The identification of genes related to METTL14 inhibition in radiation- induced hepatocyte death based on bioinformatics analysis

The identification of genes related to METTL14 inhibition in radiation- induced hepatocyte death based on bioinformatics analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The identification of genes related to METTL14 inhibition in radiation- induced hepatocyte death based on bioinformatics analysis Sijian Liu, Li Qu, Jiayi Wu, Huazhong Wang, Kewei Tan, Jiang Yu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8087326/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background: Radiation-Induced Liver Disease (RILD) is a major dose-limiting complication in radiotherapy for hepatocellular carcinoma, yet its molecular mechanisms remain incompletely understood compared to radiation injury in other organs. Programmed cell death (PCD) pathways like apoptosis, pyroptosis, and ferroptosis are crucial in RILD development. The m6A modification enzyme METTL14 is implicated in driving these PCD pathways, but its role in radiation-induced hepatocyte injury was unknown. This study aimed to elucidate METTL14's function and molecular mechanisms in RILD pathogenesis to identify novel therapeutic targets. Methods: C57BL/6J mice received 30 Gy liver irradiation (5 Gy × 6 fractions). METTL14 overexpression was achieved by tail-vein injection of AAV-METTL14. Liver injury was evaluated by transmission electron microscopy (TEM), RNA-seq, bioinformatics and molecular validation (qRT-PCR / Western blot). Results: Irradiation markedly reduced hepatic METTL14 protein. Overexpression of METTL14 preserved hepatocyte ultrastructure and decreased cell death. Transcriptomic profiling revealed 964 differentially expressed genes (DEGs), were apoptosis-related. Functional enrichment and PPI network analyses identified ten hub genes, with HMOX1 and SERPINE1 exhibiting the most consistent up-regulation at both mRNA and protein levels. A TF–mRNA–miRNA regulatory network further implicated hsa-miR-145-5p and 33 upstream transcription factors in controlling these hubs. Conclusion: METTL14 overexpression protects against radiation-induced hepatocyte injury primarily through modulation of apoptosis and ferroptosis pathways, with HMOX1 and SERPINE1 serving as key downstream effectors. Targeting the METTL14–SERPINE1- miR-145-5p axis may offer a novel therapeutic strategy for RILD. Biological sciences/Cancer Biological sciences/Cell biology Health sciences/Diseases Biological sciences/Genetics Biological sciences/Molecular biology RILD Cell death METTL14 Apoptosis Ferroptosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1 INTRODUCTION Radio-induced liver injury (RILD) is a common complication in the radiotherapy of liver cancer. The incidence of RILD varies due to factors such as radiotherapy techniques, dose fractionation, and patient-specific differences 1 . Approximately 66% of liver cancer patients undergoing 30-35 Gy liver radiation therapy exhibit significant RILD 2 , typically manifesting 2 weeks to 4 months post-treatment 3,4 . Advances in radiation technologies like intensity-modulated radiotherapy (IMRT) and stereotactic body radiotherapy (SBRT) have reduced RILD rates, but it remains a concern 5,6 . RILD not only limits the escalation of radiation doses, affecting treatment efficacy, but also leads to severe symptoms like liver dysfunction, abdominal pain, and ascites, potentially threatening patient lives 7 . This condition prolongs hospital stays, increases medical costs, and may necessitate adjustments to subsequent treatment plans, impacting overall treatment outcomes and quality of life. Recent research has focused on identifying predictive markers for personalized radiotherapy planning and exploring new prevention and treatment strategies, although effective clinical methods are still lacking. The pathogenesis of RILD involves direct damage, inflammatory response activation, oxidative stress, and cytokine and signaling pathway abnormalities. Direct damage occurs as high-energy ionizing radiation impacts critical cellular structures like DNA, cell membranes, and organelles, leading to DNA double-strand breaks, altered membrane permeability, and organelle dysfunction 8–11 . This triggers cellular stress responses, affecting metabolism and function, and can result in cell death or dysfunction. Radiation-induced hepatocyte damage triggers inflammatory responses 12 , releasing inflammatory mediators like TNF-α, IL-1, and IL-6 13–15 , which recruit immune cells to the site of injury, exacerbating inflammation. Persistent inflammation disrupts the liver microenvironment, affecting hepatocyte function and regeneration 16,17 . Additionally, radiation increases reactive oxygen species (ROS) production in hepatocytes 18 , leading to oxidative stress and damage to cellular components. The antioxidant defense system may be overwhelmed post-irradiation, disrupting redox balance and exacerbating liver cell damage 19 . Abnormalities in cytokines and signaling pathways, such as TGF-β and JAK-STAT pathways, also contribute to RILD pathogenesis 20–22 . Cell death plays a crucial role in RILD, affecting liver tissue structure and function. Various forms of cell death, including apoptosis, disulfidptosis, pyroptosis, and ferroptosis, are involved in RILD, influencing its progression. For instance, METTL3-mediated STING activation in Kupffer cells triggers pyroptosis, contributing to radiation-induced liver disease 23 . MicroRNA-146a-5p can mitigate radiation-induced hepatocyte apoptosis by inhibiting the TLR4 pathway 24 . Ionizing radiation induces DNA damage and various forms of cell death, releasing damage-associated molecular patterns (DAMPs) 25 , which interact with pattern recognition receptors to trigger inflammation. This process activates immune cells like Kupffer cells, leading to the release of inflammatory cytokines and the recruitment of immune cells, exacerbating radiation-induced liver injury 26,27 . METTL14, a methyltransferase involved in RNA N6-methyladenosine (m6A) modification, is closely associated with cell death under various physiological and pathological conditions 28–30 . In apoptosis, METTL14 can either inhibit or promote cell death depending on the cellular context. For example, it can promote the expression of anti-apoptotic genes or inhibit pro-apoptotic genes in non-small cell lung cancer cells 31 . In contrast, under oxidative or endoplasmic reticulum stress, METTL14 can promote apoptosis 32 . In ferroptosis, METTL14 regulates genes related to iron metabolism and lipid peroxidation, affecting intracellular iron levels and lipid metabolism 33,34 . METTL14 also participates in pyroptosis and autophagy, showing its complex role in cell death regulation 28,35 . Its involvement in multiple cell death pathways highlights its potential clinical significance in disease diagnosis, treatment, and prognosis. Current understanding of RILD pathogenesis is limited, focusing mainly on cell damage, inflammation, and fibrosis 2 . However, these mechanisms do not fully explain the complexity of RILD development. As a core component of the m6A methylation transferase complex, METTL14 plays a broad regulatory role in cellular processes. Its potential role in RILD could reveal new molecular regulatory networks and cellular mechanisms, offering new insights into the disease. Radiation-induced DNA damage in hepatocytes alters mRNA levels and stability, leading to cell injury and death 8 . METTL14, by modifying mRNA stability, could influence the impact of radiation on hepatocytes. It might modify mRNA of anti-apoptotic genes to promote cell survival or reduce expression of ferroptosis genes to inhibit cell death, affecting RILD progression. Given its role in liver diseases and regeneration 36–38 , studying METTL14 in RILD could lead to novel diagnostic and therapeutic strategies, potentially improving patient outcomes. 2 MATERIALS AND METHODS 2.1 Data Collection and Acquisition Cell death-related genes are from the ferroptosis-related database (FerrDB) (http://www.zhounan.org/ferrdb/current/) 39 、autophagy-related database (Human Autophagy Database) (https://autophagy.lu/v1/)、MSigDB database(Molecular Signatures Database)(https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). 2.2 Experimental Animals Male C57BL/6J mice (8–10 weeks old, SPF grade) were purchased from Changsha Tianqin Biotechnology Co., Ltd. (Hunan, China). On the day of allocation (before randomization), body weight averaged 21.5 ± 2.1 g and did not differ among groups. As expected in the RILI model, irradiated animals lost significantly more weight than controls during the study. At experiment termination, mice were deeply anaesthetised with sodium pentobarbital (150 mg/kg.). Loss of the toe-pinch reflex was followed immediately by cervical dislocation to ensure death. This two-step protocol complies with the AVMA Guidelines for the Euthanasia of Animals (2020) and was approved by the Medical Ethics Committee of the First Affiliated Hospital, University of South China. 2.3 Electron Microscopy For the preparation of liver tissue samples for electron microscopy (EM), freshly isolated tissues were trimmed into 1×2 mm³ blocks and immediately fixed using a two-step process involving 3% glutaraldehyde in 0.1 M phosphate-buffered saline (PBS) at 4°C for 24 hours, followed by 1% osmium tetroxide at 4°C for 2 hours. The samples were then subjected to a graded acetone dehydration series (30% to 100%), infiltrated with Epon812 resin, and embedded. Ultrathin sections, approximately 60-90 nm thick, were cut using a diamond knife, collected on 200-mesh copper grids, and stained with uranyl acetate and lead citrate to enhance contrast. The stained sections were examined using a JEM-1400FLASH transmission electron microscope (JEOL, Japan) at 80 kV, and images were captured with a Gatan digital camera. This detailed procedure allowed for a comprehensive examination of the liver tissue ultrastructure post-irradiation, providing insights into the cellular changes induced by radiation. 2.4 Transcriptome Sequencing Transcriptome analysis was performed using the Illumina high-throughput sequencing platform. Total RNA was extracted and assessed for quality. mRNA was enriched using oligo(dT) magnetic beads for eukaryotic RNA or an RNA removal kit for degraded or prokaryotic RNA. Library construction involved RNA fragmentation, first-strand cDNA synthesis, second-strand cDNA synthesis, end repair, A-tailing, adapter ligation, and PCR amplification. Library quality was verified using an Agilent 2100 bioanalyzer and qPCR. 2.5 Quantitative Real-Time PCR (qRT-PCR) For the analysis of gene expression, total RNA was extracted from mouse liver tissues using Trizol reagent, following the manufacturer's protocol. The quality and concentration of RNA were assessed using a NanoDrop spectrophotometer and agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using a reverse transcription kit, with oligo(dT) primers and M-MLV reverse transcriptase. The cDNA was then diluted and used as a template for quantitative real-time PCR (qRT-PCR). qRT-PCR was performed using a TB Green Master Mix in a total reaction volume of 20 μL, which included 10 μL of TB Green Master Mix, 0.4 μL each of forward and reverse primers (10 μM), and 2 μL of cDNA template. The thermal cycling conditions were as follows: an initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 5 seconds, and annealing/extension at 60°C for 20 seconds. The relative expression levels of the target genes were normalized to the housekeeping gene GAPDH using the 2^-ΔΔCt method. Each sample was run in triplicate, and the mean values were used for analysis. 