, vol. 36, pp. 177–185, 2015. View at Publisher · View at Google Scholar · View at Scopus
  6. X. Gao, Y. Mi, Y. Ma, and W. Jin, “LEF1 regulates glioblastoma cell proliferation, migration, invasion, and cancer stem-like cell self-renewal,” Tumor Biology, vol. 35, pp. 11505–11511, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. D. N. Louis et al., “The 2007 WHO classification of tumours of the central nervous system,” Acta Neuropathol, vol. 114, pp. 97–109, 2007. View at Google Scholar
  8. H. Caren, S. M. Pollard, and S. Beck, “The good, the bad and the ugly: epigenetic mechanisms in glioblastoma,” Molecular Aspects of Medicine, vol. 34, pp. 849–862, 2013. View at Google Scholar
  9. K. Hamaya, K. Doi, T. Tanaka, and A. Nishimoto, “The determination of glial fibrillary acidic protein for the diagnosis and histogenetic study of central nervous system tumors: a study of 152 cases,” Acta Medica Okayama, vol. 39, pp. 453–462, 1985. View at Google Scholar
  10. C. M. Jacque, C. Vinner, M. Kujas, M. Raoul, J. Racadot, and N. A. Baumann, “Determination of glial fibrillary acidic protein (GFAP) in human brain tumors,” Journal of the Neurological Sciences, vol. 35, no. 1, pp. 147–155, 1978. View at Publisher · View at Google Scholar · View at Scopus
  11. R. G. Vries, M. Huch, and H. Clevers, “Stem cells and cancer of the stomach and intestine,” Molecular Oncology, vol. 4, pp. 373–384, 2010. View at Google Scholar
  12. A. G. Schepers, H. J. Snippert, D. E. Stange et al., “Lineage tracing reveals Lgr5+ stem cell activity in mouse intestinal adenomas,” Science, vol. 337, no. 6095, pp. 730–735, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. G. Driessens, “Deciphering tumor growth by clonal analysis,” Critical Reviews in Oncogenesis, vol. 19, no. 5, pp. 317–325, 2014. View at Publisher · View at Google Scholar · View at Scopus
  14. L. Cheng, Z. Huang, W. Zhou et al., “Glioblastoma stem cells generate vascular pericytes to support vessel function and tumor growth,” Cell, vol. 153, no. 1, pp. 139–152, 2013. View at Publisher · View at Google Scholar · View at Scopus
  15. R. G. Verhaak, K. A. Hoadley, E. Purdom et al., “Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1,” Cancer Cell, vol. 17, no. 1, pp. 98–110, 2010. View at Publisher · View at Google Scholar
  16. H. S. Phillips, S. Kharbanda, R. Chen et al., “Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis,” Cancer Cell, vol. 9, no. 3, pp. 157–173, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. U. R. Chandran, S. Luthra, L. Santana-Santos et al., “Gene expression profiling distinguishes proneural glioma stem cells from mesenchymal glioma stem cells,” Genomics Data, vol. 5, pp. 333–336, 2015. View at Publisher · View at Google Scholar
  18. T. Sandmann, R. Bourgon, J. Garcia et al., “Patients with proneural glioblastoma may derive overall survival benefit from the addition of bevacizumab to first-line radiotherapy and temozolomide: retrospective analysis of the avaglio trial,” Journal of Clinical Oncology, vol. 33, pp. 2735–2744, 2015. View at Google Scholar
  19. I. Z. Renault and D. Golgher, “Molecular genetics of glioblastomas: defining subtypes and understanding the biology,” Neuroimaging Clinics of North America, vol. 25, pp. 97–103, 2015. View at Publisher · View at Google Scholar · View at Scopus
  20. L. Erdem-Eraslan, L. A. Gravendeel, J. De Rooi et al., “Intrinsic molecular subtypes of glioma are prognostic and predict benefit from adjuvant procarbazine, lomustine, and vincristine chemotherapy in combination with other prognostic factors in anaplastic oligodendroglial brain tumors: a report from EORTC study 26951,” Journal of Clinical Oncology, vol. 31, no. 3, pp. 328–336, 2013. View at Publisher · View at Google Scholar · View at Scopus
  21. M. Le Mercier, D. Hastir, X. Moles Lopez et al., “A simplified approach for the molecular classification of glioblastomas,” PLoS ONE, vol. 7, no. 9, Article ID e45475, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. M. E. Hegi, R.-C. Janzer, W. L. Lambiv et al., “Presence of an oligodendroglioma-like component in newly diagnosed glioblastoma identifies a pathogenetically heterogeneous subgroup and lacks prognostic value: Central pathology review of the EORTC-26981/NCIC-CE.3 trial,” Acta Neuropathologica, vol. 123, no. 6, pp. 841–852, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. K. L. McDonald, J. McDonnell, A. Muntoni et al., “Presence of alternative lengthening of telomeres mechanism in patients with glioblastoma identifies a less aggressive tumor type with longer survival,” Journal of Neuropathology and Experimental Neurology, vol. 69, no. 7, pp. 729–736, 2010. View at Publisher · View at Google Scholar · View at Scopus
  24. A. Quick, D. Patel, M. Hadziahmetovic, A. Chakravarti, and M. Mehta, “Current therapeutic paradigms in glioblastoma,” Reviews on Recent Clinical Trials, vol. 5, pp. 14–27, 2010. View at Publisher · View at Google Scholar · View at Scopus
  25. M. Meyer, J. Reimand, X. Lan et al., “Single cell-derived clonal analysis of human glioblastoma links functional and genomic heterogeneity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 112, pp. 851–856, 2015. View at Google Scholar
  26. H. Noushmehr, D. J. Weisenberger, K. Diefes et al., “Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma,” Cancer Cell, vol. 17, pp. 510–522, 2010. View at Google Scholar
