Next Article in Journal
Spinal Canal and Spinal Cord in Rat Continue to Grow Even after Sexual Maturation: Anatomical Study and Molecular Proposition
Next Article in Special Issue
RETRACTED: Markouli et al. Impact of Histone Modifications and Their Therapeutic Targeting in Hematological Malignancies. Int. J. Mol. Sci. 2022, 23, 13657
Previous Article in Journal
New Insights into MdSPS4-Mediated Sucrose Accumulation under Different Nitrogen Levels Revealed by Physiological and Transcriptomic Analysis
Previous Article in Special Issue
Navitoclax Most Promising BH3 Mimetic for Combination Therapy in Hodgkin Lymphoma
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Contingent Synergistic Interactions between Non-Coding RNAs and DNA-Modifying Enzymes in Myelodysplastic Syndromes

by
Argiris Symeonidis
1,2,
Theodora Chatzilygeroudi
1,
Vasiliki Chondrou
3 and
Argyro Sgourou
3,*
1
Hematology Division & Stem Cell Transplantation Unit, Department of Internal Medicine, University Hospital of Patras, 26504 Patras, Greece
2
Medical School University of Patras, University Campus, 26500 Patras, Greece
3
Biology Laboratory, School of Science and Technology, Hellenic Open University, 26335 Patras, Greece
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(24), 16069; https://doi.org/10.3390/ijms232416069
Submission received: 21 November 2022 / Revised: 12 December 2022 / Accepted: 13 December 2022 / Published: 16 December 2022

Abstract

:
Myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic stem cell disorders with maturation and differentiation defects exhibiting morphological dysplasia in one or more hematopoietic cell lineages. They are associated with peripheral blood cytopenias and by increased risk for progression into acute myelogenous leukemia. Among their multifactorial pathogenesis, age-related epigenetic instability and the error-rate DNA methylation maintenance have been recognized as critical factors for both the initial steps of their pathogenesis and for disease progression. Although lower-risk MDS is associated with an inflammatory bone marrow microenvironment, higher-risk disease is delineated by immunosuppression and clonal expansion. “Epigenetics” is a multidimensional level of gene regulation that determines the specific gene networks expressed in tissues under physiological conditions and guides appropriate chromatin rearrangements upon influence of environmental stimulation. Regulation of this level consists of biochemical modifications in amino acid residues of the histone proteins’ N-terminal tails and their concomitant effects on chromatin structure, DNA methylation patterns in CpG dinucleotides and the tissue-specific non-coding RNAs repertoire, which are directed against various gene targets. The role of epigenetic modifications is widely recognized as pivotal both in gene expression control and differential molecular response to drug therapies in humans. Insights to the potential of synergistic cooperations of epigenetic mechanisms provide new avenues for treatment development to comfort human diseases with a known epigenetic shift, such as MDS. Hypomethylating agents (HMAs), such as epigenetic modulating drugs, have been widely used in the past years as first line treatment for elderly higher-risk MDS patients; however, just half of them respond to therapy and are benefited. Rational outcome predictors following epigenetic therapy in MDS and biomarkers associated with disease relapse are of high importance to improve our efforts in developing patient-tailored clinical approaches.

1. Introduction

Among the complex and multifactorial pathophysiology of MDS, hypermethylation of several genetic loci plays a dominant role in all phases of the disease, from the early steps of generation of a clonal cell population until disease evolution to AML. Since MDS is heterogeneous disease, identification of easily recognized prognostic factors is of tremendous importance, and to this point the international prognostic scoring system (IPSS) or its revised form (IPSS-R) represents standard and useful tools for the assessment of risk categorization and prognosis, taking into account cytogenetics, the number and severity of cytopenias and bone marrow blasts percentage [1,2,3].
The dominant role in the initial pathogenesis of MDS has various somatic mutations, occurring at genetic loci with essential role in growth, development and differentiation of hematopoietic cells, as well as in epigenetic alterations, since MDS patients display abnormal hypermethylation patterns across many genomic regions [4,5,6,7]. Commonly mutated genetic loci in MDS which are implicated in epigenetics include DNA methyltransferases DNMT1 and mainly DNMT3A, the family of methyl-cytosine dioxygenases TET1-3 and the isocitrate dehydrogenases IDH1-2, contributing to the generation of aberrant methylation/demethylation genomic imprints [8,9,10]. DNMTs catalyze the reaction of cytosine methylation on DNA CpG dinucleotides, while the family of TET enzymes converts 5-methylcytocine (5mC) to 5-hydroxy-methylcytocine (5hmC) and other downstream oxidative products, which leads to DNA demethylation in daughter cells due to the inability of DNMT1 to recognize the modification from 5mC to 5hmC [11]. Isocitrate dehydrogenases catalyze the oxidative decarboxylation of isocitrate to 2-oxoglutarate. Mutated IDH1 catalyzes the synthesis of 2-hydroxyglutarate, which inhibits alpha-ketoglutarate dependent enzymes such as the TETs and the histone demethylases, which indirectly leads to an elevation in 5mC levels within genome and a hypermethylated phenotype [12]. These enzyme families have been associated with harmful pathogenetic background, often acquired with advancing age and they are well known to be involved in disorders, such as MDS and various cancers of epithelial origin. Currently, the enhancement or silencing of other gene loci encoding for non-coding RNAs (ncRNAs) have also highlighted their role in the onset and course of MDS, as well as in the response to various treatment approaches, applied to these patients and in the risk to pathophysiology of AML progression [13] Differential expression of long ncRNAs appears as potential biomarkers for disease progression [14,15]. Moreover, deviating expression profiles of other ncRNAs, such as miRNAs (micro-RNAs), are detected in plasma or in bone marrow mononuclear cells during transformation of MDS to AML or in treatment intervals with hypomethylating agents [16,17,18].
Hypomethylating agents (HMAs), mainly azacytidine (AZA) and decitabine (DAC), used in clinical practice, are primarily considered inhibitors of DNA methyltransferases (DNMTs), mostly of DNMT1 [19]. AZA and DAC are both chemical nucleoside analogs of cytidine with identical ring structure, thus acting also as antimetabolites inside the rapidly proliferating immature clonal cells. These agents, after incorporation into DNA and/or RNA of highly proliferating cells, mainly induce DNMT1 depletion and global DNA hypomethylation. However, their function is not equivalent and distinctly different effects have been reported for their specific mode of action, with AZA having a greater effect on reduction of cell viability and total protein synthesis and also, restoration of onco-suppressing gene’s expression [20].
Efforts to understand in depth the underlying pathogenetic mechanisms of MDS have not attained much therapeutic progress in recent years. HMAs remain for almost two decades the mainstay of treatment for non-transplant eligible patients with higher-risk MDS (HR-MDS) and AML, despite the fact that only 30–50% of them may achieve a substantial response [21,22] and is also used as bridging treatment for several patients, candidates for allogeneic stem cell transplantation (Allo-SCT). Despite the long-term use of HMAs, an association of demethylating effect on specific DNA hypermethylated loci with particular clinical patterns of response, remains yet to be shown, while their broader mode of action in gene expression regulation is still unclear. According to the existing clinical experience, median overall survival with HMA monotherapy is ∼18–20 months for HR-MDS patients [23] and less than a year for those with AML [21]. This observation implies that additional mechanisms, beyond specific demethylation genomic events are developed, ascribing to clonal cells a biologically more aggressive/leukemic phenotype. Thus, several classes of novel agents, promising to act synergistically with HMAs are emerging, to overcome the generation of resistance. RNA-based therapeutic agents are still in pre-clinical investigation and only a few of them have entered the clinical stage to evaluate their value in practice. A novel RNA treatment approach aiming to immunize MDS and AML patients against bone marrow clonal cells, is the use of autologous dendritic cells (DCs) loaded with specifically synthetic mRNA molecules encoding tumor-associated antigens (including growth factors and unique antigens preferentially expressed in cancer cells), which is in the clinical trial stage (NCT03083054).
Given that the majority of MDS patients achieve relatively short-term responses and the inevitable development of resistance to HMAs, the discovery of new molecular, disease-specific or patient-specific biological prognostic factors, besides the complete understanding of the molecular mechanisms underlying the HMAs efficacy, are of high clinical importance. In this context, examples from the epigenetic field and possible interrelated actions between non-coding RNA molecules and enzymes affecting genome methylation/demethylation status are discussed in this review.

