Epitranscriptomic Modifications (m6A, m5C) as Emerging Regulators of Drug Response and Resistance

Figure 1: A detailed illustration showing how "writer" proteins (METTL3, METTL14) add m⁶A marks, "eraser" enzymes (FTO, ALKBH5) remove them, and various "reader" proteins (YTH family, IGF2BPs, etc.) in the nucleus and cytoplasm interpret these marks. The reader proteins direct specific biological processes, including RNA splicing, export, translation initiation, and mRNA decay, demonstrating how m⁶A can lead to divergent cellular outcomes.

The biological consequences of m6A are mediated by "reader" proteins. YTHDF1 promotes cap-independent translation initiation; YTHDF2 recruits the CCR4-NOT deadenylase complex, accelerating mRNA decay; YTHDF3 cooperates with both. Nuclear readers YTHDC1 and YTHDC2 regulate pre-mRNA splicing and RNA export. Cytoplasmic IGF2BP proteins (IGF2BP1-3) stabilize m6A-marked transcripts and enhance their translation. HNRNPA2B1 and HNRNPC compete with or act downstream of m6A to further modulate RNA processing. This multilayered reader system ensures that identical m6A marks can produce opposing biological outcomes depending on cellular context.

2.2 The m5C Regulatory Network

The NSUN family of S-adenosylmethionine (SAM)-dependent methyltransferases constitutes the primary writers of m5C on RNA. NSUN2 (also known as MISU) is the most studied; it methylates specific cytosines in tRNA, mRNA, and enhancer RNA, particularly at C34 and C38 of the anticodon loop of tRNAs and at internal sites of mRNAs. NSUN1, NSUN3, NSUN4, NSUN5, NSUN6, and NSUN7 exhibit distinct subcellular localizations and substrate preferences. TRDMT1, a close homolog of DNA methyltransferases, methylates cytosines in tRNAs and certain mRNAs and plays roles in meiosis, stress response, and mitochondrial function. m5C reader proteins include ALYREF, which recognizes m5C in mRNA and facilitates nuclear export through the TREX complex. YBX1 (Y-box binding protein 1) stabilizes m5C-modified transcripts in the cytoplasm. The absence of a dedicated m5C eraser in RNA comparable to TET enzymes on DNA has been noted; though some evidence implicates ALKBH1 in the demethylation of certain m5C sites on tRNA, this remains an area of active investigation.

3. m6A and Drug Resistance: Mechanisms and Evidence

3.1 m6A in Chemotherapy Resistance

The most extensively studied link between m6A and drug resistance involves the cisplatin-resistant phenotype. In non-small cell lung cancer (NSCLC) and ovarian carcinoma, elevated METTL3 expression has been associated with cisplatin resistance. Mechanistically, METTL3-mediated m6A methylation of HOXA13 and Wnt pathway transcripts promotes their translation, activating anti-apoptotic programs that allow cells to withstand cisplatin-induced DNA damage. Conversely, in bladder cancer, METTL3 upregulation promotes m6A methylation of AFF4, an SEC elongation complex subunit, enhancing transcriptional elongation of drug resistance genes. FTO, the primary m6A eraser, has emerged as a critical vulnerability in acute myeloid leukemia (AML). FTO promotes leukemic cell survival and chemotherapy resistance by erasing m6A from ASB2 and RARA transcripts, preventing their degradation. Treatment with small molecule FTO inhibitors (meclofenamic acid, rhein, and CS1) resensitized AML cells to cytarabine (Ara-C) and all-trans retinoic acid (ATRA) in preclinical models, establishing proof-of-principle for m6A eraser targeting as a therapeutic strategy in hematologic malignancies. ALKBH5 overexpression has been demonstrated to promote doxorubicin and gemcitabine resistance in pancreatic ductal adenocarcinoma (PDAC) and breast cancer. By demethylating NANOG and FOXM1 mRNAs—transcription factors governing pluripotency and proliferation—ALKBH5 maintains a cancer stem cell (CSC) phenotype characterized by heightened drug efflux, enhanced DNA repair capacity, and resistance to apoptosis. YAP/TAZ signaling, critical to mechanotransduction and resistance to multiple chemotherapeutic agents, is also regulated post-transcriptionally by m6A-dependent YTHDF2-mediated mRNA degradation, implicating the m6A axis in broad chemoresistance.

