Hepatocyte TonEBP promotes metabolic stress-induced hepatic fibroinflammation involving transcriptional activation of ELR⁺ CXC chemokines

Hepatocyte TonEBP promotes metabolic stress-induced hepatic fibroinflammation involving transcriptional activation of ELR⁺ CXC chemokines | 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 Hepatocyte TonEBP promotes metabolic stress-induced hepatic fibroinflammation involving transcriptional activation of ELR ⁺ CXC chemokines Soo Youn Choi, Jun Ho Lee, Hana Song, Eun Jin Yoo, Yeseul Jeong, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7352787/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Feb, 2026 Read the published version in Cell Death Discovery → Version 1 posted 6 You are reading this latest preprint version Abstract Metabolic dysfunction-associated steatohepatitis (MASH), a progressive stage of metabolic dysfunction-associated steatotic liver disease (MASLD), is characterized by liver inflammation, fibrosis, and hepatocyte injury. Despite its clinical relevance, the molecular mechanisms linking metabolic stress to hepatic fibroinflammation remain poorly understood. In this study, we identify Tonicity-Responsive Enhancer-Binding Protein (TonEBP) as a key stress-responsive transcription factor that mediates the link between metabolic overload and liver inflammation in non-malignant hepatocytes. Using hepatocyte-specific TonEBP knockout (HKO) mice, we demonstrate that TonEBP deletion reduces liver injury, inflammation, and fibrosis in MASH and steatosis models. Mechanistically, TonEBP recruits nuclear factor-κB (NF-κB) to ELR⁺ CXC chemokine gene promoters, promoting neutrophil and macrophage recruitment. These findings underscore the hepatocyte-intrinsic TonEBP/NF-κB axis as a critical driver of immune cell infiltration and fibroinflammation in MASLD progression, revealing its pivotal role in the pathophysiology of liver disease. By highlighting this axis, we provide new insight into the molecular mechanisms that govern the transition from steatosis to steatohepatitis, emphasizing the importance of TonEBP in regulating inflammatory pathways within hepatocytes. Biological sciences/Genetics/Gene expression Health sciences/Medical research/Preclinical research Biological sciences/Genetics/Gene regulation Health sciences/Pathogenesis/Inflammation Health sciences/Diseases/Metabolic disorders MASLD MASH hepatocyte TonEBP inflammation fibrosis chemokines Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Metabolic dysfunction-associated steatohepatitis (MASH), a progressive form of metabolic dysfunction-associated steatotic liver disease (MASLD), is characterized by hepatic steatosis, inflammation, and fibrosis. The transition from MASLD to MASH significantly increases the risk of cirrhosis, liver failure, and hepatocellular carcinoma (HCC), making it a major global health concern [ 1 , 2 ]. Despite advances in understanding the clinical features of MASH, the molecular mechanisms linking metabolic stress to hepatic fibroinflammation are multifactorial and remain incompletely understood. However, innate immunity plays a central role, with liver-resident macrophages (Kupffer cells) and recruited immune cells, such as macrophages and neutrophils, driving disease progression [ 3 , 4 ]. Hepatocytes, the primary parenchymal cells of the liver, are essential for regulating hepatic metabolic functions and responding to metabolic stress [ 5 , 6 ]. In conditions of chronic metabolic overload, such as obesity or lipotoxicity, hepatocytes become key initiators of liver inflammation and fibrosis by releasing proinflammatory cytokines and chemokines that recruit immune cells, particularly neutrophils and macrophages [ 7 – 9 ]. These infiltrating immune cells further exacerbate the inflammatory and fibrotic environment, accelerating liver injury [ 9 ]. A critical regulator of cellular stress responses is tonicity-responsive enhancer-binding protein (TonEBP), also known as NFAT5. TonEBP is a stress-responsive transcription factor that integrates osmotic, metabolic, and inflammatory signals to regulate gene expression in a cell type- and context-dependent manner [ 10 ]. While TonEBP has been implicated in a variety of chronic conditions, including inflammation [ 11 , 12 ], insulin resistance [ 13 ], adipose tissue dysfunction [ 14 ], and oncogenesis [ 15 – 17 ], its role in hepatocytes, especially under metabolic stress, remains poorly defined. Previous studies have shown that TonEBP interacts with NF-κB, a central transcription factor regulating proinflammatory gene expression. In macrophages, TonEBP enhances NF-κB-dependent cytokine expression during inflammation [ 13 , 18 ]. However, whether TonEBP regulates inflammatory pathways in hepatocytes during metabolic stress has yet to be determined. In this study, we investigate the role of TonEBP in hepatic inflammation and fibrosis in the context of MASLD and MASH. Using hepatocyte-specific TonEBP knockout (HKO) mice, we examine the effects of TonEBP deletion on liver injury, inflammation, and fibrosis in steatosis and steatohepatitis models. We show that TonEBP is essential for chemokine-driven neutrophil and macrophage infiltration, and that its interaction with NF-κB regulates the transcriptional activation of ELR⁺ CXC chemokines. These findings highlight the TonEBP–NF-κB axis as a critical mechanism in the progression of MASLD to MASH. RESULTS Hepatocyte TonEBP coordinates fibroinflammatory and metabolic gene programs under metabolic stress To investigate the role of hepatocyte-intrinsic TonEBP in metabolic stress–driven fibroinflammation, we generated hepatocyte-specific TonEBP knockout (HKO) mice (Fig. S1 ) and applied two dietary models: methionine- and choline-deficient (MCD) and high-fat, high-carbohydrate (HFHC) diets. The MCD diet induces steatosis, inflammation, hepatocellular ballooning, cell death, and progressive fibrosis, closely reflecting advanced histological features of human MASH [ 19 ]. It is widely used for reproducible analysis of disease-related transcriptional changes and pathway-level responses but does not induce obesity or insulin resistance. The HFHC diet, in contrast, produces milder yet progressive liver injury associated with obesity, insulin resistance, and fructose intake, more closely modeling the metabolic context of human MASLD/MASH [ 20 , 21 ]. Using both models allowed us to assess the contribution of hepatocyte TonEBP under distinct metabolic stress conditions. In MCD-fed mice, wild-type (WT) and HKO groups showed comparable weight loss (~ 40%) and food intake (Fig. 1 A–B, Fig. S2A). Steatosis and serum triglyceride levels were similar (Fig. 1 C–D, Fig. S2B–C), but Sirius Red staining revealed markedly reduced fibrosis in HKO livers (Fig. 1 E, Fig. S2D). Serum ALT, AST, and LDH were also significantly lower in HKO mice (Fig. 1 F, Fig. S2E). Hepatic expression of TonEBP and 20 fibrosis-related genes linked to human MASH [ 22 ] was significantly decreased in HKO mice (Fig. 1 G, Fig. S2F). To explore transcriptional changes, we performed RNA-seq on liver tissue. Principal component analysis showed that HKO samples clustered with the control group fed a normal diet and were clearly separated from MCD-fed WT mice (Fig. 2 A). Differentially expressed genes (DEGs) analysis identified 5,325 DEGs between WT-CD and WT-MCD, and 822 DEGs between WT-MCD and HKO-MCD (Fig. 2 B). KEGG analysis revealed enrichment of fibrogenic and ECM-related pathways (‘ECM–receptor interaction,’ ‘PI3K–Akt signaling’) in WT-MCD, which were suppressed in HKO-MCD, while metabolic pathways downregulated by MCD were restored (Fig. S3A–B). GO enrichment analysis supported these findings (Fig. S4A–F). K-means clustering showed reduced expression of fibrosis-related clusters, including Cluster 5, in HKO livers (Fig. 2 C–E, Fig. S5A–B). KEGG analysis revealed enrichment of fibrogenic and ECM-related pathways (‘ECM–receptor interaction,’ ‘PI3K–Akt signaling’) in WT-MCD, which were suppressed in HKO-MCD, while metabolic pathways downregulated by MCD were restored (Fig. S3A–B). GO enrichment analysis supported these findings (Fig. S4A–F). K-means clustering showed reduced expression of fibrosis-related clusters, including Cluster 5, in HKO livers (Fig. 2 C–E, Fig. S5A–B). GSEA demonstrated downregulation of inflammatory and fibrotic pathways (‘inflammatory response,’ ‘TNFα signaling via NF-κB,’ ‘epithelial–mesenchymal transition’) and upregulation of metabolic programs (‘oxidative phosphorylation,’ ‘bile acid metabolism’) (Fig. S6A–B). Mapping mouse DEGs to human orthologs confirmed conserved suppression of inflammatory/fibrotic signatures and restoration of metabolic pathways in HKO livers (Fig. 2 F–G, Fig. S7). We next evaluated hepatocyte TonEBP in an obesity-associated setting using the HFHC model, which reflects Western dietary patterns high in cholesterol, saturated fats, and fructose [ 20 , 21 ]. WT and HKO mice showed