2. The Course of Aberrant DNA Methylation Patterns in MDS

DNA methylation is an essential epigenetic mechanism, playing very important role in the regulation of gametogenesis and zygote development in mammals (orchestrating the rounds of erasing and re-methylating of maternal and paternal derived chromosomes), imprinting and tissue-specific gene’s expression, and preservation of DNA hypermethylation as a suppressing mechanism for the locomotion of repetitive DNA elements [24,25,26]. Herein, enzymes responsible for epigenetic gene reprogramming are considered as delicate sensors of environmental signaling leading to cell responses and differential gene expression profiles. In particular, the epigenetic mark created by a methyl group covalent transfer, derived from the S-adenosyl methionine (SAM), to the 5′C position of a cytosine (C) either in scattered CpG dinucleotides across DNA sequences or in CpG islands, is catalyzed by DNMTs. By a rough classification DNMT1 is considered as the maintenance DNMT, which targets the hemi-methylated double stranded (ds)DNA to preserve the DNA methylation patterns post DNA replication and DNMT3A/DNMT3B as the de novo methylation enzymes, reacting with hemi-methylated and unmethylated dsDNA [27,28]. Contrary to DNMT1, responsible for the inherited DNA methylation, DNMT3A and DNMT3B are normally expressed and act during embryonic development or gametogenesis, independently from DNA replication. These enzymes share identical enzymatic centers at carboxyl-ends and different sequence patterns across N-ends that serve for communication with other molecules and for recognition and binding to DNA [29]. DNA recognition by DNMT3A and DNMT3B, apart from the N-terminal PWWP domain (‘Pro-Trp-Trp-Pro’ core amino acid sequence) by which bind to DNA, depends also on flanking sequences neighboring CpG targets. DNMT3B shows a significant preference for CpG methylation in a TACG (G/A) context [30], while other research groups have predicted that DNMT3A and DNMT3B preferentially methylate some representative sequences, more frequently found in naturally over-methylated genes [31,32] or that DNMTs in general, favor recruitment at DNA repair sites [33]. Furthermore, it has been reported that methylation of the Caspase-8 (CASP8) gene promoter in glioma cells is governed by both DNMT1 and DNMT3A, indicating a potential collaboration and concerted action of DNMTs [34]. Specific recruitment assisted by transcription factors or chromatin remodeling complexes is another context supporting DNMTs’ symmetrical function on DNA methylation [35]. However, there are still some interesting questions, such as the broader DNA architecture and/or epigenetic landscape that allows DNMTs to bind to CpG target sites in preferable or cognate sites or whether the flanking sequence preferences adapt to specific biological targets of DNMTs. Within this frame of action, crosstalk of DNMTs with non-coding RNA species as potential guides to specific sites for methylation across genome, remains an issue deserving further investigation.
DNMT3A and DNMT3B are frequently associated with divergent de novo DNA methylation patterns and gene repression in many pathologies. A common observation is that Myelodysplastic Syndromes are developed under an aberrant epigenetic background [10]. Cell cycle regulators, apoptotic genes, and DNA repair genes are irregularly silenced through epigenetic modifications, promoting clonal dominance and expansion of abnormal hematopoietic stem cell, favoring gradual disease progression or in association with various other somatic mutations, the transformation to AML [36]. Figure 1 illustrates phenotypic and functional cell alterations in hematopoietic stem cell (HSC) compartment of bone marrow, associated with HR-MDS that guide disease progression to AML. In MDS-derived secondary AML, mutations among the DNMTs and the TET family of genes contributing to demethylating genome pathways are frequently identified, suggesting that aberrant epigenetic programming plays a crucial role in MDS progression [10].
Cytosine methylation in CpG dinucleotides is a critical epigenetic modification, although it can be reversible. DNA demethylation occurs via a stepwise oxidation of 5-methylcytosine that is catalyzed by the Ten-Eleven Translocation or methyl-cytosine dioxygenases (TET) enzymes. The first oxidation product in this process, 5-hydroxymethylcytosine (5hmC), has been shown to act as a unique epigenetic mark, which, in contrary to 5mC, is linked to transcriptional activation. 5hmC has been implicated in the activation of lineage-specific enhancers and in substantial cell processes [37]. The oxidation pathway generates also several other intermediates (i.e., formylcytosine and carboxylcytosine), that have their own distinct biological functions [38]. The 5hmC has a functional role in promoting gene expression during active demethylation, where conversion of 5mC to 5hmC by the TETs prevent the recognition of DNA sequences by repressive (Methyl-Binding) MBD-domain complexes and DNMT proteins that would typically be recruited to rich 5mC areas [39]. The issue of cytosine epigenetic modifications across DNA CpG rich sequences apparently provides another layer of regulation, beyond the canonical genetic codes.
Hypomethylating agents (HMAs) are mainly administered as treatment to HR-MDS patients with increased percentage of bone marrow blasts, carrying a high risk for AML development [40]. Among the most widely administered MDS treatment approaches, AZA and DAC, are considered inhibitors of DNMT1, which is almost completely depleted after HMA exposure, whereas DNMT3A is significantly less sensitive and DNMT3B seems completely resistant to HMAs [19]. DAC is tri-phosphorylated and is incorporated into newly synthesized DNA as a substitute for cytosine (antimetabolite), which pairs with guanine assisted by DNA-polymerase, in contrast, AZA is converted to ribonucleoside triphosphate and is incorporated into RNA, leading to inhibition of protein synthesis [41]. Investigation has shown that DNMT1 activity decreases faster than incorporation of HMAs into DNA [19,42,43] and DNMT1 depletion occurs even in the absence of DNA replication and cell division [44,45]. The DNMT1 depletion mechanism proposed, supporting these data, is that HMAs induce DNMT1 degradation in the nucleus via its rapid hyperphosphorylation by the protein kinase C delta (PKCd), followed by ubiquitination and finally leading to proteasomal degradation [19]. Although shared epigenetic mechanisms of action have been affiliated to both AZA and DAC, such as the DNMT1 depletion and global DNA hypomethylation, their function is not equivalent. Distinctive effects have been reported on many cellular responses, such as cell viability and gene expression [20]. In proliferating cells, inactivation of DMNT1 after starting treatment with HMAs, results in a persistent hemi-methylated DNA status delivered to next generations of daughter cells. However, HMAs’ reversible activity towards the abnormal epigenetic stem cell profiles and reactivation of aberrantly silenced genes is moderate to low [46]. Response to HMA therapy is not always easily predictable, since the required molecular genetic testing is not usually applied in routine clinical practice and most MDS patients who receive HMA therapy develop resistance to treatment over time and disease progression to AML [47].
In addition to DNMTs, other epigenetic components, such microRNAs (miRNAs) and small interfering RNAs (siRNAs) exhibit altered expression profiles in MDS patients following treatment with HMAs and during disease progression, while long non-coding RNAs (lncRNAs) are shown to direct the epigenetic mechanisms and chromatin remodeling complexes in many genetic loci influencing gene expression. These perspectives are discussed in the next sections.

3. Long Non-Coding RNAs and MicroRNA Species’ Involvement in MDS

Nuclear non-coding RNAs (ncRNAs), either long or short, are exempt from protein-encoding obligations. The inherent non-protein coding nature of these transcripts is documented by the absence of an Open Reading Frame (ORF) and further confirmed by computational and biochemical approaches. Although produced intra-cellularly, ncRNAs may even found in the extra-cellular space and body fluids as parts of the micro-vesicles and/or exosomes [48,49,50]. Among the ncRNA categories, lncRNAs are characterized by their extensive length of more than 200 nucleotides and are considered as products of the RNA polymerase II, partially spliced and often polyadenylated [51]. However, a proportion of human lncRNAs identified by RNA-seq are not RNA Polymerase II transcripts [52]. Non-polyadenylated lncRNAs are transcribed by RNA polymerase III or processed by RNase P cleavage of tRNA-like structures to generate a mature 3′ end or capped by snoRNP complexes at both ends or by forming circular structures [53,54,55,56]. Particularly in AML, several lncRNA species have been identified with evidently adverse roles in disease progression. DANCR-lncRNA is upregulated in leukemic stem cells obtained from AML patients, promoting stem cell prolonged survival and self-renewal capacity [57]. LEF1-AS1, MALAT1 and NEAT1 have also oncogenic potential in AML [14]. Another category of lncRNAs that includes HOTTIP, UCA1 and MEG3 tends to sponge tumor suppressor microRNAs, thus stimulating AML reproductive capacity [14]. On the contrary, H22954-lncRNA acts as a tumor suppressor molecule in AML inducing cell apoptosis [58].
Small ncRNAs of ~20–30 nucleotides (nt) in length, have also emerged as key players in various biological processes. In mammals, major classes of small RNAs are the miRNAs, the siRNAs and the Piwi-interacting RNAs (piRNAs) [59,60]. MiRNAs and siRNAs are processed from double-stranded (ds) RNA precursors by the intranuclear Double-Stranded RNA-Specific DROSHA enzyme (or through other, DROSHA-independent processing pathways) and subsequently by DICER enzyme, two RNase type III enzymes that catalyze ncRNAs hairpin structures dissociation to generate small dsRNAs. They also interact with members of the Argonaute (AGO) family and are considered to mediate gene expression at the transcriptional or post-transcriptional level in their mature single stranded conformation via complementarity with their targets (mainly mRNAs) [61]. SiRNA molecules with accompanying Argonaute-binding proteins compose the assembled parts of the RNA-induced transcriptional silencing (RITS) complex directing epigenetic chromatin modifications. Association of RITS with nascent RNA transcripts at target loci is stabilized by proximate binding to methylated histone H3 at lysine residue 9 (H3K9me) and guide heterochromatin formation and transcriptional silencing. RNA polymerase II (Pol II) is often linked to the whole process [62].
MDS patients are also characterized by altered profiles of circulating miRNAs in plasma and ‘exosomes’ (vehicles encapsulating DNA, proteins and RNA species) as well as in bone marrow mononuclear cells (BMMC), a mixed population of single nucleus cells including monocytes, lymphocytes, NK cells and hematopoietic stem cells. Several research groups have investigated variations in miRNA subpopulations during early or advanced stages of MDS and following the administration of hypomethylating agents or progression to AML, to find representative and informative biomarkers as potential prognostic tools (Table 1). Substantial results have shown that increased miR-196b-5p, miR-320c, miR-320d, miR-422a, miR-617, miR-181a, miR-222, miR-210 and let-7a or decreased miRNA-29b expression levels were correlated with poor prognosis of MDS and increased risk for AML development [16,17,63,64]. MiR-30b, miR-30e and miR-221 have been shown to be downregulated in MDS and have been implicated in jak-STAT signaling and Th17 cell differentiation pathways as well as in cytokine–cytokine receptor interactions [18]. Characteristic MDS cytogenetic changes have been correlated with unique miRNA expression profiles: trisomy 1 is accompanied by decrease in the relative expression level of miRNA-194-5p, del(5q) by substantial decrease of miRNA-378 and miRNA-146a and by miRNA-34a increase, chromosomal translocation t(p21;q23) by increased expression levels of miRNA-125b-1, whose gene is located close to the chromosome 11q23 breakpoint, and finally, trisomy 8 by elevation of miRNA-383 expression [65]. The methylation status of miRNA promoter regions has also been proved to play a particular role, towards permissive or disincentive transcription. Hypermethylation of miRNA-34b promoter was detected during AML transformation in MDS patients [16], while hypomethylation of other miRNA loci, such as let-7a-3 gene (member of the let-7 gene family which encodes for mature miRNA let-7a together with let-7a-1 and let-7a-2) and miRNA-124-3 contribute to transformation to AML and predict poor outcome for MDS patients [66,67]. The interrelationship between different epigenetic mechanisms deserves further investigation, in terms of decoding underlying regulatory components favoring the epigenetic instability in MDS and providing new insights towards novel treatments. Among cell pathways in which miRNAs are involved, the most common target genes are Cyclin-Dependent Kinase Inhibitor 1B (CDKN1B), Cyclin Dependent Kinase 6 (CDK6), Mitogen-Activated Protein Kinase 1 (MAPK1), E3 Ubiquitin Protein Ligase (MDM2), which is a Proto-Oncogene and Protein Kinase DNA-Activated Catalytic Subunit (PRKDC), targeted by at least four different miRNAs presented in Table 1. Both CDKN1B and CDK6 control cell cycle G1 phase progression, MAPK1 is an essential component of the MAP kinase signal transduction pathway, MDM2 is implicated in cell cycle arrest and apoptosis via TP53 tumor suppressor protein and PRKDC is involved in double strand break repair and recombination. All cellular processes described emphasize the individual-tailored epigenetic variability, which is orchestrated by separate groups of epigenetic features to promote the disease manifestation and course.