  27. H. Ohgaki and P. Kleihues, “The definition of primary and secondary glioblastoma,” Clinical Cancer Research, vol. 19, pp. 764–772, 2013. View at Google Scholar
  28. R. J. Molenaar, D. Verbaan, S. Lamba et al., “The combination of IDH1 mutations and MGMT methylation status predicts survival in glioblastoma better than either IDH1 or MGMT alone,” Neuro-Oncology, vol. 16, no. 9, pp. 1263–1273, 2014. View at Publisher · View at Google Scholar · View at Scopus
  29. A. Omuro, K. Beal, P. Gutin et al., “Phase II study of bevacizumab, temozolomide, and hypofractionated stereotactic radiotherapy for newly diagnosed glioblastoma,” Clinical Cancer Research, vol. 20, pp. 5023–5031, 2014. View at Google Scholar
  30. A. Sottoriva, I. Spiteri, S. G. M. Piccirillo et al., “Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics,” Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 10, pp. 4009–4014, 2013. View at Publisher · View at Google Scholar · View at Scopus
  31. A. P. Patel, I. Tirosh, J. J. Trombetta et al., “Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma,” Science, vol. 344, no. 6190, pp. 1396–1401, 2014. View at Publisher · View at Google Scholar · View at Scopus
  32. A. Segerman, M. Niklasson, C. Haglund et al., “Clonal variation in drug and radiation response among glioma-initiating cells is linked to proneural-mesenchymal transition,” Cell Reports, vol. 17, pp. 2994–3009, 2016. View at Google Scholar
  33. T. Ozawa, M. Riester, Y. Cheng et al., “Most human non-GCIMP glioblastoma subtypes evolve from a common proneural-like precursor glioma,” Cancer Cell, vol. 26, no. 2, pp. 288–300, 2014. View at Publisher · View at Google Scholar
  34. K. P. Bhat, V. Balasubramaniyan, B. Vaillant et al., “Mesenchymal differentiation mediated by NF-kappaB promotes radiation resistance in glioblastoma,” Cancer Cell, vol. 24, pp. 331–346, 2013. View at Google Scholar
  35. P. Mao, K. Joshi, J. Li et al., “Mesenchymal glioma stem cells are maintained by activated glycolytic metabolism involving aldehyde dehydrogenase 1A3,” Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 21, pp. 8644–8649, 2013. View at Publisher · View at Google Scholar · View at Scopus
  36. J. P. Thiery, “Metastasis: alone or together?” Current Biology, vol. 19, no. 24, pp. R1121–R1123, 2009. View at Publisher · View at Google Scholar · View at Scopus
  37. Y. Piao, J. Liang, L. Holmes, V. Henry, E. Sulman, and J. F. de Groot, “Acquired resistance to anti-VEGF therapy in glioblastoma is associated with a mesenchymal transition,” Clinical Cancer Research, vol. 19, no. 16, pp. 4392–4403, 2013. View at Publisher · View at Google Scholar · View at Scopus
  38. X. Jin, H.-Y. Jeon, K. M. Joo et al., “Frizzled 4 regulates stemness and invasiveness of migrating glioma cells established by serial intracranial transplantation,” Cancer Research, vol. 71, no. 8, pp. 3066–3075, 2011. View at Publisher · View at Google Scholar · View at Scopus
  39. U. D. Kahlert, D. Maciaczyk, S. Doostkam et al., “Activation of canonical WNT/β-catenin signaling enhances in vitro motility of glioblastoma cells by activation of ZEB1 and other activators of epithelial-to-mesenchymal transition,” Cancer Letters, vol. 325, no. 1, pp. 42–53, 2012. View at Publisher · View at Google Scholar · View at Scopus
  40. H. Motegi, Y. Kamoshima, S. Terasaka, H. Kobayashi, and K. Houkin, “Type 1 collagen as a potential niche component for CD133-positive glioblastoma cells,” Neuropathology, vol. 34, pp. 378–385, 2014. View at Google Scholar
  41. T. Hide and J. Kuratsu, “Progress in the study of brain tumor stem cells as treatment targets,” Brain Nerve, vol. 61, pp. 781–789, 2009. View at Google Scholar
  42. D. Schiffer, M. Mellai, L. Annovazzi et al., “Stem cell niches in Glioblastoma: a neuropathological view,” BioMed Research International, vol. 2014, Article ID 725921, 7 pages, 2014. View at Publisher · View at Google Scholar · View at Scopus
  43. S. Bao, Q. Wu, S. Sathornsumetee et al., “Stem cell-like glioma cells promote tumor angiogenesis through vascular endothelial growth factor,” Cancer Research, vol. 66, no. 16, pp. 7843–7848, 2006. View at Publisher · View at Google Scholar · View at Scopus
  44. C. Calabrese, H. Poppleton, M. Kocak et al., “A perivascular niche for brain tumor stem cells,” Cancer Cell, vol. 11, no. 1, pp. 69–82, 2007. View at Publisher · View at Google Scholar · View at Scopus
  45. A. Fidoamore, L. Cristiano, A. Antonosante et al., “Glioblastoma stem cells microenvironment: the paracrine roles of the niche in drug and radioresistance,” Stem Cells International, vol. 2016, Article ID 6809105, 17 pages, 2016. View at Publisher · View at Google Scholar · View at Scopus
  46. E. M. Caspani, P. H. Crossley, C. Redondo-Garcia, and S. Martinez, “Glioblastoma: a pathogenic crosstalk between tumor cells and pericytes,” PLoS One, vol. 9, article e101402, 2014. View at Google Scholar
  47. S. Seidel, B. K. Garvalov, V. Wirta et al., “A hypoxic niche regulates glioblastoma stem cells through hypoxia inducible factor 2α,” Brain, vol. 133, no. 4, pp. 983–995, 2010. View at Publisher · View at Google Scholar · View at Scopus
  48. K. Mujoo, J. S. Krumenacker, and F. Murad, “Nitric oxide-cyclic GMP signaling in stem cell differentiation,” Free Radical Biology & Medicine, vol. 51, pp. 2150–2157, 2011. View at Google Scholar
