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Review

Current Approaches to Epigenetic Therapy

by
Ekaterina D. Griazeva
1,
Daria M. Fedoseeva
1,†,
Elizaveta I. Radion
1,*,†,
Pavel V. Ershov
1,
Ivan O. Meshkov
1,
Alexandra V. Semyanihina
1,2,3,
Anna S. Makarova
1,
Valentin V. Makarov
1,
Vladimir S. Yudin
1,
Anton A. Keskinov
1 and
Sergey A. Kraevoy
1
1
Federal State Budgetary Institution, Centre for Strategic Planning and Management of Biomedical Health Risks of the Federal Medical Biological Agency, Pogodinskaya Str., 10, Building 1, Moscow 119121, Russia
2
Federal State Budgetary Institution “N.N. Blokhin National Medical Research Center of Oncology” of the Ministry of Health of the Russian Federation (N.N. Blokhin NMRCO), Kashirskoe Shosse, 24, Moscow 115478, Russia
3
Federal State Budgetary Scientific Institution, Research Centre for Medical Genetics, Moskvorechye, 1, Moscow 115522, Russia
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Epigenomes 2023, 7(4), 23; https://doi.org/10.3390/epigenomes7040023
Submission received: 24 August 2023 / Revised: 14 September 2023 / Accepted: 17 September 2023 / Published: 30 September 2023
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Abstract

:
Epigenetic therapy is a promising tool for the treatment of a wide range of diseases. Several fundamental epigenetic approaches have been proposed. Firstly, the use of small molecules as epigenetic effectors, as the most developed pharmacological method, has contributed to the introduction of a number of drugs into clinical practice. Secondly, various innovative epigenetic approaches based on dCas9 and the use of small non-coding RNAs as therapeutic agents are also under extensive research. In this review, we present the current state of research in the field of epigenetic therapy, considering the prospects for its application and possible limitations.

1. Introduction

Epigenetic regulation of gene expression implies changes in gene activity without altering the coding sequence. This process depends on the balance of enzymes that catalyze reversible modifications of histones and DNA molecules [1]. Disruption of this balance may trigger the development of various diseases [2,3,4,5,6]. Currently, new approaches to correcting epigenetic mistakes are being actively developed due to progress in molecular biology methods. Indeed, NGS, as well as methylation assays, allowed us to identify new molecular targets for epigenetic therapy. Also, the boost in understanding of non-coding RNA biology contributed to progress in the treatment of certain diseases.
The prime reason for epigenetic mistakes is the dysregulation of histone- and DNA-modifying enzyme activity. To correct aberrant DNA and chromatin modifications, the following approaches are being proposed: First, low-molecular-weight (LMW) inhibitors of epigenetic regulators are being extensively studied. Despite the relative ease of use, the main drawback of LMW is its low specificity and increased risk of side effects. However, the development of CRISPR/Cas9 technology helps to address such a problem by increasing editing specificity. The core of this approach is dCas9 (dead Cas9), a catalytically inactive Cas9 that is unable to introduce double-strand DNA breaks but retains guide RNA binding activity. In therapeutic approaches, dCas9 can serve as a targeting platform for various effector proteins [7]. Indeed, dCas9 fusions with either transcriptional activators or repressors allow for the regulation of target gene expression. Next, the use of non-coding RNAs (ncRNAs) (siRNA, miRNA, etc.) empowers the degradation or posttranscriptional silencing of specific mRNA [8], which may be useful for the therapy of malignancies associated with dysregulation in oncogene expression [9]. All the existing epigenetic therapy approaches share problems of target delivery, off-target effects, and immunogenicity [10,11]. Given all the limitations, very few epigenetic drugs have been introduced into clinical practice so far; moreover, further research is needed in the epigenetic therapy field. In this review, we discuss the current state of research on epigenetic therapy in terms of prospects and limitations.

2. Pharmacotherapeutic Approach for Epigenome Modulation

To date, the use of LMW as an inhibitor of epigenetic regulators is the most developed approach in epigenetic therapy. There are several LMW-based epigenetic drugs in clinical practice, and in this chapter of the review, we consider the most striking examples of them [12].
To collect contemporary data for the last five years on preclinical and clinical trials of LMW-based epigenetic drugs, we used the Cortellis (Clarivate Analytics, Philadelphia, PA, USA) database. The database contains information on multiple patents on epigenetic drugs. Figure 1 and Figure 2 illustrate the current state of DNA- and histone-modifying enzyme-based drug development. Quite a few of the patents consider the use of LMW-based inhibitors of epigenetic regulators.
As such, LMW targets the NAD-dependent deacetylase sirtuin-1 (SIRT1), which is mentioned in 175 patents. Next, inhibitors of O6-methylguanine-DNA methyltransferase (MGMT), histone acetyltransferase p300 (EP300), DNA methyltransferase 1 (DNMT1), DNA methyltransferase-3-β (DNMT3B), histone deacetylase 1 (HDAC1), and histone deacetylase 6 (HDAC6) were cited in 85, 72, 61, 63, 60, and 66 patents, respectively. In addition, a few more clinical trials are being conducted, namely clinical trials of DNMTs and HDAC inhibitors (see Table 1). At the same time, many epigenetic inhibitors are being studied in the early phases of clinical trials alone or in combination with conventional therapy (Table 1). For example, three clinical trials are devoted to the study of the safety and efficacy of the DNMT inhibitors guadecitabine (SGI-110) [13] and azacytidine (Vidaza) [14]. Also, several clinical trials of HDAC inhibitors are being conducted, e.g., NCT01997840 (active status), NCT04231448, and NCT04674683 (recruiting status). As for LMW combination with conventional therapy, the striking example is the use of Chidamide [15], which is being studied in seven clinical trials in the III and IV phases. The next example is the use of O6-benzylguanine, an O6-alkylguanine-DNA alkyltransferase (AGT) inhibitor, in combination with standard therapy, which slows down the progression of glioblastoma and gliosarcoma in comparison with temozolomide treatment [16]. As for azacitidine, a single cohort study by Ruan and colleagues first demonstrated that the oral form of azacitidine in combination with the CHOP regimen (Cyclophosphamide, Doxorubicin, Oncovin and Prednisolone) showed good effectiveness [17]. In this case, the overall objective response rate was 85% (n = 20), and moreover, 55% of patients showed a complete response to treatment. However, not all combinations of epigenetic drugs with conventional treatment show superior efficacy. For example, in phase II/III of clinical trial NCT02472145, the use of a combination of the anti-CD123 (interleukin 3 receptor) monoclonal antibody talakotuzumab with the DNMT inhibitor decitabine was not more efficient than the treatment with decitabine alone in patients with acute myeloid leukemia (AML) [18]. The next example, guadecitabine, is a prodrug that is more active in vivo than decitabine. In AML treatment, 8 of 56 patients responded to guadecitabine, which demonstrated an increase in overall survival from 7.1 to 17.9 months compared to decitabine [19,20]. Another therapeutic scheme for AML that is currently in phase I of a clinical trial (EudraCT No. 2018-000482-36) uses iadademstat (ORY-1001), a selective inhibitor of lysine-specific histone demethylase (KDM1A) [21]. This protocol demonstrated good safety as well as clinical activity. To assess the effectiveness of iadademstat in combination with etoposide and cisplatin in patients with recurrent small cell lung cancer, a study called CLEPSIDRA (EudraCT No. 2018-000469-35) was initiated. The study showed that iadademstat alone reduces tumor growth by 90%, moreover, in combination with chemotherapy, it increases progression-free survival by up to 50% [22].
Another example is seclidemstat, a KDM1A inhibitor, alone or in combination with chemotherapy, which is going to be studied in a phase I clinical trial (NCT03600649) with the enrollment of 50 patients with relapsed or refractory sarcomas. Preclinical studies of seclidemstat showed significant inhibition of tumor growth in neoplasms with KDM1A overexpression [23].
Tumor-associated histone deacetylases (HDAC1–HDAC10 isoforms) are considered promising molecular targets for cancer therapy [24]. Table 2 shows the list of approved and experimental drugs aimed at both isoforms (e.g., abexinostat) as well as broad-spectrum HDAC inhibitors (e.g., vorinostat and pracinostat). It is interesting to note that a number of statin-related drugs are viewed as HDAC inhibitors; however, the molecular mechanisms underlying their effects are only just beginning to be explored. For example, Lin and colleagues showed that statins block the activity of HDAC2 indirectly through the induction of histone H3 acetylation in the promoter region of the p21 gene [25]. Bridgeman and colleagues suggested that statins do not directly affect the activity of HDACs and HATs (histone acetyltransferases) since the degree of histones H3 and H4 acetylation did not change when compared to the control. At the same time, there was some increase in the activity of DNA methyltransferases [26].
LMW HDAC inhibitors can also affect the activity of other proteins. Based on the chemical structure of nine different HDAC inhibitors (vorinostat, pracinostat, atorvastatin, mocetinostat, valproic acid, bufexamac, trichostatin A, abexinostat, and fingolimod) as well as using the DRUDIT web-based tool [27], 29 non-specific drug targets were predicted, 15 of which took part in metabolic and signaling pathways (Table 3). Therefore, the use of HDAC inhibitors may result in systemic non-specific (off-target) effects on various cellular pathways [28]. The problem of low LMW selectivity and off-target effects may be solved by the development of alternative therapeutic approaches. As such, new protocols that use effector proteins, ncRNAs, as well as biotherapeutic agents (small proteins, DARPins (designed ankyrin repeat proteins), and monoclonal antibodies) should be developed. Unfortunately, only a limited number of such innovative drugs are gradually being introduced into clinical practice.

Oncometabolites and Metabolic Rewiring

The expression of metabolic enzymes was demonstrated to be altered in several cancer types [30]. A high frequency of somatic mutations in IDH1 (isocitrate dehydrogenase 1), FH (fumarate hydratase), as well as SDH A–D and F (succinate dehydrogenase) genes is observed in gliomas, hepatobiliary cancers, neuroendocrine carcinomas, renal cell carcinomas, and melanomas [31]. These mutations lead to enzymatic activity deregulation and the accumulation of so-called "oncometabolites." Oncometabolites can activate oncogenic signaling cascades [32], induce deregulation of epigenetic patterns, resistance to alkylating agents, collagen maturation impairment, inhibition of protein succination, etc. [33,34,35].
Since oncometabolites cause global metabolic rewiring in cancer cells [34], pharmacological targeting of enzymes with altered activity should be considered in cancer therapy [36,37]. Recent achievements in the development of inhibitors of mutant IDH1 and IDH2 are discussed in the reviews by W. Tian and co-authors [38] as well as Issa & DiNardo [39]. The ClinicalTrials.gov database contains information on studies of metabolic reprogramming therapy in cancer patients. Table 4 contains summary information on the most prominent examples of metabolite reprogramming in cancer therapy. Thus, the pharmacotherapeutic "management" of cellular metabolite levels demonstrates high potential in cancer therapy.