4. Non-Coding RNA Species Cooperate with DNA Modifying Enzymes

Interaction of lncRNAs with genome and DNA binding proteins or chromatin remodeling complexes has been thoroughly assessed, with XIST-lncRNA being recognized as the most prominent example for the inactivation of one homologous X chromosome in females [68,69]. Another nuclear non-polyadenylated CEBPA-lncRNA originating from the CCAAT/Enhancer-Binding Protein Alpha (CEBPA) locus, regulates CEBPA methylation levels. The encoded protein (CEBPA) modulates expression of genes involved in cell cycle phase maintenance or transition and in body weight homeostasis. Mutations of this gene have been associated with AML [70]. The proposed underlying mechanism is that CEBPA-lncRNA interacts with DNA in a sequence specific manner and with DNMT1 protein preventing by this strategy the CEBPA methylation. Prevention of methylation leads to high level of CEBPA-mRNA transcription and suggests a novel regulatory mechanism of gene methylation governed by lncRNAs [71,72]. MDS patients exhibit modified levels of gene expression profiles including lncRNAs and other non-coding RNAs. The expression of several lncRNAs has been correlated with specific clinical and molecular features of MDS in various studies, which have demonstrated their importance as potential prognostic markers [73]. A DNMT1-associated lncRNA, the DACOR1-lncRNA (DNMT1-associated Colon Cancer Repressed 1), is down-regulated in colon tumors. Suppressed DACOR1-lncRNA affects unconstrained gene expression profiles in colon cancer cell lines via stimulation of genome-wide DNA demethylation [74], presenting a possible mechanism reflecting variances in response to HMAs among MDS patients. Analogous supportive evidence for interrelations between lncRNAs and enzymes of the epigenetic machinery derives from the long intergenic noncoding antisense RNA (HOTAIR), which preserves Homeobox A1 (HOAX1) gene’s methylation levels through induction of the evolutionarily conserved SET-domain-containing histone methyltransferase EZH2, the DNMT1 and DNTM3B in lung cancer [75,76]. Recently HOTAIR-lncRNA was shown to positively influence DNMT3B activity and increase methylation levels of Phosphatase and Tensin-Like protein’s gene PTEN and HOAX5 in AML [77,78]. PTEN has been shown to be associated with HMA resistance in MDS and progression to AML, suggesting that it might represent a potential target for treatment in combination with HMAs [79]. Another homeobox (HOX) antisense transcript, HOTAIRM1-lncRNA, has been implicated to cell autophagy and enhanced cell proliferation in leukemic cells and has been associated with adverse prognosis in adult NPM1 (nucleophosmin)-mutated AML [80,81]. In glioblastoma, HOTAIRM1-lncRNA acts by sequestering EZH2 and DNMTs from HOXA1, directing its up-regulation of expression [82]. Interestingly, HOXB-AS3-lncRNA, transcribed from the human HOXB cluster, is shown to recruit EZH2 to Dicer endoribonuclease’s promoter, an enzyme that cleaves double-stranded RNA and hairpins of the pre-micro and siRNAs [83], and also to be implicated in myeloid cell proliferation with adverse prognosis in AML and MDS [15]. Moreover, NR-104098-lncRNA inhibits AML proliferation and induces differentiation through repression EZH2 transcription by recruiting E2F1 to its promoter [84], a transcription factor displaying high levels of expression in bone marrow of MDS [85]. Finally, upregulation of H19-lncRNA has been associated with adverse prognosis in MDS patients [86] and has been interconnected with DNMT3B function in breast cancer [87] by promoting reactivation of BECN1 gene, a component of the phosphatidylinositol-3-kinase (PI3K) complex which mediates vesicle-trafficking processes, playing multiple roles in autophagy, also involved in MDS pathogenesis [88]. Along the DNA demethylation pathway, MAGI2-AS3-lncRNA inhibits the self-renewal of leukemic stem cells by promoting TET2-dependent DNA demethylation mechanism of the gene promoter encoding for the Leucine-Rich Repeat Protein’s (LRIG1) in AML, setting another example of ncRNA interaction with DNA modifying enzymes implicated in epigenome [89].
Functional characteristics and life cycles of identified lncRNAs linked to MDS should be underscored concerning their regulatory potential in DNA methylation and their universal action. Additionally, DNA methylation spreading restrictions depending on RNA inhibition is a cooperative epigenetic phenomenon and potentially represents a global way of inter-regulation between mechanisms, which are still considered distinct.
So far, there are few but well documented paradigms of interrelations between small ncRNA and proteins related to DNA or formation of DNA-ncRNA hybrids with regulatory functions. RNA molecules are known to impact DNA repair following damage, directly or indirectly by recruiting protein factors involved in DNA damage signaling and repair, particularly at DNA double strand breaks, considered as the most harmful DNA lesions. Production of DSB-induced small RNAs from sense and antisense sequences around DSB sites, has been obtained in human cells. DSB-induced small RNAs are associated with Argonaute (member of the RNA-induced silencing, RISC complex) and are required for the activation and efficient homologous recombination (HR) repair mechanism [90,91]. These phenomena indicate that ncRNAs intermediate the base-pairing with the damaged DNA or represent platforms responsible for DNA repair factors’ recruitment to the DSB, thus facilitating efficient DNA repair.
A few paradigms highlight the co-regulation of DNMTs, EZH2 and TET enzymes by miRNAs. MiRNA-21 and miRNA-148a are causing DNMT1 down-regulation in hematopoietic stem cells of patients with systemic lupus erythematosus [92]. MiRNA-21, which is recognized as a potential serum biomarker during epigenetic therapy in MDS [93], is also an up-regulator of EZH2 in human lung cancer stem cells [94], whereas miRNA-148a has recently been recognized as a down-regulator of DNMT1 in AML cells [95]. Additionally, miRNA-29b, down-regulates indirectly and directly DNMT1 and DNMT3A/3B expression respectively in AML patients [96] and along with miRNA-29a cooperatively target DNMT3A/3B expression in lung cancer [97], while they are both down-regulated in AML [98]. MiR-185 and miR-152, act by suppressing DNMT1 activity in hepatocellular carcinoma cells [99] and prostate cancer respectively [100], promoting PTEN expression, also shown to be associated with HMA resistance in MDS [79]. Another DNMT1-inhibitor examined in prostate cancer cells [101], miRNA-342, is downregulated in AML [102]. In addition, miRNA-221, an inhibitor of DNTM3B in breast cancer cells [103], is significantly decreased in AML evolving from MDS [104]. Other epigenetic enzymes are also regulated by miRNAs, such as TET2, a direct target of miRNA-22, a non-coding RNA with known prognostic value in MDS treated with HMAs [105], shown to provoke MDS in mice [106]. Other miRNAs that interact with TET2 in macrophages is the let-7 family [107]. MiRNA-101, that is found to delay onset or progression to AML from MDS [108] and miRNA-124, which is a possible marker of response to DAC in MDS/AML [109], both repress cancer proliferation by EZH2 inhibition [110,111]. Additionally, miRNA-34b, directly targeting histone methyltransferases and deacetylases to inhibit prostate cancer [112], also found to inhibit cell viability and promote cell apoptosis in AML cell lines [113].
Under the enlightenment of these important but still restricted results, it is anticipated that non-coding RNAs could possibly mediate the accurate targeting of CpG sites across genome offering guidance to DNMTs via sequence complementarity (between DNA and RNA) or play the role of scaffolds that recruit other DNA-modifying enzymes. Non-coding RNAs with secondary loops, such as the inter-nuclear transcribed pre-miRNA clusters and lncRNAs govern the structural principles for DNA–RNA–protein interactions (Figure 2). Future perspectives for elucidation of these mechanisms in myelodysplastic syndromes described above, are presented in Table 2.

5. Conclusions and Future Perspectives

DNA methylation in several neoplastic disease states is altered as an aggregated consequence of the gradual loss of gene and non-coding RNA expression control (which is also age-related). Moreover, the decline of mitochondrial activity, the imbalanced macromolecules’ concentration and dysfunction, the potential accumulation of destructive misfolded proteins and the presence of reactive oxygen species (ROS) within cell are manifested as cellular stress. These cell conditions are linked to genetic instability and epigenetic remodeling effects across various genetic loci that lead to pathogenesis of more aggressive and heterogeneous phenotypes. However, cellular function is completely dependent on fidelity and correct transmission and translation of genetic information under physiological epigenetic environment. Research approaches on epigenetic phenomena are based on their advantageous reversible nature, provided that key features of vital importance occurring in the shifted epigenetic background are decoded and targeted for molecular interventions before they dominate.
Current data on the roles of lncRNAs, miRNAs and DNA methylation status in MDS suggest that have the potential to become prognostic and diagnostic tools for MDS. The same is also anticipated to be applicable for patients with sAML (MDS/AML), since this disease appears to be a more advanced stage of the same group of diseases, even classified among AML. MDS and AML risk stratification, although steadily directed to the incorporation of molecular factors towards treatment, still needs improvement. To this point, the intra- or extra-cell concentrations of various non-coding RNA species can be relevant to the treatment responses, and they could also be considered as therapeutic targets. Moreover, several non-coding RNAs may mutually cooperate with enzymes involved in epigenetic events across genome by either promoting recognition and uploading on specific DNA sequences or prevention of their function, even via stereochemical inhibition. These contingent synergistic interactions can be clarified through research and become new therapeutic targets since the ultimate definition of epigenetic regulation includes short- or long-term modifications with reversible properties.
Other advanced aspects that need to be assessed by further investigation include the actual time intervals that hypomethylating effect of HMAs remain indelible, the sustainability of the beneficial results of HMAs treatment, obtained when a favorable response is achieved and the identification of the best partners of HMAs which may increase response rate, deepen the response with clearance of leukemic stem cells and prolong the period of response. Furthermore, the tissue-specific neoplastic cell populations, which are affected from ΗΜΑ treatment and the chromosomal locations licensed to reverse an established epigenetic status of hypermethylation should be unraveled. Critical questions, such as whether the DNMTs target the same groups of CpGs in different cell types or how DNMTs selectively act on specific CpGs which become hypermethylated, while others remain rather unaffected, also need a deeper insight. Finally, another “dark spot” to be assessed is whether hypomethylation/demethylation of various tumor suppressor genes, such as cell-cycle transition inhibitors or TP53 or DNA repair genes and their re-activation are the keys to treatment response with HMAs. Alternatively, the consequent restoration of dysregulation of the immune system or other cellular pathways leading to beneficial outcomes for the MDS patients, needs to be further investigated and elucidated.

Author Contributions

A.S. (Argyro Sgourou) with A.S. (Argiris Symeonidis) conceived the context and perspectives. V.C., T.C. and A.S. (Argyro Sgourou) reviewed the related literature and drafted the manuscript. A.S. (Argiris Symeonidis) revised and A.S. (Argyro Sgourou) finalized the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

Vasiliki Chondrou was supported by a two year-fellowship provided from the State Scholarships Foundation of Greece.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

