Next Article in Journal
Distinct Redox Profiles of Selected Human Prostate Carcinoma Cell Lines: Implications for Rational Design of Redox Therapy
Previous Article in Journal
An Evidence-Based Approach to the Use of Predictive Biomarkers in the Treatment of Non- Small Cell Lung Cancer (NSCLC)
Previous Article in Special Issue
Therapeutic Approaches to Target Cancer Stem Cells
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Epigenetics, Nervous System Tumors, and Cancer Stem Cells

1
Rosyln and Leslie Goldstein Laboratory for Stem Cell Biology and Regenerative Medicine, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA,
2
Institute for Brain Disorders and Neural Regeneration, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA
3
Department of Neurology, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA
4
Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA
5
Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA
6
Rose F. Kennedy Center for Research on Intellectual and Developmental Disabilities, Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA
*
Author to whom correspondence should be addressed.
Cancers 2011, 3(3), 3525-3556; https://doi.org/10.3390/cancers3033525
Submission received: 9 June 2011 / Revised: 1 August 2011 / Accepted: 8 September 2011 / Published: 13 September 2011
(This article belongs to the Special Issue Cancer Stem Cells)

Abstract

: Recent advances have begun to elucidate how epigenetic regulatory mechanisms are responsible for establishing and maintaining cell identity during development and adult life and how the disruption of these processes is, not surprisingly, one of the hallmarks of cancer. In this review, we describe the major epigenetic mechanisms (i.e., DNA methylation, histone and chromatin modification, non-coding RNA deployment, RNA editing, and nuclear reorganization) and discuss the broad spectrum of epigenetic alterations that have been uncovered in pediatric and adult nervous system tumors. We also highlight emerging evidence that suggests epigenetic deregulation is a characteristic feature of so-called cancer stem cells (CSCs), which are thought to be present in a range of nervous system tumors and responsible for tumor maintenance, progression, treatment resistance, and recurrence. We believe that better understanding how epigenetic mechanisms operate in neural cells and identifying the etiologies and consequences of epigenetic deregulation in tumor cells and CSCs, in particular, are likely to promote the development of enhanced molecular diagnostics and more targeted and effective therapeutic agents for treating recalcitrant nervous system tumors.

1. Introduction

Epigenetic mechanisms are deployed in response to complex profiles of cell-extrinsic, cell-cell, and cell-intrinsic signals and are responsible for the establishment, maintenance, and refinement of cell identity and function that occurs during development and adult life [1]. Indeed, an increasing number of studies has begun to elucidate how DNA methylation, histone and chromatin modification, non-coding RNAs (ncRNAs), RNA editing, and nuclear reorganization (Table 1) orchestrate stem cell self-renewal and maintenance, lineage restriction, lineage commitment, cell fate specification, progressive stages of maturation, and terminal differentiation. These regulatory mechanisms seem to promote the formation of relatively “open” and “poised” epigenetic states permissive for transcriptional activity that are associated with multi-lineage potential in stem and progenitor cells and to mediate the execution of lineage-specific gene expression programs, including the silencing of genes associated with alternate cell fates, in more mature cellular species.

Not surprisingly, epigenetic deregulation seems to be one of the hallmarks of cellular transformation, and our emerging understanding of the roles played by epigenetic factors in cancer biology has led to a number of recent advances in clinical oncology [2]. For example, diagnostic and prognostic tests that detect mutations in epigenetic factors and disease-associated variations in DNA methylation and ncRNA expression profiles have reached the marketplace, and drugs that target DNA methylation and histone modification pathways have been approved by the Food and Drug Administration for selected indications. A broad range of related, as well as novel, epigenetic diagnostic and treatment strategies are also being developed very actively and are expected to revolutionize cancer care.

In this review, we briefly describe the major epigenetic mechanisms and highlight their specific roles in regulating neural cell identity and function. We also illustrate how epigenetic deregulation, and the corresponding loss of normal neural cell identity and function, seems be a cardinal feature of pediatric and adult nervous system tumors including glioblastoma multiforme (GBM), medulloblastoma and neuroblastoma—which are amongst the most challenging cancers to treat because they exhibit considerable resistance to standard therapies and high recurrence rates. The cancer stem cell (CSC) hypothesis proposes that tumor maintenance, progression, treatment resistance, and recurrence are principally driven by a small population of stem–like cells present within a tumor. As such, we also draw attention to emerging evidence of epigenetic deregulation in tumor initiating and propagating cells derived from nervous system tumors—cells that are functionally defined as CSCs. Further, we consider the potential impact of epigenetic processes in promoting the establishment and maintenance of the CSC state, including the mediation of the bidirectional communications that exist between CSCs and the tumor microenvironment.

2. Epigenetic Mechanisms and Their Roles in Establishing and Maintaining Neural Cell Identity

2.1. DNA Methylation

DNA methylation refers to methylation of cytosine residues in genomic DNA, which leads to the formation 5-methycytosine (5mC) [1]. This covalently modified nucleotide is found prominently in gene regulatory regions (e.g., promoter elements) and in other regions (e.g., inter- and intra-genic sequences and repetitive elements). Members of the DNA methyltransferase (DNMT) family of enzymes are responsible for promoting de novo methylation and for maintaining methylation. Factors implicated in DNA demethylation have more recently been identified and include DNA excision repair, cytidine deaminase, and Gadd45 proteins. Methyl-CpG-binding domain (MBD) proteins bind specifically to methylated DNA and recruit additional regulatory factors to these loci. This DNA methylation machinery and the corresponding profiles of DNA methylation are dynamically regulated during development, adult life, and aging in a tissue- and cell type-specific manner that is environmentally sensitive (and activity-dependent in the nervous system). DNA methylation is, in concert with other epigenetic mechanisms, involved in mediating a broad range of cellular processes including transcriptional repression (and rarely activation) at individual gene loci and more globally; X chromosome inactivation (XCI) and genomic imprinting; and maintenance of genomic integrity.

DNA methylation plays a role in establishing and maintaining neural cell identity [1]. For example, one recent study showed that in a cellular differentiation paradigm progressing from embryonic stem cells (ESCs) to lineage-committed neural progenitor cells (NPCs), hundreds of promoter regions are methylated in NPCs, including those associated with pluripotency and germline-specific genes, suggesting that DNA methylation is responsible for silencing these genes and promoting neural lineage commitment [3]. Another study showed that, in postnatal neural stem cells (NSCs), DNMT3A methylates intergenic regions and gene bodies flanking proximal promoters regions of a large number of genes, including many regulators of neurogenesis, DNMT3A-dependent non-proximal promoter methylation promotes the expression of these neurogenic genes, and DNMT3A is required for neurogenesis [4]. These observations suggest that DNA methylation mediates neural lineage elaboration by silencing genes associated with pluripotency and activating neuronal lineage-specific genes.

Another modified cytosine residue, 5-hydroxymethylcytosine (5hmC) is also implicated in the epigenetic regulation of cell identity, though its functional roles are not as well understood. 5hmC is likely generated by the oxidation of 5mC, which is catalyzed by the Ten-Eleven Translocation (TET) family of enzymes that are highly expressed in ESCs [5,6]. Mechanistically, 5hmC inhibits the binding of MBD proteins to DNA implying that its role may, in part, be to counterbalance that of 5mC [7,8]. In fact, recent analyses of 5hmC (and TET proteins) in ESCs and induced pluripotent cells suggest that 5hmC is associated with actively transcribed genes in pluripotent cells and, further, that the balance between 5hmC and 5mC levels is important for regulating the switch from a pluripotent to a lineage committed cellular species [6,9,10]. Additional studies have found that 5hmC is widely distributed in brain and is particularly abundant in regions involved in higher cognitive functions, such as the cortex and hippocampus [11-13]. Interestingly, characterizing the distribution of 5hmC in DNA from human brain frontal lobe tissue reveals that 5hmC is selectively targeted to promoter elements and gene bodies rather than intergenic regions and, further, that genes associated with these regions are significantly enriched for those involved in neural development and patterning [13]. These findings suggest that the cell-type specific regulation of this epigenetic modification, like that of 5mC, also plays a role in the establishment and maintenance of neural cell identity.

2.2. Histone and Chromatin Modifications

Chromatin refers to the packaging of genomic DNA, along with histone and non-histone proteins and associated factors, within the cell nucleus [1]. The nucleosome is the most essential unit of chromatin. It is formed by 147 base pairs of DNA wrapped around an octamer comprised of two of each of the classical histone proteins (i.e., H2A, H2B, H3, H4) and by linker DNA and histones (i.e., H1). A series of nucleosomes forms the characteristic “beads-on-a-string” configuration that can, in turn, fold into secondary and tertiary structures representing varying degrees of condensation. For example, higher order chromatin conformations include loosely packaged euchromatin and more densely packaged heterochromatin. Chromatin states can be modulated at multiple levels within this hierarchy. Classical histone proteins can be replaced by variant histones (e.g., H2A.Z), with distinct properties. Specific classes of enzymes are responsible for regulating reversible histone post-translational modification levels including acetylation (i.e., histone acetylases and deacetylases [HATs and HDACs]) as well as methylation, phosphorylation, SUMOylation, ADP-ribosylation and others. Additional enzymes and macromolecular complexes promote nucleosome and higher order chromatin (e.g., Polycomb Group [PcG] and Trithorax Group [TrxG] proteins) remodeling. Histone-, nucleosome-, and higher order chromatin-modifying enzymes may act alone; or, because strata within this chromatin hierarchy are interconnected, these factors may be integrated into highly modular complexes, such as the REST and the functionally related CoREST epigenetic regulatory complexes. Rearrangement of chromatin is responsible for the establishment of more or less compacted configurations that play dynamic regulatory, structural, and other functional roles within the cell. These effects can include modulating interactions between DNA sequences with each other and with diverse nuclear factors including ncRNAs, DNA binding proteins, transcriptional co-regulators, transcription factors, and additional nuclear machineries, such as those involved in mediating the processes of transcription and DNA replication and repair. Like DNA methylation, histone and chromatin modifications are involved in mediating a broad range of cellular processes including transcriptional repression and activation at individual gene loci and more globally; XCI and genomic imprinting; and maintenance of genomic integrity. Histone and chromatin modifying factors and the corresponding profiles of chromatin modifications are, like DNA methylation, dynamically regulated during development, adult life, and aging in a tissue- and cell type-specific manner that is environmentally sensitive.

Histone modifications and chromatin remodeling play a role in establishing and maintaining neural cell identity (reviewed in [14,15]). For example, we recently demonstrated that developmental stage-specific deployment of REST and CoREST complexes is responsible for controlling NSC-mediated neural lineage elaboration including neuronal and glial subtype specification, progressive maturation, and terminal differentiation (i.e., oligodendrocyte [OL] myelination) through dynamic and context-specific activation and repression of cell type- and maturational stage-specific gene networks [16-18]. Similarly, recent studies have shown that the histone demethylase, LSD1, regulates the proliferation of NSCs [19]; the TrxG protein, Mll1, is essential for postnatal NSC-mediated neurogenesis [5]; and, PcG proteins play a role in the temporal regulation of NPC fate by modulating neuronal to glial fate switching [20]. Moreover, another study profiled PcG-mediated histone H3 lysine (K) 27 trimethylation (H3K27me3) in ESCs, lineage committed NPCs, and terminally differentiated neurons and found dynamic changes in these marks in promoter regions of many genes including, specifically, loss of H3K27me3 from neuron-specific genes activated upon terminal differentiation in the transition from NPCs to terminally differentiated neurons [3]. Interestingly, this study also reported that promoter regions with H3K27me3 in stem cells are often associated with DNA methylation events during differentiation, highlighting how these developmental processes are likely coordinated by crosstalk between different epigenetic regulatory mechanisms.

2.3. Non-Coding RNAs

The great majority of human genomic DNA does not code for protein; non-coding sequences are nevertheless transcribed, forming various classes of ncRNAs. These ncRNAs are more abundant than protein-coding RNAs in human cells [21]. Certain classes of ncRNAs, such as transfer RNAs and ribosomal RNAs, are well known. Other classes of ncRNAs have more recently been recognized and novel classes are being identified at a rapid pace. These include short ncRNAs such as endogenous short-interfering RNAs (siRNAs), microRNAs (miRNAs), PIWI-interacting RNAs and small nucleolar RNAs (snoRNAs), and long ncRNAs (lncRNAs) such as long intergenic ncRNAs (lincRNAs). NcRNAs have expression profiles that are cell-, tissue-, and developmental stage-specific (and activity-dependent in the nervous system) [22]. NcRNAs have diverse regulatory, structural, and other operative roles, including many that are still emerging [23]. Known molecular functions for ncRNAs include mediating and/or modulating aspects of DNA methylation, chromatin modification, transcription, and RNA post-transcriptional processing, transport, and translation [24].

MiRNAs, the best-characterized class of ncRNAs, regulate target messenger RNAs (mRNAs) through post-transcriptional mechanisms [25]. Individual miRNAs have the potential to modulate hundreds of complementary mRNA molecules through complete or partial sequence-specific interactions. Single-stranded miRNA molecules bind to mRNAs primarily in 3′ untranslated regions (UTRs) as well as in certain coding regions and 5′ UTRs, preventing the translation of these mRNAs or sequestering them for storage or degradation via the RNA-induced silencing complex. Conversely, a single mRNA may be the target of multiple distinct miRNAs.

The functions of lncRNAs, the most abundant class of ncRNAs, are not as well understood. Only a few lncRNAs have been studied in detail, such as the X inactivation-specific transcript, which mediates X chromosome inactivation. More recently, however, lncRNA biogenesis and function have been examined more systematically. LncRNAs are defined as transcripts longer than 200 nucleotides that can be, but are not necessarily, 5′ capped, polyadenylated, and spliced like mRNAs [26-29]. Some lncRNAs are derived from intergenic regions, whereas others are transcribed in antisense, bi-directional, or overlapping orientations relative to protein-coding genes—genes that may be specifically regulated by their associated lncRNAs. LncRNAs can form a range of functional secondary structures, including particular protein interaction domains [30-32]. LncRNAs can be cleaved into shorter ncRNAs (e.g., siRNAs, snoRNAs and miRNAs) [33]. Thus, lncRNAs represent highly versatile molecules. Correspondingly, these factors have a broad spectrum of functions, including the ability to recruit transcriptional and epigenetic (e.g., chromatin remodeling complexes) regulatory factors to specific genomic sites, to form of nuclear subdomains (e.g., paraspeckles), to mediate nuclear-cytoplasmic transport of proteins, and to control translation (e.g., local protein synthesis in synaptic compartments) [34,35]. Moreover, lncRNAs are implicated in mediating a wide range of normal and pathological processes, from development, plasticity, and homeostasis to cancer metastasis [36].