3. Innovative Molecular and Genetic Approaches to the Modulation of Epigenetic Regulation

3.1. CRISPR/Cas9

CRISPR/Cas9 is a genome editing platform based on the Cas9 endonuclease, which introduces double-strand breaks in DNA sequences complementary to the corresponding guide RNA (gRNA). Despite the accuracy of targeting, gRNAs may have sites of incomplete homology. In this case, the nuclease introduces DNA breaks in random places, which can lead to undesirable consequences, so-called "off-target effects."
The problem of non-specific DNA breaks may be solved by using the modified Cas9 protein, dCas9. The dCas9, carrying substitutions D10A and H841A, is unable to introduce double-strand DNA breaks but retains the gRNA binding activity [7]. dCas9 can be fused in-frame to various effector proteins, providing a platform for their targeting to the locus of interest. Different epigenetic modulators—either transcriptional activators or repressors—may act as such effectors. In early works, dCas9 was fused with either p300 (human acetyltransferase catalytic core p300), p65 (endogenous transcription factor p65 (NFkB subunit), p65 with HSF1 (heat shock factor 1), or VP64 (herpesvirus transcription factor) [40,41,42,43]. These activation systems, so-called CRISPRa (CRISPR activation), such as dCas9-p300, may act by histone acetylation in target sites, or alternatively, like dCas9-p65, may directly activate genes by recruiting transcription factors. For example, the activating effect of VP16 [44] is based on the recruitment of the RNA polymerase preinitiation complex to the transcription start site, followed by the activation of transcription of the target gene. However, the activation capability of VP16 alone is very low, so to cope with this limitation, most CRISPRa protocols use VP16 multimers (VP48, VP64, VP160, and VP192) in combination with other activators [45,46]. One such example is dCas9-VPR, which is composed of VP64-p65-RTA, where VP64 consists of four VP16 subunits and RTA is an Epstein-Barr virus transcription factor. The dCas9-VPR complex is significantly more effective than early variants [47,48].
Despite the visible activation effect, the early dCas9-based activation systems share the same limitation and require multiple gRNAs targeted to extended genome regions to achieve reliable activation. The more recent CRISPR-Cas9 technologies such as SunTag, Scaffold, Casilio, SAM, and TREE allow target genes to be activated with fewer or even a single gRNA. For example, dCas9-SunTag uses dCas9 fused to the GCN4 peptide array, which, in turn, binds scFv-GCN4-fused effector proteins [49,50]. Thus, SunTag allows the concurrent use of numerous effector domains to enhance epigenetic activation. Alternately, complexes of dCas9 with an RNA scaffold work in a different way: the modified guide RNA contains aptamer sequences (MS2, PP7) that are recognized by corresponding RNA-binding proteins (MCP, PCP). Transcriptional activators fused to these proteins are recruited to the dCas9-scaffold-RNA complex and enhance target gene transcription activation [51]. As an improvement of this, the dCas9-Casilio uses shorter Casilio aptamers in the gRNA sequence, enhancing gRNA stability and efficiency [52]. The next approach, SAM, is a combination of dCas9 fused to transcription activators with scaffolding to enhance target gene activation [53,54]. Finally, the TREE system combines the SunTag and scaffold, allowing for up to 32 copies of VP64 or p65-HSF1 to be recruited [55].
CRISPRi (CRISPR interference), the use of dCas9 to repress target gene expression, employs the fusion of functional domains of repressor proteins with dCas9. For instance, the KRAB (Krüppel-associated box) domain of several repressor proteins, such as EZH2 (Enhancer of Zeste 2 Polycomb Repressive Complex 2 subunit), is widely used in CRISPRi approaches [56,57,58]. dCas9-KRAB can recruit histone deacetylases and methyltransferases to the promoters and enhancers of target genes [59]. Being recruited, the histone methyltransferases introduce corresponding histone methyl marks, leading to heterochromatin formation and transcription repression [60,61]. Just like CRISPRa, CRISPRi suffers from some limitations. For example, the repression effect of individual use of either dCas9-KRAB or dCas9-EZH2 is temporary. To cope with this problem and achieve constant transcription repression, the combination of dCas9-KRAB/EZH2 with either dCas9-DNMT3A-3L or Cas9-SunTag-DNMT3A may be used [62,63,64,65].
Another repressive system is dCas9-KRAB-MeCP2, in which MECP2 (methyl-CpG binding protein 2) recruits histone demethylases and deacetylases independently of KRAB [66,67]. The MECP2 protein binds to 5-methylcytosines in CpG islands of promoters of target genes, repressing their transcription. The dCas9-KRAB-MeCP2 repression efficiency is significantly higher than for dCas9-KRAB [67]. Another system, dCas9-LSD1, may also be utilized for transcriptional repression. LSD1 (KDM1A, lysine-specific demethylase-1) removes methyl groups from H3K4me1/2, an active chromatin mark [68], which in turn leads to H3K27 deacetylation and heterochromatin formation [69].
dCas9 platforms for epigenetic regulation have some drawbacks that complicate their use in gene therapy. Firstly, the existing delivery systems have significant limitations in terms of transfer capacity. For instance, the size of the dCas9 ORF is 4.1 kb, which practically corresponds to the capacity of AAV vectors (4.7 kb). Alternatively, the packaging capacity of lentiviral vectors is about 8 kb, but they are mainly used for ex-vivo therapy. The second limitation of dCas9-based therapy is the duration of its therapeutic effect. The span of the dCas9-based epigenetic regulation effect is currently unknown; moreover, it may vary in each particular case. Next, off-target effects also hinder the translation of dCas9-based technologies into clinical practice. The degree of off-target effects should be studied in each case; moreover, the harm of off-target effects may outweigh the benefit of the therapeutic protocol. The development of dCas9-based gene therapy methods is a new direction in science, and no wonder it has many unresolved questions that take time to answer. So far, only a very limited number of dCas9-based technologies have reached the stage of preclinical and clinical trials. For example, only one clinical trial of the CRISPRa drug CRD-TMH-001 for the treatment of DMD (Duchenne Muscular Dystrophy) has been FDA-approved (NCT05514249). The drug is based on rAAV9 delivery of the dCas-VP65 transgene for upregulation of cortical dystrophin. Unfortunately, in this trial, the potential benefit of the therapy outweighed the risk to the patient’s immune system. Nevertheless, many studies have already been carried out on cell cultures and animal models. In the following part of this review, we will provide examples of dCas9-based epigenetic regulation in research on various therapy protocols.
The use of dCas9 in cancer therapy is an area of great interest. One such example is the epigenetic activation of the PTEN (phosphatase and tensin homolog) gene [48]. Abnormal PTEN expression is observed in many cancer types; moreover, even minor changes in PTEN expression affect the prognosis of many highly aggressive malignancies [70]. The decrease in PTEN expression may be a result of a variety of factors, including mutations and epigenetic silencing. In the latter case, the CRISPRa protocols may be used. In the work of Moses et al., PTEN expression activation was achieved by dCas-VPR in TNBC and SK-MEL-28 cells. The authors showed that PTEN activation significantly suppresses AKT, mTOR, and MAPK signaling and reduces cell migration and colony formation in the presence of B-Raf and PI3K/mTOR inhibitors [48]. Thus, dCas9-mediated PTEN activation may provide an alternative approach to treating aggressive cancers resistant to current therapeutic protocols.
One more noteworthy example of gene expression epigenetic regulation in cancer therapy is the study on hepatocellular carcinoma cells by Wang et al. Hepatocellular carcinoma is the most common primary liver cancer. In the work of Wang et al., the GRN (granulin) was chosen as a therapeutic target. Increased GRN expression is observed in many neoplasias, especially in hepatocellular carcinoma. The authors used dCas9-KRAB to epigenetically target GRN in hepatic carcinoma cells and demonstrated its effect on Hep3B carcinoma cells [71]. The next example of dCas9-based epigenetic therapy is the study of FSHD (facioscapulohumeral muscular dystrophy) treatment. The disease is caused by abnormal epigenetic modifications in the D4Z4 DNA tandem repeat array, which is located in the subtelomeric region of chromosome 4q35 [72,73]. Each repeat contains DUX4 (Double Homeobox 4) ORF. During early development, the DUX4 protein upregulates the expression of many genes whose aberrant expression in adult skeletal muscle can lead to pathology. In the work of Himeda et al., the authors showed that targeting either the promoter or the first exon of DUX4 by dSaCas9 fused with epigenetic repressors significantly reduced the expression level of DUX4 in myocytes from biopsies of FSHD patients [72]. Another interesting example is the activation of SCN1A (Sodium Voltage-Gated Channel Alpha Subunit 1) gene expression by dCas9-fused epigenetic activators. The SCN1A encodes for the α-subunit of the voltage-gated sodium channel Nav1.1. Mutations in the SCN1A are associated with Dravet Syndrome (DS, severe myoclonic epilepsy in infancy), a drug-resistant epileptic encephalopathy. The main genetic cause of DS is haploinsufficiency of the SCN1A gene. Indeed, SCN1A+\− mice develop neurological symptoms, including severe epilepsy, behavioral changes, and premature death [74]. Given that one copy of the SCN1A is still functional, stimulation of its expression may lead to an increase in Nav1.1 production and, as a result, symptom relief. In recent work, Colasante and colleagues demonstrated stable activation of SCN1A transcription in P19 mouse teratocarcinoma cells using dCas9-VP160. The authors also showed the ability of dCas9-VP160 to modulate SCN1A activity in primary neurons by increasing the level of Nav1.1. Moreover, the authors revealed that dCas9-VP64 efficiently stimulates SCN1A expression in GABAergic interneurons in vivo when delivered by means of AAV9 [75].
Recently, dCas9-based approaches have begun to be studied in the context of genomic imprinting disorders. A striking example is the use of dCas9 for epigenetic regulation in Prader-Willi syndrome (PWS). PWS, a typical genomic imprinting disorder, is a complex neurobehavioral disease with a birth incidence of 1/12,000 to 1/32,000 [76,77]. The disease is caused by a deficiency in gene expression on the 15q11–q13 locus of the paternal chromosome [76]. Gene expression in this region is regulated by an imprinting center (PWS-IC), which is located upstream of the paternally expressed SNRPN (small nuclear ribonucleoprotein polypeptide N) gene. PWS-IC is methylated on the maternal chromosome, repressing the PWS candidate genes, but is not methylated on the paternal chromosome. 23 genes are mapped in the 15q11–q13 region, including the SNORD116 cluster and 15 other genes. 12 of them are subjected to genomic imprinting and are only expressed on the paternal chromosome. In PWS patients, the expression of these genes is absent due to molecular defects in the 15q11–q13 region of the paternal chromosome. The modulation of the epigenetic state of the imprinting domain can restore the PWS genes’ expression on the maternal chromosome, providing a therapeutic effect in PWS patients. For example, it is possible to use dCas9-LSD1 to demethylate H3K9me2 in the PWS-IC of the maternal chromosome, resulting in the reactivation of SNRPN or SNORD116 expression [78]. Besides PWS, the treatment of Silver-Russell syndrome (SRS) is an interesting example of a possible use of dCas9-based approaches. SRS is a clinically and genetically heterogeneous condition characterized by severe intrauterine and postnatal growth restriction caused by the decreased expression of the IGF2 (insulin-like growth factor 2) gene [79,80]. DNA hypomethylation of the imprinting control center between the H19 and IGF2 genes (H19 differentially methylated region; H19-DMR) on the paternal chromosome can be found in 35–50% of SRS patients. IGF2 and H19 are reciprocally imprinted genes and are regulated by the methylation of H19-DMR [81,82]. IGF2 is expressed only on the paternal allele. Meanwhile, H19 is expressed only on the maternal allele. H19-DMR contains four highly conserved CG-rich CTCF binding sites that can block methylation spreading [83]. In the paternal allele, CpG methylation within CTCF binding sites abolishes CTCF binding and results in a loss of enhancer-blocking activity, thereby allowing IGF2 expression. Conversely, hypomethylation of the paternal H19-DMR allows the binding of CTCF, leading to the expression of both H19 alleles and the downregulation of IGF2. All this eventually results in growth retardation. The correction of methylation patterns is a promising strategy for patients with SRS. In the study conducted by Horii et al., the authors developed an SRS model using dCas9-SunTag fused to (GFP)-TET1CD (ten-eleven translocation hydroxylase). The authors demethylated the H19-DMR locus in mouse embryonic stem cells and in fertilized mouse eggs [84]. This work is a good demonstration of the possibility of dCas9 usage for target modification of the methylation pattern.
Apart from the therapy of genomic imprinting disorders, dCas9-based approaches can be used for potential therapy of repeat expansion diseases, such as fragile X syndrome (Martin-Bell Syndrome, Fragile X syndrome, FXS). FXS is an X-linked cognitive disorder with a range of neurological and psychiatric problems. The main cause of FXS is the loss of FMR1 (Fragile X Messenger Ribonucleoprotein 1) expression during neurodevelopment [85]. The FMR1 silencing is caused by hypermethylation of its promoter due to the CGG trinucleotide repeat expansion to the FMR1 5′-UTR. In healthy individuals, FMR1 contains approximately 6–44 repeats, while in FXS patients, more than 200 repeats can be found. FMRP (Fragile X mental retardation protein), encoded by FMR1, is an RNA-binding protein expressed in neurons that controls protein synthesis in developing synapses and plays a key role in synaptic plasticity maintenance [86]. Lui et al. showed that binding of dCas9-TET to CGG repeats caused a significant decrease in FMR1 promoter methylation as well as a partial restoration of FMRP expression in human cells [87]. Demethylation of the CGG repeat region increased both H3K27 acetylation and H3K4 trimethylation and, moreover, decreased H3K9 trimethylation in the FMR1 promoter region, leading to FMR1 expression reactivation. This study suggested that targeted demethylation of CGG repeats reactivated FMR1 in a variety of FXS models using iPSCs as well as in vitro-derived FXS neurons. Demethylation of CGG repeats resulted in the conversion of the heterochromatin into the active state of the upstream FMR1 promoter. Therefore, the results provide the first direct evidence that the de-methylation of CGG repeats is sufficient for FMR1 reactivation. It is important to know that methylation editing reversed the abnormal electrophysiological phenotype of FXS neurons and that FMRP expression in the edited neurons remained adequate in vivo [87,88].