5hmC5-hydroxy-methylcytocine
5mC5-methylcytocine
AGOArgonaute
AMLAcute Myeloid Leukemia
AZAAzacytidine
BCBreast cancer
BCL-2B-cell lymphoma 2 (protein)
BENC1Beclin-1 protein encoding gene
BMMCbone marrow mononuclear cells
CASP8Caspase-8
CDC2Cyclin-dependent kinase 2
CDK6Cyclin Dependent Kinase 6
CDKN1BCyclin-Dependent Kinase Inhibitor 1B
CDKN2ACyclin-Dependent Kinase 2A
CEBPACCAAT/Enhancer-Binding Protein Alpha
CpGcytosine nucleotide followed by a guanine nucleotide
CRCColorectal cancer
DACDecitabine
DACOR1DNMT1-associated Colon Cancer Repressed 1
DANCR-lncRNADifferentiation antagonizing nonprotein coding RNA
DCsdendritic cells
DICERendoribonuclease Dicer or helicase with RNase motif
DNADeoxyribonucleic acid
DNMTDNA methyltransferase
DROSHADrosha Ribonuclease III
DsDNAdouble stranded Deoxyribonucleic Acid
DSBDNA double strand breaks
E2F1E2F Transcription Factor 1
EZH2Enhancer Of Zeste 2 Polycomb Repressive Complex 2 Subunit
FoxOForkhead box O
GBGlioblastoma
H19H19 Imprinted Maternally Expressed Transcript
H3K9memethylated histone H3 at lysine 9
HCChepatocellular carcinoma
HDACHistone deacetylase
HIF-1Hypoxia-inducible factor 1
HMAsHypomethylating agents
HOAX1Homeobox A1- protein coding gene
HOAX5Homeobox A5
HOTAIRHomeobox (HOX) transcript antisense RNA
HOTAIRM1HOXA Transcript Antisense RNA, Myeloid-Specific 1
HOTTIPHOXA Distal Transcript Antisense RNA
HOXB-AS3HOXB Cluster Antisense RNA 3
HRhomologous recombination
HR-MDShigh-risk Myelodysplastic Syndromes
HSChematopoietic stem cell
IDHIsocitrate dehydrogenase
IL-6Interleukin-6
IPSSInternational prognostic scoring system
IPSS-RRevised international prognostic scoring system
jak-STAT The Janus kinase—signal transducer and activator of transcription pathway
LEF1-AS1Lymphoid enhancer-binding factor 1 (LEF1) antisense RNA 1
LncRNAslong non-coding RNAs
LRIG1Leucine Rich Repeats And Immunoglobulin Like Domains 1
LSCClaryngeal squamous cell carcinoma
MDM2E3 Ubiquitin Protein Ligase
MAGI2-AS3MAGI2 Antisense RNA 3
MALAT1Metastasis-Related Lung Adenocarcinoma Transcript 1
MAPKMitogen-Activated Protein Kinase
MBD-domainMethyl-CpG-binding domain
MDS Myelodysplastic syndromes
MEG3Maternally Expressed 3
miRNAsmicroRNAs
MMmultiple myeloma
Nanog Nanog Homeobox
NcRNAsnon-coding RNAs
NEAT1Nuclear Paraspeckle Assembly Transcript 1
NtNucleotide
NPM1Nucleiphosmin-1
Oct3Octamer binding transcription factor 3
ORFopen reading frame
PCprostate cancer
PKCdprotein kinase C delta
PI3K-AktPhosphatidyl-Inositol-3-Kinase-
PiRNAsPiwi-interacting RNAs
Pol IIRNA polymerase II
PRKDCProtein Kinase DNA-Activated Catalytic Subunit
PTENPhosphatase and tensin homolog
PWWP domain‘Pro-Trp-Trp-Pro’ core amino acid sequence
RNARibonucleic Acid
RITSRNA-induced transcriptional silencing
ROSreactive oxygen species
SAMS-adenosyl methionine
SCLCSmall cell lung carcinoma
SiRNAssmall interfering RNAs
SLESystemic Lupus Erythematosus
SnoRNPSmall nucleolar ribonucleoprotein
TETTen-Eleven Translocation or methyl-cytosine dioxygenase
TGFβTransforming Growth Factor-β
Th17T helper 17 cells (Th17)—a subset of pro-inflammatory T helper cells defined by their production of interleukin 17 (IL-17)
UCA1Urothelial Cancer Associated 1
XISTX-inactive specific transcript