Many studies have begun to elucidate the expression and function of miRNAs in NSC self-renewal, maintenance and lineage restriction, neuronal and glial lineage commitment, neuronal and glial subtype specification, progressive maturation, and plasticity [37]. For example, one important study showed that miR-124, the most abundant miRNA in the central nervous system (CNS), regulates the progression of NSCs into neurons [38]. Specifically, in NSCs, knocking down miR-124 derepresses its target, Sox9, and results in disruption of neuronal lineage elaboration with arrest in the proliferative precursor state. Two recent studies demonstrated that miRNAs also regulate OL development [39,40]. Both studies showed that eliminating the presence of mature miRNAs via targeted disruption of the miRNA biogenesis factor, Dicer1, leads to profound impairments in the progressive maturation of specified OL lineage species. Further, the introduction of specific miRNAs (e.g., miR-219 and miR-338) rescues the abnormal OL developmental phenotypes by modulating the expression of proteins with important roles in regulating the fidelity of OL maturation.

In addition, we, and others, have shown that lncRNAs play a role in establishing and maintaining neural cell identity. For example, one key study showed that lncRNAs are specifically expressed in the developing brain and preferentially associated with protein-coding genes expressed in the brain or involved in transcriptional regulation of CNS development. Moreover, we found 169 lncRNAs that are significantly differentially expressed during neuronal-glial fate specification and OL lineage maturation including those associated with key neural developmental genes, such as AK053922, a lncRNA transcribed from the Gli3 locus, and Sox8OT, a lncRNA transcribed from the Sox8 locus [41]. Others have similarly identified lncRNAs with roles in OL lineage elaboration including Nkx2.2AS, which is transcribed in an antisense orientation relative to Nkx2.2 [42]. Another study found more than 1,000 lincRNAs in various cell types, including neural precursor cells and identified a “brain cluster” of lncRNAs associated with hippocampal development, OL maturation, and GABAergic neuronal function [43].

Intriguingly, REST and CoREST regulate the expression levels of particular ncRNAs (i.e., miRNAs and lncRNAs) [32]. In turn, specific ncRNAs can modulate the expression levels of REST and CoREST [32]. Moreover, lncRNAs are implicated in mediating the function of these and other chromatin remodeling complexes, by recruiting them to their genomic sites of actions. These observations, once again, highlight the complex crosstalk that occurs between different epigenetic regulatory mechanisms that modulate neural cell fate decisions.

2.4. RNA Editing

Editing is a key mechanism for generating diversity in the information content of ncRNA molecules (as well as protein-coding RNAs and even DNA) [44,45]. RNA editing refers to nucleoside modifications, including adenosine-to-inosine (A-to-I) and cytidine-to-uridine (C-to-U) deaminations in RNA molecules, catalyzed by the adenosine deaminase that act on RNA (ADAR) and the apolipoprotein B editing catalytic subunit (APOBEC) families of enzymes, respectively. ADARs are differentially expressed during development with ADAR1 and 2 preferentially found in the CNS and ADAR3 restricted to brain [46,47]. The targets of A-to-I RNA editing were initially thought to encompass protein-coding transcripts, particularly those involved in the establishment and maintenance of neuronal cell identity and synaptic transmission such as voltage-gated ion channels, ligand-gated receptors, and signal transduction molecules [44,48]. More recent studies have recognized that A-to-I RNA editing occurs primarily in ncRNA transcripts derived from Alu elements and in UTRs of protein-coding transcripts [49-52] and that these editing events occur at significant levels within the human brain [53].

RNA editing plays a role in establishing and maintaining neural cell identity. For example, one study showed that human ESC differentiation is generally associated with an ADAR1-mediated global decrease in the editing levels of Alu elements, and these changes are particularly significant during neural lineage restriction [54]. Further, knocking down ADAR1 in ESCs leads to the deregulation of various genes including, particularly, those that are involved in neuronal development. Another recent study found that, as human NPCs differentiate into neuronal and glial lineages, the levels of ADAR2 and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor GluR2 subunit pre-mRNA editing increase [55]. This change in editing levels is associated with a transition from AMPA receptor calcium-permeability in NPCs to impermeability in more mature cells. In turn, overexpression of ADAR2 impairs NPC differentiation.

2.5. Nuclear Organization

Nuclear organization refers to the three dimensional arrangement of the genome, from entire chromosomes to individual gene loci, within the context of the nuclear envelope and matrix and other factors. The execution of cellular programs including DNA replication and repair, gene transcription, and RNA post-transcriptional processing and transport is associated with dynamic nuclear reorganization such as the formation and disassembly of functional nuclear domains [1,24,56-60]. The genome can undergo controlled local and long-range movements, more global reorganization, as well as other shifts (e.g., chromatin states) that have functional consequences for nuclear processes. Further, the nucleus contains a number of specialized sub-organelles comprised of particular proteins and RNA species, including some whose roles have been characterized and others that are less well understood. These heterogeneous nuclear domains can dynamically assemble and associate with specific genomic loci, interact with chromatin, move, and undergo other changes. These three-dimensional features of nuclear structure and function do not arise randomly. Rather, they are associated with particular physiological cues and cellular processes, such as cell-cycle progression and differentiation. Although the regulation and function of many nuclear features has not yet been elucidated, recent advances have highlighted the interconnected nature of nuclear organization and dynamics with epigenetic regulation, in general and in the CNS [61], both in health and in disease [62].

Nuclear reorganization plays a role in establishing and maintaining neural cell identity. For example, one important study showed how the expression of Mash1, a pro-neural gene, is mediated by the repositioning of the Mash1 locus from the nuclear periphery to the interior of the nucleus, which occurs during neural lineage commitment of ESCs [63]. At the nuclear periphery, the Mash1 locus is associated with profiles of histone modifications indicative of transcriptional repression, whereas in the interior of the nucleus, it is associated with profiles of histone modifications linked to transcriptional activation. By contrast, another study demonstrated that the expression of PLP, a myelin gene, is up regulated during progressive stages of OL lineage maturation, while the PLP locus remains at the nuclear periphery [64]. Interestingly, the increased transcription of PLP is associated with the local assembly of SC35 domains (a.k.a., nuclear speckles) proximal to the PLP gene locus. These nuclear domains are enriched in NEAT1/2, lncRNAs that we showed are upregulated during the progressive maturation of OLs [28], and are implicated in modulating transcription and RNA processing. Other ncRNAs have been linked unequivocally to gene regulation, nuclear organization, and OL development. The miRNA, miR-23, negatively regulates the expression of lamin B1 (LMNB1), a nuclear lamina protein with diverse roles in epigenetic phenomena including chromatin formation and euchromatin and heterochromatin transitions. The LMN1B gene is duplicated in adult-onset autosomal dominant leukodystrophy resulting in increased levels of LMNB1 that lead to defects in OL maturation and myelination accompanied by abnormalities of the nuclear envelope and myelin gene expression and localization [65,66].

3. Epigenetic Mechanisms and Their Roles in Cancer

3.1. Epigenetic Deregulation in Cancer

Along with inherited and acquired genetic abnormalities, epigenetic mechanisms are also implicated in promoting cellular transformation via mechanisms that include silencing tumor suppressor genes and activating oncogenes; deregulation of genes involved in cell growth and proliferation, stress responses, and survival and apoptosis; loss of genomic imprinting, derepression of parasitic repetitive elements, and producing genomic instability.

Indeed, epigenetic profiling in cancer has revealed a spectrum of abnormalities. Cancer cells exhibit changes in normal patterns of DNA methylation including global hypomethylation in intergenic and heterochromatic regions, which may lead to genomic instability, reactivation of transposable elements, and loss of imprinting, and local changes in regulatory regions that can modulate specific genes, including the repression of tumor suppressor genes and the activation of oncogenes. Further, hypermethylation may lead to long term gene silencing of tumor suppressor genes by promoting the establishment of “locked” repressive chromatin states. Cancer cells also exhibit abnormal profiles of histone, nucleosome, and chromatin regulation. Like changes in DNA methylation, these patterns can be deregulated globally or more locally. In fact, global H3K4me2 and H3K18ac patterns correlate with tumor phenotype and predict prognosis, treatment response, and outcome for different cancers [67-69]. By contrast, combinations of histone modifications at particular gene loci, such as repressive PcG-mediated H3K27me3 and H3K9me2 at tumor suppressor genes, are associated with deregulation of these specific genes [70]. Various cancers are further associated with mutations and other alterations in the expression and function of epigenetic factors including, for example, DNMTs, histone and chromatin modifying enzymes, as well as ncRNAs.

Cancer cells have deregulated miRNA expression profiles that are implicated in initiating and maintaining the abnormal cellular phenotype. These miRNAs target a broad range of mRNAs including those that control cell growth and proliferation, stress responses, and survival and apoptosis as well as those encoding factors involved in reading and writing the epigenetic modifications. Cancer cells also display changes in the methylation and chromatin states associated with miRNA genes. In turn, these abnormalities can lead to deregulation of miRNAs that act as tumor suppressor genes and oncogenes through effects on their target mRNAs and those that have more global effects on genomic stability [71]. Other ncRNAs, such as lncRNAs, may similarly have roles in the molecular mechanisms underlying cancer. For example, a number of lncRNAs are associated with the establishment of cell identity, including pluripotency [72-74] and fate restriction, lineage specification and maturation; with p53-mediated cell stress responses, survival, and apoptosis [75,76]; with genomic imprinting; XCI; and with cancer metastasis [36]. Cumulatively, these signatures highlight the emerging roles played by epigenetic deregulation in promoting the cancer phenotype.

3.2. Epigenetic Deregulation in Nervous System Tumors

3.2.1. Glioblastoma Multiforme and Other Gliomas

Recent studies have revealed that GBMs exhibit complex profiles of mutations in epigenetic factors and alterations in epigenetic regulation, including those which are potentially clinically relevant [77]. For example, in depth sequencing analyses of GBMs have found mutations in many genes that encode factors with roles in epigenetic regulation, including histone deacetylases, HDAC2 and HDAC9; histone demethylases, JMJD1A and JMJD1B; histone methyltransferases, SET7, SETD7, MLL, MLL4; and methyl-CpG binding domain protein, MBD1 [78]. In addition, GBMs display deregulation of epigenetic factors, including significant over expression of particular DNMTs (e.g., DNMT3B) associated with promoter hypomethylation and differential profiles of histone modifications (i.e., H3 and H4 acetylation and H3K4me2) [79]. Moreover, GBMs have down regulation of particular HDACs (e.g., class II and IV) [80] and increased copy numbers of the gene encoding BMI1, a PcG protein that regulates histone H3K27 methylation [81]. Further, the methylation status of the O (6)-methylguanine-DNA methyltransferase (MGMT) gene promoter is a biomarker for a GBM molecular subtype that predicts response to temozolomide and patient survival [82,83]. Interestingly, some studies profiling DNA methylation status of particular genes in GBMs and in other gliomas reveal preferential hypermethylation of specific loci in lower-grade tumors compared to higher-grade forms [84-86]. By contrast, a recent high throughput analysis demonstrated that DNA methylation remains largely stable during glioma evolution, implying that epigenetic deregulation is an early event during glioma pathogenesis [87]. These differing results provide evidence for the presence of heterogeneous epigenetic deregulation in these tumors. In fact, a detailed genomic and epigenomic evaluation of primary and secondary GBMs and other gliomas suggests that DNA methylation profiles correlate with the histology and genotype of these tumors (i.e., presence of IDH1 mutations) and can be utilized to distinguish between primary and secondary GBMs [87]. A number of studies have also identified an increasing array of miRNAs that are deregulated in GBMs. For example, a miRNA that acts as a tumor suppressor, miR-124a, is often down regulated in GBM promoting migration and invasion, and the degree of miR-124a down regulation correlates with shorter survival, clinically [88]. By contrast, a miRNA that acts as an oncogene (a.k.a., an oncomir), miR-21, is over expressed in GBMs, and its effects are mediated by targeting networks of tumor suppressors, including components of the p53, transforming growth factor-β, and mitochondrial apoptosis pathways [89]. Similarly, many other miRNAs are differentially expressed in GBMs and are implicated in modulating core regulatory pathways, such as those that mediate cell proliferation, apoptosis, cell cycle regulation, invasion, and angiogenesis [90]. Other ncRNAs, such as lncRNAs, may also play a role in GBMs. For example, anti-NOS2A is a lncRNA expressed in GBMs that is implicated in regulating the NOS2A gene [91]. In turn, NOS2A is induced in human brain tumors including GBMs and influences the efficacy of particular chemotherapeutic agents [92]. Many other genes with roles in GBMs, including oncogenes and tumor suppressor genes, are also associated with antisense lncRNAs that may regulate their related genes [93]. The expression of RNA editing enzymes and associated levels of RNA editing are also deregulated in GBMs. Specifically, ADAR1-3 are all down regulated in brain tumors, including GBM, and further, ADAR3 levels correlate with the grade of malignancy of the tumor, with a 99% decrease in ADAR3 levels found in GBMs [94]. Correspondingly, GBMs display significant global hypoediting in Alu element derived RNAs and gene-specific editing profiles in tumors [94]. For example, the AMPA receptor, GluR2, is hypoedited in GBM [95]. In addition, GBMs can also participate in intercellular epigenetic signaling. For example, tumor cells secrete exosomes (a.k.a., microvesicles) containing various ncRNAs (i.e., miRNAs), DNA sequences, and other factors reflective of the tumor state can be delivered to healthy recipient cells throughout the body [96]. A recent analysis of the contents of exosomes derived from GBMs has revealed the presence of high levels of retrotransposon-associated RNA sequences including Alu and HERV-H retrotransposon elements, suggesting that these factors may promote tumor progression and maintenance [97].

Like other gliomas, oligodendroglial tumors also exhibit complex profiles of epigenetic deregulation that are common and likely to be related to the development and prognosis of these tumors. For example, one study showed that 74% of tumors exhibited some degree of hypermethylation associated with gene loci previously linked to the pathogenesis of oligodendroglial tumors, as well as in candidate tumor suppressor genes not previously reported to be mutated in these tumors [98]. Notably, hypermethylation of MGMT was significantly correlated with loss of chromosome 19q and the combined loss of chromosomes 1p and 19q [98]. These epigenetic abnormalities can be present in low-grade tumors, suggesting that they are early events in the process of oligodendroglial cellular transformation [99]. Other studies have demonstrated that genes, such as the tumor suppressor, AJAP1, which are expressed at lower levels in oligodendrogliomas relative to normal brain tissues and associated with decreased survival, are often hypermethylated [100]. Interestingly, a recent report also demonstrated that the p53-dependent anti-apoptotic modulator PDAM, which is frequently deregulated in oligodendroglial tumors and involved in mediating chemosensitivity of these tumors, is not only subject to epigenetic regulation but also that it may itself function as a ncRNA [101].

