Yi Sun1
Kerong Yang- 1Department of Breast Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- 2Department of Orthopedics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- 3The First Clinical School of Medicine, Zhengzhou University, Zhengzhou, Henan, China
- 4Department of the Plastic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China
Background: The epitranscriptome, particularly N6-methyladenosine (m6A), represents a dynamic layer of post-transcriptional regulation fundamentally implicated in cancer. However, the clinical translation of this knowledge is hampered by profound context-dependency, where the same m6A regulator can exert opposing roles in different tumors. To overcome this barrier, we propose a novel, clinically actionable taxonomic framework that classifies tumors based on their dominant dysregulated m6A component.
Methods: We synthesized current evidence through systematic reviews of primary research and high-impact papers from PubMed and Google Scholar, focusing on the mechanistic role of m6A modifications in cancer biology, therapy resistance, and therapeutic targeting. This synthesis was used to integrate pan-cancer molecular data including regulator expression, genetic dependency scores, and modification landscapes to define and characterize m6A-driven molecular subtypes.
Results: We classify tumors into Writer-Dominant (METTL3/14-high, Eraser-High (FTO/ALKBH5-high), Reader-Amplified (IGF2BP/YTHDF-high), and Immune-Modulatory subtypes, each with distinct oncogenic programs, therapy resistance mechanisms, and, crucially, actionable therapeutic vulnerabilities. We provide explicit, evidence-based molecular and functional inclusion criteria for each subtype and acknowledge that tumors can exhibit hybrid features, which directly inform rational combination strategies. Furthermore, we detail a diagnostic-therapeutic roadmap that integrates liquid biopsy-based m6A biomarker detection with subtype-specific treatment assignment.
Conclusion: Targeting the m6A epitranscriptome represents a paradigm shift in oncology; our framework provides the essential strategic approach needed to overcome context-dependency, offering a logical structure for tumor classification, vulnerability prediction, and the translation of epitranscriptomic insights into patient benefit through personalized, biomarker-guided combination therapies.
1 Introduction
For decades, the existence of chemically modified nucleosides in RNA has been known, but a deep appreciation of their extensive and sophisticated regulatory roles in cellular processes has only emerged in recent years (1). It is now clear that these post-transcriptional modifications impart a layer of functional diversity to the four standard ribonucleotides, analogous to the side chains of amino acids in proteins, thereby empowering RNA to form intricate structures and engage in specific molecular interactions. This extensive collection of chemical alterations, collectively termed the epitranscriptome, can directly influence RNA architecture-enhancing rigidity or flexibility-and critically modulate its interactions with proteins, thereby profoundly shaping complex regulatory networks and cellular metabolism (2).
Spurred by revolutionary technological advancements, especially in liquid chromatography/mass spectrometry (LC/MS)-based methodologies, the field has seen the discovery of novel RNA modifications and the definitive elucidation of the physiological functions of many known nucleosides (3–6). A truly pivotal discovery was the identification of reversible RNA methylation, which established the epitranscriptome as a highly dynamic regulatory system, parallel to the epigenome. A prime illustration is N6-methyladenosine (m6A), which plays a non-redundant and critical role in gene expression regulation by influencing transcript stability, splicing, translation efficiency, and cap-independent translation (7). The fundamental biological importance of this machinery is further highlighted by the direct association between mutations in human genes encoding RNA-modifying enzymes and a wide spectrum of diseases, including cancer, cardiovascular disorders, and neurological conditions (8).
This review will first synthesize the current understanding of the coordinated “writer-eraser-reader” machinery and detail the mechanisms through which its dysregulation propels oncogenic processes and therapy resistance. However, a critical barrier remains: the context-dependent functions of m6A regulators often lead to contradictory findings, creating a significant obstacle for developing unified therapeutic strategies. To bridge this gap between mechanistic insight and clinical application, the central thrust of this review is to introduce and elaborate a novel m6A-based taxonomic framework. This framework is grounded in the distinct, non-redundant functions of each component class (writers, erasers, readers) and their collective impact on the tumor immune microenvironment. It moves beyond a gene-centric view to define tumors by their dominant dysregulated m6A component, classifying them into clinically actionable subtypes with explicit molecular criteria. We will demonstrate how this taxonomy-comprising Writer-Dominant, Eraser-High, Reader-Amplified, and Immune-Modulatory subtypes provides a logical structure for understanding oncogenic mechanisms, predicting therapeutic vulnerabilities, and guiding rational drug combinations. Importantly, we will address the potential for tumors to exhibit features of multiple subtypes, providing a nuanced approach to classification and combination therapy. Finally, we will detail a diagnostic-therapeutic roadmap that integrates liquid biopsy-based biomarker development with this subtype-driven approach to therapy. By proposing and validating this integrative framework, this review aims to provide a coherent strategy for leveraging the epitranscriptome to achieve personalized cancer medicine.
2 Literature search strategy
To ensure a comprehensive and current overview of the field, the literature for this review was identified through a systematic search of the PubMed and Google Scholar databases, covering the period up to October 2025. The search strategy employed a combination of the following key terms and phrases: “N6-methyladenosine” OR “m6A” OR “epitranscriptome” in conjunction with “cancer” OR “oncogenesis” OR “tumorigenesis” OR “therapeutic resistance” OR “chemotherapy” OR “immunotherapy” OR “targeted therapy” OR “METTL3” OR “FTO” OR “ALKBH5” OR “YTHDF” OR “IGF2BP”.
The initial search results were screened by title and abstract for relevance. Primary research articles and high-impact reviews that elucidated the mechanistic role of m6A modifications in cancer biology, therapy resistance, and therapeutic targeting were selected for full-text review. The reference lists of key publications were also examined to identify additional pertinent studies. This strategy was designed to synthesize a timely and authoritative perspective on the dynamic role of the m6A epitranscriptome in cancer.
3 The m6A epitranscriptomic machinery: writers, erasers, and readers
N6-methyladenosine (m6A) is the most prevalent internal chemical modification in eukaryotic (messenger RNA) mRNA and long non-coding RNA (lncRNA), found across a diverse range of species from viruses and bacteria to plants and mammals (4, 5, 9–11). This dynamic and reversible modification is intricately involved in nearly every aspect of RNA metabolism, including pre-mRNA processing, nuclear export, translation efficiency, transcript stability, and miRNA biogenesis, thereby regulating critical biological processes such as development, the cell cycle, and stress responses (7). The installation, interpretation, and removal of m6A are governed by three specialized classes of proteins: ‘writers’ (methyltransferases), ‘erasers’ (demethylases), and ‘readers’ (m6A-binding proteins), which work in concert to fine-tune gene expression in response to cellular needs (Figure 1) (12–14).
Figure 1. The m6A epitranscriptomic machinery: writers, erasers, and readers. The N6-methyladenosine (m6A) modification is dynamically regulated by a conserved set of proteins. The methylation (“writing”) is catalyzed by a multi-component methyltransferase complex, whose catalytic core is the METTL3-METTL14 heterodimer. This complex is guided and regulated by auxiliary proteins including WTAP, VIRMA, RBM15/15B, ZC3H13, and others, which determine its substrate specificity, localization, and stability. Demethylation (“erasure”) is performed by the Fe (II)/α-ketoglutarate-dependent dioxygenases FTO and ALKBH5, which oxidatively remove the methyl mark to reverse its function. The biological consequences of m6A are executed by “reader” proteins that specifically recognize the modified adenosine. These readers, which include members of the YTH domain family (YTHDF1-3, YTHDC1-2), IGF2BPs, and heterogeneous nuclear ribonucleoproteins (HNRNPs), dictate the fate of the target RNA by regulating its splicing, stability, translation, and subcellular localization.
The core writer machinery in humans is a multi-component methyltransferase complex. Its catalytic engine is the stable heterodimer formed by METTL3 and METTL14, both class I methyltransferases (15–17). This heterodimeric complex was identified as the central functional unit, where METTL3 and METTL14 form a stable 1:1 complex that is essential for cellular m6A deposition (18). While METTL14 alone possesses methyltransferase activity, its combination with METTL3 results in a dramatic, synergistic enhancement of catalytic function, underscoring their partnership as the core catalytic engine. Furthermore, the regulatory subunit Wilms’ tumor 1-associating protein (WTAP), which itself lacks catalytic activity, is a vital component that interacts with the METTL3-METTL14 heterodimer. WTAP is crucial for recruiting the complex to nuclear speckles and, critically, it significantly enhances the m6A methylation activity of the complex within cells (19–21). Structural studies reveal that the METTL3-METTL14 complex forms an asymmetric heterodimer where METTL3 contains the functional active site for S-adenosylmethionine (SAM)-dependent methyl transfer, while METTL14 serves primarily as a crucial structural scaffold that enhances METTL3’s catalytic activity and binds RNA (22). he complex is further regulated by several auxiliary subunits: RNA-binding motif protein 15 (RBM15) binds to METTL3 and WTAP and promotes mRNA nucleation; VIRMA (also known as KIAA1429) recruits the core complex to preferentially catalyze methylation in 3’UTRs and near stop codons (23); Hakai (CBLL1) is an E3 ubiquitin ligase that helps maintain complex stability (24); and ZC3H13 acts as a scaffold, connecting RBM15, WTAP, and VIRMA and regulating their nuclear localization (25, 26). Beyond this core complex, other methyltransferases perform specific functions: METTL16 regulates SAM homeostasis by methylating MAT2A mRNA and U6 small nuclear RNA (snRNA) and is implicated in DNA damage repair (27–29), while METTL5 and ZCCHC4 are responsible for methylating 18S and 28S rRNA, respectively (30, 31).
The dynamic nature of the m6A modification is enabled by eraser enzymes that oxidatively remove the methyl group. The two primary m6A demethylases, FTO and ALKBH5, are Fe (II)- and α-ketoglutarate-dependent dioxygenases from the ALKB family (32). Both enzymes possess shallow substrate-binding grooves that favor binding to single-stranded RNA (33). Cellular studies confirm their physiological role: FTO localizes to nuclear speckles and its knockdown increases cellular m6A levels, while its overexpression decreases them. Its activity is influenced by RNA sequence and tertiary structure and is chaperoned by the RNA-binding protein SFPQ, which recruits FTO to specific CUGUG sequences for proximal demethylation (34, 35). Similarly, ALKBH5 catalyzes m6A demethylation, and its knockdown also increases m6A levels. It colocalizes with nuclear speckles and is crucial for proper mRNA export and metabolism, with its biological significance highlighted by the fact that Alkbh5 deficiency in mice causes male infertility due to defective spermatogenesis. Another ALKB family member, ALKBH3, also exhibits m6A demethylation activity (36).
The functional consequences of m6A methylation are executed by reader proteins that specifically recognize the mark. The most well-characterized readers are the YTH domain family proteins. Cytosolic YTHDF1 promotes translation, YTHDF2 accelerates mRNA decay, and YTHDF3 plays a cooperative role with both-a topic of ongoing investigation regarding the precise redundancy versus specialization of these proteins (37, 38). Nuclear readers YTHDC1 and YTHDC2 regulate mRNA splicing, export, and translation. Beyond the YTH family, other proteins serve as readers. The Heterogeneous Nuclear Ribonucleoprotein (HNRNP) family includes HNRNPA2B1, which binds m6A-modified pri-miRNAs to recruit DGCR8 and promote miRNA processing (39). HNRNPC and HNRNPG function through an “m6A switch” mechanism, where m6A modification alters RNA structure to modulate their binding, thereby influencing RNA processing and metabolism (40). Recent evidence also implicates HNRNPR in m6A-mediated tumor glycolysis. The Insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs; including IGF2BP1/2/3) recognize m6A marks to enhance mRNA stability and translation, often by recruiting co-factors like HuR (41). Additional readers include NF-κB activating protein (NKAP), which promotes mRNA splicing and maturation (42), and eukaryotic initiation factor 3 (eIF3), which binds m6A in the 5’UTR to facilitate cap-independent translation initiation (43). This intricate and diverse network of readers ensures that the m6A modification is translated into precise functional outcomes, regulating RNA fate at multiple levels.