References

  1. Malcovati, L.; Hellstrom-Lindberg, E.; Bowen, D.; Ades, L.; Cermak, J.; Del Canizo, C.; Della Porta, M.G.; Fenaux, P.; Gattermann, N.; Germing, U.; et al. Diagnosis and treatment of primary myelodysplastic syndromes in adults: Recommendations from the European LeukemiaNet. Blood 2013, 122, 2943–2964. [Google Scholar] [CrossRef] [Green Version]
  2. Greenberg, P.; Cox, C.; LeBeau, M.M.; Fenaux, P.; Morel, P.; Sanz, G.; Sanz, M.; Vallespi, T.; Hamblin, T.; Oscier, D.; et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood 1997, 89, 2079–2088. [Google Scholar] [CrossRef]
  3. Greenberg, P.L.; Tuechler, H.; Schanz, J.; Sanz, G.; Garcia-Manero, G.; Sole, F.; Bennett, J.M.; Bowen, D.; Fenaux, P.; Dreyfus, F.; et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood 2012, 120, 2454–2465. [Google Scholar] [CrossRef] [Green Version]
  4. Figueroa, M.E.; Skrabanek, L.; Li, Y.; Jiemjit, A.; Fandy, T.E.; Paietta, E.; Fernandez, H.; Tallman, M.S.; Greally, J.M.; Carraway, H.; et al. MDS and secondary AML display unique patterns and abundance of aberrant DNA methylation. Blood 2009, 114, 3448–3458. [Google Scholar] [CrossRef] [Green Version]
  5. Maegawa, S.; Gough, S.M.; Watanabe-Okochi, N.; Lu, Y.; Zhang, N.; Castoro, R.J.; Estecio, M.R.; Jelinek, J.; Liang, S.; Kitamura, T.; et al. Age-related epigenetic drift in the pathogenesis of MDS and AML. Genome Res. 2014, 24, 580–591. [Google Scholar] [CrossRef] [Green Version]
  6. Jiang, Y.; Dunbar, A.; Gondek, L.P.; Mohan, S.; Rataul, M.; O’Keefe, C.; Sekeres, M.; Saunthararajah, Y.; Maciejewski, J.P. Aberrant DNA methylation is a dominant mechanism in MDS progression to AML. Blood 2009, 113, 1315–1325. [Google Scholar] [CrossRef]
  7. Zhao, X.; Yang, F.; Li, S.; Liu, M.; Ying, S.; Jia, X.; Wang, X. CpG island methylator phenotype of myelodysplastic syndrome identified through genome-wide profiling of DNA methylation and gene expression. Br. J. Haematol. 2014, 165, 649–658. [Google Scholar] [CrossRef]
  8. Papaemmanuil, E.; Gerstung, M.; Malcovati, L.; Tauro, S.; Gundem, G.; van Loo, P.; Yoon, C.J.; Ellis, P.; Wedge, D.C.; Pellagatti, A.; et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood 2013, 122, 3616–3627. [Google Scholar] [CrossRef] [Green Version]
  9. Haferlach, T.; Nagata, Y.; Grossmann, V.; Okuno, Y.; Bacher, U.; Nagae, G.; Schnittger, S.; Sanada, M.; Kon, A.; Alpermann, T.; et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia 2014, 28, 241–247. [Google Scholar] [CrossRef] [Green Version]
  10. Heuser, M.; Yun, H.; Thol, F. Epigenetics in myelodysplastic syndromes. Semin. Cancer Biol. 2018, 51, 170–179. [Google Scholar] [CrossRef]
  11. Madzo, J.; Vasanthakumar, A.; Godley, L.A. Perturbations of 5-hydroxymethylcytosine patterning in hematologic malignancies. Semin. Hematol. 2013, 50, 61–69. [Google Scholar] [CrossRef] [PubMed]
  12. Reitman, Z.J.; Jin, G.; Karoly, E.D.; Spasojevic, I.; Yang, J.; Kinzler, K.W.; He, Y.; Bigner, D.D.; Vogelstein, B.; Yan, H. Profiling the effects of isocitrate dehydrogenase 1 and 2 mutations on the cellular metabolome. Proc. Natl. Acad. Sci. USA 2011, 108, 3270–3275. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Bond, D.R.; Lee, H.J.; Enjeti, A.K. Unravelling the Epigenome of Myelodysplastic Syndrome: Diagnosis, Prognosis, and Response to Therapy. Cancers 2020, 12, 3128. [Google Scholar] [CrossRef] [PubMed]
  14. Zimta, A.A.; Tomuleasa, C.; Sahnoune, I.; Calin, G.A.; Berindan-Neagoe, I. Long Non-coding RNAs in Myeloid Malignancies. Front. Oncol. 2019, 9, 1048. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Huang, H.H.; Chen, F.Y.; Chou, W.C.; Hou, H.A.; Ko, B.S.; Lin, C.T.; Tang, J.L.; Li, C.C.; Yao, M.; Tsay, W.; et al. Long non-coding RNA HOXB-AS3 promotes myeloid cell proliferation and its higher expression is an adverse prognostic marker in patients with acute myeloid leukemia and myelodysplastic syndrome. BMC Cancer 2019, 19, 617. [Google Scholar] [CrossRef] [Green Version]
  16. Kuang, X.; Chi, J.; Wang, L. Deregulated microRNA expression and its pathogenetic implications for myelodysplastic syndromes. Hematology 2016, 21, 593–602. [Google Scholar] [CrossRef] [Green Version]
  17. Kirimura, S.; Kurata, M.; Nakagawa, Y.; Onishi, I.; Abe-Suzuki, S.; Abe, S.; Yamamoto, K.; Kitagawa, M. Role of microRNA-29b in myelodysplastic syndromes during transformation to overt leukaemia. Pathology 2016, 48, 233–241. [Google Scholar] [CrossRef]
  18. Lyu, C.; Liu, K.; Jiang, Y.; Wang, T.; Wang, Y.; Xu, R. Integrated analysis on mRNA microarray and microRNA microarray to screen immune-related biomarkers and pathways in myelodysplastic syndrome. Hematology 2021, 26, 417–431. [Google Scholar] [CrossRef]
  19. Ghoshal, K.; Datta, J.; Majumder, S.; Bai, S.; Kutay, H.; Motiwala, T.; Jacob, S.T. 5-Aza-deoxycytidine induces selective degradation of DNA methyltransferase 1 by a proteasomal pathway that requires the KEN box, bromo-adjacent homology domain, and nuclear localization signal. Mol. Cell. Biol. 2005, 25, 4727–4741. [Google Scholar] [CrossRef] [Green Version]
  20. Hollenbach, P.W.; Nguyen, A.N.; Brady, H.; Williams, M.; Ning, Y.; Richard, N.; Krushel, L.; Aukerman, S.L.; Heise, C.; MacBeth, K.J. A comparison of azacitidine and decitabine activities in acute myeloid leukemia cell lines. PLoS ONE 2010, 5, e9001. [Google Scholar] [CrossRef]
  21. Dombret, H.; Seymour, J.F.; Butrym, A.; Wierzbowska, A.; Selleslag, D.; Jang, J.H.; Kumar, R.; Cavenagh, J.; Schuh, A.C.; Candoni, A.; et al. International phase 3 study of azacitidine vs conventional care regimens in older patients with newly diagnosed AML with >30% blasts. Blood 2015, 126, 291–299. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Fenaux, P.; Mufti, G.J.; Hellstrom-Lindberg, E.; Santini, V.; Finelli, C.; Giagounidis, A.; Schoch, R.; Gattermann, N.; Sanz, G.; List, A.; et al. Efficacy of azacitidine compared with that of conventional care regimens in the treatment of higher-risk myelodysplastic syndromes: A randomised, open-label, phase III study. Lancet Oncol. 2009, 10, 223–232. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Zeidan, A.M.; Stahl, M.; DeVeaux, M.; Giri, S.; Huntington, S.; Podoltsev, N.; Wang, R.; Ma, X.; Davidoff, A.J.; Gore, S.D. Counseling patients with higher-risk MDS regarding survival with azacitidine therapy: Are we using realistic estimates? Blood Cancer J. 2018, 8, 55. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Zeng, Y.; Chen, T. DNA Methylation Reprogramming during Mammalian Development. Genes 2019, 10, 257. [Google Scholar] [CrossRef] [Green Version]
  25. Dodge, J.E.; Okano, M.; Dick, F.; Tsujimoto, N.; Chen, T.; Wang, S.; Ueda, Y.; Dyson, N.; Li, E. Inactivation of Dnmt3b in mouse embryonic fibroblasts results in DNA hypomethylation, chromosomal instability, and spontaneous immortalization. J. Biol. Chem. 2005, 280, 17986–17991. [Google Scholar] [CrossRef] [Green Version]
  26. Gowher, H.; Jeltsch, A. Mammalian DNA methyltransferases: New discoveries and open questions. Biochem. Soc. Trans. 2018, 46, 1191–1202. [Google Scholar] [CrossRef]
  27. Jurkowska, R.Z.; Jurkowski, T.P.; Jeltsch, A. Structure and function of mammalian DNA methyltransferases. ChemBioChem Eur. J. Chem. Biol. 2011, 12, 206–222. [Google Scholar] [CrossRef]
  28. Klose, R.J.; Bird, A.P. Genomic DNA methylation: The mark and its mediators. Trends Biochem. Sci. 2006, 31, 89–97. [Google Scholar] [CrossRef]
  29. Margot, J.B.; Cardoso, M.C.; Leonhardt, H. Mammalian DNA methyltransferases show different subnuclear distributions. J. Cell. Biochem. 2001, 83, 373–379. [Google Scholar] [CrossRef]
  30. Dukatz, M.; Adam, S.; Biswal, M.; Song, J.; Bashtrykov, P.; Jeltsch, A. Complex DNA sequence readout mechanisms of the DNMT3B DNA methyltransferase. Nucleic Acids Res. 2020, 48, 11495–11509. [Google Scholar] [CrossRef]
  31. Lin, I.G.; Han, L.; Taghva, A.; O’Brien, L.E.; Hsieh, C.L. Murine de novo methyltransferase Dnmt3a demonstrates strand asymmetry and site preference in the methylation of DNA in vitro. Mol. Cell. Biol. 2002, 22, 704–723. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Takahashi, M.; Kamei, Y.; Ehara, T.; Yuan, X.; Suganami, T.; Takai-Igarashi, T.; Hatada, I.; Ogawa, Y. Analysis of DNA methylation change induced by Dnmt3b in mouse hepatocytes. Biochem. Biophys. Res. Commun. 2013, 434, 873–878. [Google Scholar] [CrossRef] [PubMed]
  33. Mortusewicz, O.; Schermelleh, L.; Walter, J.; Cardoso, M.C.; Leonhardt, H. Recruitment of DNA methyltransferase I to DNA repair sites. Proc. Natl. Acad. Sci. USA 2005, 102, 8905–8909. [Google Scholar] [CrossRef] [Green Version]
  34. Hervouet, E.; Vallette, F.M.; Cartron, P.F. Impact of the DNA methyltransferases expression on the methylation status of apoptosis-associated genes in glioblastoma multiforme. Cell Death Dis. 2010, 1, e8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Hervouet, E.; Peixoto, P.; Delage-Mourroux, R.; Boyer-Guittaut, M.; Cartron, P.F. Specific or not specific recruitment of DNMTs for DNA methylation, an epigenetic dilemma. Clin. Epigenetics 2018, 10, 17. [Google Scholar] [CrossRef] [PubMed]
  36. Khan, H.; Vale, C.; Bhagat, T.; Verma, A. Role of DNA methylation in the pathogenesis and treatment of myelodysplastic syndromes. Semin. Hematol. 2013, 50, 16–37. [Google Scholar] [CrossRef] [PubMed]
  37. Lopez, V.; Fernandez, A.F.; Fraga, M.F. The role of 5-hydroxymethylcytosine in development, aging and age-related diseases. Ageing Res. Rev. 2017, 37, 28–38. [Google Scholar] [CrossRef]
  38. Zhang, Y.; Zhou, C. Formation and biological consequences of 5-Formylcytosine in genomic DNA. DNA Repair 2019, 81, 102649. [Google Scholar] [CrossRef]
  39. Szulik, M.W.; Pallan, P.S.; Nocek, B.; Voehler, M.; Banerjee, S.; Brooks, S.; Joachimiak, A.; Egli, M.; Eichman, B.F.; Stone, M.P. Differential stabilities and sequence-dependent base pair opening dynamics of Watson-Crick base pairs with 5-hydroxymethylcytosine, 5-formylcytosine, or 5-carboxylcytosine. Biochemistry 2015, 54, 1294–1305. [Google Scholar] [CrossRef] [Green Version]
  40. Nimer, S.D. Myelodysplastic syndromes. Blood 2008, 111, 4841–4851. [Google Scholar] [CrossRef]
  41. Van Rompay, A.R.; Norda, A.; Linden, K.; Johansson, M.; Karlsson, A. Phosphorylation of uridine and cytidine nucleoside analogs by two human uridine-cytidine kinases. Mol. Pharmacol. 2001, 59, 1181–1186. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Creusot, F.; Acs, G.; Christman, J.K. Inhibition of DNA methyltransferase and induction of Friend erythroleukemia cell differentiation by 5-azacytidine and 5-aza-2′-deoxycytidine. J. Biol. Chem. 1982, 257, 2041–2048. [Google Scholar] [CrossRef] [PubMed]