  49. T. S. Zhu, M. A. Costello, C. E. Talsma et al., “Endothelial cells create a stem cell niche in glioblastoma by providing NOTCH ligands that nurture self-renewal of cancer stem-like cells,” Cancer Research, vol. 71, no. 18, pp. 6061–6072, 2011. View at Publisher · View at Google Scholar · View at Scopus
  50. C. S. Cobbs, J. E. Brenman, K. D. Aldape, D. S. Bredt, and M. A. Israel, “Expression of nitric oxide synthase in human central nervous system tumors,” Cancer Research, vol. 55, pp. 727–730, 1995. View at Google Scholar
  51. S. Iwata, K. Nakagawa, H. Harada, Y. Oka, Y. Kumon, and S. Sakaki, “Endothelial nitric oxide synthase expression in tumor vasculature is correlated with malignancy in human supratentorial astrocytic tumors,” Neurosurgery, vol. 45, no. 1, pp. 24–29, 1999. View at Publisher · View at Google Scholar · View at Scopus
  52. H. C. Ludwig, I. Feiz-Erfan, V. Bockermann, J. Behnke-Mursch, K. Schallock, and E. Markakis, “Expression of nitric oxide synthase isozymes (NOS I–III) by immunohistochemistry and DNA in situ hybridization. Correlation with macrophage presence, vascular endothelial growth factor (VEGF) and oedema volumetric data in 220 glioblastomas,” Anticancer Research, vol. 20, pp. 299–304, 2000. View at Google Scholar
  53. N. Tanriover, M. O. Ulu, C. Isler et al., “Neuronal nitric oxide synthase expression in glial tumors: correlation with malignancy and tumor proliferation,” Neurological Research, vol. 30, no. 9, pp. 940–944, 2008. View at Publisher · View at Google Scholar · View at Scopus
  54. J. W. Pan, R. Y. Zhan, Y. Tong, Y. Q. Zhou, and M. Zhang, “Expression of endothelial nitric oxide synthase and vascular endothelial growth factor in association with neovascularization in human primary astrocytoma,” Journal of Zhejiang University: Science B, vol. 6, no. 7, pp. 693–698, 2005. View at Google Scholar
  55. C. E. Eyler, Q. Wu, K. Yan et al., “Glioma stem cell proliferation and tumor growth are promoted by nitric oxide synthase-2,” Cell, vol. 146, no. 1, pp. 53–66, 2011. View at Publisher · View at Google Scholar · View at Scopus
  56. N. Charles, T. Ozawa, M. Squatrito et al., “Perivascular nitric oxide activates notch signaling and promotes stem-like character in PDGF-induced glioma cells,” Cell Stem Cell, vol. 6, no. 2, pp. 141–152, 2010. View at Publisher · View at Google Scholar · View at Scopus
  57. S. Kashiwagi, K. Tsukada, L. Xu et al., “Perivascular nitric oxide gradients normalize tumor vasculature,” Nature Medicine, vol. 14, no. 3, pp. 255–257, 2008. View at Publisher · View at Google Scholar · View at Scopus
  58. H.-M. Jeon, S.-H. Kim, X. Jin et al., “Crosstalk between glioma-initiating cells and endothelial cells drives tumor progression,” Cancer Research, vol. 74, no. 16, pp. 4482–4492, 2014. View at Publisher · View at Google Scholar · View at Scopus
  59. X. Jin, J. Yin, S.-H. Kim et al., “EGFR-AKT-Smad signaling promotes formation of glioma stem-like cells and tumor angiogenesis by ID3-driven cytokine induction,” Cancer Research, vol. 71, no. 22, pp. 7125–7134, 2011. View at Publisher · View at Google Scholar · View at Scopus
  60. F. Niola, X. Zhao, D. Singh et al., “Mesenchymal high-grade glioma is maintained by the ID-RAP1 axis,” Journal of Clinical Investigation, vol. 123, no. 1, pp. 405–417, 2013. View at Publisher · View at Google Scholar · View at Scopus
  61. K. Eun, H. M. Jeon, S. O. Kim et al., “A cell-autonomous positive-signaling circuit associated with the PDGF-NO-ID4-regulatory axis in glioblastoma cells,” Biochemical and Biophysical Research Communications, vol. 486, pp. 564–570, 2017. View at Google Scholar
  62. N. Oka, A. Soeda, A. Inagaki et al., “VEGF promotes tumorigenesis and angiogenesis of human glioblastoma stem cells,” Biochemical and Biophysical Research Communications, vol. 360, no. 3, pp. 553–559, 2007. View at Publisher · View at Google Scholar · View at Scopus
  63. R. Wang, K. Chadalavada, J. Wilshire et al., “Glioblastoma stem-like cells give rise to tumour endothelium,” Nature, vol. 468, no. 7325, pp. 829–833, 2010. View at Publisher · View at Google Scholar · View at Scopus
  64. L. Ricci-Vitiani, R. Pallini, M. Biffoni et al., “Tumour vascularization via endothelial differentiation of glioblastoma stem-like cells,” Nature, vol. 468, pp. 824–828, 2010. View at Google Scholar
  65. F. J. Rodriguez, B. A. Orr, K. L. Ligon, and C. G. Eberhart, “Neoplastic cells are a rare component in human glioblastoma microvasculature,” Oncotarget, vol. 3, pp. 98–106, 2012. View at Google Scholar
  66. M. Franco, P. Roswall, E. Cortez, D. Hanahan, and K. Pietras, “Pericytes promote endothelial cell survival through induction of autocrine VEGF-A signaling and Bcl-w expression,” Blood, vol. 118, pp. 2906–2917, 2011. View at Google Scholar
  67. G. Bergers, S. Song, N. Meyer-Morse, E. Bergsland, and D. Hanahan, “Benefits of targeting both pericytes and endothelial cells in the tumor vasculature with kinase inhibitors,” Journal of Clinical Investigation, vol. 111, pp. 1287–1295, 2003. View at Google Scholar
  68. V. G. Cooke, V. S. LeBleu, D. Keskin et al., “Pericyte depletion results in hypoxia-associated epithelial-to-mesenchymal transition and metastasis mediated by met signaling pathway,” Cancer Cell, vol. 21, pp. 66–81, 2012. View at Publisher · View at Google Scholar