3.2.2. Medulloblastoma

A recent analysis revealed that mutations in epigenetic factors promote the pathogenesis of medullublastomas including, specifically, the histone lysine methyltransferases, MLL2 and MLL3; histone lysine demethylase, KDM6B; and SWI/SNF family members, SMARCA4 and ARID1A [102]. A complementary study showed that amplifications and homozygous deletions in genes responsible for modulating levels of histone lysine methylation, particularly H3K9, are involved in pathogenesis of medulloblastoma. These include the histone lysine methyltransferases, EHMT1 and SMYD4; histone lysine demethylases, JMJD2C and JMJD2B; histone lysine acetyltransferase, MYST3; and PcG factors, L3MBTL2, L3MBTL3, and SCML2 [103]. REST is another important epigenetic factor often overexpressed in medulloblastomas and implicated in the formation of tumors in the mouse cerebellum, when it is overexpressed along with c-Myc [104-107]. REST may be associated with the pathogenesis of these tumors because it modulates NSC differentiation, is involved in the Wnt and Sonic hedgehog (Shh) developmental pathways, controls the expression and functions of epigenetic regulators, including many of those listed above, and is integrated into ncRNA regulatory networks [108].

A number of studies have identified miRNAs that are deregulated in medulloblastomas, including those that are upregulated and downregulated [109-111]. Particular miRNAs may be linked to molecular pathways previously implicated in the development of these tumors. For example, mature miRNAs derived from the miR-17-92 miRNA polycistronic cluster, which have previously been identified as oncomirs, are the most highly upregulated miRNAs in medulloblastomas—specifically the subset of these tumors associated with constitutive activation of Shh signaling [109,110]. Moreover, particular miRNA signatures can be combined with gene expression and copy number variation data to identify subtypes of medulloblastomas that have meaningful differences in clinical outcomes, such as higher and lower rates of event-free and overall survival [111].

Like GBMs, medulloblastomas can also participate in intercellular epigenetic signaling through the release of exosomes containing high levels of retrotransposon-associated DNA and RNA sequences including LINE1, Alu and HERV-K retrotransposon elements [97].

3.2.3. Neuroblastoma

Studies performed utilizing neuroblastomas and related cell lines have demonstrated the presence of distinct profiles of DNA methylation at particular genomic loci and suggested that these profiles can distinguish between molecular subtypes of tumors associated with different clinical outcomes. For example, a recent DNA methylation analysis of 33,485 discrete loci in neuroblastic tumors and associated copy number analysis identified extensive epigenetic and large-scale epigenomic alterations (preferentially localized to telomeric regions) correlated with patient survival [112]. A range of other studies have similarly identified genes, which are methylated and silenced in neuroblastoma in various patterns, including but not limited to the tumor suppressor genes, RASSF1A and ZMYND10 (a.k.a., BLU); the angiogenesis inhibitor, THBS1 [113]; the anti-apoptotic decoy receptors, DcR1 and DcR2 [114]; the extrinsic pathway associated caspase, CASP8 [115,116], various Shh pathway genes [117]; and other factors [118-120]. Hypermethylation of specific genes has been associated with certain clinical outcomes, such as relapse susceptibility (i.e., CASP8) and overall survival (i.e., TMS1 and APAF1) [121]. By contrast, lower levels of methylation associated with particular genes (i.e., SCNN1A, PRKCDBP and KRT19) are linked with more favorable outcomes [119]. Furthermore, while there can be a significant correlation between the methylation of certain genes (i.e., CASP8) and previously described predictive factors for neuroblastoma (i.e., MYCN amplification status) [122]; distinct methylation signatures, such as the so-called CpG island methylator phenotype (CIMP), can independently be associated with clinical prognosis regardless of these other factors [123-125]. Additionally, an initial analysis has also demonstrated the presence of differential profiles of histone modifications at the loci of some differentially methylated genes (i.e., THBS1) in neuroblastomas, highlighting the complexity of epigenetic processes that may be involved in these tumors.

Specific epigenetic regulatory factors may, themselves, be deregulated in neuroblastomas. For example, increased expression levels [126] and changes in the alternative splicing patterns [127,128] of REST are found in neuroblastomas. Neuroblastomas also exhibit alterations in the expression of various miRNAs including, for example, those that modulate molecular pathways involved in apoptosis, cell survival and proliferation [129-131]. One interesting study demonstrated that neuroblastomas have increased levels of miR-17-5p, which inhibits p21 and BCL2L11 (a.k.a., BIM) expression, and that p21 downregulation is significant in tumors with MYCN amplification and a poor clinical outcome [132]. This study also showed that treatment of MYCN-amplified and therapy-resistant neuroblastomas with an oligonucleotide designed to block the action of miR-17-5p, a miR-17-5p antagomir, abolishes the p21 and BIM upregulation, inhibits cell cycle progression and promotes apoptosis [132]. Another study found that miR-9, a miRNA with tumor suppressor activity, is downregulated in 50% of neuroblastomas [130]. Furthermore, increased levels of REST have been implicated in downregulating miR-9 expression in neuroblastoma cells [131].

3.2.4. Other Nervous System Tumors

An increasing number of studies are revealing that other primary nervous system tumors are similarly associated with epigenetic deregulation or mutations in epigenetic regulatory factors. One example is that of ependymomas, which exhibit abnormal profiles of DNA methylation at various genomic loci including RASSF1A [133,134]; CDKN2A/B and p14 ARF [135]; and MGMT, TIMP3, THBS1 and TP73 [136]. In contrast to these candidate gene studies, a recent analysis of genome-wide patterns of DNA methylation in ependymomas revealed both gain and loss of methylation associated with a range of genomic loci, including specifically Alu repeat elements and their flanking sequences [137]. Further, hypomethylation of Alu elements was characteristic of aggressive primary tumors and even more so for recurrent tumor subtypes, suggesting that Alu methylation status may be a valuable prognostic marker [137]. Another example, rhabdoid tumors are largely caused by deletions or mutations of SMARCB1 (a.k.a., INI1/SNF5/BAF47), a component of the chromatin remodeling SWI/SNF complex, which functions as a tumor suppressor by modulating the cell cycle and cooperating with p53 to prevent transformation [138].

4. The Cancer Stem Cell Hypothesis vis-à-vis Epigenetics

4.1. Cancer Stem Cells

In contrast to the canonical stochastic theory that attributes the molecular pathogenesis of cancer to clonal evolution, the hierarchical CSC hypothesis suggests that tumor maintenance, progression, treatment resistance, and recurrence are largely driven by cells with stem cell-like characteristics, including the capacity to undergo self-renewal and differentiate into the potentially heterogeneous subpopulations of cells present within a particular tumor. Studies on acute myeloid leukemia supplied preliminary data supporting the CSC hypothesis [139]. Subsequent studies have provided evidence for the existence of CSCs in a broad range of solid tumors including those that manifest in the CNS, such as gliomas, medulloblastomas, neuroblastomas, and ependymomas [140,141]. Cells derived from nervous system tumors are operationally defined as CSCs if they express certain cell surface markers (i.e., CD133, CD15/SSEA-1, L1CAM, A2B5, or integrin a6) and exhibit particular functional properties (i.e., the ability to initiate and propagate tumors in various assays). Our understanding of these so-called CSCs, their in situ interactions with the tumor microenvironment, and corresponding methodologies used to identify and study them ex vivo are still evolving. Furthermore, the relevance of the CSC model to specific cancers remains the subject of ongoing controversies [142], though stochastic and hierarchical models are not mutually exclusive [143,144].

4.2. Epigenetic Deregulation in Tumor Initiating and Propagating Cells Derived from Nervous System Tumors

Preliminary studies of tumor initiating and propagating cells, if not CSCs, derived from nervous system tumors have demonstrated that these cells are epigenetically deregulated. In fact, the PcG protein, BMI1, is highly enriched in GBM-derived CD133+ cells and is required for sustaining stem cell self-renewal. Further, examining GBMs and associated cell lines reveals that the CD133 gene, itself, is subject to regulation by DNA methylation, though, conspicuously, this only seems to be the case in the cancer state [145]. The methylation status of the CD133 gene promoter is generally inversely correlated with the expression of this cell surface marker in GBM-derived CD133+ and CD133- cell populations [145,146]. Also, the CASP8 gene promoter is hypermethylated in GBM-derived CD133+ cells, leading to low levels of CASP8 expression in these cells [147]. Notably, this protein is required for mediating the sensitivity of the tumor to the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL); and not surprisingly, these cells are resistant to TRAIL-induced cell death. The BMP receptor 1B gene, which typically inhibits proliferation and promotes NSC differentiation, is also epigenetically silenced in GBM-derived tumor initiating and propagating cells. It is subject to promoter hypermethylation and is also the target of the H3K27 histone methyltransferase, enhancer of zeste 2 (EZH2), a PcG protein [148]. In addition, comparative profiling of miRNAs reveals that many miRNAs are differentially expressed between GBM-derived CD133+ and CD133- cells [149]. Specifically, miRNAs that may have roles in promoting brain development and neural cellular differentiation, such as miR-451, miR-486 and miR-425 [149] and miR-29b, miR-125a and miR-149 [150], are upregulated in CD133- cells. Moreover, the introduction of miR-124 or miR-137 inhibits proliferation and induces differentiation in GBM-derived (and oligodendroglioma-derived) tumor initiating and propagating cells [151]. Neuroblastoma- and medulloblastoma-derived tumor initiating and propagating cells are also subject to epigenetic regulation, though, these processes are less well characterized than those operating in GBM-derived tumor initiating and propagating cells. For example, the CD133 gene is similarly subject to regulation by DNA methylation in neuroblastoma cell lines [152]. And, in medulloblastoma, the introduction of miR-199b-5p depletes the CD133+ population of cells and reduces the expression of genes linked to the stem cell state, such as HES1 [153].

Given the recognition of the increasingly roles of epigenetic mechanisms in mediating all aspects of neural cellular development, these observations suggest that epigenetic deregulation is a critical factor for determining tumor initiating and propagating cell functions.

4.3. Epigenetic Mechanisms and the Cancer Stem Cell State

By definition, CSCs have the ability to undergo self-renewal and to differentiate into potentially heterogeneous subpopulations of cells that comprise an individual tumor. CSCs are, thus, responsible for maintaining and propagating tumors. However, our understanding of the processes by which CSCs are generated and maintained in nervous system (and other) tumors that conform to the CSC model remains limited. Many studies have focused on identifying the cells of origin—cells that acquire genetic or other lesions and are truly responsible for initiating nervous system tumors in situ [154]. Indeed, it has been shown that GBMs, medulloblastomas, neuroblastomas, and other nervous system tumors can arise from cells of origin including neural stem and progenitor cells that escape from normal proliferation and differentiation programs and even from more mature cell types that undergo de-differentiation. For example, both NSCs or cerebellar granule neuronal precursor cells can form medulloblastomas [155], and mature macroglial cells, such as astrocytes, can form gliomas. These cells of origin are distinct from CSCs, but they may be closely related to and are either directly of indirectly responsible for generating CSCs [154]. Because epigenetic mechanisms are implicated in mediating neural cell identity and function and also because they are deregulated in cancer generally and in populations of tumor initiating and propagating cells derived from nervous system tumors, epigenetic deregulation is likely to be a very important pathogenic mechanism in the cancer cell of origin and in the establishment and maintenance of the CSC state [156].

Indeed, emerging evidence has demonstrated that epigenetic mechanisms play roles in mediating all of the major acquired abilities that are the hallmarks of cancer and the characteristics that enable them (recently reviewed by Hanahan and Weinberg [157]). These properties include the capacity to sustain proliferative signaling, evade growth suppressors, resist cell death, achieve replicative immortality, induce angiogenesis, activate invasion and metastasis, reprogram energy metabolism and evade immune destruction and are underpinned by genome instability and inflammation and through bidirectional interactions with the tumor microenvironment. Here we provide leading examples of how diverse epigenetic mechanisms are involved in the molecular circuitry underlying all of these pathological processes. Proliferative signaling pathways include those that are mediated by growth factors and related developmental cues. REST, an epigenetic regulatory factor deregulated in nervous system tumors, modulates Shh signaling [158], and in turn, the activity of REST is modulated by the Wnt signaling pathway [159,160]. Growth suppressors, such as the pRb and p53 tumor suppressors, themselves, participate in epigenetic pathways. For example, the mechanism of action of pRb includes modulation of local and more global chromatin environments by recruitment of enzymes that modify histones, remodel nucleosomes, and promote the formation of heterochromatin [161]. Similarly, p53 binds to its response element, where it recruits coregulatory factors such as histone modifying enzymes, chromatin remodeling factors, and subunits of the mediator complex. This stimulus-specific p53 activity is also important for sensing cell stress and promoting apoptosis. Replicative immortality is mediated by telomeres, which are, by definition, chromosomal structures. The organization of telomeric chromatin influences telomere maintenance, and telomere dysfunction affects telomeric and subtelomeric chromatin formation and activates alternative telomere maintenance mechanisms [162]. Further, treatment of nervous system tumor cells with HDAC inhibitors has been shown to have antiproliferative and proapoptotic effects, mediated by alterations in chromatin at the telomerase reverse transcriptase (TERT) promoter [163]. Moreover, telomeres are transcribed into ncRNAs, telomere repeat-containing RNA (TERRA), that may have roles in modulating telomeric heterochromatin formation, the accessibility of telomeres to DNA repair mechanisms, and the activity of telomerase [164]. Angiogenesis is regulated by the actions of various pro- and anti-angiogenic factors including many, such as VEGF, with expression levels that are modulated by DNA methylation, histone modifications, and microRNAs [165]. In turn, VEGF influences expression of the PcG protein, EZH2, in the tumor vasculature. EZH2 promotes tumor angiogenesis by repressing the anti-angiogenic factor, Vash1 [166]. Invasion and metastasis are also mediated by epigenetic factors such as ncRNAs. The expression of certain miRNAs can correlate positively or negatively with the invasive and metastatic phenotype of cancer. For example, miR-10b is a miRNA that promotes invasion and metastasis in gliomas [167]. In contrast, miR-124a is generally downregulated in GBMs, and ectopic expression of miR-124a in GBM cells inhibits tumor invasion and migration [168]. In addition, expression of certain lncRNAs is also correlated with the phenotype of particular cancers. Higher levels of HOTAIR, a lincRNA transcribed from the HOX locus, are implicated in promoting metastasis [36] and recurrence [169] and indicate a poor clinical prognosis for particular cancers. Many aspects of energy metabolism are also modulated by epigenetic factors. In fact, HDACs play a pivotal role in glucose homeostasis by regulating Forkhead box O transcription factors, which have critical roles in modulating metabolism [170,171]. The immune response and its evasion by cancer cells are also mediated by epigenetic factors, including HDACs. For example, HDACs are implicated in transcriptional regulation of both pro- and anti-inflammatory cytokines, in immune cell differentiation, in immunological signaling pathways (i.e., STAT and NF-κB) and inflammatory responses, in forming the antigen-presenting cell/T-cell immunological synapse, and specifically in modulating the immune response to cancer [172].