similar body weight, food intake, and water consumption during 16 weeks of feeding (Fig. 3 A–C). HKO mice had significantly lower fasting glucose (Fig. 3 D) and liver-to-body weight ratios (Fig. 3 E). Histology revealed reduced steatosis and fibrosis (Fig. 3 F–G), with lower serum ALT, AST, and LDH (Fig. 3 H). Fibrosis-related genes were downregulated (Fig. 3 I). These findings indicate that hepatocyte TonEBP is necessary for activation of inflammatory, fibrogenic, and metabolic stress–responsive programs in both lipotoxic and obesity-associated injury. Hepatocyte TonEBP depletion attenuates hepatic inflammation across diverse metabolic stress models Inflammation drives the progression from simple steatosis to MASH, fibrosis, and cirrhosis [ 23 – 26 ]. To determine the contribution of hepatocyte TonEBP, we examined inflammatory and immune-related gene expression in different metabolic stress models. In MCD-fed WT mice, chemokines ( Cxcl1 , Cxcl2 , Ccl2 ), adhesion molecules ( Icam1 ), and cytokines ( Tnfα , Il1b ) were strongly induced (Fig. S8A), matching the transcriptomic profiles of WT-MCD livers. This induction was significantly reduced in HKO mice (Fig. 4 A). Similar suppression was seen in HFHC-fed HKO mice (Fig. 4 B). In the high-fat diet (HFD) model, which induces injury more gradually, HKO mice also showed reduced expression of these inflammatory markers after 14 weeks (Fig. 4 C), without changes in body weight (Fig. 4 D). Reduced hepatic inflammation correlated with improved systemic metabolic outcomes: lower fasting glucose and insulin, reduced HOMA-IR, and improved glucose tolerance (Fig. 4 E–H). TonEBP deletion efficiency was confirmed by reduced hepatic TonEBP mRNA in HFD-fed HKO mice (Fig. 4 I). These results demonstrate that hepatocyte TonEBP promotes hepatic inflammation in multiple metabolic stress settings and contributes to systemic insulin resistance. Hepatocyte TonEBP promotes neutrophil and macrophage infiltration, in part by transcriptional activation of ELR⁺ CXC chemokines To determine whether reduced Mpo and F4/80 expression in HKO livers (Fig. 4 A–B) reflected decreased immune cell infiltration, we performed histological analyses. IHC and IF revealed abundant MPO⁺ neutrophils and F4/80⁺ macrophages in WT livers under MCD and HFHC feeding, with a stronger response in MCD-fed mice (Fig. S9A–B). In HKO mice, infiltration was markedly reduced (Fig. 5 A–B, Fig. S9A–B). Serum and hepatic levels of Cxcl1 and Cxcl2 , potent ELR⁺ CXC chemokines that attract neutrophils, as well as Ccl2 , a chemokine that recruits macrophages, were also significantly lower in HKO mice (Fig. 4 A–C, Fig. 5 C). We next tested whether TonEBP directly regulates chemokine expression. To this end, we treated primary human hepatocytes (PHHs) with palmitic acid (PA), a lipotoxic saturated fatty acid known to accumulate in metabolic liver disease [ 27 , 28 ]. PHHs treated with PA showed dose-dependent induction of CXCL8 (IL-8) , CXCL1 , and CXCL2 within 3 h, sustained up to 9 h (Fig. 5 D–E), along with increased TonEBP protein (Fig. 5 F). CCL2 transcripts were undetectable (Ct > 35), suggesting that hepatocytes preferentially express neutrophil-attracting ELR⁺ CXC chemokines in response to lipotoxic stress. Since monocytes and macrophages can express CXCR1 and CXCR2 under inflammatory conditions, ELR⁺ CXC chemokines may also contribute to macrophage recruitment [ 29 , 30 ]. Based on this, we focused subsequent analyses on TonEBP-dependent regulation of ELR⁺ CXC chemokines. TonEBP knockdown using two independent siRNAs reduced TonEBP protein expression for up to 72 hours (Fig. S10A) and significantly decreased PA-induced expression of IL-8 , CXCL1 , CXCL2 , and TonEBP (Fig. 5 G–H). PA also induced TNFα , confirming the proinflammatory effect of PA, which was attenuated by TonEBP knockdown (Fig. S10B–D). Similar reductions in these chemokine mRNA were observed in PA-treated AML-12 mouse hepatocytes and HepG2 cells, a human hepatoma line (Fig. S10E–F), indicating a conserved, hepatocyte-intrinsic role for TonEBP across species. siTon #1 was used in subsequent experiments. HepG2 cells, which showed consistent PA responses and high transfection efficiency, were used for mechanistic studies. TonEBP depletion also reduced secretion of IL-8, CXCL1, and CXCL2 (Fig. 5 I), and conditioned medium from TonEBP-depleted cells showed diminished HL-60 migration (Fig. 5 J, Fig. S11A). Neutralizing individual chemokines partially inhibited migration, with additive effects when combined with TonEBP knockdown (Fig. 5 K). Conversely, adenoviral overexpression enhanced PA-induced chemokine expression (Fig. S11B–C). We also examined TNFα and H₂O₂, which enhance NF-κB activity and promote inflammatory gene expression in steatohepatitis [ 31 , 32 ]. Both stimuli increased TonEBP and chemokine expression in PHHs (Fig. S12A–C), HepG2 (Fig. S12D–F), and AML-12 cells (Fig. S12G–I), and these effects were blocked by TonEBP knockdown. TonEBP promoter activity was also elevated (Fig. S12J). These data show that TonEBP promotes ELR⁺ CXC chemokine production under metabolic and inflammatory stress. TonEBP is required for NFκB recruitment to IL-8 , CXCL1 , and CXCL2 promoters To determine whether TonEBP regulates IL-8 , CXCL1 , and CXCL2 transcription, we performed luciferase reporter assays using their proximal promoters in HepG2 cells (Fig. S13A). PA increased promoter activity of IL-8 , CXCL1 , and CXCL2 , which was reduced by TonEBP knockdown (Fig. 6 A), and NF-κB–driven reporter activity was decreased in TonEBP-deficient cells (Fig. S13B). Notably, the promoters do not contain a canonical TonEBP binding motif (Fig. S13C). Given that NF-κB is a key transcriptional regulator of these genes [ 33 – 35 ], and that TonEBP has been shown to potentiate TNFα transcriptional activity in macrophages by interacting with NF-κB p65 without directly binding the promoter [ 18 ], we investigated whether TonEBP facilitates NF-κB-dependent transactivation of PA-induced IL-8 , CXCL1 , and CXCL2 in hepatocytes. Mutation of NF-κB binding sites abolished PA-induced activity (Fig. 6 B, Fig. S13A). ChIP-qPCR confirmed increased TonEBP occupancy at these promoters after PA, TNFα, or H₂O₂ stimulation (Figs. 6 C, S13C, S14B–C). TonEBP knockdown reduced PA-induce p65 recruitment (Fig. 6 D), and co-immunoprecipitation showed PA-dependent TonEBP–p65 interaction (Fig. 6 E). p65 recruitment in response to TNFα or H₂O₂ was similarly diminished in TonEBP-deficient cells (Fig. 6 F–G), and mutation of the NF-κB binding site abrogated promoter activation by both stimuli (Fig. 6 H–I). These findings indicate that TonEBP facilitates NF-κB recruitment to these promoters under metabolic stress. Disruption of the TonEBP–NFκB interaction recapitulates TonEBP deficiency To assess the functional significance of the TonEBP–NF-κB interaction, we disrupted the complex using cerulenin, a known inhibitor of TonEBP–NF-κB binding [ 18 ]. Co-immunoprecipitation confirmed that cerulenin impaired TonEBP–p65 interaction in HepG2 cells (Fig. 7 A). Cerulenin treatment significantly reduced PA-induced IL-8 , CXCL1 , CXCL2 (Fig. 7 B), and TNFα (Fig. S15) expression, and decreased promoter activity (Fig. 7 C). Cerulenin also attenuated chemokine induction by TNFα and H₂O₂ (Fig. 7 D–E). These effects mirrored those of TonEBP knockdown, confirming that the TonEBP–NF-κB complex is essential for maximal inflammatory gene activation in hepatocytes under metabolic stress. A schematic model summarizing our findings is presented in Fig. 7 F, illustrating how hepatocyte TonEBP, through interaction with NF-κB, promotes transcription of ELR⁺ CXC chemokines, thereby driving immune cell infiltration, hepatic inflammation, and progression of steatohepatitis. DISCUSSION This study identifies hepatocyte TonEBP as a central transcriptional regulator that links metabolic stress to hepatic fibroinflammation through induction of ELR⁺ CXC chemokines, including IL-8 , CXCL1 , and CXCL2 . These chemokines are potent neutrophil chemoattractants and can also recruit macrophages under inflammatory conditions. We show that TonEBP acts in hepatocytes by forming a complex with NF-κB, enabling transcriptional activation of chemokine genes in response to lipotoxic, oxidative, and cytokine stress. This defines a hepatocyte-intrinsic mechanism by which metabolic stress drives immune cell infiltration and inflammation in metabolic liver diseases. The transition from MASLD to MASH is characterized by persistent inflammation with infiltration of neutrophils and macrophages [ 24 – 26 ], which form crown-like structures associated with advanced fibrosis and worse outcomes. [ 36 , 37 ]. These cells exacerbate liver injury by releasing reactive oxygen species, proinflammatory cytokines, and extracellular traps, thereby sustaining a pro-fibrogenic milieu [ 3 , 4 , 38 – 40 ]. In our models, hepatocyte-specific TonEBP deletion reduced both neutrophil