2.6 Western Blot Analysis Protein extraction from liver tissues was carried out using RIPA lysis buffer supplemented with protease and phosphatase inhibitors. The protein concentration was determined using the BCA protein assay kit, and equal amounts of protein (30 μg) were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). After electrophoresis, the proteins were transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were then blocked with 5% non-fat milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature. Subsequently, the membranes were incubated with primary antibodies specific to the target proteins overnight at 4°C. After washing with TBST, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies for 1 hour at room temperature. The protein bands were visualized using an enhanced chemiluminescence (ECL) detection system. The intensity of the bands was quantified using ImageJ software, and the results were normalized to the internal control β-actin. All experimental protocols involving animals were approved by the Medical Ethics Committee of the First Affiliated Hospital of University of South China. All methods were carried out in accordance with relevant guidelines and regulations and are reported in accordance with ARRIVE guidelines. Euthanasia was performed by cervical dislocation under anesthesia. 2.7 Identification of DEGs Related to cell death The RNA sequencing data underwent differential expression analysis using the R package limma (version 3.40.6). Significantly differentially expressed genes between OE and NC were identified based on a P value < 0.05 and |log(fold change)| ≥ 1.2 criteria. Subsequently, using the Venn map network tool (http://bioinformatics.psb.ugent.be/webtools/Venn/), the overlap between the DEGs of RNA-seq and 1093 cell death- related genes was examined. They are cell death- related genes that may participate in the radiation-induced hepatocyte death. 2.8 Enrichment analyses The selected DEGs and hub genes were analyzed for GO and KEGG enrichment 40 analysis using R and metascape (https://metascape.org/gp/index.html#/main/step1) 41 . GO has three levels of analysis: molecular function (MF), cellular component (CC), and biological process (BP). A widespread database used to investigate illnesses,chemicals, medications,biological processes, and genomes is called KEGG. When DEG met p < 0.05 and count ≥ 10 in the above two analyses, it had statistical significance in this study. KEGG pathway analysis was performed using the KEGG database (Kanehisa Laboratories) with appropriate permissions obtained.Weshengxin (http://www.bioinformatics.com.cn,), a free online application for data processing and visualization, was used to create the bubble diagram 2.9 PPI Network Construction and Hub Gene Screening Build a protein-protein interaction (PPI) network using the free, open-source STRING database (https://string-db.org/). To assess PPI, import the filtered DEGs into the STRING database. Create a visual network of PPIs using the Cytoscape program (https://cytoscape.org), then use Cytohubba to scan hub genes. 2.10 Construction of TF-mRNA-miRNA Network TRRUST(http://www.grnpedia.org/trrust) 42 created interaction networks between genes-miRNAs genes-transcription factors. miRWalk(http://mirwalk.umm.uni-heidelberg.de/) 43 created interaction networks between genes-miRNAs. All networks were visualized using Cytoscape software. 2.11 Statistical Analysis Data analysis was performed using GraphPad Prism 8.0.2 for visualization and basic analysis, and SPSS 27.0 for advanced statistical analysis. Mann-Whitney U test was used for comparisons between two groups, and Kruskal-Wallis H test for multiple groups (N≥3). ImageJ 1.53 was used for image quantification, and Image Lab 6.1 for Western blot band analysis. Photoshop 2022 was used for image optimization and layout. Data are presented as mean ± SD, and statistical significance was marked as *P < 0.05, **P < 0.01, ***P < 0.001. 3 RESULTS 3.1 METTL14 expression is downregulated by radiation To verify the inhibitory effect of radiation on METTL14 expression in mouse liver, we performed Western blot analysis. The Western blot results demonstrated a significant downregulation of METTL14 protein expression in liver tissues of irradiated mice compared to the control group (Figure 1A-B). These results confirm that radiation effectively suppresses METTL14 expression in murine hepatic tissues. 3.2 Develop a transgenic mouse model with METTL14 overexpression To investigate METTL14's role in radiation-induced hepatocyte injury, we generated a METTL14-overexpressing model. Western blot analysis demonstrated significantly elevated METTL14 protein expression in hepatocytes of OE-group mice versus C and NC controls (Figure 2A-B), confirming that the METTL14-overexpressing adeno-associated virus (AAV) successfully mediated hepatic METTL14 overexpression. 3.3 METTL14 overexpression significantly attenuated radiation-induced hepatocyte death To investigate the role of METTL14 in radiation-induced hepatocyte injury, we examined the effect of METTL14 overexpression on radiation-perturbed ultrastructure in hepatocytes using transmission electron microscopy (TEM). TEM analysis revealed that compared to the Control group, hepatocytes in the Negative Control (NC) group exhibited marked radiation-induced damage characterized by mitochondrial swelling, aberrant accumulation of lipid droplets, and plasma membrane rupture. In contrast, the OE group showed significantly alleviated ultrastructural damage relative to the NC group (Figure 3A). These results collectively demonstrate that METTL14 overexpression effectively mitigates radiation-induced ultrastructural injury in hepatocytes, conferring cytoprotective effects. 3.4 mRNA sequencing of the negative control (NC) and METTL14 overexpression group (OE) after radiation We therefore conclude that METTL14-mediated protection against radiation-induced hepatocyte injury operates primarily through the modulation of apoptosis-related genes.We sent three treated NC tissue samples and four tissue samples overexpressing METT14 for RNA sequencing, whose PCA analysis showed PC1(53.27%) and PC2(46.22%) (Figure 4A), followed by differential analysis, which showed that there were a total of 964 genes that were differentiated, of which 388 genes were up-regulated and 576 genes were down-regulated (Figure 4B). 3.5 Cell death-Related DEGs in METTL14 inhibition in radiation-induced hepatocyte death To determine the dominant mode of regulated cell death when METTL14 is over-expressed after irradiation, we intersected the 964 DEGs with curated cell-death gene sets. shows that 77 genes overlapped, with 61.04 % linked to apoptosis, 16.88 % to autophagy, 15.58 % to ferroptosis, 3.9 % to cuproptosis and 2.6 % to pyroptosis (Figure 5A-B).This distribution indicates that apoptosis is the most prominently represented death pathway. 3.6 GO and KEGG of cell detah-related DEGs. To elucidate the molecular mechanisms by which METTL14 mitigates radiation-induced hepatocyte injury, we performed GO and KEGG enrichment analyses on the 77 apoptosis-dominant intersecting DEGs. the results showed that BP was mainly focused on apoptosis regulation, KEGG was mainly focused on ferroptosis (Figure 6A) These enrichment patterns indicate that METTL14 orchestrates a multi-layered response centered on apoptosis modulation and lipid-related ferroptosis pathways. Collectively, we conclude that METTL14 alleviates radiation-induced hepatocyte damage by simultaneously regulating apoptosis and ferroptosis-related gene networks. 3.7 Constructing a differential gene PPI network to screen for core cell detah-related DEGs To pinpoint the downstream effectors through which METTL14 alleviates radiation-induced hepatocyte injury, we constructed a PPI network from the 77 core cell detah-related DEGs. The network diagram was constructed with Cytoscape software. After that, Cytohubba was used to continue the screening procedure for hub genes. According to the degree ranking, CytoHubba identified ten hub genes: HMOX1, AGT, MMP9, SERPINE1, SOD1, CXCL12, CAV1, SQSTM1, IL18 and CASP3 (Figure 7A).These hub genes are centrally positioned within the network, suggesting they mediate METTL14-driven cytoprotection. 3.8 Functional enrichment of ten hub genes To delineate the functional landscape of the ten hub genes, we subjected them to GO and KEGG enrichment analyses. Result shows highly significant enrichment in regulation of apoptotic signaling pathway, positive/negative regulation of apoptotic process,and related ROS- and inflammation-linked terms, with apoptotic pathways dominating both GO and KEGG outputs.This concentrated enrichment indicates that the core gene set acts primarily within apoptosis-regulatory networks(Figure 8A-C).We therefore conclude that these hub genes execute their protective roles in radiation-induced hepatocyte injury by modulating apoptosis-related signaling cascades, providing a focused molecular framework for further mechanistic studies. 3.9 Validation of ten hub genes with experiments To experimentally verify the ten hub genes identified by RNA-seq, we make qRT-PCR and western blot analysis. qRT-PCR performed that HMOX1, AGT, SERPINE1 and MMP9 mRNA levels reproduced the RNA sequencing (Figure 9A).Western blot analysis of the same liver lysates revealed that only HMOX1 and SERPINE1 proteins were significantly up-regulated in the OE group, in line with their mRNA profiles (Figure 9B-C).We therefore designate HMOX1 and SERPINE1 as METTL14-regulated, radiation-responsive effectors that merit functional follow-up. 3.10 Constructing a HMOX1 and SERPINE1 gene TF-mRNA-miRNA network To dissect the upstream and downstream regulatory circuitry of the HMOX1 and SERPINE1, we integrated transcription-factor (TF) binding and miRNA targeting data to construct a TF-mRNA-miRNA interaction network.The result positioned hsa-miR-145-5p as the most recurrent downstream miRNA and revealed 33 distinct TFs potentially governing the ten hub genes (Figure 10A).These findings indicate that a TF- SERPINE1- miR-145-5p axis may orchestrate the transcriptional and post-transcriptional control of apoptosis downstream of METTL14. 4 DISCUSSION Radiotherapy plays a pivotal role in the treatment of various cancers, including liver cancer. However, the risk of RILD poses significant challenges when applying radiotherapy to hepatocellular carcinoma (HCC). This complication not only limits the therapeutic potential of radiotherapy in HCC but also leads to severe clinical issues such as liver dysfunction, jaundice, ascites, liver failure, and gastrointestinal bleeding, potentially resulting in hemorrhagic shock or even death 3 . Despite advancements in precision radiotherapy techniques like stereotactic body radiotherapy (SBRT), which delivers high doses of radiation in limited fractions 44 , the acute and long-term adverse reactions in normal liver tissue remain a formidable obstacle. Clinically, RILD is categorized into classic fibrotic and non-classic acute types, with studies showing an increasing incidence of the latter despite the use of image-guided techniques and advanced dose planning 45,46 . METTL14, an m6A methylation enzyme, is implicated in numerous molecular functions, including apoptosis 32 , pyroptosis 47 , and ferroptosis 48 , which are closely linked to the development of RILD 25 . Our study indicates a decrease in METTL14 levels in mouse hepatocytes post-irradiation. By establishing a METTL14 overexpression mouse model, we observed an improvement in radiation-induced hepatocyte damage. Functional enrichment analysis of differentially expressed genes following METTL14 overexpression revealed a significant enrichment in apoptosis pathways, suggesting that METTL14 may ameliorate radiation-induced hepatocyte damage by regulating apoptosis. Ionizing radiation induces various forms of cell death in hepatocytes, including apoptosis 49 , ferroptosis 50 , autophagy 51 , and pyroptosis 52 . Our bioinformatics analysis identified intersection genes related to METTL14 and cell death, which are closely associated with apoptosis, autophagy, and ferroptosis. Using STRING tools to construct a protein-protein interaction (PPI) network, we identified 10 core differential genes enriched in apoptosis pathways. This suggests that apoptosis is likely a key mechanism by which METTL14 improves radiation-induced hepatocyte damage. The interaction between radiation and hepatocytes is complex, involving multiple layers and mechanisms. The dominant type of cell death in radiation-induced hepatocyte injury varies across studies due to various factors, including experimental conditions (temperature, humidity, gas composition), study design (sample selection, grouping, observation indicators), and the type and dose of radiation (X-rays, γ-rays, UV). Different radiation types have distinct energy characteristics and penetration abilities, influencing the degree and manner of hepatocyte damage and the dominant type of cell death. Research in this area is ongoing, with efforts to improve experimental techniques and designs to better understand the complex biological processes underlying radiation effects on hepatocytes. Our study identified two key genes, HMOX1 and SERPINE1, which are involved in the protective role of METTL14 against radiation-induced hepatocyte damage. HMOX1, a marker of ferroptosis, is closely related to iron metabolism and cellular stress responses 53,54 . SERPINE1, associated with apoptosis 55,56 , was found to be significantly altered in our study, suggesting its role in METTL14-mediated protection against radiation-induced hepatocyte damage. Further exploration of these genes and their mechanisms could provide insights into radiation-induced hepatocyte injury and potential therapeutic targets. This study reveals the protective role of METTL14 in radiation-induced hepatocyte damage and explores its mechanisms, including the regulation of HMOX1-mediated ferroptosis and SERPINE1-mediated apoptosis. These findings are significant for understanding the complex regulatory networks of radiation-induced liver injury and could lead to the development of novel therapeutic strategies. Future research should focus on the molecular interactions between METTL14 and these target genes and translate these findings into clinical applications through rigorous clinical trials. 