  43. Ghoshal, K.; Datta, J.; Majumder, S.; Bai, S.; Dong, X.; Parthun, M.; Jacob, S.T. Inhibitors of histone deacetylase and DNA methyltransferase synergistically activate the methylated metallothionein I promoter by activating the transcription factor MTF-1 and forming an open chromatin structure. Mol. Cell. Biol. 2002, 22, 8302–8319. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Datta, J.; Ghoshal, K.; Motiwala, T.; Jacob, S.T. Novel Insights into the Molecular Mechanism of Action of DNA Hypomethylating Agents: Role of Protein Kinase C delta in Decitabine-Induced Degradation of DNA Methyltransferase 1. Genes Cancer 2012, 3, 71–81. [Google Scholar] [CrossRef] [Green Version]
  45. Easwaran, H.P.; Schermelleh, L.; Leonhardt, H.; Cardoso, M.C. Replication-independent chromatin loading of Dnmt1 during G2 and M phases. EMBO Rep. 2004, 5, 1181–1186. [Google Scholar] [CrossRef] [Green Version]
  46. Diesch, J.; Zwick, A.; Garz, A.K.; Palau, A.; Buschbeck, M.; Gotze, K.S. A clinical-molecular update on azanucleoside-based therapy for the treatment of hematologic cancers. Clin. Epigenetics 2016, 8, 71. [Google Scholar] [CrossRef] [Green Version]
  47. Stomper, J.; Rotondo, J.C.; Greve, G.; Lubbert, M. Hypomethylating agents (HMA) for the treatment of acute myeloid leukemia and myelodysplastic syndromes: Mechanisms of resistance and novel HMA-based therapies. Leukemia 2021, 35, 1873–1889. [Google Scholar] [CrossRef]
  48. Enderle, D.; Spiel, A.; Coticchia, C.M.; Berghoff, E.; Mueller, R.; Schlumpberger, M.; Sprenger-Haussels, M.; Shaffer, J.M.; Lader, E.; Skog, J.; et al. Characterization of RNA from Exosomes and Other Extracellular Vesicles Isolated by a Novel Spin Column-Based Method. PLoS ONE 2015, 10, e0136133. [Google Scholar] [CrossRef] [Green Version]
  49. Dong, L.; Lin, W.; Qi, P.; Xu, M.D.; Wu, X.; Ni, S.; Huang, D.; Weng, W.W.; Tan, C.; Sheng, W.; et al. Circulating Long RNAs in Serum Extracellular Vesicles: Their Characterization and Potential Application as Biomarkers for Diagnosis of Colorectal Cancer. Cancer Epidemiol. Biomark. Prev. Publ. Am. Assoc. Cancer Res. Cosponsored Am. Soc. Prev. Oncol. 2016, 25, 1158–1166. [Google Scholar] [CrossRef] [Green Version]
  50. Beylerli, O.; Gareev, I.; Sufianov, A.; Ilyasova, T.; Guang, Y. Long noncoding RNAs as promising biomarkers in cancer. Non-Coding RNA Res. 2022, 7, 66–70. [Google Scholar] [CrossRef]
  51. Ponting, C.P.; Oliver, P.L.; Reik, W. Evolution and functions of long noncoding RNAs. Cell 2009, 136, 629–641. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Cabili, M.N.; Trapnell, C.; Goff, L.; Koziol, M.; Tazon-Vega, B.; Regev, A.; Rinn, J.L. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 2011, 25, 1915–1927. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Zhang, Y.; Yang, L.; Chen, L.L. Life without A tail: New formats of long noncoding RNAs. Int. J. Biochem. Cell Biol. 2014, 54, 338–349. [Google Scholar] [CrossRef]
  54. Yin, Q.F.; Yang, L.; Zhang, Y.; Xiang, J.F.; Wu, Y.W.; Carmichael, G.G.; Chen, L.L. Long noncoding RNAs with snoRNA ends. Mol. Cell 2012, 48, 219–230. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Sun, Q.; Hao, Q.; Prasanth, K.V. Nuclear Long Noncoding RNAs: Key Regulators of Gene Expression. Trends Genet. TIG 2018, 34, 142–157. [Google Scholar] [CrossRef] [PubMed]
  56. Wilusz, J.E.; Freier, S.M.; Spector, D.L. 3′ end processing of a long nuclear-retained noncoding RNA yields a tRNA-like cytoplasmic RNA. Cell 2008, 135, 919–932. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Bill, M.; Papaioannou, D.; Karunasiri, M.; Kohlschmidt, J.; Pepe, F.; Walker, C.J.; Walker, A.E.; Brannan, Z.; Pathmanathan, A.; Zhang, X.; et al. Expression and functional relevance of long non-coding RNAs in acute myeloid leukemia stem cells. Leukemia 2019, 33, 2169–2182. [Google Scholar] [CrossRef]
  58. Qi, X.; Jiao, Y.; Cheng, C.; Qian, F.; Chen, Z.; Wu, Q. H22954, a novel long non-coding RNA down-regulated in AML, inhibits cancer growth in a BCL-2-dependent mechanism. Cancer Lett. 2019, 454, 26–36. [Google Scholar] [CrossRef]
  59. Carthew, R.W.; Sontheimer, E.J. Origins and Mechanisms of miRNAs and siRNAs. Cell 2009, 136, 642–655. [Google Scholar] [CrossRef] [Green Version]
  60. Ishizu, H.; Siomi, H.; Siomi, M.C. Biology of PIWI-interacting RNAs: New insights into biogenesis and function inside and outside of germlines. Genes Dev. 2012, 26, 2361–2373. [Google Scholar] [CrossRef]
  61. Kim, V.N.; Han, J.; Siomi, M.C. Biogenesis of small RNAs in animals. Nat. Rev. Mol. Cell Biol. 2009, 10, 126–139. [Google Scholar] [CrossRef] [PubMed]
  62. Buhler, M.; Verdel, A.; Moazed, D. Tethering RITS to a nascent transcript initiates RNAi- and heterochromatin-dependent gene silencing. Cell 2006, 125, 873–886. [Google Scholar] [CrossRef] [PubMed]
  63. Wan, C.; Wen, J.; Liang, X.; Xie, Q.; Wu, W.; Wu, M.; Liu, Z. Identification of miR-320 family members as potential diagnostic and prognostic biomarkers in myelodysplastic syndromes. Sci. Rep. 2021, 11, 183. [Google Scholar] [CrossRef]
  64. Wen, J.; Huang, Y.; Li, H.; Zhang, X.; Cheng, P.; Deng, D.; Peng, Z.; Luo, J.; Zhao, W.; Lai, Y.; et al. Over-expression of miR-196b-5p is significantly associated with the progression of myelodysplastic syndrome. Int. J. Hematol. 2017, 105, 777–783. [Google Scholar] [CrossRef]
  65. Veryaskina, Y.A.; Titov, S.E.; Kovynev, I.B.; Fedorova, S.S.; Pospelova, T.I.; Zhimulev, I.F. MicroRNAs in the Myelodysplastic Syndrome. Acta Nat. 2021, 13, 4–15. [Google Scholar] [CrossRef] [PubMed]
  66. Wang, H.; Zhang, T.T.; Jin, S.; Liu, H.; Zhang, X.; Ruan, C.G.; Wu, D.P.; Han, Y.; Wang, X.Q. Pyrosequencing quantified methylation level of miR-124 predicts shorter survival for patients with myelodysplastic syndrome. Clin. Epigenetics 2017, 9, 91. [Google Scholar] [CrossRef] [PubMed]
  67. Wu, D.H.; Yao, D.M.; Yang, L.; Ma, J.C.; Wen, X.M.; Yang, J.; Guo, H.; Li, X.X.; Qian, W.; Lin, J.; et al. Hypomethylation of let-7a-3 is associated with poor prognosis in myelodysplastic syndrome. Leuk. Lymphoma 2017, 58, 96–103. [Google Scholar] [CrossRef]
  68. Luo, S.; Lu, J.Y.; Liu, L.; Yin, Y.; Chen, C.; Han, X.; Wu, B.; Xu, R.; Liu, W.; Yan, P.; et al. Divergent lncRNAs Regulate Gene Expression and Lineage Differentiation in Pluripotent Cells. Cell Stem Cell 2016, 18, 637–652. [Google Scholar] [CrossRef]
  69. Plath, K.; Mlynarczyk-Evans, S.; Nusinow, D.A.; Panning, B. Xist RNA and the mechanism of X chromosome inactivation. Annu. Rev. Genet. 2002, 36, 233–278. [Google Scholar] [CrossRef]
  70. Pabst, T.; Mueller, B.U.; Zhang, P.; Radomska, H.S.; Narravula, S.; Schnittger, S.; Behre, G.; Hiddemann, W.; Tenen, D.G. Dominant-negative mutations of CEBPA, encoding CCAAT/enhancer binding protein-alpha (C/EBPalpha), in acute myeloid leukemia. Nat. Genet. 2001, 27, 263–270. [Google Scholar] [CrossRef]
  71. Di Ruscio, A.; Ebralidze, A.K.; Benoukraf, T.; Amabile, G.; Goff, L.A.; Terragni, J.; Figueroa, M.E.; De Figueiredo Pontes, L.L.; Alberich-Jorda, M.; Zhang, P.; et al. DNMT1-interacting RNAs block gene-specific DNA methylation. Nature 2013, 503, 371–376. [Google Scholar] [CrossRef] [Green Version]
  72. Esposito, C.; Autiero, I.; Basal, M.; Sandomenico, A.; Ummarino, S.; Borchiellini, M.; Ruvo, M.; Catuogno, S.; Ebralidze, A.; de Franciscis, V.; et al. Targeted systematic evolution of an RNA platform neutralizing DNMT1 function and controlling DNA methylation. bioRxiv 2020. bioRxiv:2020.07.29.226803. [Google Scholar]
  73. Yao, C.Y.; Chen, C.H.; Huang, H.H.; Hou, H.A.; Lin, C.C.; Tseng, M.H.; Kao, C.J.; Lu, T.P.; Chou, W.C.; Tien, H.F. A 4-lncRNA scoring system for prognostication of adult myelodysplastic syndromes. Blood Adv. 2017, 1, 1505–1516. [Google Scholar] [CrossRef]
  74. Merry, C.R.; Forrest, M.E.; Sabers, J.N.; Beard, L.; Gao, X.H.; Hatzoglou, M.; Jackson, M.W.; Wang, Z.; Markowitz, S.D.; Khalil, A.M. DNMT1-associated long non-coding RNAs regulate global gene expression and DNA methylation in colon cancer. Hum. Mol. Genet. 2015, 24, 6240–6253. [Google Scholar] [CrossRef] [Green Version]
  75. Fang, S.; Shen, Y.; Chen, B.; Wu, Y.; Jia, L.; Li, Y.; Zhu, Y.; Yan, Y.; Li, M.; Chen, R.; et al. H3K27me3 induces multidrug resistance in small cell lung cancer by affecting HOXA1 DNA methylation via regulation of the lncRNA HOTAIR. Ann. Transl. Med. 2018, 6, 440. [Google Scholar] [CrossRef]
  76. Fang, S.; Gao, H.; Tong, Y.; Yang, J.; Tang, R.; Niu, Y.; Li, M.; Guo, L. Long noncoding RNA-HOTAIR affects chemoresistance by regulating HOXA1 methylation in small cell lung cancer cells. Lab. Investig. J. Tech. Methods Pathol. 2016, 96, 60–68. [Google Scholar] [CrossRef] [Green Version]
  77. Zhou, W.; Xu, S.; Chen, X.; Wang, C. HOTAIR suppresses PTEN via DNMT3b and confers drug resistance in acute myeloid leukemia. Hematology 2021, 26, 170–178. [Google Scholar] [CrossRef]
  78. Wang, S.L.; Huang, Y.; Su, R.; Yu, Y.Y. Silencing long non-coding RNA HOTAIR exerts anti-oncogenic effect on human acute myeloid leukemia via demethylation of HOXA5 by inhibiting Dnmt3b. Cancer Cell Int. 2019, 19, 114. [Google Scholar] [CrossRef]
  79. Lee, P.; Yim, R.; Miu, K.K.; Fung, S.H.; Liao, J.J.; Wang, Z.; Li, J.; Yung, Y.; Chu, H.T.; Yip, P.K.; et al. Epigenetic Silencing of PTEN and Epi-Transcriptional Silencing of MDM2 Underlied Progression to Secondary Acute Myeloid Leukemia in Myelodysplastic Syndrome Treated with Hypomethylating Agents. Int. J. Mol. Sci. 2022, 23, 5670. [Google Scholar] [CrossRef]
  80. Diaz-Beya, M.; Brunet, S.; Nomdedeu, J.; Pratcorona, M.; Cordeiro, A.; Gallardo, D.; Escoda, L.; Tormo, M.; Heras, I.; Ribera, J.M.; et al. The lincRNA HOTAIRM1, located in the HOXA genomic region, is expressed in acute myeloid leukemia, impacts prognosis in patients in the intermediate-risk cytogenetic category, and is associated with a distinctive microRNA signature. Oncotarget 2015, 6, 31613–31627. [Google Scholar] [CrossRef] [Green Version]
  81. Jing, Y.; Jiang, X.; Lei, L.; Peng, M.; Ren, J.; Xiao, Q.; Tao, Y.; Tao, Y.; Huang, J.; Wang, L.; et al. Mutant NPM1-regulated lncRNA HOTAIRM1 promotes leukemia cell autophagy and proliferation by targeting EGR1 and ULK3. J. Exp. Clin. Cancer Res. CR 2021, 40, 312. [Google Scholar] [CrossRef] [PubMed]