Tumor microenvironments (or niches) include the extracellular matrix (ECM) and various stromal, endothelial, and other cell types that create the local milieu permitting tumor initiation and subsequently supporting tumor maintenance and progression. The bidirectional communication that exists between CSCs and tumor microenvironments located in perivascular and, putatively, in hypoxic and invasive edge regions is modulated, at least in part, by epigenetic factors. For example, GBM CSCs secrete VEGF that promotes endothelial cell growth [173], and we have already noted how VEGF signaling is under epigenetic control. In addition, Notch signaling maintains CSCs [174], and many epigenetic factors such as histone modifying enzymes and corepressor complexes and associated epigenetic marks are important for regulating Notch target gene expression [175]. Furthermore, it is likely that many other bidirectional communications are mediated by epigenetic factors. Indeed, integrins and ECM interactions are important for CSC maintenance [176], and emerging evidence suggests an epigenetic level of control for these factors, mediated particularly by REST and CoREST [16-18,177]. Diffusible cerebrospinal fluid-borne signals that impact NSC proliferation, including specifically those derived from patients with GBMs, are partly dependent on insulin-like growth factor 2 (IGF2) levels [178], and IGF2 is regulated by intricate epigenetic mechanisms including imprinting and lncRNAs [179,180]. The release of exosomes containing regulatory and functional ncRNAs, including those derived from transposable elements, also represents an intriguing mechanism for bidirectional intercellular communication in the tumor microenvironment, and more general evidence already exists for such neural-endothelial cell communication promoting an angiogenic phenotype [96,181].

5. Epigenetic Medicine

Fundamental biological questions have yet to be answered regarding the precise roles played by epigenetic deregulation in cancer pathogenesis, generally, and in the emergence, maintenance and evolution of CSCs, in particular. Nevertheless, molecular diagnostics evaluating epigenetic factors and processes and complementary therapeutic agents targeting epigenetic factors are very actively being developed for a variety of tumors and have even been approved by the FDA for selected indications. In fact, MGMT promoter methylation and CIMP are clearly clinically relevant biomarkers. In addition, agents currently used to treat nervous system tumors, such temozolomide and carmustine, exert their effects, at least in part, by impacting epigenetic states including DNA methylation status, chromatin structure and nuclear organization [182]. Thus, the broad range of observations that we have highlighted here provides strong evidence supporting the vigorous advancement of existing and novel epigenetic strategies in concert with other approaches for diagnosing and treating nervous system tumors, including those focusing on the elimination of CSCs.

Many agents that can modulate DNA methylation have been identified. The best-characterized DNMT enzyme inhibitors include 5-azacytidine, 5-aza-2-deoxycytidine, and zebularine. Some commonly used drugs, such as hydralazine, procainamide and valproic acid (VPA), can also influence DNA methylation profiles [183]. In addition, a number of drugs that can modulate histone-modifying enzyme activity are also available. The best-described agents are the HDAC inhibitors, which include trichostatin A, suberoylanilide hydroxamic acid, sodium butyrate, sodium 4-phenylbutyrate, romidepsin and VPA. Each of these drugs differentially inhibits the activity of the 5 major classes of HDAC enzymes and of individual HDAC isotypes. In pre-clinical studies, various HDAC inhibitors, alone or in combination with other therapies, have shown significant anti-cancer effects through a broad range of cellular mechanisms, including but not limited to the modulation of oncogene and tumor suppressor gene expression, cell cycle, intrinsic and extrinsic apoptotic pathways, autophagy, reactive oxygen species generation, angiogenesis, inflammation, immunosurveillance, DNA repair, and radiosensitization. Correspondingly, the most notable clinical trials that have been performed, and those that are currently underway, utilizing epigenetic therapeutic agents to treat nervous system tumors—primarily gliomas—have focused on studying the effects of HDAC inhibitors alone or in combination with other modalities, such as chemotherapies, biologic therapies, or radiation therapies (reviewed in [184]). Despite important advances, however, these first-generation epigenetic drugs are non-specific and often associated with off-target effects and significant toxicity, thus more selective agents that affect these pathways are being developed. Moreover, small molecules and other agents targeting a more diverse range of histone- and chromatin-modifying factors are being identified or designed at a rapid pace. For example, compounds, such as BIX-01294 and chaetocin, can inhibit G9a and SUV39H1 histone methyltransferase activity [185,186]; certain monoamine oxidase inhibitors, such as trans-2-phenylcyclopropylamine, can inhibit LSD1 histone demethylase activity [187-189]; agents, such as the S-adenosylhomocysteine hydrolase inhibitor 3-deazaneplanocin and radicicol, can modulate the levels and functions of PcG and TrxG proteins, respectively [190,191]; and, compounds, such 2-aminothiazole derivatives, can inhibit REST activity [192-194].

Our evolving understanding of ncRNA biology suggests that interrogating these factors and targeting them directly, or indirectly via their biogenesis and effector pathways, represent important and potentially more sensitive and specific strategies for diagnosing and treating nervous system tumors. For example, sequencing genomic DNA can be used to identify variations in regions that give rise to ncRNAs and in regions of cancer-associated genes to identify pathogenic variability in ncRNA-mRNA interactions that may result in altered target gene regulation. Further, the existence of various classes of ncRNAs with highly pathological cell- and tissue-selective expression profiles implies that these factors may be more effective molecular biomarkers and mechanistic targets for identifying and modifying cancer pathogenesis compared to existing approaches. Indeed, molecular diagnostics that measure the levels of certain classes of ncRNAs, such as miRNAs, are already in relatively advanced stages of development, both for cancer and for other disorders [195-200]. Other ncRNAs may similarly be useful as biomarkers for risk stratification, screening, prognostication, customization of therapies, and monitoring treatment responses and disease recurrence [201,202]. Intriguingly, ncRNA levels in peripheral tissues may even provide signatures of central disease activity, as significant correlations are present between ncRNA expression profiles in brain and those in other tissues, such as blood, in certain disease processes [203,204]. Moreover, exosomes containing various ncRNAs circulate in the blood of patients with nervous system tumors and may play roles in promoting malignant transformation and dissemination and in suppressing immune responses [96,205]. In addition, small molecule, oligonucleotide and related treatment approaches are also being developed with the potential to disrupt and inhibit, or to replace and promote, ncRNA expression and function [206,207]. While many of these emerging epigenetic therapeutic approaches are very promising, significant technical barriers also exist for designing and delivering specific agents to the brain. Can these molecules be engineered to very selectively modulate a particular epigenetic regulatory factor or pathway and optimized to promote particular gene expression programs (i.e., those associated with survival in healthy cells but cell death in cancer cells and in CSCs, specifically)? Can these agents be delivered successfully to the tumor and to CSCs without off-target effects in the brain, vascular, immune, and other systems to minimize toxicities, perhaps through emerging neuro-interventional approaches?

6. Conclusions

It is clear that understanding nervous system tumors in general and the origins and behavior of CSCs in particular requires a deeper appreciation for epigenetic mechanisms that modulate neural cell identity, including their interplay with genetic and other cell-intrinsic factors and cell-extrinsic and cell-cell cues, such as those derived from the microenvironment. Efforts are underway to collect and analyze complex genomic, transcriptomic, and epigenomic data from nervous system tumors and to correlate these molecular signatures with clinical features and outcomes [208]. These studies will hopefully lead to earlier detection and better risk stratification and guide the development of more effective and even preventive therapies for nervous system tumors.

Table 1. Principal epigenetic regulatory mechanisms and associated examples of factors implicated in mediating these processes.
Table 1. Principal epigenetic regulatory mechanisms and associated examples of factors implicated in mediating these processes.
Epigenetic mechanismEpigenetic factors
DNA (de)methylation and hydroxymethylationDNA methyltransferase enzymes
Methyl-CpG-binding domain proteins
DNA excision repair proteins
Cytidine deaminase enzymes
Gadd45 proteins
Ten-Eleven Translocation enzymes
Histone and chromatin modificationsHistone modifying enzymes (e.g., histone [de]acetylase and [de]methylase)
Polycomb group proteins
Trithorax group proteins
REST and CoREST epigenetic regulatory complexes
Non-coding RNAs (ncRNAs)Short-interfering RNAs
MicroRNAs
PIWI-interacting RNAs
Small nucleolar RNAs
Long ncRNAs
Long intergenic ncRNAs
RNA editingAdenosine deaminase that act on RNA enzymes
Apolipoprotein B editing catalytic subunit enzymes
Nuclear organizationNuclear domains (e.g., nuclear speckles)
Nuclear lamina (e.g., lamin genes)

Acknowledgements

M.F.M. is supported by grants from the National Institutes of Health (NS38902, MH66290, NS071571), as well as by the Roslyn and Leslie Goldstein, Harold and Isabel Feld, Mildred and Bernard H. Kayden, F. M. Kirby, and Alpern Family Foundations.