5 CONCLUSION This study provides preliminary evidence that METTL14 overexpression ameliorates radiation-induced hepatocyte damage, potentially through the regulation of apoptosis. We demonstrate that hepatic METTL14 expression is acutely suppressed after irradiation and that restoration of METTL14 via AAV-mediated gene transfer markedly attenuates radiation-induced hepatocyte death. Integrated transcriptomic and network analyses converge on apoptosis and ferroptosis as the dominant pathways, with HMOX1 and SERPINE1 emerging as METTL14-regulated effector molecules. These findings not only extend the known functions of m6A modification to radiation biology but also nominate METTL14, HMOX1 and SERPINE1 as tractable therapeutic targets for mitigating RILD. Declarations Acknowledgements Permission to use KEGG pathway images has been obtained from Kanehisa Laboratories via the copyright request form (www.kegg.jp/feedback/copyright.html). KEGG pathway maps were generated using the KEGG database (Kanehisa Laboratories) and are cited in accordance with their guidelines. Funding information This work was supported by the National Natural Science Foundation of China (grant number: 8210121825) and Foundation of of No. 922 PLA Hospital (grant number: 2025YJ01) . Availability of data and material The datasets generated and/or analysed during the current study are available in the arrayexpress (EMTAB-16163) repository . Author Contributions Sijian Liu: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. Li Qu: Conceptualization, Funding acquisition, Data curation, Investigation, Methodology, Supervision, Writing – review & editing. Jiayi Wu: Investigation, Formal analysis, Validation, Writing – review & editing. Huazhong Wang: Investigation, Resources, Writing – review & editing. Kewei Tan: Data curation, Software, Visualization, Writing – review & editing. Jiang Yu: Investigation, Validation, Writing – review & editing. Yuzhen He: Investigation, Validation, Writing – review & editing. Yiteng Ding: Investigation, Resources, Writing – review & editing. Huangui Zhang: Investigation, Formal analysis, Writing – review & editing. Wenjun Yin: Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing. All authors have read and approved the final version of the manuscript. Ethics approval and consent to participate All animal experiments were approved by the Medical Ethics Committee of the First Affiliated Hospital of University of South China. All methods were carried out in accordance with relevant guidelines and regulations and are reported in accordance with ARRIVE guidelines. Euthanasia was performed by cervical dislocation under anesthesia. Competing interests The authors declare that the research was conducted in the absence of any commercial or fnancial relationships that could be construed as a potential confict of interest. Consent for publication All authors have provided their consent for publication. References Burgio, E., Piscitelli, P. & Migliore, L. Ionizing Radiation and Human Health: Reviewing Models of Exposure and Mechanisms of Cellular Damage. An Epigenetic Perspective. Int J Environ Res Public Health 15 , 1971 (2018). Kim, J. & Jung, Y. Radiation-induced liver disease: current understanding and future perspectives. Exp Mol Med 49 , e359 (2017). Benson, R., Madan, R., Kilambi, R. & Chander, S. Radiation induced liver disease: A clinical update. J Egypt Natl Canc Inst 28 , 7–11 (2016). Koay, E. J., Owen, D. & Das, P. Radiation-Induced Liver Disease and Modern Radiotherapy. Semin Radiat Oncol 28 , 321–331 (2018). Michel, R. et al. Dose to organ at risk and dose prescription in liver SBRT. Rep Pract Oncol Radiother 22 , 96–102 (2017). Jang, W. I., Jo, S., Moon, J. E., Bae, S. H. & Park, H. C. The Current Evidence of Intensity-Modulated Radiotherapy for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Cancers (Basel) 15 , 4914 (2023). Munoz-Schuffenegger, P., Ng, S. & Dawson, L. A. Radiation-Induced Liver Toxicity. Semin Radiat Oncol 27 , 350–357 (2017). Zhou, Y. J. et al. Radiation-induced liver disease: beyond DNA damage. Cell Cycle 22 , 506–526 (2023). Sage, E. & Shikazono, N. Radiation-induced clustered DNA lesions: Repair and mutagenesis. Free Radic Biol Med 107 , 125–135 (2017). Chatzipapas, K. P. et al. Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations. Cancers (Basel) 12 , 799 (2020). Qin, H., Zhang, H., Zhang, S., Zhu, S. & Wang, H. Protective Effect of Sirt1 against Radiation-Induced Damage. Radiat Res 196 , 647–657 (2021). Ali, O. S. M., Amin, N. E.-D., Abdel Fattah, S. M. & Abd El-Rahman, O. Ameliorative effect of kefir against γ-irradiation induced liver injury in male rats: impact on oxidative stress and inflammation. Environ Sci Pollut Res Int 27 , 35161–35173 (2020). Szatmári, T. et al. Extracellular Vesicles Mediate Radiation-Induced Systemic Bystander Signals in the Bone Marrow and Spleen. Front Immunol 8 , 347 (2017). Christiansen, H. et al. Irradiation leads to susceptibility of hepatocytes to TNF-alpha mediated apoptosis. Radiother Oncol 72 , 291–296 (2004). Huang, X. W. et al. Antisense oligonucleotide inhibition of tumor necrosis factor receptor 1 protects the liver from radiation-induced apoptosis. Clin Cancer Res 12 , 2849–2855 (2006). Jing, Z.-T. et al. AKT activator SC79 protects hepatocytes from TNF-α-mediated apoptosis and alleviates d-Gal/LPS-induced liver injury. Am J Physiol Gastrointest Liver Physiol 316 , G387–G396 (2019). Iracheta-Vellve, A. et al. Interleukin-1 inhibition facilitates recovery from liver injury and promotes regeneration of hepatocytes in alcoholic hepatitis in mice. Liver Int 37 , 968–973 (2017). LoBianco, F. V. et al. The Role of Sirtuin 3 in Radiation-Induced Long-Term Persistent Liver Injury. Antioxidants (Basel) 9 , 409 (2020). Yi, J. et al. Radioprotection of EGCG based on immunoregulatory effect and antioxidant activity against 60Coγ radiation-induced injury in mice. Food Chem Toxicol 135 , 111051 (2020). Du, S.-S. et al. Radiation-induced liver fibrosis is mitigated by gene therapy inhibiting transforming growth factor-β signaling in the rat. Int J Radiat Oncol Biol Phys 78 , 1513–1523 (2010). Dong, Y. et al. Activation of the JNK-c-Jun pathway in response to irradiation facilitates Fas ligand secretion in hepatoma cells and increases hepatocyte injury. J Exp Clin Cancer Res 35 , 114 (2016). Xiao, L. et al. Role of phosphatidylinositol 3-kinase signaling pathway in radiation-induced liver injury. Kaohsiung J Med Sci 36 , 990–997 (2020). Wang, B. et al. METTL3-Mediated STING Upregulation and Activation in Kupffer Cells Contribute to Radiation-Induced Liver Disease via Pyroptosis. Int J Radiat Oncol Biol Phys 119 , 219–233 (2024). Chen, Y. et al. MicroRNA-146a-5p attenuates irradiation-induced and LPS-induced hepatic stellate cell activation and hepatocyte apoptosis through inhibition of TLR4 pathway. Cell Death Dis 9 , 22 (2018). Rodriguez-Ruiz, M. E., Vitale, I., Harrington, K. J., Melero, I. & Galluzzi, L. Immunological impact of cell death signaling driven by radiation on the tumor microenvironment. Nat Immunol 21 , 120–134 (2020). Su, L. et al. Kupffer cell-derived TNF-α promotes hepatocytes to produce CXCL1 and mobilize neutrophils in response to necrotic cells. Cell Death Dis 9 , 323 (2018). Yamaga, S., Aziz, M., Murao, A., Brenner, M. & Wang, P. DAMPs and radiation injury. Front Immunol 15 , 1353990 (2024). Meng, L. et al. METTL14 suppresses pyroptosis and diabetic cardiomyopathy by downregulating TINCR lncRNA. Cell Death Dis 13 , 38 (2022). Chen, Y. et al. N6-methyladenosine-modified TRAF1 promotes sunitinib resistance by regulating apoptosis and angiogenesis in a METTL14-dependent manner in renal cell carcinoma. Mol Cancer 21 , 111 (2022). Liu, J. et al. METTL14 is essential for β-cell survival and insulin secretion. Biochim Biophys Acta Mol Basis Dis 1865 , 2138–2148 (2019). Qian, S., Liu, J., Liao, W. & Wang, F. METTL14 drives growth and metastasis of non-small cell lung cancer by regulating pri-miR-93-5p maturation and TXNIP expression. Genes Genomics 46 , 213–229 (2024). Gao, G. et al. METTL14 promotes apoptosis of spinal cord neurons by inducing EEF1A2 m6A methylation in spinal cord injury. Cell Death Discov 8 , 15 (2022). Li, L., Zeng, J., He, S., Yang, Y. & Wang, C. METTL14 decreases FTH1 mRNA stability via m6A methylation to promote sorafenib-induced ferroptosis of cervical cancer. Cancer Biol Ther 25 , 2349429 (2024). Chen, F., Su, M., Han, D., Wang, Y. & Song, M. METTL14 depletion ameliorates ferroptosis in severe acute pancreatitis by increasing the N6-methyladenosine modification of ACSL4 and STA1. Int Immunopharmacol 128 , 111495 (2024). Liang, J. et al. METTL14 inhibits malignant progression of oral squamous cell carcinoma by targeting the autophagy-related gene RB1CC1 in an m6A-IGF2BP2-dependent manner. Clin Sci (Lond) 137 , 1373–1389 (2023). Hou, X. et al. METTL14 reverses liver fibrosis by inhibiting NOVA2 through an m6A-YTHDF2-dependent mechanism. Hepatol Commun 7 , e0199 (2023). Wang, Y.-F. et al. METTL14 downregulation drives S100A4+ monocyte-derived macrophages via MyD88/NF-κB pathway to promote MAFLD progression. Signal Transduct Target Ther 9 , 91 (2024). Cao, X. et al. Mettl14-Mediated m6A Modification Facilitates Liver Regeneration by Maintaining Endoplasmic Reticulum Homeostasis. Cell Mol Gastroenterol Hepatol 12 , 633–651 (2021). FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations - PubMed. https://pubmed.ncbi.nlm.nih.gov/32219413/. Kanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. & Ishiguro-Watanabe, M. KEGG: biological systems database as a model of the real world. Nucleic Acids Res 53 , D672–D677 (2025). Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 10 , 1523 (2019). Han, H. et al. TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res 46 , D380–D386 (2018). Sticht, C., De La Torre, C., Parveen, A. & Gretz, N. miRWalk: An online resource for prediction of microRNA binding sites. PLoS One 13 , e0206239 (2018). Toesca, D. A. S. et al. Strategies for prediction and mitigation of radiation-induced liver toxicity. J Radiat Res 59 , i40–i49 (2018). Liang, S.