3.2 m6A in Targeted Therapy Resistance

Resistance to tyrosine kinase inhibitors (TKIs) represents a major unmet clinical need. In chronic myeloid leukemia (CML), BCR-ABL-targeted therapy with imatinib induces upregulation of YTHDF2, which mediates degradation of LHPP and NKX2-1 tumor suppressor mRNAs, contributing to a survival advantage and eventual drug tolerance. In EGFR-mutant NSCLC treated with osimertinib, METTL3-mediated m6A modification of EGFR transcript 3'-UTR stabilizes the transcript via IGF2BP2 reading, sustaining EGFR signaling and attenuating the drug effect. FTO has been identified as a driver of resistance to anti-PD-1 immunotherapy. By removing m6A marks from transcripts encoding immune checkpoint ligands such as PD-L1 and CXCL1, FTO stabilizes their expression, facilitating tumor immune evasion. FTO inhibition in melanoma models enhanced anti-PD-1 efficacy, supporting a synergistic approach to immunotherapy resistance. These data underscore the dual pharmacological relevance of m6A regulation: not only in direct cytotoxic drug resistance but also in modulating the tumor immune microenvironment.

3.3 Context-Dependency and Tumor-Specific Roles

A recurring complexity in the field is the context-dependent and occasionally opposing roles of m6A regulators across cancer types. For instance, METTL3 acts as an oncogene promoting drug resistance in lung and bladder cancers yet functions as a tumor suppressor in glioblastoma and endometrial cancer. This dichotomy reflects the differential transcript landscape in each cell type—the same enzyme targets distinct mRNAs depending on the transcriptome, chromatin architecture, and co-regulatory environment. This underscores the necessity of tumor-type-specific characterization before any clinical translation of m6A-targeting strategies.

4. m5C and Drug Resistance: Mechanisms and Evidence

4.1 NSUN2 in Chemotherapy Resistance

NSUN2 is the most studied m5C writer in the context of drug resistance. In hepatocellular carcinoma (HCC), NSUN2 overexpression correlates with sorafenib resistance. NSUN2-mediated m5C modification of the HDGF (hepatoma-derived growth factor) mRNA enhances its translation, activating downstream PI3K/AKT/mTOR signaling, a pathway widely implicated in multidrug resistance (MDR). Pharmacological inhibition of NSUN2 or genetic knockdown resensitizes HCC cells to sorafenib in vitro and in vivo. In colorectal cancer, NSUN2 has been found to methylate SERBP1 mRNA, stabilizing it and promoting the synthesis of PAI-1, which activates the uPA/plasminogen system involved in metastatic dissemination and resistance to 5-fluorouracil (5-FU). Additionally, NSUN2-mediated tRNA methylation prevents tRNA fragmentation under drug-induced stress conditions, preserving translational fidelity in drug-resistant cells—a mechanism distinct from direct mRNA regulation but equally consequential for cellular proteostasis during chemotherapy.

4.2 m5C, tRNA Modifications, and Translational Reprogramming

tRNA modifications are a critical but often overlooked mechanism of translational reprogramming in drug-resistant cells. m5C at positions 34 and 38 of tRNAs, deposited by NSUN2 and TRDMT1, protects against endonucleolytic cleavage and maintains translational efficiency of specific codon-biased mRNAs. Under chemotherapeutic stress, the balance between intact tRNAs and tRNA-derived small fragments (tsRNAs/tRFs) shifts; m5C-deficient cells accumulate stress granules, activate the integrated stress response (ISR), and may paradoxically develop drug tolerance through ISR-mediated translational reprogramming involving ATF4 and downstream resistance genes including ASNS and CHAC1. This tRNA-mediated mechanism connects m5C to a broad translational resistance network that may operate independently of canonical oncogene/tumor suppressor pathways. It suggests that NSUN2 inhibition, while potentially resensitizing cancer cells through mRNA-level effects, might simultaneously engage protective stress responses—a duality that must be carefully considered in therapeutic design.

4.3 TRDMT1 and Immunotherapy Resistance

Emerging evidence positions TRDMT1 as a regulator of cancer immune evasion. TRDMT1 deposits m5C on specific mRNAs in the tumor microenvironment, including immune modulatory transcripts. Studies in breast cancer have suggested that TRDMT1 expression inversely correlates with CD8+ T cell infiltration and responsiveness to anti-PD-L1 therapy, potentially through modulation of MHC-I presentation pathway transcripts. While mechanistic details remain to be fully elucidated, TRDMT1 represents an intriguing candidate for combinatorial immunotherapy strategies.