  69. M. Durbeej, “Laminins,” Cell and Tissue Research, vol. 339, no. 1, pp. 259–268, 2010. View at Publisher · View at Google Scholar · View at Scopus
  70. J. H. Miner and P. D. Yurchenco, “Laminin functions in tissue morphogenesis,” Annual Review of Cell and Developmental Biology, vol. 20, pp. 255–284, 2004. View at Publisher · View at Google Scholar
  71. J. D. Lathia, M. Li, P. E. Hall et al., “Laminin alpha 2 enables glioblastoma stem cell growth,” Annals of Neurology, vol. 72, no. 5, pp. 766–778, 2012. View at Publisher · View at Google Scholar · View at Scopus
  72. H. Fujiwara, Y. Kikkawa, N. Sanzen, and K. Sekiguchi, “Purification and characterization of human laminin-8. Laminin-8 stimulates cell adhesion and migration through α3β1 and α6β1 integrins,” Journal of Biological Chemistry, vol. 276, pp. 17550–17558, 2001. View at Google Scholar
  73. H. Fujiwara, J. Gu, and K. Sekiguchi, “Rac regulates integrin-mediated endothelial cell adhesion and migration on laminin-8,” Experimental Cell Research, vol. 292, pp. 67–77, 2004. View at Google Scholar
  74. T. Kawataki, T. Yamane, H. Naganuma et al., “Laminin isoforms and their integrin receptors in glioma cell migration and invasiveness: Evidence for a role of α5-laminin(s) and α3β1 integrin,” Experimental Cell Research, vol. 313, no. 18, pp. 3819–3831, 2007. View at Publisher · View at Google Scholar · View at Scopus
  75. N. Vainionpaa, V. P. Lehto, K. Tryggvason, and I. Virtanen, “Alpha4 chain laminins are widely expressed in renal cell carcinomas and have a de-adhesive function,” Laboratory Investigation, vol. 87, pp. 780–791, 2007. View at Google Scholar
  76. M. Takkunen, M. Ainola, N. Vainionpää et al., “Epithelial-mesenchymal transition downregulates laminin α5 chain and upregulates laminin α4 chain in oral squamous carcinoma cells,” Histochemistry and Cell Biology, vol. 130, no. 3, pp. 509–525, 2008. View at Publisher · View at Google Scholar · View at Scopus
  77. Y. Oikawa, J. Hansson, T. Sasaki et al., “Melanoma cells produce multiple laminin isoforms and strongly migrate on α5 laminin(s) via several integrin receptors,” Experimental Cell Research, vol. 317, no. 8, pp. 1119–1133, 2011. View at Publisher · View at Google Scholar · View at Scopus
  78. J. Y. Ljubimova, M. Fugita, N. M. Khazenzon et al., “Association between laminin-8 and glial tumor grade, recurrence, and patient survival,” Cancer, vol. 101, no. 3, pp. 604–612, 2004. View at Publisher · View at Google Scholar · View at Scopus
  79. P. Huang, M. R. S. Rani, M. S. Ahluwalia et al., “Endothelial expression of TNF receptor-1 generates a proapoptotic signal inhibited by integrin α6β1 in glioblastoma,” Cancer Research, vol. 72, no. 6, pp. 1428–1437, 2012. View at Publisher · View at Google Scholar · View at Scopus
  80. T. M. Fael Al-Mayhani, S. L. R. Ball, J.-W. Zhao et al., “An efficient method for derivation and propagation of glioblastoma cell lines that conserves the molecular profile of their original tumours,” Journal of Neuroscience Methods, vol. 176, no. 2, pp. 192–199, 2009. View at Publisher · View at Google Scholar · View at Scopus
  81. S. M. Pollard, K. Yoshikawa, I. D. Clarke et al., “Glioma stem cell lines expanded in adherent culture have tumor-specific phenotypes and are suitable for chemical and genetic screens,” Cell Stem Cell, vol. 4, no. 6, pp. 568–580, 2009. View at Publisher · View at Google Scholar · View at Scopus
  82. M. D. Brooks, R. Sengupta, S. C. Snyder, and J. B. Rubin, “Hitting them where they live: targeting the glioblastoma perivascular stem cell niche,” Current Pathobiology Reports, vol. 1, pp. 101–110, 2013. View at Google Scholar
  83. R. Stupp, M. E. Hegi, T. Gorlia et al., “Cilengitide combined with standard treatment for patients with newly diagnosed glioblastoma with methylated MGMT promoter (CENTRIC EORTC 26071-22072 study): a multicentre, randomised, open-label, phase 3 trial,” The Lancet Oncology, vol. 15, no. 10, pp. 1100–1108, 2014. View at Publisher · View at Google Scholar · View at Scopus
  84. M. Nakada, E. Nambu, N. Furuyama et al., “Integrin α3 is overexpressed in glioma stem-like cells and promotes invasion,” British Journal of Cancer, vol. 108, no. 12, pp. 2516–2524, 2013. View at Publisher · View at Google Scholar · View at Scopus
  85. J. D. Lathia, J. Gallagher, J. M. Heddleston et al., “Integrin alpha 6 regulates glioblastoma stem cells,” Cell Stem Cell, vol. 6, no. 5, pp. 421–432, 2010. View at Publisher · View at Google Scholar · View at Scopus
  86. G. Renner, H. Janouskova, F. Noulet et al., “Integrin α5β1 and p53 convergent pathways in the control of anti-apoptotic proteins PEA-15 and survivin in high-grade glioma,” Cell Death and Differentiation, vol. 23, no. 4, pp. 640–653, 2016. View at Publisher · View at Google Scholar · View at Scopus
  87. U. Cavallaro and G. Christofori, “Cell adhesion and signalling by cadherins and Ig-CAMs in cancer,” Nature Reviews Cancer, vol. 4, pp. 118–132, 2004. View at Google Scholar
  88. B. M. Gumbiner, “Regulation of cadherin-mediated adhesion in morphogenesis,” Nature Reviews Molecular Cell Biology, vol. 6, no. 8, pp. 622–634, 2005. View at Publisher · View at Google Scholar · View at Scopus
  89. M. Takeichi, “Cadherins in cancer: implications for invasion and metastasis,” Current Opinion in Cell Biology, vol. 5, no. 5, pp. 806–811, 1993. View at Publisher · View at Google Scholar · View at Scopus