-X. et al. Radiation-induced liver disease in three-dimensional conformal radiation therapy for primary liver carcinoma: the risk factors and hepatic radiation tolerance. Int J Radiat Oncol Biol Phys 65 , 426–434 (2006). Ohri, N. et al. Radiotherapy for Hepatocellular Carcinoma: New Indications and Directions for Future Study. J Natl Cancer Inst 108 , djw133 (2016). Cao, Y. & Guo, W. Role of METTL14 in cardiomyocyte pyroptosis in mice with heart failure by regulating miR-221-3p RNA methylation. Int Immunopharmacol 149 , 114172 (2025). Zhuang, S. et al. METTL14 promotes doxorubicin-induced cardiomyocyte ferroptosis by regulating the KCNQ1OT1-miR-7-5p-TFRC axis. Cell Biol Toxicol 39 , 1015–1035 (2023). Kim, H.-G., Jang, S.-S., Lee, J.-S., Kim, H.-S. & Son, C.-G. Panax ginseng Meyer prevents radiation-induced liver injury via modulation of oxidative stress and apoptosis. J Ginseng Res 41 , 159–168 (2017). Gawish, R. A., Samy, E. M. & Aziz, M. M. Ferulic acid protects against gamma-radiation induced liver injury via regulating JAK/STAT/Nrf2 pathways. Arch Biochem Biophys 753 , 109895 (2024). Wang, X. et al. Autophagy suppresses radiation damage by activating PARP-1 and attenuating reactive oxygen species in hepatoma cells. Int J Radiat Biol 95 , 1051–1057 (2019). Cataldi, S. et al. Acid and Neutral Sphingomyelinase Behavior in Radiation-Induced Liver Pyroptosis and in the Protective/Preventive Role of rMnSOD. Int J Mol Sci 21 , 3281 (2020). Wu, D. et al. Identification of HMOX1 as a Critical Ferroptosis-Related Gene in Atherosclerosis. Front Cardiovasc Med 9 , 833642 (2022). Lin, H. et al. EF24 induces ferroptosis in osteosarcoma cells through HMOX1. Biomed Pharmacother 136 , 111202 (2021). Long, X., Yang, Y. & Zhou, K. Sepsis induces the cardiomyocyte apoptosis and cardiac dysfunction through activation of YAP1/Serpine1/caspase-3 pathway. Open Med (Wars) 19 , 20241018 (2024). Pavón, M. A. et al. Enhanced cell migration and apoptosis resistance may underlie the association between high SERPINE1 expression and poor outcome in head and neck carcinoma patients. Oncotarget 6 , 29016–29033 (2015). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8087326","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":610463339,"identity":"89c79d84-4a75-4ec0-9191-27135632df06","order_by":0,"name":"Sijian Liu","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Sijian","middleName":"","lastName":"Liu","suffix":""},{"id":610463340,"identity":"7d801cc5-9f89-4e62-8a8c-fefd485c0f2c","order_by":1,"name":"Li Qu","email":"","orcid":"","institution":"No.924 Hospital of PLA Joint Logistic Support Force","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Qu","suffix":""},{"id":610463341,"identity":"0c05f690-c688-4419-8148-665cb7459961","order_by":2,"name":"Jiayi Wu","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Jiayi","middleName":"","lastName":"Wu","suffix":""},{"id":610463342,"identity":"f7061d57-b873-4053-8b04-ead7c886e731","order_by":3,"name":"Huazhong Wang","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Huazhong","middleName":"","lastName":"Wang","suffix":""},{"id":610463343,"identity":"f7296f33-db5b-4d29-9eea-c8df9cdb00ba","order_by":4,"name":"Kewei Tan","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Kewei","middleName":"","lastName":"Tan","suffix":""},{"id":610463344,"identity":"c5fd211f-7bd8-446c-88c7-7789f5e89692","order_by":5,"name":"Jiang Yu","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Jiang","middleName":"","lastName":"Yu","suffix":""},{"id":610463345,"identity":"51914352-f4f4-48c3-94e3-81c493a796ab","order_by":6,"name":"Yuzhen He","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Yuzhen","middleName":"","lastName":"He","suffix":""},{"id":610463346,"identity":"6ab36c36-08f3-4880-a916-db48f2ec1536","order_by":7,"name":"Yiteng Ding","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Yiteng","middleName":"","lastName":"Ding","suffix":""},{"id":610463347,"identity":"0bb77db1-75a5-4479-91c2-bae1f398c5f0","order_by":8,"name":"Huangui Zhang","email":"","orcid":"","institution":"No.922 Hospital OF PLA Joint Logistics Support Force","correspondingAuthor":false,"prefix":"","firstName":"Huangui","middleName":"","lastName":"Zhang","suffix":""},{"id":610463348,"identity":"23bf0673-b123-455a-aefb-d5dad5928bf9","order_by":9,"name":"Wenjun Yin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACgwNAzMBwmIeBmfngg4QKCTl54rWwsyUbPDhjYWzYQIQWIEhjYODnMZN82FaRyHCAkJbjvQeKeXfYyJgz8xgbJM6TSGBsYH746AYeLWZnziUY856R4LFsZit8kLhNIo+dgc3YOAeflhs5Bsa8bRI8BoeZNxsAtRQzNvCwSePVcv8NTAuDmUTiHInEhgMEtNjf4IFpYQFqaSBCi+WZHAPDuWAtwEBOOCZhbNhMwC8Gx8+YGbxtk7A3OH/44MMfNXVy8uzNDx/j0wIEbAaofGb8ysFKHhBWMwpGwSgYBSMaAADVKkpkQjj4egAAAABJRU5ErkJggg==","orcid":"","institution":"The Affiliated Changsha Central Hospital, University of South China","correspondingAuthor":true,"prefix":"","firstName":"Wenjun","middleName":"","lastName":"Yin","suffix":""}],"badges":[],"createdAt":"2025-11-11 13:23:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8087326/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8087326/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105564574,"identity":"e124a045-c030-4f46-ab0c-9ef1c80e917e","added_by":"auto","created_at":"2026-03-27 12:50:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1384272,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMETTL14 expression is downregulated by radiation:\u003c/strong\u003e(A) Western blot analysis shows the protein expression levels of METTL14 and GAPDH in the control group (C) and the treatment group (F). (B) The bar graph illustrates the relative expression levels of METTL14 protein normalized to GAPDH\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/cdc0a8f82b27be9f4d9cc27b.png"},{"id":105286468,"identity":"ce9f325d-967c-49ff-bcdf-9feda37bba9e","added_by":"auto","created_at":"2026-03-24 11:20:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":667560,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDevelop a transgenic mouse model with METTL14 overexpression:\u003c/strong\u003e (A) Western blot analysis shows the protein expression levels of METTL14 and GAPDH in the overexpression group、control group (C) and the treatment group (F). (B) The bar graph illustrates the relative expression levels of METTL14 protein normalized to GAPDH\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/2183a5f06de905ca638eb0f1.png"},{"id":105286474,"identity":"52d8fbff-660f-4b06-aadb-8700c9fb8684","added_by":"auto","created_at":"2026-03-24 11:20:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":7940557,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMETTL14 overexpression significantly attenuated radiation-induced hepatocyte death:\u003c/strong\u003e (A) Transmission electron microscopy shows the hepatocytes levels of METTL14 in the overexpression group、control group (C) and the treatment group (F).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/9a3060f15871ebfa84730fa3.png"},{"id":105564747,"identity":"c666cc61-c749-4156-86b4-6f620895dc83","added_by":"auto","created_at":"2026-03-27 12:50:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1079712,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTranscriptomic overview.:\u003c/strong\u003e (A). PCA principal component analysis demonstrating the distribution of the seven samples. (B) Volcano plot demonstrating the differential genes of OE and NC.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/f0ce4e4c18cac70849dcd8fe.png"},{"id":105564761,"identity":"cec1efd4-65be-49d0-b149-c6cd34e6cab6","added_by":"auto","created_at":"2026-03-27 12:50:47","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1276370,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalyzing the intersecting genes of differential genes with various cell death related genes: \u003c/strong\u003e(A) upset plot showing the intersection of differential genes with cell death genes. (B) pie chart showing the distribution of intersecting genes.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/32b419ec52d4d32ae736dc7c.png"},{"id":105286471,"identity":"6e7c7ab1-83b2-45ac-832e-1d7262df1a24","added_by":"auto","created_at":"2026-03-24 11:20:03","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":939675,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional enrichment analysis of cell detah-related DEGs:\u003c/strong\u003e (A). Lollipop diagram showing differential gene functional enrichment.BP-biological process, CC-cellular component, MF-molecular function, KEGG-pathway enrichment\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/244eb6dc73142a7cb65bf2ec.png"},{"id":105564400,"identity":"c0045240-be6a-473c-a210-3ea72d5020f9","added_by":"auto","created_at":"2026-03-27 12:49:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":959033,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConstructing a differential gene PPI network to screen for core cell detah-related DEG:\u003c/strong\u003e(A) Cytoscape visualization of the PPI network highlighting ten hub genes (orange) identified by CytoHubba.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/d7889e9f581a07b4012beac0.png"},{"id":105286477,"identity":"97092f85-ed7c-483c-8df0-df4fb1204358","added_by":"auto","created_at":"2026-03-24 11:20:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":6176175,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional enrichment of ten hub gene\u003c/strong\u003es: (A) The bar chart illustrates the functional enrichment of ten hub genes .(B) The network diagram depicts the functional enrichment of ten hub genes.(C) The P-values for the network diagram.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/b4ed0c83f3292f43f22ee652.png"},{"id":105286478,"identity":"275bdcc2-9dc2-4cca-ace6-0527d1219d65","added_by":"auto","created_at":"2026-03-24 11:20:04","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":24458071,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eValidation of ten hub genes with experiments:\u003c/strong\u003e (A) qRT-PCR was used to quantify the mRNA levels of HMOX1, AGT, MMP9, SERPINE1, SOD1, CXCL12, CAV1, SQSTM1, IL18, and CASP3 in hepatocytes. (B) Western blot was performed to determine the protein expression levels of HMOX1, AGT, SERPINE1, and MMP9 in hepatocytes. (C) The bar graph illustrates the relative expression levels of HMOX1, AGT, SERPINE1, and MMP9 protein normalized to GAPDH\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/24fb04277fd534e2e19e7e6f.png"},{"id":105565388,"identity":"8f656b14-079a-40c4-a05a-a03936dfa70b","added_by":"auto","created_at":"2026-03-27 12:53:06","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":543912,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated TF–mRNA–miRNA regulatory network:\u003c/strong\u003e (A) Cytoscape map showing interactions among transcription factors (orange), hub genes (red) and hsa-miR-145-5p (green).\u003c/p\u003e","description":"","filename":"Figure10.png","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/f2b455b4b4b002808c6b2df1.png"},{"id":105569752,"identity":"ffdb48b1-97a0-4bd1-a4d8-6d1fd7d52620","added_by":"auto","created_at":"2026-03-27 13:13:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":37749124,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/3235f25c-4490-44a1-8c18-f496149cba2f.pdf"},{"id":105286476,"identity":"a1205708-003b-4b9b-a2bc-ec28d28fa6bc","added_by":"auto","created_at":"2026-03-24 11:20:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3171468,"visible":true,"origin":"","legend":"","description":"","filename":"wb.docx","url":"https://assets-eu.researchsquare.com/files/rs-8087326/v1/f94a89b57861b01eae574a50.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The identification of genes related to METTL14 inhibition in radiation- induced hepatocyte death based on bioinformatics analysis","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cp\u003eRadio-induced liver injury (RILD) is a common complication in the radiotherapy of liver cancer. The incidence of RILD varies due to factors such as radiotherapy techniques, dose fractionation, and patient-specific differences\u003csup\u003e1\u003c/sup\u003e. Approximately 66% of liver cancer patients undergoing 30-35 Gy liver radiation therapy exhibit significant RILD\u003csup\u003e2\u003c/sup\u003e, typically manifesting 2 weeks to 4 months post-treatment\u003csup\u003e3,4\u003c/sup\u003e. Advances in radiation technologies like intensity-modulated radiotherapy (IMRT) and stereotactic body radiotherapy (SBRT) have reduced RILD rates, but it remains a concern\u003csup\u003e5,6\u003c/sup\u003e . RILD not only limits the escalation of radiation doses, affecting treatment efficacy, but also leads to severe symptoms like liver dysfunction, abdominal pain, and ascites, potentially threatening patient lives\u003csup\u003e7\u003c/sup\u003e. This condition prolongs hospital stays, increases medical costs, and may necessitate adjustments to subsequent treatment plans, impacting overall treatment outcomes and quality of life. Recent research has focused on identifying predictive markers for personalized radiotherapy planning and exploring new prevention and treatment strategies, although effective clinical methods are still lacking.