and macrophage accumulation, accompanied by suppression of chemokine expression and fibroinflammatory gene programs. This effect was observed in both lipotoxic (MCD) and obesity-associated (HFHC) models, indicating a conserved role for TonEBP in metabolic stress–induced hepatic inflammation. Chronic liver inflammation reflects coordinated interactions among hepatocytes, Kupffer cells, hepatic stellate cells (HSCs), and sinusoidal endothelial cells [25, 41−43]. Under metabolic stress, hepatocytes release chemokines and danger signals that activate Kupffer cells and HSCs. Activated Kupffer cells secrete cytokines to amplify inflammation, while HSCs differentiate into myofibroblasts, leading to extracellular matrix deposition. Our findings place hepatocyte TonEBP at the upstream point of this network: its deletion not only suppresses chemokine expression, but also reduces immune cell infiltration, fibrosis, and hepatocellular injury, highlighting the pivotal intrinsic role of hepatocytes in shaping the liver’s response to metabolic stress and inflammation. Notably, the protective effects of TonEBP deletion were consistently observed across multiple models of steatohepatitis, suggesting that this mechanism is conserved and broadly applicable, regardless of the specific metabolic or dietary challenge. The ELR⁺ CXC chemokines— IL-8 , CXCL1 , and CXCL2 —and CCL2 are clinically relevant in both animal models and human MASH, correlating with immune cell infiltration, disease activity, and fibrosis stage. Elevated serum IL-8 and CCL2 levels associate with advanced fibrosis and poor prognosis in MASH patients [ 44 ]. IL-8 levels are particularly elevated in chronic liver diseases, including cirrhosis, and have been shown to be associated with macrophage accumulation in the liver [ 30 ]. Furthermore, CXCR1 expression is elevated in circulating monocytes from cirrhotic patients [ 30 ], which further suggests the clinical relevance of this chemokine signaling axis in disease progression. In our study, Cxcl1 and Cxcl2 serve as functional analogs of IL-8 in mice, mediating neutrophil recruitment. We demonstrate that TonEBP regulates the expression of these chemokines in hepatocytes, and its deletion results in reduced neutrophil migration in vitro and immune cell infiltration in vivo . Importantly, our study shows that TonEBP does not activate these promoters via its canonical DNA-binding motif, but by facilitating NF-κB p65 recruitment, thereby amplifying transcription. This was supported by loss-of-function (TonEBP knockdown) and pharmacologic disruption of the TonEBP–NF-κB complex, both of which impaired chemokine induction and neutrophil chemotaxis. This finding extends previous studies showing that TonEBP activates NF-κB signaling in immune cells, demonstrating a similar cooperative effect in hepatocytes under metabolic stress. Our study also highlights the potential of TonEBP as a therapeutic target for metabolic liver diseases. TonEBP is known to promote pro-inflammatory programs in various tissues, including adipose tissue and macrophages [ 10 ]. Here, we extend its role to hepatocytes, identifying the TonEBP–NF-κB complex as a key integrator of metabolic and inflammatory signals that converge on chemokine gene regulation. Inhibition of this axis attenuates immune cell infiltration and fibrosis, supporting the idea that TonEBP may be a viable therapeutic target for neutrophil-dominant MASH phenotypes. Several limitations should be considered. First, while we observed reduced neutrophil infiltration and chemokine expression, the functional properties of infiltrating neutrophils, such as ROS production and NET formation, were not assessed. Second, species-specific differences in chemokine repertoires, notably the absence of IL-8 in mice, may limit the direct translation of our findings to humans. Third, although TonEBP deletion improved glucose metabolism in both HFHC and HFD models, insulin signaling in peripheral tissues was not evaluated. Finally, clinical validation using patient-derived samples is essential to confirm the relevance of our findings in human MASLD/MASH. In conclusion, TonEBP emerges as a key hepatocyte-intrinsic regulator of chemokine-driven inflammation and fibrosis in metabolic liver diseases. Targeting the TonEBP–NF-κB axis represents a promising therapeutic approach for treating MASH and other metabolically driven liver diseases. MATERIALS AND METHODS Animal studies Male C57BL/6J mice (7–8 weeks) were used in all experiments. All animal studies were conducted using male C57BL/6J mice aged 7–8 weeks. Hepatocyte-specific TonEBP knockout (HKO) mice were generated by crossing TonEBP fl/fl mice [ 45 ] with Alb-Cre transgenic mice (Jackson Laboratory, Bar Harbor, ME) (Supplementary Fig. S1 A). To validate hepatocyte-specific deletion, TonEBP protein levels were assessed in liver, kidney, spleen, and lung. TonEBP was selectively ablated in the liver of Cre + mice (Fig. S16A). Under chow diet (CD) conditions, no significant differences in body weight, liver weight, or fasting glucose were observed between Cre + and Cre − mice (Fig. S16B), indicating no baseline phenotype. Age-matched littermates were randomly assigned to experimental groups based on body weight and fed one of the following diets obtained from Research Diets (New Brunswick, NJ), each accompanied by a model-specific control diet: (1) MCD diet for 8 weeks; (2) HFHC diet for 16 weeks, with drinking water supplemented with high-fructose corn syrup (42 g/L total carbohydrates, composed of 55% fructose and 45% sucrose by weight; Sigma-Aldrich, St. Louis, MO); or (3) HFD (60% kcal from fat) for 14 weeks. Mice were euthanized for tissue collection, and liver injury, fibrosis, and inflammation were assessed using histological analysis, serum markers, and transcriptome analysis. Histology and Immunohistochemistry Liver tissues were fixed in paraformaldehyde, embedded in paraffin, and stained with Hematoxylin and Eosin (H&E) and Sirius Red for histological evaluation of liver fibrosis and inflammation. Immunohistochemistry (IHC) for MPO and F4/80 (neutrophil and macrophage markers) was performed using standard protocols. Fluorescence images were captured using a Cytation 7 imaging system (NFEC-2025-02-303179). Staining intensity and positive cell counts were quantified using ImageJ software ( https://imagej.nih.gov/ij/ ). Glucose tolerance test Following a 16-hour fasting period, mice were injected intraperitoneally with glucose (2 g/kg). Blood samples were collected at various time points and glucose levels were measured using a glucometer. Immunoblot and chemokine analyses Protein extraction and immunoblotting were performed using standard methods [ 46 ]. Protein concentrations were determined using the BCA assay (Pierce, Rockford, IL). Equal amounts of protein were separated by SDS-PAGE and probed with primary antibodies. HRP-conjugated secondary antibodies were used for detection via enhanced chemiluminescence (GE Healthcare, Buckinghamshire, UK). Primary antibodies used included anti-TonEBP [ 47 ], anti-NF-κB p65 (Abcam, #ab16502), and anti-Hsc70 (Rockland, #200-301-A28, Limerick, PA, USA). The levels of CXC chemokines Cxcl1 and Cxcl2 in mouse serum and cell culture media were quantified using ELISA kits (R&D Systems, Minneapolis, MN). IL-8 (CXCL8), CXCL1, and CXCL2 levels in human cell culture media were measured using Human Quantikine ELISA Kits (R&D Systems), following the manufacturer’s protocol. Immunoprecipitation assay Total cell lysates were prepared using RIPA buffer on ice. Lysates were incubated overnight at 4°C with 5 µg of antibody under rotary agitation. Protein A/G agarose beads (40 µL, GE Healthcare) were then added and incubated for 2 h at 4°C. After centrifugation, the beads were washed with RIPA buffer. Immunoprecipitated proteins were eluted by adding 40 µL of sample buffer and boiling at 95°C for 5 min. Eluted samples were analyzed by immunoblotting using anti-TonEBP and anti-NF-κB p65 (Abcam, #ab16502) antibodies. RNA-sequencing analysis RNA was extracted from liver tissues and processed for RNA sequencing on the Illumina HiSeq platform. Differential expression analysis and Gene Set Enrichment Analysis (GSEA) were performed using StringTie (v2.1.3b) and iDEP (v2.01) [49]. Cell culture, transfection, and adenovirus infection Primary human hepatocytes (Lonza, Basel, Switzerland) were cultured on BioCoat Collagen I-coated plates (Corning, Steuben County, NY) using hepatocyte growth medium provided by Lonza. HepG2 cells (HB-8065; ATCC, Manassas, VA) were maintained in Eagle’s MEM supplemented with 10% fetal bovine serum (FBS). AML12 cells (CRL-2254; ATCC) were cultured in DMEM supplemented with 10% FBS, insulin (10 µg/mL), transferrin (5.5 µg/mL), selenium (5 ng/mL), and dexamethasone (40 ng/mL). HL-60 cells (CCL-240; ATCC) were cultured in RPMI 1640 medium with 10% FBS. All cells were maintained at 37°C in a humidified