  90. M. Klingener, M. Chavali, J. Singh et al., “N-cadherin promotes recruitment and migration of neural progenitor cells from the SVZ neural stem cell niche into demyelinated lesions,” Journal of Neuroscience, vol. 34, pp. 9590–9606, 2014. View at Google Scholar
  91. P. Li, T. Sun, Q. Yuan, G. Pan, J. Zhang, and D. Sun, “The expressions of NEDD9 and E-cadherin correlate with metastasis and poor prognosis in triple-negative breast cancer patients,” OncoTargets and Therapy, vol. 9, pp. 5751–5759, 2016. View at Google Scholar
  92. H. Kaur, P. J. Phillips-Mason, S. M. Burden-Gulley et al., “Cadherin-11, a marker of the mesenchymal phenotype, regulates glioblastoma cell migration and survival in vivo,” Molecular Cancer Research, vol. 10, no. 3, pp. 293–304, 2012. View at Publisher · View at Google Scholar · View at Scopus
  93. D. Hanahan and R. A. Weinberg, “Hallmarks of cancer: the next generation,” Cell, vol. 144, pp. 646–674, 2011. View at Google Scholar
  94. E. T. Wong and S. Brem, “Antiangiogenesis treatment for glioblastoma multiforme: challenges and opportunities,” Journal of the National Comprehensive Cancer Network, vol. 6, pp. 515–522, 2008. View at Google Scholar
  95. U. Fischer, J. Radermacher, J. Mayer, Y. Mehraein, and E. Meese, “Tumor hypoxia: impact on gene amplification in glioblastoma,” International Journal of Oncology, vol. 33, pp. 509–515, 2008. View at Google Scholar
  96. K. Irshad, S. K. Mohapatra, C. Srivastava et al., “A combined gene signature of hypoxia and Notch pathway in human glioblastoma and its prognostic relevance,” PLoS ONE, vol. 10, no. 3, Article ID e0118201, 2015. View at Publisher · View at Google Scholar · View at Scopus
  97. J. D. Gordan, J. A. Bertout, C. J. Hu, J. A. Diehl, and M. C. Simon, “HIF-2alpha promotes hypoxic cell proliferation by enhancing c-myc transcriptional activity,” Cancer Cell, vol. 11, pp. 335–347, 2007. View at Google Scholar
  98. J. D. Gordan, C. B. Thompson, and M. C. Simon, “HIF and c-Myc: sibling rivals for control of cancer cell metabolism and proliferation,” Cancer Cell, vol. 12, pp. 108–113, 2007. View at Google Scholar
  99. E. Binello and I. M. Germano, “Targeting glioma stem cells: a novel framework for brain tumors,” Cancer Science, vol. 102, pp. 1958–1966, 2011. View at Google Scholar
  100. L. Yang, C. Lin, L. Wang, H. Guo, and X. Wang, “Hypoxia and hypoxia-inducible factors in glioblastoma multiforme progression and therapeutic implications,” Experimental Cell Research, vol. 318, pp. 2417–2426, 2012. View at Google Scholar
  101. D. J. Brat, A. A. Castellano-Sanchez, S. B. Hunter et al., “Pseudopalisades in glioblastoma are hypoxic, express extracellular matrix proteases, and are formed by an actively migrating cell population,” Cancer Research, vol. 64, no. 3, pp. 920–927, 2004. View at Publisher · View at Google Scholar · View at Scopus
  102. O. Méndez, J. Zavadil, M. Esencay et al., “Knock down of HIF-1α in glioma cells reduces migration in vitro and invasion in vivo and impairs their ability to form tumor spheres,” Molecular Cancer, vol. 9, article no. 133, 2010. View at Publisher · View at Google Scholar · View at Scopus
  103. K. Takahashi, K. Tanabe, M. Ohnuki et al., “Induction of pluripotent stem cells from adult human fibroblasts by defined factors,” Cell, vol. 131, no. 5, pp. 861–872, 2007. View at Publisher · View at Google Scholar · View at Scopus
  104. K. L. Covello, J. Kehler, and H. Yu, “HIF-2α regulates Oct-4: effects of hypoxia on stem cell function, embryonic development, and tumor growth,” Genes & Development, vol. 20, no. 5, pp. 557–570, 2006. View at Publisher · View at Google Scholar
  105. V. Moreno-Manzano, F. J. Rodríguez-Jiménez, J. L. Aceña-Bonilla et al., “FM19G11, a new hypoxia-inducible factor (HIF) modulator, affects stem cell differentiation status,” The Journal of Biological Chemistry, vol. 285, no. 2, pp. 1333–1342, 2010. View at Publisher · View at Google Scholar · View at Scopus
  106. J. M. Heddleston, Z. Li, R. E. McLendon, A. B. Hjelmeland, and J. N. Rich, “The hypoxic microenvironment maintains glioblastoma stem cells and promotes reprogramming towards a cancer stem cell phenotype,” Cell Cycle, vol. 8, pp. 3274–3284, 2009. View at Google Scholar
  107. J. Mathieu, Z. Zhang, W. Zhou et al., “HIF induces human embryonic stem cell markers in cancer cells,” Cancer Research, vol. 71, no. 13, pp. 4640–4652, 2011. View at Publisher · View at Google Scholar · View at Scopus
  108. A. M. McCord, M. Jamal, U. T. Shankavarum, F. F. Lang, K. Camphausen, and P. J. Tofilon, “Physiologic oxygen concentration enhances the stem-like properties of CD133+ human glioblastoma cells in vitro,” Molecular Cancer Research, vol. 7, no. 4, pp. 489–497, 2009. View at Publisher · View at Google Scholar · View at Scopus
  109. R. K. Jain, “Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy,” Science, vol. 307, no. 5706, pp. 58–62, 2005. View at Publisher · View at Google Scholar · View at Scopus
  110. Y. Piao, J. Liang, L. Holmes et al., “Glioblastoma resistance to anti-VEGF therapy is associated with myeloid cell infiltration, stem cell accumulation, and a mesenchymal phenotype,” Neuro-Oncology, vol. 14, no. 11, pp. 1379–1392, 2012. View at Publisher · View at Google Scholar · View at Scopus
  111. X.-Z. Ye, S.-L. Xu, Y.-H. Xin et al., “Tumor-associated microglia/macrophages enhance the invasion of glioma stem-like cells via TGF-β1 signaling pathway,” Journal of Immunology, vol. 189, no. 1, pp. 444–453, 2012. View at Publisher · View at Google Scholar · View at Scopus