5. Detection Technologies and Methodological Considerations

Accurate mapping of m6A and m5C across the transcriptome is essential for both mechanistic studies and biomarker development. Several complementary technologies have been developed. MeRIP-seq (methylated RNA immunoprecipitation sequencing, also called m6A-seq) uses m6A-specific antibodies to enrich methylated fragments prior to sequencing, providing transcriptome-wide coverage but limited to ~200 nucleotide resolution. Single-nucleotide resolution methods include m6A-CLIP, MAZTER-seq, and DART-seq (deamination adjacent to RNA modification targets), each with distinct biases, coverage, and input RNA requirements. For m5C, bisulfite sequencing of RNA (RNA-BS-seq) converts unmethylated cytosines to uracil while preserving m5C, providing base-resolution maps. Aza-IP and miCLIP (m5C individual-nucleotide resolution crosslinking immunoprecipitation) are antibody-based alternatives. A critical challenge in the field is the incomplete and variable antibody specificity noted for both m6A and m5C, leading to false positives and cross-reactivity that have complicated several published datasets. The development of chemoenzymatic and direct nanopore sequencing-based approaches promises to overcome these limitations and enable clinical-grade epitranscriptomic profiling.

6. Therapeutic Targeting of Epitranscriptomic Enzymes

6.1 m6A Writers as Drug Targets

METTL3 has attracted considerable pharmaceutical interest. STM2457 is the first highly selective, orally bioavailable METTL3 inhibitor developed. In preclinical AML models, STM2457 reduces m6A levels on oncogenic transcripts, promotes differentiation, and significantly prolongs survival without substantial toxicity. It has now entered early-phase clinical evaluation (NCT05584982). Additional METTL3 inhibitors including UZH1a, AMKS and SAM-competitive compounds are under investigation. Key challenge: given the broad substrate scope of METTL3, systemic inhibition risks disrupting normal epitranscriptomic homeostasis, particularly in rapidly dividing hematopoietic cells.

6.2 m6A Erasers as Drug Targets

FTO inhibitors have advanced furthest in preclinical development. Meclofenamic acid (MA), originally an NSAID, was identified as an FTO inhibitor that selectively suppresses glioblastoma stem cell self-renewal and AML growth. Rhein (a natural anthraquinone) and its derivatives exhibit FTO inhibitory activity and have demonstrated efficacy in AML and obese adipose tissue models. CS1 and FB23 series compounds represent next-generation, structurally distinct FTO inhibitors with improved selectivity over ALKBH demethylases. ALKBH5 inhibitors remain less developed but are actively pursued, particularly in the context of triple-negative breast cancer (TNBC) and pancreatic cancer.

6.3 m5C Enzyme Targeting

NSUN2 inhibitors are an early-stage area of research. Tenovin-1, originally identified as an MDM2 inhibitor, was found to indirectly suppress NSUN2 function in melanoma models. Direct NSUN2 inhibitors have been designed based on the crystal structure of the enzyme's catalytic pocket, though none have yet entered clinical trials. Given NSUN2's roles in tRNA modification, precision targeting of its mRNA methyltransferase activity (distinct from its tRNA function) would be necessary to avoid global translational toxicity—a challenging feat given the overlapping active sites.

6.4 RNA-Based Approaches

Beyond small molecules, RNA-based strategies including antisense oligonucleotides (ASOs) targeting METTL3, FTO, NSUN2, and reader mRNAs, as well as CRISPR-based epitranscriptomic editing using dCas13-fused methyltransferase or demethylase domains, represent orthogonal approaches with high specificity. These tools are particularly valuable for functional studies and, with continued improvement in delivery systems, hold clinical promise for localized tumor targeting.

7. Clinical Implications and Biomarker Potential

Several retrospective studies and transcriptomic analyses have identified m6A and m5C regulators as prognostic biomarkers. High METTL3 expression correlates with poor overall survival in lung adenocarcinoma, HCC, and bladder cancer cohorts from TCGA datasets. FTO expression inversely correlates with overall survival in AML and cervical cancer. NSUN2 overexpression is associated with reduced disease-free survival in gastric and colorectal cancers. In the clinical setting, liquid biopsy approaches detecting m6A-modified circulating tumor RNAs have been proposed as minimally invasive diagnostic and monitoring tools, though sensitivity and specificity remain to be validated in large prospective studies. Translation of these findings into predictive biomarkers for treatment selection requires prospective validation in uniformly treated cohorts. Moreover, the dynamic and reversible nature of epitranscriptomic marks means that single time-point biopsies may inadequately capture the evolving epitranscriptomic landscape under treatment pressure. Serial sampling and integration with other omics modalities (genomics, proteomics, metabolomics) will likely be necessary for clinically meaningful stratification.