4 Mechanisms of epitranscriptome-driven oncogenesis
4.1 Regulation of key oncogenes and tumor suppressors
The epitranscriptome exerts precise control over the life cycle of mRNAs encoding critical oncoproteins and tumor suppressors, thereby functioning as a master switch for malignant transformation. This control is not isolated but is part of a vast, interconnected regulatory network where writers, erasers, and readers coordinate to dictate tumor cell fate. As summarized in Figure 2, this intricate network demonstrates how the m6A machinery regulates a diverse array of oncogenic pathways-from the enhancement of MYC and BCL2 expression to the silencing of p53 and the activation of pro-metastatic signals like Smad3 and ARHGEF2-across a spectrum of cancer types. A prime example is the regulation of the MYC oncogene. In Acute Myeloid Leukemia the m6A writer METTL3 is recruited to the promoters of specific genes, leading to m6A methylation within the coding regions of their transcripts (44). This modification is critical for the efficient translation of key transcripts. For instance, METTL3-mediated m6A methylation of SP1 and SP2 mRNA does not affect their abundance but is essential for their translation (45, 46). The subsequent SP1/SP2 proteins then drive the expression of the MYC oncogene, creating a powerful feed-forward loop that sustains leukemogenesis (44). This simultaneous epitranscriptome-driven upregulation of oncogenes and downregulation of tumor suppressors creates a powerful driver of malignant transformation.
Figure 2. The oncogenic m6A regulatory network across cancer types. This figure summarizes the complex interactions between the core m6A machinery (Writers: METTL3, METTL14, METTL16, WTAP, KIAA1429; Eraser: FTO; Readers: YTHDF1/2/3, YTHDC1) and their key downstream targets. Arrows denote promoting effects, while blunt lines denote inhibitory effects. The network highlights how epitranscriptomic dysregulation drives fundamental cancer hallmarks-including uncontrolled proliferation, metastasis, and therapy resistance-in a variety of cancers (Acute Myeloid Leukemia, Breast Cancer, Glioblastoma).
Beyond METTL3, the m6A writer METTL16 also plays a critical role in regulating MYC. In Hepatocellular Carcinoma (HCC), METTL16 is frequently upregulated and promotes tumor progression. It achieves this by installing m6A modifications on the long non-coding RNA RAB11B-AS1, which leads to the transcript’s destabilization and downregulation. The loss of this lncRNA creates a permissive environment for the expression of MYC, thereby fueling HCC growth and proliferation (47). This establishes METTL16 as a key upstream regulator of MYC in liver cancer. Conversely, the m6A eraser FTO plays an oncogenic role in specific AML subtypes by demethylating and destabilizing mRNAs of tumor suppressors like ASB2 and RARA (45). A summary of key m6A-regulated oncogenes and tumor suppressors across various cancer types is provided in Tables 1 and 2. This simultaneous epitranscriptome-driven upregulation of oncogenes and downregulation of tumor suppressors creates a powerful driver of malignant transformation.
Table 1. Pro-tumorigenic roles of m6A regulators via oncogene activation.
Table 2. Pro-tumorigenic roles of m6A regulators via tumor suppressor silencing.
Conversely, the m6A machinery can also function to silence tumor suppressor genes, either through the erasure of stabilizing m6A marks or the writing of marks that promote the decay of tumor suppressor transcripts, thereby removing critical barriers to tumor progression.
4.2 m6A-mediated reprogramming of cancer cell metabolism
Cancer cells rewire their metabolism to support rapid growth, a process masterfully regulated by m6A RNA modifications. This epitranscriptomic reprogramming directly targets the core machinery of metabolic pathways, enhancing the stability or translation of key transcripts to fuel the Warburg effect and provide essential biosynthetic building blocks (27).
The Warburg effect describes the phenomenon where cancer cells preferentially utilize glycolysis for energy production, even in the presence of oxygen (69). Glycolysis decomposes glucose into pyruvate, a process involving numerous enzymes including hexokinase (HK), phosphofructokinase-1 (PFK), and pyruvate kinase (PK) (70, 71). While yielding less ATP than oxidative phosphorylation (OXPHOS) per glucose molecule, glycolysis operates at a much faster rate and generates intermediate metabolites crucial for synthesizing lipids, proteins, and nucleic acids, thereby supporting rapid proliferation (72). A key feature of this metabolic shift is the conversion of pyruvate to lactate by lactate dehydrogenase (73), which acidifies the tumor microenvironment and promotes immune escape by inhibiting the function of T and NK cells (74).
m6A methylation serves as a central regulator of this oncogenic metabolic switch. Transcripts encoding critical glycolytic enzymes, such as those for HK, PFK, and LDHA, are frequently modified by m6A, which enhances their translation efficiency and stability. For instance, the m6A reader YTHDF1 can bind to and promote the translation of glycolytic enzyme mRNAs, while IGF2BPs stabilize these transcripts to amplify their expression. This coordinated action significantly increases the flux through the glycolytic pathway. Furthermore, m6A modifications regulate transcripts involved in glutaminolysis and lipid synthesis, ensuring a steady supply of nitrogen and lipid precursors for membrane biogenesis. This epitranscriptomic control allows cancer cells to meet the heightened energetic and anabolic demands of uncontrolled proliferation, sustains a tumor-promoting microenvironment, and contributes to the clinical phenotypes observed in metabolic imaging (Supplementary Table S1) (24, 26).
4.3 Sustaining proliferative signaling and evading growth suppressors
The m6A machinery is integral to sustaining proliferative signaling, a dependency that can define specific molecular subtypes. A prime example is found in Acute Myeloid Leukemia, which often represents a prototypical “Writer-Dominant” subtype. CRISPR-Cas9 screens reveal that METTL3 is essential for the survival and proliferation of AML cells, while being dispensable for non-transformed cell. Its loss reverses the characteristic differentiation block of AML, promoting myeloid differentiation and apoptosis (75). This dependency is driven by METTL3’s catalytic activity, as a catalytically dead mutant cannot rescue the proliferation defect caused by its knockdown. METTL3 achieves this by regulating transcripts crucial for cell cycle progression and survival, such as BCL2 and MYC. Furthermore, METTL3 depletion in AML cells activates the PI3K/AKT pathway, as evidenced by increased phosphorylated AKT, which can contribute to differentiation signals (76). This establishes METTL3-high AML as a distinct entity with a unique therapeutic vulnerability to writer inhibition.
4.4 Promoting metastasis and invasion
The epitranscriptome is a key driver of cancer metastasis, particularly in solid tumors that can be classified as pro-invasive “Reader-Amplified” or “Eraser-High” subtypes. m6A modifications regulate the expression of transcripts critical for the epithelial-mesenchymal transition (77), such as the transcription factors SNAIL and ZEB1. By enhancing the stability or translation of these EMT master regulators, the m6A machinery promotes loss of cell adhesion and acquisition of migratory capabilities. Additionally, mRNAs encoding matrix metalloproteinases (MMPs) and integrins, which are essential for degrading the extracellular matrix and facilitating invasion, are common targets of m6A-mediated regulation, enabling cancer cells to invade surrounding tissues and vasculature (51, 52, 78). This epitranscriptomic reprogramming of the invasion machinery provides a functional signature for defining aggressive tumor subtypes.
4.5 Shaping the tumor immune microenvironment
Beyond cell-intrinsic effects, the epitranscriptome plays a crucial role in shaping the tumor immune microenvironment to enable immune evasion. The provided text highlights that FTO expression is upregulated by certain oncogenic proteins (MLL-fusion proteins, PML-RARA) in AML (45). While the direct immune checkpoint mechanisms are more prominent in solid tumors, the principle remains: m6A modifications precisely regulate the expression of immunomodulatory transcripts. For instance, the stability and translation of PD-L1 mRNA in tumor cells and PD-1 mRNA in T cells can be modulated by m6A, directly influencing the intensity of the immune response. Furthermore, cytokine signaling between tumor and immune cells is tuned by epitranscriptomic modifications, altering the inflammatory landscape of the tumor. This regulation also extends to innate immunity, influencing macrophage polarization and function within the tumor microenvironment (TME). This strategic manipulation allows cancer cells to create an immunosuppressive niche (79–81).
5 The role of the epitranscriptome in therapy resistance
The epitranscriptome is a critical mediator of therapeutic resistance across multiple cancer treatment modalities, including chemotherapy, targeted therapy, radiotherapy, and immunotherapy. Its dynamic and reversible nature provides cancer cells with a remarkable plasticity to rapidly adapt and survive under therapeutic pressure (82, 83). Rather than operating through a single mechanism, the m6A machinery orchestrates a coordinated multi-faceted response that drives resistance. As summarized in Figure 3, the m6A regulators promote tumor cell resistance through distinct yet interconnected molecular programs. These include enhancing DNA damage repair to overcome genotoxic stress, upregulating drug efflux pumps and pro-survival signaling to create a multidrug-resistant phenotype and sculpting an immunosuppressive tumor microenvironment to evade immune surveillance (84–86). Specifically, m6A regulators promote tumor cell resistance to radiation via stabilizing mRNA, regulating HR and inhibiting signaling pathways. In the context of immunotherapy, m6A regulators promote the stability of target gene mRNA and affect the recruitment of immune cells and the secretion of cytokines. Furthermore, various pathways of m6A regulators drive resistance to chemical drugs (Cisplatin, Gemcitabine) and kinase inhibitors (83, 87). The following sections will detail the molecular mechanisms underpinning each of these epitranscriptome-driven resistance pathways, highlighting how the dysregulation of writers, erasers, and readers enables cancer cell survival and ultimately leads to treatment failure and relapse.
Figure 3. The role of m6A methylation in therapy resistance. The m6A regulators promote tumor cell resistance to radiation via stabilizing mRNA, regulating homologous recombination (HR) and inhibiting signaling pathways. The m6A regulators promote the stability of target gene mRNA and affect the recruitment of immune cells and the secretion of cytokines. The figure also outlines various pathways of m6A regulators in resistance to chemical drugs (Cisplatin, Gemcitabine, Kinase inhibitor). The red arrows indicate “promote” and the blue arrows indicate “inhibit”.
5.1 Chemotherapy
Resistance to chemotherapeutic agents is frequently driven by epitranscriptomic modifications. A key mechanism involves the m6A-mediated upregulation of drug efflux pumps, such as MDR1/ABCB1, which enhance the expulsion of chemotherapeutic drugs from cancer cells, reducing their intracellular concentration and efficacy (88). Furthermore, the epitranscriptome enhances DNA damage repair capacity, a primary mechanism of resistance to DNA-damaging chemotherapies. METTL3-catalyzed m6A modification plays a direct role in the homologous recombination (HR) repair pathway. In response to DNA double-strand breaks (DSBs), ATM phosphorylates and activates METTL3, which localizes to damage sites (89). There, it methylates damage-associated RNAs, facilitating the recruitment of HR repair proteins like RAD51 and promoting efficient DSB repair, thereby allowing cancer cells to survive genotoxic effect (89).
5.2 Targeted therapy
Resistance to targeted agents is also orchestrated by RNA modifications. For example, in lung cancer, the m6A demethylase ALKBH5 promotes resistance to EGFR tyrosine kinase inhibitors by stabilizing FOXM1 transcripts, a transcription factor involved in cell proliferation and drug resistance (45). Conversely, in leukemia, the demethylase FTO confers resistance to PARP inhibitors. FTO is upregulated by oncogenic drivers like MLL-fusions and PML-RARA, and its activity leads to the demethylation and downregulation of tumor suppressor mRNAs such as ASB2 and RARA (45). This suppression of negative regulators of growth diminishes the efficacy of PARP inhibition, enabling cell survival.
5.3 Radiotherapy
The response to radiotherapy is significantly influenced by the epitranscriptome. As with chemotherapy, the METTL3-m6A axis is crucial for repairing radiation-induced DNA damage. METTL3-mediated methylation of RNAs at DSB sites is essential for the recruitment of DNA repair machinery. The reader protein YTHDC1 binds these m6A-modified RNAs, protecting them from degradation and promoting the formation of DNA-RNA hybrids that facilitate the accumulation of repair factors like DNA polymerase κ (Pol κ) at the damage site (90). This pathway is critical for efficient repair and cell survival post-irradiation. Consequently, inhibition of this mechanism sensitizes cancer cells to radiotherapy.