  82. Li, Q.; Dong, C.; Cui, J.; Wang, Y.; Hong, X. Over-expressed lncRNA HOTAIRM1 promotes tumor growth and invasion through up-regulating HOXA1 and sequestering G9a/EZH2/Dnmts away from the HOXA1 gene in glioblastoma multiforme. J. Exp. Clin. Cancer Res. CR 2018, 37, 265. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Tseng, C.F.; Chen, L.T.; Wang, H.D.; Liu, Y.H.; Shiah, S.G. Transcriptional suppression of Dicer by HOXB-AS3/EZH2 complex dictates sorafenib resistance and cancer stemness. Cancer Sci. 2022, 113, 1601–1612. [Google Scholar] [CrossRef] [PubMed]
  84. Feng, Y.; Hu, S.; Li, L.; Zhang, S.; Liu, J.; Xu, X.; Zhang, M.; Du, T.; Du, Y.; Peng, X.; et al. LncRNA NR-104098 Inhibits AML Proliferation and Induces Differentiation Through Repressing EZH2 Transcription by Interacting with E2F1. Front. Cell Dev. Biol. 2020, 8, 142. [Google Scholar] [CrossRef] [Green Version]
  85. Saberwal, G.; Lucas, S.; Janssen, I.; Deobhakta, A.; Hu, W.Y.; Galili, N.; Raza, A.; Mundle, S.D. Increased levels and activity of E2F1 transcription factor in myelodysplastic bone marrow. Int. J. Hematol. 2004, 80, 146–154. [Google Scholar] [CrossRef] [PubMed]
  86. Szikszai, K.; Krejcik, Z.; Klema, J.; Loudova, N.; Hrustincova, A.; Belickova, M.; Hruba, M.; Vesela, J.; Stranecky, V.; Kundrat, D.; et al. LncRNA Profiling Reveals That the Deregulation of H19, WT1-AS, TCL6, and LEF1-AS1 Is Associated with Higher-Risk Myelodysplastic Syndrome. Cancers 2020, 12, 2726. [Google Scholar] [CrossRef]
  87. Wang, J.; Xie, S.; Yang, J.; Xiong, H.; Jia, Y.; Zhou, Y.; Chen, Y.; Ying, X.; Chen, C.; Ye, C.; et al. The long noncoding RNA H19 promotes tamoxifen resistance in breast cancer via autophagy. J. Hematol. Oncol. 2019, 12, 81. [Google Scholar] [CrossRef]
  88. Hu, B.; Yue, Q.F.; Chen, Y.; Bu, F.D.; Sun, C.Y.; Liu, X.Y. Expression of autophagy related gene BECLIN-1 and number of autophagic vacuoles in bone marrow mononuclear cells from 40 myelodysplastic syndromes patients and their significance. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2015, 23, 146–149. [Google Scholar]
  89. Chen, L.; Fan, X.; Zhu, J.; Chen, X.; Liu, Y.; Zhou, H. LncRNA MAGI2-AS3 inhibits the self-renewal of leukaemic stem cells by promoting TET2-dependent DNA demethylation of the LRIG1 promoter in acute myeloid leukaemia. RNA Biol. 2020, 17, 784–793. [Google Scholar] [CrossRef]
  90. Wei, W.; Ba, Z.; Gao, M.; Wu, Y.; Ma, Y.; Amiard, S.; White, C.I.; Rendtlew Danielsen, J.M.; Yang, Y.G.; Qi, Y. A role for small RNAs in DNA double-strand break repair. Cell 2012, 149, 101–112. [Google Scholar] [CrossRef] [Green Version]
  91. Gao, M.; Wei, W.; Li, M.M.; Wu, Y.S.; Ba, Z.; Jin, K.X.; Li, M.M.; Liao, Y.Q.; Adhikari, S.; Chong, Z.; et al. Ago2 facilitates Rad51 recruitment and DNA double-strand break repair by homologous recombination. Cell Res. 2014, 24, 532–541. [Google Scholar] [CrossRef] [PubMed]
  92. Pan, W.; Zhu, S.; Yuan, M.; Cui, H.; Wang, L.; Luo, X.; Li, J.; Zhou, H.; Tang, Y.; Shen, N. MicroRNA-21 and microRNA-148a contribute to DNA hypomethylation in lupus CD4+ T cells by directly and indirectly targeting DNA methyltransferase 1. J. Immunol. 2010, 184, 6773–6781. [Google Scholar] [CrossRef] [PubMed]
  93. Kim, Y.; Cheong, J.W.; Kim, Y.K.; Eom, J.I.; Jeung, H.K.; Kim, S.J.; Hwang, D.; Kim, J.S.; Kim, H.J.; Min, Y.H. Serum microRNA-21 as a potential biomarker for response to hypomethylating agents in myelodysplastic syndromes. PLoS ONE 2014, 9, e86933. [Google Scholar] [CrossRef] [PubMed]
  94. Xia, H.; Zhang, W.; Zhang, B.; Zhao, Y.; Zhao, Y.; Li, S.; Liu, Y. miR-21 modulates the effect of EZH2 on the biological behavior of human lung cancer stem cells in vitro. Oncotarget 2017, 8, 85442–85451. [Google Scholar] [CrossRef] [Green Version]
  95. Wang, X.X.; Zhang, H.; Li, Y. Preliminary study on the role of miR148a and DNMT1 in the pathogenesis of acute myeloid leukemia. Mol. Med. Rep. 2019, 19, 2943–2952. [Google Scholar]
  96. Garzon, R.; Liu, S.; Fabbri, M.; Liu, Z.; Heaphy, C.E.; Callegari, E.; Schwind, S.; Pang, J.; Yu, J.; Muthusamy, N.; et al. MicroRNA-29b induces global DNA hypomethylation and tumor suppressor gene reexpression in acute myeloid leukemia by targeting directly DNMT3A and 3B and indirectly DNMT1. Blood 2009, 113, 6411–6418. [Google Scholar] [CrossRef] [Green Version]
  97. Fabbri, M.; Garzon, R.; Cimmino, A.; Liu, Z.; Zanesi, N.; Callegari, E.; Liu, S.; Alder, H.; Costinean, S.; Fernandez-Cymering, C.; et al. MicroRNA-29 family reverts aberrant methylation in lung cancer by targeting DNA methyltransferases 3A and 3B. Proc. Natl. Acad. Sci. USA 2007, 104, 15805–15810. [Google Scholar] [CrossRef] [Green Version]
  98. Xu, L.; Xu, Y.; Jing, Z.; Wang, X.; Zha, X.; Zeng, C.; Chen, S.; Yang, L.; Luo, G.; Li, B.; et al. Altered expression pattern of miR-29a, miR-29b and the target genes in myeloid leukemia. Exp. Hematol. Oncol. 2014, 3, 17. [Google Scholar] [CrossRef] [Green Version]
  99. Qadir, X.V.; Han, C.; Lu, D.; Zhang, J.; Wu, T. miR-185 inhibits hepatocellular carcinoma growth by targeting the DNMT1/PTEN/Akt pathway. Am. J. Pathol. 2014, 184, 2355–2364. [Google Scholar] [CrossRef] [Green Version]
  100. Gurbuz, V.; Sozen, S.; Bilen, C.Y.; Konac, E. miR-148a, miR-152 and miR-200b promote prostate cancer metastasis by targeting DNMT1 and PTEN expression. Oncol. Lett. 2021, 22, 805. [Google Scholar] [CrossRef]
  101. Wang, H.; Wu, J.; Meng, X.; Ying, X.; Zuo, Y.; Liu, R.; Pan, Z.; Kang, T.; Huang, W. MicroRNA-342 inhibits colorectal cancer cell proliferation and invasion by directly targeting DNA methyltransferase 1. Carcinogenesis 2011, 32, 1033–1042. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Wang, H.; He, H.; Yang, C. miR-342 suppresses the proliferation and invasion of acute myeloid leukemia by targeting Naa10p. Artif. Cells Nanomed. Biotechnol. 2019, 47, 3671–3676. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Roscigno, G.; Quintavalle, C.; Donnarumma, E.; Puoti, I.; Diaz-Lagares, A.; Iaboni, M.; Fiore, D.; Russo, V.; Todaro, M.; Romano, G.; et al. MiR-221 promotes stemness of breast cancer cells by targeting DNMT3b. Oncotarget 2016, 7, 580–592. [Google Scholar] [CrossRef]
  104. Hussein, K.; Theophile, K.; Busche, G.; Schlegelberger, B.; Gohring, G.; Kreipe, H.; Bock, O. Significant inverse correlation of microRNA-150/MYB and microRNA-222/p27 in myelodysplastic syndrome. Leuk. Res. 2010, 34, 328–334. [Google Scholar] [CrossRef] [PubMed]
  105. Yun, J.; Ji, Y.S.; Jang, G.H.; Lim, S.H.; Kim, S.H.; Kim, C.K.; Bae, S.B.; Won, J.H.; Park, S.K. TET2 Mutation and High miR-22 Expression as Biomarkers to Predict Clinical Outcome in Myelodysplastic Syndrome Patients Treated with Hypomethylating Therapy. Curr. Issues Mol. Biol. 2021, 43, 917–931. [Google Scholar] [CrossRef] [PubMed]
  106. Song, S.J.; Ito, K.; Ala, U.; Kats, L.; Webster, K.; Sun, S.M.; Jongen-Lavrencic, M.; Manova-Todorova, K.; Teruya-Feldstein, J.; Avigan, D.E.; et al. The oncogenic microRNA miR-22 targets the TET2 tumor suppressor to promote hematopoietic stem cell self-renewal and transformation. Cell Stem Cell 2013, 13, 87–101. [Google Scholar] [CrossRef] [Green Version]
  107. Jiang, S.; Yan, W.; Wang, S.E.; Baltimore, D. Dual mechanisms of posttranscriptional regulation of Tet2 by Let-7 microRNA in macrophages. Proc. Natl. Acad. Sci. USA 2019, 116, 12416–12421. [Google Scholar] [CrossRef] [Green Version]
  108. Gonzales-Aloy, E.; Connerty, P.; Salik, B.; Liu, B.; Woo, A.J.; Haber, M.; Norris, M.D.; Wang, J.; Wang, J.Y. miR-101 suppresses the development of MLL-rearranged acute myeloid leukemia. Haematologica 2019, 104, e296–e299. [Google Scholar] [CrossRef] [Green Version]
  109. Castoro, R.J.; Dekmezian, M.; Saraf, A.J.; Watanabe, Y.; Chung, W.; Adhab, S.E.; Jelinek, J.; Issa, J.-P. Microrna 124 and Its Role in Response to Epigenetic Therapy in Patients with Acute Mylogenous Leukemia and Myelodysplastic Syndrome. Blood 2008, 112, 598. [Google Scholar] [CrossRef]
  110. Chen, L.; Jia, J.; Zang, Y.; Li, J.; Wan, B. MicroRNA-101 regulates autophagy, proliferation and apoptosis via targeting EZH2 in laryngeal squamous cell carcinoma. Neoplasma 2019, 66, 507–515. [Google Scholar] [CrossRef]
  111. Sabour Takanlu, J.; Aghaie Fard, A.; Mohammdi, S.; Hosseini Rad, S.M.A.; Abroun, S.; Nikbakht, M. Indirect Tumor Inhibitory Effects of MicroRNA-124 through Targeting EZH2 in The Multiple Myeloma Cell Line. Cell J. 2020, 22, 23–29. [Google Scholar] [PubMed]
  112. Majid, S.; Dar, A.A.; Saini, S.; Shahryari, V.; Arora, S.; Zaman, M.S.; Chang, I.; Yamamura, S.; Tanaka, Y.; Chiyomaru, T.; et al. miRNA-34b inhibits prostate cancer through demethylation, active chromatin modifications, and AKT pathways. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 2013, 19, 73–84. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Li, G.; Song, Y.; Zhang, Y.; Wang, H.; Xie, J. miR-34b Targets HSF1 to Suppress Cell Survival in Acute Myeloid Leukemia. Oncol. Res. 2016, 24, 109–116. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Overview of cells’ aberrations in epigenome of higher-risk MDS patients within the hematopoietic stem cell (HSC) compartment of bone marrow. Impaired gene expression implicated in maturation and differentiation of pluripotent stem cells give rise to myeloid lineage-committed cells showing further phenotypical as well as functional changes. MDS patients of the higher-risk group present significantly expanded granulocytic-monocytic progenitor cells and HSC compartments, while the megakaryocytic–erythroid progenitor cell population is severely reduced. Cellular and molecular changes are in line with the observed cytopenias and emergence of aberrant blast cells in the bone marrow and peripheral blood of higher-risk MDS patients. Aberrant cells characterized by the generation of multiple copies per cell, are indicated by a solid red star. Obstructed pathways of myelopoiesis and erythropoiesis are indicated within a transparent rectangle.
Figure 1. Overview of cells’ aberrations in epigenome of higher-risk MDS patients within the hematopoietic stem cell (HSC) compartment of bone marrow. Impaired gene expression implicated in maturation and differentiation of pluripotent stem cells give rise to myeloid lineage-committed cells showing further phenotypical as well as functional changes. MDS patients of the higher-risk group present significantly expanded granulocytic-monocytic progenitor cells and HSC compartments, while the megakaryocytic–erythroid progenitor cell population is severely reduced. Cellular and molecular changes are in line with the observed cytopenias and emergence of aberrant blast cells in the bone marrow and peripheral blood of higher-risk MDS patients. Aberrant cells characterized by the generation of multiple copies per cell, are indicated by a solid red star. Obstructed pathways of myelopoiesis and erythropoiesis are indicated within a transparent rectangle.
