IMR Press / FBL / Volume 27 / Issue 12 / DOI: 10.31083/j.fbl2712326
Open Access Review
DNA Methylation: From Cancer Biology to Clinical Perspectives
Show Less
1 Department of Oncology, The First Affiliated Hospital of Zhengzhou University, 450052 Zhengzhou, Henan, China
*Correspondence: yanruqin@163.com (Yanru Qin)
These authors contributed equally.
Academic Editor: Alika K. Maunakea
Front. Biosci. (Landmark Ed) 2022, 27(12), 326; https://doi.org/10.31083/j.fbl2712326
Submitted: 30 September 2022 | Revised: 19 November 2022 | Accepted: 21 November 2022 | Published: 20 December 2022
Copyright: © 2022 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

DNA methylation plays an important role in the silence of tissue-specific genes to prevent them from being expressed in the wrong tissue. Aberrant DNA methylation (genome-wide hypomethylation and site-specific hypermethylation) are observed in many types of cancer. DNA methylation patterns are established and maintained through the combined actions of methyltransferase and demethylase, such as DNA methyltransferase (DNMT)-1, DNMT-3, and ten-eleven translocation (TET) family enzymes. It is well known that the process of tumor evolution is complicated with different hallmarks. Early findings put forward the model that focal hypermethylation of tumor suppressor genes (TSG) could straightly trigger transcriptional silencing and malignant transformation, whereas varying levels of DNA methylation also occur at other sites and can differently regulate gene expression and biological processes. The interplay of tumor and immune cells in the tumor microenvironment is complex. Understanding the role of DNA methylation in cancer immunity is critical to better navigate epigenetic agents. Furthermore, a greater understanding of the interaction of DNA methylation with tumor metabolic reprogramming would create a bright avenue for pharmacologic managements of malignancies. In this review, we will describe the molecular mechanisms of DNA methylation abnormalities in cancer biology, introduce the roles of DNA methylation patterns on cancer-immunity cycle and metabolic reprogramming, summarize modulators that are used in targeting DNA remodeling, and highlight the importance of combining epigenome-targeting drugs with other cancer therapies.

Keywords
DNA methylation
metabolism reprogramming
cancer-immunity
novel anti-cancer strategy
1. Introduction

Covalent epigenetic modifications made on DNA and histone cooperatively regulate chromatin structure and gene expression [1]. DNA methylation is the most well-characterized epigenetic mechanism. It plays an important role in the silence of tissue-specific genes to prevent them from being expressed in the wrong tissue. The addition and removal of methyl groups to DNA are catalyzed by specific chromatin-modifying proteins (CMP) known as ‘writers’ and ‘erasers’, which is a reversible process and is dynamically regulated [2]. DNA methylation is the covalent addition of a methyl-group (-CH3) to the cytosine (C) base that is subsequently converted to 5-methycytosine (5mC) [3, 4], which is mainly catalyzed by the DNA methyltransferase (DNMT) family, including DNMT1, DNMT3A, and DNMT3B. S-adenosylmethionine (SAM) is the methyl donor provided by the methionine cycle. Conversely, the ten-eleven translocation (TET) family has been proposed to mediate DNA demethylation in an indirect manner through the oxidization of 5-methylcytosine [5].

Genetic alterations of CMPs, such as DNMT3A and TET2, are frequently observed in human cancers [6], leading to aberrant DNA methylation patterns (genome-wide hypomethylation and site-specific hypermethylation). Theoretically, focal hypermethylation of tumor suppressor genes (TSG) could trigger transcriptional silencing and malignant transformation. Varying levels of DNA methylation can also occur at other sites and differently regulate gene expression and biological processes [7, 8, 9, 10]. DNA methylation supports dynamic gene expression, affecting the highly orchestrated trafficking and activation of tumor infiltrating lymphocytes [11, 12]. Therefore, it is capable of modulating anti-tumor immune responses. It is known that DNA methylation is essential for T cell fate and function. A thorough understanding of the role of DNA methylation in cancer immunity is critical to better navigate epigenetic agents. Further, increasing evidence indicates that DNA methylation affects the alteration of metabolic enzymes, which is directly linked to metabolism reprogramming in oncogenesis [13].

Given the extensive alterations and functions in the DNA methylomes, DNA methylation inhibitors form the standard of care for hematological malignancies and the fundamentals of clinical trials in solid tumors [14]. Therapies that combine DNA methylation inhibitors with standard chemotherapy, metabolism modulators, and immunotherapy, will bring novel therapies to clinical decision making.

In this review, we outline the molecular mechanism of DNA methylation abnormalities in cancer biology, highlight the functions of DNA methylation on immune-oncology and metabolic reprogramming, introduce the emerging strategies to target DNA methylation, and explore potential combinations of epigenetic drugs with other therapies.

2. DNA Methylation in Oncogenesis

DNA methylation is the first epigenetic modification observed in human to determine which gene should be turned on or off. Promoter regions contain an increased quality of GC bases that are recognized as CpG islands (CGI). Tumors often present a global DNA hypomethylation with gains of focal DNA hypermethylation at CpG-rich sites [15, 16]. An aberrant DNA methylation landscape has been reported in a variety of tumors, including both hematological malignancies and solid tumors [17, 18, 19, 20, 21, 22, 23]. The mechanisms of carcinogenesis induced by DNA methylation events are displayed in Fig. 1.

Fig. 1.

Basic mechanisms of oncogenesis induced by DNA methylation. In normal cells, tumor suppressor genes are demethylated and expressed, while oncogenes are methylated and unexpressed. In the tumor cells, tumor suppressor genes are blocked by DNA de novo methylation with DNMT, whereas oncogenes are actively transcribed due to global hypomethylation. TSG, tumor suppressor gene; DNMT, DNA methyltransferase.

2.1 Hypomethylation and Gene Activation

Genome-wide hypomethylation at CpG sites has been reported in many tumor types, such as brain tumor, gastric cancer, liver cancer, and breast cancer [24, 25]. Though global DNA hypomethylation usually occurs in intergenic regions and contributes less to genetic mutations, it can result in genome instability via gene mutations, deletions, inversions, translocations, and amplifications [26]. For example, Long Interspersed Nucleotide Element 1 (LINE-1) is a key component of interspersed DNA repeats. LINE-1 hypomethylation has been reported in several cancer types and portends to a worse prognosis [27, 28, 29, 30]. A recent meta-analysis pointed out that LINE-1 hypomethylation in tissue samples may serve as an epigenetic marker for cancer risk [30]. In addition, several studies highlighted that hypomethylation of cancer-specific CGI may drive the overexpression of oncogenic driver genes [31]. A well-illustrated example is the relationship between BCL-2 and B-cell chronic lymphocytic leukemia [32].

2.2 Hypermethylation and Gene Silencing

In healthy tissues, the CpG dinucleotides at promoter sites of tumor suppressor genes (TSG) are generally unmethylated and transcriptionally active. However, approximately 5–10% CGI are hypermethylated to prompt TSG silencing in cancer cells [33], such as VHL, RB1, CDKN2A, GATA4, and MHL1 [34, 35]. DNA hypermethylation was first observed in colon cancer. Studies also indicated that CGI methylated phenotype was related to BRAF mutations in colon cancer [36, 37, 38], whereas glioblastoma displaying promoter hypermethylation was significantly associated with IDH1 mutations [39, 40]. Hypermethylation of mismatch repair gene MHL1 has been found in human colorectal cancers, which is related to microsatellite instability [41]. Another example is the hypermethylation of CDKN2A (p16), leading to the inactivation of this gene in esophageal adenocarcinoma [42].

2.3 Generation of Tumor Neoantigens

There is a bidirectional interplay between genetic and epigenetic alterations. In addition to genetic mutations driving the dysregulated epigenetic landscape, DNA methylation-induced mutagenesis are also one of the major sources of genetic alterations, resulting in the formation of tumor-associated neoantigens [43]. DNA methylation enables the cytosine base to be more susceptive to deamination, either spontaneous or mutagen motivated, leading to C to T transitions. DNA hypermethylation of transposable elements is critical to epigenetic silencing, as DNA 5-methycytosine is mostly found to locate in the transposable elements [44]. For example, cancer-testis antigens (CTA) could be suppressed by DNA methylation in most somatic cells, but they can be specifically expressed in normal male germ cells [43]. Importantly, reactivation of CTA-coding genes by demethylation can contribute to the presence of neoantigens with immunogenicity and thus enhance immune surveillance [45].

3. Roles of DNA Methylation in the Cancer-Immunity Cycle

Theoretically, the human immune system is able to recognize and eliminate tumor cells involving a series of immune responses, a process called ‘cancer-immunity cycle’ [46]. It has been reported that tumors commonly hijack various epigenetic remodeling to escape immune surveillance. DNA methylation not only exerts seminal roles in the proliferation and effector functions of CD8+ and CD4+ T cells within the tumor microenvironment (TME) [47], but also profoundly impacts T cell activation and exhaustion (Fig. 2).

Fig. 2.

Epigenetic reprogramming on T cells. Naïve T cells will be activated into an ‘effector’ or ‘functional’ state after antigen exposure, which is characterized by the rapid secretion of cytokines and effector proteins, as well as the capacity of infiltration and migration into the tumor microenvironment. But continuous antigen stimulation would inevitably result in T cell exhaustion that is subdivided into ‘plastic dysfunctional state’ and ‘fixed dysfunctional state’. TSCM, stem cell memory T cells; TCM, central memory cells; TEM, effector memory T cells.

3.1 CD8+ T Cell Fate

DNA methylation changes can regulate the differentiation of naïve CD8+ T cells into effector T cells, consisting of cytotoxic and memory subtypes [48, 49, 50, 51] (Fig. 3). Naïve CD8+ T cells will be activated into an ‘effector’ state after antigen exposure, which is characterized by the rapid secretion of cytokines and effector proteins, as well as the capacity for infiltration and migration into the TME. However, continuous antigen stimulation would inevitably result in T cell exhaustion that is subdivided into a ‘plastic dysfunctional state’ and a ‘fixed dysfunctional state’ [52]. This process is accompanied by an epigenome-wide remodeling wherein hundreds of thousands of genes are variously methylated [53], which are collectively maintained by DNMT1, DNMT3A, and TET2. In the developmental trajectory, genes that prompt the activation, proliferation, and differentiation of T cells are demethylated and highly expressed, such as IFNG and GZMB [53]. Conversely, unnecessary genes are frequently methylated and regressed, such as TCF7. Naïve CD8+ T cells more commonly undergo demethylation compared to cytotoxic and exhausted CD8+ T cells, whereas effector genes of cytotoxic CD8+ T cells generally experienced hypermethylation to hypomethylation from naïve to cytotoxic T cell fate, such as GZMB, IFNG, CCL4, and CCL3 [54]. Furthermore, memory CD8+ T cells maintain demethylated effector genes, inducing the rapid and robust immune response of memory CD8+ T cells to re-challenge with antigens [52]. DNMT3A is a methyltransferase in charge of de novo methylation. Studies have shown that genetic ablation of DNMT3A may induce fewer effector CD8+ T cells [55]. In addition, the loss of DNMT3A can abolish de novo methylation which serves to establish immunological memory [52].

Fig. 3.

DNA methylation plays a key role in the differentiation of CD8+ T cells from naïve to effector status. DNA methylation changes can lead to the formation of different subtypes of CD8+ T cells, including effector T cells and exhausted T cells. Effector genes of cytotoxic CD8+ T cells generally experienced hypermethylation to hypomethylation from naïve to cytotoxic T cell fate. In memory CD8+ T cells, naïve T cell-associated genes are methylated but effector T cell-associated genes are demethylated. These methylation levels are maintained by DNMT1, DNMT3A, and TET2.

3.2 CD4+ T Cell Fate

Consistently, DNA methylation is responsible for the fate-decision of naïve CD4+ T cells, modulating their differentiation into various effector subtypes, such as Th1, Th2, Th17, Treg, and memory T cells (Fig. 4). Th1 cells secrete type I cytokines (IL-12 and IFN-γ) that prompt tumor suppression, whereas Th2 cells secrete type II cytokines (IL-4, IL-5, and IL-13) that polarize immunity towards tumor progression [48, 50, 51]. The methylation status of immune genes is linked to the immune response in the TME. The differentiation of naïve CD4+ T cells into Th1 and Th2 relies on different epigenetic remodeling of certain genes. It has been demonstrated that some genes present opposite patterns of expression. For example, IFN-γ remains demethylated at promoter regions and upregulates IFN-γ production upon Th1 cell differentiation [56]. In contrast, the IFN-γ promoter is methylated through de novo methylation catalyzed by DNMT3A during the development of Th2 cells and Th17 cells [57, 58]. Previous studies reported DNMT3A deletion may result in the failure of the formation of Th2 and Th17 cells, mainly due to the absence of de novo methylation at the IFN-γlocus [59]. Furthermore, IL-4 and IL-17 genes are demethylated and Th2 and Th17 subtypes are activated [59, 60]. It has been found that a global loss of DNA methylation occurs in the formation of CD4+ memory T cells [61]. There is, strong evidence to indicate that differentiation of CD4+ naïve T cells into Th1, Th2, Th17, Treg, and memory T cells depends on the dynamic changes of DNA methylation at gene promoter and enhancers, which is maintained by DNMT1, DNMT3A, and TET2.

Fig. 4.

DNA methylation plays a key role in the activation of naïve CD4+ T cells into effector T cells, such as Th1, Th2, Th17, and Treg cells. Naïve CD4+ T cells are stimulated by IL-12 and IFN-γ and form Th1 cells, of which process the methylation status is maintained by DNMT1 and TET2. Th1 cells secrete type I cytokines (IL-12 and IFN-γ) that prompt tumor suppression. The IFN-γpromoter is methylated through de novo methylation catalyzed by DNMT3A during the development of Th2 cells and Th17 cells. Also, the IL-4 gene is demethylated and upregulated in Th2 cell, while IL-17 is demethylated and highly expressed in Th17 cell. For the Treg cells, FOXP3 gene is demethylated at promoters and enhancers, followed by the increased expression of FOXP3.

3.3 T Cell Activation

Activation of naïve T cells initially requires the interactions between T cell receptor (TCR) present on T cells and MHC complex (signal 1) expressed on antigen-presenting cells (APC), followed by the activation of co-stimulatory molecules (signal 2) provided by mature dendritic cells. When both signals are present, T cell activation initiates an autonomous intracellular signaling cascade, leading to T cell expansion and differentiation. Global DNA methylation remodeling plays a critical role in priming and activation of cytotoxic effector T cells. For example, demethylation at a promoter-enhancer region of the IL-2 loci, significantly drives the increased levels of IL-2 cytokines that are required for T cell activation and proliferation [62]. Promoter demethylation is observed in several effector genes, such as GZMK and GZMB [53].

3.4 T Cell Exhaustion

T cells become dysfunctional or exhausted when they are exposed to continuous antigen stimulation, resulting in the failure to produce effective immune response. Generally, exhausted T cells display high levels of inhibitory receptors, such as PD-L1, leading to reduced effector function and suppressed T cell proliferation [63, 64, 65]. It is recognized that DNA methylation contributes to regulating PD-L1 expression. Compelling evidence implicates that PD-L1 promoter is demethylated within exhausted CD8+ T cells in multiple tumors [66, 67, 68], whereas PD-L1 in effector CD8+ T cells remained in the methylated status. PD-1 blockade has the ability to reverse T cell exhaustion in both chronic infection and tumor settings. But this reinvigoration is transient, as T cells become re-exhausted after the withdrawal of PD-1 blockade [69]. Based on ATAC-seq analysis, this is mainly because immune checkpoint inhibitor (ICI) is unable to completely revert exhausted T cells into effector T cells [70]. Furthermore, de novo DNA methylation by DNMT3A at post-effector stage is required for the exhaustion phenotype [70]. Genetic ablation of DNMT3A significantly induced the generation of effector cytokines in the mice model infected with lymphocytic choriomeningitis virus (LCMV) [70]. PD-1 blockade does not erase exhaustion-related DNA methylation. The ablation of DNMT3A combined with a DNA demethylating agent before PD-1 blockade, will result in pronounced T cell expansion and effective immune responses. Overall, aberrant DNA methylation at specific gene loci confers T cell exhaustion [54, 63, 71]. ICI can successfully rejuvenate exhausted T cells that have been epigenetically remodeled.

4. Roles of DNA Methylation on Metabolism Reprogramming

Dysregulated metabolism represents a hallmark of malignancy [72, 73]. Recently, accumulating evidence suggests that DNA methylation affects malignant cells’ metabolism and vice versa [13]. The metabolic pathways that DNA methylation participates in mainly involve glycolysis, methionine cycle, and tricarboxylic acid (TCA) cycle [74, 75, 76] (Fig. 5).

Fig. 5.

The association between DNA methylation and metabolism. The green cycle represents DNA methylation that occurs on genome; the orange cycle indicates methionine cycle that generates SAM in the cytoplasm. The 5-carbonxylcytosine could be methylated to form 5-methylcytosine by DNA methyltransferases (DNMTs), including DNMT1, DNMT3A, and DNMT3B. Small molecules agents, such as 5-azacytidine and 5-aza-2’-deoxycytidine, could inhibit the activity of DNMTs leading to hypomethylation. These hypomethylating agents are used to treat a variety of human tumors. IDH1-2, isocitrate dehydrogenase 1-2; HCY, homocysteine; SAM, S-adenosylmethionine; SAH, S-adenosylhomocysteine; DNMT, DNA methyltransferase; TET, ten-eleven translocation demethylase.

DNA methylation indirectly controls the preferential use of aerobic glycolysis (the Warburg effect) even with an abundant supply of oxygen, contributing to a higher glycolytic influx. Several TSGs that regulate aerobic glycolysis are silenced by DNA hypermethylation, such as VHL which is crucial to TSG in the HIF pathway [77]. Therefore, VHL deficiency reinforces glycolytic activity [78]. Also, studies have demonstrated that hypermethylation of the VHL promoter induces gene silencing and consequently reduces HIF1-mediated proteolysis in multiple myeloma [77]. Additionally, promoter demethylation is associated with overexpression of HK2 and PKM2, both of which favor enhanced glycolysis [79, 80, 81]. Oppositely, promoter hypermethylation leads to the gene silencing of FBP-1 and FBP-2 that encode rate-limiting enzymes in glucogenesis. The silence of FBP-1 and FBP-2 could limit gluconeogenesis but support glycolysis, which is beneficial for the proliferation of tumor cells [82, 83].

The methionine cycle gives rise to SAM which is a methyl donor required by DNMT to methylate DNA. It is thought that navigating the methionine cycle may counter leukemogenesis, especially for DNMT3A-mutated AML [84]. Authors have confirmed the findings that alteration of SAM metabolism and DOTL1 inhibition exert a synergistical effect on inhibiting leukemogenesis [84, 85].

Epigenetic enzymes require TCA metabolites as either substrates or co-factors for post-translational modifications of DNA. For example, the TET family (TET1, TET2, and TET3) is a group of DNA demethylases that are flavin adenine dinucleotide (FAD)- and α-ketoglutarate (α-KG)-dependent. Both FAD and αKG are generated in the TCA cycle [86, 87, 88]. Likewise, mutant metabolic enzymes that are involved in the TCA cycle might facilitate aberrant DNA methylation as well. Distortion of succinate dehydrase (SH) and fumarate hydratase (FH) would lead to the accumulation of succinate and fumarate, which in turn induces DNA hypermethylation by interfering the TET functions [89, 90, 91, 92]. Similarly, NADP+-dependent isocitrate dehydrogenase (IDH1/2) mutations lead to a high concentration of D2HG that would inhibit the activity of TET-family DNA demethylases [93].

Metabolism not only orchestrates epigenetic marks but also functions in cancer immunity [94, 95]. Several studies supported that metabolism reprogramming impacts intercellular signaling cascade and epigenetic landscape to regulate the longevity and functionality of T cells [96]. Both epigenetics and metabolism are able to regulate T cell exhaustion [97]. Specifically, exhausted T cells would go through nutrient deficiency, along with the altered epigenome.

5. Modulators of DNA Methylation

Abnormalities in DNA methylation are related to tumor initiation and progression [98]. Therefore, a large number of epigenetic modulators are currently being developed to target DNA hyper- and hypo-methylation (Table 1). Several trials are ongoing to investigate potential combinations of therapies [15, 99]. Epigenetic modulators can be broadly divided into ‘reprogramming agents’ and ‘targeted agents’. The former includes DNMT inhibitors (DNMTi) that may reverse abnormal DNA methylation patterns, whereas the latter specifically targets genetic alterations in the epigenetic pathways, such as targeting IDH1/2 mutations in AML.

Table 1.Genetic alterations of CMP and small molecular inhibitors of CMP for cancer.
Target Genetic alteration Inhibitors Status Indication
DNA methylation DNMT LOF-mutations; Dominant-negative mutations at Arg882 Decitabine Approved MDS, AML
Azaciditine Approved MDS, AML
Guadecitabine (SGI-110) Phase-III MDS, AML, CMML
TET2 LOF-mutations NA NA NA
Abbreviations: CMP, chromatin-modifying protein; DNMT, DNA methyltransferase; TET, ten-eleven translocation dioxygenase; LOF, loss-of-function; MDS, myelodysplastic syndrome; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; NA, not available.
5.1 DNMT Inhibitors

TSG silencing caused by promoter hypermethylation is a common mechanism of tumorigenesis, which greatly facilitated the discovery of DNA methyltransferase inhibitors (DNMTi) in the past few decades [100, 101, 102, 103]. DNMTi, also termed as hypomethylating agents, are the most widely utilized epigenetic drugs, especially for treating hematologic malignancies. Analogues of the nucleoside cytidine involve 5-azacytidine (5-AZA), 5-aza-2’deoxycytidine (decitabine), and SGI-110 (guadecitabine), which make DNMT inaccessible to DNA and consequently cause DNA hypomethylation [104, 105, 106]. Both 5-AZA and decitabine have been approved by the Food and Drug Administration (FDA) [107]. These two drugs are currently used as first-line therapy for myelodysplastic syndrome (MDS), bringing improved response rates and prolonged survival [108, 109]. Impressive success has also been achieved in the treatment of acute myeloid leukemia (AML) and chronic myelomonocytic leukemia (CMML) (Table 1). In addition, DNMTi has shown improved outcomes in solid tumors, such as ovarian cancer and non-small cell lung cancer [110, 111, 112].

5.2 TET Inhibitors

There is a frequently overlooked phenomenon that the genome-wide DNA hypomethylation occurs in several solid tumors [113], which is related to tumor initiation and progression. TET2 mutations are detected in approximately 20–25% of MDS, 7–23% AML, and over 53% CMML [114, 115, 116]. Further, previous studies indicated that TET1 acts as a suppressor of hematological malignancies [117, 118]. However, there are no approved TET inhibitors to reverse DNA hypomethylation, though several agents are being tested at preclinical stages. For example, the novel compound Bobcat339 has been shown to directly block the enzymatic activity of TET1/2 [119]. Since the JAK/STAT pathways are involved in TET1 transcription, STAT inhibitor UC-51423 may avoid aberrant TET1 function [120]. An alternative approach is to target SAM that donates the methyl group and manipulates the level of methylation. More importantly, emerging studies suggest that SAM could modulate cancer immunity by affecting the functionality of CD8+ T cells [121].

6. Multiple Drug Combinations.
6.1 Combinations of DNMTi and HDACi

Since DNA methylation and histone modification usually work in parallel, considerable efforts are being made to explore various combinations that may significantly increase the efficacy of a single agent and decrease drug resistance. For instance, in a murine ovarian cancer model, the combination of DNMTi and histone deacetylase (HDACi) is capable of increasing the cytotoxic activity of CD8+ cells and NK cells, and promoting effector T cell infiltration in the tumor microenvironment (TME) [122]. Similarly, as the location of DNA methylation and enhancer of zeste homolog 2 (EZH2)-mediated histone acetylation in chromatin are usually mutually exclusive, EZH2 is able to maintain quiescence of particular genes when CGI become activated due to DNA hypermethylation [123, 124]. Therefore, the combination of DNMTi with EZH2 inhibitors is a promising method to enhance anti-tumor responses.

6.2 Combinations of DNMTi and ICI

Numerous clinical trials are evaluating the combination of epigenetic modulators with immune checkpoint inhibitors (ICIs) [125]. The rationale for this proposal is that epigenetic drugs may assist immunotherapy to increase the ability of cytotoxic T cells to attack malignant cells [126, 127, 128, 129]. ICI, an exciting cancer therapy which has emerged in the past several years, has been approved by FDA for non-small cell lung cancer (NSCLC) , melanoma, and renal cancer [130, 131, 132]. There was an unexpected finding that a group of advanced NSCLC patients who had relapsed after a combination of azacytidine (DNMTi) and entinostat (HDACi), received a robust and durable response when they were subsequently enrolled in a clinical trial of ICI [129]. However, it is unknown whether the favorable outcomes reflect the effectiveness of combined therapy or are merely responses to the exposure to ICI. Numerous efforts have been made to figure out the underlying mechanisms as to how epigenetic therapy mediates the augmentation of ICI. It is thought that DNMT inhibitors could reverse immune evasion, as they are able to upregulate the expression of tumor-associated antigens (TAAs) and MHC molecules on the tumor cell surface [133, 134]. Recent studies highlighted that ‘viral mimicry’ produced by DNMTi was tightly associated with increased interferon that may trigger immune attraction [126, 127]. Interests have been switched into the activation of endogenous retroviruses (ERV) which are generally methylated and suppressed in most somatic cells. Mounting evidence suggests that ERV expressed in clear cell renal cell carcinoma could encode peptides that induce T cell and B cell immunoreactivity [135]. As cytosine methylation is critical to the regulation of ERV, reactivation of ERV could be achieved by exposure to DNMTi, and might be effective in reversing immune tolerance for ICI therapy [126, 127, 136, 137].

6.3 Combinations of DNMTi and Metabolic Modulators

Aberrant DNA methylation is an epigenetic memory signature that is central to the pathobiological of IDH-mutant tumors, such as gliomas and AML [138]. DNMTi could be used in combination with isocitrate dehydrogenase (IDH) inhibitors, reducing the production of oncometabolites. More specifically, inhibition of mutant forms of IDH, an enzyme in the TCA cycle, could impact the demethylation status of DNA and histone. Findings also demonstrated that DNMTi might be more effective than IDH inhibitors [139], but the efficacy of combination therapy is still unknown. Another example is the combination use of DNMTi with serine metabolism that has been shown to more aggressively kill liver kinase B1-deficiency tumors carrying KRAS [140]. Overall, despite great attentions in targeting both metabolism reprogramming and epigenetic remodeling, it is unknown whether these two hallmarks function in a synergistical manner.

6.4 Combinations of DNMTi and Chemotherapy

Preclinical studies suggest that DNMTi may improve outcomes when combined with standard cytotoxic drugs. Epigenetic regulation might be a potential mechanism leading to drug resistance to cytotoxic drugs, and thus DNMTi could reverse these pathways and improve the durability of clinical responses [141]. One ongoing clinical trial is being tested to combine DNMTi with cytotoxic agents, making ovarian cancers re-sensitive to these standard drugs [142, 143, 144, 145, 146]. Furthermore, a series of clinical trials are underway to explore combinations of DNMTi with chemotherapy, in an attempt to restore chemosensitivity among patients whose disease have relapsed.

6.5 Triple Combination

A triple combination of DNMTi, HDACi, and ICI, has also been shown to trigger a stronger anti-tumor effect. The application of ICI following combined inhibition of DNMT1 and EZH2 would make ovarian cancer cells to express CXCL9 and CXCL10, which could activate T helper 1 cells and attract tumor-infiltrating lymphocytes (TILs) [147].

7. DNA Methylation in Cancer Prevention

There is a remarkable association between epigenetics and environmental exposure. Lifestyle factors, such as diet, body weight, smoking, and physical activity, constitute the majority of cancer causes, playing an essential role in cancer prevention [148]. One research put forward that lifestyle may modify DNA methylation status leading to genome reprogramming [149]. For example, a study illustrated that the intake of ‘healthy food’ is positively associated with LINE-1 methylation level, which was negatively related to the genome instability [150]. Besides, it has been proven that increased BMI was associated with a lower LINE-1 methylation, particularly for obese females [151]. Increasing evidence suggested that nutritional status may have a lasting effect on metabolism via DNA methylation. A prospective study found that higher dietary folate intake was associated with less LINE-1 hypomethylation in colon cancer, whereas higher alcohol consumption is related to a higher risk of LINE-1 hypomethylation [152]. It is notable that the degree of LINE-1 hypomethylation had a dose-response relationship with poor prognosis and higher mortality in colon tumors [153]. Therefore, modulating DNA methylation may hold the potential to reverse the harmful effects of dietary and lifestyle on tumorigenesis.

8. Conclusions

In summary, both hypomethylation and hypermethylation of DNA coexist in the process of oncogenesis. DNA hypomethylation is capable of activating proto-oncogenes that leads to genomic instability, while DNA hypermethylation could silence the promoters of TSGs that are frequently associated with tumor suppression. Epigenetic alterations may reactivate several genes that are normally limited to immune-privileged organs, such as CTA. These neoantigens are immunogenic and thus enhance the visibility to immune surveillance. In addition, DNA methylation plays critical roles in the regulation of metabolic reprogramming and the cancer-immunity cycle, and thus intensive investigations have focused on expanding the application of DNMTi to rational combinations with other cancer treatments. The efficacy of single DNMTi is likely to be enhanced by combinatorial therapies. Combining DNA methylation inhibitors with ICIs might sensitize less-immunogenic tumors and overcome immune escape. Combing DNMTi and HDACi can synergistically increase the expression levels of TSG. A combination of DNMTi with chemotherapy may restore sensitivity and reverse drug resistance in relapsed patients. Finally, the reciprocal connection between metabolism and epigenetics will continue to motivate this novel combination strategy. Identifying the most effective epigenetic targeting strategies and exploring rationale-based combinational strategies to boost durable anti-tumor response will play an important role in future clinical practice.

Author Contributions

YQ designed the study and reviewed the manuscript. CC and ZW participated in study design and wrote the original draft of the manuscript. CC was mainly responsible for the design of tables and figures. YD, LW, SW, and HW contributed to the conception of the paper. All authors agreed to the submission of the final manuscript.

Ethics Approval and Consent to Participate

Not applicable.

Acknowledgment

Not applicable.

Funding

This study was supported by the National Natural Science Foundation of China (grant no. 81872264).

Conflict of Interest

The authors declare no conflict of interest.

References
[1]
Goldberg AD, Allis CD, Bernstein E. Epigenetics: a Landscape Takes Shape. Cell. 2007; 128: 635–638.
[2]
Dawson M, Kouzarides T. Cancer Epigenetics: from Mechanism to Therapy. Cell. 2012; 150: 12–27.
[3]
Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nature Reviews Genetics. 2002; 3: 415–428.
[4]
Patil V, Ward RL, Hesson LB. The evidence for functional non-CpG methylation in mammalian cells. Epigenetics. 2014; 9: 823–828.
[5]
Tahiliani M, Koh KP, Shen Y, Pastor WA, Bandukwala H, Brudno Y, et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science. 2009; 324: 930–935.
[6]
Baylin SB, Jones PA. Epigenetic Determinants of Cancer. Cold Spring Harbor Perspectives in Biology. 2016; 8: a019505.
[7]
Luo C, Hajkova P, Ecker JR. Dynamic DNA methylation: in the right place at the right time. Science. 2018; 361: 1336–1340.
[8]
McGuire MH, Herbrich SM, Dasari SK, Wu SY, Wang Y, Rupaimoole R, et al. Pan-cancer genomic analysis links 3’UTR DNA methylation with increased gene expression in T cells. EBioMedicine. 2019; 43: 127–137.
[9]
Neri F, Rapelli S, Krepelova A, Incarnato D, Parlato C, Basile G, et al. Intragenic DNA methylation prevents spurious transcription initiation. Nature. 2017; 543: 72–77.
[10]
Schultz MD, He Y, Whitaker JW, Hariharan M, Mukamel EA, Leung D, et al. Human body epigenome maps reveal noncanonical DNA methylation variation. Nature. 2015; 523: 212–216.
[11]
Falkenberg KJ, Johnstone RW. Histone deacetylases and their inhibitors in cancer, neurological diseases and immune disorders. Nature Reviews Drug Discovery. 2014; 13: 673–691.
[12]
Henning AN, Roychoudhuri R, Restifo NP. Epigenetic control of CD8+ T cell differentiation. Nature Reviews Immunology. 2018; 18: 340–356.
[13]
Chen C, Wang Z, Qin Y. Connections between metabolism and epigenetics: mechanisms and novel anti-cancer strategy. Frontiers in Pharmacology. 2022; 13: 935536.
[14]
Nishiyama A, Nakanishi M. Navigating the DNA methylation landscape of cancer. Trends in Genetics. 2021; 37: 1012–1027.
[15]
Jones PA, Issa JJ, Baylin S. Targeting the cancer epigenome for therapy. Nature Reviews Genetics. 2016; 17: 630–641.
[16]
Riggs AD, Jones PA. 5-Methylcytosine, Gene Regulation, and Cancer. Advances in Cancer Research. 1983; 40: 1–30.
[17]
Barbano R, Muscarella LA, Pasculli B, Valori VM, Fontana A, Coco M, et al. Aberrant Keap1 methylation in breast cancer and association with clinicopathological features. Epigenetics. 2013; 8: 105–112.
[18]
Cecotka A, Polanska J. Region-Specific Methylation Profiling in Acute Myeloid Leukemia. Interdisciplinary Sciences: Computational Life Sciences. 2018; 10: 33–42.
[19]
Chao C, Chi M, Preciado M, Black MH. Methylation markers for prostate cancer prognosis: a systematic review. Cancer Causes and Control. 2013; 24: 1615–1641.
[20]
Klughammer J, Kiesel B, Roetzer T, Fortelny N, Nemc A, Nenning K, et al. The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space. Nature Medicine. 2018; 24: 1611–1624.
[21]
Liu X, Brenner DA. Liver: DNA methylation controls liver fibrogenesis. Nature Reviews Gastroenterology and Hepatology. 2016; 13: 126–128.
[22]
Mehta A, Dobersch S, Romero-Olmedo AJ, Barreto G. Epigenetics in lung cancer diagnosis and therapy. Cancer and Metastasis Reviews. 2015; 34: 229–241.
[23]
Sun W, Liu Y, Glazer CA, Shao C, Bhan S, Demokan S, et al. TKTL1 is activated by promoter hypomethylation and contributes to head and neck squamous cell carcinoma carcinogenesis through increased aerobic glycolysis and HIF1alpha stabilization. Clinical Cancer Research. 2010; 16: 857–866.
[24]
Feinberg AP, Tycko B. The history of cancer epigenetics. Nature Reviews Cancer. 2004; 4: 143–153.
[25]
Goyos A, Sowa J, Ohta Y, Robert J. Remarkable Conservation of Distinct Nonclassical MHC Class I Lineages in Divergent Amphibian Species. The Journal of Immunology. 2011; 186: 372–381.
[26]
Chen RZ, Pettersson U, Beard C, Jackson-Grusby L, Jaenisch R. DNA hypomethylation leads to elevated mutation rates. Nature. 1998; 395: 89–93.
[27]
Zhu Z, Sparrow D, Hou L, Tarantini L, Bollati V, Litonjua AA, et al. Repetitive element hypomethylation in blood leukocyte DNA and cancer incidence, prevalence, and mortality in elderly individuals: the Normative Aging Study. Cancer Causes and Control. 2011; 22: 437–447.
[28]
Ting Hsiung D, Marsit CJ, Houseman EA, Eddy K, Furniss CS, McClean MD, et al. Global DNA Methylation Level in whole Blood as a Biomarker in Head and Neck Squamous Cell Carcinoma. Cancer Epidemiology, Biomarkers and Prevention. 2007; 16: 108–114.
[29]
Wilhelm CS, Kelsey KT, Butler R, Plaza S, Gagne L, Zens MS, et al. Implications of LINE1 Methylation for Bladder Cancer Risk in Women. Clinical Cancer Research. 2010; 16: 1682–1689.
[30]
Barchitta M, Quattrocchi A, Maugeri A, Vinciguerra M, Agodi A. LINE-1 hypomethylation in blood and tissue samples as an epigenetic marker for cancer risk: a systematic review and meta-analysis. PLoS ONE. 2014; 9: e109478.
[31]
Zhao SG, Chen WS, Li H, Foye A, Zhang M, Sjöström M, et al. The DNA methylation landscape of advanced prostate cancer. Nature Genetics. 2020; 52: 778–789.
[32]
Hanada M, Delia D, Aiello A, Stadtmauer E, Reed J. Bcl-2 gene hypomethylation and high-level expression in B-cell chronic lymphocytic leukemia. Blood. 1993; 82: 1820–1828.
[33]
Jones PA. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nature Reviews Genetics. 2012; 13: 484–492.
[34]
Baylin SB, Höppener JW, de Bustros A, Steenbergh PH, Lips CJ, Nelkin BD. DNA methylation patterns of the calcitonin gene in human lung cancers and lymphomas. Cancer Research. 1986; 46: 2917–2922.
[35]
Taby R, Issa JJ. Cancer Epigenetics. CA: a Cancer Journal for Clinicians. 2010; 60: 376–392.
[36]
Hinoue T, Weisenberger DJ, Lange CPE, Shen H, Byun H, Van Den Berg D, et al. Genome-scale analysis of aberrant DNA methylation in colorectal cancer. Genome Research. 2012; 22: 271–282.
[37]
Weisenberger DJ, Siegmund KD, Campan M, Young J, Long TI, Faasse MA, et al. CpG island methylator phenotype underlies sporadic microsatellite instability and is tightly associated with BRAF mutation in colorectal cancer. Nature Genetics. 2006; 38: 787–793.
[38]
Yagi K, Akagi K, Hayashi H, Nagae G, Tsuji S, Isagawa T, et al. Three DNA Methylation Epigenotypes in Human Colorectal Cancer. Clinical Cancer Research. 2010; 16: 21–33.
[39]
Brennan C, Verhaak RW, McKenna A, Campos B, Noushmehr H, Salama S, et al. The Somatic Genomic Landscape of Glioblastoma. Cell. 2013; 155: 462–477.
[40]
Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, et al. Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma. Cancer Cell. 2010; 17: 510–522.
[41]
Herman JG, Umar A, Polyak K, Graff JR, Ahuja N, Issa JP, et al. Incidence and functional consequences of hMLH1 promoter hypermethylation in colorectal carcinoma. Proceedings of the National Academy of Sciences of the United States of America. 1998; 95: 6870–6875.
[42]
Wong DJ, Barrett MT, Stöger R, Emond MJ, Reid BJ. p16INK4a promoter is hypermethylated at a high frequency in esophageal adenocarcinomas. Cancer Research. 1997; 57: 2619–2622.
[43]
Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, et al. Signatures of mutational processes in human cancer. Nature. 2013; 500: 415–421.
[44]
Yoder JA, Walsh CP, Bestor TH. Cytosine methylation and the ecology of intragenomic parasites. Trends in Genetics. 1997; 13: 335–340.
[45]
Ilyas S, Yang JC. Landscape of Tumor Antigens in T Cell Immunotherapy. The Journal of Immunology. 2015; 195: 5117–5122.
[46]
Chen D, Mellman I. Oncology Meets Immunology: the Cancer-Immunity Cycle. Immunity. 2013; 39: 1–10.
[47]
Kioussis D, Georgopoulos K. Epigenetic Flexibility Underlying Lineage Choices in the Adaptive Immune System. Science. 2007; 317: 620–622.
[48]
Ostrand-Rosenberg S. Immune surveillance: a balance between protumor and antitumor immunity. Current Opinion in Genetics and Development. 2008; 18: 11–18.
[49]
Raval RR, Sharabi AB, Walker AJ, Drake CG, Sharma P. Tumor immunology and cancer immunotherapy: summary of the 2013 SITC primer. Journal for ImmunoTherapy of Cancer. 2014; 2: 14.
[50]
Sukari A, Nagasaka M, Al-Hadidi A, Lum LG. Cancer Immunology and Immunotherapy. Anticancer Research. 2016; 36: 5593–5606.
[51]
Zhang M, Fujiwara K, Che X, Zheng S, Zheng L. DNA methylation in the tumor microenvironment. Journal of Zhejiang University-Science B. 2017; 18: 365–372.
[52]
Youngblood B, Hale JS, Kissick HT, Ahn E, Xu X, Wieland A, et al. Effector CD8 T cells dedifferentiate into long-lived memory cells. Nature. 2017; 552: 404–409.
[53]
Scharer CD, Barwick BG, Youngblood BA, Ahmed R, Boss JM. Global DNA Methylation Remodeling Accompanies CD8 T Cell Effector Function. The Journal of Immunology. 2013; 191: 3419–3429.
[54]
Yang R, Cheng S, Luo N, Gao R, Yu K, Kang B, et al. Distinct epigenetic features of tumor-reactive CD8+ T cells in colorectal cancer patients revealed by genome-wide DNA methylation analysis. Genome Biology. 2019; 21: 2.
[55]
Ladle BH, Li KP, Phillips MJ, Pucsek AB, Haile A, Powell JD, et al. De novo DNA methylation by DNA methyltransferase 3a controls early effector CD8+ T-cell fate decisions following activation. Proceedings of the National Academy of Sciences of the United States of America. 2016; 113: 10631–10636.
[56]
Janson PC, Marits P, Thörn M, Ohlsson R, Winqvist O. CpG methylation of the IFNG gene as a mechanism to induce immunosuppression [correction of immunosupression] in tumor-infiltrating lymphocytes. Journal of Immunology. 2008; 181: 2878–2886.
[57]
Young HA, Ghosh P, Ye J, Lederer J, Lichtman A, Gerard JR, et al. Differentiation of the T helper phenotypes by analysis of the methylation state of the IFN-gamma gene. Journal of Immunology. 1994; 153: 3603–3610.
[58]
Winders BR, Schwartz RH, Bruniquel D. A distinct region of the murine IFN-gamma promoter is hypomethylated from early T cell development through mature naive and Th1 cell differentiation, but is hypermethylated in Th2 cells. Journal of Immunology. 2004; 173: 7377–7384.
[59]
Thomas RM, Gamper CJ, Ladle BH, Powell JD, Wells AD. De Novo DNA Methylation is Required to Restrict T Helper Lineage Plasticity. Journal of Biological Chemistry. 2012; 287: 22900–22909.
[60]
Ichiyama K, Chen T, Wang X, Yan X, Kim B, Tanaka S, et al. The Methylcytosine Dioxygenase Tet2 Promotes DNA Demethylation and Activation of Cytokine Gene Expression in T Cells. Immunity. 2015; 42: 613–626.
[61]
Morales-Nebreda L, McLafferty FS, Singer BD. DNA methylation as a transcriptional regulator of the immune system. Translational Research. 2019; 204: 1–18.
[62]
Bruniquel D, Schwartz RH. Selective, stable demethylation of the interleukin-2 gene enhances transcription by an active process. Nature Immunology. 2003; 4: 235–240.
[63]
Wherry EJ, Kurachi M. Molecular and cellular insights into T cell exhaustion. Nature Reviews Immunology. 2015; 15: 486–499.
[64]
McKinney EF, Smith KG. T cell exhaustion and immune-mediated disease—the potential for therapeutic exhaustion. Current Opinion in Immunology. 2016; 43: 74–80.
[65]
Emran AA, Chatterjee A, Rodger EJ, Tiffen JC, Gallagher SJ, Eccles MR, et al. Targeting DNA Methylation and EZH2 Activity to Overcome Melanoma Resistance to Immunotherapy. Trends in Immunology. 2019; 40: 328–344.
[66]
Gevensleben H, Holmes EE, Goltz D, Dietrich J, Sailer V, Ellinger J, et al. PD-L1 promoter methylation is a prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients following radical prostatectomy. Oncotarget. 2016; 7: 79943–79955.
[67]
Goltz D, Gevensleben H, Grünen S, Dietrich J, Kristiansen G, Landsberg J, et al. PD-L1 (CD274) promoter methylation predicts survival in patients with acute myeloid leukemia. Leukemia. 2017; 31: 738–743.
[68]
Heiland DH, Haaker G, Delev D, Mercas B, Masalha W, Heynckes S, et al. Comprehensive analysis of PD-L1 expression in glioblastoma multiforme. Oncotarget. 2017; 8: 42214–42225.
[69]
Pauken KE, Sammons MA, Odorizzi PM, Manne S, Godec J, Khan O, et al. Epigenetic stability of exhausted T cells limits durability of reinvigoration by PD-1 blockade. Science. 2016; 354: 1160–1165.
[70]
Ghoneim HE, Fan Y, Moustaki A, Abdelsamed HA, Dash P, Dogra P, et al. De Novo Epigenetic Programs Inhibit PD-1 Blockade-Mediated T Cell Rejuvenation. Cell. 2017; 170: 142–157.e19.
[71]
Duhen T, Duhen R, Montler R, Moses J, Moudgil T, de Miranda NF, et al. Co-expression of CD39 and CD103 identifies tumor-reactive CD8 T cells in human solid tumors. Nature Communications. 2018; 9: 2724.
[72]
Ward P, Thompson C. Metabolic Reprogramming: a Cancer Hallmark even Warburg did not Anticipate. Cancer Cell. 2012; 21: 297–308.
[73]
Elia I, Haigis MC. Metabolites and the tumour microenvironment: from cellular mechanisms to systemic metabolism. Nature Metabolism. 2021; 3: 21–32.
[74]
Shanmugam M, McBrayer SK, Rosen ST. Targeting the Warburg effect in hematological malignancies: from PET to therapy. Current Opinion in Oncology. 2009; 21: 531–536.
[75]
Zeng J, Wu WKK, Wang H, Li X. Serine and one-carbon metabolism, a bridge that links mTOR signaling and DNA methylation in cancer. Pharmacological Research. 2019; 149: 104352.
[76]
Rashkovan M, Ferrando A. Metabolic dependencies and vulnerabilities in leukemia. Genes and Development. 2019; 33: 1460–1474.
[77]
Hatzimichael E, Dranitsaris G, Dasoula A, Benetatos L, Stebbing J, Crook T, et al. Von Hippel–Lindau Methylation Status in Patients with Multiple Myeloma: a Potential Predictive Factor for the Development of Bone Disease. Clinical Lymphoma and Myeloma. 2009; 9: 239–242.
[78]
Crispo F, Condelli V, Lepore S, Notarangelo T, Sgambato A, Esposito F, et al. Metabolic Dysregulations and Epigenetics: A Bidirectional Interplay that Drives Tumor Progression. Cells. 2019; 8: 798.
[79]
Chen M, Zhang J, Li N, Qian Z, Zhu M, Li Q, et al. Promoter hypermethylation mediated downregulation of FBP1 in human hepatocellular carcinoma and colon cancer. PLoS ONE. 2011; 6: e25564.
[80]
Wolf A, Agnihotri S, Munoz D, Guha A. Developmental profile and regulation of the glycolytic enzyme hexokinase 2 in normal brain and glioblastoma multiforme. Neurobiology of Disease. 2011; 44: 84–91.
[81]
Desai S, Ding M, Wang B, Lu Z, Zhao Q, Shaw K, et al. Tissue-specific isoform switch and DNA hypomethylation of the pyruvate kinase PKM gene in human cancers. Oncotarget. 2014; 5: 8202–8210.
[82]
Kamphorst JJ, Chung MK, Fan J, Rabinowitz JD. Quantitative analysis of acetyl-CoA production in hypoxic cancer cells reveals substantial contribution from acetate. Cancer and Metabolism. 2014; 2: 23.
[83]
Gao X, Lin S, Ren F, Li J, Chen J, Yao C, et al. Acetate functions as an epigenetic metabolite to promote lipid synthesis under hypoxia. Nature Communications. 2016; 7: 11960.
[84]
Rau RE, Rodriguez BA, Luo M, Jeong M, Rosen A, Rogers JH, et al. DOT1L as a therapeutic target for the treatment of DNMT3A-mutant acute myeloid leukemia. Blood. 2016; 128: 971–981.
[85]
Barve A, Vega A, Shah PP, Ghare S, Casson L, Wunderlich M, et al. Perturbation of Methionine/S-adenosylmethionine Metabolism as a Novel Vulnerability in MLL Rearranged Leukemia. Cells. 2019; 8: 1322.
[86]
Bhutani N, Burns D, Blau H. DNA Demethylation Dynamics. Cell. 2011; 146: 866–872.
[87]
He Y, Li B, Li Z, Liu P, Wang Y, Tang Q, et al. Tet-Mediated Formation of 5-Carboxylcytosine and its Excision by TDG in Mammalian DNA. Science. 2011; 333: 1303–1307.
[88]
Itkonen HM, Minner S, Guldvik IJ, Sandmann MJ, Tsourlakis MC, Berge V, et al. O-GlcNAc Transferase Integrates Metabolic Pathways to Regulate the Stability of c-MYC in Human Prostate Cancer Cells. Cancer Research. 2013; 73: 5277–5287.
[89]
Baysal BE, Ferrell RE, Willett-Brozick JE, Lawrence EC, Myssiorek D, Bosch A, et al. Mutations in SDHD, a mitochondrial complex II gene, in hereditary paraganglioma. Science. 2000; 287: 848–851.
[90]
Tomlinson IP, Alam NA, Rowan AJ, Barclay E, Jaeger EE, Kelsell D, et al. Germline mutations in FH predispose to dominantly inherited uterine fibroids, skin leiomyomata and papillary renal cell cancer. Nature Genetics. 2002; 30: 406–410.
[91]
Gottlieb E, Tomlinson IPM. Mitochondrial tumour suppressors: a genetic and biochemical update. Nature Reviews Cancer. 2005; 5: 857–866.
[92]
Nowicki S, Gottlieb E. Oncometabolites: tailoring our genes. The FEBS Journal. 2015; 282: 2796–2805.
[93]
Xu W, Yang H, Liu Y, Yang Y, Wang P, Kim S, et al. Oncometabolite 2-Hydroxyglutarate is a Competitive Inhibitor of α-Ketoglutarate-Dependent Dioxygenases. Cancer Cell. 2011; 19: 17–30.
[94]
Kinnaird A, Zhao S, Wellen KE, Michelakis ED. Metabolic control of epigenetics in cancer. Nature Reviews Cancer. 2016; 16: 694–707.
[95]
Kelly B, O’Neill LA. Metabolic reprogramming in macrophages and dendritic cells in innate immunity. Cell Research. 2015; 25: 771–784.
[96]
Kishton RJ, Sukumar M, Restifo NP. Metabolic Regulation of T Cell Longevity and Function in Tumor Immunotherapy. Cell Metabolism. 2017; 26: 94–109.
[97]
Franco F, Jaccard A, Romero P, Yu Y, Ho P. Metabolic and epigenetic regulation of T-cell exhaustion. Nature Metabolism. 2020; 2: 1001–1012.
[98]
Biswas S, Rao CM. Epigenetics in cancer: Fundamentals and beyond. Pharmacology and Therapeutics. 2017; 173: 118–134.
[99]
Loo Yau H, Ettayebi I, De Carvalho DD. The Cancer Epigenome: Exploiting its Vulnerabilities for Immunotherapy. Trends in Cell Biology. 2019; 29: 31–43.
[100]
Subramaniam D, Thombre R, Dhar A, Anant S. DNA methyltransferases: a novel target for prevention and therapy. Frontiers in Oncology. 2014; 4: 80.
[101]
Giri AK, Aittokallio T. DNMT Inhibitors Increase Methylation in the Cancer Genome. Frontiers in Pharmacology. 2019; 10: 385.
[102]
Gnyszka A, Jastrzebski Z, Flis S. DNA methyltransferase inhibitors and their emerging role in epigenetic therapy of cancer. Anticancer Research. 2013; 33: 2989–2996.
[103]
Ehrlich M. DNA hypermethylation in disease: mechanisms and clinical relevance. Epigenetics. 2019; 14: 1141–1163.
[104]
Christman JK. 5-Azacytidine and 5-aza-2′-deoxycytidine as inhibitors of DNA methylation: mechanistic studies and their implications for cancer therapy. Oncogene. 2002; 21: 5483–5495.
[105]
Jüttermann R, Li E, Jaenisch R. Toxicity of 5-aza-2’-deoxycytidine to mammalian cells is mediated primarily by covalent trapping of DNA methyltransferase rather than DNA demethylation. Proceedings of the National Academy of Sciences. 1994; 91: 11797–11801.
[106]
Stresemann C, Lyko F. Modes of action of the DNA methyltransferase inhibitors azacytidine and decitabine. International Journal of Cancer. 2008; 123: 8–13.
[107]
Mahmood N, Rabbani SA. Targeting DNA Hypomethylation in Malignancy by Epigenetic Therapies. Advances in Experimental Medicine and Biology. 2019; 1164: 179–196.
[108]
Silverman LR, Demakos EP, Peterson BL, Kornblith AB, Holland JC, Odchimar-Reissig R, et al. Randomized Controlled Trial of Azacitidine in Patients with the Myelodysplastic Syndrome: a Study of the Cancer and Leukemia Group B. Journal of Clinical Oncology. 2002; 20: 2429–2440.
[109]
Kantarjian H, Issa JJ, Rosenfeld CS, Bennett JM, Albitar M, DiPersio J, et al. Decitabine improves patient outcomes in myelodysplastic syndromes. Cancer. 2006; 106: 1794–1803.
[110]
Derissen EJB, Beijnen JH, Schellens JHM. Concise Drug Review: Azacitidine and Decitabine. The Oncologist. 2013; 18: 619–624.
[111]
Nervi C, De Marinis E, Codacci-Pisanelli G. Epigenetic treatment of solid tumours: a review of clinical trials. Clinical Epigenetics. 2015; 7: 127.
[112]
Koch A, Joosten SC, Feng Z, de Ruijter TC, Draht MX, Melotte V, et al. Analysis of DNA methylation in cancer: location revisited. Nature Reviews Clinical Oncology. 2018; 15: 459–466.
[113]
Ehrlich M. DNA hypomethylation in cancer cells. Epigenomics. 2009; 1: 239–259.
[114]
Kosmider O, Gelsi-Boyer V, Ciudad M, Racoeur C, Jooste V, Vey N, et al. TET2 gene mutation is a frequent and adverse event in chronic myelomonocytic leukemia. Haematologica. 2009; 94: 1676–1681.
[115]
Shih AH, Abdel-Wahab O, Patel JP, Levine RL. The role of mutations in epigenetic regulators in myeloid malignancies. Nature Reviews Cancer. 2012; 12: 599–612.
[116]
Yamazaki J, Estecio MR, Lu Y, Long H, Malouf GG, Graber D, et al. The epigenome of AML stem and progenitor cells. Epigenetics. 2013; 8: 92–104.
[117]
Cimmino L, Dawlaty MM, Ndiaye-Lobry D, Yap YS, Bakogianni S, Yu Y, et al. TET1 is a tumor suppressor of hematopoietic malignancy. Nature Immunology. 2015; 16: 653–662.
[118]
An J, González-Avalos E, Chawla A, Jeong M, López-Moyado IF, Li W, et al. Acute loss of TET function results in aggressive myeloid cancer in mice. Nature Communications. 2015; 6: 10071.
[119]
Chua GNL, Wassarman KL, Sun H, Alp JA, Jarczyk EI, Kuzio NJ, et al. Cytosine-Based TET Enzyme Inhibitors. ACS Medicinal Chemistry Letters. 2019; 10: 180–185.
[120]
Li C, Dong L, Su R, Bi Y, Qing Y, Deng X, et al. Homoharringtonine exhibits potent anti-tumor effect and modulates DNA epigenome in acute myeloid leukemia by targeting SP1/TET1/5hmC. Haematologica. 2020; 105: 148–160.
[121]
Bian Y, Li W, Kremer DM, Sajjakulnukit P, Li S, Crespo J, et al. Cancer SLC43A2 alters T cell methionine metabolism and histone methylation. Nature. 2020; 585: 277–282.
[122]
Stone ML, Chiappinelli KB, Li H, Murphy LM, Travers ME, Topper MJ, et al. Epigenetic therapy activates type I interferon signaling in murine ovarian cancer to reduce immunosuppression and tumor burden. Proceedings of the National Academy of Sciences of the United States of America. 2017; 114: E10981–E10990.
[123]
Lay FD, Liu Y, Kelly TK, Witt H, Farnham PJ, Jones PA, et al. The role of DNA methylation in directing the functional organization of the cancer epigenome. Genome Research. 2015; 25: 467–477.
[124]
Gal-Yam EN, Egger G, Iniguez L, Holster H, Einarsson S, Zhang X, et al. Frequent switching of Polycomb repressive marks and DNA hypermethylation in the PC3 prostate cancer cell line. Proceedings of the National Academy of Sciences of the United States of America. 2008; 105: 12979–12984.
[125]
Chen X, Pan X, Zhang W, Guo H, Cheng S, He Q, et al. Epigenetic strategies synergize with PD-L1/PD-1 targeted cancer immunotherapies to enhance antitumor responses. Acta Pharmaceutica Sinica B. 2020; 10: 723–733.
[126]
Roulois D, Loo Yau H, Singhania R, Wang Y, Danesh A, Shen S, et al. DNA-Demethylating Agents Target Colorectal Cancer Cells by Inducing Viral Mimicry by Endogenous Transcripts. Cell. 2015; 162: 961–973.
[127]
Chiappinelli K, Strissel P, Desrichard A, Li H, Henke C, Akman B, et al. Inhibiting DNA Methylation Causes an Interferon Response in Cancer via dsRNA Including Endogenous Retroviruses. Cell. 2015; 162: 974–986.
[128]
Li H, Chiappinelli KB, Guzzetta AA, Easwaran H, Yen RC, Vatapalli R, et al. Immune regulation by low doses of the DNA methyltransferase inhibitor 5-azacitidine in common human epithelial cancers. Oncotarget. 2014; 5: 587–598.
[129]
Wrangle J, Wang W, Koch A, Easwaran H, Mohammad HP, Pan X, et al. Alterations of immune response of non-small cell lung cancer with Azacytidine. Oncotarget. 2013; 4: 2067–2079.
[130]
Brahmer JR, Tykodi SS, Chow LQM, Hwu W, Topalian SL, Hwu P, et al. Safety and Activity of Anti–PD-L1 Antibody in Patients with Advanced Cancer. New England Journal of Medicine. 2012; 366: 2455–2465.
[131]
Sharma P, Allison J. Immune Checkpoint Targeting in Cancer Therapy: toward Combination Strategies with Curative Potential. Cell. 2015; 161: 205–214.
[132]
Topalian S, Drake C, Pardoll D. Immune Checkpoint Blockade: a Common Denominator Approach to Cancer Therapy. Cancer Cell. 2015; 27: 450–461.
[133]
Héninger E, Krueger TE, Lang JM. Augmenting antitumor immune responses with epigenetic modifying agents. Frontiers in Immunology. 2015; 6: 29.
[134]
Karpf AR. A Potential Role for Epigenetic Modulatory Drugs in the Enhancement of Cancer/Germ-Line Antigen Vaccine Efficacy. Epigenetics. 2006; 1: 116–120.
[135]
Smith CC, Beckermann KE, Bortone DS, De Cubas AA, Bixby LM, Lee SJ, et al. Endogenous retroviral signatures predict immunotherapy response in clear cell renal cell carcinoma. Journal of Clinical Investigation. 2018; 128: 4804–4820.
[136]
Chiappinelli KB, Zahnow CA, Ahuja N, Baylin SB. Combining Epigenetic and Immunotherapy to Combat Cancer. Cancer Research. 2016; 76: 1683–1689.
[137]
Dear AE. Epigenetic Modulators and the New Immunotherapies. New England Journal of Medicine. 2016; 374: 684–686.
[138]
Raynal NJ-, Si J, Taby RF, Gharibyan V, Ahmed S, Jelinek J, et al. DNA Methylation does not Stably Lock Gene Expression but instead Serves as a Molecular Mark for Gene Silencing Memory. Cancer Research. 2012; 72: 1170–1181.
[139]
Turcan S, Fabius AWM, Borodovsky A, Pedraza A, Brennan C, Huse J, et al. Efficient induction of differentiation and growth inhibition in IDH1 mutant glioma cells by the DNMT Inhibitor Decitabine. Oncotarget. 2013; 4: 1729–1736.
[140]
Kottakis F, Nicolay BN, Roumane A, Karnik R, Gu H, Nagle JM, et al. LKB1 loss links serine metabolism to DNA methylation and tumorigenesis. Nature. 2016; 539: 390–395.
[141]
Sharma SV, Lee DY, Li B, Quinlan MP, Takahashi F, Maheswaran S, et al. A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations. Cell. 2010; 141: 69–80.
[142]
Benson EA, Skaar TC, Liu Y, Nephew KP, Matei D. Carboplatin with Decitabine Therapy, in Recurrent Platinum Resistant Ovarian Cancer, Alters Circulating miRNAs Concentrations: A Pilot Study. PLoS ONE. 2015; 10: e0141279.
[143]
Fang F, Balch C, Schilder J, Breen T, Zhang S, Shen C, et al. A phase 1 and pharmacodynamic study of decitabine in combination with carboplatin in patients with recurrent, platinum-resistant, epithelial ovarian cancer. Cancer. 2010; 116: 4043–4053.
[144]
Fang F, Zuo Q, Pilrose J, Wang Y, Shen C, Li M, et al. Decitabine reactivated pathways in platinum resistant ovarian cancer. Oncotarget. 2014; 5: 3579–3589.
[145]
Matei D, Fang F, Shen C, Schilder J, Arnold A, Zeng Y, et al. Epigenetic Resensitization to Platinum in Ovarian Cancer. Cancer Research. 2012; 72: 2197–2205.
[146]
Matei DE, Nephew KP. Epigenetic therapies for chemoresensitization of epithelial ovarian cancer. Gynecologic Oncology. 2010; 116: 195–201.
[147]
Peng D, Kryczek I, Nagarsheth N, Zhao L, Wei S, Wang W, et al. Epigenetic silencing of TH1-type chemokines shapes tumour immunity and immunotherapy. Nature. 2015; 527: 249–253.
[148]
Lim U, Song M. Dietary and Lifestyle Factors of DNA Methylation. Methods in Molecular Biology. 2012; 863: 359–376.
[149]
Burris HH, Baccarelli AA. Environmental epigenetics: from novelty to scientific discipline. Journal of Applied Toxicology. 2014; 34: 113–116.
[150]
Barchitta M, Maugeri A, Magnano San Lio R, Favara G, La Rosa MC, La Mastra C, et al. Dietary Patterns are Associated with Leukocyte LINE-1 Methylation in Women: A Cross-Sectional Study in Southern Italy. Nutrients. 2019; 11: 1843.
[151]
Maugeri A, Barchitta M, Magnano San Lio R, Favara G, La Mastra C, La Rosa MC, et al. The Relationship between Body Mass Index, Obesity, and LINE-1 Methylation: a Cross-Sectional Study on Women from Southern Italy. Disease Markers. 2021; 2021: 9910878.
[152]
Schernhammer ES, Giovannucci E, Kawasaki T, Rosner B, Fuchs CS, Ogino S. Dietary folate, alcohol and B vitamins in relation to LINE-1 hypomethylation in colon cancer. Gut. 2010; 59: 794–799.
[153]
Ogino S, Nosho K, Kirkner GJ, Kawasaki T, Chan AT, Schernhammer ES, et al. A cohort study of tumoral LINE-1 hypomethylation and prognosis in colon cancer. Journal of the National Cancer Institute. 2008; 100: 1734–1738.
Share
Back to top