5.4 Immunotherapy
The epitranscriptome is a key determinant of the tumor immune microenvironment and the response to immune checkpoint blockade (ICB). Distinct m6A methylation patterns in tumors correlate with different immune phenotypes: immune-inflamed (“hot”), immune-excluded, and immune-desert (“cold”) (91–93). These patterns directly influence the infiltration of immunosuppressive cells. For instance, loss of the demethylase ALKBH5 in melanoma cells alters the m6A landscape, leading to reduced expression of MCT4/Slc16a3, a lactate transporter. This reduction decreases lactate secretion into the tumor microenvironment, which in turn impairs the expansion and differentiation of myeloid-derived suppressor cells (MDSCs) and Tregs (93, 94). The resulting shift in the immune contexture-characterized by fewer immunosuppressive cells and increased DC abundance-renders tumors more susceptible to anti-PD-1 therapy (79). Beyond erasers, reader proteins also play a direct role in mediating an immunosuppressive environment. In ovarian cancer, the m6A reader YTHDF1 is frequently amplified and overexpressed. YTHDF1 drives tumor progression by enhancing the translation of its target transcripts in an m6A-dependent manner. A key oncogenic target of YTHDF1 is the translation initiation factor EIF3C. By creating a feed-forward loop that augments the global translational capacity of cancer cells, the YTHDF1-EIF3C axis promotes a highly aggressive and immunosuppressive tumor phenotype, contributing to therapy resistance (95). This demonstrates that targeting m6A regulators can effectively modulate the TME and overcome resistance to immunotherapy.
6 Therapeutic targeting of the epitranscriptome
The dynamic and reversible nature of RNA modifications, particularly m6A, presents a promising and novel therapeutic avenue for cancer treatment. However, the context-dependent roles of its regulators necessitate a targeted, subtype-specific approach. The pharmacological toolkit for manipulating the epitranscriptome has expanded rapidly, as summarized in Supplementary Table S2, with numerous companies advancing candidates against writers, erasers, and readers. The critical next step is to align these therapeutic modalities with the m6A-based taxonomy we propose. The efficacy of a given inhibitor is not universal but is intrinsically linked to the dominant m6A subtype of the tumor.
Targeting the writers, erasers, and readers of the epitranscriptome with small molecules, RNA-based therapies, or rational combination strategies offers a powerful approach to disrupt the oncogenic pathways that are fundamentally dependent on this regulatory layer. The development of these agents signifies a paradigm shift in oncology, moving beyond traditional DNA and protein targets to directly modulate the RNA regulatory code itself. This section details the current and emerging arsenal of therapeutic strategies, from pioneering small-molecule inhibitors that validate the druggability of these proteins to next-generation modalities that promise greater potency and specificity.
6.1 First-generation catalytic inhibitors
The most advanced area of epitranscriptomic therapeutics is the development of small-molecule inhibitors that competitively target the catalytic sites of writers and erasers, thereby directly altering the cellular m6A landscape. For the m6A eraser FTO, significant progress has been made through a combination of drug repurposing and structure-based design. The anti-inflammatory drug meclofenamic acid (MA) was identified as an FTO inhibitor that increases global cellular m6A levels (79). This discovery paved the way for more potent and selective derivatives; notably, FB23 and its optimized counterpart, FB23-2, a benzohydroxamic acid derivative, exhibit dramatically improved inhibitory activity (IC50 = 0.06 μM for FB23) and enhanced cellular uptake (13). FB23–2 binds directly within FTO’s substrate-binding pocket, as confirmed by co-crystal structures, and demonstrates potent anti-leukemic effects both in vitro and in vivo. Its mechanism of action involves increasing m6A methylation on key tumor suppressor transcripts such as ASB2 and RARA, leading to their stabilization and the subsequent suppression of oncogenic drivers like MYC and CEBPA (45, 48). In a similar vein, the oncometabolite R-2-hydroxyglutarate (R-2HG), which accumulates in IDH-mutant cancers, has been shown to function as an FTO inhibitor, contributing significantly to its anti-tumor effects in AML models (48). Furthermore, natural compounds like Rhein have also been identified as FTO inhibitors, demonstrating potential in suppressing cancer progression (96).
Concurrently, parallel efforts have focused on inhibiting the m6A writer complex. A landmark achievement in this area was the development of STM2457, a highly potent (IC50 = 16.9 nM) and selective METTL3 inhibitor discovered through high-throughput screening and subsequent optimization (75, 97). STM2457 functions by competitively binding the S-adenosylmethionine (SAM) binding site of the METTL3-METTL14 heterodimer, the catalytic core of the writer complex. In models of acute myeloid leukemia, treatment with STM2457 phenocopies the genetic ablation of METTL3, robustly impairing leukemia cell proliferation and clonogenic growth, while inducing differentiation and apoptosis. These anti-tumor effects are driven by a reduction in the protein levels of key METTL3 oncogenic targets, such as SP1 and BRD4, without adversely affecting normal hematopoiesis, highlighting a potential therapeutic window (98). The compelling pre-clinical data generated by these first-generation inhibitors, STM2457 and FB23-2, provide unequivocal proof-of-concept that the m6A epitranscriptomic machinery is druggable and represents a viable target for cancer therapy. The rapid expansion of this pharmacological toolkit is illustrated in Supplementary Table S3, which summarizes a wide array of additional small-molecule inhibitors and activators targeting writers, erasers, and readers. These compounds, ranging from repurposed drugs like Entacapone to naturally derived molecules like Quercetin and specialized research tools like the YTHDF2 inhibitor DF-A7, have been instrumental in dissecting the complex biological functions of m6A modifiers in various cancer models. While STM2457 and FB23–2 represent the most advanced and specific candidates, the diverse agents highlight the intense research efforts and the potential for discovering new chemical scaffolds for clinical development.
6.2 Next-generation therapeutic modalities
While catalytic inhibitors have successfully validated the druggability of the m6A machinery, the field is rapidly advancing towards more sophisticated and potentially more powerful therapeutic modalities. These next-generation approaches aim to overcome limitations of traditional occupancy-based inhibitors, such as the need for sustained high target occupancy and vulnerability to resistance mutations, while also expanding the scope of targetable proteins within the epitranscriptome.
One of the most promising emerging modalities is the use of Proteolysis Targeting Chimeras (PROTACs). These heterobifunctional molecules are designed to recruit an E3 ubiquitin ligase to a protein of interest, leading to its ubiquitination and subsequent degradation by the proteasome. A PROTAC designed to degrade a key m6A regulator, such as METTL3 or FTO, would offer several potential advantages over catalytic inhibition. Its event-driven mechanism of action is catalytic, meaning a single PROTAC molecule can facilitate the degradation of multiple target proteins, potentially leading to a more potent and sustained pharmacological effect (99). Furthermore, by removing the target protein entirely, a PROTAC could overcome resistance mechanisms related to protein overexpression or point mutations that reduce drug-binding affinity. Although m6A-targeted PROTACs are still in early stages of development, the broader PROTAC platform has been clinically validated for other oncogenic targets. As summarized in Table 3, numerous PROTACs are now in clinical trials, targeting proteins such as the androgen and estrogen receptors (AR, ER), and Bruton’s tyrosine kinase (BTK). The rapid progression of these agents underscores the feasibility of targeted protein degradation and paves the way for applying this powerful modality to the m6A epitranscriptomic machinery (100, 101).
Table 3. Selected PROTAC degraders in clinical development for oncology.
Another frontier is the direct targeting of reader proteins, which have historically been considered challenging due to their protein-RNA interaction interfaces. However, readers like the IGF2BP family are critical nodes in oncogenesis, stabilizing a network of potent oncogenic mRNAs, including MYC. Small molecules that specifically disrupt the interaction between a reader like IGF2BP1 and its target oncogenic transcripts could offer a highly precise therapeutic strategy. Such an approach would selectively downregulate key drivers of tumorigenesis without altering the global m6A landscape, potentially mitigating on-target toxicities associated with writer or eraser inhibition that affect thousands of transcripts (41, 90). Advances in screening and structural biology are making this challenging goal increasingly feasible.
Finally, RNA-based therapies continue to be a vital tool and potential therapeutic avenue. siRNA and shRNA-mediated knockdown of specific writers (METTL3, METTL14), erasers (FTO, ALKBH5), or readers (YTHDF1/2, IGF2BP1) has been extensively and successfully used in pre-clinical models to validate their oncogenic functions, inducing anti-tumor effects such as differentiation, apoptosis, and impaired self-renewal (13, 44, 45, 102). For instance, ALKBH5 knockdown in melanoma cells was shown to alter the tumor immune microenvironment and enhance the efficacy of anti-PD-1 therapy (79). The primary hurdle for this modality remains the development of efficient, safe, and tumor-specific systems for the in vivo delivery of these RNAi agents.
6.3 Rational combination therapy: a logic framework
The m6A epitranscriptome does not operate in isolation; it functions as a central signaling hub that cancer cells co-opt to develop resistance to a wide array of therapies. This biological understanding provides a powerful rationale for combining m6A-targeted agents with established standard-of-care treatments. Rather than applying combinations empirically, the choice of regimen should be guided by the specific resistance mechanism driven by the dysregulated m6A regulator in each cancer context, creating a logical and personalized framework for combination therapy.
The rationale for combining m6A-targeted agents with chemotherapy is strongly supported by mechanistic studies. For example, FTO inhibitors like FB23–2 and R-2HG can reverse resistance to PARP inhibitors and tyrosine kinase inhibitors in AML. They achieve this by preventing the FTO-mediated demethylation and destabilization of tumor suppressor transcripts such as ASB2 and RARA, thereby restoring the cellular checks and balances that the targeted therapies rely upon (53, 83). Conversely, METTL3 inhibitors can sensitize cancer cells to DNA-damaging chemotherapies. This is because METTL3-catalyzed m6A modification plays a direct role in the homologous recombination (HR) repair pathway; inhibiting METTL3 impairs the recruitment of repair proteins like RAD51 to DNA damage sites, compromising the cancer cell’s ability to survive genotoxic stress (89).
The combination with radiotherapy follows a similar logic, targeting the epitranscriptome’s role in DNA damage response. The METTL3-m6A-YTHDC1 axis has been identified as critical for repairing radiation-induced DNA double-strand breaks. Inhibiting this axis, particularly through METTL3 inhibition, sensitizes cancer cells to radiotherapy by impairing the rapid, RNA methylation-dependent recruitment of DNA repair factors, such as DNA polymerase κ, to the damage sites (49, 103).
Perhaps one of the most exciting applications is the combination of m6A-targeted agents with immunotherapy. The epitranscriptome is a master regulator of the tumor immune microenvironment and targeting it can convert “cold” tumors into “hot” ones. For instance, inhibiting the eraser ALKBH5 in melanoma cells reduces lactate secretion, which in turn impairs the expansion and function of immunosuppressive myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs), thereby enhancing the response to anti-PD-1 therapy (104). Similarly, depleting the reader YTHDF1 in dendritic cells enhances cross-presentation of tumor antigens to T cells and synergizes with PD-L1 blockade (58). Additionally, FTO inhibition has been shown to reduce the stability of key immunosuppressive checkpoint transcripts, including PD-1, CTLA-4, and LILRB4, in immune cells, potentially enhancing anti-tumor immunity and the efficacy of checkpoint blockade (105, 106).
In conclusion, the development of highly specific small-molecule inhibitors such as STM2457 and FB23–2 has provided the foundational tools to pharmacologically manipulate the epitranscriptome. The ongoing clinical evaluation of next-generation inhibitors like STC-15, an oral derivative of STM2457 (NCT05584111), represents a pivotal step in translating this novel therapeutic paradigm from the laboratory to the clinic. By leveraging a deep understanding of the mechanistic links between specific m6A regulators and distinct therapy resistance pathways, the future of cancer treatment will likely involve rational combinations that include epitranscriptome-targeting agents to overcome the formidable challenge of therapeutic resistance and improve patient outcomes.
7 Clinical translation: an m6a-based taxonomy and therapeutic roadmap
The immense promise of targeting the m6A epitranscriptome is tempered by the significant challenge of context-dependency, where the same regulator can exert opposing roles in different cancer types or stages. To bridge this gap between mechanistic understanding and clinical application, we propose a move from a descriptive model to a predictive, subtype-driven framework. By integrating pan-cancer analyses from gastric cancer (STAD), low-grade glioma (LGG), acute myeloid leukemia, and others, we can define distinct m6A-driven subtypes and create a diagnostic-therapeutic roadmap for personalized oncology (107, 108).
7.1 Decoding context-dependency: defining m6A subtypes
The seemingly paradoxical roles of m6A regulators across different cancers reflect distinct biological states rather than experimental noise. To reconcile these context-dependent functions and enable clinical translation, emerging pan-cancer evidence supports the classification of tumors based on their predominant dysregulated m6A component.