\u003c/p\u003e\n\u003cp\u003eThe pathogenesis of RILD involves direct damage, inflammatory response activation, oxidative stress, and cytokine and signaling pathway abnormalities. Direct damage occurs as high-energy ionizing radiation impacts critical cellular structures like DNA, cell membranes, and organelles, leading to DNA double-strand breaks, altered membrane permeability, and organelle dysfunction\u003csup\u003e8\u0026ndash;11\u003c/sup\u003e. This triggers cellular stress responses, affecting metabolism and function, and can result in cell death or dysfunction. Radiation-induced hepatocyte damage triggers inflammatory responses\u003csup\u003e12\u003c/sup\u003e, releasing inflammatory mediators like TNF-\u0026alpha;, IL-1, and IL-6\u003csup\u003e13\u0026ndash;15\u003c/sup\u003e, which recruit immune cells to the site of injury, exacerbating inflammation. Persistent inflammation disrupts the liver microenvironment, affecting hepatocyte function and regeneration\u003csup\u003e16,17\u003c/sup\u003e. Additionally, radiation increases reactive oxygen species (ROS) production in hepatocytes\u003csup\u003e18\u003c/sup\u003e, leading to oxidative stress and damage to cellular components. The antioxidant defense system may be overwhelmed post-irradiation, disrupting redox balance and\u0026nbsp;exacerbating liver cell damage\u003csup\u003e19\u003c/sup\u003e. Abnormalities in cytokines and signaling pathways, such as TGF-\u0026beta;\u0026nbsp;and JAK-STAT pathways, also contribute to RILD pathogenesis\u003csup\u003e20\u0026ndash;22\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eCell death plays a crucial role in RILD, affecting liver tissue structure and function. Various forms of cell death, including apoptosis, disulfidptosis, pyroptosis, and ferroptosis, are involved in RILD, influencing its progression. For instance, METTL3-mediated STING activation in Kupffer cells triggers pyroptosis, contributing to radiation-induced liver disease\u003csup\u003e23\u003c/sup\u003e. MicroRNA-146a-5p can mitigate radiation-induced hepatocyte apoptosis by inhibiting the TLR4 pathway\u003csup\u003e24\u003c/sup\u003e . Ionizing radiation induces DNA damage and various forms of cell death, releasing damage-associated molecular patterns (DAMPs)\u003csup\u003e25\u003c/sup\u003e, which interact with pattern recognition receptors to trigger inflammation. This process activates immune cells like Kupffer cells, leading to the release of inflammatory cytokines and the recruitment of immune cells, exacerbating radiation-induced liver injury\u003csup\u003e26,27\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eMETTL14, a methyltransferase involved in RNA N6-methyladenosine (m6A) modification, is closely associated with cell death under various physiological and pathological conditions\u003csup\u003e28\u0026ndash;30\u003c/sup\u003e. In apoptosis, METTL14 can either inhibit or promote cell death depending on the cellular context. For example, it can promote the expression of anti-apoptotic genes or inhibit pro-apoptotic genes in non-small cell lung cancer cells\u003csup\u003e31\u003c/sup\u003e. In contrast, under oxidative or endoplasmic reticulum stress, METTL14 can promote apoptosis\u003csup\u003e32\u003c/sup\u003e. In ferroptosis, METTL14 regulates genes related to iron metabolism and lipid peroxidation, affecting intracellular iron levels and lipid metabolism\u003csup\u003e33,34\u003c/sup\u003e. METTL14 also participates in pyroptosis and autophagy, showing its complex role in cell death regulation\u003csup\u003e28,35\u003c/sup\u003e. Its involvement in multiple cell death pathways highlights its potential clinical significance in disease diagnosis, treatment, and prognosis.\u003c/p\u003e\n\u003cp\u003eCurrent understanding of RILD pathogenesis is limited, focusing mainly on cell damage, inflammation, and fibrosis\u003csup\u003e2\u003c/sup\u003e. However, these mechanisms do not fully explain the complexity of RILD development. As a core component of the m6A methylation transferase complex, METTL14 plays a broad regulatory role in cellular processes. Its potential role in RILD could reveal new molecular regulatory networks and cellular mechanisms, offering new insights into the disease. Radiation-induced DNA damage in hepatocytes alters mRNA levels and stability, leading to cell injury and death\u003csup\u003e8\u003c/sup\u003e. METTL14, by modifying mRNA stability, could influence the impact of radiation on hepatocytes. It might modify mRNA of anti-apoptotic genes to promote cell survival or reduce expression of ferroptosis genes to inhibit cell death, affecting RILD progression. Given its role in liver diseases and regeneration\u003csup\u003e36\u0026ndash;38\u003c/sup\u003e, studying METTL14 in RILD could lead to novel diagnostic and therapeutic strategies, potentially improving patient outcomes.\u003c/p\u003e"},{"header":"2 MATERIALS AND METHODS","content":"\u003cp\u003e2.1 Data Collection and Acquisition \u003c/p\u003e\n\u003cp\u003eCell death-related genes are from the ferroptosis-related database (FerrDB) (http://www.zhounan.org/ferrdb/current/)\u003csup\u003e39\u003c/sup\u003e、autophagy-related database (Human Autophagy Database) (https://autophagy.lu/v1/)、MSigDB database(Molecular Signatures Database)(https://www.gsea-msigdb.org/gsea/msigdb/index.jsp).\u003c/p\u003e\n\u003cp\u003e2.2 Experimental Animals\u003c/p\u003e\n\u003cp\u003eMale C57BL/6J mice (8–10 weeks old, SPF grade) were purchased from Changsha Tianqin Biotechnology Co., Ltd. (Hunan, China). On the day of allocation (before randomization), body weight averaged 21.5 ± 2.1 g and did not differ among groups. As expected in the RILI model, irradiated animals lost significantly more weight than controls during the study.\u003c/p\u003e\n\u003cp\u003eAt experiment termination, mice were deeply anaesthetised with sodium pentobarbital (150 mg/kg.). Loss of the toe-pinch reflex was followed immediately by cervical dislocation to ensure death. This two-step protocol complies with the AVMA Guidelines for the Euthanasia of Animals (2020) and was approved by the Medical Ethics Committee of the First Affiliated Hospital, University of South China. \u003c/p\u003e\n\u003cp\u003e2.3 Electron Microscopy\u003c/p\u003e\n\u003cp\u003eFor the preparation of liver tissue samples for electron microscopy (EM), freshly isolated tissues were trimmed into 1×2 mm³ blocks and immediately fixed using a two-step process involving 3% glutaraldehyde in 0.1 M phosphate-buffered saline (PBS) at 4°C for 24 hours, followed by 1% osmium tetroxide at 4°C for 2 hours. The samples were then subjected to a graded acetone dehydration series (30% to 100%), infiltrated with Epon812 resin, and embedded. Ultrathin sections, approximately 60-90 nm thick, were cut using a diamond knife, collected on 200-mesh copper grids, and stained with uranyl acetate and lead citrate to enhance contrast. The stained sections were examined using a JEM-1400FLASH transmission electron microscope (JEOL, Japan) at 80 kV, and images were captured with a Gatan digital camera. This detailed procedure allowed for a comprehensive examination of the liver tissue ultrastructure post-irradiation, providing insights into the cellular changes induced by radiation.\u003c/p\u003e\n\u003cp\u003e2.4 Transcriptome Sequencing\u003c/p\u003e\n\u003cp\u003eTranscriptome analysis was performed using the Illumina high-throughput sequencing platform. Total RNA was extracted and assessed for quality. mRNA was enriched using oligo(dT) magnetic beads for eukaryotic RNA or an RNA removal kit for degraded or prokaryotic RNA. Library construction involved RNA fragmentation, first-strand cDNA synthesis, second-strand cDNA synthesis, end repair, A-tailing, adapter ligation, and PCR amplification. Library quality was verified using an Agilent 2100 bioanalyzer and qPCR.\u003c/p\u003e\n\u003cp\u003e2.5 Quantitative Real-Time PCR (qRT-PCR)\u003c/p\u003e\n\u003cp\u003eFor the analysis of gene expression, total RNA was extracted from mouse liver tissues using Trizol reagent, following the manufacturer's protocol. The quality and concentration of RNA were assessed using a NanoDrop spectrophotometer and agarose gel electrophoresis. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using a reverse transcription kit, with oligo(dT) primers and M-MLV reverse transcriptase. The cDNA was then diluted and used as a template for quantitative real-time PCR (qRT-PCR). qRT-PCR was performed using a TB Green Master Mix in a total reaction volume of 20 μL, which included 10 μL of TB Green Master Mix, 0.4 μL each of forward and reverse primers (10 μM), and 2 μL of cDNA template. The thermal cycling conditions were as follows: an initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 5 seconds, and annealing/extension at 60°C for 20 seconds. The relative expression levels of the target genes were normalized to the housekeeping gene GAPDH using the 2^-ΔΔCt method. Each sample was run in triplicate, and the mean values were used for analysis. \u003c/p\u003e\n\u003cp\u003e2.6 Western Blot Analysis\u003c/p\u003e\n\u003cp\u003eProtein extraction from liver tissues was carried out using RIPA lysis buffer supplemented with protease and phosphatase inhibitors. The protein concentration was determined using the BCA protein assay kit, and equal amounts of protein (30 μg) were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). After electrophoresis, the proteins were transferred onto polyvinylidene fluoride (PVDF) membranes. The membranes were then blocked with 5% non-fat milk in Tris-buffered saline containing 0.1% Tween-20 (TBST) for 1 hour at room temperature. Subsequently, the membranes were incubated with primary antibodies specific to the target proteins overnight at 4°C. After washing with TBST, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies for 1 hour at room temperature. The protein bands were visualized using an enhanced chemiluminescence (ECL) detection system. The intensity of the bands was quantified using ImageJ software, and the results were normalized to the internal control β-actin.\u003c/p\u003e\n\u003cp\u003eAll experimental protocols involving animals were approved by the Medical Ethics Committee of the First Affiliated Hospital of University of South China. All methods were carried out in accordance with relevant guidelines and regulations and are reported in accordance with ARRIVE guidelines. Euthanasia was performed by cervical dislocation under anesthesia.\u003c/p\u003e\n\u003cp\u003e2.7 Identification of DEGs Related to cell death\u003c/p\u003e\n\u003cp\u003eThe RNA sequencing data underwent differential expression analysis using the R package limma (version 3.40.6). Significantly differentially expressed genes between OE and NC were identified based on a P value \u0026lt; 0.05 and |log(fold change)| ≥ 1.2 criteria. Subsequently, using the Venn map network tool (http://bioinformatics.psb.ugent.be/webtools/Venn/), the overlap between the DEGs of RNA-seq and 1093 cell death- related genes was examined. They are cell death- related genes that may participate in the radiation-induced hepatocyte death.