LIMITATIONS AND FUTURE DIRECTIONS

Despite rapid progress, several critical limitations temper enthusiasm for clinical translation. First, most mechanistic studies have been conducted in cell lines or xenograft models that do not recapitulate the complexity of human tumor microenvironments. Second, the context-dependency of m6A and m5C effects—sometimes oncogenic, sometimes tumor-suppressive—within different cancer types and even within the same tumor at different stages creates significant uncertainty for therapeutic targeting. Third, the incomplete selectivity of current antibody-based detection methods limits confidence in published transcriptome-wide m6A and m5C maps. Fourth, epitranscriptomic modifications do not act in isolation. They intersect extensively with other post-transcriptional regulatory layers: RNA secondary structure, RNA-binding protein networks, microRNA-mediated regulation, and alternative polyadenylation all interact with m6A and m5C landscapes. Systems-level approaches integrating multi-omics data will be essential to disentangle these interactions and predict the net effect of epitranscriptomic perturbations on drug response.

Future research priorities include: (1) development of highly selective, pharmacologically optimized inhibitors of METTL3, FTO, ALKBH5, and NSUN2; (2) robust clinical biomarker studies correlating epitranscriptomic profiles with drug response in prospectively designed trials; (3) investigation of combination strategies pairing epitranscriptomic modulators with standard chemotherapy, targeted agents, or immune checkpoint inhibitors; (4) application of single-cell epitranscriptomics to characterize tumor heterogeneity in m6A/m5C landscapes; and (5) nanopore direct RNA sequencing as a clinical-grade, antibody-independent platform for comprehensive modification profiling.

CONCLUSION

Epitranscriptomic modifications, particularly m6A and m5C, have emerged as integral regulators of the cellular response to pharmacological stress. Through their dynamic, reversible, and context-dependent effects on RNA stability, translation, and processing, these marks modulate the expression of oncogenes, tumor suppressors, drug efflux transporters, DNA repair enzymes, and immune modulatory factors—each a critical determinant of treatment outcome. The enzymes that write, erase, and read these marks are actionable therapeutic targets, with early-phase clinical data for METTL3 inhibitors (STM2457) representing a landmark advance in the field. As our understanding of the epitranscriptome deepens and detection technologies mature, m6A and m5C are poised to become clinically integrated biomarkers and therapeutic targets. Realizing this potential will require concerted interdisciplinary efforts bridging chemical biology, RNA biochemistry, translational oncology, and clinical pharmacology. The epitranscriptomic dimension of drug resistance is no longer a curiosity—it is a frontier of therapeutic opportunity that demands urgent scientific and clinical attention.

ACKNOWLEDGMENTS

The authors declare no specific acknowledgments. All figures and content were developed by the authors. No external funding supported this review.

Author Contributions (ICMJE CRediT)

All authors contributed to the conceptualization, literature search, drafting, critical revision, and final approval of this manuscript. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