  112. F. M. Iwamoto, L. E. Abrey, K. Beal et al., “Patterns of relapse and prognosis after bevacizumab failure in recurrent glioblastoma,” Neurology, vol. 73, no. 15, pp. 1200–1206, 2009. View at Publisher · View at Google Scholar · View at Scopus
  113. S. D. Rose and M. K. Aghi, “Mechanisms of evasion to antiangiogenic therapy in glioblastoma,” Clinical Neurosurgery, vol. 57, pp. 123–128, 2010. View at Google Scholar
  114. E. Papaevangelou, G. S. Whitley, A. P. Johnstone, S. P. Robinson, and F. A. Howe, “Investigating the role of tumour cell derived iNOS on tumour growth and vasculature in vivo using a tetracycline regulated expression system,” International Journal of Cancer, vol. 138, pp. 2678–2687, 2016. View at Google Scholar
  115. C. Eckerich, S. Zapf, R. Fillbrandt, S. Loges, M. Westphal, and K. Lamszus, “Hypoxia can induce c-Met expression in glioma cells and enhance SF/HGF-induced cell migration,” International Journal of Cancer, vol. 121, no. 2, pp. 276–283, 2007. View at Publisher · View at Google Scholar · View at Scopus
  116. K. V. Lu, J. P. Chang, C. A. Parachoniak et al., “VEGF inhibits tumor cell invasion and mesenchymal transition through a met/vegfr2 complex,” Cancer Cell, vol. 22, no. 1, pp. 21–35, 2012. View at Publisher · View at Google Scholar · View at Scopus
  117. G. L. Semenza, “Targeting HIF-1 for cancer therapy,” Nature Reviews Cancer, vol. 3, no. 10, pp. 721–732, 2003. View at Publisher · View at Google Scholar · View at Scopus
  118. G. L. Semenza, “HIF-1: upstream and downstream of cancer metabolism,” Current Opinion in Genetics and Development, vol. 20, no. 1, pp. 51–56, 2010. View at Publisher · View at Google Scholar · View at Scopus
  119. H. M. Said, A. Staab, C. Hagemann et al., “Distinct patterns of hypoxic expression of carbonic anhydrase IX (CA IX) in human malignant glioma cell lines,” Journal of Neuro-Oncology, vol. 81, no. 1, pp. 27–38, 2007. View at Publisher · View at Google Scholar · View at Scopus
  120. H. M. Said, C. Hagemann, A. Staab et al., “Expression patterns of the hypoxia-related genes osteopontin, CA9, erythropoietin, VEGF and HIF-1α in human glioma in vitro and in vivo,” Radiotherapy and Oncology, vol. 83, no. 3, pp. 398–405, 2007. View at Publisher · View at Google Scholar · View at Scopus
  121. P. S. Ward and C. B. Thompson, “Metabolic reprogramming: a cancer hallmark even warburg did not anticipate,” Cancer Cell, vol. 21, pp. 297–308, 2012. View at Google Scholar
  122. M. Fang, Z. Shen, S. Huang et al., “The ER UDPase ENTPD5 promotes protein N-glycosylation, the Warburg effect, and proliferation in the PTEN pathway,” Cell, vol. 143, no. 5, pp. 711–724, 2010. View at Publisher · View at Google Scholar · View at Scopus
  123. R. J. DeBerardinis, J. J. Lum, G. Hatzivassiliou, and C. B. Thompson, “The biology of cancer: metabolic reprogramming fuels cell growth and proliferation,” Cell Metab, vol. 7, pp. 11–20, 2008. View at Google Scholar
  124. D. E. Bauer, G. Hatzivassiliou, F. Zhao, C. Andreadis, and C. B. Thompson, “ATP citrate lyase is an important component of cell growth and transformation,” Oncogene, vol. 24, pp. 6314–6322, 2005. View at Google Scholar
  125. D. C. Berwick, I. Hers, K. J. Heesom, S. K. Moule, and J. M. Tavare, “The identification of ATP-citrate lyase as a protein kinase B (Akt) substrate in primary adipocytes,” Journal of Biological Chemistry, vol. 277, pp. 33895–33900, 2002. View at Google Scholar
  126. K. Bensaad, A. Tsuruta, M. A. Selak et al., “TIGAR, a p53-inducible regulator of glycolysis and apoptosis,” Cell, vol. 126, no. 1, pp. 107–120, 2006. View at Publisher · View at Google Scholar · View at Scopus
  127. D. R. Green and J. E. Chipuk, “p53 and metabolism: inside the TIGAR,” Cell, vol. 126, pp. 30–32, 2006. View at Google Scholar
  128. C. B. Colen, Y. Shen, F. Ghoddoussi et al., “Metabolic targeting of lactate efflux by malignant glioma inhibits invasiveness and induces necrosis: an in vivo study 1,” Neoplasia, vol. 13, no. 7, pp. 620–632, 2011. View at Publisher · View at Google Scholar · View at Scopus
  129. E. D. Michelakis, G. Sutendra, P. Dromparis et al., “Metabolic modulation of glioblastoma with dichloroacetate,” Science Translational Medicine, vol. 2, no. 31, pp. 31–34, 2010. View at Publisher · View at Google Scholar · View at Scopus
  130. S. K. Marie and S. M. Shinjo, “Metabolism and brain cancer,” Clinics (Sao Paulo), vol. 66, supplement 1, pp. 33–43, 2011. View at Google Scholar
  131. P. Kucharzewska, H. C. Christianson, and M. Belting, “Global profiling of metabolic adaptation to hypoxic stress in human glioblastoma cells,” PLoS One, vol. 10, Article ID e0116740, 2015. View at Google Scholar
  132. M. M. Fuster and J. D. Esko, “The sweet and sour of cancer: glycans as novel therapeutic targets,” Nature Reviews Cancer, vol. 5, pp. 526–542, 2005. View at Google Scholar
  133. M. J. Allalunis-Turner, A. J. Franko, and M. B. Parliament, “Modulation of oxygen consumption rate and vascular endothelial growth factor mRNA expression in human malignant glioma cells by hypoxia,” British Journal of Cancer, vol. 80, pp. 104–109, 1999. View at Google Scholar