References

  1. Mehler, M.F. Epigenetic principles and mechanisms underlying nervous system functions in health and disease. Prog. Neurobiol. 2008, 86, 305–341. [Google Scholar]
  2. Rodriguez-Paredes, M.; Esteller, M. Cancer epigenetics reaches mainstream oncology. Nat. Med. 2011, 17, 330–339. [Google Scholar]
  3. Mohn, F.; Weber, M.; Rebhan, M.; Roloff, T.C.; Richter, J.; Stadler, M.B.; Bibel, M.; Schubeler, D. Lineage-specific polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 2008, 30, 755–766. [Google Scholar]
  4. Wu, H.; Coskun, V.; Tao, J.; Xie, W.; Ge, W.; Yoshikawa, K.; Li, E.; Zhang, Y.; Sun, Y.E. Dnmt3a-dependent nonpromoter DNA methylation facilitates transcription of neurogenic genes. Science 2010, 329, 444–448. [Google Scholar]
  5. Tahiliani, M.; Koh, K.P.; Shen, Y.; Pastor, W.A.; Bandukwala, H.; Brudno, Y.; Agarwal, S.; Iyer, L.M.; Liu, D.R.; Aravind, L.; Rao, A. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 2009, 324, 930–935. [Google Scholar]
  6. Koh, K.P.; Yabuuchi, A.; Rao, S.; Huang, Y.; Cunniff, K.; Nardone, J.; Laiho, A.; Tahiliani, M.; Sommer, C.A.; Mostoslavsky, G.; et al. Tet1 and Tet2 regulate 5-hydroxymethylcytosine production and cell lineage specification in mouse embryonic stem cells. Cell Stem Cell 2011, 8, 200–213. [Google Scholar]
  7. Valinluck, V.; Tsai, H.H.; Rogstad, D.K.; Burdzy, A.; Bird, A.; Sowers, L.C. Oxidative damage to methyl-CpG sequences inhibits the binding of the methyl-CpG binding domain (MBD) of methyl-CpG binding protein 2 (MeCP2). Nucleic Acids Res. 2004, 32, 4100–4108. [Google Scholar]
  8. Jin, S.G.; Kadam, S.; Pfeifer, G.P. Examination of the specificity of DNA methylation profiling techniques towards 5-methylcytosine and 5-hydroxymethylcytosine. Nucleic Acids Res. 2010, 38, e125. [Google Scholar]
  9. Wu, H.; D'Alessio, A.C.; Ito, S.; Wang, Z.; Cui, K.; Zhao, K.; Sun, Y.E.; Zhang, Y. Genome-wide analysis of 5-hydroxymethylcytosine distribution reveals its dual function in transcriptional regulation in mouse embryonic stem cells. Genes Dev. 2011, 25, 679–684. [Google Scholar]
  10. Ficz, G.; Branco, M.R.; Seisenberger, S.; Santos, F.; Krueger, F.; Hore, T.A.; Marques, C.J.; Andrews, S.; Reik, W. Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation. Nature 2011, 473, 398–402. [Google Scholar]
  11. Kriaucionis, S.; Heintz, N. The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain. Science 2009, 324, 929–930. [Google Scholar]
  12. Munzel, M.; Globisch, D.; Bruckl, T.; Wagner, M.; Welzmiller, V.; Michalakis, S.; Muller, M.; Biel, M.; Carell, T. Quantification of the sixth DNA base hydroxymethylcytosine in the brain. Angew. Chem. Int. Ed. Engl. 2010, 49, 5375–5377. [Google Scholar]
  13. Jin, S.G.; Wu, X.; Li, A.X.; Pfeifer, G.P. Genomic mapping of 5-hydroxymethylcytosine in the human brain. Nucleic Acids Res. 2011, 39, 5015–5024. [Google Scholar]
  14. Hirabayashi, Y.; Gotoh, Y. Epigenetic control of neural precursor cell fate during development. Nat. Rev. Neurosci. 2010, 11, 377–388. [Google Scholar]
  15. Juliandi, B.; Abematsu, M.; Nakashima, K. Chromatin remodeling in neural stem cell differentiation. Curr. Opin. Neurobiol. 2010, 20, 408–415. [Google Scholar]
  16. Abrajano, J.J.; Qureshi, I.A.; Gokhan, S.; Zheng, D.; Bergman, A.; Mehler, M.F. REST and CoREST modulate neuronal subtype specification, maturation and maintenance. PLoS one 2009, 4, e7936. [Google Scholar]
  17. Abrajano, J.J.; Qureshi, I.A.; Gokhan, S.; Zheng, D.; Bergman, A.; Mehler, M.F. Differential deployment of REST and CoREST promotes glial subtype specification and oligodendrocyte lineage maturation. PLoS one 2009, 4, e7665. [Google Scholar]
  18. Abrajano, J.J.; Qureshi, I.A.; Gokhan, S.; Molero, A.E.; Zheng, D.; Bergman, A.; Mehler, M.F. Corepressor for element-1-silencing transcription factor preferentially mediates gene networks underlying neural stem cell fate decisions. Proc. Natl. Acad. Sci. USA 2010, 107, 16685–16690. [Google Scholar]
  19. Sun, G.; Alzayady, K.; Stewart, R.; Ye, P.; Yang, S.; Li, W.; Shi, Y. Histone demethylase LSD1 regulates neural stem cell proliferation. Mol. Cell. Biol. 2010, 30, 1997–2005. [Google Scholar]
  20. Hirabayashi, Y.; Suzki, N.; Tsuboi, M.; Endo, T.A.; Toyoda, T.; Shinga, J.; Koseki, H.; Vidal, M.; Gotoh, Y. Polycomb limits the neurogenic competence of neural precursor cells to promote astrogenic fate transition. Neuron 2009, 63, 600–613. [Google Scholar]
  21. Kapranov, P.; St Laurent, G.; Raz, T.; Ozsolak, F.; Reynolds, C.P.; Sorensen, P.H.; Reaman, G.; Milos, P.; Arceci, R.J.; Thompson, J.F. The majority of total nuclear-encoded non-ribosomal RNA in a human cell is ‘dark matter’ un-annotated RNA. BMC Biol. 2010, 8, 149. [Google Scholar]
  22. Amaral, P.P.; Dinger, M.E.; Mercer, T.R.; Mattick, J.S. The eukaryotic genome as an RNA machine. Science 2008, 319, 1787–1789. [Google Scholar]
  23. Mehler, M.F.; Mattick, J.S. Non-coding RNAs in the nervous system. J. Physiol. 2006, 575, 333–341. [Google Scholar]
  24. Mattick, J.S.; Amaral, P.P.; Dinger, M.E.; Mercer, T.R.; Mehler, M.F. RNA regulation of epigenetic processes. Bioessays 2009, 31, 51–59. [Google Scholar]
  25. Krol, J.; Loedige, I.; Filipowicz, W. The widespread regulation of microRNA biogenesis, function and decay. Nat. Rev. Genet. 2010, 11, 597–610. [Google Scholar]
  26. Okazaki, Y.; Furuno, M.; Kasukawa, T.; Adachi, J.; Bono, H.; Kondo, S.; Nikaido, I.; Osato, N.; Saito, R.; Suzuki, H.; et al. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 2002, 420, 563–573. [Google Scholar]
  27. Ponjavic, J.; Ponting, C.P.; Lunter, G. Functionality or transcriptional noise? Evidence for selection within long noncoding RNAs. Genome Res 2007, 17, 556–565. [Google Scholar]
  28. Carninci, P.; Kasukawa, T.; Katayama, S.; Gough, J.; Frith, M.C.; Maeda, N.; Oyama, R.; Ravasi, T.; Lenhard, B.; Wells, C. The transcriptional landscape of the mammalian genome. Science 2005, 309, 1559–1563. [Google Scholar]
  29. Kapranov, P.; Cheng, J.; Dike, S.; Nix, D.A.; Duttagupta, R.; Willingham, A.T.; Stadler, P.F.; Hertel, J.; Hackermuller, J.; Hofacker, I.L.; et al. RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science 2007, 316, 1484–1488. [Google Scholar]
  30. Washietl, S.; Hofacker, I.L.; Lukasser, M.; Huttenhofer, A.; Stadler, P.F. Mapping of conserved RNA secondary structures predicts thousands of functional noncoding RNAs in the human genome. Nat. Biotechnol. 2005, 23, 1383–1390. [Google Scholar]
  31. Pedersen, J.S.; Bejerano, G.; Siepel, A.; Rosenbloom, K.; Lindblad-Toh, K.; Lander, E.S.; Kent, J.; Miller, W.; Haussler, D. Identification and classification of conserved RNA secondary structures in the human genome. PLoS Comput. Biol. 2006, 2, e33. [Google Scholar]
  32. Torarinsson, E.; Yao, Z.; Wiklund, E.D.; Bramsen, J.B.; Hansen, C.; Kjems, J.; Tommerup, N.; Ruzzo, W.L.; Gorodkin, J. Comparative genomics beyond sequence-based alignments: RNA structures in the ENCODE regions. Genome Res. 2008, 18, 242–251. [Google Scholar]
  33. Mattick, J.S.; Makunin, I.V. Small regulatory RNAs in mammals. Hum. Mol. Genet. 2005, 14, Spec No 1. R121–R132. [Google Scholar]
  34. Qureshi, I.A.; Mattick, J.S.; Mehler, M.F. Long non-coding RNAs in nervous system function and disease. Brain Res. 2010, 1338, 20–35. [Google Scholar]
  35. Mercer, T.R.; Dinger, M.E.; Mattick, J.S. Long non-coding RNAs: Insights into functions. Nat. Rev. Genet. 2009, 10, 155–159. [Google Scholar]
  36. Gupta, R.A.; Shah, N.; Wang, K.C.; Kim, J.; Horlings, H.M.; Wong, D.J.; Tsai, M.C.; Hung, T.; Argani, P.; Rinn, J.L.; et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 2010, 464, 1071–1076. [Google Scholar]
  37. Shi, Y.; Zhao, X.; Hsieh, J.; Wichterle, H.; Impey, S.; Banerjee, S.; Neveu, P.; Kosik, K.S. MicroRNA regulation of neural stem cells and neurogenesis. J. Neurosci. 2010, 30, 14931–14936. [Google Scholar]
  38. Cheng, L.C.; Pastrana, E.; Tavazoie, M.; Doetsch, F. miR-124 regulates adult neurogenesis in the subventricular zone stem cell niche. Nat. Neurosci. 2009, 12, 399–408. [Google Scholar]
  39. Dugas, J.C.; Cuellar, T.L.; Scholze, A.; Ason, B.; Ibrahim, A.; Emery, B.; Zamanian, J.L.; Foo, L.C.; McManus, M.T.; Barres, B.A. Dicer1 and miR-219 Are required for normal oligodendrocyte differentiation and myelination. Neuron 2010, 65, 597–611. [Google Scholar]
  40. Zhao, X.; He, X.; Han, X.; Yu, Y.; Ye, F.; Chen, Y.; Hoang, T.; Xu, X.; Mi, Q.S.; Xin, M.; et al. MicroRNA-mediated control of oligodendrocyte differentiation. Neuron 2010, 65, 612–626. [Google Scholar]
  41. Mercer, T.R.; Qureshi, I.A.; Gokhan, S.; Dinger, M.E.; Li, G.; Mattick, J.S.; Mehler, M.F. Long noncoding RNAs in neuronal-glial fate specification and oligodendrocyte lineage maturation. BMC Neurosci. 2010, 11, 14. [Google Scholar]
  42. Tochitani, S.; Hayashizaki, Y. Nkx2.2 antisense RNA overexpression enhanced oligodendrocytic differentiation. Biochem. Biophys. Res. Commun. 2008, 372, 691–696. [Google Scholar]
  43. Guttman, M.; Amit, I.; Garber, M.; French, C.; Lin, M.F.; Feldser, D.; Huarte, M.; Zuk, O.; Carey, B.W.; Cassady, J.P.; et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 2009, 458, 223–227. [Google Scholar]
  44. Nishikura, K. Functions and regulation of RNA editing by ADAR deaminases. Annu. Rev. Biochem. 2010, 79, 321–349. [Google Scholar]
  45. St Laurent, G., 3rd.; Savva, Y.A.; Reenan, R. Enhancing non-coding RNA information content with ADAR editing. Neurosci. Lett. 2009, 466, 89–98. [Google Scholar]
  46. Jacobs, M.M.; Fogg, R.L.; Emeson, R.B.; Stanwood, G.D. ADAR1 and ADAR2 expression and editing activity during forebrain development. Dev. Neurosci. 2009, 31, 223–237. [Google Scholar]
  47. Melcher, T.; Maas, S.; Herb, A.; Sprengel, R.; Higuchi, M.; Seeburg, P.H. RED2, a brain-specific member of the RNA-specific adenosine deaminase family. J. Biol. Chem. 1996, 271, 31795–31798. [Google Scholar]
  48. Mehler, M.F.; Mattick, J.S. Noncoding RNAs and RNA editing in brain development, functional diversification, and neurological disease. Physiol. Rev. 2007, 87, 799–823. [Google Scholar]
  49. Blow, M.; Futreal, P.A.; Wooster, R.; Stratton, M.R. A survey of RNA editing in human brain. Genome Res. 2004, 14, 2379–2387. [Google Scholar]
  50. Li, J.B.; Levanon, E.Y.; Yoon, J.K.; Aach, J.; Xie, B.; Leproust, E.; Zhang, K.; Gao, Y.; Church, G.M. Genome-wide identification of human RNA editing sites by parallel DNA capturing and sequencing. Science 2009, 324, 1210–1213. [Google Scholar]
  51. Athanasiadis, A.; Rich, A.; Maas, S. Widespread A-to-I RNA editing of Alu-containing mRNAs in the human transcriptome. PLoS Biol. 2004, 2, e391. [Google Scholar]
  52. Hundley, H.A.; Bass, B.L. ADAR editing in double-stranded UTRs and other noncoding RNA sequences. Trends Biochem. Sci. 2010, 35, 377–383. [Google Scholar]
  53. Kawahara, Y.; Megraw, M.; Kreider, E.; Iizasa, H.; Valente, L.; Hatzigeorgiou, A.G.; Nishikura, K. Frequency and fate of microRNA editing in human brain. Nucleic Acids Res. 2008, 36, 5270–5280. [Google Scholar]
  54. Osenberg, S.; Paz Yaacov, N.; Safran, M.; Moshkovitz, S.; Shtrichman, R.; Sherf, O.; Jacob-Hirsch, J.; Keshet, G.; Amariglio, N.; Itskovitz-Eldor, J.; et al. Alu sequences in undifferentiated human embryonic stem cells display high levels of A-to-I RNA editing. PLoS one 2010, 5, e11173. [Google Scholar]
  55. Whitney, N.P.; Peng, H.; Erdmann, N.B.; Tian, C.; Monaghan, D.T.; Zheng, J.C. Calcium-permeable AMPA receptors containing Q/R-unedited GluR2 direct human neural progenitor cell differentiation to neurons. FASEB J. 2008, 22, 2888–2900. [Google Scholar]
  56. Qureshi, I.A.; Mehler, M.F. Regulation of non-coding RNA networks in the nervous system--what's the REST of the story? Neurosci. Lett. 2009, 466, 73–80. [Google Scholar]
  57. Nunez, E.; Fu, X.D.; Rosenfeld, M.G. Nuclear organization in the 3D space of the nucleus -cause or consequence? Curr. Opin. Genet. Dev. 2009, 19, 424–436. [Google Scholar]
  58. Zhao, R.; Bodnar, M.S.; Spector, D.L. Nuclear neighborhoods and gene expression. Curr. Opin. Genet. Dev. 2009, 19, 172–179. [Google Scholar]
  59. Lanctot, C.; Cheutin, T.; Cremer, M.; Cavalli, G.; Cremer, T. Dynamic genome architecture in the nuclear space: regulation of gene expression in three dimensions. Nat. Rev. Genet. 2007, 8, 104–115. [Google Scholar]
  60. Joffe, B.; Leonhardt, H.; Solovei, I. Differentiation and large scale spatial organization of the genome. Curr. Opin. Genet. Dev. 2010, 20, 562–569. [Google Scholar]
  61. Qureshi, I.A.; Mehler, M.F. Impact of nuclear organization and dynamics on epigenetic regulation in the central nervous system: implications for neurological disease states. Ann. N.Y. Acad. Sci. 2010, 1204, E20–E37. [Google Scholar]
  62. Misteli, T. Higher-order genome organization in human disease. Cold Spring Harb. Perspect. Biol. 2010. [Google Scholar] [CrossRef]
  63. Williams, R.R.; Azuara, V.; Perry, P.; Sauer, S.; Dvorkina, M.; Jorgensen, H.; Roix, J.; McQueen, P.; Misteli, T.; Merkenschlager, M.; et al. Neural induction promotes large-scale chromatin reorganisation of the Mash1 locus. J. Cell Sci. 2006, 119, 132–140. [Google Scholar]
  64. Nielsen, J.A.; Hudson, L.D.; Armstrong, R.C. Nuclear organization in differentiating oligodendrocytes. J. Cell Sci. 2002, 115, 4071–4079. [Google Scholar]
  65. Lin, S.T.; Fu, Y.H. miR-23 regulation of lamin B1 is crucial for oligodendrocyte development and myelination. Dis. Model. Mech. 2009, 2, 178–188. [Google Scholar]
  66. Lin, S.T.; Ptacek, L.J.; Fu, Y.H. Adult-onset autosomal dominant leukodystrophy: linking nuclear envelope to myelin. J. Neurosci. 2011, 31, 1163–1166. [Google Scholar]
  67. Manuyakorn, A.; Paulus, R.; Farrell, J.; Dawson, N.A.; Tze, S.; Cheung-Lau, G.; Hines, O.J.; Reber, H.; Seligson, D.B.; Horvath, S.; et al. Cellular histone modification patterns predict prognosis and treatment response in resectable pancreatic adenocarcinoma: results from RTOG 9704. J. Clin. Oncol. 2010, 28, 1358–1365. [Google Scholar]
  68. Elsheikh, S.E.; Green, A.R.; Rakha, E.A.; Powe, D.G.; Ahmed, R.A.; Collins, H.M.; Soria, D.; Garibaldi, J.M.; Paish, C.E.; Ammar, A.A.; et al. Global histone modifications in breast cancer correlate with tumor phenotypes, prognostic factors, and patient outcome. Cancer Res. 2009, 69, 3802–3809. [Google Scholar]
  69. Seligson, D.B.; Horvath, S.; McBrian, M.A.; Mah, V.; Yu, H.; Tze, S.; Wang, Q.; Chia, D.; Goodglick, L.; Kurdistani, S.K. Global levels of histone modifications predict prognosis in different cancers. Am. J. Pathol. 2009, 174, 1619–1628. [Google Scholar]
  70. Kondo, Y.; Shen, L.; Cheng, A.S.; Ahmed, S.; Boumber, Y.; Charo, C.; Yamochi, T.; Urano, T.; Furukawa, K.; Kwabi-Addo, B.; et al. Gene silencing in cancer by histone H3 lysine 27 trimethylation independent of promoter DNA methylation. Nat. Genet. 2008, 40, 741–750. [Google Scholar]
  71. Guil, S.; Esteller, M. DNA methylomes, histone codes and miRNAs: Tying it all together. Int. J. Biochem. Cell Biol. 2009, 41, 87–95. [Google Scholar]
  72. Dinger, M.E.; Amaral, P.P.; Mercer, T.R.; Pang, K.C.; Bruce, S.J.; Gardiner, B.B.; Askarian-Amiri, M.E.; Ru, K.; Solda, G.; Simons, C.; et al. Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation. Genome Res. 2008, 18, 1433–1445. [Google Scholar]
  73. Sheik Mohamed, J.; Gaughwin, P.M.; Lim, B.; Robson, P.; Lipovich, L. Conserved long noncoding RNAs transcriptionally regulated by Oct4 and Nanog modulate pluripotency in mouse embryonic stem cells. RNA 2010, 16, 324–337. [Google Scholar]
  74. Hawkins, P.G.; Morris, K.V. Transcriptional regulation of Oct4 by a long non-coding RNA antisense to Oct4-pseudogene 5. Transcription 2010, 1, 165–175. [Google Scholar]
  75. Huarte, M.; Guttman, M.; Feldser, D.; Garber, M.; Koziol, M.J.; Kenzelmann-Broz, D.; Khalil, A.M.; Zuk, O.; Amit, I.; Rabani, M.; et al. A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell 2010, 142, 409–419. [Google Scholar]
  76. Huarte, M.; Rinn, J.L. Large non-coding RNAs: Missing links in cancer? Hum. Mol. Genet. 2010, 19, R152–R161. [Google Scholar]