The feasibility and clinical utility of m6A-based tumor classification is substantiated by comprehensive pan-cancer studies. A landmark analysis by Li et al. systematically characterized the genetic and expression landscapes of 20 m6A regulators across 33 cancer types in The Cancer Genome Atlas (TCGA) (107). This study revealed that m6A regulators exhibit cancer-specific patterns of copy number variation (CNV) and differential expression, with clear prognostic associations. For instance, readers such as IGF2BP1/2/3 and YTHDF1/3 showed frequent CNV amplification and corresponding overexpression in multiple cancers, whereas writers like METTL14 and erasers like ALKBH5 often exhibited reduced expression. Critically, unsupervised clustering based solely on m6A regulator expression patterns successfully stratified patients into subgroups with distinct clinical outcomes. In kidney cancer, this approach identified two molecular subgroups-an m6A regulator-high (RM-high) group and an RM-low group with significantly different overall survival (log-rank p = 0.005) (107). This pan-cancer analysis provides fundamental proof-of-concept: coordinated dysregulation of the m6A machinery defines biologically coherent tumor subtypes with inherent prognostic value.
The prognostic power and biological coherence of these m6A-based subtypes are further validated by in-depth mechanistic studies in specific cancers, which align precisely with our proposed taxonomy. These studies demonstrate that dysregulation of specific regulator classes drives coherent oncogenic programs. For example, work in ovarian cancer provides a clear archetype for the Reader-Amplified Subtype. Liu et al. showed that the m6A reader YTHDF1 is frequently amplified and overexpressed in high-grade serous ovarian carcinoma, with its high expression correlating strongly with advanced FIGO stage and shorter overall and progression-free survival (109). Functionally, YTHDF1 acts as a potent oncogene, promoting tumor cell proliferation, migration, and invasion both in vitro and in vivo by enhancing the translation of key targets like the translation initiation factor EIF3C in an m6A-dependent manner. Similarly, the Eraser-High Subtype is exemplified by studies in glioblastoma, where Zhang et al. demonstrated that the demethylase ALKBH5 is essential for maintaining the tumorigenicity of glioblastoma stem-like cells (GSCs) by sustaining FOXM1 expression through transcript demethylation (63). This establishes a direct link between eraser dysregulation, stemness maintenance, and therapeutic resistance.
Building upon this converging evidence, we propose a molecular taxonomy that classifies tumors into four major m6A-driven subtypes based on their dominant dysregulated component. Each subtype is defined by specific molecular and functional criteria, supported by extensive evidence of component-specific dysregulation across cancer types, including regulation of both coding and non-coding RNAs (107).
The Writer-Dominant (METTL3/14-High) Subtype is characterized by overexpression of core methyltransferase components and elevated global m6A deposition. In AML, METTL3 is identified as a dependency gene essential for leukemia cell survival and proliferation, with its loss reversing differentiation blocks and promoting apoptosis (110). In HCC, METTL3 is significantly elevated and stabilizes oncogenic lncRNAs such as RMRP to activate the TGFBR1/Smad2/Smad3 pathway (111). METTL3 also modifies lncRNA ANRIL in pancreatic cancer to enhance gemcitabine resistance via enhanced DNA repair (112). METTL14 shows similar oncogenic roles, stabilizing lncRNA FAM225A in nasopharyngeal carcinoma to promote metastasis (113). Other writers include WTAP, which stabilizes lncRNA FOXD2-AS1 in osteosarcoma (114), and KIAA1429, which regulates circDLC1 in HCC (115). Assignment criteria for this subtype include: (1) METTL3/METTL14 mRNA or protein expression significantly higher in acute myeloid leukemia (AML) cells compared to normal hematopoietic stem and progenitor cells (HSPCs); (2) High METTL3 dependency score in CRISPR screens; (3) Enrichment of m6A modifications on oncogenic transcripts like MYC, BCL2, and SP1/2; and (4) Evidence of writer-mediated regulation of key ncRNAs such as lncRNA RMRP or circDLC1.
FTO is highly expressed in specific AML subtypes (MLL-rearranged, PML-RARA, FLT3-ITD, NPM1-mutant) and promotes leukemogenesis by destabilizing tumor suppressor mRNAs like ASB2 and RARA (44, 76). In glioblastoma, ALKBH5 is aberrantly upregulated in GSCs and its depletion inhibits self-renewal and tumorigenesis (63). In breast cancer, hypoxia-induced ALKBH5 upregulation enriches cancer stem cells through NANOG stabilization (116). Beyond mRNA targets, FTO removes m6A marks from lncRNAs including LINC00022 in esophageal squamous cell carcinoma (ESCC), preventing YTHDF2-mediated degradation and promoting proliferation (117). ALKBH5 is aberrantly upregulated in glioblastoma stem cells where it stabilizes lncRNA NEAT1 under hypoxic conditions to upregulate CXCL8/IL8 (118). In pancreatic cancer, ALKBH5 regulates lncRNA KCNK15-AS1 to influence invasion and metastasis (119). Assignment criteria include: (1) FTO or ALKBH5 expression in the top tertile of tumor cohorts; (2) Correlation with hypoxic signatures (for ALKBH5); and (3) Stabilization of known target transcripts (MYC/CEBPA for FTO; FOXM1/NANOG for ALKBH5).
The Reader-Amplified (IGF2BP-High/YTHDF1-High) Subtype features amplification or overexpression of reader proteins. IGF2BP1/2/3 are unfavorable prognostic factors in gastric cancer (STAD) and drive proliferation and glycolysis (120). YTHDF1 is frequently amplified in ovarian cancer and promotes an immunosuppressive phenotype via EIF3C translation (109). IGF2BP3 stabilizes oncogenic mRNAs like MYC through m6A recognition (13). IGF2BP1 stabilizes circMDK in HCC to promote proliferation and invasion (121). IGF2BP2 stabilizes lncRNA DANCR in prostate cancer (122). IGF2BP3 stabilizes lncRNA KCNMB2-AS1 in cervical cancer (123). YTHDF1 promotes translation of lncRNA-encoded micropeptides in ESCC (109, 124). YTHDF2 stabilizes lncRNA KCNQ1OT1 in laryngeal squamous cell carcinoma (125). YTHDC1 promotes circRNA biosynthesis and export in HCC (126). Assignment criteria include: (1) IGF2BP or YTHDF family gene amplification or protein overexpression (e.g., by IHC or RNA-seq); (2) Co-upregulation of validated target oncogenes (MYC, LIN28B, SOX2); (3) Association with poor prognosis in clinical cohorts; and (4) Evidence of reader-mediated stabilization or degradation of key ncRNAs such as circMDK or lncRNA DANCR.
The Immune-Modulatory Subtype is identified through clustering analyses that reveal distinct m6A-immune phenotypes. In STAD, an “immune-inflamed” m6A cluster (Cluster C) shows high CD8+ T cell and dendritic cell infiltration (127). In LGG, clusters with high M2 macrophage and neutrophil infiltration correlate with poor outcomes (128). Loss of ALKBH5 creates “hot” tumors in melanoma models (129). METTL14-mediated m6A modification of lncRNA MIR155HG in HCC regulates PD-L1 expression (130). ALKBH5 regulates lncRNA NEAT1 to influence CXCL8/IL8 expression in glioblastoma (118). Assignment criteria include: (1) Distinct m6A regulator expression pattern by unsupervised clustering; (2) Specific immune cell infiltration signature; (3) Enrichment of m6A modifications on immune checkpoint transcripts.
Regarding multi-subtype tumors and hybrid features, biological complexity dictates that tumors may not exclusively fit a single subtype but can exhibit molecular features of multiple m6A-driven categories. This is strongly supported by genomic and functional evidence of co-dysregulation across different classes of m6A regulators. For instance, pan-cancer analyses reveal that genetic alterations and expression changes in writers, erasers, and readers frequently co-occur, and their expression is highly correlated across cancer types, indicating intertwined regulatory networks (107). A prime functional example is found in Acute Myeloid Leukemia, where a tumor can simultaneously display characteristics of both Writer-Dominant and Reader-Amplified subtypes. The writer METTL3 is recruited to specific promoters (SP1/SP2) to install m6A marks that are critical for the efficient translation of these transcripts, which in turn drive MYC expression-a hallmark of the Writer-Dominant program (44). Concurrently, the reader IGF2BP2 (and other IGF2BPs) can recognize and stabilize m6A-modified MYC mRNA, amplifying its oncogenic output and exemplifying a Reader-Amplified mechanism (13, 48). Furthermore, the co-occurrence of high writer (METTL3) and high eraser activity has been documented in specific AML subtypes, such as those with MLL rearrangements or NPM1 mutations, where FTO-mediated demethylation of tumor suppressors like ASB2 and RARA operates alongside METTL3-driven oncogene translation (45). This functional overlap underscores that the m6A machinery operates as a coordinated network rather than in isolated silos. Therefore, for clinical subtyping, when a tumor meets molecular criteria for multiple categories, the dominant subtype is assigned based on the highest regulator expression level and functional dependency score. However, the identification of secondary hybrid features is critically important, as it provides a direct rationale for designing rational combination therapies that simultaneously target multiple dysregulated axes.
7.2 A diagnostic and decision-making roadmap
To translate the proposed m6A-based taxonomic framework into clinical practice, we propose a comprehensive diagnostic-therapeutic roadmap that integrates liquid biopsy-based biomarker detection with subtype-directed treatment strategies. This roadmap is structured as a continuous clinical workflow that begins with patient presentation and extends through longitudinal monitoring, with clear decision points informed by the molecular criteria established in Section 7.1. The process initiates with Patient Presentation and Liquid Biopsy Acquisition at the time of cancer diagnosis or disease progression, where a peripheral blood sample is collected for liquid biopsy analysis. This minimally invasive approach enables the isolation of circulating tumor biomarkers, including circulating tumor cells (CTCs), cell-free RNA (cfRNA), and exosomes. The choice of analyte is context-dependent: cfRNA offers direct epitranscriptomic profiling but presents technical challenges due to its lability and susceptibility to degradation by RNases; exosomal proteins provide more stable detection of m6A regulators such as METTL3 or YTHDF1 but offer indirect functional information regarding the actual m6A modification landscape (131–134). This initial step facilitates real-time molecular profiling without the need for repeated invasive tissue biopsies, aligning with the principles of dynamic cancer monitoring and personalized oncology.
The next phase, m6A Subtyping via Multi-Omics Profiling, involves comprehensive molecular analysis to assign the tumor to one of the four proposed subtypes. The sample undergoes targeted RNA sequencing (RNA-seq) to quantify expression levels of key m6A regulators-writers (METTL3, METTL14, WTAP), erasers (FTO, ALKBH5), and readers (IGF2BP1-3, YTHDF1-3). Complementarily, mass spectrometry (LC-MS/MS) or immunoaffinity-based methods (MeRIP-seq, m6A-qPCR) measure global m6A levels and specific modification patterns on oncogenic and immune-related transcripts such as MYC, PD-L1, and CXCL10 (135, 136). Subtype assignment follows a predefined decision algorithm based on evidence-based criteria: tumors with significant METTL3/METTL14 overexpression and elevated global m6A are classified as Writer-Dominant; those with high FTO or ALKBH5 expression and global hypomethylation as Eraser-High; tumors with reader amplification and corresponding oncogene stabilization as Reader-Amplified; and those with distinct m6A-immune gene signatures as Immune-Modulatory. For tumors meeting criteria for multiple subtypes-a possibility due to biological complexity-the primary subtype is assigned based on the highest regulator expression and functional dependency, while secondary characteristics are documented to inform potential combination therapy.
Following subtype classification, Assignment to Rational Combination Therapy directs patients to subtype-specific therapeutic regimens. Writer-Dominant tumors are candidates for METTL3 catalytic inhibitors such as STM2457 or its oral derivative STC-15, strategically combined with DNA-damaging chemotherapy or radiotherapy to exploit synthetic lethality given the writer’s role in homologous recombination repair (75, 89, 137). Eraser-High tumors receive FTO inhibitors (FB23-2) or ALKBH5 inhibitors combined with immune checkpoint blockade (e.g., anti-PD-1/PD-L1) to reverse immunosuppression and enhance T-cell activity, as demonstrated in melanoma and AML models (79, 104–106). Reader-Amplified tumors are directed toward emerging reader-targeted therapies, such as small molecules disrupting the IGF2BP-MYC interaction or YTHDF1 inhibitors, potentially combined with pathway-specific agents (57, 138). Immune-Modulatory tumors are treated with immunotherapy regimens selected based on their specific m6A-immune phenotype, with potential priming using epitranscriptomic modulators like ALKBH5 inhibitors to convert immunologically “cold” tumors to “hot” ones (139–141). For tumors with hybrid features-such as those with both Writer-Dominant and Reader-Amplified characteristics-combination strategies targeting both axes (METTL3 inhibitor plus IGF2BP inhibitor) are considered within clinical trial frameworks or off-label use were supported by safety data.