incubator with 5% CO 2 . Small interfering RNAs (siRNAs) were purchased from Integrated DNA Technologies (Coralville, IA). Human hepatocytes, HepG2, and AML12 cells were transfected with scrambled siRNA (siScr) or gene-specific siRNAs at equal concentrations using Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA) for 48 h. After transfection, cells were cultured in fresh medium, treated with indicated chemicals, and analyzed as described. For overexpression experiments, HepG2 cells were infected with adenovirus expressing TonEBP (Ad-TonEBP) or control empty vector (Ad-EV) at a multiplicity of infection (MOI) of 50 for 24 h. Palmitate (saturated fatty acid) treatment in vitro Palmitate (PA) was conjugated to fatty acid-free bovine serum albumin (BSA) at a 6:1 molar ratio and added to the culture medium. Cells were treated with PA–BSA or 0.5% BSA alone as a vehicle control for the indicated durations and concentrations. Real-time PCR Total RNA was extracted using TRIzol® Reagent (Invitrogen), and cDNA was synthesized using M-MLV reverse transcriptase (Promega, Madison, WI). Quantitative real-time PCR was performed using a CFX384 Real-Time PCR Detection System (Bio-Rad, Hercules, CA). Gene expression was normalized to cyclophilin A and calculated using the 2^−ΔΔCt method. Primer sequences are listed in Table S1 . Luciferase reporter assay Cells were transfected with promoter-driven firefly luciferase constructs along with Renilla luciferase as an internal control. After 24 h, cells were treated as indicated, lysed in Passive Lysis Buffer, and analyzed using a dual-luciferase reporter assay system (Promega). Chromatin immunoprecipitation (ChIP)-qPCR HepG2 cells were treated as indicated. ChIP assays were performed using a commercial kit (Millipore, Bedford, MA). Cells were crosslinked with 1% formaldehyde, quenched with glycine, washed, and lysed in SDS lysis buffer. Chromatin was sonicated using a Bioruptor KRB-01 (BMS, Tokyo, Japan) to generate 400–1000 bp DNA fragments. Immunoprecipitation was carried out overnight at 4°C using anti-TonEBP serum, anti-NF-κB p65 antibody (#510500, Thermo Fisher Scientific), normal rabbit serum, or normal rabbit IgG (ab171870, Abcam). DNA was purified using the QIAquick PCR Purification Kit (QIAGEN, Redwood, CA) and analyzed by qPCR. Primer sequences are listed in Table S1 . Statistical analysis Data are presented as means ± standard deviation (SD) or standard error of the mean (SEM), as indicated. For comparisons between two groups, an unpaired two-tailed Student’s t-test was used. For comparisons involving more than two groups, one-way ANOVA followed by Tukey’s post hoc test was applied. Statistical significance was defined as p < 0.05. Analyses were performed using GraphPad Prism 10.0 (GraphPad Software, San Diego, CA). Declarations DATA AVAILABILITY All data supporting the conclusions in the paper are provided in the main text or the supplementary materials. Detailed datasets regarding RNA sequencing are available from the corresponding author upon reasonable request. COMPETING INTERESTS The authors declare no competing interests. ETHICS APPROVAL AND CONSENT TO PARTICIPATE For animal studies, all experimental procedures were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of UNIST (UNISTACUC-20-27). FUNDING This work was supported by the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT; Grant No. RS-2023-NR076466, RS-2024-NR00416052, RS-2025-00514468) and Ministry of Education (2019R1A6A1A10072987). This research was also supported by "Regional Innovation Strategy (RIS)" through NRF funded by the Ministry of Education (2023RIS-009). AUTHOR CONTRIBUTIONS Jun Ho Lee, Hana Song, and Eun Jin Yoo contributed equally to writing the original draft, review & editing, conceptualization, investigation, data curation, validation, and visualization. Yeseul Jeong, Seung Mi Ko contributed to visualization, validation, and investigation. Go Woon Shin, Ji-Hyun Yun, and Mi-Kyoung Jang performed investigations and formal analysis. Gee Euhn Choi, Youngheun Jee, Minhyeok Kang, Jiwon Yang, Sung-Pyo Hur, Jong-Eun Park, Yunkyoung Lee, Hye-Kyung Park, and Whaseon Lee-Kwon provided resources and methodology. Hyug Moo Kwon and Soo Youn Choi supervised the project, reviewed & edited the manuscript, and secured funding. All authors read and approved the final manuscript. References Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018;15:11–20. Babu AF, Palomurto S, Kärjä V, Käkelä P, Lehtonen M, Hanhineva K, et al. Metabolic signatures of metabolic dysfunction-associated steatotic liver disease in severely obese patients. Dig Liver Dis. 2024;56:2103–10. Kazankov K, Jørgensen SMD, Thomsen KL, Møller HJ, Vilstrup H, George J, et al. The role of macrophages in nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Nat Rev Gastroenterol Hepatol. 2019;16:145–159. Hwang S, Yun H, Moon S, Cho YE, Gao B. Role of neutrophils in the pathogenesis of nonalcoholic steatohepatitis. Front Endocrinol (Lausanne). 2021;12:751802. Meex RCR, Watt MJ. Hepatokines: linking nonalcoholic fatty liver disease and insulin resistance. Nat Rev Endocrinol. 2017;13:509–20. Stefan N, Schick F, Birkenfeld AL, Häring HU, White MF. The role of hepatokines in NAFLD. Cell Metab. 2023;35:236–52. Wang X, Zheng Z, Caviglia JM, Corey KE, Herfel TM, Cai B, et al. Hepatocyte TAZ/WWTR1 promotes inflammation and fibrosis in nonalcoholic steatohepatitis. Cell Metab. 2016;24:848–62. Zhu C, Kim K, Wang X, Bartolome A, Salomao M, Dongiovanni P, et al. Hepatocyte Notch activation induces liver fibrosis in nonalcoholic steatohepatitis. Sci Transl Med. 2018;10:eaat0344. Schwabe RF, Tabas I, Pajvani UB. Mechanisms of fibrosis development in nonalcoholic steatohepatitis. Gastroenterology. 2020;158:1913–28. Choi SY, Lee-Kwon W, Kwon HM. The evolving role of TonEBP as an immunometabolic stress protein. Nat Rev Nephrol. 2020;16:352–64. Yoo EJ, Oh KH, Piao H, Kang HJ, Jeong GW, Park H, et al. Macrophage transcription factor TonEBP promotes systemic lupus erythematosus and kidney injury via damage-induced signaling pathways. Kidney Int. 2023;104:163–180. Li M, Kim YM, Koh JH, Park J, Kwon HM, Park JH, et al. Serum amyloid A expression in liver promotes synovial macrophage activation and chronic arthritis via NFAT5. J Clin Invest. 2024;134:e167835. Lee HH, Jeong GW, Ye BJ, et al. TonEBP in myeloid cells promotes obesity-induced insulin resistance and inflammation through adipose tissue remodeling. Diabetes. 2022;71:2557–71. Lee HH, Jeong GW, Ye BJ, Yoo EJ, Son KS, Kim DK, et al. TonEBP/NFAT5 promotes obesity and insulin resistance by epigenetic suppression of white adipose tissue beiging. Nat Commun. 2019;10:3536. Choi SY. The roles of TonEBP in the DNA damage response: From DNA damage bypass to R-loop resolution. DNA Repair (Amst). 2024;140:103697. Lee JH, Suh JH, Choi SY, Kang HJ, Lee HH, Ye BJ, et al. et al. Tonicity-responsive enhancer-binding protein promotes hepatocellular carcinogenesis, recurrence and metastasis. Gut. 2019;68:347–58. Lee JH, Suh JH, Kang HJ, Choi SY, Jung SW, Lee-Kwon W, et al. Tonicity-responsive enhancer-binding protein promotes stemness of liver cancer and cisplatin resistance. EBioMedicine. 2020;58:102926. Lee HH, Sanada S, An SM, Ye BJ, Lee JH, Seo YK, et al. LPS-induced NFκB enhanceosome requires TonEBP/NFAT5 without DNA binding. Sci Rep. 2016;6:24921. Machado MV, Michelotti GA, Xie G, Almeida Pereira T, Boursier J, Bohnic B, et al. Mouse models of diet-induced nonalcoholic steatohepatitis reproduce the heterogeneity of the human disease. PLoS One. 2015;10:e0127991. Vacca M, Kamzolas I, Harder LM, Andreassen M, Eriksen MB, Borrebaek J, et al. An unbiased ranking of murine dietary models based on their proximity to human metabolic dysfunction-associated steatotic liver disease (MASLD). Nat Metab. 2024;6:1178–96. Jensen T, Abdelmalek MF, Sullivan S, Nadeau KJ, Green M, Roncal C, et al. Fructose and sugar: a major mediator of non-alcoholic fatty liver disease. J Hepatol. 2018;68:1063–75. Hwang S, He Y, Xiang X, Seo W, Kim SJ, Ma J, et al. Interleukin-22 ameliorates neutrophil-driven nonalcoholic steatohepatitis through multiple targets. Hepatology. 2020;72:412–29. Park I, Kim N, Lee S, Park K, Son MY, Cho HS, et al. Characterization of signature trends across the spectrum of non-alcoholic fatty liver disease using deep learning method. Life Sci. 2023;314:121195. Huby T, Gautier EL. Immune cell-mediated features of non-alcoholic steatohepatitis. Nat Rev Immunol. 2022;22:429–43. Peiseler M, Schwabe R, Hampe J, Kubes P, Heikenwälder M, Tacke F. Immune mechanisms linking metabolic injury to inflammation and fibrosis in fatty liver disease - novel insights into cellular communication circuits. J Hepatol. 2022;77:1136–60. Hammerich L, Tacke F. Hepatic inflammatory responses in liver fibrosis. Nat Rev Gastroenterol Hepatol. 2023;20:633–46. Joshi-Barve S, Barve SS, Amancherla K, Gobejishvili L, Hill D, Cave M, et al. Palmitic acid induces production of proinflammatory cytokine interleukin-8 from hepatocytes. Hepatology. 2007;46:823–30. Bence KK, Birnbaum MJ. Metabolic drivers of non-alcoholic fatty liver disease. Mol Metab. 2021;50:101143. Rigamonti E, Fontaine C, Lefebvre B, Duhem C, Lefebvre P, Marx N, et al. Induction of CXCR2 receptor by peroxisome proliferator-activated receptor gamma in human macrophages. Arterioscler Thromb Vasc Biol. 2008;28:932–9. Zimmermann HW, Seidler S, Gassler N, Nattermann J, Luedde T, Trautwein C, et al. Interleukin-8 is activated in patients with chronic liver diseases and associated with hepatic macrophage accumulation in human liver fibrosis. PLoS One. 2011;6:e21381. Dong W, Simeonova PP, Gallucci R, Matheson J, Fannin R, Montuschi P, et al. Cytokine expression in hepatocytes: role of oxidant stress. J Interferon Cytokine Res. 1998;18:629–38. Fromenty B, Roden M. Mitochondrial alterations in fatty liver diseases. J Hepatol. 2023;78:415–29. Elliott CL, Allport VC, Loudon JA, Wu GD, Bennett PR. Nuclear factor-kappa B is essential for up-regulation of interleukin-8 expression in human amnion and cervical epithelial cells. Mol Hum Reprod. 2001;7:787–90. Wood LD, Farmer AA, Richmond A. HMGI(Y) and Sp1 in addition to NF-kappa B regulate transcription of the MGSA/GRO alpha gene. Nucleic Acids Res. 1995;23:4210–9. Wu Z, Neufeld H, Torlakovic E, Xiao W. Uev1A-Ubc13 promotes colorectal cancer metastasis through regulating CXCL1 expression via NF-кB activation. Oncotarget. 2018;9:15952–67. Itoh M, Kato H, Suganami T, Konuma K, Marumoto Y, Terai S, et al. Hepatic crown-like structure: a unique histological feature in non-alcoholic steatohepatitis in mice and humans. PLoS One. 2013;8:e82163. Fan M, Song E, Zhang Y, Zhang P, Huang B, Yan K, et al. Metabolic dysfunction-associated steatohepatitis detected by neutrophilic crown-like structures in morbidly obese patients: a multicenter and clinicopathological study. Research (Wash D C). 2024;7:0382. Fabre T, Barron AMS, Christensen SM, Asano S, Bound K, Lech MP, et al. Identification of a broadly fibrogenic macrophage subset induced by type 3 inflammation. Sci Immunol. 2023;8:eadd8945. Baragetti A, Da Dalt L, Moregola A, Svecla M, Terenghi O, Mattavelli E, et al. Neutrophil aging exacerbates high fat diet-induced metabolic alterations. Metabolism. 2023;144:155576. Liu K, Wang FS, Xu R. Neutrophils in liver diseases: pathogenesis and therapeutic targets. Cell Mol Immunol. 2021;18:38–44. Kostallari E, Schwabe RF, Guillot A. Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells. Cell Mol Immunol. 2025; https://doi.org/10.1038/s41423-025-01313-7 Ge C, Tan J, Dai X, Kuang Q, Zhong S, Lai L, et al. Hepatocyte phosphatase DUSP22 mitigates NASH-HCC progression by targeting FAK. Nat Commun. 2022;13:5945. Loft A, Alfaro AJ, Schmidt SF, Pedersen FB, Terkelsen MK, Puglia M, et al. Liver-fibrosis-activated transcriptional networks govern hepatocyte reprogramming and intra-hepatic communication. Cell Metab. 2021;33:1685 – 700.e9. Glass O, Henao R, Patel K, Guy CD, Gruss HJ, Syn WK, et al. Serum Interleukin-8, Osteopontin, and Monocyte Chemoattractant Protein 1 Are Associated With Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Hepatol Commun. 2018;2:1344–1355. Küper C, Beck FX, Neuhofer W. Generation of a conditional knockout allele for the NFAT5 gene in mice. Front Physiol. 2015;5:507. Mahmood T, Yang PC. Western blot: technique, theory, and trouble shooting. N Am J Med Sci. 2012;4:429–34. Miyakawa H, Woo SK, Dahl SC, Handler JS, Kwon HM. Tonicity-responsive enhancer binding protein, a rel-like protein that stimulates transcription in response to hypertonicity. Proc Natl Acad Sci U S A. 1999;96:2538–42. Ge SX, Son EW, Yao R. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics. 2018;19:534. Additional Declarations There is no duality of interest Supplementary Files Supplementarymaterial.pdf Supplementary Information UncroppedWBdata.pdf Uncropped WB data Cite Share Download PDF Status: Published Journal Publication published 26 Feb, 2026 Read the published version in Cell Death Discovery → Version 1 posted Unknown event 19 Aug, 2025 Editorial decision: Reject before peer review 18 Aug, 2025 First submitted to journal 12 Aug, 2025 Unknown event 12 Aug, 2025 Submission checks completed at journal 12 Aug, 2025 Editor assigned by journal 12 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7352787","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":501790509,"identity":"0b391395-d3e4-4666-8ce4-7959b966d321","order_by":0,"name":"Soo Youn Choi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYJCCAx8qbHj4QayEAuJ0MB6ccSZNRrIBpMWAOC3Mh3lbDtsYHACxidHC33/G4DBvQxqP8fnViR8eGDDI84sdwK9F4kaOwcG5O2x4zG683SwBdJjhzNkJ+LUYSPAYHHh7Jg2o5ewGkJYEg9uEtPCfMTjA23aYx3jG2c0/iNPCAHQYSIsBf+824myRuJFWAApkHokbvNssEgwkCPuFv//w5g/AqLTn7z+7+eaPCht5fmkCWhgYOKBxIQFWKUFIOQiwP4Dad4AY1aNgFIyCUTASAQDIMUm8DTruBAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0008-3645-3040","institution":"Jeju National University","correspondingAuthor":true,"prefix":"","firstName":"Soo","middleName":"Youn","lastName":"Choi","suffix":""},{"id":501790510,"identity":"757c2da8-6b98-41c9-a920-72789236d297","order_by":1,"name":"Jun Ho Lee","email":"","orcid":"","institution":"Memorial Sloan Kettering Cancer Center/Sloan Kettering Institute","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"Ho","lastName":"Lee","suffix":""},{"id":501790511,"identity":"de93e159-a836-4294-9622-a8e715b1b90d","order_by":2,"name":"Hana Song","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Hana","middleName":"","lastName":"Song","suffix":""},{"id":501790512,"identity":"e7e4881c-b80e-4d38-8349-49ee0e46289e","order_by":3,"name":"Eun Jin Yoo","email":"","orcid":"","institution":"Ulsan National Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Eun","middleName":"Jin","lastName":"Yoo","suffix":""},{"id":501790513,"identity":"35849aec-6cb4-47a7-a4b4-4b6a19563784","order_by":4,"name":"Yeseul Jeong","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Yeseul","middleName":"","lastName":"Jeong","suffix":""},{"id":501790514,"identity":"39e71b4d-5aa7-491b-bace-852639331641","order_by":5,"name":"Seung Mi Ko","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Seung","middleName":"Mi","lastName":"Ko","suffix":""},{"id":501790515,"identity":"5bfb6152-68f1-4ea7-83d7-f1a1dc60c94a","order_by":6,"name":"Go Woon Shin","email":"","orcid":"","institution":"Ulsan National Institutes of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Go","middleName":"Woon","lastName":"Shin","suffix":""},{"id":501790516,"identity":"35481aec-8b2b-4589-9458-09ae17a3725e","order_by":7,"name":"Gee Euhn Choi","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Gee","middleName":"Euhn","lastName":"Choi","suffix":""},{"id":501790517,"identity":"00cc05c7-513c-4096-a523-40b7cb3787b4","order_by":8,"name":"Youngheun Jee","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Youngheun","middleName":"","lastName":"Jee","suffix":""},{"id":501790518,"identity":"515e769e-64b1-4e67-8077-ab372652fcf8","order_by":9,"name":"Minhyeok Kang","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Minhyeok","middleName":"","lastName":"Kang","suffix":""},{"id":501790519,"identity":"531ce1f3-7c35-4eb7-845f-310f26c8b565","order_by":10,"name":"Jiwon Yang","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Jiwon","middleName":"","lastName":"Yang","suffix":""},{"id":501790520,"identity":"5168616e-eb08-48a2-a4a7-eb8be8ffcdcc","order_by":11,"name":"Sung-Pyo Hur","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Sung-Pyo","middleName":"","lastName":"Hur","suffix":""},{"id":501790521,"identity":"eb701d4f-a396-45bf-b141-1756097a9ca3","order_by":12,"name":"Jong-Eun Park","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Jong-Eun","middleName":"","lastName":"Park","suffix":""},{"id":501790522,"identity":"3b0d097b-8330-478e-b095-e91a0355b4c5","order_by":13,"name":"Yunkyoung Lee","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Yunkyoung","middleName":"","lastName":"Lee","suffix":""},{"id":501790523,"identity":"a7fe609e-1d29-41c1-a5ec-e29610c3512f","order_by":14,"name":"Hye-Kyung Park","email":"","orcid":"","institution":"Ulsan National Institute of Science and Technology (UNIST)","correspondingAuthor":false,"prefix":"","firstName":"Hye-Kyung","middleName":"","lastName":"Park","suffix":""},{"id":501790524,"identity":"b1ea41e8-b926-4481-b7bb-8d695d6fe130","order_by":15,"name":"Ji-Hyun Yun","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Ji-Hyun","middleName":"","lastName":"Yun","suffix":""},{"id":501790525,"identity":"3d4c27ec-8954-4675-8782-5b73991e73ac","order_by":16,"name":"Mi-Kyoung Jang","email":"","orcid":"","institution":"Jeju National University","correspondingAuthor":false,"prefix":"","firstName":"Mi-Kyoung","middleName":"","lastName":"Jang","suffix":""},{"id":501790526,"identity":"27bc9922-5997-4ebc-bfbf-d45a9c9ea8cd","order_by":17,"name":"Whaseon