  77. Martinez, R.; Esteller, M. The DNA methylome of glioblastoma multiforme. Neurobiol. Dis. 2010, 39, 40–46. [Google Scholar]
  78. Parsons, D.W.; Jones, S.; Zhang, X.; Lin, J.C.; Leary, R.J.; Angenendt, P.; Mankoo, P.; Carter, H.; Siu, I.M.; Gallia, G.L.; et al. An integrated genomic analysis of human glioblastoma multiforme. Science 2008, 321, 1807–1812. [Google Scholar]
  79. Rajendran, G.; Shanmuganandam, K.; Bendre, A.; Mujumdar, D.; Goel, A.; Shiras, A. Epigenetic regulation of DNA methyltransferases: DNMT1 and DNMT3B in gliomas. J. Neuro-Oncol. 2011, 104, 483–494. [Google Scholar]
  80. Lucio-Eterovic, A.K.; Cortez, M.A.; Valera, E.T.; Motta, F.J.; Queiroz, R.G.; Machado, H.R.; Carlotti, C.G., Jr.; Neder, L.; Scrideli, C.A.; Tone, L.G. Differential expression of 12 histone deacetylase (HDAC) genes in astrocytomas and normal brain tissue: Class II and IV are hypoexpressed in glioblastomas. BMC Cancer 2008, 8, 243. [Google Scholar]
  81. Hayry, V.; Tanner, M.; Blom, T.; Tynninen, O.; Roselli, A.; Ollikainen, M.; Sariola, H.; Wartiovaara, K.; Nupponen, N.N. Copy number alterations of the polycomb gene BMI1 in gliomas. Acta Neuropathol. 2008, 116, 97–102. [Google Scholar]
  82. Shah, N.; Lin, B.; Sibenaller, Z.; Ryken, T.; Lee, H.; Yoon, J.G.; Rostad, S.; Foltz, G. Comprehensive Analysis of MGMT Promoter Methylation: Correlation with MGMT Expression and Clinical Response in GBM. PLoS one 2011, 6, e16146. [Google Scholar]
  83. Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 2008, 455, 1061–1068. [Google Scholar]
  84. Gonzalez-Gomez, P.; Bello, M.J.; Arjona, D.; Lomas, J.; Alonso, M.E.; De Campos, J.M.; Vaquero, J.; Isla, A.; Gutierrez, M.; Rey, J.A. Promoter hypermethylation of multiple genes in astrocytic gliomas. Int. J. Oncol. 2003, 22, 601–608. [Google Scholar]
  85. Yu, J.; Zhang, H.; Gu, J.; Lin, S.; Li, J.; Lu, W.; Wang, Y.; Zhu, J. Methylation profiles of thirty four promoter-CpG islands and concordant methylation behaviours of sixteen genes that may contribute to carcinogenesis of astrocytoma. BMC Cancer 2004, 4, 65. [Google Scholar]
  86. Piperi, C.; Themistocleous, M.S.; Papavassiliou, G.A.; Farmaki, E.; Levidou, G.; Korkolopoulou, P.; Adamopoulos, C.; Papavassiliou, A.G. High incidence of MGMT and RARbeta promoter methylation in primary glioblastomas: association with histopathological characteristics, inflammatory mediators and clinical outcome. Mol. Med. 2010, 16, 1–9. [Google Scholar]
  87. Laffaire, J.; Everhard, S.; Idbaih, A.; Criniere, E.; Marie, Y.; de Reynies, A.; Schiappa, R.; Mokhtari, K.; Hoang-Xuan, K.; Sanson, M.; et al. Methylation profiling identifies 2 groups of gliomas according to their tumorigenesis. Neuro Oncol. 2011, 13, 84–98. [Google Scholar]
  88. Fowler, A.; Thomson, D.; Giles, K.; Maleki, S.; Mreich, E.; Wheeler, H.; Leedman, P.; Biggs, M.; Cook, R.; Little, N.; et al. miR-124a is frequently down-regulated in glioblastoma and is involved in migration and invasion. Eur. J. Cancer 2011, 47, 953–963. [Google Scholar]
  89. Papagiannakopoulos, T.; Shapiro, A.; Kosik, K.S. MicroRNA-21 targets a network of key tumor-suppressive pathways in glioblastoma cells. Cancer Res. 2008, 68, 8164–8172. [Google Scholar]
  90. Dong, H.; Siu, H.; Luo, L.; Fang, X.; Jin, L.; Xiong, M. Investigation gene and microRNA expression in glioblastoma. BMC Genomics 2010, 11 Suppl. 3, S16. [Google Scholar]
  91. Korneev, S.A.; Korneeva, E.I.; Lagarkova, M.A.; Kiselev, S.L.; Critchley, G.; O'Shea, M. Novel noncoding antisense RNA transcribed from human anti-NOS2A locus is differentially regulated during neuronal differentiation of embryonic stem cells. RNA 2008, 14, 2030–2037. [Google Scholar]
  92. Broholm, H.; Rubin, I.; Kruse, A.; Braendstrup, O.; Schmidt, K.; Skriver, E.B.; Lauritzen, M. Nitric oxide synthase expression and enzymatic activity in human brain tumors. Clin. Neuropathol. 2003, 22, 273–281. [Google Scholar]
  93. Grinchuk, O.V.; Jenjaroenpun, P.; Orlov, Y.L.; Zhou, J.; Kuznetsov, V.A. Integrative analysis of the human cis-antisense gene pairs, miRNAs and their transcription regulation patterns. Nucleic Acids Res 2010, 38, 534–547. [Google Scholar]
  94. Paz, N.; Levanon, E.Y.; Amariglio, N.; Heimberger, A.B.; Ram, Z.; Constantini, S.; Barbash, Z.S.; Adamsky, K.; Safran, M.; Hirschberg, A.; et al. Altered adenosine-to-inosine RNA editing in human cancer. Genome Res. 2007, 17, 1586–1595. [Google Scholar]
  95. Maas, S.; Patt, S.; Schrey, M.; Rich, A. Underediting of glutamate receptor GluR-B mRNA in malignant gliomas. Proc. Natl. Acad. Sci. USA 2001, 98, 14687–14692. [Google Scholar]
  96. Skog, J.; Wurdinger, T.; van Rijn, S.; Meijer, D.H.; Gainche, L.; Sena-Esteves, M.; Curry, W.T., Jr.; Carter, B.S.; Krichevsky, A.M.; Breakefield, X.O. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat. Cell Biol. 2008, 10, 1470–1476. [Google Scholar]
  97. Balaj, L.; Lessard, R.; Dai, L.; Cho, Y.J.; Pomeroy, S.L.; Breakefield, X.O.; Skog, J. Tumour microvesicles contain retrotransposon elements and amplified oncogene sequences. Nat. Commun. 2011, 2, 180. [Google Scholar]
  98. Dong, S.M.; Pang, J.C.; Poon, W.S.; Hu, J.; To, K.F.; Chang, A.R.; Ng, H.K. Concurrent hypermethylation of multiple genes is associated with grade of oligodendroglial tumors. J. Neuropathol. Exp. Neurol. 2001, 60, 808–816. [Google Scholar]
  99. Alonso, M.E.; Bello, M.J.; Gonzalez-Gomez, P.; Arjona, D.; Lomas, J.; de Campos, J.M.; Isla, A.; Sarasa, J.L.; Rey, J.A. Aberrant promoter methylation of multiple genes in oligodendrogliomas and ependymomas. Cancer Genet. Cytogenet. 2003, 144, 134–142. [Google Scholar]
  100. Cogdell, D.; Chung, W.; Liu, Y.; McDonald, J.M.; Aldape, K.; Issa, J.P.; Fuller, G.N.; Zhang, W. Tumor-associated methylation of the putative tumor suppressor AJAP1 gene and association between decreased AJAP1 expression and shorter survival in patients with glioma. Chin. J. Cancer 2011, 30, 247–253. [Google Scholar]
  101. Pang, J.C.; Li, K.K.; Lau, K.M.; Ng, Y.L.; Wong, J.; Chung, N.Y.; Li, H.M.; Chui, Y.L.; Lui, V.W.; Chen, Z.P.; et al. KIAA0495/PDAM is frequently downregulated in oligodendroglial tumors and its knockdown by siRNA induces cisplatin resistance in glioma cells. Brain Pathol. 2010, 20, 1021–1032. [Google Scholar]
  102. Parsons, D.W.; Li, M.; Zhang, X.; Jones, S.; Leary, R.J.; Lin, J.C.; Boca, S.M.; Carter, H.; Samayoa, J.; Bettegowda, C.; et al. The genetic landscape of the childhood cancer medulloblastoma. Science 2011, 331, 435–439. [Google Scholar]
  103. Northcott, P.A.; Nakahara, Y.; Wu, X.; Feuk, L.; Ellison, D.W.; Croul, S.; Mack, S.; Kongkham, P.N.; Peacock, J.; Dubuc, A.; et al. Multiple recurrent genetic events converge on control of histone lysine methylation in medulloblastoma. Nat. Genet. 2009, 41, 465–472. [Google Scholar]
  104. Lawinger, P.; Venugopal, R.; Guo, Z.S.; Immaneni, A.; Sengupta, D.; Lu, W.; Rastelli, L.; Marin Dias Carneiro, A.; Levin, V.; Fuller, G.N.; et al. The neuronal repressor REST/NRSF is an essential regulator in medulloblastoma cells. Nat. Med. 2000, 6, 826–831. [Google Scholar]
  105. Fuller, G.N.; Su, X.; Price, R.E.; Cohen, Z.R.; Lang, F.F.; Sawaya, R.; Majumder, S. Many human medulloblastoma tumors overexpress repressor element-1 silencing transcription (REST)/neuron-restrictive silencer factor, which can be functionally countered by REST-VP16. Mol. Cancer Ther. 2005, 4, 343–349. [Google Scholar]
  106. Blom, T.; Tynninen, O.; Puputti, M.; Halonen, M.; Paetau, A.; Haapasalo, H.; Tanner, M.; Nupponen, N.N. Molecular genetic analysis of the REST/NRSF gene in nervous system tumors. Acta Neuropathol. 2006, 112, 483–490. [Google Scholar]
  107. Su, X.; Gopalakrishnan, V.; Stearns, D.; Aldape, K.; Lang, F.F.; Fuller, G.; Snyder, E.; Eberhart, C.G.; Majumder, S. Abnormal expression of REST/NRSF and Myc in neural stem/progenitor cells causes cerebellar tumors by blocking neuronal differentiation. Mol. Cell. Biol. 2006, 26, 1666–1678. [Google Scholar]
  108. Qureshi, I.A.; Gokhan, S.; Mehler, M.F. REST and CoREST are transcriptional and epigenetic regulators of seminal neural fate decisions. Cell Cycle 2010, 9, 4477–4486. [Google Scholar]
  109. Uziel, T.; Karginov, F.V.; Xie, S.; Parker, J.S.; Wang, Y.D.; Gajjar, A.; He, L.; Ellison, D.; Gilbertson, R.J.; Hannon, G.; et al. The miR-17∼92 cluster collaborates with the Sonic Hedgehog pathway in medulloblastoma. Proc. Natl. Acad. Sci. USA 2009, 106, 2812–2817. [Google Scholar]
  110. Northcott, P.A.; Fernandez, L.A.; Hagan, J.P.; Ellison, D.W.; Grajkowska, W.; Gillespie, Y.; Grundy, R.; Van Meter, T.; Rutka, J.T.; Croce, C.M.; et al. The miR-17/92 polycistron is up-regulated in sonic hedgehog-driven medulloblastomas and induced by N-myc in sonic hedgehog-treated cerebellar neural precursors. Cancer Res. 2009, 69, 3249–3255. [Google Scholar]
  111. Cho, Y.J.; Tsherniak, A.; Tamayo, P.; Santagata, S.; Ligon, A.; Greulich, H.; Berhoukim, R.; Amani, V.; Goumnerova, L.; Eberhart, C.G.; et al. Integrative genomic analysis of medulloblastoma identifies a molecular subgroup that drives poor clinical outcome. J. Clin. Oncol. 2011, 29, 1424–1430. [Google Scholar]
  112. Buckley, P.G.; Das, S.; Bryan, K.; Watters, K.M.; Alcock, L.; Koster, J.; Versteeg, R.; Stallings, R.L. Genome-wide DNA methylation analysis of neuroblastic tumors reveals clinically relevant epigenetic events and large-scale epigenomic alterations localized to telomeric regions. Int. J. Cancer 2011, 128, 2296–2305. [Google Scholar]
  113. Yang, Q.W.; Liu, S.; Tian, Y.; Salwen, H.R.; Chlenski, A.; Weinstein, J.; Cohn, S.L. Methylation-associated silencing of the thrombospondin-1 gene in human neuroblastoma. Cancer Res. 2003, 63, 6299–6310. [Google Scholar]
  114. van Noesel, M.M.; van Bezouw, S.; Salomons, G.S.; Voute, P.A.; Pieters, R.; Baylin, S.B.; Herman, J.G.; Versteeg, R. Tumor-specific down-regulation of the tumor necrosis factor-related apoptosis-inducing ligand decoy receptors DcR1 and DcR2 is associated with dense promoter hypermethylation. Cancer Res. 2002, 62, 2157–2161. [Google Scholar]
  115. Eggert, A.; Grotzer, M.A.; Zuzak, T.J.; Wiewrodt, B.R.; Ho, R.; Ikegaki, N.; Brodeur, G.M. Resistance to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-induced apoptosis in neuroblastoma cells correlates with a loss of caspase-8 expression. Cancer Res. 2001, 61, 1314–1319. [Google Scholar]
  116. Teitz, T.; Wei, T.; Valentine, M.B.; Vanin, E.F.; Grenet, J.; Valentine, V.A.; Behm, F.G.; Look, A.T.; Lahti, J.M.; Kidd, V.J. Caspase 8 is deleted or silenced preferentially in childhood neuroblastomas with amplification of MYCN. Nat. Med. 2000, 6, 529–535. [Google Scholar]
  117. Shahi, M.H.; Schiapparelli, P.; Afzal, M.; Sinha, S.; Rey, J.A.; Castresana, J.S. Expression and epigenetic modulation of sonic hedgehog-GLI1 pathway genes in neuroblastoma cell lines and tumors. Tumour Biol. 2011, 32, 113–127. [Google Scholar]
  118. Yang, Q.; Tian, Y.; Ostler, K.R.; Chlenski, A.; Guerrero, L.J.; Salwen, H.R.; Godley, L.A.; Cohn, S.L. Epigenetic alterations differ in phenotypically distinct human neuroblastoma cell lines. BMC Cancer 2010, 10, 286. [Google Scholar]
  119. Caren, H.; Djos, A.; Nethander, M.; Sjoberg, R.M.; Kogner, P.; Enstrom, C.; Nilsson, S.; Martinsson, T. Identification of epigenetically regulated genes that predict patient outcome in neuroblastoma. BMC Cancer 2011, 11, 66. [Google Scholar]
  120. Gonzalez-Gomez, P.; Bello, M.J.; Lomas, J.; Arjona, D.; Alonso, M.E.; Aminoso, C.; Lopez-Marin, I.; Anselmo, N.P.; Sarasa, J.L.; Gutierrez, M.; et al. Aberrant methylation of multiple genes in neuroblastic tumours. relationship with MYCN amplification and allelic status at 1p. Eur. J. Cancer 2003, 39, 1478–1485. [Google Scholar]
  121. Grau, E.; Martinez, F.; Orellana, C.; Canete, A.; Yanez, Y.; Oltra, S.; Noguera, R.; Hernandez, M.; Bermudez, J.D.; Castel, V. Hypermethylation of apoptotic genes as independent prognostic factor in neuroblastoma disease. Mol. Carcinog. 2011, 50, 153–162. [Google Scholar]
  122. Hoebeeck, J.; Michels, E.; Pattyn, F.; Combaret, V.; Vermeulen, J.; Yigit, N.; Hoyoux, C.; Laureys, G.; De Paepe, A.; Speleman, F.; et al. Aberrant methylation of candidate tumor suppressor genes in neuroblastoma. Cancer Lett. 2009, 273, 336–346. [Google Scholar]
  123. Abe, M.; Ohira, M.; Kaneda, A.; Yagi, Y.; Yamamoto, S.; Kitano, Y.; Takato, T.; Nakagawara, A.; Ushijima, T. CpG island methylator phenotype is a strong determinant of poor prognosis in neuroblastomas. Cancer Res. 2005, 65, 828–834. [Google Scholar]
  124. Abe, M.; Westermann, F.; Nakagawara, A.; Takato, T.; Schwab, M.; Ushijima, T. Marked and independent prognostic significance of the CpG island methylator phenotype in neuroblastomas. Cancer Lett. 2007, 247, 253–258. [Google Scholar]
  125. Abe, M.; Watanabe, N.; McDonell, N.; Takato, T.; Ohira, M.; Nakagawara, A.; Ushijima, T. Identification of genes targeted by CpG island methylator phenotype in neuroblastomas, and their possible integrative involvement in poor prognosis. Oncology 2008, 74, 50–60. [Google Scholar]
  126. Nishimura, E.; Sasaki, K.; Maruyama, K.; Tsukada, T.; Yamaguchi, K. Decrease in neuron-restrictive silencer factor (NRSF) mRNA levels during differentiation of cultured neuroblastoma cells. Neurosci. Lett. 1996, 211, 101–104. [Google Scholar]
  127. Palm, K.; Metsis, M.; Timmusk, T. Neuron-specific splicing of zinc finger transcription factor REST/NRSF/XBR is frequent in neuroblastomas and conserved in human, mouse and rat. Brain Res. Mol. Brain Res. 1999, 72, 30–39. [Google Scholar]
  128. Lee, J.H.; Chai, Y.G.; Hersh, L.B. Expression patterns of mouse repressor element-1 silencing transcription factor 4 (REST4) and its possible function in neuroblastoma. J. Mol. Neurosci. 2000, 15, 205–214. [Google Scholar]
  129. Chen, H.; Shalom-Feuerstein, R.; Riley, J.; Zhang, S.D.; Tucci, P.; Agostini, M.; Aberdam, D.; Knight, R.A.; Genchi, G.; Nicotera, P.; et al. miR-7 and miR-214 are specifically expressed during neuroblastoma differentiation, cortical development and embryonic stem cells differentiation, and control neurite outgrowth in vitro. Biochem. Biophys. Res. Commun. 2010, 394, 921–927. [Google Scholar]
  130. Laneve, P.; Di Marcotullio, L.; Gioia, U.; Fiori, M.E.; Ferretti, E.; Gulino, A.; Bozzoni, I.; Caffarelli, E. The interplay between microRNAs and the neurotrophin receptor tropomyosin-related kinase C controls proliferation of human neuroblastoma cells. Proc. Natl. Acad. Sci. USA 2007, 104, 7957–7962. [Google Scholar]
  131. Laneve, P.; Gioia, U.; Andriotto, A.; Moretti, F.; Bozzoni, I.; Caffarelli, E. A minicircuitry involving REST and CREB controls miR-9-2 expression during human neuronal differentiation. Nucleic Acids Res. 2010, 38, 6895–6905. [Google Scholar]
  132. Fontana, L.; Fiori, M.E.; Albini, S.; Cifaldi, L.; Giovinazzi, S.; Forloni, M.; Boldrini, R.; Donfrancesco, A.; Federici, V.; Giacomini, P.; et al. Antagomir-17-5p abolishes the growth of therapy-resistant neuroblastoma through p21 and BIM. PLoS one 2008, 3, e2236. [Google Scholar]
  133. Michalowski, M.B.; de Fraipont, F.; Michelland, S.; Entz-Werle, N.; Grill, J.; Pasquier, B.; Favrot, M.C.; Plantaz, D. Methylation of RASSF1A and TRAIL pathway-related genes is frequent in childhood intracranial ependymomas and benign choroid plexus papilloma. Cancer Genet. Cytogenet. 2006, 166, 74–81. [Google Scholar]
  134. Hamilton, D.W.; Lusher, M.E.; Lindsey, J.C.; Ellison, D.W.; Clifford, S.C. Epigenetic inactivation of the RASSF1A tumour suppressor gene in ependymoma. Cancer Lett. 2005, 227, 75–81. [Google Scholar]
  135. Rousseau, E.; Ruchoux, M.M.; Scaravilli, F.; Chapon, F.; Vinchon, M.; De Smet, C.; Godfraind, C.; Vikkula, M. CDKN2A, CDKN2B and p14ARF are frequently and differentially methylated in ependymal tumours. Neuropathol. Appl. Neurobiol. 2003, 29, 574–583. [Google Scholar]
  136. Alonso, M.E.; Bello, M.J.; Gonzalez-Gomez, P.; Arjona, D.; de Campos, J.M.; Gutierrez, M.; Rey, J.A. Aberrant CpG island methylation of multiple genes in ependymal tumors. J. Neurooncol. 2004, 67, 159–165. [Google Scholar]