REFERENCES

1. Dominissini D, Moshitch-Moshkovitz S, Schwartz S, et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq. Nature. 2012;485(7397):201-206.
2. Meyer KD, Saletore Y, Zumbo P, et al. Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons. Cell. 2012;149(7):1635-1646.
3. Liu J, Yue Y, Han D, et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat Chem Biol. 2014;10(2):93-95.
4. Jia G, Fu Y, Zhao X, et al. N6-methyladenosine in nuclear RNA is a major substrate of the obesity-associated FTO. Nat Chem Biol. 2011;7(12):885-887.
5. Zheng G, Dahl JA, Niu Y, et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. Mol Cell. 2013;49(1):18-29.
6. Wang X, Lu Z, Gomez A, et al. N6-methyladenosine-dependent regulation of messenger RNA stability. Nature. 2014;505(7481):117-120.
7. Wang X, Zhao BS, Roundtree IA, et al. N6-methyladenosine modulates messenger RNA translation efficiency. Cell. 2015;161(6):1388-1399.
8. Su R, Dong L, Li C, et al. R-2HG exhibits anti-tumor activity by targeting FTO/m6A/MYC/CEBPA signaling. Cell. 2018;172(1-2):90-105.
9. Barbieri I, Tzelepis K, Pandolfini L, et al. Promoter-bound METTL3 maintains myeloid leukaemia by m6A-dependent translation control. Nature. 2017;552(7683):126-131.
10. Vu LP, Pickering BF, Cheng Y, et al. The N6-methyladenosine (m6A)-forming enzyme METTL3 controls myeloid differentiation of normal hematopoietic and leukemia cells. Nat Med. 2017;23(11):1369-1376.
11. Huang H, Weng H, Sun W, et al. Recognition of RNA N6-methyladenosine by IGF2BP proteins enhances mRNA stability and translation. Nat Cell Biol. 2018;20(3):285-295.
12. Roundtree IA, Evans ME, Pan T, He C. Dynamic RNA modifications in gene expression regulation. Cell. 2017;169(7):1187-1200.
13. Frye M, Harada BT, Behm M, He C. RNA modifications modulate gene expression during development. Science. 2018;361(6409):1346-1349.
14. Bohnsack KE, Höbartner C, Bohnsack MT. Eukaryotic 5-methylcytosine (m5C) RNA methyltransferases: mechanisms, cellular functions, and links to disease. Genes (Basel). 2019;10(2):102.
15. Squires JE, Patel HR, Nousch M, et al. Widespread occurrence of 5-methylcytosine in human coding and non-coding RNA. Nucleic Acids Res. 2012;40(11):5023-5033.
16. Huang T, Chen W, Liu J, et al. Genome-wide identification of mRNA 5-methylcytosine in mammals. Nat Struct Mol Biol. 2019;26(5):380-388.
17. Yang X, Yang Y, Sun BF, et al. 5-methylcytosine promotes mRNA export—NSUN2 as the methyltransferase and ALYREF as an m5C reader. Cell Res. 2017;27(5):606-625.
18. Linder B, Grozhik AV, Olarerin-George AO, et al. Single-nucleotide-resolution mapping of m6A and m6Am throughout the transcriptome. Nat Methods. 2015;12(8):767-772.
19. Delaunay S, Frye M. RNA modifications regulating cell fate in cancer. Nat Cell Biol. 2019;21(5):552-559.
20. He L, Li H, Wu A, Peng Y, Shu G, Yin G. Functions of N6-methyladenosine and its role in cancer. Mol Cancer. 2019;18(1):176.
21. Chen J, Sun Y, Xu X, et al. YTH domain family 2 orchestrates epithelial-mesenchymal transition/proliferation dichotomy in pancreatic cancer cells. Cell Cycle. 2017;16(23):2259-2271.
22. Weng H, Huang H, Wu H, et al. METTL14 inhibits hematopoietic stem/progenitor differentiation and promotes leukemogenesis via mRNA m6A modification. Cell Stem Cell. 2018;22(2):191-205.
23. Li Z, Weng H, Su R, et al. FTO plays an oncogenic role in acute myeloid leukemia as a N6-methyladenosine RNA demethylase. Cancer Cell. 2017;31(1):127-141.
24. Zhang C, Samanta D, Lu H, 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 USA. 2016;113(14): E2047-E2056.
25. Lossos IS, Czerwinski DK, Alizadeh AA, et al. Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med. 2004;350(18):1828-1837.
26. Paris J, Morgan M, Campos J, et al. Targeting the RNA m6A reader YTHDF2 selectively compromises cancer stem cells in acute myeloid leukemia. Cell Stem Cell. 2019;25(1):137-148.
27. Yankova E, Blackaby W, Albertella M, et al. Small-molecule inhibition of METTL3 as a strategy against myeloid leukaemia. Nature. 2021;593(7860):597-601.
28. Chen B, Ye F, Yu L, et al. Development of cell-active N6-methyladenosine RNA demethylase FTO inhibitor. J Am Chem Soc. 2012;134(43):17963-17971.
29. Xiao S, Cao S, Huang Q, et al. The RNA N6-methyladenosine modification landscape of human fetal tissues. Nat Cell Biol. 2019;21(5):651-661.
30. Nombela P, Miguel-López B, Blanco S. The role of m6A, m5C and Ψ RNA modifications in cancer: novel therapeutic opportunities. Mol Cancer. 2021;20(1):18.