Lee-Kwon","email":"","orcid":"","institution":"Ulsan National Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Whaseon","middleName":"","lastName":"Lee-Kwon","suffix":""},{"id":501790527,"identity":"6c95018e-af46-4386-bb2e-e17f6e39cb3f","order_by":18,"name":"Hyug Moo Kwon","email":"","orcid":"https://orcid.org/0000-0003-3244-2025","institution":"Ulsan National Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Hyug","middleName":"Moo","lastName":"Kwon","suffix":""}],"badges":[],"createdAt":"2025-08-12 07:45:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7352787/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7352787/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41420-026-02978-3","type":"published","date":"2026-02-26T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89349344,"identity":"3af14914-53c3-4226-854e-81826365dcf4","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10704010,"visible":true,"origin":"","legend":"\u003cp\u003eHepatocyte TonEBP depletion alleviates MCD-induced liver injury and fibrosis in mice. Male hepatocyte-specific TonEBP knockout (HKO) and wild-type (WT) mice (8 weeks old) were fed an MCD diet for 8 weeks (n = 10 per group). (A, B) Body weight (A) and food intake (B). (C) Representative H\u0026amp;E-stained liver sections and quantification of lipid droplet area. (D) Serum triglyceride levels. (E) Sirius Red staining and quantification of fibrotic area. (F) Serum ALT, AST, and LDH activities. (G) Hepatic expression of fibrosis-related genes determined by RT-qPCR. Data are mean ± SEM. *p \u0026lt; 0.05 vs. WT; ns, not significant (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/ff16730b11cedd10f47bdaa5.jpg"},{"id":89349356,"identity":"2940b725-dc22-4ed3-8209-6f526557b1ad","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24913760,"visible":true,"origin":"","legend":"\u003cp\u003eLiver transcriptome analysis reveals reduced steatohepatitis-related gene expression in TonEBP-deficient mice. RNA-seq was performed on livers from male WT and HKO mice fed a control diet (CD, \u003cem\u003en\u003c/em\u003e = 3) or MCD diet (\u003cem\u003en\u003c/em\u003e = 5) for 8 weeks. (A) PCA plot. (B) Number of differentially expressed genes (DEGs) between groups identified by DESeq2 and edgeR (|log2FC| \u0026gt; 2, FDR \u0026lt; 0.05)). (C) K-means clustering of the top 2,000 variable genes. (D, E) KEGG (D) and GO-BP (E) enrichment analyses for Cluster 5 genes. (F) GSEA normalized enrichment scores (NES) for HKO-MCD vs. WT-MCD livers. (G) Representative enrichment plots for selected pathways.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/94fd9b465a392ba0a48250eb.jpg"},{"id":89350360,"identity":"457f435a-031b-456b-9497-db5baeca74e8","added_by":"auto","created_at":"2025-08-19 06:05:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":16108283,"visible":true,"origin":"","legend":"\u003cp\u003eHepatocyte TonEBP deficiency attenuates liver injury and fibrosis in HFHC-fed mice. Male WT and HKO mice were fed an HFHC diet for 16 weeks (\u003cem\u003en\u003c/em\u003e = 8 per group). (A–E) Body weight (A), food intake (B), water intake (C), fasting blood glucose (D), and liver-to-body weight ratio (E). (F) Representative H\u0026amp;E-stained sections and lipid droplet quantification. (G) Sirius Red staining and fibrotic area quantification. (H) Serum ALT, AST, and LDH activities. (I) Hepatic expression of fibrosis-related genes determined by RT-qPCR. Data are mean ± SEM. *p \u0026lt; 0.05 vs. WT (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/42c291efd9cc7fa3240a463b.jpg"},{"id":89349347,"identity":"2fec65bd-26a8-4b7d-a582-70a9ea9cd62a","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12419378,"visible":true,"origin":"","legend":"\u003cp\u003eHepatocyte TonEBP depletion attenuates hepatic inflammation in metabolic stress models. (A, B) Hepatic expression of inflammatory and fibrotic genes in WT and HKO mice fed an MCD diet for 8 weeks (A, \u003cem\u003en\u003c/em\u003e = 10) or an HFHC diet for 16 weeks (B, \u003cem\u003en\u003c/em\u003e= 8). (C–I) In HFD-fed mice (14 weeks; WT, \u003cem\u003en\u003c/em\u003e = 10; HKO, \u003cem\u003en\u003c/em\u003e = 9): hepatic inflammatory/fibrotic gene expression (C), body weight (D), fasting blood glucose (E), serum insulin (F), HOMA-IR (G), glucose tolerance test (H), and hepatic TonEBP mRNA expression (I). Data are mean ± SEM. *p \u0026lt; 0.05 vs. WT (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/e2801dd14cc6da53b615832a.jpg"},{"id":89349348,"identity":"a17c0195-77cb-48f6-ac60-956134b5192b","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":12809783,"visible":true,"origin":"","legend":"\u003cp\u003eHepatocyte TonEBP promotes neutrophil and macrophage infiltration, in part by ELR⁺ CXC chemokine induction. (A, B) Representative IHC and IF images showing MPO⁺ neutrophils and F4/80⁺ macrophages in livers from WT and HKO mice fed an MCD diet (A) or an HFHC diet (B). Quantification shown below. Scale bars: IHC, 25 μm; IF, 100 μm. (C) Serum CXCL1 and CXCL2 levels in WT and HKO mice (MCD, \u003cem\u003en\u003c/em\u003e = 10). (D, E) \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2 \u003c/em\u003emRNA levels in primary human hepatocytes (PHHs) treated with BSA or palmitate (PA) at varying concentrations (D) or times (E). (F–H) Chemokine mRNA levels in PHHs transfected with control or TonEBP siRNAs and treated with BSA or PA. (I) Chemokine protein levels in HepG2 cell culture medium after PA stimulation. (J, K) Neutrophil chemotaxis toward conditioned medium (J) or after neutralizing antibody pretreatment (K). Data are mean ± SEM or SD as indicated. *p \u0026lt; 0.05; #p \u0026lt; 0.05 vs. control (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/e3a02e9ab4b2397ff79d7afb.jpg"},{"id":89349351,"identity":"f681b234-000f-41c2-8c97-32d19bb0bd0d","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":10158167,"visible":true,"origin":"","legend":"\u003cp\u003eTonEBP is required for NF-κB recruitment to \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e promoters. (A, B) Luciferase reporter assays in HepG2 cells with TonEBP knockdown using wild-type (WT) (A) or κB mutant (κBmt) (B) promoter constructs for \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e, treated with BSA or PA. (C, D) \u0026nbsp;ChIP-qPCR analysis of TonEBP (C) and NF-κB p65 (D) binding to κB regions of the chemokine promoters after PA treatment. (E) Co-immunoprecipitation of TonEBP and p65 following PA treatment. (F, G) p65 ChIP-qPCR after TNFα (F) or H₂O₂ (G) stimulation. (H, I) Luciferase activity of WT and κBmt promoter constructs after TNFα (H) or H₂O₂ (I) treatment. Data are mean ± SD. *p \u0026lt; 0.05; ns, not significant (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/38d026d609ff1096c26097f8.jpg"},{"id":89350163,"identity":"bed006d0-adc4-4da8-8e4d-d7ba7c5dfa3d","added_by":"auto","created_at":"2025-08-19 05:57:05","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":5537648,"visible":true,"origin":"","legend":"\u003cp\u003eDisruption of the TonEBP–NF-κB interaction mimics TonEBP deficiency. (A–C) HepG2 cells were pretreated with vehicle (Veh) or cerulenin (5 μM) for 1 h, followed by treatment with BSA or palmitate (PA, 0.3 mM) for 3 h (A), or 9 h (B, C). Co-immunoprecipitation showing reduced TonEBP–p65 interaction in HepG2 cells pretreated with cerulenin (5 μM) before PA stimulation (A). \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003emRNA levels after cerulenin and PA treatment (B). Luciferase activity of chemokine promoters (C). (D, E) Chemokine mRNA levels after treatment with TNFα (10 ng/mL) (D) or H₂O₂ (1 mM) (E) for 6 h in the presence or absence of cerulenin. (F) Proposed model illustrating how hepatocyte TonEBP, through NF-κB interaction, promotes chemokine transcription, immune cell infiltration, and progression of steatohepatitis. Data are mean ± SD. *p \u0026lt; 0.05 vs. vehicle; #p \u0026lt; 0.05 vs. control (one-way ANOVA with Tukey’s test).\u003c/p\u003e","description":"","filename":"Fig.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/cede16b1c36f764d5bf76415.jpg"},{"id":89349381,"identity":"e1878577-6218-4674-a353-0fd0ae42665d","added_by":"auto","created_at":"2025-08-19 05:49:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":50470517,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/41dcac68-c592-4fc1-91f3-8b68c819a43c.pdf"},{"id":89349343,"identity":"069cf110-07dc-4c55-85fd-836cf27738c5","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3103714,"visible":true,"origin":"","legend":"Supplementary Information","description":"","filename":"Supplementarymaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/31e350297aa431a4e23f8562.pdf"},{"id":89349342,"identity":"c6bc2cd9-33eb-4520-87e2-1b8e73184fcf","added_by":"auto","created_at":"2025-08-19 05:49:05","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1334764,"visible":true,"origin":"","legend":"Uncropped WB data","description":"","filename":"UncroppedWBdata.