The final component, Longitudinal Monitoring via Dynamic m6A Biomarkers, implements serial liquid biopsies to assess treatment response and detect emerging resistance. During therapy, repeat blood samples track quantitative changes in m6A regulator expression, global and transcript-specific m6A levels, and subtype signature persistence or evolution. For example, a decline in METTL3 cfRNA or an increase in m6A on MYC mRNA may indicate effective METTL3 inhibition, while rising exosomal FTO levels could signal developing resistance to demethylase-targeted therapy (55, 131). This real-time molecular monitoring enables adaptive treatment adjustments, such as switching therapies or adding combination agents based on evolving molecular profiles. The non-invasive nature of liquid biopsy and the dynamic responsiveness of m6A modifications make this an ideal platform for implementing precision oncology in a clinically feasible manner, moving beyond static tissue-based diagnostics to a continuous, biomarker-guided treatment paradigm that can address tumor evolution and therapeutic resistance (142, 143).
8 Liquid biopsies for m6A-based diagnosis and monitoring: from cfRNA to exosomal proteins
The transition of m6A research from a mechanistic understanding to clinical application hinges on the development of robust, non-invasive diagnostic tools. Liquid biopsy, which analyzes biomarkers in body fluids like blood, represents a paradigm shift in oncology, enabling real-time monitoring of tumor dynamics, early detection, and assessment of therapeutic response without the need for invasive tissue sampling (132, 133). The epitranscriptome, with its dynamic and cancer-specific alterations, is poised to be a cornerstone of this new diagnostic frontier. This section explores the technical landscape, specific biomarker candidates, and the immense potential of integrating m6A analysis into liquid biopsy platforms for transforming cancer management.
8.1 Technical challenges: cfRNA vs. exosomal proteins
A central consideration in developing m6A-based liquid biopsies is the choice of analyte. Two primary sources are cell-free RNA (cfRNA) and exosomal proteins, each with distinct advantages and limitations.
Detecting m6A-modified cfRNA offers a direct window into the epitranscriptomic state of tumors. cfRNA, released into the bloodstream through apoptosis, necrosis, or active secretion (134, 135), can reflect the real-time transcriptional and post-transcriptional regulation within tumor cells. Studies on non-small cell lung cancer (NSCLC) and other malignancies have demonstrated that cfRNA sequencing (cfRNA-Seq) can distinguish cancer patients from healthy individuals by revealing disease-specific gene expression signatures, immune repertoire (TCR/BCR) signals, and even microbial-derived transcripts (136, 144). The primary advantage of this approach is the direct measurement of the modification itself. For instance, techniques like MeRIP-seq could, in principle, be adapted to profile m6A epitranscriptomes from circulating RNA, allowing for the detection of global m6A shifts or hypermethylation of specific oncogenic transcripts like MYC or *PD-L1* in patient plasma. However, the profound technical challenge is the inherent lability and low abundance of cfRNA. RNA is susceptible to degradation by ubiquitous RNases, leading to short fragment lengths and a low overall concentration in circulation. This makes the reliable detection of specific m6A-modified transcripts technically demanding and requires highly sensitive, specialized protocols to preserve RNA integrity and avoid artifacts.
In contrast, measuring m6A regulator proteins (e.g., METTL3, FTO, YTHDF1) packaged within exosomes presents a more stable alternative. Exosomes are lipid-bilayer vesicles actively secreted by cells that protect their cargo from degradation. They are abundant in blood and contain proteins, lipids, and nucleic acids reflective of their cell of origin. The key advantage here is stability; exosomal proteins are far less susceptible to degradation than naked cfRNA, making them more reliable analytes for clinical assays. Furthermore, the detection of these proteins, potentially via immunoassays or proximity extension assays, is often more technically straightforward and amenable to high-throughput clinical workflows than RNA modification mapping. For example, the overexpression of METTL3 or YTHDF1 in tumor tissues could be mirrored by their elevated levels in circulating exosomes, serving as a surrogate, stable biomarker for an “m6A-high” tumor subtype. The limitation of this approach is its indirect nature. Measuring protein levels does not directly report on the functional outcome-the m6A modification landscape-which can be influenced by complex regulatory dynamics. A tumor might overexpress METTL3 protein, but its catalytic activity could be contextually modulated. Therefore, while exosomal proteins offer a robust and practical detection method, they may not capture the full functional complexity of the epitranscriptome. The choice between these analytes may ultimately be context-dependent, with a combination of both providing the most comprehensive picture. For early detection and prognosis, stable exosomal proteins might be preferable, while for monitoring dynamic response to therapy, direct measurement of m6A on cfRNA could be more informative.
8.2 Promising biomarker candidates
Substantial research has identified specific components of the m6A machinery as promising biomarker candidates for various clinical applications, from early detection to monitoring therapeutic response.
For Early Detection: Global m6A Levels and Specific Regulator Profiles. Pan-cancer studies suggest that the global abundance of m6A modifications in tissue can be a distinguishing feature, with certain cancers exhibiting widespread hypomethylation (107). This global signature could potentially be detected in blood-based assays. For instance, mass spectrometry-based quantification of m6A nucleosides in circulating RNA could serve as a pan-cancer screening tool. More specifically, the detection of exosomal proteins or cfRNA transcripts for specific m6A regulators shows great promise. In glioblastoma, the detection of the FTO inhibitor FTO-04 in circulation could indicate the presence of FTO-driven tumors (145). Similarly, the upregulation of m6A-related genes in pancreatic cancer, such as METTL3 and IGF2BP2, could form the basis for an early detection signature, especially in high-risk populations.
For Prognosis and Subtyping: Reader and Writer Amplification. The amplification and overexpression of specific “reader” and “writer” proteins are strongly correlated with aggressive disease and poor prognosis, making them excellent prognostic biomarkers. The reader YTHDF1 is a prime example. Its frequent amplification and overexpression in ovarian cancer drives a highly aggressive and immunosuppressive phenotype (146). Detecting YTHDF1 protein in exosomes or its transcript in cfRNA could identify patients with particularly virulent disease, guiding more aggressive initial therapy. Similarly, in stomach adenocarcinoma (STAD), a high expression of IGF2BP1/2/3 in tumors are unfavorable prognostic factor, and an m6A-based signature (m6ASig) derived from these and other regulators can stratify patients into distinct risk groups. These m6A-based subtypes, such as the “Reader-Amplified” or “Writer-Dominant” classifications, have direct prognostic implications and can be translated into a liquid biopsy format by building multi-analyte panels that quantify the key regulators defining each subtype.
For Monitoring Therapeutic Response: Dynamic m6A Changes on Key Transcripts. Perhaps the most powerful application of m6A liquid biopsies is the real-time monitoring of treatment efficacy and the emergence of resistance. The dynamic and reversible nature of m6A makes it an ideal responsive biomarker. For example, the efficacy of a METTL3 inhibitor like STM2457 could be monitored by tracking the reduction in m6A methylation on known target transcripts, such as MYC or BRD4, in cfRNA post-treatment (98). Conversely, the development of resistance to anti-PD-1 immunotherapy has been linked to specific epitranscriptomic alterations. The demethylase ALKBH5 can promote resistance by stabilizing immunosuppressive transcripts. Therefore, a decrease in m6A levels on the PD-L1 transcript or an increase in ALKBH5 cfRNA could serve as an early liquid biomarker of immunotherapy failure, allowing for a timely switch to alternative treatments. This principle extends to chemotherapy; the upregulation of FTO in AML relapse samples contributes to chemoresistance, and its detection in plasma could signal impending relapse long before it is clinically apparent (55).
In conclusion, the integration of m6A analysis into liquid biopsy platforms is poised to revolutionize cancer diagnostics. By tackling the technical challenges of cfRNA analysis and leveraging the stability of exosomal proteins, clinically viable assays can be developed. These assays will utilize a growing arsenal of m6A-based biomarkers-from global levels to specific regulator proteins and modification sites on key transcripts-to enable early detection, refine prognostic stratification, and provide an unprecedented, dynamic view of treatment response, ultimately paving the way for truly personalized epitranscriptome-guided therapy.
9 Conclusion
The epitranscriptome has been established as a master regulatory layer governing cancer biology, from driving malignant transformation to mediating therapeutic failure. The development of specific inhibitors against writers and erasers provides compelling proof that this regulatory axis is druggable. However, as this review has argued, the true clinical potential of this paradigm shift lies in navigating its profound context-dependency. The m6A-based taxonomic framework proposed herein-classifying tumors into Writer-Dominant, Eraser-High, Reader-Amplified, and Immune-Modulatory subtypes provides a strategic blueprint for personalizing therapy. This model offers a coherent logic to reconcile contradictory findings and directly links tumor biology to specific therapeutic vulnerabilities. Coupled with the integration of m6A analysis into liquid biopsies, this framework promises to revolutionize diagnostics by enabling real-time, dynamic subtyping and monitoring of treatment response. While significant translational hurdles remain, a concerted effort to validate these subtypes and their associated biomarkers in clinical cohorts will be essential. The future of epitranscriptome-targeted therapy is not merely in inhibiting a single protein, but in leveraging this deep mechanistic understanding to reprogram the malignant identity of cancer cells through rational, biomarker-guided combinations tailored to the tumor’s dominant m6A state.
Author contributions
KY: Conceptualization, Formal analysis, Funding acquisition, Investigation, Supervision, Validation, Visualization, Writing – review & editing. YS: Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft. JW: Formal analysis, Validation, Visualization, Writing – review & editing. GC: Formal analysis, Investigation, Validation, Visualization, Writing – review & editing. HM: Formal analysis, Investigation, Validation, Visualization, Writing – review & editing. WL: Formal analysis, Investigation, Validation, Visualization, Writing – review & editing. HT: Formal analysis, Validation, Visualization, Writing – review & editing.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This work was supported by China Postdoctoral Science Foundation (2021M692924), and the Joint Construction Project of Medical Science and Technology Research Program of Henan Province (No. LHGJ20200304, No. LHGJ20210335).
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2026.1749911/full#supplementary-material
Abbreviations
4SU, 4-Thiouracil; AML, Acute Myeloid Leukemia; CAF, Cancer-Associated Fibroblast; cfDNA, Cell-free DNA; cfRNA, Cell-free RNA; CRPC, Castration-Resistant Prostate Cancer; CRC, Colorectal Cancer; ctDNA, Circulating Tumor DNA; DSB, Double-Strand Break; EMT, Epithelial-Mesenchymal Transition; HR, Homologous Recombination; ICB, Immune Checkpoint Blockade; LC/MS, Liquid Chromatography/Mass Spectrometry; LEC, Lymphatic Endothelial Cell; MCED, Multi-Cancer Early Detection; MDSC, Myeloid-Derived Suppressor Cell; miCLIP, m6A individual-nucleotide resolution Cross-Linking and Immuno-Precipitation; NSCLC, Non-Small Cell Lung Cancer; OXPHOS, Oxidative Phosphorylation; PAR-CLIP, Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation; SAM, S-Adenosylmethionine; SILAC, Stable Isotope Labeling by/with Amino acids in Cell culture; TIME, Tumor Immune Microenvironment; TME, Tumor Microenvironment; TNBC, Triple-Negative Breast Cancer.
References
1. Boccaletto P, Machnicka MA, Purta E, Piatkowski P, Baginski B, Wirecki TK, et al. MODOMICS: a database of RNA modification pathways. 2017 update. Nucleic Acids Res. (2018) 46:D303–d307.
2. Roundtree IA, Evans ME, Pan T, and He C. Dynamic RNA modifications in gene expression regulation. Cell. (2017) 169:1187–200.
3. Dubin DT and Taylor RH. The methylation state of poly A-containing messenger RNA from cultured hamster cells. Nucleic Acids Res. (1975) 2:1653–68. doi: 10.1093/nar/2.10.1653
4. Meyer KD, Saletore Y, Zumbo P, Elemento O, Mason CE, and Jaffrey SR. Comprehensive analysis of mRNA methylation reveals enrichment in 3’ UTRs and near stop codons. Cell. (2012) 149:1635–46.
5. Dominissini D, Moshitch-Moshkovitz S, Schwartz S, Salmon-Divon M, Ungar L, Osenberg S, et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature. (2012) 485:201–6.
7. Zaccara S, Ries RJ, and Jaffrey SR. Reading, writing and erasing mRNA methylation. Nat Rev Mol Cell Biol. (2019) 20:608–24. doi: 10.1038/s41580-019-0168-5
8. Frye M, Harada BT, Behm M, and He C. RNA modifications modulate gene expression during development. Science. (2018) 361:1346–9.
9. Deng X, Chen K, Luo GZ, Weng X, Ji Q, Zhou T, et al. Widespread occurrence of N6-methyladenosine in bacterial mRNA. Nucleic Acids Res. (2015) 43:6557–67. doi: 10.1093/nar/gkv596
10. Schwartz S, Agarwala SD, Mumbach MR, Jovanovic M, Mertins P, Shishkin A, et al. High-resolution mapping reveals a conserved, widespread, dynamic mRNA methylation program in yeast meiosis. Cell. (2013) 155:1409–21.
11. Luo GZ, MacQueen A, Zheng G, Duan H, Dore LC, Lu Z, et al. Unique features of the m6A methylome in Arabidopsis thaliana. Nat Commun. (2014) 5. doi: 10.1038/ncomms6630
12. Alarcón CR, Lee H, Goodarzi H, Halberg N, and Tavazoie SF. N6-methyladenosine marks primary microRNAs for processing. Nature. (2015) 519:482–5.
13. Huang H, Weng H, Sun W, Qin X, Shi H, Wu H, et al. Recognition of RNA N(6)-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat Cell Biol. (2018) 20:285–95. doi: 10.1038/s41556-018-0045-z
14. Yu D, Horton JR, Yang J, Hajian T, Vedadi M, Sagum CA, et al. Human MettL3-MettL14 RNA adenine methyltransferase complex is active on double-stranded DNA containing lesions. Nucleic Acids Res. (2021) 49:11629–42. doi: 10.1093/nar/gkab460
15. Woodcock CB, Yu D, Hajian T, Li J, Huang Y, Dai N, et al. Human MettL3-MettL14 complex is a sequence-specific DNA adenine methyltransferase active on single-strand and unpaired DNA in vitro. Cell Discov. (2019) 5. doi: 10.1038/s41421-019-0136-4
16. Wang X, Feng J, Xue Y, Guan Z, Zhang D, Liu Z, et al. Structural basis of N(6)-adenosine methylation by the METTL3-METTL14 complex. Nature. (2016) 534:575–8.
17. Du Y, Hou G, Zhang H, Dou J, He J, Guo Y, et al. SUMOylation of the m6A-RNA methyltransferase METTL3 modulates its function. Nucleic Acids Res. (2018) 46:5195–208. doi: 10.1093/nar/gky156
18. Linder B, Grozhik AV, Olarerin-George AO, Meydan C, Mason CE, and Jaffrey SR. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods. (2015) 12:767–72. doi: 10.1038/nmeth.3453
19. Zheng G, Dahl JA, Niu Y, Fedorcsak P, Huang CM, Li CJ, et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell. (2013) 49:18–29. doi: 10.1016/j.molcel.2012.10.015
20. Meyer KD and Jaffrey SR. Rethinking m(6)A readers, writers, and erasers. Annu Rev Cell Dev Biol. (2017) 33:319–42. doi: 10.1146/annurev-cellbio-100616-060758
21. Wang X, Lu Z, Gomez A, Hon GC, Yue Y, Han D, et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. (2014) 505:117–20.
22. Yoshida A, Oyoshi T, Suda A, Futaki S, and Imanishi M. Recognition of G-quadruplex RNA by a crucial RNA methyltransferase component, METTL14. Nucleic Acids Res. (2022) 50:449–57. doi: 10.1093/nar/gkab1211
23. Yue Y, Liu J, Cui X, Cao J, Luo G, Zhang Z, et al. VIRMA mediates preferential m(6)A mRNA methylation in 3’UTR and near stop codon and associates with alternative polyadenylation. Cell Discov. (2018) 4. doi: 10.1038/s41421-018-0019-0
24. Bawankar P, Lence T, Paolantoni C, Haussmann IU, Kazlauskiene M, Jacob D, et al. Hakai is required for stabilization of core components of the m(6)A mRNA methylation machinery. Nat Commun. (2021) 12:3778. doi: 10.1038/s41467-021-23892-5
25. Knuckles P, Lence T, Haussmann IU, Jacob D, Kreim N, Carl SH, et al. Zc3h13/Flacc is required for adenosine methylation by bridging the mRNA-binding factor Rbm15/Spenito to the m(6)A machinery component Wtap/Fl(2)d. Genes Dev. (2018) 32:415–29. doi: 10.1101/gad.309146.117
26. Wen J, Lv R, Ma H, Shen H, He C, Wang J, et al. Zc3h13 regulates nuclear RNA m(6)A methylation and mouse embryonic stem cell self-renewal. Mol Cell. (2018) 69:1028–1038.e1026. doi: 10.1016/j.molcel.2018.02.015
27. Pendleton KE, Chen B, Liu K, Hunter OV, Xie Y, and Tu BPConrad NK. The U6 snRNA m(6)A Methyltransferase METTL16 Regulates SAM Synthetase Intron Retention. Cell. (2017) 169:824–835.e814. doi: 10.1016/j.cell.2017.05.003
28. Ruszkowska A. METTL16, methyltransferase-like protein 16: current insights into structure and function. Int J Mol Sci. (2021) 22. doi: 10.3390/ijms22042176
29. Perez-Pepe M and Alarcón CR. An RNA link for METTL16 and DNA repair in PDAC. Nat Cancer. (2022) 3:1018–20. doi: 10.1038/s43018-022-00434-6
30. Pinto R, Vågbø CB, Jakobsson ME, Kim Y, Baltissen MP, O’Donohue MF, et al. The human methyltransferase ZCCHC4 catalyses N6-methyladenosine modification of 28S ribosomal RNA. Nucleic Acids Res. (2020) 48:830–46. doi: 10.1093/nar/gkz1147
31. van Tran N, Ernst FGM, Hawley BR, Zorbas C, Ulryck N, Hackert P, et al. The human 18S rRNA m6A methyltransferase METTL5 is stabilized by TRMT112. Nucleic Acids Res. (2019) 47:7719–33. doi: 10.1093/nar/gkz619
32. Wei J, Liu F, Lu Z, Fei Q, Ai Y, He PC, et al. Differential m(6)A, m(6)A(m), and m(1)A Demethylation Mediated by FTO in the Cell Nucleus and Cytoplasm. Mol Cell. (2018) 71:973–985.e975.
33. Xu B, Liu D, Wang Z, Tian R, and Zuo Y. Multi-substrate selectivity based on key loops and non-homologous domains: new insight into ALKBH family. Cell Mol Life Sci. (2021) 78:129–41. doi: 10.1007/s00018-020-03594-9
34. Song H, Wang Y, Wang R, Zhang X, Liu Y, Jia G, et al. SFPQ is an FTO-binding protein that facilitates the demethylation substrate preference. Cell Chem Biol. (2020) 27:283–291.e286. doi: 10.1016/j.chembiol.2020.01.002
35. Zhang X, Wei LH, Wang Y, Xiao Y, Liu J, Zhang W, et al. Structural insights into FTO’s catalytic mechanism for the demethylation of multiple RNA substrates. Proc Natl Acad Sci U S A. (2019) 116:2919–24. doi: 10.1073/pnas.1820574116
36. Jia G, Fu Y, Zhao X, Dai Q, Zheng G, Yang Y, et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat Chem Biol. (2011) 7:885–7. doi: 10.1038/nchembio.687
37. Zaccara S and Jaffrey SR. A Unified Model for the Function of YTHDF Proteins in Regulating m(6)A-Modified mRNA. Cell. (2020) 181:1582–1595.e1518. doi: 10.1016/j.cell.2020.05.012
38. Xia Z, Tang M, Ma J, Zhang H, Gimple RC, Prager BC, et al. Epitranscriptomic editing of the RNA N6-methyladenosine modification by dCasRx conjugated methyltransferase and demethylase. Nucleic Acids Res. (2021) 49:7361–74. doi: 10.1093/nar/gkab517
39. Alarcón CR, Goodarzi H, Lee H, Liu X, Tavazoie S, and Tavazoie SF. HNRNPA2B1 is a mediator of m(6)A-dependent nuclear RNA processing events. Cell. (2015) 162:1299–308.
40. Liu N, Zhou KI, Parisien M, Dai Q, Diatchenko L, and Pan T. N6-methyladenosine alters RNA structure to regulate binding of a low-complexity protein. Nucleic Acids Res. (2017) 45:6051–63. doi: 10.1093/nar/gkx141
41. Ramesh-Kumar D and Guil S. The IGF2BP family of RNA binding proteins links epitranscriptomics to cancer. Semin Cancer Biol. (2022) 86:18–31. doi: 10.1016/j.semcancer.2022.05.009
42. Sun S, Gao T, Pang B, Su X, Guo C, Zhang R, et al. RNA binding protein NKAP protects glioblastoma cells from ferroptosis by promoting SLC7A11 mRNA splicing in an m6A-dependent manner. Cell Death Disease. (2022) 13:73. doi: 10.1038/s41419-022-04524-2
43. Choe J, Lin S, Zhang W, Liu Q, Wang L, Ramirez-Moya J, et al. mRNA circularization by METTL3-eIF3h enhances translation and promotes oncogenesis. Nature. (2018) 561:556–60.
44. Barbieri I, Tzelepis K, Pandolfini L, Shi J, Millán-Zambrano G, Robson SC, et al. Promoter-bound METTL3 maintains myeloid leukaemia by m(6)A-dependent translation control. Nature. (2017) 552:126–31.
45. Li Z, Weng H, Su R, Weng X, Zuo Z, Li C, et al. FTO plays an oncogenic role in acute myeloid leukemia as a N(6)-methyladenosine RNA demethylase. Cancer Cell. (2017) 31:127–41. doi: 10.1016/j.ccell.2016.11.017
46. Vu LP, Pickering BF, Cheng Y, Zaccara S, Nguyen D, Minuesa G, et al. The N(6)-methyladenosine (m(6)A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat Med. (2017) 23:1369–76. doi: 10.1038/nm.4416
47. Bove G, Babaei M, Bueno-Costa A, Amin S, Simonelli N, Benedetti R, et al. METTL16-mediated inhibition of MXD4 promotes leukemia through activation of the MYC-MAX axis. Oncogene. (2025). doi: 10.1038/s41388-025-03563-1
48. Su R, Dong L, Li C, Nachtergaele S, Wunderlich M, Qing Y, et al. R-2HG exhibits anti-tumor activity by targeting FTO/m(6)A/MYC/CEBPA signaling. Cell. (2018) 172:90–105. doi: 10.1016/j.cell.2017.11.031
49. Xie GS and Richard HT. m(6)A mRNA modifications in glioblastoma: emerging prognostic biomarkers and therapeutic targets. Cancers (Basel). (2024) 16. doi: 10.3390/cancers16040727
50. Yang J, Fang J, Singh S, Wells B, Wu Q, Jin H, et al. The context-dependent epigenetic and organogenesis programs determine 3D vs. 2D cellular fitness of MYC-driven murine liver cancer cells. Res Sq. (2025). doi: 10.21203/rs.3.rs-4390765/v4
51. Yue B, Song C, Yang L, Cui R, Cheng X, and Zhang ZZhao G. METTL3-mediated N6-methyladenosine modification is critical for epithelial-mesenchymal transition and metastasis of gastric cancer. Mol Cancer. (2019) 18:142. doi: 10.1186/s12943-019-1065-4
52. Zhang C, Zhang M, Ge S, Huang W, Lin X, Gao J, et al. Reduced m6A modification predicts Malignant phenotypes and augmented Wnt/PI3K-Akt signaling in gastric cancer. Cancer Med. (2019) 8:4766–81. doi: 10.1002/cam4.2360
53. Zhu DH, Su KK, Ou-Yang XX, Zhang YH, Yu XP, Li ZH, et al. Mechanisms and clinical landscape of N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers. Mol Cell Biochem. (2024) 479:1553–70. doi: 10.1007/s11010-024-05040-x
54. Zeng C, Huang W, Li Y, and Weng H. Roles of METTL3 in cancer: mechanisms and therapeutic targeting. J Hematol Oncol. (2020) 13:117. doi: 10.1186/s13045-020-00951-w
55. Wang H, Peng H, Zhang Z, Abulimiti Y, Hu J, Zhou Y, et al. FTO-mediated m(6)A demethylation regulates IGFBP3 expression and AKT activation through IMP3-dependent P-body re-localisation in lung cancer. Clin Transl Med. (2025) 15:e70392. doi: 10.1002/ctm2.70392
56. Lin Z, Li J, Zhang J, Feng W, Lu J, Ma X, et al. Metabolic reprogramming driven by IGF2BP3 promotes acquired resistance to EGFR inhibitors in non–small cell lung cancer. Cancer Res. (2023) 83:2187–207. doi: 10.1158/0008-5472.CAN-22-3059
57. Duan M, Liu H, Xu S, Yang Z, Zhang F, Wang G, et al. IGF2BPs as novel m(6)A readers: Diverse roles in regulating cancer cell biological functions, hypoxia adaptation, metabolism, and immunosuppressive tumor microenvironment. Genes Dis. (2024) 11:890–920. doi: 10.1016/j.gendis.2023.06.017
58. Shi Y, Zhuang Y, Zhang J, Chen M, and Wu S. METTL14 inhibits hepatocellular carcinoma metastasis through regulating EGFR/PI3K/AKT signaling pathway in an m6A-dependent manner. Cancer Manag Res. (2020) 12:13173–84. doi: 10.2147/CMAR.S286275
59. Bao L, Yuan L, Li P, Bu Q, Guo A, Zhang H, et al. A FUS-LATS1/2 axis inhibits hepatocellular carcinoma progression via activating hippo pathway. Cell Physiol Biochem. (2018) 50:437–51. doi: 10.1159/000494155
60. Zheng J, Liang Y, Xu X, Zhou J, Jiang S, and Yu J. N6-methyladenosine binding protein YTHDF2 inhibits gastric cancer cell growth and predicts better prognosis in patients with gastric cancer. Trans Oncol. (2025) 56. doi: 10.1016/j.tranon.2025.102395
61. Yan J, Huang X, Zhang X, Chen Z, Ye C, Xiang W, et al. LncRNA LINC00470 promotes the degradation of PTEN mRNA to facilitate Malignant behavior in gastric cancer cells. Biochem Biophys Res Commun. (2020) 521:887–93. doi: 10.1016/j.bbrc.2019.11.016
62. Huang H, Weng H, and Chen J. m6A modification in coding and non-coding RNAs: roles and therapeutic implications in cancer. Cancer Cell. (2020) 37:270–88. doi: 10.1016/j.ccell.2020.02.004
63. Zhang S, Zhao BS, Zhou A, Lin K, Zheng S, Lu Z, et al. m(6)A demethylase ALKBH5 maintains tumorigenicity of glioblastoma stem-like cells by sustaining FOXM1 expression and cell proliferation program. Cancer Cell. (2017) 31:591–606.e596. doi: 10.1016/j.ccell.2017.02.013
64. Achour C, Bhattarai DP, Groza P, Román ÁC, and Aguilo F. METTL3 regulates breast cancer-associated alternative splicing switches. Oncogene. (2023) 42:911–25.