\u003c/p\u003e\n\u003cp\u003e2.8 Enrichment analyses\u003c/p\u003e\n\u003cp\u003eThe selected DEGs and hub genes were analyzed for GO and KEGG enrichment\u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eanalysis using R and metascape (https://metascape.org/gp/index.html#/main/step1)\u003csup\u003e41\u003c/sup\u003e. GO has three levels of analysis: molecular function (MF), cellular component (CC), and biological process (BP). A widespread database used to investigate illnesses,chemicals, medications,biological processes, and genomes is called KEGG. When DEG met p \u0026lt; 0.05 and count ≥ 10 in the above two analyses, it had statistical significance in this study. KEGG pathway analysis was performed using the KEGG database (Kanehisa Laboratories) with appropriate permissions obtained.Weshengxin (http://www.bioinformatics.com.cn,), a free online application for data processing and visualization, was used to create the bubble diagram\u003c/p\u003e\n\u003cp\u003e2.9 PPI Network Construction and Hub Gene Screening \u003c/p\u003e\n\u003cp\u003eBuild a protein-protein interaction (PPI) network using the free, open-source STRING database (https://string-db.org/). To assess PPI, import the filtered DEGs into the STRING database. Create a visual network of PPIs using the Cytoscape program (https://cytoscape.org), then use Cytohubba to scan hub genes. \u003c/p\u003e\n\u003cp\u003e2.10 Construction of TF-mRNA-miRNA Network\u003c/p\u003e\n\u003cp\u003eTRRUST(http://www.grnpedia.org/trrust)\u003csup\u003e42\u003c/sup\u003e created interaction networks between genes-miRNAs genes-transcription factors. miRWalk(http://mirwalk.umm.uni-heidelberg.de/)\u003csup\u003e43\u003c/sup\u003e created interaction networks between genes-miRNAs. All networks were visualized using Cytoscape software. \u003c/p\u003e\n\u003cp\u003e2.11 Statistical Analysis\u003c/p\u003e\n\u003cp\u003eData analysis was performed using GraphPad Prism 8.0.2 for visualization and basic analysis, and SPSS 27.0 for advanced statistical analysis. Mann-Whitney U test was used for comparisons between two groups, and Kruskal-Wallis H test for multiple groups (N≥3). ImageJ 1.53 was used for image quantification, and Image Lab 6.1 for Western blot band analysis. Photoshop 2022 was used for image optimization and layout. Data are presented as mean ± SD, and statistical significance was marked as *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001.\u003c/p\u003e"},{"header":"3 RESULTS","content":"\u003cp\u003e3.1 METTL14 expression is downregulated by radiation\u003c/p\u003e\n\u003cp\u003eTo verify the inhibitory effect of radiation on METTL14 expression in mouse liver, we performed Western blot analysis. The Western blot results demonstrated a significant downregulation of METTL14 protein expression in liver tissues of irradiated mice compared to the control group (Figure 1A-B). These results confirm that radiation effectively suppresses METTL14 expression in murine hepatic tissues.\u003c/p\u003e\n\u003cp\u003e3.2 Develop a transgenic mouse model with METTL14 overexpression\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo investigate METTL14's role in radiation-induced hepatocyte injury, we generated a METTL14-overexpressing model. Western blot analysis demonstrated significantly elevated METTL14 protein expression in hepatocytes of OE-group mice versus C and NC controls (Figure 2A-B), confirming that the METTL14-overexpressing adeno-associated virus (AAV) successfully mediated hepatic METTL14 overexpression.\u003c/p\u003e\n\u003cp\u003e3.3 METTL14\u0026nbsp;overexpression significantly attenuated radiation-induced hepatocyte death\u003c/p\u003e\n\u003cp\u003eTo investigate the role of METTL14 in radiation-induced hepatocyte injury, we examined the effect of METTL14 overexpression on radiation-perturbed ultrastructure in hepatocytes using transmission electron microscopy (TEM). TEM analysis revealed that compared to the Control group, hepatocytes in the Negative Control (NC) group exhibited marked radiation-induced damage characterized by mitochondrial swelling, aberrant accumulation of lipid droplets, and plasma membrane rupture. In contrast, the OE group showed significantly alleviated ultrastructural damage relative to the NC group (Figure 3A). These results collectively demonstrate that METTL14 overexpression effectively mitigates radiation-induced ultrastructural injury in hepatocytes, conferring cytoprotective effects.\u003c/p\u003e\n\u003cp\u003e3.4 mRNA sequencing of the negative control (NC) and METTL14 overexpression group (OE) after radiation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe therefore conclude that METTL14-mediated protection against radiation-induced hepatocyte injury operates primarily through the modulation of apoptosis-related genes.We sent three treated NC tissue samples and four tissue samples overexpressing METT14 for RNA sequencing, whose PCA analysis showed PC1(53.27%) and PC2(46.22%)\u0026nbsp;(Figure 4A), followed by differential analysis, which showed that there were a total of 964 genes that were differentiated, of which 388 genes were up-regulated and 576 genes were down-regulated (Figure 4B).\u003c/p\u003e\n\u003cp\u003e3.5 Cell death-Related DEGs in METTL14 inhibition in radiation-induced hepatocyte death\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo determine the dominant mode of regulated cell death when METTL14 is over-expressed after irradiation, we intersected the 964 DEGs with curated cell-death gene sets. shows that 77 genes overlapped, with 61.04 % linked to apoptosis, 16.88 % to autophagy, 15.58 % to ferroptosis, 3.9 % to cuproptosis and 2.6 % to pyroptosis (Figure 5A-B).This distribution indicates that apoptosis is the most prominently represented death pathway.\u003c/p\u003e\n\u003cp\u003e3.6 GO and KEGG of cell detah-related DEGs.\u003c/p\u003e\n\u003cp\u003eTo elucidate the molecular mechanisms by which METTL14 mitigates radiation-induced hepatocyte injury, we performed GO and KEGG enrichment analyses on the 77 apoptosis-dominant intersecting DEGs. the results showed that BP was mainly focused on apoptosis regulation, KEGG was mainly focused on ferroptosis (Figure 6A)\u003c/p\u003e\n\u003cp\u003eThese enrichment patterns indicate that METTL14 orchestrates a multi-layered response centered on apoptosis modulation and lipid-related ferroptosis pathways.\u003cbr\u003e\u0026nbsp;Collectively, we conclude that METTL14 alleviates radiation-induced hepatocyte damage by simultaneously regulating apoptosis and ferroptosis-related gene networks.\u003c/p\u003e\n\u003cp\u003e3.7 Constructing a differential gene PPI network to screen for core cell detah-related DEGs\u003c/p\u003e\n\u003cp\u003eTo pinpoint the downstream effectors through which METTL14 alleviates radiation-induced hepatocyte injury, we constructed a PPI network from the 77 core cell detah-related DEGs. The network diagram was constructed with Cytoscape software. After that, Cytohubba was used to continue the screening procedure for hub genes. According to the degree ranking, CytoHubba identified ten hub genes: HMOX1, AGT, MMP9, SERPINE1, SOD1, CXCL12, CAV1, SQSTM1, IL18 and CASP3 (Figure 7A).These hub genes are centrally positioned within the network, suggesting they mediate METTL14-driven cytoprotection.\u003c/p\u003e\n\u003cp\u003e3.8 Functional enrichment of ten hub genes\u003c/p\u003e\n\u003cp\u003eTo delineate the functional landscape of the ten hub genes, we subjected them to GO and KEGG enrichment analyses. Result shows highly significant enrichment in regulation of apoptotic signaling pathway, positive/negative regulation of apoptotic process,and related ROS- and inflammation-linked terms, with apoptotic pathways dominating both GO and KEGG outputs.This concentrated enrichment indicates that the core gene set acts primarily within apoptosis-regulatory networks(Figure 8A-C).We therefore conclude that these hub genes execute their protective roles in radiation-induced hepatocyte injury by modulating apoptosis-related signaling cascades, providing a focused molecular framework for further mechanistic studies.\u003c/p\u003e\n\u003cp\u003e3.9 Validation of ten hub genes with experiments\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo experimentally verify the ten hub genes identified by RNA-seq, we make qRT-PCR and western blot analysis. qRT-PCR performed that HMOX1, AGT, SERPINE1 and MMP9 mRNA levels reproduced the RNA sequencing (Figure 9A).Western blot analysis of the same liver lysates revealed that only HMOX1 and SERPINE1 proteins were significantly up-regulated in the OE group, in line with their mRNA profiles (Figure 9B-C).We therefore designate HMOX1 and SERPINE1 as METTL14-regulated, radiation-responsive effectors that merit functional follow-up.\u003c/p\u003e\n\u003cp\u003e3.10\u0026nbsp;Constructing a HMOX1 and SERPINE1 gene TF-mRNA-miRNA network\u003c/p\u003e\n\u003cp\u003eTo dissect the upstream and downstream regulatory circuitry of the HMOX1 and SERPINE1, we integrated transcription-factor (TF) binding and miRNA targeting data to construct a TF-mRNA-miRNA interaction network.The result positioned hsa-miR-145-5p as the most recurrent downstream miRNA and revealed 33 distinct TFs potentially governing the ten hub genes (Figure 10A).These findings indicate that a TF- SERPINE1- miR-145-5p axis may orchestrate the transcriptional and post-transcriptional control of apoptosis downstream of METTL14.\u003c/p\u003e"},{"header":"4 DISCUSSION ","content":"\u003cp\u003eRadiotherapy plays a pivotal role in the treatment of various cancers, including liver cancer. However, the risk of RILD poses significant challenges when applying radiotherapy to hepatocellular carcinoma (HCC). This complication not only limits the therapeutic potential of radiotherapy in HCC but also leads to severe clinical issues such as liver dysfunction, jaundice, ascites, liver failure, and gastrointestinal bleeding, potentially resulting in hemorrhagic shock or even death\u003csup\u003e3\u003c/sup\u003e. Despite advancements in precision radiotherapy techniques like stereotactic body radiotherapy (SBRT), which delivers high doses of radiation in limited fractions\u003csup\u003e44\u003c/sup\u003e, the acute and long-term adverse reactions in normal liver tissue remain a formidable obstacle. Clinically, RILD is categorized into classic fibrotic and non-classic acute types, with studies showing an increasing incidence of the latter despite the use of image-guided techniques and advanced dose planning\u003csup\u003e45,46\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMETTL14, an m6A methylation enzyme, is implicated in numerous molecular functions, including apoptosis\u003csup\u003e32\u003c/sup\u003e, pyroptosis\u003csup\u003e47\u003c/sup\u003e, and ferroptosis\u003csup\u003e48\u003c/sup\u003e, which are closely linked to the development of RILD\u003csup\u003e25\u003c/sup\u003e. Our study indicates a decrease in METTL14 levels in mouse hepatocytes post-irradiation. By establishing a METTL14 overexpression mouse model, we observed an improvement in radiation-induced hepatocyte damage. Functional enrichment analysis of differentially expressed genes following METTL14 overexpression revealed a significant enrichment in apoptosis pathways, suggesting that METTL14 may ameliorate radiation-induced hepatocyte damage by regulating apoptosis.\u003c/p\u003e\n\u003cp\u003eIonizing radiation induces various forms of cell death in hepatocytes, including apoptosis\u003csup\u003e49\u003c/sup\u003e, ferroptosis\u003csup\u003e50\u003c/sup\u003e, autophagy\u003csup\u003e51\u003c/sup\u003e, and pyroptosis\u003csup\u003e52\u003c/sup\u003e. Our bioinformatics analysis identified intersection genes related to METTL14 and cell death, which are closely associated with apoptosis, autophagy, and ferroptosis. Using STRING tools to construct a protein-protein interaction (PPI) network, we identified 10 core differential genes enriched in apoptosis pathways. This suggests that apoptosis is likely a key mechanism by which METTL14 improves radiation-induced hepatocyte damage.\u003c/p\u003e\n\u003cp\u003eThe interaction between radiation and hepatocytes is complex, involving multiple layers and mechanisms. The dominant type of cell death in radiation-induced hepatocyte injury varies across studies due to various factors, including experimental conditions (temperature, humidity, gas composition), study design (sample selection, grouping, observation indicators), and the type and dose of radiation (X-rays,\u0026nbsp;\u0026gamma;-rays, UV). Different radiation types have distinct energy characteristics and penetration abilities, influencing the degree and manner of hepatocyte damage and the dominant type of cell death. Research in this area is ongoing, with efforts to improve experimental techniques and designs to better understand the complex biological processes underlying radiation effects on hepatocytes.