3.2. Non-Coding RNAs

The use of ncRNAs is another convenient tool for epigenetic regulation. In recent years, several classes of ncRNAs have been discovered: miRNA, siRNAs, long noncoding RNAs (lncRNA), piwi-interacting RNAs (piRNAs), circular RNAs (circRNAs), etc. [8]. Despite the fact that the first attempts to therapeutically use ncRNAs started immediately after the discovery of RNA interference (RNAi) in 1998 [89], the first RNAi-based drug, patisiran (ONPATTRO), was approved only in 2018 [90,91]. Table 5 contains a summary of siRNA-based drugs that have already been FDA-approved or are currently in clinical trials.
The development of ncRNA-based drugs is complicated by the following issues: low stability of RNA molecules, target delivery difficulties [93], possible toxicity, and immunogenicity [8,94]. The first two major problems with ncRNA-based therapy are the low stability of RNA molecules and their rapid clearance from the system. When injected into the blood, unmodified RNAs are rapidly degraded by serum RNases and also excreted from the body by secretion in the renal tubules. This leads to a short half-life of RNA drugs when systemically administered. To cope with the stability problem, an RNA molecule may be chemically modified on either the ribose or the phosphodiesterase bond [95,96]. Ribose modifications include 2′-O-(2-Methoxyethyl), 2′-O-Methyl, 2′-LNA (Locked Nucleic Acid), 2′-F (2′-fluoro). The phosphodiesterase bond modifications are usually associated with the replacement of phosphate groups by thiophosphate ones [97]. These days, all FDA-approved RNA aptamers (pegaptanib), inhibitory antisense oligonucleotydes (mipomersen, nusinersen, inotersen), and siRNA (patisiran) contain various ribose modifications [98]. However, some RNA modifications may activate the cellular part of the immune system or impede ncRNA function. This applies particularly to the methylation of nitrogen bases, especially cytosine. Moreover, for siRNA, the complete or partial nucleotide substitution for 2′-O-Methyl results in the loss or reduction of inhibition activity [95]. One explanation for such a functional impediment would be the blocking of siRNA-RISC interaction by the 2′-O-methyl group [99]. The introduction of 2′-F into all siRNA nucleotide positions has a similar effect. At the same time, the combination of phosphodiesterase bond thiophosphate modification and the 2′-F significantly increases the toxicity of RNA-based drugs [100]. Modification with LNA (locked nucleic acid) increases the stability of the duplex and suppresses the immune response; however, it was shown that LNA introduction into the first 5′-RNA nucleotide completely inhibits RNA interference [101].
Another challenge for the therapeutic use of RNA-based drugs is target delivery. Due to their small size and negative charge, RNA molecules are unable to cross the cell membrane by themselves. To facilitate penetration through the cell membrane, cationic polymers enriched with positively charged amino groups should be utilized. Polyethyleneimine (PEI) is an example of a polymer that is widely used for siRNA delivery. PEI can not only bind siRNA but also act as a proton sponge capable of destroying the endosome membrane and facilitating the release of the siRNA complex into the cytoplasm. However, in preclinical and clinical trials, the siRNA-PEI complexes induce inflammation, liver necrosis, thrombus formation, and affect lung endothelium [102]. Polylysine-based nanoparticles and branched polymeric substances (dendrimers) can also be used for siRNA delivery. Dendrimers have a regular three-dimensional structure and usually carry amino acid residues, facilitating entry into the cell. Next, polysaccharides constitute another class of siRNA delivery facilitator molecules; among them are chitosan, dextran, hyaluronan, and hyaluronic acid [103]. The important advantage of such molecules is their low toxicity and immunogenicity, as well as their enhanced biodegradability. Conjugates of N-acetylgalactosamine (GalNAc) with siRNAs are actively utilized for RNA-based drug delivery into liver cells through interaction with the asialoglycoprotein receptor [104]. In addition, lipid nanoparticles (LNPs) are often used to deliver siRNAs [105].
Immune response is the next issue in ncRNA-based therapeutic approaches. In the cytoplasm, double-stranded RNAs (dsRNAs) are recognized by cellular defense systems as foreign RNAs, causing activation of TLRs (Toll-like receptors), NLRs (NOD-like receptors), and RLRs (RIG-I-like receptors), as well as stimulating an interferon response [106,107,108]. For example, TLR7 and TLR8 recognize the 5′-UGU-3′ motif inside the RNA sequence [109,110], activating the interferon response. Next, the 5′-GUCCUUCAA-3′ motif causes TLR7-dependent increased cytokine production [111]. In general, immune response activation via TLR7 and TLR8 is caused by the presence of closely spaced ribose and uracil molecules. Thus, immune response activation is highly dependent on the sequence and chemical structure of siRNA molecules [112,113]. Endogenous miRNAs may also act as TLR agonists, as has been shown for most miRNAs secreted by tumor cells. MiR-21 and miR-29a are able to cause macrophage activation through interaction with TLR-7 and TLR-8 receptors, leading to NF-kB activation and proinflammatory cytokines production (e.g., TNF and ILs) [94]. The let7 miRNA is also able to activate TLR-7 receptors in macrophages, microglial cells, and neurons, which also indicates the presence of GU-rich regions in the RNA sequence [114]. One of the possible approaches to reducing siRNA toxicity and immunogenicity is long-term drug administration in minimal doses. For example, the delivery of anti-KRAS oncogene siRNA mimetics into cells of inoperable pancreatic cancer resulted in the release of the RNA-based drug within 12 weeks (NCT01676259) [9].
siRNA and miRNA are the main players in post-transcriptional gene silencing. They act by targeting complementary mRNA sequences, mainly in the 3′UTR. The key difference between the actions of siRNA and miRNA is their target molecule degradation mechanism. While siRNAs act through direct degradation of the target RNA transcript, miRNAs mainly provide translational silencing. However, miRNA can facilitate the indirect degradation of transcripts via target mRNA deadenylation and decapping, followed by subsequent RNA lysis with exonucleases [115].
The following options exist for siRNA drug design: delivery of either siRNA precursors or mature siRNA [90]. siRNA precursors are usually 26–28 bp long and have a hairpin-shaped region corresponding to the 5′-end of the leading (antisense) strand [116]. The mature siRNAs form dsRNA complexes of 21 and 23 nt long with a 2-nt unpaired region at the 3′ end. For activation, siRNA binds to Argonaute proteins, then the sense siRNA strand is removed, followed by the antisense strand binding to the active protein complex [117]. For proper binding, siRNAs must be long enough to interact with RISC complex machinery, and siRNA silencing efficiency is significantly decreased for siRNAs shorter than 19 bp in length [118].
As for miRNA-based drug development, the following issues should be considered: First, miRNAs have a complementary seed region of 6–7 bp long. Such a small complementarity area causes miRNA molecules to act on several targets simultaneously, resulting in an uncontrolled impact on gene expression [119]. To overcome this problem, a cocktail of several miRNAs at very low concentrations that are targeted to the same mRNA can be used. As an example, a combination of miR-34a and miR-15a/16 was applied to non-small cell lung cancer cells, causing cell cycle arrest via CCNE1 and CCND3 gene knockdown [120]. Currently, there are no approved miRNA-based drugs. Moreover, none of the miRNA-based drugs have reached phase III clinical trials. An important problem in miR-NA-based drug implementation is off-target effects [121].
Another class of ncRNA molecules, circRNAs (circular RNAs), has recently been intensively studied [122,123]. circRNAs appear to play an important role in gene expression regulation. Changes in circRNA expression have been shown to be associated with various tumors, neurodegenerative diseases, and metabolic diseases [124]. circRNAs perform different functions in the cell. They can act as molecular sponges that adsorb both miRNAs and transcription factors, regulating their functional activity. For example, ciRS-7, the first discovered circRNA, contains more than 70 conserved miR-7 binding sites [123]. Both endogenous and artificial circRNAs may be used as miRNA sponges for changing pathogenic miRNA activity levels in the regulation of certain diseases [124]. Several circRNA sponges, complementary to oncogenic miR-21 and miR-122, have been developed [125,126,127], but currently, there are no circRNA-based drugs in preclinical or clinical trials. The use of circRNAs as therapeutic agents is a promising area of drug development. Due to their structure, circRNAs are more resistant to RNase degradation than linear RNAs [128], which allows the use of lower doses of circRNA-based drugs. Also, circRNAs demonstrate lower immunogenicity even without any modifications [129]. Thus, circRNAs are an attractive area for drug development.
Apart from being miRNA sponges, circRNAs are able to adsorb some transcription factors. Protein adsorption is achieved by introducing protein-binding sites into the circRNA sequence [130]. Furthermore, circRNAs in the cell often act as RNA aptamers that facilitate protein complex assembly. The creation of artificial circRNA aptamers may also be useful for therapeutic protein delivery as well as for controlling their activity [122]. Next, circRNAs can be used as templates for peptide synthesis. This is achieved by introducing an internal ribosome entry site into the RNA sequence along with an ORF containing start and stop codons. Protein synthesis, in this case, occurs via the rolling circle mechanism [131]. In this case, much higher levels of protein expression can be achieved than when translated from linear transcripts. However, without termination signals, such translation can trigger multimeric repetitive peptide motif synthesis and also cause undesirable toxic effects [128].
Apart from small RNA molecules, synthetic analogues of miRNA molecules are currently being developed. Synthetic or modified miRNA molecules can be used as miRNA inhibitors. Table 6 summarizes current data on clinical trials of such drugs.

4. Conclusions

Epigenetic aberrations and pathogenesis processes are tightly interlinked. These days, epigenetic aberrations may be subject to pharmacological correction. According to the scale of current clinical trials, one may assume that the introduction into clinical practice of an extended list of epigenetic drugs is coming soon. Particularly, epigenetic drugs targeting cellular enzymes that reversibly modify chromatin are being intensively studied. Several epigenetic therapy approaches are being developed. Among them, the dCas9-based approach is a promising direction that is still in its infancy. More research is needed for a better understanding of the opportunities and limitations of epigenetic therapy.

Author Contributions

Conceptualization, E.I.R., D.M.F. and A.S.M.; resources, V.V.M., A.A.K., V.S.Y. and S.A.K.; writing—original draft preparation—E.D.G., P.V.E., I.O.M., A.V.S. and E.I.R.; writing—review and editing, E.D.G., E.I.R., D.M.F. and P.V.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Deichmann, U. Epigenetics: The origins and evolution of a fashionable topic. Dev. Biol. 2016, 416, 249–254. [Google Scholar] [CrossRef] [PubMed]
  2. Lu, Y.; Chan, Y.T.; Tan, H.Y.; Li, S.; Wang, N.; Feng, Y. Epigenetic regulation in human cancer: The potential role of epi-drug in cancer therapy. Mol. Cancer 2020, 19, 79. [Google Scholar] [CrossRef] [PubMed]
  3. Li, M.; Zhang, D. DNA methyltransferase-1 in acute myeloid leukaemia: Beyond the maintenance of DNA methylation. Ann. Med. 2022, 54, 2011–2023. [Google Scholar] [CrossRef] [PubMed]
  4. Fiñana, C.; Gómez-Molina, N.; Alonso-Moreno, S.; Belver, L. Genomic and Epigenomic Landscape of Juvenile Myelomonocytic Leukemia. Cancers 2022, 14, 1335. [Google Scholar] [CrossRef]
  5. Li, J.; Li, L.; Wang, Y.; Huang, G.; Li, X.; Xie, Z.; Zhou, Z. Insights into the Role of DNA Methylation in Immune Cell Development and Autoimmune Disease. Front. Cell Dev. Biol. 2021, 9, 757318. [Google Scholar] [CrossRef]
  6. Sharma, V.; Wright, K.L.; Epling-Burnette, P.K.; Reuther, G.W. Metabolic Vulnerabilities and Epigenetic Dysregulation in Myeloproliferative Neoplasms. Front. Immunol. 2020, 11, 604142. [Google Scholar] [CrossRef]
  7. Qi, L.S.; Larson, M.H.; Gilbert, L.A.; Doudna, J.A.; Weissman, J.S.; Arkin, A.P.; Lim, W.A. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 2013, 152, 1173–1183. [Google Scholar] [CrossRef]
  8. Winkle, M.; El-Daly, S.M.; Fabbri, M.; Calin, G.A. Noncoding RNA therapeutics—Challenges and potential solutions. Nat. Rev. Drug Discov. 2021, 20, 629–651. [Google Scholar] [CrossRef]
  9. Golan, T.; Khvalevsky, E.Z.; Hubert, A.; Gabai, R.M.; Hen, N.; Segal, A.; Domb, A.; Harari, G.; David, E.B.; Raskin, S.; et al. RNAi therapy targeting KRAS in combination with chemotherapy for locally advanced pancreatic cancer patients. Oncotarget 2015, 6, 24560–24570. [Google Scholar] [CrossRef]
  10. Ho, P.T.B.; Clark, I.M.; Le, L.T.T. MicroRNA-Based Diagnosis and Therapy. Int. J. Mol. Sci. 2022, 23, 7167. [Google Scholar] [CrossRef]
  11. Rupaimoole, R.; Slack, F.J. MicroRNA therapeutics: Towards a new era for the management of cancer and other diseases. Nat. Rev. Drug. Discov. 2017, 16, 203–222. [Google Scholar] [CrossRef] [PubMed]
  12. Jones, P.A.; Issa, J.P.J.; Baylin, S. Targeting the cancer epigenome for therapy. Nat. Rev. Genet. 2016, 17, 630–641. [Google Scholar] [CrossRef] [PubMed]
  13. Daher-Reyes, G.S.; Merchan, B.M.; Yee, K.W.L. Guadecitabine (SGI-110): An investigational drug for the treatment of myelodysplastic syndrome and acute myeloid leukemia. Expert Opin. Investig. Drugs. 2019, 28, 835–849. [Google Scholar] [CrossRef]
  14. Raj, K.; Mufti, G.J. Azacytidine (Vidaza(R)) in the treatment of myelodysplastic syndromes. Ther. Clin. Risk Manag. 2006, 2, 377–388. [Google Scholar] [CrossRef] [PubMed]
  15. Wen, T.; Sun, G.; Jiang, W.; He, X.; Shi, Y.; Ma, F.; Liu, P. Histone deacetylases inhibitor chidamide synergizes with humanized PD1 antibody to enhance T-cell chemokine expression and augment Ifn-γ response in NK-T cell lymphoma. eBioMedicine 2023, 87, 104420. [Google Scholar] [CrossRef] [PubMed]
  16. Adair, J.E.; Johnston, S.K.; Mrugala, M.M.; Beard, B.C.; Guyman, L.A.; Baldock, A.L.; Bridge, C.A.; Hawkins-Daarud, A.; Gori, J.L.; Born, D.E.; et al. Gene therapy enhances chemotherapy tolerance and efficacy in glioblastoma patients. J. Clin. Investig. 2014, 124, 4082–4092. [Google Scholar] [CrossRef]
  17. Ruan, J.; Moskowitz, A.J.; Mehta-Shah, N.; Sokol, L.; Chen, Z.; Rahim, R.; Song, W.; Van Besien, K.; Horwitz, S.M.; Rutherford, S.C. Multi-Center Phase II Study of Oral Azacitidine (CC-486) Plus CHOP As Initial Treatment for Peripheral T-Cell Lymphoma (PTCL). Blood 2020, 136 (Suppl. S1), 33–34. [Google Scholar] [CrossRef]
  18. Montesinos, P.P.; Roboz, G.J.; Bulabois, C.E.; Subklewe, M.; Platzbecker, U.; Ofran, Y.; Papayannidis, C.; Wierzbowska, A.; Shin, H.J.; Doronin, V. Safety and efficacy of talacotuzumab plus decitabine or decitabine alone in patients with acute myeloid leukemia not eligible for chemotherapy: Results from a multicenter, randomized, phase 2/3 study. Leukemia 2021, 35, 62–74. [Google Scholar] [CrossRef]
  19. Garcia-Manero, G.; Roboz, G.; Walsh, K.; Kantarjian, H.; Ritchie, E.; Kropf, P.; O’Connell, C.; Tibes, R.; Lunin, S.; Rosenblat, T.; et al. Guadecitabine (SGI-110) in patients with intermediate or high-risk myelodysplastic syndromes: Phase 2 results from a multicentre, open-label, randomised, phase 1/2 trial. Lancet. Haematol. 2019, 6, e317–e327. [Google Scholar] [CrossRef]
  20. Sébert, M.; Renneville, A.; Bally, C.; Peterlin, P.; Beyne-Rauzy, O.; Legros, L.; Gourin, M.P.; Sanhes, L.; Wattel, E.; Gyan, E.; et al. A phase II study of guadecitabine in higher-risk myelodysplastic syndrome and low blast count acute myeloid leukemia after azacitidine failure. Haematologica 2019, 104, 1565–1571. [Google Scholar] [CrossRef]
  21. Salamero, O.; Montesinos, P.; Willekens, C.; Pérez-Simón, J.A.; Pigneux, A.; Récher, C.; Popat, R.; Carpio, C.; Molinero, C.; Mascaró, C.; et al. First-in-Human Phase I Study of Iadademstat (ORY-1001): A First-in-Class Lysine-Specific Histone Demethylase 1A Inhibitor, in Relapsed or Refractory Acute Myeloid Leukemia. J. Clin. Oncol. 2020, 38, 4260–4273. [Google Scholar] [CrossRef] [PubMed]
  22. Navarro Mendivil, A.F.; Gutierrez, S.; Bullock, R.; Buesa, C. 1806P Final safety and efficacy data from CLEPSIDRA trial in 2L ED-SCLC. Ann. Oncol. 2020, 31, S1044. [Google Scholar] [CrossRef]
  23. Kurmasheva, R.T.; Erickson, S.W.; Han, R.; Teicher, B.A.; Smith, M.A.; Roth, M.; Gorlick, R.; Houghton, P.J. In vivo evaluation of the lysine-specific demethylase (KDM1A/LSD1) inhibitor SP-2577 (Seclidemstat) against pediatric sarcoma preclinical models: A report from the Pediatric Preclinical Testing Consortium (PPTC). Pediatr. Blood Cancer 2021, 68, e29304. [Google Scholar] [CrossRef] [PubMed]
  24. Marks, P.; Rifkind, R.A.; Richon, V.M.; Breslow, R.; Miller, T.; Kelly, W.K. Histone deacetylases and cancer: Causes and therapies. Nat. Rev. Cancer 2001, 1, 194–202. [Google Scholar] [CrossRef] [PubMed]
  25. Lin, Y.C.; Lin, J.H.; Chou, C.W.; Chang, Y.F.; Yeh, S.H.; Chen, C.C. Statins increase p21 through inhibition of histone deacetylase activity and release of promoter-associated HDAC1/2. Cancer Res. 2008, 68, 2375–2383. [Google Scholar] [CrossRef] [PubMed]
  26. Bridgeman, S.; Northrop, W.; Ellison, G.; Sabapathy, T.; Melton, P.E.; Newsholme, P.; Mamotte, C.D.S. Statins Do Not Directly Inhibit the Activity of Major Epigenetic Modifying Enzymes. Cancers 2019, 11, 516. [Google Scholar] [CrossRef]
  27. Lauria, A.; Mannino, S.; Gentile, C.; Mannino, G.; Martorana, A.; Peri, D. DRUDIT: Web-based DRUgs DIscovery Tools to design small molecules as modulators of biological targets. Bioinformatics 2020, 36, 1562–1569. [Google Scholar] [CrossRef]
  28. Lin, A.; Giuliano, C.J.; Palladino, A.; John, K.M.; Abramowicz, C.; Yuan, M.L.; Sausville, E.L.; Lukow, D.A.; Liu, L.; Chait, A.R.; et al. Off-target toxicity is a common mechanism of action of cancer drugs undergoing clinical trials. Sci. Transl. Med. 2019, 11, eaaw8412. [Google Scholar] [CrossRef]
  29. Jiao, X.; Sherman, B.T.; Huang, D.W.; Stephens, R.; Baseler, M.W.; Lane, H.C.; Lempicki, R.A. DAVID-WS: A stateful web service to facilitate gene/protein list analysis. Bioinformatics 2012, 28, 1805–1806. [Google Scholar] [CrossRef]
  30. Pavlova, N.N.; Zhu, J.; Thompson, C.B. The hallmarks of cancer metabolism: Still emerging. Cell Metab. 2022, 34, 355–377. [Google Scholar] [CrossRef]
  31. Cerami, E.; Gao, J.; Dogrusoz, U.; Gross, B.E.; Sumer, S.O.; Aksoy, B.A.; Jacobsen, A.; Byrne, C.J.; Heuer, M.L.; Larsson, E.; et al. The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012, 2, 401–404. [Google Scholar] [CrossRef]
  32. Majchrzak-Celińska, A.; Warych, A.; Szoszkiewicz, M. Novel Approaches to Epigenetic Therapies: From Drug Combinations to Epigenetic Editing. Genes 2021, 12, 208. [Google Scholar] [CrossRef] [PubMed]
  33. Morin, A.; Letouzé, E.; Gimenez-Roqueplo, A.P.; Favier, J. Oncometabolites-driven tumorigenesis: From genetics to targeted therapy. Int. J. Cancer 2014, 135, 2237–2248. [Google Scholar] [CrossRef] [PubMed]
  34. Wong, C.C.; Qian, Y.; Yu, J. Interplay between epigenetics and metabolism in oncogenesis: Mechanisms and therapeutic approaches. Oncogene 2017, 36, 3359–3374. [Google Scholar] [CrossRef]
  35. Chen, C.; Wang, Z.; Qin, Y. Connections between metabolism and epigenetics: Mechanisms and novel anti-cancer strategy. Front. Pharmacol. 2022, 13, 935536. [Google Scholar] [CrossRef] [PubMed]
  36. Zarei, M. Wild-type IDH1 inhibition enhances chemotherapy response in melanoma. J. Exp. Clin. Cancer Res. 2022, 41, 283. [Google Scholar] [CrossRef]
  37. Fan, D.; Yue, Q.; Chen, J.; Wang, C.; Yu, R.; Jin, Z.; Yin, S.; Wang, Q.; Chen, L.; Liao, X.; et al. Reprogramming the immunosuppressive microenvironment of IDH1 wild-type glioblastoma by blocking Wnt signaling between microglia and cancer cells. Oncoimmunology 2021, 10, 1932061. [Google Scholar] [CrossRef]
  38. Tian, W.; Zhang, W.; Wang, Y.; Jin, R.; Wang, Y.; Guo, H.; Tang, Y.; Yao, X. Recent advances of IDH1 mutant inhibitor in cancer therapy. Front. Pharmacol. 2022, 3, 982424. [Google Scholar] [CrossRef]
  39. Issa, G.C.; DiNardo, C.D. Acute myeloid leukemia with IDH1 and IDH2 mutations: 2021 treatment algorithm. Blood Cancer J. 2021, 11, 107. [Google Scholar] [CrossRef]
  40. Hilton, I.B.; D’Ippolito, A.M.; Vockley, C.M.; Thakore, P.I.; Crawford, G.E.; Reddy, T.E.; Gersbach, C.A. Epigenome editing by a CRISPR-Cas9-based acetyltransferase activates genes from promoters and enhancers. Nat. Biotechnol. 2015, 33, 510–517. [Google Scholar] [CrossRef]
  41. Chavez, A.; Scheiman, J.; Vora, S.; Pruitt, B.W.; Tuttle, M.; Iyer, E.P.R.; Lin, S.; Kiani, S.; Guzman, C.D.; Wiegand, D.J.; et al. Highly efficient Cas9-mediated transcriptional programming. Nat. Methods 2015, 12, 326–328. [Google Scholar] [CrossRef] [PubMed]
  42. Bogerd, H.P.; Kornepati, A.V.; Marshall, J.B.; Kennedy, E.M.; Cullen, B.R. Specific induction of endogenous viral restriction factors using CRISPR/Cas-derived transcriptional activators. Proc. Natl. Acad. Sci. USA 2015, 112, E7249–E7256. [Google Scholar] [CrossRef] [PubMed]
  43. Garcia-Bloj, B.; Moses, C.; Sgro, A.; Plani-Lam, J.; Arooj, M.; Duffy, C.; Thiruvengadam, S.; Sorolla, A.; Rashwan, R.; Mancera, R.L.; et al. Waking up dormant tumor suppressor genes with zinc fingers, TALEs and the CRISPR/dCas9 system. Oncotarget 2016, 7, 60535–60554. [Google Scholar] [CrossRef]
  44. Balboa, D.; Weltner, J.; Eurola, S.; Trokovic, R.; Wartiovaara, K.; Otonkoski, T. Conditionally Stabilized dCas9 Activator for Controlling Gene Expression in Human Cell Reprogramming and Differentiation. Stem Cell Rep. 2015, 5, 448–459. [Google Scholar] [CrossRef] [PubMed]
  45. Javaid, N.; Pham, T.L.H.; Choi, S. Functional Comparison between VP64-dCas9-VP64 and dCas9-VP192 CRISPR Activators in Human Embryonic Kidney Cells. Int. J. Mol. Sci. 2021, 22, 397. [Google Scholar] [CrossRef]
  46. Elbasani, E.; Falasco, F.; Gramolelli, S.; Nurminen, V.; Günther, T.; Weltner, J.; Balboa, D.; Grundhoff, A.; Otonkoski, T.; Ojala, P.M. Kaposi’s Sarcoma-Associated Herpesvirus Reactivation by Targeting of a dCas9-Based Transcription Activator to the ORF50 Promoter. Viruses 2020, 12, 952. [Google Scholar] [CrossRef] [PubMed]
  47. Villamizar, O.; Waters, S.A.; Scott, T.; Saayman, S.; Grepo, N.; Urak, R.; Davis, A.; Jaffe, A.; Morris, K.V. Targeted Activation of Cystic Fibrosis Transmembrane Conductance Regulator. Mol. Ther. 2019, 27, 1737–1748. [Google Scholar] [CrossRef]
  48. Moses, C.; Nugent, F.; Waryah, C.B.; Garcia-Bloj, B.; Harvey, A.R.; Blancafort, P. Activating PTEN Tumor Suppressor Expression with the CRISPR/dCas9 System. Mol. Ther. Nucleic Acids 2019, 14, 287–300. [Google Scholar] [CrossRef]
  49. Tanenbaum, M.E.; Gilbert, L.A.; Qi, L.S.; Weissman, J.S.; Vale, R.D. A protein-tagging system for signal amplification in gene expression and fluorescence imaging. Cell 2014, 159, 635–646. [Google Scholar] [CrossRef]
  50. Pflueger, C.; Tan, D.; Swain, T.; Nguyen, T.; Pflueger, J.; Nefzger, C.; Polo, J.M.; Ford, E.; Lister, R. A modular dCas9-SunTag DNMT3A epigenome editing system overcomes pervasive off-target activity of direct fusion dCas9-DNMT3A constructs. Genome Res. 2018, 28, 1193–1206. [Google Scholar] [CrossRef]
  51. Zalatan, J.G.; Lee, M.E.; Almeida, R.; Gilbert, L.A.; Whitehead, E.H.; La Russa, M.; Tsai, J.C.; Weissman, J.S.; Dueber, J.E.; Qi, L.S.; et al. Engineering complex synthetic transcriptional programs with CRISPR RNA scaffolds. Cell 2015, 160, 339–350. [Google Scholar] [CrossRef] [PubMed]
  52. Cheng, A.W.; Jillette, N.; Lee, P.; Plaskon, D.; Fujiwara, Y.; Wang, W.; Taghbalout, A.; Wang, H. Casilio: A versatile CRISPR-Cas9-Pumilio hybrid for gene regulation and genomic labeling. Cell Res. 2016, 26, 254–257. [Google Scholar] [CrossRef] [PubMed]
  53. Sajwan, S.; Mannervik, M. Gene activation by dCas9-CBP and the SAM system differ in target preference. Sci. Rep. 2019, 9, 18104. [Google Scholar] [CrossRef] [PubMed]
  54. Jiang, J.; Sun, Y.; Xiao, R.; Wai, K.; Ahmad, M.J.; Khan, F.A.; Zhou, H.; Li, Z.; Zhang, Y.; Zhou, A.; et al. Porcine antiviral activity is increased by CRISPRa-SAM system. Biosci. Rep. 2019, 39, BSR20191496. [Google Scholar] [CrossRef]
  55. Kunii, A.; Hara, Y.; Takenaga, M.; Hattori, N.; Fukazawa, T.; Ushijima, T.; Yamamoto, T.; Sakuma, T. Three-Component Repurposed Technology for Enhanced Expression: Highly Accumulable Transcriptional Activators via Branched Tag Arrays. CRISPR J. 2018, 1, 337–347. [Google Scholar] [CrossRef]
  56. Gilbert, L.A.; Larson, M.H.; Morsut, L.; Liu, Z.; Brar, G.A.; Torres, S.E.; Stern-Ginossar, N.; Brandman, O.; Whitehead, E.H.; Doudna, J.A.; et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 2013, 154, 442. [Google Scholar] [CrossRef]
  57. O’Geen, H.; Bates, S.L.; Carter, S.S.; Nisson, K.A.; Halmai, J.; Fink, K.D.; Rhie, S.K.; Farnham, P.J.; Segal, D.J. Ezh2-dCas9 and KRAB-dCas9 enable engineering of epigenetic memory in a context-dependent manner. Epigenetics Chromatin 2019, 12, 26. [Google Scholar] [CrossRef]
  58. Alerasool, N.; Segal, D.; Lee, H.; Taipale, M. An efficient KRAB domain for CRISPRi applications in human cells. Nat. Methods 2020, 17, 1093–1096. [Google Scholar] [CrossRef]
  59. Groner, A.C.; Meylan, S.; Ciuffi, A.; Zangger, N.; Ambrosini, G.; Dénervaud, N.; Bucher, P.; Trono, D. KRAB-zinc finger proteins and KAP1 can mediate long-range transcriptional repression through heterochromatin spreading. PLoS Genet. 2010, 6, e1000869. [Google Scholar] [CrossRef]
  60. Gjaltema, R.A.F.; Goubert, D.; Huisman, C.; Pilar García Tobilla, C.D.; Koncz, M.; Jellema, P.G.; Wu, D.; Brouwer, U.; Kiss, A.; Verschure, P.J.; et al. KRAB-Induced Heterochromatin Effectively Silences PLOD2 Gene Expression in Somatic Cells and Is Resilient to TGFβ1 Activation. Int. J. Mol. Sci. 2020, 21, 3634. [Google Scholar] [CrossRef]
  61. Das, S.; Chadwick, B.P. CRISPR mediated targeting of DUX4 distal regulatory element represses DUX4 target genes dysregulated in Facioscapulohumeral muscular dystrophy. Sci. Rep. 2021, 11, 12598. [Google Scholar] [CrossRef]
  62. Stepper, P.; Kungulovski, G.; Jurkowska, R.Z.; Chandra, T.; Krueger, F.; Reinhardt, R.; Reik, W.; Jeltsch, A.; Jurkowski, T.P. Efficient targeted DNA methylation with chimeric dCas9-Dnmt3a-Dnmt3L methyltransferase. Nucleic Acids Res. 2017, 45, 1703–1713. [Google Scholar] [CrossRef] [PubMed]
  63. O’Geen, H.; Tomkova, M.; Combs, J.A.; Tilley, E.K.; Segal, D.J. Determinants of heritable gene silencing for KRAB-dCas9 + DNMT3 and Ezh2-dCas9 + DNMT3 hit-and-run epigenome editing. Nucleic Acids Res. 2022, 50, 3239–3253. [Google Scholar] [CrossRef] [PubMed]
  64. Chen, X.; Wei, M.; Liu, X.; Song, S.; Wang, L.; Yang, X.; Song, Y. Construction and validation of the CRISPR/dCas9-EZH2 system for targeted H3K27Me3 modification. Biochem. Biophys. Res. Commun. 2019, 511, 246–252. [Google Scholar] [CrossRef] [PubMed]
  65. Huang, Y.H.; Su, J.; Lei, Y.; Brunetti, L.; Gundry, M.C.; Zhang, X.; Jeong, M.; Li, W.; Goodell, M.A. DNA epigenome editing using CRISPR-Cas SunTag-directed DNMT3A. Genome Biol. 2017, 18, 176. [Google Scholar] [CrossRef] [PubMed]
  66. Yeo, N.C.; Chavez, A.; Lance-Byrne, A.; Chan, Y.; Menn, D.; Milanova, D.; Kuo, C.C.; Guo, X.; Sharma, S.; Tung, A.; et al. An enhanced CRISPR repressor for targeted mammalian gene regula tion. Nat. Methods 2018, 15, 611–616. [Google Scholar] [CrossRef]
  67. Duke, C.G.; Bach, S.V.; Revanna, J.S.; Sultan, F.A.; Southern, N.T.; Davis, M.N.; Carullo, N.V.N.; Bauman, A.J.; Phillips, R.A., 3rd; Day, J.J. An Improved CRISPR/dCas9 Interference Tool for Neuronal Gene Suppression. Front. Genome Ed. 2020, 2, 9. [Google Scholar] [CrossRef]
  68. Perillo, B.; Tramontano, A.; Pezone, A.; Migliaccio, A. LSD1: More than demethylation of histone lysine residues. Exp. Mol. Med. 2020, 52, 1936–1947. [Google Scholar] [CrossRef]
  69. Haldeman, J.M.; Conway, A.E.; Arlotto, M.E.; Slentz, D.H.; Muoio, D.M.; Becker, T.C.; Newgard, C.B. Creation of versatile cloning platforms for transgene expression and dCas9-based epigenome editing. Nucleic Acids Res. 2019, 47, e23. [Google Scholar] [CrossRef]
  70. Ngeow, J.; Eng, C. PTEN in Hereditary and Sporadic Cancer. Cold Spring Harb. Perspect. Med. 2020, 10, a036087. [Google Scholar] [CrossRef]
  71. Wang, H.; Guo, R.; Du, Z.; Bai, L.; Li, L.; Cui, J.; Li, W.; Hoffman, A.R.; Hu, J.F. Epigenetic Targeting of Granulin in Hepatoma Cells by Synthetic CRISPR dCas9 Epi-suppressors. Mol. Ther. Nucleic Acids 2018, 11, 23–33. [Google Scholar] [CrossRef] [PubMed]
  72. Himeda, C.L.; Jones, P.L. The Genetics and Epigenetics of Facioscapulohumeral Muscular Dystrophy. Annu. Rev. Genom. Hum. Genet. 2019, 20, 265–291. [Google Scholar] [CrossRef] [PubMed]
  73. Himeda, C.L.; Jones, T.I.; Jones, P.L. Targeted epigenetic repression by CRISPR/dSaCas9 suppresses pathogenic DUX4-fl expression in FSHD. Mol. Ther. Methods Clin. Dev. 2020, 20, 298–311. [Google Scholar] [CrossRef] [PubMed]
  74. Han, S.; Tai, C.; Westenbroek, R.E.; Yu, F.H.; Cheah, C.S.; Potter, G.B.; Rubenstein, J.L.; Scheuer, T.; de la Iglesia, H.O.; Catterall, W.A. Autistic-like behaviour in Scn1a+/− mice and rescue by enhanced GABA-mediated neurotransmission. Nature 2012, 489, 385–390. [Google Scholar] [CrossRef] [PubMed]
  75. Colasante, G.; Lignani, G.; Brusco, S.; Di Berardino, C.; Carpenter, J.; Giannelli, S.; Valassina, N.; Bido, S.; Ricci, R.; Castoldi, V.; et al. dCas9-Based Scn1a Gene Activation Restores Inhibitory Interneuron Excitability and Attenuates Seizures in Dravet Syndrome Mice. Mol. Ther. 2020, 28, 235–253. [Google Scholar] [CrossRef]
  76. Butler, M.G.; Miller, J.L.; Forster, J.L. Prader-Willi Syndrome—Clinical Genetics, Diagnosis and Treatment Approaches: An Update. Curr. Pediatr. Rev. 2019, 15, 207–244. [Google Scholar] [CrossRef]
  77. Cassidy, S.B.; Schwartz, S.; Miller, J.L.; Driscoll, D.J. Prader-Willi syndrome. Genet. Med. 2012, 14, 10–26. [Google Scholar] [CrossRef]
  78. Wang, S.E.; Jiang, Y.h. Potential of Epigenetic Therapy for Prader-Willi Syndrome. Trends Pharmacol. Sci. 2019, 40, 605–608. [Google Scholar] [CrossRef] [PubMed]
  79. Spiteri, B.S.; Stafrace, Y.; Calleja-Agius, J. Silver-Russell Syndrome: A Review. Neonatal Netw. 2017, 36, 206–212. [Google Scholar] [CrossRef]
  80. Butler, M.G. Imprinting disorders in humans: A review. Curr. Opin. Pediatr. 2020, 32, 719–729. [Google Scholar] [CrossRef]
  81. Bartolomei, M.S.; Webber, A.L.; Brunkow, M.E.; Tilghman, S.M. Epigenetic mechanisms underlying the imprinting of the mouse H19 gene. Genes Dev. 1993, 7, 1663–1673. [Google Scholar] [CrossRef] [PubMed]
  82. Tremblay, K.D.; Saam, J.R.; Ingram, R.S.; Tilghman, S.M.; Bartolomei, M.S. A paternal-specific methylation imprint marks the alleles of the mouse H19 gene. Nat. Genet. 1995, 9, 407–413. [Google Scholar] [CrossRef] [PubMed]
  83. Bell, A.C.; Felsenfeld, G. Methylation of a CTCF-dependent boundary controls imprinted expression of the Igf2 gene. Nature 2000, 405, 482–485. [Google Scholar] [CrossRef]
  84. Horii, T.; Morita, S.; Hino, S.; Kimura, M.; Hino, Y.; Kogo, H.; Nakao, M.; Hatada, I. Successful generation of epigenetic disease model mice by targeted demethylation of the epigenome. Genome Biol. 2020, 21, 77. [Google Scholar] [CrossRef] [PubMed]
  85. Penagarikano, O.; Mulle, J.G.; Warren, S.T. The pathophysiology of fragile x syndrome. Annu. Rev. Genom. Hum. Genet. 2007, 8, 109–129. [Google Scholar] [CrossRef] [PubMed]
  86. Contractor, A.; Klyachko, V.A.; Portera-Cailliau, C. Altered Neuronal and Circuit Excitability in Fragile X Syndrome. Neuron 2015, 87, 699–715. [Google Scholar] [CrossRef] [PubMed]
  87. Liu, X.S.; Wu, H.; Krzisch, M.; Wu, X.; Graef, J.; Muffat, J.; Hnisz, D.; Li, C.H.; Yuan, B.; Xu, C.; et al. Rescue of Fragile X Syndrome Neurons by DNA Methylation Editing of the FMR1 Gene. Cell 2018, 172, 979–992.e6. [Google Scholar] [CrossRef]
  88. Ricci, R.; Colasante, G. CRISPR/dCas9 as a Therapeutic Approach for Neurodevelopmental Disorders: Innovations and Limitations Compared to Traditional Strategies. Dev. Neurosci. 2021, 43, 253–261. [Google Scholar] [CrossRef]
  89. Weiss, B.; Davidkova, G.; Zhou, L.W. Antisense RNA gene therapy for studying and modulating biological processes. Cell. Mol. Life Sci. 1999, 55, 334–358. [Google Scholar] [CrossRef]
  90. Saw, P.E.; Song, E.W. siRNA therapeutics: A clinical reality. Sci. China Life Sci. 2020, 63, 485–500. [Google Scholar] [CrossRef]
  91. Mollocana-Lara, E.C.; Ni, M.; Agathos, S.N.; Gonzales-Zubiate, F.A. The infinite possibilities of RNA therapeutics. J. Ind. Microbiol. Biotechnol. 2021, 48, kuab063. [Google Scholar] [CrossRef] [PubMed]
  92. Raal, F.J.; Kallend, D.; Ray, K.K.; Turner, T.; Koenig, W.; Wright, R.S.; Wijngaard, P.L.J.; Curcio, D.; Jaros, M.J.; Leiter, L.A.; et al. Inclisiran for the Treatment of Heterozygous Familial Hypercholesterolemia. N. Engl. J. Med. 2020, 382, 1520–1530. [Google Scholar] [CrossRef] [PubMed]
  93. Crooke, S.T.; Witztum, J.L.; Bennett, C.F.; Baker, B.F. RNA-Targeted Therapeutics. Cell Metab. 2018, 27, 714–739. [Google Scholar] [CrossRef] [PubMed]
  94. Fabbri, M.; Paone, A.; Calore, F.; Galli, R.; Gaudio, E.; Santhanam, R.; Lovat, F.; Fadda, P.; Mao, C.; Nuovo, G.J.; et al. MicroRNAs bind to Toll-like receptors to induce prometastatic inflammatory response. Proc. Natl Acad. Sci. USA 2012, 109, E2110–E2116. [Google Scholar] [CrossRef] [PubMed]
  95. Yan, Y.; Liu, X.Y.; Lu, A.; Wang, X.Y.; Jiang, L.X.; Wang, J.C. Non-viral vectors for RNA delivery. J. Control. Release 2022, 342, 241. [Google Scholar] [CrossRef]
  96. Czauderna, F.; Fechtner, M.; Dames, S.; Aygün, H.; Klippel, A.; Pronk, G.J.; Giese, K.; Kaufmann, J. Structural variations and stabilising modifications of synthetic siRNAs in mammalian cells. Nucleic Acids Res. 2003, 31, 2705–2716. [Google Scholar] [CrossRef]
  97. Paunovska, K.; Loughrey, D.; Dahlman, J.E. Drug delivery systems for RNA therapeutics. Nat. Rev. Genet. 2022, 23, 265. [Google Scholar] [CrossRef]
  98. Hu, B.; Zhong, L.; Weng, Y.; Peng, L.; Huang, Y.; Zhao, Y.; Liang, X.J. Therapeutic siRNA: State of the art. Signal Transduct. Target. Ther. 2020, 5, 101. [Google Scholar] [CrossRef]
  99. Foster, D.J.; Brown, C.R.; Shaikh, S.; Trapp, C.; Schlegel, M.K.; Qian, K.; Sehgal, A.; Rajeev, K.G.; Jadhav, V.; Manoharan, M.; et al. Advanced siRNA Designs Further Improve In Vivo Performance of GalNAc-siRNA Conjugates. Mol. Ther. 2018, 26, 708–717. [Google Scholar] [CrossRef]
  100. Shen, W.; De Hoyos, C.L.; Sun, H.; Vickers, T.A.; Liang, X.H.; Crooke, S.T. Acute hepatotoxicity of 2′ fluoro-modified 5–10–5 gapmer phosphorothioate oligonucleotides in mice correlates with intracellular protein binding and the loss of DBHS proteins. Nucleic Acids Res. 2018, 46, 2204–2217. [Google Scholar] [CrossRef]
  101. Morita, K.; Hasegawa, C.; Kaneko, M.; Tsutsumi, S.; Sone, J.; Ishikawa, T.; Imanishi, T.; Koizumi, M. 2′-O,4′-C-ethylene-bridged nucleic acids (ENA): Highly nuclease-resistant and thermodynamically stable oligonucleotides for antisense drug. Bioorg. Med. Chem. Lett. 2002, 12, 73–76. [Google Scholar] [CrossRef] [PubMed]
  102. Xue, L.; Yan, Y.; Kos, P.; Chen, X.; Siegwart, D.J. PEI fluorination reduces toxicity and promotes liver-targeted siRNA delivery. Drug Deliv. Transl. Res. 2021, 11, 255–260. [Google Scholar] [CrossRef] [PubMed]
  103. Serrano-Sevilla, I.; Artiga, Á.; Mitchell, S.G.; De Matteis, L.; de la Fuente, J.M. Natural Polysaccharides for siRNA Delivery: Nanocarriers Based on Chitosan, Hyaluronic Acid, and Their Derivatives. Molecules 2019, 24, 2570. [Google Scholar] [CrossRef] [PubMed]
  104. Brown, C.R.; Gupta, S.; Qin, J.; Racie, T.; He, G.; Lentini, S.; Malone, R.; Yu, M.; Matsuda, S.; Shulga-Morskaya, S.; et al. NAR Breakthrough Article Investigating the pharmacodynamic durability of GalNAc-siRNA conjugates. Nucleic Acids Res. 2020, 48, 11827–11844. [Google Scholar] [CrossRef]
  105. Shi, B.; Keough, E.; Matter, A.; Leander, K.; Young, S.; Carlini, E.; Sachs, A.B.; Tao, W.; Abrams, M.; Howell, B.; et al. Biodistribution of Small Interfering RNA at the Organ and Cellular Levels after Lipid Nanoparticle-mediated Delivery. J. Histochem. Cytochem. 2011, 59, 727. [Google Scholar] [CrossRef]
  106. Sioud, M. Induction of inflammatory cytokines and interferon responses by double-stranded and single-stranded siRNAs is sequence-dependent and requires endosomal localization. J. Mol. Biol. 2005, 348, 1079–1090. [Google Scholar] [CrossRef]
  107. Sledz, C.A.; Holko, M.; de Veer, M.J.; Silverman, R.H.; Williams, B.R. Activation of the interferon system by short-interfering RNAs. Nat. Cell Biol. 2003, 5, 834–839. [Google Scholar] [CrossRef]
  108. Marques, J.T.; Devosse, T.; Wang, D.; Zamanian-Daryoush, M.; Serbinowski, P.; Hartmann, R.; Fujita, T.; Behlke, M.A.; Williams, B.R. A structural basis for discriminating between self and nonself double-stranded RNAs in mammalian cells. Nat. Biotechnol. 2006, 24, 559–565. [Google Scholar] [CrossRef]
  109. Hornung, V.; Guenthner-Biller, M.; Bourquin, C.; Ablasser, A.; Schlee, M.; Uematsu, S.; Noronha, A.; Manoharan, M.; Akira, S.; de Fougerolles, A.; et al. Sequence-specific potent induction of IFN-alpha by short interfering RNA in plasmacytoid dendritic cells through TLR7. Nat. Med. 2005, 11, 263–270. [Google Scholar] [CrossRef]
  110. Forsbach, A.; Nemorin, J.G.; Montino, C.; Müller, C.; Samulowitz, U.; Vicari, A.P.; Jurk, M.; Mutwiri, G.K.; Krieg, A.M.; Lipford, G.B.; et al. Identification of RNA Sequence Motifs Stimulating Sequence-Specific TLR8-Dependent Immune Responses. J. Immunol. 2008, 180, 3729–3738. [Google Scholar] [CrossRef]
  111. Li, Y.; Chen, M.; Cao, H.; Zhu, Y.; Zheng, J.; Zhou, H. Extraordinary GU-rich single-strand RNA identified from SARS coronavirus contributes an excessive innate immune response. Microbes Infect. 2013, 15, 88–95. [Google Scholar] [CrossRef] [PubMed]
  112. Diebold, S.S.; Massacrier, C.; Akira, S.; Paturel, C.; Morel, Y.; Reis e Sousa, C. Nucleic acid agonists for Toll-like receptor 7 are defined by the presence of uridine ribonucleotides. Eur. J. Immunol. 2006, 36, 3256–3267. [Google Scholar] [CrossRef] [PubMed]
  113. Chen, X.; Qian, Y.; Yan, F.; Tu, J.; Yang, X.; Xing, Y.; Chen, Z. 5′-Triphosphate-siRNA activates RIG-I-dependent type i interferon production and enhances inhibition of hepatitis B virus replication in HepG2.2.15 cells. Eur. J. Pharmacol. 2013, 721, 86–95. [Google Scholar] [CrossRef] [PubMed]
  114. Coleman, L.G.; Zou, J.; Crews, F.T. Microglial-derived miRNA let-7 and HMGB1 contribute to ethanol-induced neurotoxicity via TLR7. J. Neuroinflammation 2017, 14, 22. [Google Scholar] [CrossRef] [PubMed]
  115. Naeli, P.; Winter, T.; Hackett, A.P.; Alboushi, L.; Jafarnejad, S.M. The intricate balance between microRNA-induced mRNA decay and translational repression. FEBS J. 2023, 290, 2508–2524. [Google Scholar] [CrossRef]
  116. Gangopadhyay, S.; Gore, K.R. Advances in siRNA therapeutics and synergistic effect on siRNA activity using emerging dual ribose modifications. RNA Biol. 2022, 19, 452–467. [Google Scholar] [CrossRef]
  117. Herrera-Carrillo, E.; Liu, Y.P.; Berkhout, B. Improving miRNA delivery by optimizing mirna expression cassettes in diverse virus vectors. Hum. Gene. Ther. Methods 2017, 28, 177–190. [Google Scholar] [CrossRef]
  118. Kim, D.H.; Behlke, M.A.; Rose, S.D.; Chang, M.S.; Choi, S.; Rossi, J.J. Synthetic dsRNA Dicer substrates enhance RNAi potency and efficacy. Nat. Biotechnol. 2005, 23, 222–226. [Google Scholar] [CrossRef]
  119. Agarwal, V.; Bell, G.W.; Nam, J.W.; Bartel, D.P. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015, 4, e05005. [Google Scholar] [CrossRef]
  120. Petrek, H.; Yu, A.M. MicroRNAs in non-small cell lung cancer: Gene regulation, impact on cancer cellular processes, and therapeutic potential. Pharmacol. Res. Perspect. 2019, 7, e00528. [Google Scholar] [CrossRef]
  121. Shah, M.Y.; Ferrajoli, A.; Sood, A.K.; Lopez-Berestein, G.; Calin, G.A. MicroRNA therapeutics in cancer—An emerging concept. eBioMedicine 2016, 12, 34–42. [Google Scholar] [CrossRef] [PubMed]
  122. Holdt, L.M.; Kohlmaier, A.; Teupser, D. Circular RNAs as Therapeutic Agents and Targets. Front. Physiol. 2018, 9, 1262. [Google Scholar] [CrossRef] [PubMed]
  123. Barrett, S.P.; Salzman, J. Circular RNAs: Analysis, expression and potential functions. Development 2016, 143, 1838–1847. [Google Scholar] [CrossRef] [PubMed]
  124. Breuer, J.; Rossbach, O. Production and Purification of Artificial Circular RNA Sponges for Application in Molecular Biology and Medicine. Methods Protoc. 2020, 3, 42. [Google Scholar] [CrossRef]
  125. Rama, A.R.; Quiñonero, F.; Mesas, C.; Melguizo, C.; Prados, J. Synthetic Circular miR-21 Sponge as Tool for Lung Cancer Treatment. Int. J. Mol. Sci. 2022, 23, 2963. [Google Scholar] [CrossRef]
  126. Li, D.; Zhang, J.; Li, J. Role of miRNA sponges in hepatocellular carcinoma. Clin. Chim. Acta 2020, 500, 10–19. [Google Scholar] [CrossRef]
  127. Jost, I.; Shalamova, L.A.; Gerresheim, G.K.; Niepmann, M.; Bindereif, A.; Rossbach, O. Functional sequestration of microRNA-122 from Hepatitis C Virus by circular RNA sponges. RNA Biol. 2018, 15, 1032–1039. [Google Scholar] [CrossRef]
  128. Wesselhoeft, R.A.; Kowalski, P.S.; Anderson, D.G. Engineering circular RNA for potent and stable translation in eukaryotic cells. Nat. Commun. 2018, 9, 2629. [Google Scholar] [CrossRef]
  129. Wesselhoeft, R.A.; Kowalski, P.S.; Parker-Hale, F.C.; Huang, Y.; Bisaria, N.; Anderson, D.G. RNA circularization diminishes immunogenicity and can extend translation duration in vivo. Mol. Cell. 2019, 74, 508. [Google Scholar] [CrossRef]
  130. Schreiner, S.; Didio, A.; Hung, L.H.; Bindereif, A. Design and application of circular RNAs with protein-sponge function. Nucleic Acids Res. 2020, 48, 12326–12335. [Google Scholar] [CrossRef]
  131. Abe, N.; Matsumoto, K.; Nishihara, M.; Nakano, Y.; Shibata, A.; Maruyama, H.; Shuto, S.; Matsuda, A.; Yoshida, M.; Ito, Y.; et al. Rolling Circle Translation of Circular RNA in Living Human Cells. Sci. Rep. 2015, 5, 16435. [Google Scholar] [CrossRef] [PubMed]
  132. Gallant-Behm, C.L.; Piper, J.; Lynch, J.M.; Seto, A.G.; Hong, S.J.; Mustoe, T.A.; Maari, C.; Pestano, L.A.; Dalby, C.M.; Jackson, A.L.; et al. A microRNA-29 mimic (Remlarsen) represses extracellular matrix expression and fibroplasia in the skin. J. Investig. Dermatol. 2019, 139, 1073–1081. [Google Scholar] [CrossRef] [PubMed]
  133. Lindow, M.; Kauppinen, S. Discovering the first microrna-targeted drug. J. Cell Biol. 2012, 199, 407–412. [Google Scholar] [CrossRef] [PubMed]
  134. Ottosen, S.; Parsley, T.B.; Yang, L.; Zeh, K.; van Doorn, L.J.; van der Veer, E.; Raney, A.K.; Hodges, M.R.; Patick, A.K. In vitro antiviral activity and preclinical and clinical resistance profile of miravirsen, a novel anti-hepatitis C virus therapeutic targeting the human factor miR-122. Antimicrob. Agents Chemother. 2015, 59, 599–608. [Google Scholar] [CrossRef]
Epigenomes 07 00023 g001
Figure 1. Panoramic view of drug development in relation to targeting DNA-modifying enzymes ALKBH (alkB homolog 1, histone H2A dioxygenase); DNMT (DNA methyltransferase); METTL3 (methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit); MGMT (O6-methylguanine-DNA methyltransferase). The vertical numbers indicate the number of clinical and preclinical trials, as well as the number of patients involved.
Figure 1. Panoramic view of drug development in relation to targeting DNA-modifying enzymes ALKBH (alkB homolog 1, histone H2A dioxygenase); DNMT (DNA methyltransferase); METTL3 (methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit); MGMT (O6-methylguanine-DNA methyltransferase). The vertical numbers indicate the number of clinical and preclinical trials, as well as the number of patients involved.
Epigenomes 07 00023 g001
Epigenomes 07 00023 g002
Figure 2. Panoramic view of drug development in relation to targeting histone-modifying enzymes The x-axis represents the number of clinical trials, and the y-axis represents the number of preclinical trials. DOT1L (DOT1-like histone lysine methyltransferase); EHMT2 (euchromatic histone-lysine N-methyltransferase 2); EP300 (histone acetyltransferase p300); HDAC (histone deacetylase); KMT2A (lysine methyltransferase 2A); PRMT5 (protein arginine methyltransferase 5); SIRT1 (deacetylase sirtuin-1).
Figure 2. Panoramic view of drug development in relation to targeting histone-modifying enzymes The x-axis represents the number of clinical trials, and the y-axis represents the number of preclinical trials. DOT1L (DOT1-like histone lysine methyltransferase); EHMT2 (euchromatic histone-lysine N-methyltransferase 2); EP300 (histone acetyltransferase p300); HDAC (histone deacetylase); KMT2A (lysine methyltransferase 2A); PRMT5 (protein arginine methyltransferase 5); SIRT1 (deacetylase sirtuin-1).
Epigenomes 07 00023 g002
Table 1. A spectrum of clinical trials of drugs targeting proteins involved in epigenetic regulation.
Table 1. A spectrum of clinical trials of drugs targeting proteins involved in epigenetic regulation.
Protein NameDrugID Trial (www.ClinicalTrials.gov, Accessed on 16 September 2023)PhaseDisease
DNA methyltransferase DNMTGuadecitabine, SGI-110NCT03206047I/IIPlatinum-Resistant Fallopian Tube Carcinoma,
Platinum-Resistant Ovarian Carcinoma,
Platinum-Resistant Primary Peritoneal Carcinoma, etc.
NCT01261312I/IIMyelodysplastic Syndromes (MDS),
Acute myeloid leukemia (AML),
Chronic Myelomonocytic Leukemia (CMML)
NCT02197676IIMyelodysplastic Syndromes (MDS),
DecitabineNCT02472145II/IIIAcute myeloid leukemia (AML)
NCT04051996IIAcute myeloid leukemia (AML)
Azacitidine, CC-486NCT03542266IIPeripheral T-cell lymphoma (PTCL)
Histone acetyltransferase EP300Inobrodib, CCS1477NCT03568656I/IIMetastatic Castration-Resistant Prostate Cancer,
Metastatic Breast Cancer,
Non-small Cell Lung Cancer,
Advanced Solid Tumors
Histone acetyltransferase DOT1LPinometostatNCT03701295, NCT03724084I/IIAcute myeloid leukemia (AML)
Histone methyltransferase PRMT5Pemramethostat, GSK3326595NCT04676516II Early stages of breast cancer
Histone demethylase KDM1ATranylcypramineNCT02717884I/IIAcute myeloid leukemia (AML)
Myelodysplastic Syndrome
SeclidemstatNCT03600649I/IIEwing Sarcoma, Myxoid Liposarcoma,
Sarcoma, Soft Tissue,
Desmoplastic Small Round Cell Tumor, etc.
IadademstatNCT05546580IAcute myeloid leukemia (AML)
NCT05420636IISmall cell lung cancer (SCLC), Neuroendocrine Carcinoma
NAD-dependent deacetylase SIRT1Selisistat, SEN0014196NCT01521585IIHuntington’s disease
Chidamide, HBI-8000,Tucidinostat,ChiCTR1800017698 *IVDiffuse large B-cell lymphoma (DLBCL)
ChiCTR2000034301 *N/AAdvanced breast cancer
ChiCTR-OIC-17011303 *IVPeripheral T-cell lymphoma (PTCL)
NCT03023358IIIPeripheral T-cell lymphoma (PTCL)
NCT04674683IIIMetastatic inoperable melanoma
NCT04231448IIIDiffuse large B-cell lymphoma (DLBCL)
NCT04040491IVPeripheral T-cell lymphoma
Fimepinostat, CUDC-907NCT03002623II Thyroid Neoplasms, Poorly Differentiated and Undifferentiated Thyroid Cancer, Differentiated Thyroid Cancer
Histone deacetylase HDACGivinostatNCT01901432I/IIPolycythemia Vera
Ricolinostat, ACY-1215NCT01997840I/IIMultiple myeloma
NCT02856568INon-Resectable Cholangiocarcinoma,
Recurrent Cholangiocarcinoma,
Stage III Extrahepatic Bile Duct Cancer,
Stage III Intrahepatic Cholangiocarcinoma, etc.
QuizinostatNCT01486277IIT cell lymphoma
MGCD-0103NCT00358982IIHodgkin’s lymphoma
Resminostat, 4SC-201NCT00943449IIAdvanced hepatocellular carcinoma
EntinostatNCT00866333IIHodgkin’s lymphoma
* ID Trial (https://www.chictr.org.cn, Accessed on 16 September 2023).
Table 2. Histone deacetylase inhibitors and their status.
Table 2. Histone deacetylase inhibitors and their status.
Protein Name Drug NameDrugBank IDStatus
HDAC1-3, HDAC6, HDAC8VorinostatDB02546FDA approved
HDAC1-3, HDAC6PracinostatDB05223Investigational
HDAC1, HDAC2, HDAC4, HDAC6AtorvastatinDB06176FDA approved
HDAC1–3MocetinostatDB11830Investigational
HDAC2 HDAC9Valproic acidDB00313FDA approved
HDAC10 HDAC6BufexamacDB13346FDA approved
HDAC7 HDAC8Trichostatin ADB04297Experimental
HDAC1AbexinostatDB12565Investigational
FingolimodDB08868FDA approved
HDAC2AtorvastatinDB06176FDA approved
FluvastatinDB01095FDA approved
PravastatinDB00175FDA approved
LovastatinDB00227FDA approved
SimvastatinDB00641FDA approved
HDAC4CID 24836810 *DB08613Experimental
CID 24836811 *DB07879Experimental
HDAC8CID 3994 *DB02565Experimental
CID 5287979 *DB07586Experimental
CID 10379137 *DB07350Experimental
CID 449096 *DB02917Experimental
Cumarin 120DB08168Experimental
* Entry No. in the PubChem database (https://pubchem.ncbi.nlm.nih.gov/, accessed on 16 September 2023).
Table 3. Prediction of off-target proteins for HDAC inhibitors and their involvement in cellular processes.
Table 3. Prediction of off-target proteins for HDAC inhibitors and their involvement in cellular processes.
KEGG Terms *p-ValueProtein *
hsa00350: Tyrosine metabolism 0.0002Amine oxidase copper containing 3 (AOC3)
Monoamine oxidase A (MAOA)
Tyrosinase (TYR)
4-hydroxyphenylpyruvate dioxygenase (HPD)
hsa00360: Phenylalanine metabolism 0.0016Amine oxidase copper containing three proteins (AOC3)
Monoamine oxidase A (MAOA)
4-hydroxyphenylpyruvate dioxygenase (HPD)
hsa04068: FoxO signaling pathway0.0012Mitogen-activated protein kinase 10 (MAPK10)
Mitogen-activated protein kinase 9 (MAPK9)
Serine/threonine kinase 4 (STK4)
Serum/glucocoticoid regulated kinase 1 (SGK1)
Sirtuin 1 (SIRT1)
hsa04024: cAMP signaling pathway 0.0052Mitogen-activated protein kinase 10 (MAPK10)
Mitogen-activated protein kinase 9 (MAPK9)
Phosphodiesterase 4D (PDE4D)
5-hydroxytryptamine receptor 1A (HTR1A)
Phosphodiesterase 4A (PDE4A)
hsa04010: MAPK signaling pathway 0.0120Mitogen-activated protein kinase 10 (MAPK10)
Mitogen-activated protein kinase 9 (MAPK9)
Calcium voltage-gated channel auxiliary subunit alpha2 delta 1 (CACNA2D1)
Protein tyrosine phosphatase non-receptor type 7 (PTPN7)
Serine/threonine kinase 4 (STK4)
hsa04012: ErbB signaling pathway0.0392Mitogen-activated protein kinase 10 (MAPK10)
Mitogen-activated protein kinase 9 (MAPK9)
ABL proto-oncogene 1, non-receptor tyrosine kinase (ABL1)
hsa04014: Ras signaling pathway0.0472Mitogen-activated protein kinase 10 (MAPK10)
Mitogen-activated protein kinase 9 (MAPK9)
ABL proto-oncogene 1, non-receptor tyrosine kinase (ABL1)
Serine/threonine kinase 4 (STK4)
* Functional enrichment with KEGG (Kyoto Encyclopedia of Genes and Genomes) terms was performed using DAVID v. 6.8 [29].
Table 4. A list of relevant clinical trials on metabolite reprogramming in different types of cancer.
Table 4. A list of relevant clinical trials on metabolite reprogramming in different types of cancer.
ID *PhaseCancer TypeOncometaboliteDrug Combination
NCT03449901IISoft tissue sarcomaArginineADI-PEG20, gemcitabine, docetaxel
NCT04776889IVProstate cancer (metastatic)CholesterolRosuvastatin
NCT04862260Early Phase I Pancreatic cancerCholesterolFOLFIRINOX, ezetimibe, atorvastatin, evolocumab
NCT04164901IIIGlioma2-hydroxyglutarateVorasidenib
NCT03173248IIIAcute myeloid leukemia2-hydroxyglutarateIvosidenib, azacitidine
* (www.ClinicalTrials.gov, accessed on 16 September 2023).
Table 5. A spectrum of clinical trials of siRNA-based drugs.
Table 5. A spectrum of clinical trials of siRNA-based drugs.
Commercial Name SubstanceClinical Trial No.TargetProgress
ONPATTROpatisiranNCT01617967
NCT02510261
NCT04201418
NCT03997383
NCT05040373		Transthyretin (TTR)FDA approved, long-term studies, pregnancy safety studies
LEQVIOInclisiran [92]NCT05362903, NCT04929249
NCT05682378
NCT03159416
NCT05399992		Proprotein convertase subtilisin/kexin type 9 (PCSK9)FDA approved, long-term study, combination therapy effectiveness study, extension trials
OXLUMOLumasiran NCT04152200
NCT03905694
NCT03350451
NCT04982393		Hydroxyacid oxidase (OA1)FDA approved,
observational study, extension trials
GIVLAARIgivosiranNCT04883905
NCT02452372		aminolevulinic acid synthase 1 (ALAS1) FDA approved, combination therapy
-Cemdisiran NCT02352493
NCT05070858
NCT04601844
NCT05744921
NCT05133531		Complement 5 Phase I/II completed,
Combination therapy trials
Anti-EpHa2 siRNAAnti-EpHa2 siRNANCT01591356ephrin type-A receptor 2 (EpHa2)Phase I estimated in 2024
CAS3/SS3Anti-CpG-STAT3 siRNANCT04995536TLR9 receptor and signal transducer and activator of transcription 3 (STAT3)Phase I estimated in 2024
NBF-006Anti-KRAS siRNANCT03819387KRAS proto-oncogene (KRAS)Phase I estimated in 2024
ALN-KHKantiKHK siRNANCT05761301ketohexokinase (KHK)Phase I/II estimated in 2025
OLX10212Asymmetric siRNA NCT05643118Pathways upstream of VEGF (vascular endothelial growth factor)Phase I estimated in 2024
ADX-038 Anti-PK siRNANCT05876312Prekallikrein (PK),Phase I estimated in 2025
SRN-001Anti-AREG siRNANCT05984992Amphiregulin (AREG)Phase I estimated in 2024
AOC 1020Anti-DUX4 siRNANCT05747924Double homeobox 4(DUX4)Phase I estimated in 2025
AGX148/PH-762Anti PD-1 siRNANCT05902520siRNA Modulation of PD-1Phase I estimated in 2026
Table 6. A spectrum of clinical trials of miRNA mimetics and inhibitors.
Table 6. A spectrum of clinical trials of miRNA mimetics and inhibitors.
Commercial Name SubstanceClinical Trial No.Progress
INT-1B3 miR-193a-3p mimicNCT04675996Phase I estimated in 2024
MRX34miR-34a mimicNCT01829971
NCT03033329		Terminated with adverse effects in 2017
Phase I completed in 2017
MRG-201Remlarsen [132]NCT03601052
NCT02603224		Phase 2 completed in 2020
SPC3649Miravirsen [133,134]NCT00979927
NCT00688012
NCT01200420		Phase 2 discontinued in 2021
MRG-106Cobomarsen NCT03837457
NCT02580552
NCT03713320		Phase 2 terminated in 2020
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Griazeva, E.D.; Fedoseeva, D.M.; Radion, E.I.; Ershov, P.V.; Meshkov, I.O.; Semyanihina, A.V.; Makarova, A.S.; Makarov, V.V.; Yudin, V.S.; Keskinov, A.A.; et al. Current Approaches to Epigenetic Therapy. Epigenomes 2023, 7, 23. https://doi.org/10.3390/epigenomes7040023

AMA Style

Griazeva ED, Fedoseeva DM, Radion EI, Ershov PV, Meshkov IO, Semyanihina AV, Makarova AS, Makarov VV, Yudin VS, Keskinov AA, et al. Current Approaches to Epigenetic Therapy. Epigenomes. 2023; 7(4):23. https://doi.org/10.3390/epigenomes7040023

Chicago/Turabian Style

Griazeva, Ekaterina D., Daria M. Fedoseeva, Elizaveta I. Radion, Pavel V. Ershov, Ivan O. Meshkov, Alexandra V. Semyanihina, Anna S. Makarova, Valentin V. Makarov, Vladimir S. Yudin, Anton A. Keskinov, and et al. 2023. "Current Approaches to Epigenetic Therapy" Epigenomes 7, no. 4: 23. https://doi.org/10.3390/epigenomes7040023

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