65. Guan Q, Lin H, Miao L, Guo H, Chen Y, Zhuo Z, et al. Functions, mechanisms, and therapeutic implications of METTL14 in human cancer. J Hematol Oncol. (2022) 15:13. doi: 10.1186/s13045-022-01231-5
66. Liu J, Eckert MA, Harada BT, Liu SM, Lu Z, Yu K, et al. m(6)A mRNA methylation regulates AKT activity to promote the proliferation and tumorigenicity of endometrial cancer. Nat Cell Biol. (2018) 20:1074–83. doi: 10.1038/s41556-018-0174-4
67. Han B, Yan S, Wei S, Xiang J, Liu K, Chen Z, et al. YTHDF1-mediated translation amplifies Wnt-driven intestinal stemness. EMBO Rep. (2020) 21:e49229.
68. Bai Y, Yang C, Wu R, Huang L, Song S, Li W, et al. YTHDF1 regulates tumorigenicity and cancer stem cell-like activity in human colorectal carcinoma. Front Oncol. (2019) 9. doi: 10.3389/fonc.2019.00332
69. Bononi G, Masoni S, Di Bussolo V, Tuccinardi T, Granchi C, and Minutolo F. Historical perspective of tumor glycolysis: A century with Otto Warburg. Semin Cancer Biol. (2022) 86:325–33. doi: 10.1016/j.semcancer.2022.07.003
70. Chandel NS. Glycolysis. Cold Spring Harb Perspect Biol. (2021) 13. doi: 10.1101/cshperspect.a040535
71. Houles T, Gravel SP, Lavoie G, Shin S, Savall M, Méant A, et al. RSK regulates PFK-2 activity to promote metabolic rewiring in melanoma. Cancer Res. (2018) 78:2191–204. doi: 10.1158/0008-5472.CAN-17-2215
72. Paul S, Ghosh S, and Kumar S. Tumor glycolysis, an essential sweet tooth of tumor cells. Semin Cancer Biol. (2022) 86:1216–30. doi: 10.1016/j.semcancer.2022.09.007
73. Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, et al. Detection of circulating tumor DNA in early- and late-stage human Malignancies. Sci Transl Med. (2014) 6:224ra224.
74. Xie M, Fu XG, and Jiang K. Notch1/TAZ axis promotes aerobic glycolysis and immune escape in lung cancer. Cell Death Dis. (2021) 12:832. doi: 10.1038/s41419-021-04124-6
75. Yankova E, Blackaby W, Albertella M, Rak J, De Braekeleer E, Tsagkogeorga G, et al. Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia. Nature. (2021) 593:597–601.
76. Cheng Y, Luo H, Izzo F, Pickering BF, Nguyen D, Myers R, et al. m(6)A RNA methylation maintains hematopoietic stem cell identity and symmetric commitment. Cell Rep. (2019) 28:1703–1716.e1706. doi: 10.1016/j.celrep.2019.07.032
77. Lavrichenko K, Engdal ES, Marvig RL, Jemt A, Vignes JM, Almusa H, et al. Recommendations for bioinformatics in clinical practice. Genome Med. (2025) 17:124. doi: 10.1186/s13073-025-01543-4
78. Zhang M, Song J, Yuan W, Zhang W, and Sun Z. Roles of RNA methylation on tumor immunity and clinical implications. Front Immunol. (2021) 12. doi: 10.3389/fimmu.2021.641507
79. Li N, Kang Y, Wang L, Huff S, Tang R, Hui H, et al. ALKBH5 regulates anti-PD-1 therapy response by modulating lactate and suppressive immune cell accumulation in tumor microenvironment. Proc Natl Acad Sci U S A. (2020) 117:20159–70. doi: 10.1073/pnas.1918986117
80. Han D, Liu J, Chen C, Dong L, Liu Y, Chang R, et al. Anti-tumour immunity controlled through mRNA m(6)A methylation and YTHDF1 in dendritic cells. Nature. (2019) 566:270–4.
81. Zhao Y, Li J, Lian Y, Zhou Q, Wu Y, and Kang J. METTL3-dependent N6-methyladenosine modification programs human neural progenitor cell proliferation. Int J Mol Sci. (2023) 24. doi: 10.3390/ijms242115535
82. Li N, Shi K, and Li W. TUSC7: A novel tumor suppressor long non-coding RNA in human cancers. J Cell Physiol. (2018) 233:6401–7. doi: 10.1002/jcp.26544
83. Yan F, Al-Kali A, Zhang Z, Liu J, Pang J, Zhao N, et al. A dynamic N(6)-methyladenosine methylome regulates intrinsic and acquired resistance to tyrosine kinase inhibitors. Cell Res. (2018) 28:1062–76. doi: 10.1038/s41422-018-0097-4
84. Pan S, Deng Y, Fu J, Zhang Y, Zhang Z, and Qin X. N6−methyladenosine upregulates miR−181d−5p in exosomes derived from cancer−associated fibroblasts to inhibit 5−FU sensitivity by targeting NCALD in colorectal cancer. Int J Oncol. (2022) 60. doi: 10.3892/ijo.2022.5304
85. Meng W, Xiao H, Mei P, Chen J, Wang Y, Zhao R, et al. Critical roles of METTL3 in translation regulation of cancer. Biomolecules. (2023) 13. doi: 10.3390/biom13020243
86. Ding N, You A, Tian W, Gu L, and Deng D. Chidamide increases the sensitivity of Non-small Cell Lung Cancer to Crizotinib by decreasing c-MET mRNA methylation. Int J Biol Sci. (2020) 16:2595–611. doi: 10.7150/ijbs.45886
87. Fisusi FAAkala EO. Drug combinations in breast cancer therapy. Pharm Nanotechnol. (2019) 7:3–23. doi: 10.2174/2211738507666190122111224
88. Lin S, Choe J, Du P, Triboulet R, and Gregory RI. The m(6)A methyltransferase METTL3 promotes translation in human cancer cells. Mol Cell. (2016) 62:335–45. doi: 10.1016/j.molcel.2016.03.021
89. Zhang C, Chen L, Peng D, Jiang A, He Y, Zeng Y, et al. METTL3 and N6-methyladenosine promote homologous recombination-mediated repair of DSBs by modulating DNA-RNA hybrid accumulation. Mol Cell. (2020) 79:425–442.e427. doi: 10.1016/j.molcel.2020.06.017
90. Xiang Y, Laurent B, Hsu CH, Nachtergaele S, Lu Z, Sheng W, et al. RNA m(6)A methylation regulates the ultraviolet-induced DNA damage response. Nature. (2017) 543:573–6.
92. Binnewies M, Roberts EW, Kersten K, Chan V, Fearon DF, Merad M, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med. (2018) 24:541–50. doi: 10.1038/s41591-018-0014-x
93. Veglia F, Perego M, and Gabrilovich D. Myeloid-derived suppressor cells coming of age. Nat Immunol. (2018) 19:108–19. doi: 10.1038/s41590-017-0022-x
94. Watson MJ, Vignali PDA, Mullett SJ, Overacre-Delgoffe AE, Peralta RM, Grebinoski S, et al. Metabolic support of tumour-infiltrating regulatory T cells by lactic acid. Nature. (2021) 591:645–51.
95. Zhuang H, Yu B, Tao D, Xu X, Xu Y, Wang J, et al. The role of m6A methylation in therapy resistance in cancer. Mol Cancer. (2023) 22:91. doi: 10.1186/s12943-023-01782-2
96. Bove G, Amin S, Babaei M, Benedetti R, Nebbioso A, Altucci L, et al. Interplay between m(6) A epitranscriptome and epigenome in cancer: current knowledge and therapeutic perspectives. Int J Cancer. (2023) 153:464–75. doi: 10.1002/ijc.34378
97. Fraser G, Sorlet C, Parmentier N, Brunel E, Hartiel A-F, Oukoloff K, et al. Abstract 6282: EP102: Pharmacological inhibition of METTL3 arrests tumor progression and prolongs survival in CDX and PDX models of AML. Cancer Res. (2023) 83:6282–2. doi: 10.1158/1538-7445.AM2023-6282
98. Guan AWong JJ. Targeting RNA modifications with pharmacological agents: New frontiers in cancer therapy. Cancer Med. (2024) 13:e6989.
99. Li R, Liu M, Yang Z, Li J, Gao Y, and Tan R. Proteolysis-targeting chimeras (PROTACs) in cancer therapy: present and future. Molecules. (2022) 27. doi: 10.3390/molecules27248828
100. Kelm JM, Pandey DS, Malin E, Kansou H, Arora S, Kumar R, et al. PROTAC’ing oncoproteins: targeted protein degradation for cancer therapy. Mol Cancer. (2023) 22:62. doi: 10.1186/s12943-022-01707-5
101. Du W, Huang Y, Chen X, Deng Y, Sun Y, Yang H, et al. Discovery of a PROTAC degrader for METTL3-METTL14 complex. Cell Chem Biol. (2024) 31:177–183.e117. doi: 10.1016/j.chembiol.2023.12.009
102. Huang F, Wang Y, Zhang X, Gao W, Li J, Yang Y, et al. m6A/IGF2BP3-driven serine biosynthesis fuels AML stemness and metabolic vulnerability. Nat Commun. (2025) 16:4214. doi: 10.1038/s41467-025-58966-1
103. Wei Y, Wu Y, Zhang C, Yuan M, Sun Y, Li M, et al. The m(6)A modification in cancer: roles, implications, and its potential in therapy. Mol Biomed. (2025) 6:67. doi: 10.1186/s43556-025-00314-2
104. Liu Z, Chen J, Ren Y, Liu S, Ba Y, Zuo A, et al. Multi-stage mechanisms of tumor metastasis and therapeutic strategies. Signal Transduction Targeted Ther. (2024) 9:270. doi: 10.1038/s41392-024-01955-5
105. Su R, Dong L, Li Y, Gao M, Han L, Wunderlich M, et al. Targeting FTO suppresses cancer stem cell maintenance and immune evasion. Cancer Cell. (2020) 38:79–96.e11. doi: 10.1016/j.ccell.2020.04.017
106. Dai W, Qiao X, Fang Y, Guo R, Bai P, Liu S, et al. Epigenetics-targeted drugs: current paradigms and future challenges. Signal Transduction Targeted Ther. (2024) 9:332. doi: 10.1038/s41392-024-02039-0
107. Li Y, Xiao J, Bai J, Tian Y, Qu Y, Chen X, et al. Molecular characterization and clinical relevance of m(6)A regulators across 33 cancer types. Mol Cancer. (2019) 18:137. doi: 10.1186/s12943-019-1066-3
108. Liu B, Tao W, Zhou X, Xu LD, Luo Y, Yang X, et al. Multi−omics analysis identifies different molecular subtypes with unique outcomes in early-stage poorly differentiated lung adenocarcinoma. Mol Cancer. (2025) 24:129. doi: 10.1186/s12943-025-02333-7
109. Liu T, Wei Q, Jin J, Luo Q, Liu Y, Yang Y, et al. The m6A reader YTHDF1 promotes ovarian cancer progression via augmenting EIF3C translation. Nucleic Acids Res. (2020) 48:3816–31. doi: 10.1093/nar/gkaa048
110. Fang J, Singh S, Wells B, Wu Q, Jin H, Janke LJ, et al. The context-dependent epigenetic and organogenesis programs determine 3D vs. 2D cellular fitness of MYC-driven murine liver cancer cells. Elife. (2025) 14.