  137. Xie, H.; Wang, M.; Bonaldo Mde, F.; Rajaram, V.; Stellpflug, W.; Smith, C.; Arndt, K.; Goldman, S.; Tomita, T.; Soares, M.B. Epigenomic analysis of Alu repeats in human ependymomas. Proc Natl Acad Sci USA 2010, 107, 6952–6957. [Google Scholar]
  138. Roberts, C.W.; Galusha, S.A.; McMenamin, M.E.; Fletcher, C.D.; Orkin, S.H. Haploinsufficiency of Snf5 (integrase interactor 1) predisposes to malignant rhabdoid tumors in mice. Proc. Natl. Acad. Sci. USA 2000, 97, 13796–13800. [Google Scholar]
  139. Bonnet, D.; Dick, J.E. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med. 1997, 3, 730–737. [Google Scholar]
  140. Dirks, P.B. Brain tumor stem cells: The cancer stem cell hypothesis writ large. Mol. Oncol. 2010, 4, 420–430. [Google Scholar]
  141. Dimov, I.; Tasic Dimov, D.; Conic, I.; Stefanovic, V. Glioblastoma multiforme stem cells. ScientificWorldJournal 2011, 11, 930–958. [Google Scholar]
  142. Prestegarden, L.; Enger, P.O. Cancer stem cells in the central nervous system—A critical review. Cancer Res. 2010, 70, 8255–8258. [Google Scholar]
  143. Notta, F.; Mullighan, C.G.; Wang, J.C.; Poeppl, A.; Doulatov, S.; Phillips, L.A.; Ma, J.; Minden, M.D.; Downing, J.R.; Dick, J.E. Evolution of human BCR-ABL1 lymphoblastic leukaemia-initiating cells. Nature 2011, 469, 362–367. [Google Scholar]
  144. Anderson, K.; Lutz, C.; van Delft, F.W.; Bateman, C.M.; Guo, Y.; Colman, S.M.; Kempski, H.; Moorman, A.V.; Titley, I.; Swansbury, J.; et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature 2011, 469, 356–361. [Google Scholar]
  145. Yi, J.M.; Tsai, H.C.; Glockner, S.C.; Lin, S.; Ohm, J.E.; Easwaran, H.; James, C.D.; Costello, J.F.; Riggins, G.; Eberhart, C.G.; et al. Abnormal DNA methylation of CD133 in colorectal and glioblastoma tumors. Cancer Res. 2008, 68, 8094–8103. [Google Scholar]
  146. Tabu, K.; Sasai, K.; Kimura, T.; Wang, L.; Aoyanagi, E.; Kohsaka, S.; Tanino, M.; Nishihara, H.; Tanaka, S. Promoter hypomethylation regulates CD133 expression in human gliomas. Cell Res. 2008, 18, 1037–1046. [Google Scholar]
  147. Capper, D.; Gaiser, T.; Hartmann, C.; Habel, A.; Mueller, W.; Herold-Mende, C.; von Deimling, A.; Siegelin, M.D. Stem-cell-like glioma cells are resistant to TRAIL/Apo2L and exhibit down-regulation of caspase-8 by promoter methylation. Acta Neuropathol. 2009, 117, 445–456. [Google Scholar]
  148. Lee, J.; Son, M.J.; Woolard, K.; Donin, N.M.; Li, A.; Cheng, C.H.; Kotliarova, S.; Kotliarov, Y.; Walling, J.; Ahn, S.; et al. Epigenetic-mediated dysfunction of the bone morphogenetic protein pathway inhibits differentiation of glioblastoma-initiating cells. Cancer Cell 2008, 13, 69–80. [Google Scholar]
  149. Gal, H.; Pandi, G.; Kanner, A.A.; Ram, Z.; Lithwick-Yanai, G.; Amariglio, N.; Rechavi, G.; Givol, D. MIR-451 and Imatinib mesylate inhibit tumor growth of Glioblastoma stem cells. Biochem. Biophys. Res. Commun. 2008, 376, 86–90. [Google Scholar]
  150. Cortez, M.A.; Nicoloso, M.S.; Shimizu, M.; Rossi, S.; Gopisetty, G.; Molina, J.R.; Carlotti, C., Jr.; Tirapelli, D.; Neder, L.; Brassesco, M.S.; et al. miR-29b and miR-125a regulate podoplanin and suppress invasion in glioblastoma. Genes Chromosomes Cancer 2010, 49, 981–990. [Google Scholar]
  151. Silber, J.; Lim, D.A.; Petritsch, C.; Persson, A.I.; Maunakea, A.K.; Yu, M.; Vandenberg, S.R.; Ginzinger, D.G.; James, C.D.; Costello, J.F.; et al. miR-124 and miR-137 inhibit proliferation of glioblastoma multiforme cells and induce differentiation of brain tumor stem cells. BMC Med. 2008, 6, 14. [Google Scholar]
  152. Schiapparelli, P.; Enguita-German, M.; Balbuena, J.; Rey, J.A.; Lazcoz, P.; Castresana, J.S. Analysis of stemness gene expression and CD133 abnormal methylation in neuroblastoma cell lines. Oncol. Rep. 2010, 24, 1355–1362. [Google Scholar]
  153. Garzia, L.; Andolfo, I.; Cusanelli, E.; Marino, N.; Petrosino, G.; De Martino, D.; Esposito, V.; Galeone, A.; Navas, L.; Esposito, S.; et al. MicroRNA-199b-5p impairs cancer stem cells through negative regulation of HES1 in medulloblastoma. PLoS one 2009, 4, e4998. [Google Scholar]
  154. Visvader, J.E. Cells of origin in cancer. Nature 2011, 469, 314–322. [Google Scholar]
  155. Yang, Z.J.; Ellis, T.; Markant, S.L.; Read, T.A.; Kessler, J.D.; Bourboulas, M.; Schuller, U.; Machold, R.; Fishell, G.; Rowitch, D.H.; et al. Medulloblastoma can be initiated by deletion of Patched in lineage-restricted progenitors or stem cells. Cancer Cell 2008, 14, 135–145. [Google Scholar]
  156. Scaffidi, P.; Misteli, T. Cancer epigenetics: From disruption of differentiation programs to the emergence of cancer stem cells. Cold Spring Harb. Symp. Quant. Biol. 2010. [Google Scholar] [CrossRef]
  157. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: the next generation. Cell 2011, 144, 646–674. [Google Scholar]
  158. Gates, K.P.; Mentzer, L.; Karlstrom, R.O.; Sirotkin, H.I. The transcriptional repressor REST/NRSF modulates hedgehog signaling. Dev. Biol. 2010, 340, 293–305. [Google Scholar]
  159. Nishihara, S.; Tsuda, L.; Ogura, T. The canonical Wnt pathway directly regulates NRSF/REST expression in chick spinal cord. Biochem. Biophys. Res. Commun. 2003, 311, 55–63. [Google Scholar]
  160. Kohyama, J.; Sanosaka, T.; Tokunaga, A.; Takatsuka, E.; Tsujimura, K.; Okano, H.; Nakashima, K. BMP-induced REST regulates the establishment and maintenance of astrocytic identity. J. Cell Biol. 2010, 189, 159–170. [Google Scholar]
  161. Longworth, M.S.; Dyson, N.J. pRb, a local chromatin organizer with global possibilities. Chromosoma 2010, 119, 1–11. [Google Scholar]
  162. Schoeftner, S.; Blasco, M.A. Chromatin regulation and non-coding RNAs at mammalian telomeres. Semin. Cell Dev. Biol. 2010, 21, 186–193. [Google Scholar]
  163. Rahman, R.; Osteso-Ibanez, T.; Hirst, R.A.; Levesley, J.; Kilday, J.P.; Quinn, S.; Peet, A.; O'Callaghan, C.; Coyle, B.; Grundy, R.G. Histone deacetylase inhibition attenuates cell growth with associated telomerase inhibition in high-grade childhood brain tumor cells. Mol. Cancer Ther. 2010, 9, 2568–2581. [Google Scholar]
  164. Caslini, C. Transcriptional regulation of telomeric non-coding RNA: Implications on telomere biology, replicative senescence and cancer. RNA Biol. 2010, 7, 18–22. [Google Scholar]
  165. Turunen, M.P.; Yla-Herttuala, S. Epigenetic regulation of key vascular genes and growth factors. Cardiovasc. Res. 2011, 90, 441–446. [Google Scholar]
  166. Lu, C.; Han, H.D.; Mangala, L.S.; Ali-Fehmi, R.; Newton, C.S.; Ozbun, L.; Armaiz-Pena, G.N.; Hu, W.; Stone, R.L.; Munkarah, A.; et al. Regulation of tumor angiogenesis by EZH2. Cancer Cell 2010, 18, 185–197. [Google Scholar]
  167. Sasayama, T.; Nishihara, M.; Kondoh, T.; Hosoda, K.; Kohmura, E. MicroRNA-10b is overexpressed in malignant glioma and associated with tumor invasive factors, uPAR and RhoC. Int. J. Cancer 2009, 125, 1407–1413. [Google Scholar]
  168. Fowler, A.; Thomson, D.; Giles, K.; Maleki, S.; Mreich, E.; Wheeler, H.; Leedman, P.; Biggs, M.; Cook, R.; Little, N.; et al. miR-124a is frequently down-regulated in glioblastoma and is involved in migration and invasion. Eur. J. Cancer 2011, 47, 953–963. [Google Scholar]
  169. Yang, Z.; Zhou, L.; Wu, L.M.; Lai, M.C.; Xie, H.Y.; Zhang, F.; Zheng, S.S. Overexpression of long non-coding RNA HOTAIR predicts tumor recurrence in hepatocellular carcinoma patients following liver transplantation. Ann. Surg. Oncol. 2011, 18, 1243–1250. [Google Scholar]
  170. Wang, B.; Moya, N.; Niessen, S.; Hoover, H.; Mihaylova, M.M.; Shaw, R.J.; Yates, J.R., 3rd; Fischer, W.H.; Thomas, J.B.; Montminy, M. A hormone-dependent module regulating energy balance. Cell 2011, 145, 596–606. [Google Scholar]
  171. Mihaylova, M.M.; Vasquez, D.S.; Ravnskjaer, K.; Denechaud, P.D.; Yu, R.T.; Alvarez, J.G.; Downes, M.; Evans, R.M.; Montminy, M.; Shaw, R.J. Class IIa histone deacetylases are hormone-activated regulators of FOXO and mammalian glucose homeostasis. Cell 2011, 145, 607–621. [Google Scholar]
  172. Villagra, A.; Sotomayor, E.M.; Seto, E. Histone deacetylases and the immunological network: implications in cancer and inflammation. Oncogene 2010, 29, 157–173. [Google Scholar]
  173. Gilbertson, R.J.; Rich, J.N. Making a tumour's bed: glioblastoma stem cells and the vascular niche. Nat. Rev. Cancer 2007, 7, 733–736. [Google Scholar]
  174. Fan, X.; Khaki, L.; Zhu, T.S.; Soules, M.E.; Talsma, C.E.; Gul, N.; Koh, C.; Zhang, J.; Li, Y.M.; Maciaczyk, J.; et al. NOTCH pathway blockade depletes CD133-positive glioblastoma cells and inhibits growth of tumor neurospheres and xenografts. Stem Cells 2010, 28, 5–16. [Google Scholar]
  175. Borggrefe, T.; Oswald, F. The Notch signaling pathway: Transcriptional regulation at Notch target genes. Cell. Mol. Life Sci. 2009, 66, 1631–1646. [Google Scholar]
  176. Lathia, J.D.; Gallagher, J.; Heddleston, J.M.; Wang, J.; Eyler, C.E.; Macswords, J.; Wu, Q.; Vasanji, A.; McLendon, R.E.; Hjelmeland, A.B.; et al. Integrin alpha 6 regulates glioblastoma stem cells. Cell Stem Cell 2010, 6, 421–432. [Google Scholar]
  177. Sun, Y.M.; Cooper, M.; Finch, S.; Lin, H.H.; Chen, Z.F.; Williams, B.P.; Buckley, N.J. Rest-mediated regulation of extracellular matrix is crucial for neural development. PLoS one 2008, 3, e3656. [Google Scholar]
  178. Lehtinen, M.K.; Zappaterra, M.W.; Chen, X.; Yang, Y.J.; Hill, A.D.; Lun, M.; Maynard, T.; Gonzalez, D.; Kim, S.; Ye, P.; et al. The cerebrospinal fluid provides a proliferative niche for neural progenitor cells. Neuron 2011, 69, 893–905. [Google Scholar]
  179. Berteaux, N.; Aptel, N.; Cathala, G.; Genton, C.; Coll, J.; Daccache, A.; Spruyt, N.; Hondermarck, H.; Dugimont, T.; Curgy, J.J.; et al. A novel H19 antisense RNA overexpressed in breast cancer contributes to paternal IGF2 expression. Mol. Cell. Biol. 2008, 28, 6731–6745. [Google Scholar]
  180. Chao, W.; D'Amore, P.A. IGF2: Epigenetic regulation and role in development and disease. Cytokine Growth Factor Rev. 2008, 19, 111–120. [Google Scholar]
  181. Smalheiser, N.R. Do neural cells communicate with endothelial cells via secretory exosomes and microvesicles? Cardiovasc. Psychiatry Neurol. 2009, 2009, 383086. [Google Scholar]
  182. Papait, R.; Magrassi, L.; Rigamonti, D.; Cattaneo, E. Temozolomide and carmustine cause large-scale heterochromatin reorganization in glioma cells. Biochem. Biophys. Res. Commun. 2009, 379, 434–439. [Google Scholar]
  183. Csoka, A.B.; Szyf, M. Epigenetic side-effects of common pharmaceuticals: A potential new field in medicine and pharmacology. Med. Hypotheses 2009, 73, 770–780. [Google Scholar]
  184. Nagarajan, R.P.; Costello, J.F. Epigenetic mechanisms in glioblastoma multiforme. Semin. Cancer Biol. 2009, 19, 188–197. [Google Scholar]
  185. Greiner, D.; Bonaldi, T.; Eskeland, R.; Roemer, E.; Imhof, A. Identification of a specific inhibitor of the histone methyltransferase SU(VAR)3-9. Nat. Chem. Biol. 2005, 1, 143–145. [Google Scholar]
  186. Kubicek, S.; O'Sullivan, R.J.; August, E.M.; Hickey, E.R.; Zhang, Q.; Teodoro, M.L.; Rea, S.; Mechtler, K.; Kowalski, J.A.; Homon, C.A.; et al. Reversal of H3K9me2 by a small-molecule inhibitor for the G9a histone methyltransferase. Mol. Cell 2007, 25, 473–481. [Google Scholar]
  187. Lee, M.G.; Wynder, C.; Schmidt, D.M.; McCafferty, D.G.; Shiekhattar, R. Histone H3 lysine 4 demethylation is a target of nonselective antidepressive medications. Chem. Biol. 2006, 13, 563–567. [Google Scholar]
  188. Schmidt, D.M.; McCafferty, D.G. trans-2-Phenylcyclopropylamine is a mechanism-based inactivator of the histone demethylase LSD1. Biochemistry 2007, 46, 4408–4416. [Google Scholar]
  189. Culhane, J.C.; Wang, D.; Yen, P.M.; Cole, P.A. Comparative analysis of small molecules and histone substrate analogues as LSD1 lysine demethylase inhibitors. J. Am. Chem. Soc. 2010, 132, 3164–3176. [Google Scholar]
  190. Tan, J.; Yang, X.; Zhuang, L.; Jiang, X.; Chen, W.; Lee, P.L.; Karuturi, R.K.; Tan, P.B.; Liu, E.T.; Yu, Q. Pharmacologic disruption of Polycomb-repressive complex 2-mediated gene repression selectively induces apoptosis in cancer cells. Genes Dev. 2007, 21, 1050–1063. [Google Scholar]
  191. Tariq, M.; Nussbaumer, U.; Chen, Y.; Beisel, C.; Paro, R. Trithorax requires Hsp90 for maintenance of active chromatin at sites of gene expression. Proc. Natl. Acad. Sci. USA 2009, 106, 1157–1162. [Google Scholar]
  192. Rigamonti, D.; Mutti, C.; Zuccato, C.; Cattaneo, E.; Contini, A. Turning REST/NRSF dysfunction in Huntington's disease into a pharmaceutical target. Curr. Pharm. Des. 2009, 15, 3958–3967. [Google Scholar]
  193. Leone, S.; Mutti, C.; Kazantsev, A.; Sturlese, M.; Moro, S.; Cattaneo, E.; Rigamonti, D.; Contini, A. SAR and QSAR study on 2-aminothiazole derivatives, modulators of transcriptional repression in Huntington's disease. Bioorg. Med. Chem. 2008, 16, 5695–5703. [Google Scholar]
  194. Rigamonti, D.; Bolognini, D.; Mutti, C.; Zuccato, C.; Tartari, M.; Sola, F.; Valenza, M.; Kazantsev, A.G.; Cattaneo, E. Loss of huntingtin function complemented by small molecules acting as repressor element 1/neuron restrictive silencer element silencer modulators. J. Biol. Chem. 2007, 282, 24554–24562. [Google Scholar]
  195. Benjamin, H.; Lebanony, D.; Rosenwald, S.; Cohen, L.; Gibori, H.; Barabash, N.; Ashkenazi, K.; Goren, E.; Meiri, E.; Morgenstern, S.; et al. A diagnostic assay based on microrna expression accurately identifies malignant pleural mesothelioma. J. Mol. Diagn. 2010, 12, 771–779. [Google Scholar]
  196. Meiri, E.; Levy, A.; Benjamin, H.; Ben-David, M.; Cohen, L.; Dov, A.; Dromi, N.; Elyakim, E.; Yerushalmi, N.; Zion, O.; et al. Discovery of microRNAs and other small RNAs in solid tumors. Nucleic Acids Res. 2010, 38, 6234–6246. [Google Scholar]
  197. Gupta, S.K.; Bang, C.; Thum, T. Circulating microRNAs as biomarkers and potential paracrine mediators of cardiovascular disease. Circ. Cardiovasc. Genet. 2010, 3, 484–488. [Google Scholar]
  198. Buckland, J. Biomarkers: microRNAs under the spotlight in inflammatory arthritis. Nat. Rev. Rheumatol. 2010, 6, 436. [Google Scholar]
  199. D'Alessandra, Y.; Devanna, P.; Limana, F.; Straino, S.; Di Carlo, A.; Brambilla, P.G.; Rubino, M.; Carena, M.C.; Spazzafumo, L.; De Simone, M.; et al. Circulating microRNAs are new and sensitive biomarkers of myocardial infarction. Eur. Heart J. 2010. [Google Scholar] [CrossRef]
  200. Alevizos, I.; Illei, G.G. MicroRNAs as biomarkers in rheumatic diseases. Nat. Rev. Rheumatol. 2010, 6, 391–398. [Google Scholar]
  201. De Smaele, E.; Ferretti, E.; Gulino, A. MicroRNAs as biomarkers for CNS cancer and other disorders. Brain Res. 2010, 1338, 100–111. [Google Scholar]
  202. Santos-Reboucas, C.B.; Pimentel, M.M. MicroRNAs: Macro challenges on understanding human biological functions and neurological diseases. Curr. Mol. Med. 2010, 10, 692–704. [Google Scholar]
  203. Jeyaseelan, K.; Lim, K.Y.; Armugam, A. MicroRNA expression in the blood and brain of rats subjected to transient focal ischemia by middle cerebral artery occlusion. Stroke 2008, 39, 959–966. [Google Scholar]
  204. Tan, K.S.; Armugam, A.; Sepramaniam, S.; Lim, K.Y.; Setyowati, K.D.; Wang, C.W.; Jeyaseelan, K. Expression profile of MicroRNAs in young stroke patients. PLoS one 2009, 4, e7689. [Google Scholar]
  205. Chen, C.; Skog, J.; Hsu, C.H.; Lessard, R.T.; Balaj, L.; Wurdinger, T.; Carter, B.S.; Breakefield, X.O.; Toner, M.; Irimia, D. Microfluidic isolation and transcriptome analysis of serum microvesicles. Lab. Chip 2010, 10, 505–511. [Google Scholar]
  206. Bader, A.G.; Brown, D.; Winkler, M. The promise of microRNA replacement therapy. Cancer Res. 2010, 70, 7027–7030. [Google Scholar]
  207. Li, Y.; He, C.; Jin, P. Emergence of chemical biology approaches to the RNAi/miRNA pathway. Chem. Biol. 2010, 17, 584–589. [Google Scholar]
  208. Wang, M.; Xie, H.; Stellpflug, W.; Rajaram, V.; de Fatima Bonaldo, M.; Goldman, S.; Tomita, T.; Soares, M.B. BTECH: A platform to integrate genomic, transcriptomic and epigenomic alterations in brain tumors. Neuroinformatics 2011, 9, 59–67. [Google Scholar]