\u003c/p\u003e\n\u003cp\u003eOur study identified two key genes, HMOX1 and SERPINE1, which are involved in the protective role of METTL14 against radiation-induced hepatocyte damage. HMOX1, a marker of ferroptosis, is closely related to iron metabolism and cellular stress responses\u003csup\u003e53,54\u003c/sup\u003e. SERPINE1, associated with apoptosis\u003csup\u003e55,56\u003c/sup\u003e, was found to be significantly altered in our study, suggesting its role in METTL14-mediated protection against radiation-induced hepatocyte damage. Further exploration of these genes and their mechanisms could provide insights into radiation-induced hepatocyte injury and potential therapeutic targets.\u003c/p\u003e\n\u003cp\u003eThis study reveals the protective role of METTL14 in radiation-induced hepatocyte damage and explores its mechanisms, including the regulation of HMOX1-mediated ferroptosis and SERPINE1-mediated apoptosis. These findings are significant for understanding the complex regulatory networks of radiation-induced liver injury and could lead to the development of novel therapeutic strategies. Future research should focus on the molecular interactions between METTL14 and these target genes and translate these findings into clinical applications through rigorous clinical trials.\u003c/p\u003e"},{"header":"5 CONCLUSION","content":"\u003cp\u003eThis study provides preliminary evidence that METTL14 overexpression ameliorates radiation-induced hepatocyte damage, potentially through the regulation of apoptosis. We demonstrate that hepatic METTL14 expression is acutely suppressed after irradiation and that restoration of METTL14 via AAV-mediated gene transfer markedly attenuates radiation-induced hepatocyte death. Integrated transcriptomic and network analyses converge on apoptosis and ferroptosis as the dominant pathways, with HMOX1 and SERPINE1 emerging as METTL14-regulated effector molecules. These findings not only extend the known functions of m6A modification to radiation biology but also nominate METTL14, HMOX1 and SERPINE1 as tractable therapeutic targets for mitigating RILD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePermission to use KEGG pathway images has been obtained from Kanehisa Laboratories via the copyright request form (www.kegg.jp/feedback/copyright.html). KEGG pathway maps were generated using the KEGG database (Kanehisa Laboratories) and are cited in accordance with their guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (grant number: 8210121825) and Foundation of of No. 922 PLA Hospital (grant number: 2025YJ01) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available in the arrayexpress (EMTAB-16163) repository .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSijian Liu: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Li Qu: Conceptualization, Funding acquisition, Data curation, Investigation, Methodology, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Jiayi Wu: Investigation, Formal analysis, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Huazhong Wang: Investigation, Resources, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Kewei Tan: Data curation, Software, Visualization, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003e\u0026nbsp;Jiang Yu: Investigation, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eYuzhen He: Investigation, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003eYiteng Ding: Investigation, Resources, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003eHuangui Zhang: Investigation, Formal analysis, Writing \u0026ndash; review \u0026amp; editing.\u003cbr\u003eWenjun Yin: Conceptualization, Funding acquisition, Project administration, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Medical Ethics Committee of the First Affiliated Hospital of University of South China. All methods were carried out in accordance with relevant guidelines and regulations and are reported in accordance with ARRIVE guidelines. Euthanasia was performed by cervical dislocation under anesthesia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or fnancial relationships that could be construed as a potential confict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have provided their consent for publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBurgio, E., Piscitelli, P. \u0026amp; Migliore, L. Ionizing Radiation and Human Health: Reviewing Models of Exposure and Mechanisms of Cellular Damage. An Epigenetic Perspective. \u003cem\u003eInt J Environ Res Public Health\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1971 (2018).\u003c/li\u003e\n\u003cli\u003eKim, J. \u0026amp; Jung, Y. Radiation-induced liver disease: current understanding and future perspectives. \u003cem\u003eExp Mol Med\u003c/em\u003e \u003cstrong\u003e49\u003c/strong\u003e, e359 (2017).\u003c/li\u003e\n\u003cli\u003eBenson, R., Madan, R., Kilambi, R. \u0026amp; Chander, S. Radiation induced liver disease: A clinical update. \u003cem\u003eJ Egypt Natl Canc Inst\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 7\u0026ndash;11 (2016).\u003c/li\u003e\n\u003cli\u003eKoay, E. J., Owen, D. \u0026amp; Das, P. Radiation-Induced Liver Disease and Modern Radiotherapy. \u003cem\u003eSemin Radiat Oncol\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 321\u0026ndash;331 (2018).\u003c/li\u003e\n\u003cli\u003eMichel, R. \u003cem\u003eet al.\u003c/em\u003e Dose to organ at risk and dose prescription in liver SBRT. \u003cem\u003eRep Pract Oncol Radiother\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 96\u0026ndash;102 (2017).\u003c/li\u003e\n\u003cli\u003eJang, W. I., Jo, S., Moon, J. E., Bae, S. H. \u0026amp; Park, H. C. The Current Evidence of Intensity-Modulated Radiotherapy for Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. \u003cem\u003eCancers (Basel)\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 4914 (2023).\u003c/li\u003e\n\u003cli\u003eMunoz-Schuffenegger, P., Ng, S. \u0026amp; Dawson, L. A. Radiation-Induced Liver Toxicity. \u003cem\u003eSemin Radiat Oncol\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 350\u0026ndash;357 (2017).\u003c/li\u003e\n\u003cli\u003eZhou, Y. J. \u003cem\u003eet al.\u003c/em\u003e Radiation-induced liver disease: beyond DNA damage. \u003cem\u003eCell Cycle\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 506\u0026ndash;526 (2023).\u003c/li\u003e\n\u003cli\u003eSage, E. \u0026amp; Shikazono, N. Radiation-induced clustered DNA lesions: Repair and mutagenesis. \u003cem\u003eFree Radic Biol Med\u003c/em\u003e \u003cstrong\u003e107\u003c/strong\u003e, 125\u0026ndash;135 (2017).\u003c/li\u003e\n\u003cli\u003eChatzipapas, K. P. \u003cem\u003eet al.\u003c/em\u003e Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations. \u003cem\u003eCancers (Basel)\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 799 (2020).\u003c/li\u003e\n\u003cli\u003eQin, H., Zhang, H., Zhang, S., Zhu, S. \u0026amp; Wang, H. Protective Effect of Sirt1 against Radiation-Induced Damage. \u003cem\u003eRadiat Res\u003c/em\u003e \u003cstrong\u003e196\u003c/strong\u003e, 647\u0026ndash;657 (2021).\u003c/li\u003e\n\u003cli\u003eAli, O. S. M., Amin, N. E.-D., Abdel Fattah, S. M. \u0026amp; Abd El-Rahman, O. Ameliorative effect of kefir against \u0026gamma;-irradiation induced liver injury in male rats: impact on oxidative stress and inflammation. \u003cem\u003eEnviron Sci Pollut Res Int\u003c/em\u003e \u003cstrong\u003e27\u003c/strong\u003e, 35161\u0026ndash;35173 (2020).\u003c/li\u003e\n\u003cli\u003eSzatm\u0026aacute;ri, T. \u003cem\u003eet al.\u003c/em\u003e Extracellular Vesicles Mediate Radiation-Induced Systemic Bystander Signals in the Bone Marrow and Spleen. \u003cem\u003eFront Immunol\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 347 (2017).\u003c/li\u003e\n\u003cli\u003eChristiansen, H. \u003cem\u003eet al.\u003c/em\u003e Irradiation leads to susceptibility of hepatocytes to TNF-alpha mediated apoptosis. \u003cem\u003eRadiother Oncol\u003c/em\u003e \u003cstrong\u003e72\u003c/strong\u003e, 291\u0026ndash;296 (2004).\u003c/li\u003e\n\u003cli\u003eHuang, X. W. \u003cem\u003eet al.\u003c/em\u003e Antisense oligonucleotide inhibition of tumor necrosis factor receptor 1 protects the liver from radiation-induced apoptosis. \u003cem\u003eClin Cancer Res\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 2849\u0026ndash;2855 (2006).\u003c/li\u003e\n\u003cli\u003eJing, Z.-T. \u003cem\u003eet al.\u003c/em\u003e AKT activator SC79 protects hepatocytes from TNF-\u0026alpha;-mediated apoptosis and alleviates d-Gal/LPS-induced liver injury. \u003cem\u003eAm J Physiol Gastrointest Liver Physiol\u003c/em\u003e \u003cstrong\u003e316\u003c/strong\u003e, G387\u0026ndash;G396 (2019).\u003c/li\u003e\n\u003cli\u003eIracheta-Vellve, A. \u003cem\u003eet al.\u003c/em\u003e Interleukin-1 inhibition facilitates recovery from liver injury and promotes regeneration of hepatocytes in alcoholic hepatitis in mice. \u003cem\u003eLiver Int\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 968\u0026ndash;973 (2017).\u003c/li\u003e\n\u003cli\u003eLoBianco, F. V. \u003cem\u003eet al.\u003c/em\u003e The Role of Sirtuin 3 in Radiation-Induced Long-Term Persistent Liver Injury. \u003cem\u003eAntioxidants (Basel)\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 409 (2020).\u003c/li\u003e\n\u003cli\u003eYi, J. \u003cem\u003eet al.\u003c/em\u003e Radioprotection of EGCG based on immunoregulatory effect and antioxidant activity against 60Co\u0026gamma; radiation-induced injury in mice. \u003cem\u003eFood Chem Toxicol\u003c/em\u003e \u003cstrong\u003e135\u003c/strong\u003e, 111051 (2020).\u003c/li\u003e\n\u003cli\u003eDu, S.-S. \u003cem\u003eet al.\u003c/em\u003e Radiation-induced liver fibrosis is mitigated by gene therapy inhibiting transforming growth factor-\u0026beta; signaling in the rat. \u003cem\u003eInt J Radiat Oncol Biol Phys\u003c/em\u003e \u003cstrong\u003e78\u003c/strong\u003e, 1513\u0026ndash;1523 (2010).\u003c/li\u003e\n\u003cli\u003eDong, Y. \u003cem\u003eet al.\u003c/em\u003e Activation of the JNK-c-Jun pathway in response to irradiation facilitates Fas ligand secretion in hepatoma cells and increases hepatocyte injury. \u003cem\u003eJ Exp Clin Cancer Res\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 114 (2016).\u003c/li\u003e\n\u003cli\u003eXiao, L. \u003cem\u003eet al.\u003c/em\u003e Role of phosphatidylinositol 3-kinase signaling pathway in radiation-induced liver injury. \u003cem\u003eKaohsiung J Med Sci\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 990\u0026ndash;997 (2020).\u003c/li\u003e\n\u003cli\u003eWang, B. \u003cem\u003eet al.\u003c/em\u003e METTL3-Mediated STING Upregulation and Activation in Kupffer Cells Contribute to Radiation-Induced Liver Disease via Pyroptosis. \u003cem\u003eInt J Radiat Oncol Biol Phys\u003c/em\u003e \u003cstrong\u003e119\u003c/strong\u003e, 219\u0026ndash;233 (2024).\u003c/li\u003e\n\u003cli\u003eChen, Y. \u003cem\u003eet al.\u003c/em\u003e MicroRNA-146a-5p attenuates irradiation-induced and LPS-induced hepatic stellate cell activation and hepatocyte apoptosis through inhibition of TLR4 pathway. \u003cem\u003eCell Death Dis\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 22 (2018).\u003c/li\u003e\n\u003cli\u003eRodriguez-Ruiz, M. E., Vitale, I., Harrington, K. J., Melero, I. \u0026amp; Galluzzi, L. Immunological impact of cell death signaling driven by radiation on the tumor microenvironment. \u003cem\u003eNat Immunol\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 120\u0026ndash;134 (2020).\u003c/li\u003e\n\u003cli\u003eSu, L. \u003cem\u003eet al.\u003c/em\u003e Kupffer cell-derived TNF-\u0026alpha; promotes hepatocytes to produce CXCL1 and mobilize neutrophils in response to necrotic cells. \u003cem\u003eCell Death Dis\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 323 (2018).\u003c/li\u003e\n\u003cli\u003eYamaga, S., Aziz, M., Murao, A., Brenner, M. \u0026amp; Wang, P. DAMPs and radiation injury. \u003cem\u003eFront Immunol\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 1353990 (2024).\u003c/li\u003e\n\u003cli\u003eMeng, L. \u003cem\u003eet al.\u003c/em\u003e METTL14 suppresses pyroptosis and diabetic cardiomyopathy by downregulating TINCR lncRNA. \u003cem\u003eCell Death Dis\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 38 (2022).\u003c/li\u003e\n\u003cli\u003eChen, Y. \u003cem\u003eet al.\u003c/em\u003e N6-methyladenosine-modified TRAF1 promotes sunitinib resistance by regulating apoptosis and angiogenesis in a METTL14-dependent manner in renal cell carcinoma. \u003cem\u003eMol Cancer\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 111 (2022).\u003c/li\u003e\n\u003cli\u003eLiu, J. \u003cem\u003eet al.\u003c/em\u003e METTL14 is essential for \u0026beta;-cell survival and insulin secretion. \u003cem\u003eBiochim Biophys Acta Mol Basis Dis\u003c/em\u003e \u003cstrong\u003e1865\u003c/strong\u003e, 2138\u0026ndash;2148 (2019).\u003c/li\u003e\n\u003cli\u003eQian, S., Liu, J., Liao, W. \u0026amp; Wang, F. METTL14 drives growth and metastasis of non-small cell lung cancer by regulating pri-miR-93-5p maturation and TXNIP expression. \u003cem\u003eGenes Genomics\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, 213\u0026ndash;229 (2024).\u003c/li\u003e\n\u003cli\u003eGao, G. \u003cem\u003eet al.\u003c/em\u003e METTL14 promotes apoptosis of spinal cord neurons by inducing EEF1A2 m6A methylation in spinal cord injury. \u003cem\u003eCell Death Discov\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 15 (2022).\u003c/li\u003e\n\u003cli\u003eLi, L., Zeng, J., He, S., Yang, Y. \u0026amp; Wang, C. METTL14 decreases FTH1 mRNA stability via m6A methylation to promote sorafenib-induced ferroptosis of cervical cancer. \u003cem\u003eCancer Biol Ther\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 2349429 (2024).\u003c/li\u003e\n\u003cli\u003eChen, F., Su, M., Han, D., Wang, Y. \u0026amp; Song, M. METTL14 depletion ameliorates ferroptosis in severe acute pancreatitis by increasing the N6-methyladenosine modification of ACSL4 and STA1. \u003cem\u003eInt Immunopharmacol\u003c/em\u003e \u003cstrong\u003e128\u003c/strong\u003e, 111495 (2024).\u003c/li\u003e\n\u003cli\u003eLiang, J. \u003cem\u003eet al.\u003c/em\u003e METTL14 inhibits malignant progression of oral squamous cell carcinoma by targeting the autophagy-related gene RB1CC1 in an m6A-IGF2BP2-dependent manner. \u003cem\u003eClin Sci (Lond)\u003c/em\u003e \u003cstrong\u003e137\u003c/strong\u003e, 1373\u0026ndash;1389 (2023).\u003c/li\u003e\n\u003cli\u003eHou, X. \u003cem\u003eet al.\u003c/em\u003e METTL14 reverses liver fibrosis by inhibiting NOVA2 through an m6A-YTHDF2-dependent mechanism. \u003cem\u003eHepatol Commun\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, e0199 (2023).\u003c/li\u003e\n\u003cli\u003eWang, Y.-F. \u003cem\u003eet al.\u003c/em\u003e METTL14 downregulation drives S100A4+ monocyte-derived macrophages via MyD88/NF-\u0026kappa;B pathway to promote MAFLD progression. \u003cem\u003eSignal Transduct Target Ther\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 91 (2024).\u003c/li\u003e\n\u003cli\u003eCao, X. \u003cem\u003eet al.\u003c/em\u003e Mettl14-Mediated m6A Modification Facilitates Liver Regeneration by Maintaining Endoplasmic Reticulum Homeostasis. \u003cem\u003eCell Mol Gastroenterol Hepatol\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 633\u0026ndash;651 (2021).\u003c/li\u003e\n\u003cli\u003eFerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations - PubMed. https://pubmed.ncbi.nlm.nih.gov/32219413/.\u003c/li\u003e\n\u003cli\u003eKanehisa, M., Furumichi, M., Sato, Y., Matsuura, Y. \u0026amp; Ishiguro-Watanabe, M. KEGG: biological systems database as a model of the real world. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, D672\u0026ndash;D677 (2025).\u003c/li\u003e\n\u003cli\u003eZhou, Y. \u003cem\u003eet al.\u003c/em\u003e Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. \u003cem\u003eNat Commun\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1523 (2019).\u003c/li\u003e\n\u003cli\u003eHan, H. \u003cem\u003eet al.\u003c/em\u003e TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e46\u003c/strong\u003e, D380\u0026ndash;D386 (2018).\u003c/li\u003e\n\u003cli\u003eSticht, C., De La Torre, C., Parveen, A. \u0026amp; Gretz, N. miRWalk: An online resource for prediction of microRNA binding sites. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, e0206239 (2018).\u003c/li\u003e\n\u003cli\u003eToesca, D. A. S. \u003cem\u003eet al.\u003c/em\u003e Strategies for prediction and mitigation of radiation-induced liver toxicity. \u003cem\u003eJ Radiat Res\u003c/em\u003e \u003cstrong\u003e59\u003c/strong\u003e, i40\u0026ndash;i49 (2018).\u003c/li\u003e\n\u003cli\u003eLiang, S.-X. \u003cem\u003eet al.\u003c/em\u003e Radiation-induced liver disease in three-dimensional conformal radiation therapy for primary liver carcinoma: the risk factors and hepatic radiation tolerance. \u003cem\u003eInt J Radiat Oncol Biol Phys\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 426\u0026ndash;434 (2006).\u003c/li\u003e\n\u003cli\u003eOhri, N. \u003cem\u003eet al.\u003c/em\u003e Radiotherapy for Hepatocellular Carcinoma: New Indications and Directions for Future Study. \u003cem\u003eJ Natl Cancer Inst\u003c/em\u003e \u003cstrong\u003e108\u003c/strong\u003e, djw133 (2016).\u003c/li\u003e\n\u003cli\u003eCao, Y. \u0026amp; Guo, W. Role of METTL14 in cardiomyocyte pyroptosis in mice with heart failure by regulating miR-221-3p RNA methylation. \u003cem\u003eInt Immunopharmacol\u003c/em\u003e \u003cstrong\u003e149\u003c/strong\u003e, 114172 (2025).\u003c/li\u003e\n\u003cli\u003eZhuang, S. \u003cem\u003eet al.\u003c/em\u003e METTL14 promotes doxorubicin-induced cardiomyocyte ferroptosis by regulating the KCNQ1OT1-miR-7-5p-TFRC axis. \u003cem\u003eCell Biol Toxicol\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 1015\u0026ndash;1035 (2023).\u003c/li\u003e\n\u003cli\u003eKim, H.-G., Jang, S.-S., Lee, J.-S., Kim, H.-S. \u0026amp; Son, C.-G. Panax ginseng Meyer prevents radiation-induced liver injury via modulation of oxidative stress and apoptosis. \u003cem\u003eJ Ginseng Res\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 159\u0026ndash;168 (2017).\u003c/li\u003e\n\u003cli\u003eGawish, R. A., Samy, E. M. \u0026amp; Aziz, M. M. Ferulic acid protects against gamma-radiation induced liver injury via regulating JAK/STAT/Nrf2 pathways. \u003cem\u003eArch Biochem Biophys\u003c/em\u003e \u003cstrong\u003e753\u003c/strong\u003e, 109895 (2024).\u003c/li\u003e\n\u003cli\u003eWang, X. \u003cem\u003eet al.\u003c/em\u003e Autophagy suppresses radiation damage by activating PARP-1 and attenuating reactive oxygen species in hepatoma cells. \u003cem\u003eInt J Radiat Biol\u003c/em\u003e \u003cstrong\u003e95\u003c/strong\u003e, 1051\u0026ndash;1057 (2019).\u003c/li\u003e\n\u003cli\u003eCataldi, S. \u003cem\u003eet al.\u003c/em\u003e Acid and Neutral Sphingomyelinase Behavior in Radiation-Induced Liver Pyroptosis and in the Protective/Preventive Role of rMnSOD. \u003cem\u003eInt J Mol Sci\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 3281 (2020).\u003c/li\u003e\n\u003cli\u003eWu, D. \u003cem\u003eet al.\u003c/em\u003e Identification of HMOX1 as a Critical Ferroptosis-Related Gene in Atherosclerosis. \u003cem\u003eFront Cardiovasc Med\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 833642 (2022).\u003c/li\u003e\n\u003cli\u003eLin, H. \u003cem\u003eet al.\u003c/em\u003e EF24 induces ferroptosis in osteosarcoma cells through HMOX1. \u003cem\u003eBiomed Pharmacother\u003c/em\u003e \u003cstrong\u003e136\u003c/strong\u003e, 111202 (2021).\u003c/li\u003e\n\u003cli\u003eLong, X., Yang, Y. \u0026amp; Zhou, K. Sepsis induces the cardiomyocyte apoptosis and cardiac dysfunction through activation of YAP1/Serpine1/caspase-3 pathway. \u003cem\u003eOpen Med (Wars)\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 20241018 (2024).\u003c/li\u003e\n\u003cli\u003ePav\u0026oacute;n, M. A. \u003cem\u003eet al.\u003c/em\u003e Enhanced cell migration and apoptosis resistance may underlie the association between high SERPINE1 expression and poor outcome in head and neck carcinoma patients. \u003cem\u003eOncotarget\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 29016\u0026ndash;29033 (2015).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"RILD, Cell death, METTL14, Apoptosis, Ferroptosis","lastPublishedDoi":"10.21203/rs.3.rs-8087326/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8087326/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eRadiation-Induced Liver Disease (RILD) is a major dose-limiting complication in radiotherapy for hepatocellular carcinoma, yet its molecular mechanisms remain incompletely understood compared to radiation injury in other organs. Programmed cell death (PCD) pathways like apoptosis, pyroptosis, and ferroptosis are crucial in RILD development. The m6A modification enzyme METTL14 is implicated in driving these PCD pathways, but its role in radiation-induced hepatocyte injury was unknown. This study aimed to elucidate METTL14's function and molecular mechanisms in RILD pathogenesis to identify novel therapeutic targets.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eC57BL/6J mice received 30 Gy liver irradiation (5 Gy × 6 fractions). METTL14 overexpression was achieved by tail-vein injection of AAV-METTL14. Liver injury was evaluated by transmission electron microscopy (TEM), RNA-seq, bioinformatics and molecular validation (qRT-PCR / Western blot).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIrradiation markedly reduced hepatic METTL14 protein. Overexpression of METTL14 preserved hepatocyte ultrastructure and decreased cell death. Transcriptomic profiling revealed 964 differentially expressed genes (DEGs), were apoptosis-related. Functional enrichment and PPI network analyses identified ten hub genes, with HMOX1 and SERPINE1 exhibiting the most consistent up-regulation at both mRNA and protein levels. A TF–mRNA–miRNA regulatory network further implicated hsa-miR-145-5p and 33 upstream transcription factors in controlling these hubs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e METTL14 overexpression protects against radiation-induced hepatocyte injury primarily through modulation of apoptosis and ferroptosis pathways, with HMOX1 and SERPINE1 serving as key downstream effectors. Targeting the METTL14–SERPINE1- miR-145-5p axis may offer a novel therapeutic strategy for RILD.\u003c/p\u003e","manuscriptTitle":"The identification of genes related to METTL14 inhibition in radiation- induced hepatocyte death based on bioinformatics analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 11:19:43","doi":"10.21203/rs.3.rs-8087326/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-30T07:36:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T07:34:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T10:18:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"270828921836361425907825435596047115009","date":"2026-03-22T11:57:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6463543055208355547070948457826076228","date":"2026-03-20T03:21:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T19:09:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T07:33:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-16T06:40:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T03:47:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-11T03:42:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eab24455-78f7-48f9-9799-d5f77c7c8420","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":64947728,"name":"Biological sciences/Cancer"},{"id":64947729,"name":"Biological sciences/Cell biology"},{"id":64947730,"name":"Health sciences/Diseases"},{"id":64947731,"name":"Biological sciences/Genetics"},{"id":64947732,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2026-05-06T09:56:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 11:19:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8087326","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8087326","identity":"rs-8087326","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}