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7352787/v1/6ed6f66efb7c8fa5bd7e0a43.pdf"}],"financialInterests":"There is no duality of interest","formattedTitle":"\u003cp\u003eHepatocyte TonEBP promotes metabolic stress-induced hepatic fibroinflammation involving transcriptional activation of ELR\u003csup\u003e⁺\u003c/sup\u003e CXC chemokines\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMetabolic dysfunction-associated steatohepatitis (MASH), a progressive form of metabolic dysfunction-associated steatotic liver disease (MASLD), is characterized by hepatic steatosis, inflammation, and fibrosis. The transition from MASLD to MASH significantly increases the risk of cirrhosis, liver failure, and hepatocellular carcinoma (HCC), making it a major global health concern [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Despite advances in understanding the clinical features of MASH, the molecular mechanisms linking metabolic stress to hepatic fibroinflammation are multifactorial and remain incompletely understood. However, innate immunity plays a central role, with liver-resident macrophages (Kupffer cells) and recruited immune cells, such as macrophages and neutrophils, driving disease progression [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHepatocytes, the primary parenchymal cells of the liver, are essential for regulating hepatic metabolic functions and responding to metabolic stress [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In conditions of chronic metabolic overload, such as obesity or lipotoxicity, hepatocytes become key initiators of liver inflammation and fibrosis by releasing proinflammatory cytokines and chemokines that recruit immune cells, particularly neutrophils and macrophages [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These infiltrating immune cells further exacerbate the inflammatory and fibrotic environment, accelerating liver injury [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA critical regulator of cellular stress responses is tonicity-responsive enhancer-binding protein (TonEBP), also known as NFAT5. TonEBP is a stress-responsive transcription factor that integrates osmotic, metabolic, and inflammatory signals to regulate gene expression in a cell type- and context-dependent manner [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While TonEBP has been implicated in a variety of chronic conditions, including inflammation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], insulin resistance [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], adipose tissue dysfunction [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and oncogenesis [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], its role in hepatocytes, especially under metabolic stress, remains poorly defined.\u003c/p\u003e\u003cp\u003ePrevious studies have shown that TonEBP interacts with NF-κB, a central transcription factor regulating proinflammatory gene expression. In macrophages, TonEBP enhances NF-κB-dependent cytokine expression during inflammation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, whether TonEBP regulates inflammatory pathways in hepatocytes during metabolic stress has yet to be determined.\u003c/p\u003e\u003cp\u003eIn this study, we investigate the role of TonEBP in hepatic inflammation and fibrosis in the context of MASLD and MASH. Using hepatocyte-specific TonEBP knockout (HKO) mice, we examine the effects of TonEBP deletion on liver injury, inflammation, and fibrosis in steatosis and steatohepatitis models. We show that TonEBP is essential for chemokine-driven neutrophil and macrophage infiltration, and that its interaction with NF-κB regulates the transcriptional activation of ELR⁺ CXC chemokines. These findings highlight the TonEBP\u0026ndash;NF-κB axis as a critical mechanism in the progression of MASLD to MASH.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eHepatocyte TonEBP coordinates fibroinflammatory and metabolic gene programs under metabolic stress\u003c/h2\u003e\u003cp\u003eTo investigate the role of hepatocyte-intrinsic TonEBP in metabolic stress\u0026ndash;driven fibroinflammation, we generated hepatocyte-specific TonEBP knockout (HKO) mice (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and applied two dietary models: methionine- and choline-deficient (MCD) and high-fat, high-carbohydrate (HFHC) diets. The MCD diet induces steatosis, inflammation, hepatocellular ballooning, cell death, and progressive fibrosis, closely reflecting advanced histological features of human MASH [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It is widely used for reproducible analysis of disease-related transcriptional changes and pathway-level responses but does not induce obesity or insulin resistance. The HFHC diet, in contrast, produces milder yet progressive liver injury associated with obesity, insulin resistance, and fructose intake, more closely modeling the metabolic context of human MASLD/MASH [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Using both models allowed us to assess the contribution of hepatocyte TonEBP under distinct metabolic stress conditions.\u003c/p\u003e\u003cp\u003eIn MCD-fed mice, wild-type (WT) and HKO groups showed comparable weight loss (~\u0026thinsp;40%) and food intake (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;B, Fig. S2A). Steatosis and serum triglyceride levels were similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u0026ndash;D, Fig. S2B\u0026ndash;C), but Sirius Red staining revealed markedly reduced fibrosis in HKO livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE, Fig. S2D). Serum ALT, AST, and LDH were also significantly lower in HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, Fig. S2E). Hepatic expression of \u003cem\u003eTonEBP\u003c/em\u003e and 20 fibrosis-related genes linked to human MASH [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] was significantly decreased in HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG, Fig. S2F).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo explore transcriptional changes, we performed RNA-seq on liver tissue. Principal component analysis showed that HKO samples clustered with the control group fed a normal diet and were clearly separated from MCD-fed WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Differentially expressed genes (DEGs) analysis identified 5,325 DEGs between WT-CD and WT-MCD, and 822 DEGs between WT-MCD and HKO-MCD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). KEGG analysis revealed enrichment of fibrogenic and ECM-related pathways (\u0026lsquo;ECM\u0026ndash;receptor interaction,\u0026rsquo; \u0026lsquo;PI3K\u0026ndash;Akt signaling\u0026rsquo;) in WT-MCD, which were suppressed in HKO-MCD, while metabolic pathways downregulated by MCD were restored (Fig. S3A\u0026ndash;B). GO enrichment analysis supported these findings (Fig. S4A\u0026ndash;F). K-means clustering showed reduced expression of fibrosis-related clusters, including Cluster 5, in HKO livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u0026ndash;E, Fig. S5A\u0026ndash;B). KEGG analysis revealed enrichment of fibrogenic and ECM-related pathways (\u0026lsquo;ECM\u0026ndash;receptor interaction,\u0026rsquo; \u0026lsquo;PI3K\u0026ndash;Akt signaling\u0026rsquo;) in WT-MCD, which were suppressed in HKO-MCD, while metabolic pathways downregulated by MCD were restored (Fig. S3A\u0026ndash;B). GO enrichment analysis supported these findings (Fig. S4A\u0026ndash;F). K-means clustering showed reduced expression of fibrosis-related clusters, including Cluster 5, in HKO livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u0026ndash;E, Fig. S5A\u0026ndash;B). GSEA demonstrated downregulation of inflammatory and fibrotic pathways (\u0026lsquo;inflammatory response,\u0026rsquo; \u0026lsquo;TNFα signaling via NF-κB,\u0026rsquo; \u0026lsquo;epithelial\u0026ndash;mesenchymal transition\u0026rsquo;) and upregulation of metabolic programs (\u0026lsquo;oxidative phosphorylation,\u0026rsquo; \u0026lsquo;bile acid metabolism\u0026rsquo;) (Fig. S6A\u0026ndash;B). Mapping mouse DEGs to human orthologs confirmed conserved suppression of inflammatory/fibrotic signatures and restoration of metabolic pathways in HKO livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF\u0026ndash;G, Fig. S7).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next evaluated hepatocyte TonEBP in an obesity-associated setting using the HFHC model, which reflects Western dietary patterns high in cholesterol, saturated fats, and fructose [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. WT and HKO mice showed similar body weight, food intake, and water consumption during 16 weeks of feeding (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;C). HKO mice had significantly lower fasting glucose (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) and liver-to-body weight ratios (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Histology revealed reduced steatosis and fibrosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF\u0026ndash;G), with lower serum ALT, AST, and LDH (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Fibrosis-related genes were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eI).