Abbreviations

5hmC

5-hydroxymethylcytosine

5mC

5-methylcytosine

ac

acetylation

ADAR

adenosine deaminase that act on RNA

APOBEC

apolipoprotein B editing catalytic subunit

CIMP

CpG island methylator phenotype

CNS

central nervous system

CSC

cancer stem cell

DNMT

DNA methyltransferase

ECM

extracellular matrix

ESC

embryonic stem cell

EZH2

enhancer of zeste 2

GBM

glioblastoma multiforme

H

histone

HAT

histone acetylase

HDAC

histone deacetylase

K

lysine

lincRNA

long intergenic ncRNA

lncRNA

long ncRNA

MBD

methyl-CpG-binding domain protein

me

methylation

MGMT

O (6)-methylguanine-DNA methyltransferase

miRNA

microRNA

mRNA

messenger RNA

ncRNA

non-coding RNA

NPC

neural progenitor cell

NSC

neural stem cell

OL

oligodendrocyte

PcG

Polycomb group

Shh

sonic hedgehog

siRNA

short interfering RNA

snoRNA

small nucleolar RNA

TERRA

telomere repeat-containing RNA

TERT

telomerase reverse transcriptase

TET

Ten-Eleven Translocation

TRAIL

tumor necrosis factor-related apoptosis-inducing ligand

TrxG

Trithorax group

UTR

untranslated region

VPA

valproic acid

XCI

X chromosome inactivation

Share and Cite

MDPI and ACS Style

Qureshi, I.A.; Mehler, M.F. Epigenetics, Nervous System Tumors, and Cancer Stem Cells. Cancers 2011, 3, 3525-3556. https://doi.org/10.3390/cancers3033525

AMA Style

Qureshi IA, Mehler MF. Epigenetics, Nervous System Tumors, and Cancer Stem Cells. Cancers. 2011; 3(3):3525-3556. https://doi.org/10.3390/cancers3033525

Chicago/Turabian Style

Qureshi, Irfan A., and Mark F. Mehler. 2011. "Epigenetics, Nervous System Tumors, and Cancer Stem Cells" Cancers 3, no. 3: 3525-3556. https://doi.org/10.3390/cancers3033525

Article Metrics

Back to TopTop