Ijms 23 16069 g001
Figure 2. RNAs capable of adopting stem-loop structures exhibit the potential to associate with DNA modifying enzymes depending on RNA secondary structure. The basis of this preferential interaction and targeting of specific CpGs lengthwise genome is the complementarity of DNA-RNA sequences. (A). Immature pre-miRNA clusters may bind and provide a scaffold for either DNMTs or TET enzymes to DNA sites for de novo DNA methylation or demethylation events, respectively. DNA hypermethylation prevents transcription, while even partial demethylation promotes transcription albeit at minimal levels (lower). (B). DNA sequences occupied by lncRNAs may prevent enzymatic modifications to DNA by obstructing enzymes from binding, which results in an ongoing transcriptional activity.
Figure 2. RNAs capable of adopting stem-loop structures exhibit the potential to associate with DNA modifying enzymes depending on RNA secondary structure. The basis of this preferential interaction and targeting of specific CpGs lengthwise genome is the complementarity of DNA-RNA sequences. (A). Immature pre-miRNA clusters may bind and provide a scaffold for either DNMTs or TET enzymes to DNA sites for de novo DNA methylation or demethylation events, respectively. DNA hypermethylation prevents transcription, while even partial demethylation promotes transcription albeit at minimal levels (lower). (B). DNA sequences occupied by lncRNAs may prevent enzymatic modifications to DNA by obstructing enzymes from binding, which results in an ongoing transcriptional activity.
Ijms 23 16069 g002
Table 1. Up- and down-regulated miRNAs in MDS, related KEGG pathways and targeted human genes. Data were extracted via mirPath v.3 tool provided by DIANATOOLS (https://dianalab.e-ce.uth.gr/html/mirpathv3/).
Table 1. Up- and down-regulated miRNAs in MDS, related KEGG pathways and targeted human genes. Data were extracted via mirPath v.3 tool provided by DIANATOOLS (https://dianalab.e-ce.uth.gr/html/mirpathv3/).
Upregulated miRNAs TissueImpaired KEGG PathwaysGene Targets within KEGG Pathway
miR-196b-5pBone marrowPI3K-Akt/TGFβ signaling BRAF, TGFBR1, E2F2, NRAS, AF1, CDKN1B, SMAD4, MYC, MAPK1, MDM2
ECM-receptor interaction ITGB1, ITGB8, THBS2, ITGA3, COL3A1, COL1A2, HMMR
cell cycle via MAPK signalingESPL1, CCNB1, E2F2, CDK2, CND2, SMC3, CDKN1B, STAG1, YWHAB, SMAD4, SKP2, MYC, PLK1, MDM2, MCM3
miR-320c, miR-320dBone marrowTGFβ signalingPPP2CA, SMAD3, ACVR2B, SMAD7, MAPK1
miR-422aBone marrow GNG12, MAPK1, GNG5, YAP1
miR-617Bone marrowRNA transport, translation initiationXPO1,
EIF5, EIF5B, EIF4G2
miR-181a, further divided to miR-181a-2-3p, miR-181a-3p and miR-181a-5pBone marrowSignaling pathways regulating pluripotency of stem cellsIGF1R, HESX1, WNT8A, POU5F1B, ACVR2B, JAK3
miR-222, further dived to miR-222-3p and miR-222-5pBone marrowPI3K-Akt/TGFβ signalingSOS2, CDK4, E2F2, CRKL, RUNX1,
CDKN1B, CDK6, E2F3, MYC, MAPK1, MDM2
cell cycle via MAPK signalingYWHAH, CDK4, E2F2, YWHAE,
YWHAG, CDKN1B, WEE1, CDK1, CDK6, ATM, CDKN1C, E2F3, MYC, YWHAZ, CDC20, BUB1B, CDC27, PRKDC, MDM2, CDC25A
miR-210, further divided to miR-210-3p and miR-210-5pBone marrowNo related pathway
let-7a, further divided to let-7a-2-3p, let-7a-3p and let-7a-5p Bone marrowcell cycle via MAPK signaling46 genes targeted/CREBBP, CDK6, WEE1, MAP3K1, ELK4, MAX and TAOK1 confirmed by more than 1 lists
FoxO, HIF-1 and PI3K-Akt signalingOver than 100 genes targeted/IRS2, CREBBP, BCL2L11, SLC2A1, TFRC, EFNA1, PRKAA1, COL4A1 and CDK6 confirmed by more than 1 lists
miRNA-34a (further dived to miRNA-34a-3p and -5p) in del(5q) MDS PI3K-Akt/TGFβ signaling35 genes targeted
cell cycle via MAPK signalingOver than 100 genes targeted/PRKDC, DUSP16 and MCM7 confirmed by more than 1 lists
Cell cycle and apoptosis via P53 signaling34 genes targeted/THBS1, confirmed by more than 1 lists
miRNA-125b-1-3p in translocation (p21;q23) MDSPlasma/bone marrowNo related pathway
miRNA-383 (further divided to miR-383-3p and -5p) in trisomy 8 MDSBone marrowNo related pathway
downregulated miRNAs
miR-29b further divided to miR-29b-1-5, -2-5p and -3pBone marrowPI3K-Akt/TGFβ signaling 63 genes targeted/PKN2, SGK1, NRAS, CCND1, YWHAB, CDK6, MCL1 and MDM2 confirmed by more than 1 lists
cell cycle via MAPK signaling33 genes targeted/MDM2, SMC1A, YWHAB, CCND1, CDK6, HDAC1 and WEE1 confirmed by more than 1 lists
Cell cycle and apoptosis via P53 signaling22 genes targeted/CCND1, CDK6 and MDM2 confirmed by more than 1 lists
FoxO signaling27 genes targeted/GF1R, NRAS, STK4, SGK1, MDM2, CCND1 and GABARAP confirmed by more than 1 lists
miR-130b-5pPlasmaCell cycle and apoptosis via P53 signalingZMAT3, CDK6, CHEK1, ATM, CCND1, MDM4,
RRM2, SESN3, SERPINE1, PPM1D, MDM2
miR-30e further divided to miR-30e-3p and -5pBone marrowCell cycle and apoptosis via TGFβ signalingFST, TGFBR1,SMAD2, THBS1, CUL1, INHBA,
DCN,MYC, PPP2R1A, SMURF1, ZFYVE9, BMP2, SP1, EP300, SMAD7, E2F4, MAPK1,
PPP2R1B, TGFBR2, BMPR2, RPS6KB1, the underlined confirmed by more than 1 lists
cell cycle via MAPK signaling39 genes targeted/MDM2, SMAD2, YWHAZ, PRKDC, STAG2, MYC, CDK6, CCNB1 and E2F3 confirmed by more than 1 lists
Cell cycle and apoptosis via P53 signaling24 genes targeted/MDM2, CDK6, CCNB1, CCNG1, CASP3 and SIAH1 confirmed by more than 1 lists
RNA transport, translation initiation37 genes targeted/XPO1, NCBP1 and RANBP2 confirmed by more than 1 lists
miR-221 further divided to miR-221-3p and -5pPlasmamRNA surveillance pathway21 genes targeted/ACIN1 and PABPC1 confirmed by more than 1 lists
cell cycle via MAPK signaling26 genes targeted/CCND1 confirmed by more than 1 lists
Cell cycle and apoptosis via P53 signaling50 genes targeted/EFNA1, CDKN1B, CCND1 and ATF4 confirmed by more than 1 lists
miRNA-194-5pBone marrowUbiquitin mediated proteolysisWWP1, TRIP12, CBLB, BIRC6, SMURF1, DDB1, CDC23, RBX1, UBE2W, UBE2B, PIAS1,
CUL4B
miRNA-146a (further dived to miRNA-146a-3p and -5p) in del(5q) MDSPeripheral blood mononuclear cellscell cycle via MAPK signalingGSK3B, CCNB1, CDC25B, YWHAG, CDKN1B,
SMAD4, RBL1, CDC23, CDKN1A, PRKDC, MDM2, ABL1, CDC25A
miRNA-125b-1 No related pathway
Table 2. Epigenetic enzymes coregulated by lncRNAs and miRNAs and implicated in MDS and AML.
Table 2. Epigenetic enzymes coregulated by lncRNAs and miRNAs and implicated in MDS and AML.
Non-Coding RNAEpigenetic Enzyme TargetedDisease/Tissue of InvestigationGene/Function ImplicatedPossible Relation in MDS/AML Pathogenesis
MAGI2-AS3-lncRNA ↑TET2AMLLRIG1 [89] -
HOTAIR-lncRNA ↑DNMT3B
↑EZH2, DNMT1/3B
AML
SCLC
PTEN [77], ↓HOXA5 [78]
HOAX1 [76]
-
HOXB-AS3-lncRNA ↕EZH2Liver cancerDICER1 [83]Implicated in myeloid cell proliferation with adverse prognosis in AML and MDS [15]
H19-lncRNA ↨DNMT3BBCBECN1/
autophagy [87]
Associated with adverse prognosis in MDS patients [86]
BECN1 is also implicated in MDS autophagy [88]
HOTAIRM1-lncRNA ↨EZH2/DNMTsGBHOAX1 [82]Associated with leukemia cell autophagy and proliferation and adverse prognosis in NPM1-mutated AML [80,81]
NR-104098-lncRNA ↓EZH2 (via E2F1)AML Inhibits AML proliferation
& Induces differentiation [84]
-
CEBPA-lncRNA↨DNMT1AML CEBPA [71,72]-
DACOR1-lncRNA ↨DNMT1CRCWhole genome demethylation [74]MDS have abnormal methylation patterns across many genomic regions [4,5,6,7]
miR-22↓TET2HSCprovoke MDS in mice [106]Significant prognostic value in MDS treated with HMAs [105]
Let-7 family↓TET2murine macrophages IL-6 [107]Altered methylation and expression profiles in MDS [10,11]
miR-101↓EZH2LSCC ↓autophagy, proliferation & ↑apoptosis [110]Reduces incidence and delays the onset and progression of AML in mice [108]
miR-124↓EZH2MMCDKN2A
↓proliferation &viability of myeloma cell line [111]
Potential marker of response to DAC in MDS/AML [109]
miR-21 ↓EZH2
↓DNMT1
Lung cancer
SLE
Cdc2, cyclinB1, BLC-2 [94]
aberrant DNA hypomethylation [92]
Potential biomarker of epigenetic therapy in MDS [93]
miR-29b↓DNTM3A/B, ↓DNMT1AMLglobal DNA hypomethylation [96] -
miR-29a↓DNTM3A/BLung cancerRe-expression of methylation-silenced tumor suppressor genes [97]Downregulated in AML [98]
miR-221↓DNTM3BBC ↓ methylation levels of Nanog & Oct 3 [103]Decreased levels in AML evolving from MDS [104]
miR-185↓DNMT1HCCPTEN/Akt pathwayPTEN is associated with HMA resistance in MDS and progression to AML [79]
miR-152↓DNMT1PCPTENPTEN is associated with HMA resistance in MDS and progression to AML [79]
miR-148a↓DNMT1SLE
AML
aberrant DNA hypomethylation [92]
↑miR-148a, mutual negative feedback loop/↓cell proliferation & ↑ apoptosis [95]
-
miR-34b↓DNMT1, HDAC1, HDAC2 & HDAC4PC↓proliferation through demethylation/active chromatin modifications/Akt pathway [112]Cell viability inhibition/enhance cell apoptosis in AML cell lines [113]
miR-342↓DNMT1CRC↓ cancer cell proliferation & invasionDownregulation in AML [102]
↑ upregulated, ↓ downregulated, ↕ recruit, ↨ inhibit connection, Acute myeloid leukemia = AML, Small cell lung carcinoma = SCLC, Breast cancer = BC, Glioblastoma = GB, Colorectal cancer = CRC, Hematopoietic stem cell = HSC, laryngeal squamous cell carcinoma = LSCC, multiple myeloma = MM, Systemic Lupus Erythematosus = SLE, hepatocellular carcinoma = HCC, prostate cancer = PC.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Symeonidis, A.; Chatzilygeroudi, T.; Chondrou, V.; Sgourou, A. Contingent Synergistic Interactions between Non-Coding RNAs and DNA-Modifying Enzymes in Myelodysplastic Syndromes. Int. J. Mol. Sci. 2022, 23, 16069. https://doi.org/10.3390/ijms232416069

AMA Style

Symeonidis A, Chatzilygeroudi T, Chondrou V, Sgourou A. Contingent Synergistic Interactions between Non-Coding RNAs and DNA-Modifying Enzymes in Myelodysplastic Syndromes. International Journal of Molecular Sciences. 2022; 23(24):16069. https://doi.org/10.3390/ijms232416069

Chicago/Turabian Style

Symeonidis, Argiris, Theodora Chatzilygeroudi, Vasiliki Chondrou, and Argyro Sgourou. 2022. "Contingent Synergistic Interactions between Non-Coding RNAs and DNA-Modifying Enzymes in Myelodysplastic Syndromes" International Journal of Molecular Sciences 23, no. 24: 16069. https://doi.org/10.3390/ijms232416069

APA Style

Symeonidis, A., Chatzilygeroudi, T., Chondrou, V., & Sgourou, A. (2022). Contingent Synergistic Interactions between Non-Coding RNAs and DNA-Modifying Enzymes in Myelodysplastic Syndromes. International Journal of Molecular Sciences, 23(24), 16069. https://doi.org/10.3390/ijms232416069

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop