Next Article in Journal
Roles of Polycomb Complexes in the Reconstruction of 3D Genome Architecture during Preimplantation Embryonic Development
Next Article in Special Issue
Integrated Profiles of Transcriptome and mRNA m6A Modification Reveal the Intestinal Cytotoxicity of Aflatoxin B1 on HCT116 Cells
Previous Article in Journal
Machine Learning Heuristics on Gingivobuccal Cancer Gene Datasets Reveals Key Candidate Attributes for Prognosis
Previous Article in Special Issue
Integrative Transcriptomic Analysis Identify Potential m6A Pathway-Related Drugs That Inhibit Cancer Cell Proliferation
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Genes
Volume 13
Issue 12
10.3390/genes13122381
genes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

RNA Epigenetics in Chronic Lung Diseases

by
Xiaorui Wang
1,†,
Zhihou Guo
2,† and
Furong Yan
2,*
1
Department of Ophthalmology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362002, China
2
Center for Molecular Diagnosis and Therapy, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362002, China
*
Author to whom correspondence should be addressed.
†
Xiaorui Wang and Zhihou Guo contributed to this article equally as the first authors.
Genes 2022, 13(12), 2381; https://doi.org/10.3390/genes13122381
Submission received: 7 October 2022 / Revised: 29 November 2022 / Accepted: 13 December 2022 / Published: 16 December 2022
(This article belongs to the Special Issue RNA Epigenetics: RNA Modification and Epitranscriptome Analysis)
Browse Figures
Review Reports Versions Notes

Abstract

:
Chronic lung diseases are highly prevalent worldwide and cause significant mortality. Lung cancer is the end stage of many chronic lung diseases. RNA epigenetics can dynamically modulate gene expression and decide cell fate. Recently, studies have confirmed that RNA epigenetics plays a crucial role in the developing of chronic lung diseases. Further exploration of the underlying mechanisms of RNA epigenetics in chronic lung diseases, including lung cancer, may lead to a better understanding of the diseases and promote the development of new biomarkers and therapeutic strategies. This article reviews basic information on RNA modifications, including N6 methylation of adenosine (m6A), N1 methylation of adenosine (m1A), N7-methylguanosine (m7G), 5-methylcytosine (m5C), 2′O-methylation (2′-O-Me or Nm), pseudouridine (5-ribosyl uracil or Ψ), and adenosine to inosine RNA editing (A-to-I editing). We then show how they relate to different types of lung disease. This paper hopes to summarize the mechanisms of RNA modification in chronic lung disease and finds a new way to develop early diagnosis and treatment of chronic lung disease.

1. Introduction

Chronic lung diseases include chronic obstructive pulmonary disease (COPD), pneumonia, idiopathic pulmonary fibrosis(IPF), asthma, and lung cancer [1]. Despite many new treatments for chronic lung disease, the death rate for the disease has remained nearly unchanged over the years [2]. With the update of research techniques, our understanding of the changes in the genome and signaling pathways associated with chronic lung diseases has dramatically improved. These advances allow clinicians to treat patients precisely to improve outcomes. Unfortunately, due to the vast heterogeneity in most chronic lung diseases, new tried-and-true treatments are still needed for the diagnosis and treatment of chronic lung diseases [3,4,5,6]. Epigenetics and epigenetic-based targeted therapies have begun to be applied in the clinic and have made remarkable progress.
Epigenetics is a study of molecular biology that deals with the heritable variation in gene function above the primary DNA sequence. It regulates gene expression without changing the DNA sequence. The properties of cells and the differences between different types of cells often rely on systems without DNA variation. Epigenetics includes but is not limited to four principal mechanisms: DNA and RNA methylation, chromatin remodeling, noncoding RNAs, and histone modifications [7]. The development of approaches for the detection of RNA modifications has played a crucial role in the field of RNA modification research. Methylated RNA immunoprecipitation sequencing (MeRIP-Seq), as a detection method of m6A modification, can detect the presence of m6A in the whole genome [8]. Sequencing technology based on bisulfite has been widely used for the identification of m5C [9]. Pseudouridine sequencing (Pseudo-seq) is a method for pseudouracil recognition in genome-wide single nucleotide resolution. This method can accurately locate the one-base resolution at the full transcriptome level [10]. The m1A detection methods use antibodies that can specifically recognize m1A to enrich the RNA containing m1A, and then detects m1A on the mRNA [11,12]. As the approaches for the detection of RNA modifications continue to improve, more and more RNA modifications are being discovered.
RNA epigenetics has introduced a new layer of gene regulation in the study of chronic lung diseases. It dynamically regulates gene expression through a series of different modifications, broadening the potential of epigenetics in the diagnosis and treatment of chronic lung diseases [13]. Currently, a number of articles have summarized the relationship between RNA modification and respiratory diseases [14,15,16]. The majority of them have focused on lung cancer and m6A. With the progress of the technologies, more and more studies have confirmed the relationship between lung diseases other than lung cancer and other types of RNA modification. The computational work has made a great contribution to the development of RNA modification research and provided a valuable data set for chronic lung diseases related analysis. This review therefore also covers a number of known database/functional tools to make this review more informative and useful to the readers. This review aims to explore the mechanisms of epigenetic modifications associated with RNA, especially the impact of these modifications on chronic lung diseases.

2. RNA Epigenetics Mechanisms

RNA epigenetics research has developed rapidly in the last decade. RNAs participate in many processes, such as transcription, splicing, and translation. RNA regulates gene expression not only through the form of an intermediate in protein synthesis (messenger RNA (mRNA)) or an effector molecule (transfer RNA (tRNA) and ribosomal RNA (rRNA)), but also acts directly on gene expression, including through the action of multiple classes of other noncoding RNAs(ncRNAs), such as microRNA (miRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA) and long ncRNA (lncRNA) [17,18,19]. RNA is a novel function as a catalyst and regulator of many biochemical reactions, a carrier of genetic information, an adaptor for protein synthesis, and a structural scaffold for subcellular organelles [20,21,22,23,24]. RNA epigenetics is generally considered to be irreversible changes that have significant effects on RNA structure stability and/or function. However, some RNA modifications are reversible [25,26]. With only 4 bases, RNA is less diverse than protein with 20 different amino acid residues. To enrich the structure and function of RNA, nature modifies RNA through various chemical modifications. More than 150 structurally distinct modification types have been identified across all types of RNA [27,28]. These modifications are associated with various biological processes and human diseases [29,30]. RNA modification was initially only studied in rRNA, tRNA, and snRNA. Using immunoprecipitating RNA or covalently binding RNA-methylase complexes in combination with sequencing, the researchers gained a global understanding of the characteristics of these RNA modifications [8,31,32]. More and more RNA modifications are now confirmed, and these changes are detected in a variety of RNAs [33,34,35,36,37]. RNA modifications affect base pairing, secondary structure, and the ability of RNA to interact with proteins directly. These chemical changes further affect RNA processing, localization, translation, and decay processes to regulate gene expression [38].

2.1. Several Most Common RNA Modification Types

The common RNA modifications include N6 methylation of adenosine (m6A), N1 methylation of adenosine (m1A), N7-methylguanosine (m7G), 5-methylcytosine (m5C), 2′O-methylation (2′-O-Me or Nm), pseudouridine (5-ribosyl uracil or Ψ) and adenosine to inosine RNA editing (A-to-I editing), etc. (Figure 1) [39]. Among these RNA modifications, m6A is the most abundant form in eukaryotic cells, extensively studied in recent years. m6A expression was abundant in the liver, kidney, and brain. The content of it in different cancer cell lines varies greatly. Studies have found that m6A is mainly distributed within genes, and the proportion of m6A in protein-coding regions (CDS) and untranslated regions (UTRs) is relatively high. m6A in UTRs tended to be highly expressed in the third UTR region, while CDS regions were mainly enriched near-stop codons. The modification of m6A primarily occurs on the adenine of the RRACH sequence, where R is guanine, or adenine, and H is uracil, adenine, or cytosine [40]. The m6A modification has been implicated in the activation of multiple signaling pathways associated with lung cancer, in addition to COPD, pulmonary fibrosis, asthma, and other respiratory diseases. The m1A modification is formed by the methylation of N1 adenosine. It is an isoform of m6A and is regulated by multiple transferase complexes and demethylases, and this regulation is reversible [41,42]. The m1A-modified tRNA can regulate translation by increasing tRNA stability, while m1A-modified mRNA and lncRNA can influence RNA processing or protein translation. Some studies have found that m1A may regulate mitochondrial function [43]. The m7G was first discovered at the 5′ caps and internal positions of mRNAs, as well as inside rRNAs and tRNAs [44,45,46]. Recently, m7G has also been detected in miRNAs [47]. The m7G is associated with tumor metastasis and growth. The m5C is ubiquitous in mRNAs, tRNAs, RNAs, and ncRNAs [48]. It is involved in various RNA metabolisms. In tRNA, m5C is involved in stabilizing tRNA secondary structure and enhancing codon recognition. In addition, m5C modifies rRNA and ncRNA, thereby regulating mitochondrial dysfunction, stress response defects, gametocyte and embryonic development, tumorigenesis and cell migration [49,50,51]. 2′-O-Me(Nm) is a co- or post-transcriptional modification of RNA, where one of the methyl groups (-CH3) is added to the 2’ hydroxyl (-OH) of ribose. 2′-O-Me is widespread in tRNAs, RNAs, and mRNAs and regulates pre-mRNA splicing and small RNA stability [52,53]. Of all RNA species, rRNAs carry the most 2′-O-Me modifications. 2′-O-Me is found mainly in mRNA caps, but 2′-O-Me has recently been detected in CDS. 2′-O-Me can also modify sncRNAs (including miRNAs and piRNAs) [54]. Ψ can change mRNA’s secondary structure. When Ψ occurs in the stop codons, or nonsense codons it can affect the translation process and translation result [55]. Ψ could affect the development of lung cancer. A-to-I editing mainly exists on the primary transcript of mRNA, tRNAs, and miRNAs, and this RNA modification mechanism can modify the secondary structure of RNA. It is the deamination of adenosine in RNA to inosine. Inosine is recognized as guanosine in cells. A-to-I editing is associated with lung cancer cell phenotype.

2.2. RNA Modification Database

High-throughput sequencing data has a key impact in the study of RNA modification. These sequencing data are available on public websites, including the NCBI-Gene Expression Omnibus database (NCBI-GEO) (https://www.ncbi.nlm.nih.gov/geo, accessed on 27 November 2022). The data related to chronic lung disease in the GEO database is mainly related to m6A modification. The m6A levels in cisplatin-resistant A549 cells were up-regulated compared to A549 cells (GSE140020, GSE136433). In addition, multiple data sets were compared and screened for m6A markers in LUAD cells (GSE198288, GSE176348, GSE161090). There are also RNA-seq expression profiles associated with writer/eraser perturbation. For example, expression profiles after METTL3 knockdown in A549 and H1299 cells (GSE76367), ALKBH5 knockdown in PC9 cells (GSE165453), and YTHDF1 or YTHDF2 knockdown PC9 cells (GSE171634).
With the further study of RNA modification, databases containing various information are emerging. These databases, which have received widespread interest and use, in turn, provide the basis for further research about the function of RNA modification. The existing RNA modification databases can be divided into biochemical RNA modification databases, comprehensive reversible RNA modification databases, specialized reversible RNA modification databases, and RNA editing databases [56]. Biochemical RNA modification databases can query the chemical structure and biosynthetic pathways of RNA modification, among which RNA Modification Database (RNAMDB) [57] and Modomics [58] are the most common. Comprehensive reversible RNA modification databases include MethylTranscriptome DataBase (MeT-DB) [59], RNA Modification Base Database (RMBase) [60], m6A-Atlas [61], m6A2target [62], m5C-Atlas [63], m7GHub [64] and RNA Epi-transcriptome Collection (REPIC) [65]. RMBase is the most comprehensive RNA modification database available. The m6A2Target is a comprehensive database of target genes for m6A modified enzymes (writers, erasers, and readers). Specialized reversible RNA modification databases include m6Avar [66], m6A-TSHub [67], CVm6A [68], RMVar [69] and RMDisease [70]. RNA editing databases include RNA Editing Database (REDIdb) [71], Rigorously Annotated Database of A-to-I RNA Editing (RADAR) [72], Database of RNA Editing (DARNED) [73], and REDIportal [74]. There are other functional tools available for RNA modification such as m6ASNP [75] and ConsRM [76]. Genetic variants that affect RNA modification play a key role in many aspects of RNA metabolism and are also associated with chronic lung disease. It is important to assess the effect of single nucleotide variants in the human genome on m6A modification. The m6AVar database is a comprehensive database for studying m6A-related variants that may affect m6A modification. It will explain the influence of variants through the function of m6A modification. The m6AVar can be used to predict potential modification sites of m6A in chronic lung disease. According to the m6AVar database, three m6A-related genes (ZCRB1, ADH1C, and YTHDC2) are reliable prognostic indicators for lung adenocarcinoma (LUAD) patients and are potential therapeutic targets [77]. RMVar is similar to m6AVar in that it mainly collects related variants affecting m6A modification. However, RMVar has more comprehensive functions than m6AVar. RMVar also contains other RNA-modified variants. The databases of genetic variation in RNA modification also include RMDisease and m6A- TSHub. RMDisease integrates the predictions of 18 different RNA modification prediction tools and a large number of experimentally validated RNA modification sites and identifies single nucleotide polymorphisms (SNPs) that may affect eight types of RNA modification. Most of the m6A-associated cancer variants are tissue- and cancer-specific. The m6A-TSHub consists of four core components, namely m6A-TSDB, m6A-TSFinde, m6A-TSVar, and m6A-CAVar. The m6A-TSDB platform can be used to retrieve m6A sites in normal lung tissue and lung cancer cell lines. Then, m6A-TSVa can be used to explore the influence of lung tissue variation on m6A by integrating tissue-specific m6A. Finally, m6A-CAVar can be used to screen for cancer variants affecting m6A in lung tissue. Through these databases, we can screen out the gene variants associated with RNA modification in chronic lung disease for further verification.

2.3. The Regulation of RNA Modification

Three proteins have been found to regulate RNA modification. The first is an enzyme that introduces modified nucleotides into RNA during post-transcriptional RNA modification; the second protein interacts with the modified nucleotides; the third protein removes the modification labels [78]. The methylation modification of m6A is regulated by three types of proteases, methyltransferases (writers, including methyltransferase like protein-3/14/16 (METTL3/14/16), RNA-binding motif protein 15/15B (RBM15/15B), zinc finger CCCH type containing 13 (ZC3H13), virlike m6A methyltransferase associated (VIRMA, also known as KIAA1429), cbl proto-oncogene like 1 (CBLL1), and Wilms’ tumor-associated protein (WTAP), demethylases (erasers, including fat mass and obesity-associated (FTO) and alkB homolog 5 (ALKBH5)), and readers (including YTH domain family 1/2/3 (YTHDF1/2/3), YTH domain containing 1/2 (YTHDC1/2), insulinlike growth factor 2 mRNA binding protein 1/2/3 (IGF2BP1/2/3), and heterogeneous nuclear ribonucleoprotein A2B1 (HNRNPA2B1)), and is reversible and can be dynamically regulated [79,80]. These regulatory proteases work together in a coordinated manner to maintain a homeostatic balance of intracellular m6A levels. Reversible m1A methylomes are achieved by the dynamic modulation of m1A RNA-modifying proteins, including m1A methyltransferases such as tRNA methyltransferase 6 noncatalytic subunit (TRMT6)-TRMT61A complex, TRMT10C, TRMT61B and nucleomethylin (NML), m1A demethylases such as ALKBH1, ALKBH3 and FTO, and m1A-dependent RNA-binding proteins such as YTHDF1/2/3 and YTHDC1 [81]. The modification of m7G in mammals is catalyzed by the compounds METTL1 and WD repeat domain 4 (WDR4), a complex that facilitates the installation of m7G in tRNA, miRNA, and mRNA [82,83]. RNA guanine-7 methyltransferase (RNMT) and its cofactor RNMT-activating miniprotein (RAM) actively catalyze m7G. Among them, RNMT is the catalytic subunit, and RAM is the regulatory subunit, which plays the role of activation. Williams–Beuren syndrome chromosome region 22 (WBSCR22) and TRMT112 are responsible for regulating m7G in rRNA. The main function of these regulatory mechanisms is to add m7G to the target RNAs, thereby mediating many key biological processes by modulating RNA production, structure, and maturation [84]. The m5C is reversibly regulated by methyltransferases, including DNA methyltransferase (DNMTs, such as DNMT1, DNMT2, and DNMT3A/3B) and NOP2/Sun RNA methyltransferases (NSUNs), and demethylases, including ten-eleven translocation (TETs), and reader proteins including YTHDF2, Aly/REF Export Factor(ALYREF) and Y-box binding protein 1(YBX1) [85,86]. There are two ways to add 2′-O-Me modification: either by the complex assembly of proteins associated with snoRNA guides (sno(s)RNPs) to carry out site-specific modification or standalone protein enzymes with direct specific site modification [87,88]. In addition, the methylated reader protein TAR RNA-binding protein (TRBP) binds to the methyltransferase FtsJ RNA 2’-O-methyltransferase 3 (FTSJ3) to form a TRBP-FTSJ3 complex, which induces 2′-O-Me [89]. Fibrillarin (FBL) is also a 2’-O-methyltransferase that can form a small nucleolar ribonucleoproteins (snoRNPs) with three other proteins and snoRNA for specific rRNA modifications [90]. Ψ is produced by the isomerization of uridine, catalyzed by pseudouridine synthase (PUS). Thirteen pseudouridine synthases have been identified, which can be divided into two categories, RNA-dependent and RNA-independent PUSs. Dyskerin pseudouridine synthase 1 (DKC1) is the catalytic subunit of the H/ACA snoRNP complex and catalyzes rRNA pseudouridylation. The other 12 writers are PUSs: PUS1, PUSL1, PUS3, TRUB1, TRUB2, PUS7, PUS7L, RPUSD1-4, and PUS10. The cellular localization and RNA targets of these enzymes are fixed. No Ψ erasers and readers have been identified. This is probably because of the formation of relatively inert C-C bonds between the ribose and the base, which leads to the fact that the pseudoureacylation process is irreversible [91]. A-to-I editing is catalyzed by adenosine deaminases acting on the RNA (ADAR) family of enzymes. There are 3 ADAR enzymes, ADAR1 and ADAR2 being catalytically active, while ADAR3 lacks catalytic activity [92].

3. RNA Modifications in Lung Cancer and Other Chronic Lung Diseases

3.1. The Roles of RNA Modifications

RNA modifications have a key influence in the regulation of many fundamental biological processes associated with chronic lung disease (Table 1). The methylation of m6A can affect the RNA stability, localization, turnover, and translation efficiency of genes, thereby regulating cellular processes such as cell self-renewal, differentiation, invasion, and apoptosis, and is even critical for skeletal development and homeostasis [93,94]. The METTL3-METTL14 complex increases the expression of the cyclin-dependent kinase p21 by regulating m6A. This complex enhances m5C methylation, which synergistically promotes p21 expression and affects oxidative stress-induced cellular senescence [95]. In the cardiovascular system, multiple m6A-related regulators promote the progression of atherosclerosis by regulating macrophage polarization and inflammation. WTAP and METTL14 also can affect the phenotypic regulation of vascular smooth muscle cells (VSMCs) via m6A modification [96]. Enhanced m6A RNA methylation generates compensatory cardiac hypertrophy, whereas decreased m6A causes cardiomyocyte remodeling and dysfunction [97]. An increasing number of studies have found that m6A modification plays an important role in controlling the generation and self-renewal of hematopoietic stem cells and in mediating the development and differentiation of T and B lymphocytes from hematopoietic stem cells [98]. YTHDF2, the first recognized “reader” of m6A, can maintain the homeostasis and maturation of natural killer (NK) cells, and positively regulate the antitumor and antiviral activities of NK cells. Its deletion significantly impairs NK cell antitumor and antiviral activity in vivo [99]. METTL3-mediated m6A methylation is also associated with NK cell homeostasis and antitumor immunity [100]. In addition, m6A is associated with apoptosis, autophagy, pyroptosis, ferroptosis, and necrosis [101], and m5C mediates cell proliferation, differentiation, apoptosis, and stress response [102].

3.2. RNA Modifications in the Respiratory System

RNA epigenetic modifications have been broadly reported in lung cancer development and other chronic lung diseases (Figure 2). The most studied m6A modification plays an important role in tumorigenesis, proliferation, and metastasis. Active m6A regulators in lung cancer are related with the activation of multiple signaling pathways, such as DNA replication, RNA metabolism, epithelial–mesenchymal transition (EMT), cell cycle, cell proliferation and apoptosis, energy metabolism, inflammatory response, drug resistance, tumor metastasis and recurrence [103]. Reprogramming of energy metabolism is the hallmarks of cancer. The m6A regulates tumor metabolism by directly regulating nutrient transporters and metabolic enzymes or indirectly by controlling key components in metabolic pathways [104]. Aberrant m6A modification contributes to the progression of malignant tumors and affects patient prognosis. Some m6A-related mRNA markers have also been shown to be independent prognostic biomarkers in patients with different types of cancer [105,106]. Recent studies have found that the m6A methylase METTL3 is abnormally activated in cisplatin-resistant nonsmall-cell lung cancer (NSCLC) cells. METTL3 enhances YAP mRNA translation by introducing YTHDF1/3 and eIF3b into the translation initiation complex and increasing YAP mRNA stability by regulating the MALAT1-miR-1914-3p-YAP axis. This induces NSCLC drug resistance and metastasis [107]. FTO is the first m6A demethylase discovered to promote NSCLC cell growth by demethylating USP7 mRNA or MZF1 mRNA transcripts and increasing their stability and transcriptional levels [108,109]. The 5’-UTR of m6A-modified PDK4 mRNA positively regulates the glycolysis of cells by binding to IGF2BP3, thereby promoting the development of cancer. While METTL14 knockout can reverse the function of IGF2BP3 and play a tumor suppressor role [110]. In addition, IGF2BP1 can also promote cancer development and induce therapeutic resistance by stabilizing oncogenic mRNAs [111]. The m6A modification also affects the mediating tumor metastasis process. When lung cancer brain metastasis (BM) occurs, miR-143-3p was upregulated in paired BM tissues compared with primary lung cancer tissues. METTL3-mediated m6A modification induces the maturation of miR-143-3p, which induces lung cancer invasion and angiogenesis via suppressing the expression of the target gene vasohibin-1 [112]. The lncRNA HCG11 is modulated by METTL14-mediated m6A modification in LUAD. METTL14-mediated HCG11 inhibits the growth of LUAD by targeting large tumor suppressor kinase 1 (LATS1) mRNA through IGF2BP2 [113]. The m7G methyltransferase METTL1 and WDR4 complex is significantly elevated in lung cancer, which can promote lung cancer cell growth and invasion and negatively correlate with patient prognosis. Impaired m7G tRNA modification in the absence of METTL1/WDR4 results in decreased proliferation, colony formation, cell invasion, and tumorigenicity of lung cancer cells [114]. Highly expressed METTL1 can also methylate mature let-7 miRNAs by interfering with inhibitory secondary structure (G-quadruplex) in the pri-miRNA transcript of let-7. The m7G-let-7 miRNA can inhibit lung cancer cell metastasis by reducing the expression of target oncogenes, including high mobility group AT-hook 2 (HMGA2), RAS, and MYC, at the posttranscriptional level [47]. Studies have confirmed that m5C levels can be used as a cancer marker. For example, in lung squamous cell carcinoma (LUSC), the upregulation of m5C-related NSUN3 and NSUN4 is related to poor patient prognosis [115]. In LUAD, cells with high NSUN1 expression are more likely to be poorly differentiated [116]. Abnormally elevated RNA m5C levels can be found in circulating tumor cells from lung cancer patients [117]. The studies of Ψ are mainly concerned with breast, lung, and prostate cancers. In NSCLC, the expression of lncRNAs PCAT1 is highly expressed, and cooperates with DKC1 to influence the proliferation, invasion, and apoptosis of NSCLC cells through the VEGF/AKT/Bcl-2/caspase9 pathway [118]. The rs9309336 may interfere with PUS10 expression, thereby reducing the sensitivity of tumor cells to tumor necrosis factor-associated apoptosis-inducing ligand (TRAIL) [119]. Finally, it promotes the immortalization of tumor cells and the development of lung cancer. The RNA editing protein ADAR promotes LUAD progression by stabilizing transcripts encoding focal adhesion kinase (FAK). The increased abundance of ADAR in the mRNA and protein levels in lung tissues of LUAD patients was associated with tumor recurrence. ADAR increases the stability of FAK mRNA by binding to FAK. FAK blocks the ADAR-induced invasiveness of LUAD cells [120]. A-to-I microRNA editing is correlated with tumor phenotypes in multiple cancer types. Altered editing levels of microRNAs in LUAD may be a potential biomarker [121].
Genes 13 02381 g002 550
Figure 2. The mechanisms and pathways of RNA modifications in lung cancer. The RNA modifications that have been confirmed to be involved in the development and progression of lung cancer include m6A, m7G, m5C, Ψ, and A to I editing. The most studied modification in lung cancer is m6A. METTL3 increases the expression of YAP mRNA by combining YTHDF1/3-eIF3b axis and MALAT1-miR-1914 axis, causing drug resistance and metastasis of lung cancer. The m6A-modified PDK4 mRNA enhances cellular glycolysis through IGF2BP3, thereby promoting tumor growth. The knockdown of METTL14 reversed this process. USP7 mRNA or MZF1 mRNA demethylated by FTO can promote the tumor growth. IGF2BP1 can promote drug resistance and tumor growth by stabilizing oncogenic mRNAs. METTL3 induces the maturation of miR-143 and inhibits the expression of Vasohibin-1, thereby inducing lung cancer brain metastasis. METTL14 regulates the expression of lncRNA HCG11 and then inhibits tumor growth by targeting LATS1 mRNA via IGF2BP2. The m7G methyltransferase METTL1 and WDR4 complex promotes the tumor growth and invasion. In addition, METTTL1 promotes the methylation of Let-7 miRNA, increases the expression of HMGA2, RAS and MYC, and induces the tumor metastasis. The m5C-associated upregulations of NSUN3 and NSUN4 are associated with poor prognosis. Cancer cells with high NSUN1 expression are related with poor differentiated. LncRNA PCAT1 and Ψ methyltransferase DKC1 cooperate to promote the proliferation, invasion and apoptosis of lung cancer cells. ADAR promotes tumor progression by stabilizing FAK transcripts. The expression of Ψ methyltransferase PUS10 is associated with the tumor growth. A-to-I miRNA editing correlates with tumor phenotype.
Figure 2. The mechanisms and pathways of RNA modifications in lung cancer. The RNA modifications that have been confirmed to be involved in the development and progression of lung cancer include m6A, m7G, m5C, Ψ, and A to I editing. The most studied modification in lung cancer is m6A. METTL3 increases the expression of YAP mRNA by combining YTHDF1/3-eIF3b axis and MALAT1-miR-1914 axis, causing drug resistance and metastasis of lung cancer. The m6A-modified PDK4 mRNA enhances cellular glycolysis through IGF2BP3, thereby promoting tumor growth. The knockdown of METTL14 reversed this process. USP7 mRNA or MZF1 mRNA demethylated by FTO can promote the tumor growth. IGF2BP1 can promote drug resistance and tumor growth by stabilizing oncogenic mRNAs. METTL3 induces the maturation of miR-143 and inhibits the expression of Vasohibin-1, thereby inducing lung cancer brain metastasis. METTL14 regulates the expression of lncRNA HCG11 and then inhibits tumor growth by targeting LATS1 mRNA via IGF2BP2. The m7G methyltransferase METTL1 and WDR4 complex promotes the tumor growth and invasion. In addition, METTTL1 promotes the methylation of Let-7 miRNA, increases the expression of HMGA2, RAS and MYC, and induces the tumor metastasis. The m5C-associated upregulations of NSUN3 and NSUN4 are associated with poor prognosis. Cancer cells with high NSUN1 expression are related with poor differentiated. LncRNA PCAT1 and Ψ methyltransferase DKC1 cooperate to promote the proliferation, invasion and apoptosis of lung cancer cells. ADAR promotes tumor progression by stabilizing FAK transcripts. The expression of Ψ methyltransferase PUS10 is associated with the tumor growth. A-to-I miRNA editing correlates with tumor phenotype.
Genes 13 02381 g002
Table
Table 1. A summary of RNA modifications in chronic lung diseases.
Table 1. A summary of RNA modifications in chronic lung diseases.
Modification TypeWriterEraserReaderMechanismReference
m6AMETTL3/14/16,
RBM15/15B, ZC3H3,
VIRMA,
CBLL1,
WTAP,
KIAA1429		FTO, ALKBH5YTHDF1/2/3, YTHDC1/2, IGF2BP1/2/3, HNRNPA2B1(1) Activation of METTL3 promotes drug resistance and metastasis in NSCLC; (2) FTO promotes the growth of NSCLC cells by demethylating USP7 mRNA or MZF1 mRNA transcripts; (3) PDK4 mRNA binds to IGF2BP3 and promotes the development of cancer. METTL14 knockout can reverse the function of IGF2BP3; (4) IGF2BP1 promotes cancer development and induces therapeutic resistance; (5) METTL3 inhibited vasohibin-1 expression and induced lung cancer invasion and angiogenesis; (6) METTL14 inhibits LUAD growth through IGF2BP2; (7) High expression m6A promotes the development and progression of COPD and participates in PM2.5-induced microvascular injury; (8) Inhibition of METTL3 function promotes LPS-induced pneumonia; (9) METTL3 promotes pulmonary fibrosis; (10) ALKBH5 promotes silicon-induced pulmonary fibrosis; (11) YTHDF3 affects eosinophil function in severe asthma.[85,86,87,88,89,90,91,103,104,106,107,108,109,110]
m1ATRMT6-TRMT61A complex, TRMT10C, TRMT61B,
NML		ALKBH1/3,
FTO		YTHDF1-3, YTHDC1
m7GMETTL1 and WDR4 complex,
RNMT and RAM complex,
WBSCR22,
TRMT112		 (1) METTL1 and WDR4 complexes promote lung cancer cell growth and invasion; (2) High expression of METTL1 inhibits metastasis of lung cancer cells; (3) The m7G has a key value in the prognosis and early diagnosis of IPF patients.[47,92,111]
m5CNSUNs,
DNMT1,
DNMT2, DNMT3A/3B		TETsALYREF,
YBX1,
YTHDF2		(1) Upregulation of NSUN3 and NSUN4 is associated with poor prognosis in LUSC patients; (2) Cells with high NSUN1 expression are more likely to be poorly differentiated in LUAD; (3) Increased m5C modification negatively affects normal lung metabolic activities.[93,94,105]
2′-O-MeFBL, FTSJ3 TRBP
ΨDKC1,
PUS1,
PUSL1,
PUS3,
TRUB1,
TRUB2,
PUS7,
PUS7L,
RPUSD1-4,
PUS10		 (1) LncRNAs PCAT1 is highly expressed in NSCLC and cooperates with DKC1 to affect proliferation, invasion and apoptosis of NSCLC cells; (2) PUS10 promotes the immortalization of tumor cells and the development of lung cancer; (3) ADAR promotes LUAD progression.[96,97,98]
A-to-I editingADAR1,
ADAR2		 (1) A-to-I microRNA editing is correlated with tumor phenotypes.[99]
In addition to studies on lung cancer, the effects of RNA modification in other chronic lung diseases such as COPD, pneumonia, asthma, and pulmonary fibrosis have also been explored (Figure 3). Exposure to some toxicants can cause A-to-I editing of lung cells. Potassium chromate (VI) induced upregulation of ADARB1 in human lung cells [122], whereas tetrachlorodibenzodioxin (TCDD) exposure resulted in the decreased expression of ADARB1 [123]. Carbon nanotubes can increase ADAR expression in mouse lungs [124]. It has been found that the expression of m6A RNA methylation regulators is abnormal in COPD, among which the mRNA expressions of IGF2BP3, FTO, METTL3, and YTHDC2 show a tight association with the occurrence of COPD. IGF2BP3, FTO, METTL3, and YTHDC2 have obvious correlations with various important genes enriched in signaling pathways and biological processes that promote the development and progression of COPD [125]. Exposure to fine particulate matter (PM2.5) is an important cause of COPD. METTL16 may regulate sulfate expression through m6A modification, thereby participating in PM2.5-induced microvascular injury and promoting the development of COPD [126]. In addition, the increase of mRNA m5C modification may negatively affect normal lung metabolic activities by upregulating gene expression levels in the lungs of mice exposed to PM2.5 [127]. LncRNA small nucleolar RNA host gene 4 (SNHG4) promotes LPS-induced lung inflammation by inhibiting METTL3-mediated expression of STAT2 mRNA m6A [128]. Myofibroblasts are the main collagen-producing cells in pulmonary fibrosis, which are mostly derived from resident fibroblasts via fibroblast-to-myofibroblast transition (FMT). m6A modification was upregulated in the bleomycin (BLM)-induced pulmonary fibrosis mouse model, FMT-derived myofibroblasts, and lung samples from IPF patients. Silencing METTL3 can inhibit FMT by reducing m6A levels. KCNH6 is involved in the m6A-regulated FMT process. m6A modification regulates KCNH6 expression through YTHDF1 [129,130]. ALKBH5 promotes silica-induced pulmonary fibrosis through miR-320a-3p/forkhead box protein M1 (FOXM1) axis or directly targeting FOXM1. Targeting ALKBH5 can be used to treat pulmonary fibrosis [131]. The m6A methylation has also been implicated in the pathogenesis of asthma, and YTHDF3 has an effect on eosinophils for severe asthma, which can guide future immunotherapy strategies [132]. Increased METTL1 level in IPF patients is associated with poor prognosis. IPF can be divided into two molecular subtypes (subtype 1 and subtype 2) by combining the expression levels of METTL1 and RNMT. Patients with subtype 2 have a more unfavorable prognosis than patients with subtype 1. It suggests that m7G has an important value in predicting the prognosis of IPF patients and early diagnosis of IPF patients [133].

4. Diagnosis and Therapeutic Potential

In recent years, RNA modification has been identified as a novel regulatory mechanism in controlling cancer pathogenesis and treatment response/resistance. The m6A modification plays a multifunctional role in normal and abnormal biological processes, and its regulatory proteins can act as therapeutic targets for cancer and are expected to be biomarkers for overcoming drug resistance [134]. METTL3 is the major catalytic subunit of m6A modification. METTL3 facilitates the translation of a large subset of oncogenic mRNAs and has direct physical and functional interactions with translation initiation factor 3 subunit h (eIF3h). METTL3-eIF3h interaction is required for oncogenic transformation. The depletion of METTL3 inhibits tumorigenicity and sensitizes lung cancer cells to bromodomain-containing protein 4 (BRD4) inhibition [135]. METTL3 promotes tumor development in human lung cancer cells by upregulating the translation of important oncogenes such as EGFR and TAZ. MiR-33a, a negative regulator of METTL3, can directly target the 3’UTR of METTL3 mRNA, reduce its expression, and further inhibit NSCLC cell proliferation [136]. The dynamic m6A methylome is a new mechanism for drug resistance in cancer, such as tyrosine kinase inhibitors (TKIs) [137]. FTO is an oncogene of LUSC, and its increased expression can promote the growth of cancer cells. Knockout of FTO significantly decreased MZF1 mRNA level, and MZF1 gene silencing significantly inhibited the cell viability and invasion of LUSC [109]. Two FTO inhibitors, FB23 and FB23-2, can attenuate the activity of FTO demethylase by directly binding to the activity pocket of FTO demethylase, resulting in a significant lethal effect on cancer cells [138]. Under the action of intermittent hypoxia (IH), the expression of ALKBH5 was upregulated in lung cancer cells, resulting in a decrease in the level of m6A. Knockdown of ALKBH5 under this condition significantly inhibited cell invasion by upregulating the m6A level of FOXM1 mRNA and reducing its translation efficiency [139]. Downregulation of solute carrier 7A11 (SLC7A11) expression in lung cancer inhibits cell proliferation and colony formation. In LUAD, m6A modification destabilizes SLC7A11 mRNA and accelerates mRNA decay upon recognition by YTHDC2, thereby affecting cystine uptake and contributing to antitumor activity [140]. The m6A modification-related inflammatory cytokine interleukin 37 (IL-37) has received extensive attention for the treatment of lung cancer. IL-37 inhibits the proliferative capacity of LUAD cells by regulating RNA methylation. Meanwhile, overexpression of IL-37 decreased the expression of ALKBH5 and thus can also be used to treat NSCLC patients [141]. Gefitinib is indicated for the treatment of locally advanced or metastatic NSCLC. However, acquired resistance limits its long-term efficacy. m6A modification reduces gefitinib resistance (GR) in NSCLC patients via the FTO/YTHDF2/ABCC10 axis [142]. The development of selective inhibitors to RNA modification regulators for future clinical applications would create more effective therapeutic approaches for treating lung cancers and chronic lung diseases.

5. Conclusions and Future Perspectives

In conclusion, this article reviews the recent advances in the function and molecular mechanism of RNA epigenetics in the progression of chronic lung diseases. RNA epigenetics is expected to be a research tool for the development of new diagnostic biomarkers with clinical value. Enzymes involved in regulating RNA modification can be new targets for the treatment of chronic lung diseases. Most of the m6A regulators are upregulated in cancer and play a role in promoting tumor growth. These regulators, including METTL3, METTL14, and WTAP, and their key targets are associated with the clinical characteristics of various cancer patients, which may provide new possibilities for early cancer diagnosis [143]. The combination of m6A targeted drugs with traditional chemotherapy drugs or PD-1/PD-L1 inhibitors has great therapeutic prospects [144]. The mechanism by which IL-37 inhibits the proliferation of LUAD cells and is used to treat NSCLC patients is also related to m6A methylation [141]. YTHDF1 knockout can significantly enhance the therapeutic effect of PD-L1 immune checkpoint blocking, suggesting that YTHDF1 is a potential therapeutic target in tumor immunotherapy [145]. The m5C deletion of mitochondrial RNA in tumor cells can reduce the metastasis and invasion of cancer cells. This means that when cancer patients undergo clinical treatment, they can inhibit the metastasis and spread of cancer cells by inhibiting m5C modification in mitochondria, thus increasing clinical benefits. As an enzyme responsible for modifying RNA, NSUN3 is only used to modify the formation of m5C, so it is a very promising drug target [146]. RNA modification provides a new research direction for the early diagnosis and treatment of tumors.
In the future, precision medicine based on RNA epigenetics may target individual patients with chronic lung diseases for diagnosis and treatment. However, the function of these chemical modifications in both coding and noncoding RNAs remains in its infancy, and collaborative efforts are still needed to establish a clear link between RNA epigenetics and chronic lung diseases. At present, many new methods of RNA modification have emerged, among which Direct RNA sequencing is the representative one. Through the unique way of the library building and relying on the algorithm, the collection of RNA modification information at the single base level can be achieved. The development of RNA modification quantitative map databases (such as DirectRMDB) based on this sequencing method also undoubtedly opens another direction for RNA modification detection [147]. In brief, the advances in RNA epigenetics detection technologies will undoubtedly lead to the discovery of new mechanisms regulating gene expression in chronic lung diseases in the future.

Author Contributions

Writing—original draft preparation, X.W. and Z.G.; writing—review and editing, Z.G.; supervision, F.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by The National Natural Science Foundation of China (Grant number: 82200043); Quanzhou City Science & Technology Program of China (Grant number: 2018N008S); Natural Science Foundation of Fujian Province (Grant number: 2020J05052); Startup Fund for Scientific Research, Fujian Medical University (Grant No. 2019QH1121).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yhee, J.Y.; Im, J.; Nho, R.S. Advanced Therapeutic Strategies for Chronic Lung Disease Using Nanoparticle-Based Drug Delivery. J. Clin. Med. 2016, 5, 82. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Ask, K.; Eickelberg, O.; Gauldie, J.; Kaminski, N.; Kolb, M. Have advanced research technologies made real impact on respiratory medicine? Respirology 2010, 15, 876–880. [Google Scholar] [CrossRef] [PubMed]
  3. Fingerlin, T.E.; Murphy, E.; Zhang, W.; Peljto, A.L.; Brown, K.K.; Steele, M.P.; Loyd, J.E.; Cosgrove, G.P.; Lynch, D.; Groshong, S.; et al. Genome-wide association study identifies multiple susceptibility loci for pulmonary fibrosis. Nat. Genet. 2013, 45, 613–620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Pleasance, E.D.; Stephens, P.J.; O’Meara, S.; McBride, D.J.; Meynert, A.; Jones, D.; Lin, M.L.; Beare, D.; Lau, K.W.; Greenman, C.; et al. A small-cell lung cancer genome with complex signatures of tobacco exposure. Nature 2010, 463, 184–190. [Google Scholar] [CrossRef] [Green Version]
  5. Soler Artigas, M.; Loth, D.W.; Wain, L.V.; Gharib, S.A.; Obeidat, M.; Tang, W.; Zhai, G.; Zhao, J.H.; Smith, A.V.; Huffman, J.E.; et al. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat. Genet. 2011, 43, 1082–1090. [Google Scholar] [CrossRef] [Green Version]
  6. Lee, A.J.; Swanton, C. Tumour heterogeneity and drug resistance: Personalising cancer medicine through functional genomics. Biochem. Pharmacol. 2012, 83, 1013–1020. [Google Scholar] [CrossRef]
  7. Esteller, M. Epigenetics in cancer. N. Engl. J. Med. 2008, 358, 1148–1159. [Google Scholar] [CrossRef]
  8. Dominissini, D.; Moshitch-Moshkovitz, S.; Schwartz, S.; Salmon-Divon, M.; Ungar, L.; Osenberg, S.; Cesarkas, K.; Jacob-Hirsch, J.; Amariglio, N.; Kupiec, M.; et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature 2012, 485, 201–206. [Google Scholar] [CrossRef]
  9. Amort, T.; Rieder, D.; Wille, A.; Khokhlova-Cubberley, D.; Riml, C.; Trixl, L.; Jia, X.Y.; Micura, R.; Lusser, A. Distinct 5-methylcytosine profiles in poly(A) RNA from mouse embryonic stem cells and brain. Genome Biol. 2017, 18, 1. [Google Scholar] [CrossRef] [Green Version]
  10. Carlile, T.M.; Rojas-Duran, M.F.; Zinshteyn, B.; Shin, H.; Bartoli, K.M.; Gilbert, W.V. Pseudouridine profiling reveals regulated mRNA pseudouridylation in yeast and human cells. Nature 2014, 515, 143–146. [Google Scholar] [CrossRef]
  11. Dominissini, D.; Nachtergaele, S.; Moshitch-Moshkovitz, S.; Peer, E.; Kol, N.; Ben-Haim, M.S.; Dai, Q.; Di Segni, A.; Salmon-Divon, M.; Clark, W.C.; et al. The dynamic N1-methyladenosine methylome in eukaryotic messenger RNA. Nature 2016, 530, 441–446. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Li, X.; Xiong, X.; Wang, K.; Wang, L.; Shu, X.; Ma, S.; Yi, C. Transcriptome-wide mapping reveals reversible and dynamic N1-methyladenosine methylome. Nat. Chem. Biol. 2016, 12, 311–316. [Google Scholar] [CrossRef] [PubMed]
  13. Dowdy, S.F. Overcoming cellular barriers for RNA therapeutics. Nat. Biotechnol. 2017, 35, 222–229. [Google Scholar] [CrossRef] [PubMed]
  14. Khan, R.I.N.; Malla, W.A. m6A modification of RNA and its role in cancer, with a special focus on lung cancer. Genomics 2021, 113, 2860–2869. [Google Scholar] [CrossRef]
  15. Teng, P.C.; Liang, Y.; Yarmishyn, A.A.; Hsiao, Y.J.; Lin, T.Y.; Lin, T.W.; Teng, Y.C.; Yang, Y.P.; Wang, M.L.; Chien, C.S.; et al. RNA Modifications and Epigenetics in Modulation of Lung Cancer and Pulmonary Diseases. Int. J. Mol. Sci. 2021, 22, 592. [Google Scholar] [CrossRef]
  16. Ma, L.; Xue, X.; Zhang, X.; Yu, K.; Xu, X.; Tian, X.; Miao, Y.; Meng, F.; Liu, X.; Guo, S.; et al. The essential roles of m6A RNA modification to stimulate ENO1-dependent glycolysis and tumorigenesis in lung adenocarcinoma. J. Exp. Clin. Cancer Res. CR 2022, 41, 36. [Google Scholar] [CrossRef]
  17. Gebert, L.F.R.; MacRae, I.J. Regulation of microRNA function in animals. Nat. Rev. Mol. Cell Biol. 2019, 20, 21–37. [Google Scholar] [CrossRef]
  18. Yao, R.W.; Wang, Y.; Chen, L.L. Cellular functions of long noncoding RNAs. Nat. Cell Biol. 2019, 21, 542–551. [Google Scholar] [CrossRef]
  19. Karijolich, J.; Yu, Y.T. Spliceosomal snRNA modifications and their function. RNA Biol. 2010, 7, 192–204. [Google Scholar] [CrossRef]
  20. Jia, G.; Fu, Y.; He, C. Reversible RNA adenosine methylation in biological regulation. Trends Genet. TIG 2013, 29, 108–115. [Google Scholar] [CrossRef]
  21. Noh, J.H.; Kim, K.M.; McClusky, W.G.; Abdelmohsen, K.; Gorospe, M. Cytoplasmic functions of long noncoding RNAs. Wiley Interdiscip. Rev. RNA 2018, 9, e1471. [Google Scholar] [CrossRef] [PubMed]
  22. Yin, X.; Liang, C.; Feng, Y.; Zhang, H.; Wang, Y.; Li, Y. Research progress on synthetic scaffold in metabolic engineering—A review. Sheng Wu Gong Cheng Xue Bao—Chin. J. Biotechnol. 2019, 35, 363–374. [Google Scholar] [CrossRef]
  23. Den Boon, J.A.; Ahlquist, P. Organelle-like membrane compartmentalization of positive-strand RNA virus replication factories. Annu. Rev. Microbiol. 2010, 64, 241–256. [Google Scholar] [CrossRef] [PubMed]
  24. Howard, M.J.; Liu, X.; Lim, W.H.; Klemm, B.P.; Fierke, C.A.; Koutmos, M.; Engelke, D.R. RNase P enzymes: Divergent scaffolds for a conserved biological reaction. RNA Biol. 2013, 10, 909–914. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  25. Jia, G.; Fu, Y.; Zhao, X.; Dai, Q.; Zheng, G.; Yang, Y.; Yi, C.; Lindahl, T.; Pan, T.; Yang, Y.G.; et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat. Chem. Biol. 2011, 7, 885–887. [Google Scholar] [CrossRef]
  26. Liu, F.; Clark, W.; Luo, G.; Wang, X.; Fu, Y.; Wei, J.; Wang, X.; Hao, Z.; Dai, Q.; Zheng, G.; et al. ALKBH1-Mediated tRNA Demethylation Regulates Translation. Cell 2016, 167, 1897. [Google Scholar] [CrossRef] [Green Version]
  27. Lewis, C.J.; Pan, T.; Kalsotra, A. RNA modifications and structures cooperate to guide RNA-protein interactions. Nat. Rev. Mol. Cell Biol. 2017, 18, 202–210. [Google Scholar] [CrossRef] [Green Version]
  28. Ontiveros, R.J.; Stoute, J.; Liu, K.F. The chemical diversity of RNA modifications. Biochem. J. 2019, 476, 1227–1245. [Google Scholar] [CrossRef]
  29. Batista, P.J.; Molinie, B.; Wang, J.; Qu, K.; Zhang, J.; Li, L.; Bouley, D.M.; Lujan, E.; Haddad, B.; Daneshvar, K.; et al. m6A RNA modification controls cell fate transition in mammalian embryonic stem cells. Cell Stem Cell 2014, 15, 707–719. [Google Scholar] [CrossRef] [Green Version]
  30. Zaccara, S.; Ries, R.J.; Jaffrey, S.R. Reading, writing and erasing mRNA methylation. Nat. Rev. Mol. Cell Biol. 2019, 20, 608–624. [Google Scholar] [CrossRef]
  31. Zheng, H.X.; Zhang, X.S.; Sui, N. Advances in the profiling of N6-methyladenosine (m6A) modifications. Biotechnol. Adv. 2020, 45, 107656. [Google Scholar] [CrossRef] [PubMed]
  32. Li, X.; Xiong, X.; Yi, C. Epitranscriptome sequencing technologies: Decoding RNA modifications. Nat. Methods 2016, 14, 23–31. [Google Scholar] [CrossRef] [PubMed]
  33. Zhao, B.S.; Roundtree, I.A.; He, C. Post-transcriptional gene regulation by mRNA modifications. Nat. Rev. Mol. Cell Biol. 2017, 18, 31–42. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Motorin, Y.; Helm, M. RNA nucleotide methylation. Wiley Interdiscip. Rev. RNA 2011, 2, 611–631. [Google Scholar] [CrossRef] [PubMed]
  35. Glaich, O.; Parikh, S.; Bell, R.E.; Mekahel, K.; Donyo, M.; Leader, Y.; Shayevitch, R.; Sheinboim, D.; Yannai, S.; Hollander, D.; et al. DNA methylation directs microRNA biogenesis in mammalian cells. Nat. Commun. 2019, 10, 5657. [Google Scholar] [CrossRef] [Green Version]
  36. He, R.Z.; Jiang, J.; Luo, D.X. The functions of N6-methyladenosine modification in lncRNAs. Genes Dis. 2020, 7, 598–605. [Google Scholar] [CrossRef]
  37. Yang, Y.; Fan, X.; Mao, M.; Song, X.; Wu, P.; Zhang, Y.; Jin, Y.; Yang, Y.; Chen, L.L.; Wang, Y.; et al. Extensive translation of circular RNAs driven by N6-methyladenosine. Cell Res. 2017, 27, 626–641. [Google Scholar] [CrossRef] [Green Version]
  38. Roundtree, I.A.; Evans, M.E.; Pan, T.; He, C. Dynamic RNA Modifications in Gene Expression Regulation. Cell 2017, 169, 1187–1200. [Google Scholar] [CrossRef] [Green Version]
  39. Jiapaer, Z.; Su, D.; Hua, L.; Lehmann, H.I.; Gokulnath, P.; Vulugundam, G.; Song, S.; Zhang, L.; Gong, Y.; Li, G. Regulation and roles of RNA modifications in aging-related diseases. Aging Cell 2022, 21, e13657. [Google Scholar] [CrossRef]
  40. Deng, X.; Su, R.; Weng, H.; Huang, H.; Li, Z.; Chen, J. RNA N6-methyladenosine modification in cancers: Current status and perspectives. Cell Res. 2018, 28, 507–517. [Google Scholar] [CrossRef]
  41. Zhang, C.; Jia, G. Reversible RNA Modification N1-methyladenosine (m1A) in mRNA and tRNA. Genom. Proteom. Bioinform. 2018, 16, 155–161. [Google Scholar] [CrossRef] [PubMed]
  42. Kawarada, L.; Suzuki, T.; Ohira, T.; Hirata, S.; Miyauchi, K.; Suzuki, T. ALKBH1 is an RNA dioxygenase responsible for cytoplasmic and mitochondrial tRNA modifications. Nucleic Acids Res. 2017, 45, 7401–7415. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Li, X.; Xiong, X.; Zhang, M.; Wang, K.; Chen, Y.; Zhou, J.; Mao, Y.; Lv, J.; Yi, D.; Chen, X.W.; et al. Base-Resolution Mapping Reveals Distinct m1A Methylome in Nuclear- and Mitochondrial-Encoded Transcripts. Mol. Cell 2017, 68, 993–1005.e9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Ramanathan, A.; Robb, G.B.; Chan, S.H. mRNA capping: Biological functions and applications. Nucleic Acids Res. 2016, 44, 7511–7526. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Sloan, K.E.; Warda, A.S.; Sharma, S.; Entian, K.D.; Lafontaine, D.L.J.; Bohnsack, M.T. Tuning the ribosome: The influence of rRNA modification on eukaryotic ribosome biogenesis and function. RNA Biol. 2017, 14, 1138–1152. [Google Scholar] [CrossRef] [Green Version]
  46. Tomikawa, C. 7-Methylguanosine Modifications in Transfer RNA (tRNA). Int. J. Mol. Sci. 2018, 19, 4080. [Google Scholar] [CrossRef] [Green Version]
  47. Pandolfini, L.; Barbieri, I.; Bannister, A.J.; Hendrick, A.; Andrews, B.; Webster, N.; Murat, P.; Mach, P.; Brandi, R.; Robson, S.C.; et al. METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation. Mol. Cell 2019, 74, 1278–1290 e1279. [Google Scholar] [CrossRef] [Green Version]
  48. Chen, Y.S.; Yang, W.L.; Zhao, Y.L.; Yang, Y.G. Dynamic transcriptomic m5C and its regulatory role in RNA processing. Wiley Interdiscip. Rev. RNA 2021, 12, e1639. [Google Scholar] [CrossRef]
  49. Yang, X.; Yang, Y.; Sun, B.F.; Chen, Y.S.; Xu, J.W.; Lai, W.Y.; Li, A.; Wang, X.; Bhattarai, D.P.; Xiao, W.; et al. 5-methylcytosine promotes mRNA export—NSUN2 as the methyltransferase and ALYREF as an m5C reader. Cell Res. 2017, 27, 606–625. [Google Scholar] [CrossRef] [Green Version]
  50. Zhang, X.; Liu, Z.; Yi, J.; Tang, H.; Xing, J.; Yu, M.; Tong, T.; Shang, Y.; Gorospe, M.; Wang, W. The tRNA methyltransferase NSun2 stabilizes p16INK(4) mRNA by methylating the 3'-untranslated region of p16. Nat. Commun. 2012, 3, 712. [Google Scholar] [CrossRef]
  51. Hoernes, T.P.; Clementi, N.; Faserl, K.; Glasner, H.; Breuker, K.; Lindner, H.; Huttenhofer, A.; Erlacher, M.D. Nucleotide modifications within bacterial messenger RNAs regulate their translation and are able to rewire the genetic code. Nucleic Acids Res. 2016, 44, 852–862. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Ge, J.; Liu, H.; Yu, Y.T. Regulation of pre-mRNA splicing in Xenopus oocytes by targeted 2′-O-methylation. RNA 2010, 16, 1078–1085. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Ji, L.; Chen, X. Regulation of small RNA stability: Methylation and beyond. Cell Res. 2012, 22, 624–636. [Google Scholar] [CrossRef] [PubMed]
  54. Wu, Y.; Zhan, S.; Xu, Y.; Gao, X. RNA modifications in cardiovascular diseases, the potential therapeutic targets. Life Sci. 2021, 278, 119565. [Google Scholar] [CrossRef] [PubMed]
  55. Eyler, D.E.; Franco, M.K.; Batool, Z.; Wu, M.Z.; Dubuke, M.L.; Dobosz-Bartoszek, M.; Jones, J.D.; Polikanov, Y.S.; Roy, B.; Koutmou, K.S. Pseudouridinylation of mRNA coding sequences alters translation. Proc. Natl. Acad. Sci. USA 2019, 116, 23068–23074. [Google Scholar] [CrossRef] [PubMed]
  56. Ma, J.; Zhang, L.; Chen, S.; Liu, H. A brief review of RNA modification related database resources. Methods 2022, 203, 342–353. [Google Scholar] [CrossRef]
  57. Cantara, W.A.; Crain, P.F.; Rozenski, J.; McCloskey, J.A.; Harris, K.A.; Zhang, X.; Vendeix, F.A.; Fabris, D.; Agris, P.F. The RNA Modification Database, RNAMDB: 2011 update. Nucleic Acids Res. 2011, 39, D195–D201. [Google Scholar] [CrossRef] [Green Version]
  58. Boccaletto, P.; Stefaniak, F.; Ray, A.; Cappannini, A.; Mukherjee, S.; Purta, E.; Kurkowska, M.; Shirvanizadeh, N.; Destefanis, E.; Groza, P.; et al. MODOMICS: A database of RNA modification pathways. 2021 update. Nucleic Acids Res. 2022, 50, D231–D235. [Google Scholar] [CrossRef]
  59. Liu, H.; Wang, H.; Wei, Z.; Zhang, S.; Hua, G.; Zhang, S.W.; Zhang, L.; Gao, S.J.; Meng, J.; Chen, X.; et al. MeT-DB V2.0: Elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome. Nucleic Acids Res. 2018, 46, D281–D287. [Google Scholar] [CrossRef] [Green Version]
  60. Xuan, J.J.; Sun, W.J.; Lin, P.H.; Zhou, K.R.; Liu, S.; Zheng, L.L.; Qu, L.H.; Yang, J.H. RMBase v2.0: Deciphering the map of RNA modifications from epitranscriptome sequencing data. Nucleic Acids Res. 2018, 46, D327–D334. [Google Scholar] [CrossRef]
  61. Tang, Y.; Chen, K.; Song, B.; Ma, J.; Wu, X.; Xu, Q.; Wei, Z.; Su, J.; Liu, G.; Rong, R.; et al. m6A-Atlas: A comprehensive knowledgebase for unraveling the N6-methyladenosine (m6A) epitranscriptome. Nucleic Acids Res. 2021, 49, D134–D143. [Google Scholar] [CrossRef] [PubMed]
  62. Deng, S.; Zhang, H.; Zhu, K.; Li, X.; Ye, Y.; Li, R.; Liu, X.; Lin, D.; Zuo, Z.; Zheng, J. M6A2Target: A comprehensive database for targets of m6A writers, erasers and readers. Brief. Bioinform. 2021, 22, bbaa055. [Google Scholar] [CrossRef] [PubMed]
  63. Ma, J.; Song, B.; Wei, Z.; Huang, D.; Zhang, Y.; Su, J.; de Magalhaes, J.P.; Rigden, D.J.; Meng, J.; Chen, K. m5C-Atlas: A comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome. Nucleic Acids Res. 2022, 50, D196–D203. [Google Scholar] [CrossRef]
  64. Song, B.; Tang, Y.; Chen, K.; Wei, Z.; Rong, R.; Lu, Z.; Su, J.; de Magalhaes, J.P.; Rigden, D.J.; Meng, J. m7GHub: Deciphering the location, regulation and pathogenesis of internal mRNA N7-methylguanosine (m7G) sites in human. Bioinformatics 2020, 36, 3528–3536. [Google Scholar] [CrossRef] [PubMed]
  65. Liu, S.; Zhu, A.; He, C.; Chen, M. REPIC: A database for exploring the N6-methyladenosine methylome. Genome Biol. 2020, 21, 100. [Google Scholar] [CrossRef]
  66. Zheng, Y.; Nie, P.; Peng, D.; He, Z.; Liu, M.; Xie, Y.; Miao, Y.; Zuo, Z.; Ren, J. m6AVar: A database of functional variants involved in m6A modification. Nucleic Acids Res. 2018, 46, D139–D145. [Google Scholar] [CrossRef]
  67. Song, B.; Huang, D.; Zhang, Y.; Wei, Z.; Su, J.; Pedro de Magalhaes, J.; Rigden, D.J.; Meng, J.; Chen, K. m6A-TSHub: Unveiling the Context-specific m6A Methylation and m6A-affecting Mutations in 23 Human Tissues. Genom. Proteom. Bioinform. 2022, in press. [Google Scholar] [CrossRef]
  68. Han, Y.; Feng, J.; Xia, L.; Dong, X.; Zhang, X.; Zhang, S.; Miao, Y.; Xu, Q.; Xiao, S.; Zuo, Z.; et al. CVm6A: A Visualization and Exploration Database for m6As in Cell Lines. Cells 2019, 8, 168. [Google Scholar] [CrossRef] [Green Version]
  69. Luo, X.; Li, H.; Liang, J.; Zhao, Q.; Xie, Y.; Ren, J.; Zuo, Z. RMVar: An updated database of functional variants involved in RNA modifications. Nucleic Acids Res. 2021, 49, D1405–D1412. [Google Scholar] [CrossRef]
  70. Song, B.; Wang, X.; Liang, Z.; Ma, J.; Huang, D.; Wang, Y.; de Magalhaes, J.P.; Rigden, D.J.; Meng, J.; Liu, G.; et al. RMDisease V2.0: An updated database of genetic variants that affect RNA modifications with disease and trait implication. Nucleic Acids Res. 2022, 1, gkac750. [Google Scholar] [CrossRef]
  71. Picardi, E.; Regina, T.M.; Brennicke, A.; Quagliariello, C. REDIdb: The RNA editing database. Nucleic Acids Res. 2007, 35, D173–D177. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Ramaswami, G.; Li, J.B. RADAR: A rigorously annotated database of A-to-I RNA editing. Nucleic Acids Res. 2014, 42, D109–D113. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  73. Kiran, A.; Baranov, P.V. DARNED: A DAtabase of RNa EDiting in humans. Bioinformatics 2010, 26, 1772–1776. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Picardi, E.; D’Erchia, A.M.; Lo Giudice, C.; Pesole, G. REDIportal: A comprehensive database of A-to-I RNA editing events in humans. Nucleic Acids Res. 2017, 45, D750–D757. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Jiang, S.; Xie, Y.; He, Z.; Zhang, Y.; Zhao, Y.; Chen, L.; Zheng, Y.; Miao, Y.; Zuo, Z.; Ren, J. m6ASNP: A tool for annotating genetic variants by m6A function. GigaScience 2018, 7, giy035. [Google Scholar] [CrossRef] [Green Version]
  76. Song, B.; Chen, K.; Tang, Y.; Wei, Z.; Su, J.; de Magalhaes, J.P.; Rigden, D.J.; Meng, J. ConsRM: Collection and large-scale prediction of the evolutionarily conserved RNA methylation sites, with implications for the functional epitranscriptome. Brief. Bioinform. 2021, 22, bbab088. [Google Scholar] [CrossRef]
  77. Guo, B.; Zhang, H.; Wang, J.; Wu, R.; Zhang, J.; Zhang, Q.; Xu, L.; Shen, M.; Zhang, Z.; Gu, F.; et al. Identification of the Signature Associated With m6A RNA Methylation Regulators and m6A-Related Genes and Construction of the Risk Score for Prognostication in Early-Stage Lung Adenocarcinoma. Front. Genet. 2021, 12, 656114. [Google Scholar] [CrossRef]
  78. Dinescu, S.; Ignat, S.; Lazar, A.D.; Constantin, C.; Neagu, M.; Costache, M. Epitranscriptomic Signatures in lncRNAs and Their Possible Roles in Cancer. Genes 2019, 10, 52. [Google Scholar] [CrossRef] [Green Version]
  79. Yang, Y.; Hsu, P.J.; Chen, Y.S.; Yang, Y.G. Dynamic transcriptomic m6A decoration: Writers, erasers, readers and functions in RNA metabolism. Cell Res. 2018, 28, 616–624. [Google Scholar] [CrossRef] [Green Version]
  80. Jiang, X.; Liu, B.; Nie, Z.; Duan, L.; Xiong, Q.; Jin, Z.; Yang, C.; Chen, Y. The role of m6A modification in the biological functions and diseases. Signal Transduct. Target. Ther. 2021, 6, 74. [Google Scholar] [CrossRef]
  81. Jin, H.; Huo, C.; Zhou, T.; Xie, S. m1A RNA Modification in Gene Expression Regulation. Genes 2022, 13, 910. [Google Scholar] [CrossRef] [PubMed]
  82. Alexandrov, A.; Martzen, M.R.; Phizicky, E.M. Two proteins that form a complex are required for 7-methylguanosine modification of yeast tRNA. RNA 2002, 8, 1253–1266. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Haag, S.; Kretschmer, J.; Bohnsack, M.T. WBSCR22/Merm1 is required for late nuclear pre-ribosomal RNA processing and mediates N7-methylation of G1639 in human 18S rRNA. RNA 2015, 21, 180–187. [Google Scholar] [CrossRef] [Green Version]
  84. Luo, Y.; Yao, Y.; Wu, P.; Zi, X.; Sun, N.; He, J. The potential role of N7-methylguanosine (m7G) in cancer. J. Hematol. Oncol. 2022, 15, 63. [Google Scholar] [CrossRef] [PubMed]
  85. Zhang, Q.; Liu, F.; Chen, W.; Miao, H.; Liang, H.; Liao, Z.; Zhang, Z.; Zhang, B. The role of RNA m5C modification in cancer metastasis. Int. J. Biol. Sci. 2021, 17, 3369–3380. [Google Scholar] [CrossRef]
  86. Dai, X.; Gonzalez, G.; Li, L.; Li, J.; You, C.; Miao, W.; Hu, J.; Fu, L.; Zhao, Y.; Li, R.; et al. YTHDF2 Binds to 5-Methylcytosine in RNA and Modulates the Maturation of Ribosomal RNA. Anal. Chem. 2020, 92, 1346–1354. [Google Scholar] [CrossRef]
  87. Nostramo, R.T.; Hopper, A.K. Beyond rRNA and snRNA: tRNA as a 2’-O-methylation target for nucleolar and Cajal body box C/D RNPs. Genes Dev. 2019, 33, 739–740. [Google Scholar] [CrossRef]
  88. Vitali, P.; Kiss, T. Cooperative 2’-O-methylation of the wobble cytidine of human elongator tRNA(Met)(CAT) by a nucleolar and a Cajal body-specific box C/D RNP. Genes Dev. 2019, 33, 741–746. [Google Scholar] [CrossRef] [Green Version]
  89. Ringeard, M.; Marchand, V.; Decroly, E.; Motorin, Y.; Bennasser, Y. FTSJ3 is an RNA 2'-O-methyltransferase recruited by HIV to avoid innate immune sensing. Nature 2019, 565, 500–504. [Google Scholar] [CrossRef]
  90. Zhou, F.; Aroua, N.; Liu, Y.; Rohde, C.; Cheng, J.; Wirth, A.K.; Fijalkowska, D.; Gollner, S.; Lotze, M.; Yun, H.; et al. A dynamic rRNA ribomethylome drives stemness in acute myeloid leukemia. Cancer Discov. 2022, CD-22-0210. [Google Scholar] [CrossRef]
  91. Cui, L.; Ma, R.; Cai, J.; Guo, C.; Chen, Z.; Yao, L.; Wang, Y.; Fan, R.; Wang, X.; Shi, Y. RNA modifications: Importance in immune cell biology and related diseases. Signal Transduct. Targets Ther. 2022, 7, 334. [Google Scholar] [CrossRef] [PubMed]
  92. Tan, M.H.; Li, Q.; Shanmugam, R.; Piskol, R.; Kohler, J.; Young, A.N.; Liu, K.I.; Zhang, R.; Ramaswami, G.; Ariyoshi, K.; et al. Dynamic landscape and regulation of RNA editing in mammals. Nature 2017, 550, 249–254. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  93. Li, Y.; Meng, L.; Zhao, B. The roles of N6-methyladenosine methylation in the regulation of bone development, bone remodeling and osteoporosis. Pharmacol. Ther. 2022, 238, 108174. [Google Scholar] [CrossRef] [PubMed]
  94. Chen, X.Y.; Zhang, J.; Zhu, J.S. The role of m6A RNA methylation in human cancer. Mol. Cancer 2019, 18, 103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  95. Li, Q.; Li, X.; Tang, H.; Jiang, B.; Dou, Y.; Gorospe, M.; Wang, W. NSUN2-Mediated m5C Methylation and METTL3/METTL14-Mediated m6A Methylation Cooperatively Enhance p21 Translation. J. Cell. Biochem. 2017, 118, 2587–2598. [Google Scholar] [CrossRef] [PubMed]
  96. Chen, L.H.; Zhao, Y.Y.; Huang, L.; Li, Y.Z.; Xu, H.Q.; Yang, C.; Zhang, C. The potential roles of RNA N6-methyladenosine in atherosclerosis. Eur. Rev. Med. Pharmacol. Sci. 2022, 26, 1075–1083. [Google Scholar] [CrossRef]
  97. Dorn, L.E.; Lasman, L.; Chen, J.; Xu, X.; Hund, T.J.; Medvedovic, M.; Hanna, J.H.; van Berlo, J.H.; Accornero, F. The N6-Methyladenosine mRNA Methylase METTL3 Controls Cardiac Homeostasis and Hypertrophy. Circulation 2019, 139, 533–545. [Google Scholar] [CrossRef]
  98. Zhao, C.; Xu, G.; Zhang, X.; Ye, Y.; Cai, W.; Shao, Q. RNA m6A modification orchestrates the rhythm of immune cell development from hematopoietic stem cells to T and B cells. Front. Immunol. 2022, 13, 839291. [Google Scholar] [CrossRef]
  99. Ma, S.; Yan, J.; Barr, T.; Zhang, J.; Chen, Z.; Wang, L.S.; Sun, J.C.; Chen, J.; Caligiuri, M.A.; Yu, J. The RNA m6A reader YTHDF2 controls NK cell antitumor and antiviral immunity. J. Exp. Med. 2021, 218, e20210279. [Google Scholar] [CrossRef]
  100. Song, H.; Song, J.; Cheng, M.; Zheng, M.; Wang, T.; Tian, S.; Flavell, R.A.; Zhu, S.; Li, H.B.; Ding, C.; et al. METTL3-mediated m6A RNA methylation promotes the anti-tumour immunity of natural killer cells. Nat. Commun. 2021, 12, 5522. [Google Scholar] [CrossRef]
  101. Liu, L.; Li, H.; Hu, D.; Wang, Y.; Shao, W.; Zhong, J.; Yang, S.; Liu, J.; Zhang, J. Insights into N6-methyladenosine and programmed cell death in cancer. Mol. Cancer 2022, 21, 32. [Google Scholar] [CrossRef] [PubMed]
  102. Li, M.; Tao, Z.; Zhao, Y.; Li, L.; Zheng, J.; Li, Z.; Chen, X. 5-methylcytosine RNA methyltransferases and their potential roles in cancer. J. Transl. Med. 2022, 20, 214. [Google Scholar] [CrossRef] [PubMed]
  103. Li, N.; Zhan, X. Identification of pathology-specific regulators of m6A RNA modification to optimize lung cancer management in the context of predictive, preventive, and personalized medicine. EPMA J. 2020, 11, 485–504. [Google Scholar] [CrossRef] [PubMed]
  104. Han, X.; Wang, L.; Han, Q. Advances in the role of m6A RNA modification in cancer metabolic reprogramming. Cell Biosci. 2020, 10, 117. [Google Scholar] [CrossRef] [PubMed]
  105. Du, J.; Hou, K.; Mi, S.; Ji, H.; Ma, S.; Ba, Y.; Hu, S.; Xie, R.; Chen, L. Malignant Evaluation and Clinical Prognostic Values of m6A RNA Methylation Regulators in Glioblastoma. Front. Oncol. 2020, 10, 208. [Google Scholar] [CrossRef]
  106. Chen, M.; Nie, Z.Y.; Wen, X.H.; Gao, Y.H.; Cao, H.; Zhang, S.F. m6A RNA methylation regulators can contribute to malignant progression and impact the prognosis of bladder cancer. Biosci. Rep. 2019, 39, BSR20192892. [Google Scholar] [CrossRef] [Green Version]
  107. Jin, D.; Guo, J.; Wu, Y.; Du, J.; Yang, L.; Wang, X.; Di, W.; Hu, B.; An, J.; Kong, L.; et al. m6A mRNA methylation initiated by METTL3 directly promotes YAP translation and increases YAP activity by regulating the MALAT1-miR-1914-3p-YAP axis to induce NSCLC drug resistance and metastasis. J. Hematol. Oncol. 2019, 12, 135. [Google Scholar] [CrossRef] [Green Version]
  108. Li, J.; Han, Y.; Zhang, H.; Qian, Z.; Jia, W.; Gao, Y.; Zheng, H.; Li, B. The m6A demethylase FTO promotes the growth of lung cancer cells by regulating the m6A level of USP7 mRNA. Biochem. Biophys. Res. Commun. 2019, 512, 479–485. [Google Scholar] [CrossRef]
  109. Liu, J.; Ren, D.; Du, Z.; Wang, H.; Zhang, H.; Jin, Y. m6A demethylase FTO facilitates tumor progression in lung squamous cell carcinoma by regulating MZF1 expression. Biochem. Biophys. Res. Commun. 2018, 502, 456–464. [Google Scholar] [CrossRef]
  110. Huang, H.; Weng, H.; Sun, W.; Qin, X.; Shi, H.; Wu, H.; Zhao, B.S.; Mesquita, A.; Liu, C.; Yuan, C.L.; et al. Recognition of RNA N6-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat. Cell Biol. 2018, 20, 285–295. [Google Scholar] [CrossRef]
  111. Elcheva, I.A.; Wood, T.; Chiarolanzio, K.; Chim, B.; Wong, M.; Singh, V.; Gowda, C.P.; Lu, Q.; Hafner, M.; Dovat, S.; et al. RNA-binding protein IGF2BP1 maintains leukemia stem cell properties by regulating HOXB4, MYB, and ALDH1A1. Leukemia 2020, 34, 1354–1363. [Google Scholar] [CrossRef] [PubMed]
  112. Wang, H.; Deng, Q.; Lv, Z.; Ling, Y.; Hou, X.; Chen, Z.; Dinglin, X.; Ma, S.; Li, D.; Wu, Y.; et al. N6-methyladenosine induced miR-143-3p promotes the brain metastasis of lung cancer via regulation of VASH1. Mol. Cancer 2019, 18, 181. [Google Scholar] [CrossRef] [Green Version]
  113. Mao, J.; Qiu, H.; Guo, L. LncRNA HCG11 mediated by METTL14 inhibits the growth of lung adenocarcinoma via IGF2BP2/LATS1. Biochem. Biophys. Res. Commun. 2021, 580, 74–80. [Google Scholar] [CrossRef] [PubMed]
  114. Ma, J.; Han, H.; Huang, Y.; Yang, C.; Zheng, S.; Cai, T.; Bi, J.; Huang, X.; Liu, R.; Huang, L.; et al. METTL1/WDR4-mediated m7G tRNA modifications and m7G codon usage promote mRNA translation and lung cancer progression. Mol. Ther. J. Am. Soc. Gene Ther. 2021, 29, 3422–3435. [Google Scholar] [CrossRef] [PubMed]
  115. Pan, J.; Huang, Z.; Xu, Y. m5C RNA Methylation Regulators Predict Prognosis and Regulate the Immune Microenvironment in Lung Squamous Cell Carcinoma. Front. Oncol. 2021, 11, 657466. [Google Scholar] [CrossRef] [PubMed]
  116. Sun, L.; Liu, W.K.; Du, X.W.; Liu, X.L.; Li, G.; Yao, Y.; Han, T.; Li, W.Y.; Gu, J. Large-scale transcriptome analysis identified RNA methylation regulators as novel prognostic signatures for lung adenocarcinoma. Ann. Transl. Med. 2020, 8, 751. [Google Scholar] [CrossRef] [PubMed]
  117. Huang, W.; Qi, C.B.; Lv, S.W.; Xie, M.; Feng, Y.Q.; Huang, W.H.; Yuan, B.F. Determination of DNA and RNA Methylation in Circulating Tumor Cells by Mass Spectrometry. Anal. Chem. 2016, 88, 1378–1384. [Google Scholar] [CrossRef]
  118. Liu, S.Y.; Zhao, Z.Y.; Qiao, Z.; Li, S.M.; Zhang, W.N. LncRNA PCAT1 Interacts with DKC1 to Regulate Proliferation, Invasion and Apoptosis in NSCLC Cells via the VEGF/AKT/Bcl2/Caspase9 Pathway. Cell Transplant. 2021, 30, 963689720986071. [Google Scholar] [CrossRef]
  119. Jana, S.; Hsieh, A.C.; Gupta, R. Reciprocal amplification of caspase-3 activity by nuclear export of a putative human RNA-modifying protein, PUS10 during TRAIL-induced apoptosis. Cell Death Dis. 2017, 8, e3093. [Google Scholar] [CrossRef] [Green Version]
  120. Amin, E.M.; Liu, Y.; Deng, S.; Tan, K.S.; Chudgar, N.; Mayo, M.W.; Sanchez-Vega, F.; Adusumilli, P.S.; Schultz, N.; Jones, D.R. The RNA-editing enzyme ADAR promotes lung adenocarcinoma migration and invasion by stabilizing FAK. Sci. Signal. 2017, 10, eaah3941. [Google Scholar] [CrossRef]
  121. Maemura, K.; Watanabe, K.; Ando, T.; Hiyama, N.; Sakatani, T.; Amano, Y.; Kage, H.; Nakajima, J.; Yatomi, Y.; Nagase, T.; et al. Altered editing level of microRNAs is a potential biomarker in lung adenocarcinoma. Cancer Sci. 2018, 109, 3326–3335. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  122. Clancy, H.A.; Sun, H.; Passantino, L.; Kluz, T.; Munoz, A.; Zavadil, J.; Costa, M. Gene expression changes in human lung cells exposed to arsenic, chromium, nickel or vanadium indicate the first steps in cancer. Met. Integr. Biometal Sci. 2012, 4, 784–793. [Google Scholar] [CrossRef] [Green Version]
  123. Henry, E.C.; Welle, S.L.; Gasiewicz, T.A. TCDD and a putative endogenous AhR ligand, ITE, elicit the same immediate changes in gene expression in mouse lung fibroblasts. Toxicol. Sci. Off. J. Soc. Toxicol. 2010, 114, 90–100. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  124. Poulsen, S.S.; Saber, A.T.; Williams, A.; Andersen, O.; Kobler, C.; Atluri, R.; Pozzebon, M.E.; Mucelli, S.P.; Simion, M.; Rickerby, D.; et al. MWCNTs of different physicochemical properties cause similar inflammatory responses, but differences in transcriptional and histological markers of fibrosis in mouse lungs. Toxicol. Appl. Pharmacol. 2015, 284, 16–32. [Google Scholar] [CrossRef]
  125. Huang, X.; Lv, D.; Yang, X.; Li, M.; Zhang, H. m6A RNA methylation regulators could contribute to the occurrence of chronic obstructive pulmonary disease. J. Cell. Mol. Med. 2020, 24, 12706–12715. [Google Scholar] [CrossRef] [PubMed]
  126. Guo, X.; Lin, Y.; Lin, Y.; Zhong, Y.; Yu, H.; Huang, Y.; Yang, J.; Cai, Y.; Liu, F.; Li, Y.; et al. PM2.5 induces pulmonary microvascular injury in COPD via METTL16-mediated m6A modification. Environ. Pollut. 2022, 303, 119115. [Google Scholar] [CrossRef] [PubMed]
  127. Han, X.; Liu, H.; Zhang, Z.; Yang, W.; Wu, C.; Liu, X.; Zhang, F.; Sun, B.; Zhao, Y.; Jiang, G.; et al. Epitranscriptomic 5-Methylcytosine Profile in PM2.5-induced Mouse Pulmonary Fibrosis. Genom. Proteom. Bioinform. 2020, 18, 41–51. [Google Scholar] [CrossRef]
  128. Li, S.X.; Yan, W.; Liu, J.P.; Zhao, Y.J.; Chen, L. Long noncoding RNA SNHG4 remits lipopolysaccharide-engendered inflammatory lung damage by inhibiting METTL3—Mediated m6A level of STAT2 mRNA. Mol. Immunol. 2021, 139, 10–22. [Google Scholar] [CrossRef]
  129. Zhang, J.X.; Huang, P.J.; Wang, D.P.; Yang, W.Y.; Lu, J.; Zhu, Y.; Meng, X.X.; Wu, X.; Lin, Q.H.; Lv, H.; et al. m6A modification regulates lung fibroblast-to-myofibroblast transition through modulating KCNH6 mRNA translation. Mol. Ther. J. Am. Soc. Gene Ther. 2021, 29, 3436–3448. [Google Scholar] [CrossRef]
  130. Deng, M.S.; Chen, K.J.; Zhang, D.D.; Li, G.H.; Weng, C.M.; Wang, J.M. m6A RNA Methylation Regulators Contribute to Predict and as a Therapy Target of Pulmonary Fibrosis. Evid. Based Complement. Altern. Med. eCAM 2022, 2022, 2425065. [Google Scholar] [CrossRef]
  131. Sun, W.; Li, Y.; Ma, D.; Liu, Y.; Xu, Q.; Cheng, D.; Li, G.; Ni, C. ALKBH5 promotes lung fibroblast activation and silica-induced pulmonary fibrosis through miR-320a-3p and FOXM1. Cell. Mol. Biol. Lett. 2022, 27, 26. [Google Scholar] [CrossRef] [PubMed]
  132. Sun, D.; Cai, X.; Shen, F.; Fan, L.; Yang, H.; Zheng, S.; Zhou, L.; Chen, K.; Wang, Z. Transcriptome-Wide m6A Methylome and m6A-Modified Gene Analysis in Asthma. Front. Cell Dev. Biol. 2022, 10, 799459. [Google Scholar] [CrossRef] [PubMed]
  133. Huang, T.; He, W.Y. Construction and Validation of a Novel Prognostic Signature of Idiopathic Pulmonary Fibrosis by Identifying Subtypes Based on Genes Related to 7-Methylguanosine Modification. Front. Genet. 2022, 13, 890530. [Google Scholar] [CrossRef] [PubMed]
  134. Xu, Z.; Peng, B.; Cai, Y.; Wu, G.; Huang, J.; Gao, M.; Guo, G.; Zeng, S.; Gong, Z.; Yan, Y. N6-methyladenosine RNA modification in cancer therapeutic resistance: Current status and perspectives. Biochem. Pharmacol. 2020, 182, 114258. [Google Scholar] [CrossRef] [PubMed]
  135. Choe, J.; Lin, S.; Zhang, W.; Liu, Q.; Wang, L.; Ramirez-Moya, J.; Du, P.; Kim, W.; Tang, S.; Sliz, P.; et al. mRNA circularization by METTL3-eIF3h enhances translation and promotes oncogenesis. Nature 2018, 561, 556–560. [Google Scholar] [CrossRef] [Green Version]
  136. Du, M.; Zhang, Y.; Mao, Y.; Mou, J.; Zhao, J.; Xue, Q.; Wang, D.; Huang, J.; Gao, S.; Gao, Y. MiR-33a suppresses proliferation of NSCLC cells via targeting METTL3 mRNA. Biochem. Biophys. Res. Commun. 2017, 482, 582–589. [Google Scholar] [CrossRef]
  137. Yan, F.; Al-Kali, A.; Zhang, Z.; Liu, J.; Pang, J.; Zhao, N.; He, C.; Litzow, M.R.; Liu, S. A dynamic N6-methyladenosine methylome regulates intrinsic and acquired resistance to tyrosine kinase inhibitors. Cell Res. 2018, 28, 1062–1076. [Google Scholar] [CrossRef] [Green Version]
  138. Huang, Y.; Su, R.; Sheng, Y.; Dong, L.; Dong, Z.; Xu, H.; Ni, T.; Zhang, Z.S.; Zhang, T.; Li, C.; et al. Small-Molecule Targeting of Oncogenic FTO Demethylase in Acute Myeloid Leukemia. Cancer Cell 2019, 35, 677–691 e610. [Google Scholar] [CrossRef] [Green Version]
  139. Chao, Y.; Shang, J.; Ji, W. ALKBH5-m6A-FOXM1 signaling axis promotes proliferation and invasion of lung adenocarcinoma cells under intermittent hypoxia. Biochem. Biophys. Res. Commun. 2020, 521, 499–506. [Google Scholar] [CrossRef]
  140. Ma, L.; Chen, T.; Zhang, X.; Miao, Y.; Tian, X.; Yu, K.; Xu, X.; Niu, Y.; Guo, S.; Zhang, C.; et al. The m6A reader YTHDC2 inhibits lung adenocarcinoma tumorigenesis by suppressing SLC7A11-dependent antioxidant function. Redox Biol. 2021, 38, 101801. [Google Scholar] [CrossRef]
  141. Mu, X.; Zhao, Q.; Chen, W.; Zhao, Y.; Yan, Q.; Peng, R.; Zhu, J.; Yang, C.; Lan, K.; Gu, X.; et al. IL-37 Confers Anti-Tumor Activity by Regulation of m6A Methylation. Front. Oncol. 2020, 10, 526866. [Google Scholar] [CrossRef] [PubMed]
  142. Xiao, P.; Liu, Y.K.; Han, W.; Hu, Y.; Zhang, B.Y.; Liu, W.L. Exosomal Delivery of FTO Confers Gefitinib Resistance to Recipient Cells through ABCC10 Regulation in an m6A-dependent Manner. Mol. Cancer Res. MCR 2021, 19, 726–738. [Google Scholar] [CrossRef] [PubMed]
  143. Liu, S.; Li, Q.; Chen, K.; Zhang, Q.; Li, G.; Zhuo, L.; Zhai, B.; Sui, X.; Hu, X.; Xie, T. The emerging molecular mechanism of m6A modulators in tumorigenesis and cancer progression. Biomed. Pharmacother. 2020, 127, 110098. [Google Scholar] [CrossRef] [PubMed]
  144. Dong, S.; Wu, Y.; Liu, Y.; Weng, H.; Huang, H. N6-methyladenosine Steers RNA Metabolism and Regulation in Cancer. Cancer Commun. 2021, 41, 538–559. [Google Scholar] [CrossRef]
  145. Han, D.; Liu, J.; Chen, C.; Dong, L.; Liu, Y.; Chang, R.; Huang, X.; Liu, Y.; Wang, J.; Dougherty, U.; et al. Anti-tumour immunity controlled through mRNA m6A methylation and YTHDF1 in dendritic cells. Nature 2019, 566, 270–274. [Google Scholar] [CrossRef]
  146. Delaunay, S.; Pascual, G.; Feng, B.; Klann, K.; Behm, M.; Hotz-Wagenblatt, A.; Richter, K.; Zaoui, K.; Herpel, E.; Munch, C.; et al. Mitochondrial RNA modifications shape metabolic plasticity in metastasis. Nature 2022, 607, 593–603. [Google Scholar] [CrossRef]
  147. Zhang, Y.; Jiang, J.; Ma, J.; Wei, Z.; Wang, Y.; Song, B.; Meng, J.; Jia, G.; de Magalhaes, J.P.; Rigden, D.J.; et al. DirectRMDB: A database of post-transcriptional RNA modifications unveiled from direct RNA sequencing technology. Nucleic Acids Res. 2022, 1, gkac1061. [Google Scholar] [CrossRef]
Genes 13 02381 g001 550
Figure 1. The most common types of RNA modifications. Common RNA modifications include N6 methylation of adenosine (m6A), N1 methylation of adenosine (m1A), N7-methylguanosine (m7G), 5-methylcytosine (m5C), 2′O-methylation (2′-O-Me), pseudouridine (Ψ), and adenosine to inosine RNA editing (A-to-I editing), and regulated by methyltransferase (writers), demethylases (erasers), and some specific proteins (readers).
Figure 1. The most common types of RNA modifications. Common RNA modifications include N6 methylation of adenosine (m6A), N1 methylation of adenosine (m1A), N7-methylguanosine (m7G), 5-methylcytosine (m5C), 2′O-methylation (2′-O-Me), pseudouridine (Ψ), and adenosine to inosine RNA editing (A-to-I editing), and regulated by methyltransferase (writers), demethylases (erasers), and some specific proteins (readers).
Genes 13 02381 g001
Genes 13 02381 g003 550
Figure 3. The mechanisms and pathways of RNA modifications in chronic lung diseases. RNA modifications promote the occurrence and development of chronic lung diseases such as COPD, pneumonia, asthma, and pulmonary fibrosis. Among these modifications, m6A have been the most studied in chronic lung diseases. The mRNA expressions of m6A related IGF2BP3, FTO, METTL3 and YTHDC2 promote the progression of COPD. The m6A methyltransferase METTL16 regulates the level of sulfate and participates in microvascular injury induced by PM2.5. In addition, increased m5C modification is also involved in the process of PM2.5 induced COPD by inhibiting lung metabolic activity. LncRNA SNHG4 promotes LPS-induced pneumonia by inhibiting METTL3-mediated STAT2 mRNA expression. The enhancement of FMT promotes pulmonary fibrosis. METTL3 increases the FMT process. The m6A modification also is involved in FMT process by regulating KCNH6 expression through YTHDF1. METTL1 level in IPF patients is positive associated with poor prognosis. ALKBH5 promotes silicon-induced pulmonary fibrosis through FOXM1. The m6A-related YTHDF3 causes severe asthma by affecting eosinophils.
Figure 3. The mechanisms and pathways of RNA modifications in chronic lung diseases. RNA modifications promote the occurrence and development of chronic lung diseases such as COPD, pneumonia, asthma, and pulmonary fibrosis. Among these modifications, m6A have been the most studied in chronic lung diseases. The mRNA expressions of m6A related IGF2BP3, FTO, METTL3 and YTHDC2 promote the progression of COPD. The m6A methyltransferase METTL16 regulates the level of sulfate and participates in microvascular injury induced by PM2.5. In addition, increased m5C modification is also involved in the process of PM2.5 induced COPD by inhibiting lung metabolic activity. LncRNA SNHG4 promotes LPS-induced pneumonia by inhibiting METTL3-mediated STAT2 mRNA expression. The enhancement of FMT promotes pulmonary fibrosis. METTL3 increases the FMT process. The m6A modification also is involved in FMT process by regulating KCNH6 expression through YTHDF1. METTL1 level in IPF patients is positive associated with poor prognosis. ALKBH5 promotes silicon-induced pulmonary fibrosis through FOXM1. The m6A-related YTHDF3 causes severe asthma by affecting eosinophils.
Genes 13 02381 g003
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wang, X.; Guo, Z.; Yan, F. RNA Epigenetics in Chronic Lung Diseases. Genes 2022, 13, 2381. https://doi.org/10.3390/genes13122381

AMA Style

Wang X, Guo Z, Yan F. RNA Epigenetics in Chronic Lung Diseases. Genes. 2022; 13(12):2381. https://doi.org/10.3390/genes13122381

Chicago/Turabian Style

Wang, Xiaorui, Zhihou Guo, and Furong Yan. 2022. "RNA Epigenetics in Chronic Lung Diseases" Genes 13, no. 12: 2381. https://doi.org/10.3390/genes13122381

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

Article Metrics

Back to TopTop