111. Yin H, Chen L, Piao S, Wang Y, Li Z, Lin Y, et al. M6A RNA methylation-mediated RMRP stability renders proliferation and progression of non-small cell lung cancer through regulating TGFBR1/SMAD2/SMAD3 pathway. Cell Death Differ. (2023) 30:605–17. doi: 10.1038/s41418-021-00888-8
112. Wang ZW, Pan JJ, Hu JF, Zhang JQ, Huang L, Huang Y, et al. SRSF3-mediated regulation of N6-methyladenosine modification-related lncRNA ANRIL splicing promotes resistance of pancreatic cancer to gemcitabine. Cell Rep. (2022) 39:110813. doi: 10.1016/j.celrep.2022.110813
113. Zheng ZQ, Li ZX, Zhou GQ, Lin L, Zhang LL, Lv JW, et al. Long Noncoding RNA FAM225A Promotes Nasopharyngeal Carcinoma Tumorigenesis and Metastasis by Acting as ceRNA to Sponge miR-590-3p/miR-1275 and Upregulate ITGB3. Cancer Res. (2019) 79:4612–26. doi: 10.1158/0008-5472.CAN-19-0799
114. Ren Z, Hu Y, Sun J, Kang Y, Li G, and Zhao H. N(6)-methyladenosine methyltransferase WTAP-stabilized FOXD2-AS1 promotes the osteosarcoma progression through m(6)A/FOXM1 axis. Bioengineered. (2022) 13:7963–73.
115. Liu H, Lan T, Li H, Xu L, Chen X, Liao H, et al. Circular RNA circDLC1 inhibits MMP1-mediated liver cancer progression via interaction with HuR. Theranostics. (2021) 11:1396–411.
116. Zhang C, Samanta D, Lu H, Bullen JW, Zhang H, Chen I, et al. Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA. Proc Natl Acad Sci U S A. (2016) 113:E2047–2056.
117. Cui Y, Zhang C, Ma S, Li Z, Wang W, Li Y, et al. RNA m6A demethylase FTO-mediated epigenetic up-regulation of LINC00022 promotes tumorigenesis in esophageal squamous cell carcinoma. J Exp Clin Cancer Res. (2021) 40:294. doi: 10.1186/s13046-021-02096-1
118. Dong F, Qin X, Wang B, Li Q, Hu J, Cheng X, et al. ALKBH5 facilitates hypoxia-induced paraspeckle assembly and IL8 secretion to generate an immunosuppressive tumor microenvironment. Cancer Res. (2021) 81:5876–88. doi: 10.1158/0008-5472.CAN-21-1456
119. He Y, Hu H, Wang Y, Yuan H, Lu Z, Wu P, et al. ALKBH5 inhibits pancreatic cancer motility by decreasing long non-coding RNA KCNK15-AS1 methylation. Cell Physiol Biochem. (2018) 48:838–46. doi: 10.1159/000491915
120. Liu K, Liu Y, Zhang S, Li Z, Qu W, Li P, et al. Epigenetic regulation of RNA methylations in gastric cancer. Oncol Rev. (2025) 19. doi: 10.3389/or.2025.1601511
121. Du A, Li S, Zhou Y, Disoma C, Liao Y, Zhang Y, et al. M6A-mediated upregulation of circMDK promotes tumorigenesis and acts as a nanotherapeutic target in hepatocellular carcinoma. Mol Cancer. (2022) 21:109. doi: 10.1186/s12943-022-01575-z
122. Hu X, Peng W-X, Zhou H, Jiang J, Zhou X, Huang D, et al. IGF2BP2 regulates DANCR by serving as an N6-methyladenosine reader. Cell Death Differentiation. (2020) 27:1782–94. doi: 10.1038/s41418-019-0461-z
123. Zhang Y, Wang D, Wu D, and Zhang DSun M. Long noncoding RNA KCNMB2-AS1 stabilized by N(6)-methyladenosine modification promotes cervical cancer growth through acting as a competing endogenous RNA. Cell Transplant. (2020) 29:963689720964382. doi: 10.1177/0963689720964382
124. Wu S, Zhang L, Deng J, Guo B, Li F, Wang Y, et al. A novel micropeptide encoded by Y-linked LINC00278 links cigarette smoking and AR signaling in male esophageal squamous cell carcinoma. Cancer Res. (2020) 80:2790–803. doi: 10.1158/0008-5472.CAN-19-3440
125. Li Y, Yan B, Wang X, Li Q, Kan X, Wang J, et al. ALKBH5-mediated m6A modification of lncRNA KCNQ1OT1 triggers the development of LSCC via upregulation of HOXA9. J Cell Mol Med. (2022) 26:385–98. doi: 10.1111/jcmm.17091
126. Dattilo D, Di Timoteo G, Setti A, Giuliani A, Peruzzi G, Beltran Nebot M, et al. The m(6)A reader YTHDC1 and the RNA helicase DDX5 control the production of rhabdomyosarcoma-enriched circRNAs. Nat Commun. (2023) 14:1898. doi: 10.1038/s41467-023-37578-7
127. Shi G, Li Y, Gao H, Wei Y, and Wang Y. Development a m(6)A regulators characterized by the immune cell infiltration in stomach adenocarcinoma for predicting the prognosis and immunotherapy response. Aging (Albany NY). (2023) 15:1944–63. doi: 10.18632/aging.204574
128. Li J, Guo Q, and Xing R. Construction and validation of an immune infiltration-related risk model for predicting prognosis and immunotherapy response in low grade glioma. BMC Cancer. (2023) 23:727. doi: 10.1186/s12885-023-11222-5
129. Yang J, Xu J, Wang W, Zhang B, Yu X, and Shi S. Epigenetic regulation in the tumor microenvironment: molecular mechanisms and therapeutic targets. Signal Transduction Targeted Ther. (2023) 8:210. doi: 10.1038/s41392-023-01480-x
130. Peng L, Pan B, Zhang X, Wang Z, Qiu J, Wang X, et al. Lipopolysaccharide facilitates immune escape of hepatocellular carcinoma cells via m6A modification of lncRNA MIR155HG to upregulate PD-L1 expression. Cell Biol Toxicol. (2022) 38:1159–73. doi: 10.1007/s10565-022-09718-0
131. Wang J, Liu Y, Sun W, Zhang Q, Gu T, and Li G. Plasma exosomes as novel biomarker for the early diagnosis of gastric cancer. Cancer biomark. (2018) 21:805–12. doi: 10.3233/CBM-170738
132. Heitzer E, Haque IS, Roberts CES, and Speicher MR. Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat Rev Genet. (2019) 20:71–88. doi: 10.1038/s41576-018-0071-5
133. Barbieri I and Kouzarides T. Role of RNA modifications in cancer. Nat Rev Cancer. (2020) 20:303–22. doi: 10.1038/s41568-020-0253-2
134. Liu Y, Liang Y, Li Q, and Li Q. Comprehensive analysis of circulating cell-free RNAs in blood for diagnosing non-small cell lung cancer. Comput Struct Biotechnol J. (2023) 21:4238–51. doi: 10.1016/j.csbj.2023.08.029
135. Larson MH, Pan W, Kim HJ, Mauntz RE, Stuart SM, Pimentel M, et al. A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection. Nat Commun. (2021) 12:2357. doi: 10.1038/s41467-021-22444-1
136. Adalsteinsson VA, Ha G, Freeman SS, Choudhury AD, Stover DG, Parsons HA, et al. Scalable whole-exome sequencing of cell-free DNA reveals high concordance with metastatic tumors. Nat Commun. (2017) 8:1324. doi: 10.1038/s41467-017-00965-y
137. Lin C, Li T, Wang Y, Lai S, Huang Y, Guo Z, et al. METTL3 enhances pancreatic ductal adenocarcinoma progression and gemcitabine resistance through modifying DDX23 mRNA N6 adenosine methylation. Cell Death Disease. (2023) 14:221. doi: 10.1038/s41419-023-05715-1
138. Li S, Wu Q, and Liu JZhong Y. Identification of two m6A readers YTHDF1 and IGF2BP2 as immune biomarkers in head and neck squamous cell carcinoma. Front Genet. (2022) 13:903634. doi: 10.3389/fgene.2022.903634
139. Su Y, Wang F, Lei Z, Li J, Ma M, Yan Y, et al. An integrated multi-omics analysis identifying immune subtypes of pancreatic cancer. Int J Mol Sci. (2023) 25. doi: 10.3390/ijms25010142
140. Shen S, Zhang R, Jiang Y, Li Y, Lin L, Liu Z, et al. Comprehensive analyses of m6A regulators and interactive coding and non-coding RNAs across 32 cancer types. Mol Cancer. (2021) 20:67. doi: 10.1186/s12943-021-01362-2
141. Zhao X and Guan S. Epitranscriptomic control of cancer immunity and therapy resistance. Front Immunol. (2025) 16:1706557. doi: 10.3389/fimmu.2025.1706557
142. Adhit KK, Wanjari A, and Menon SKS. Liquid biopsy: an evolving paradigm for non-invasive disease diagnosis and monitoring in medicine. Cureus. (2023) 15:e50176. doi: 10.7759/cureus.50176
143. Ma L, Guo H, Zhao Y, Liu Z, Wang C, Bu J, et al. Liquid biopsy in cancer: current status, challenges and future prospects. Signal Transduction Targeted Ther. (2024) 9:336. doi: 10.1038/s41392-024-02021-w
144. Yang T, Qin Y, Yan S, Guo S, Sun J, Huang J, et al. Comprehensive evaluation of methods for identifying tissues or cell types of origin of the plasma cell-free transcriptome. PeerJ. (2025) 13:e19241. doi: 10.7717/peerj.19241
145. Popescu ID, Codrici E, Albulescu L, Mihai S, Enciu AM, Albulescu R, et al. Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches. Proteome Sci. (2014) 12:47. doi: 10.1186/s12953-014-0047-0
Keywords: cancer immunotherapy, epitranscriptome, N6-methylAdenosine (m6A), RNA modification, targeted therapy, therapeutic resistance
Citation: Sun Y, Wu J, Chen G, Ma H, Li W, Tan H and Yang K (2026) Rewriting the RNA code: an m6a-centric framework to classify tumors and guide combination therapies. Front. Immunol. 17:1749911. doi: 10.3389/fimmu.2026.1749911
Received: 19 November 2025; Accepted: 08 January 2026; Revised: 05 January 2026;
Published: 30 January 2026.
Edited by:
Jose A. Garcia-Sanz, Spanish National Research Council (CSIC), SpainReviewed by:
Ana Kvolik Pavić, Osijek Clinical Hospital Center, CroatiaAlice Cleynen, Délégation Languedoc Roussillon (CNRS), France
Copyright © 2026 Sun, Wu, Chen, Ma, Li, Tan and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Kerong Yang, eWFuZ2tlcm9uZ19vcnRob0AxNjMuY29t; eWtyOTNvcnRob0B6enUuZWR1LmNu