  134. M. B. Parliament, A. J. Franko, M. J. Allalunis-Turner et al., “Anomalous patterns of nitroimidazole binding adjacent to necrosis in human glioma xenografts: possible role of decreased oxygen consumption,” British Journal of Cancer, vol. 75, no. 3, pp. 311–318, 1997. View at Publisher · View at Google Scholar · View at Scopus
  135. M. L. Turcotte, M. Parliament, A. Franko, and J. Allalunis-Turner, “Variation in mitochondrial function in hypoxia-sensitive and hypoxia-tolerant human glioma cells,” British Journal of Cancer, vol. 86, pp. 619–624, 2002. View at Google Scholar
  136. A. Marusyk and K. Polyak, “Tumor heterogeneity: causes and consequences,” Biochimica et Biophysica Acta, vol. 1805, pp. 105–117, 2010. View at Google Scholar
  137. G. Bonuccelli, D. Whitaker-Menezes, R. Castello-Cros et al., “The reverse Warburg effect: glycolysis inhibitors prevent the tumor promoting effects of caveolin-1 deficient cancer associated fibroblasts,” Cell Cycle, vol. 9, no. 10, pp. 1960–1971, 2010. View at Publisher · View at Google Scholar · View at Scopus
  138. U. E. Martinez-Outschoorn, S. Pavlides, A. Howell et al., “Stromal-epithelial metabolic coupling in cancer: integrating autophagy and metabolism in the tumor microenvironment,” International Journal of Biochemistry and Cell Biology, vol. 43, no. 7, pp. 1045–1051, 2011. View at Publisher · View at Google Scholar · View at Scopus
  139. S. Pavlides, D. Whitaker-Menezes, R. Castello-Cros et al., “The reverse Warburg effect: aerobic glycolysis in cancer associated fibroblasts and the tumor stroma,” Cell Cycle, vol. 8, no. 23, pp. 3984–4001, 2009. View at Publisher · View at Google Scholar · View at Scopus
  140. M. M. Chaumeil, P. E. Z. Larson, S. M. Woods et al., “Hyperpolarized [1–13C] glutamate: a metabolic imaging biomarker of IDH1 mutational status in glioma,” Cancer Research, vol. 74, no. 16, pp. 4247–4257, 2014. View at Publisher · View at Google Scholar · View at Scopus
  141. P. Cheng, K. Wang, I. Waghmare et al., “FOXD1-ALDH1A3 signaling is a determinant for the self-renewal and tumorigenicity of mesenchymal glioma stem cells,” Cancer Research, vol. 76, pp. 7219–7230, 2016. View at Google Scholar
  142. G. Marziali, M. Signore, M. Buccarelli et al., “Metabolic/Proteomic signature defines two glioblastoma subtypes with different clinical outcome,” Scientific Reports, vol. 6, Article ID 21557, 2016. View at Publisher · View at Google Scholar · View at Scopus
  143. I. Marin-Valencia, C. Yang, T. Mashimo et al., “Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse human glioblastomas in the mouse brain in vivo,” Cell Metab, vol. 15, pp. 827–837, 2012. View at Google Scholar
  144. M. Janiszewska, M. L. Suvà, N. Riggi et al., “Imp2 controls oxidative phosphorylation and is crucial for preservin glioblastoma cancer stem cells,” Genes and Development, vol. 26, no. 17, pp. 1926–1944, 2012. View at Publisher · View at Google Scholar · View at Scopus
  145. N. J. Abbott, “Blood-brain barrier structure and function and the challenges for CNS drug delivery,” Journal of Inherited Metabolic Disease, vol. 36, no. 3, pp. 437–449, 2013. View at Publisher · View at Google Scholar · View at Scopus
  146. X. Feng, F. Szulzewsky, A. Yerevanian et al., “Loss of CX3CR1 increases accumulation of inflammatory monocytes and promotes gliomagenesis,” Oncotarget, vol. 6, no. 17, pp. 15077–15094, 2015. View at Publisher · View at Google Scholar · View at Scopus
  147. J. Liang, Y. Piao, L. Holmes et al., “Neutrophils promote the malignant glioma phenotype through S100A4,” Clinical Cancer Research, vol. 20, no. 1, pp. 187–198, 2014. View at Publisher · View at Google Scholar · View at Scopus
  148. G. Kohanbash and H. Okada, “Myeloid-derived suppressor cells (MDSCs) in gliomas and glioma-development,” Immunological Investigations, vol. 41, pp. 658–679, 2012. View at Google Scholar
  149. B. Otvos, D. J. Silver, E. E. Mulkearns-Hubert et al., “Cancer stem cell-secreted macrophage migration inhibitory factor stimulates myeloid derived suppressor cell function and facilitates glioblastoma immune evasion,” Stem Cells, vol. 34, no. 8, pp. 2026–2039, 2016. View at Publisher · View at Google Scholar · View at Scopus
  150. B. Badie and J. M. Schartner, “Flow cytometric characterization of tumor-associated macrophages in experimental gliomas,” Neurosurgery, vol. 46, pp. 957–961, 2000. View at Google Scholar
  151. H. Kettenmann, U. K. Hanisch, M. Noda, and A. Verkhratsky, “Physiology of microglia,” Physiological Reviews, vol. 91, pp. 461–553, 2011. View at Google Scholar
  152. K. Gabrusiewicz, B. Rodriguez, J. Wei et al., “Glioblastoma-infiltrated innate immune cells resemble M0 macrophage phenotype,” JCI Insight, vol. 1, 2016. View at Google Scholar
  153. D. Hambardzumyan, D. H. Gutmann, and H. Kettenmann, “The role of microglia and macrophages in glioma maintenance and progression,” Nature Neuroscience, vol. 19, pp. 20–27, 2016. View at Google Scholar
  154. L. Yi, H. Xiao, M. Xu et al., “Glioma-initiating cells: a predominant role in microglia/macrophages tropism to glioma,” Journal of Neuroimmunology, vol. 232, no. 1-2, pp. 75–82, 2011. View at Publisher · View at Google Scholar · View at Scopus
  155. Y. Komohara, K. Ohnishi, J. Kuratsu, and M. Takeya, “Possible involvement of the M2 anti-inflammatory macrophage phenotype in growth of human gliomas,” Journal of Pathology, vol. 216, pp. 15–24, 2008. View at Publisher · View at Google Scholar · View at Scopus
  156. F. O. Martinez, A. Sica, A. Mantovani, and M. Locati, “Macrophage activation and polarization,” Frontiers in Bioscience, vol. 13, pp. 453–461, 2008. View at Publisher · View at Google Scholar
  157. A. Mantovani, S. Sozzani, M. Locati, P. Allavena, and A. Sica, “Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes,” Trends in Immunology, vol. 23, pp. 549–555, 2002. View at Google Scholar
  158. B. C. Kennedy, C. R. Showers, D. E. Anderson et al., “Tumor-associated macrophages in glioma: friend or foe?” Journal of Oncology, vol. 2013, Article ID 486912, 11 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  159. W. Jia, C. Jackson-Cook, and M. R. Graf, “Tumor-infiltrating, myeloid-derived suppressor cells inhibit T cell activity by nitric oxide production in an intracranial rat glioma + vaccination model,” Journal of Neuroimmunology, vol. 223, pp. 20–30, 2010. View at Google Scholar
  160. W. Zhou, S. Q. Ke, Z. Huang et al., “Periostin secreted by glioblastoma stem cells recruits M2 tumour-associated macrophages and promotes malignant growth,” Nature Cell Biology, vol. 17, no. 2, pp. 170–182, 2015. View at Publisher · View at Google Scholar · View at Scopus
  161. E. Tartour, H. Pere, B. Maillere et al., “Angiogenesis and immunity: a bidirectional link potentially relevant for the monitoring of antiangiogenic therapy and the development of novel therapeutic combination with immunotherapy,” Cancer and Metastasis Reviews, vol. 30, no. 1, pp. 83–95, 2011. View at Publisher · View at Google Scholar · View at Scopus
  162. J. M. Weiss, L. A. Ridnour, T. Back et al., “Macrophage-dependent nitric oxide expression regulates tumor cell detachment and metastasis after IL-2/anti-CD40 immunotherapy,” The Journal of Experimental Medicine, vol. 207, no. 11, pp. 2455–2467, 2010. View at Publisher · View at Google Scholar · View at Scopus
  163. R. Albulescu, E. Codrici, I. D. Popescu et al., “Cytokine patterns in brain tumour progression,” Mediators of Inflammation, vol. 2013, Article ID 979748, 7 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  164. A. Wu, J. Wei, L.-Y. Kong et al., “Glioma cancer stem cells induce immunosuppressive macrophages/microglia,” Neuro-Oncology, vol. 12, no. 11, pp. 1113–1125, 2010. View at Publisher · View at Google Scholar · View at Scopus
  165. F. Hu, M.-C. Ku, D. Markovic et al., “Glioma-associated microglial MMP9 expression is upregulated by TLR2 signaling and sensitive to minocycline,” International Journal of Cancer, vol. 135, no. 11, pp. 2569–2578, 2014. View at Publisher · View at Google Scholar · View at Scopus
  166. D. S. Markovic, R. Glass, M. Synowitz, N. Rooijen, and H. Kettenmann, “Microglia stimulate the invasiveness of glioma cells by increasing the activity of metalloprotease-2,” Journal of Neuropathology and Experimental Neurology, vol. 64, pp. 754–762, 2005. View at Google Scholar
  167. D. S. Markovic, K. Vinnakota, S. Chirasani et al., “Gliomas induce and exploit microglial MT1-MMP expression for tumor expansion,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 30, pp. 12530–12535, 2009. View at Publisher · View at Google Scholar · View at Scopus
  168. N. A. Charles, E. C. Holland, R. Gilbertson, R. Glass, and H. Kettenmann, “The brain tumor microenvironment,” Glia, vol. 60, pp. 502–514, 2012. View at Google Scholar
  169. R. Domenis, D. Cesselli, B. Toffoletto et al., “Systemic T cells immunosuppression of glioma stem cell-derived exosomes is mediated by monocytic myeloid-derived suppressor cells,” PLoS ONE, vol. 12, Article ID e0169932, 2017. View at Google Scholar
  170. P. C. Rodriguez and A. C. Ochoa, “Arginine regulation by myeloid derived suppressor cells and tolerance in cancer: mechanisms and therapeutic perspectives,” Immunological Reviews, vol. 222, pp. 180–191, 2008. View at Google Scholar
  171. J. R. Engler, A. E. Robinson, I. Smirnov et al., “Increased microglia/macrophage gene expression in a subset of adult and pediatric astrocytomas,” PLoS ONE, vol. 7, no. 8, Article ID e43339, 2012. View at Publisher · View at Google Scholar · View at Scopus
  172. T. Doucette, G. Rao, and A. Rao, “Immune heterogeneity of glioblastoma subtypes: extrapolation from the cancer genome atlas,” Cancer Immunology Research, vol. 1, no. 2, pp. 112–122, 2013. View at Publisher · View at Google Scholar · View at Scopus
  173. A. Pietras, A. M. Katz, E. J. Ekström et al., “Osteopontin-CD44 signaling in the glioma perivascular niche enhances cancer stem cell phenotypes and promotes aggressive tumor growth,” Cell Stem Cell, vol. 14, no. 3, pp. 357–369, 2014. View at Publisher · View at Google Scholar · View at Scopus
  174. F. Szulzewsky, A. Pelz, X. Feng et al., “Glioma-associated microglia/macrophages display an expression profile different from M1 and M2 polarization and highly express Gpnmb and Spp1,” PLoS ONE, vol. 10, no. 2, Article ID 0116644, 2015. View at Publisher · View at Google Scholar · View at Scopus
  175. K. P. Bhat, K. L. Salazar, V. Balasubramaniyan et al., “The transcriptional coactivator TAZ regulates mesenchymal differentiation in malignant glioma,” Genes & Development, vol. 25, pp. 2594–2609, 2011. View at Google Scholar
  176. I. Nakano, “Stem cell signature in glioblastoma: therapeutic development for a moving target,” Journal of Neurosurgery, vol. 122, no. 2, pp. 324–330, 2015. View at Publisher · View at Google Scholar · View at Scopus