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese findings indicate that hepatocyte TonEBP is necessary for activation of inflammatory, fibrogenic, and metabolic stress\u0026ndash;responsive programs in both lipotoxic and obesity-associated injury.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHepatocyte TonEBP depletion attenuates hepatic inflammation across diverse metabolic stress models\u003c/h3\u003e\n\u003cp\u003eInflammation drives the progression from simple steatosis to MASH, fibrosis, and cirrhosis [\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. To determine the contribution of hepatocyte TonEBP, we examined inflammatory and immune-related gene expression in different metabolic stress models. In MCD-fed WT mice, chemokines (\u003cem\u003eCxcl1\u003c/em\u003e, \u003cem\u003eCxcl2\u003c/em\u003e, \u003cem\u003eCcl2\u003c/em\u003e), adhesion molecules (\u003cem\u003eIcam1\u003c/em\u003e), and cytokines (\u003cem\u003eTnfα\u003c/em\u003e, \u003cem\u003eIl1b\u003c/em\u003e) were strongly induced (Fig. S8A), matching the transcriptomic profiles of WT-MCD livers. This induction was significantly reduced in HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Similar suppression was seen in HFHC-fed HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the high-fat diet (HFD) model, which induces injury more gradually, HKO mice also showed reduced expression of these inflammatory markers after 14 weeks (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), without changes in body weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Reduced hepatic inflammation correlated with improved systemic metabolic outcomes: lower fasting glucose and insulin, reduced HOMA-IR, and improved glucose tolerance (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u0026ndash;H). TonEBP deletion efficiency was confirmed by reduced hepatic \u003cem\u003eTonEBP\u003c/em\u003e mRNA in HFD-fed HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI). These results demonstrate that hepatocyte TonEBP promotes hepatic inflammation in multiple metabolic stress settings and contributes to systemic insulin resistance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHepatocyte TonEBP promotes neutrophil and macrophage infiltration, in part by transcriptional activation of ELR⁺ CXC chemokines\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine whether reduced \u003cem\u003eMpo\u003c/em\u003e and \u003cem\u003eF4/80\u003c/em\u003e expression in HKO livers (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026ndash;B) reflected decreased immune cell infiltration, we performed histological analyses. IHC and IF revealed abundant MPO⁺ neutrophils and F4/80⁺ macrophages in WT livers under MCD and HFHC feeding, with a stronger response in MCD-fed mice (Fig. S9A\u0026ndash;B). In HKO mice, infiltration was markedly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;B, Fig. S9A\u0026ndash;B). Serum and hepatic levels of \u003cem\u003eCxcl1\u003c/em\u003e and \u003cem\u003eCxcl2\u003c/em\u003e, potent ELR⁺ CXC chemokines that attract neutrophils, as well as \u003cem\u003eCcl2\u003c/em\u003e, a chemokine that recruits macrophages, were also significantly lower in HKO mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u0026ndash;C, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe next tested whether TonEBP directly regulates chemokine expression. To this end, we treated primary human hepatocytes (PHHs) with palmitic acid (PA), a lipotoxic saturated fatty acid known to accumulate in metabolic liver disease [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. PHHs treated with PA showed dose-dependent induction of \u003cem\u003eCXCL8 (IL-8)\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e within 3 h, sustained up to 9 h (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u0026ndash;E), along with increased TonEBP protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). \u003cem\u003eCCL2\u003c/em\u003e transcripts were undetectable (Ct\u0026thinsp;\u0026gt;\u0026thinsp;35), suggesting that hepatocytes preferentially express neutrophil-attracting ELR⁺ CXC chemokines in response to lipotoxic stress. Since monocytes and macrophages can express \u003cem\u003eCXCR1\u003c/em\u003e and \u003cem\u003eCXCR2\u003c/em\u003e under inflammatory conditions, ELR⁺ CXC chemokines may also contribute to macrophage recruitment [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Based on this, we focused subsequent analyses on TonEBP-dependent regulation of ELR⁺ CXC chemokines. TonEBP knockdown using two independent siRNAs reduced TonEBP protein expression for up to 72 hours (Fig. S10A) and significantly decreased PA-induced expression of \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, \u003cem\u003eCXCL2\u003c/em\u003e, and \u003cem\u003eTonEBP\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG\u0026ndash;H). PA also induced \u003cem\u003eTNFα\u003c/em\u003e, confirming the proinflammatory effect of PA, which was attenuated by TonEBP knockdown (Fig. S10B\u0026ndash;D). Similar reductions in these chemokine mRNA were observed in PA-treated AML-12 mouse hepatocytes and HepG2 cells, a human hepatoma line (Fig. S10E\u0026ndash;F), indicating a conserved, hepatocyte-intrinsic role for TonEBP across species. siTon #1 was used in subsequent experiments. HepG2 cells, which showed consistent PA responses and high transfection efficiency, were used for mechanistic studies. TonEBP depletion also reduced secretion of IL-8, CXCL1, and CXCL2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI), and conditioned medium from TonEBP-depleted cells showed diminished HL-60 migration (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eJ, Fig. S11A). Neutralizing individual chemokines partially inhibited migration, with additive effects when combined with TonEBP knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK). Conversely, adenoviral overexpression enhanced PA-induced chemokine expression (Fig. S11B\u0026ndash;C).\u003c/p\u003e\u003cp\u003eWe also examined TNFα and H₂O₂, which enhance NF-κB activity and promote inflammatory gene expression in steatohepatitis [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Both stimuli increased TonEBP and chemokine expression in PHHs (Fig. S12A\u0026ndash;C), HepG2 (Fig. S12D\u0026ndash;F), and AML-12 cells (Fig. S12G\u0026ndash;I), and these effects were blocked by TonEBP knockdown. TonEBP promoter activity was also elevated (Fig. S12J). These data show that TonEBP promotes ELR⁺ CXC chemokine production under metabolic and inflammatory stress.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTonEBP is required for NFκB recruitment to\u003c/b\u003e \u003cb\u003eIL-8\u003c/b\u003e, \u003cb\u003eCXCL1\u003c/b\u003e, \u003cb\u003eand\u003c/b\u003e \u003cb\u003eCXCL2\u003c/b\u003e \u003cb\u003epromoters\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo determine whether TonEBP regulates \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e transcription, we performed luciferase reporter assays using their proximal promoters in HepG2 cells (Fig. S13A). PA increased promoter activity of \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e, which was reduced by TonEBP knockdown (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), and NF-κB\u0026ndash;driven reporter activity was decreased in TonEBP-deficient cells (Fig. S13B). Notably, the promoters do not contain a canonical TonEBP binding motif (Fig. S13C). Given that NF-κB is a key transcriptional regulator of these genes [\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and that TonEBP has been shown to potentiate TNFα transcriptional activity in macrophages by interacting with NF-κB p65 without directly binding the promoter [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], we investigated whether TonEBP facilitates NF-κB-dependent transactivation of PA-induced \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e in hepatocytes. Mutation of NF-κB binding sites abolished PA-induced activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB, Fig. S13A). ChIP-qPCR confirmed increased TonEBP occupancy at these promoters after PA, TNFα, or H₂O₂ stimulation (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, S13C, S14B\u0026ndash;C). TonEBP knockdown reduced PA-induce p65 recruitment (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD), and co-immunoprecipitation showed PA-dependent TonEBP\u0026ndash;p65 interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). p65 recruitment in response to TNFα or H₂O₂ was similarly diminished in TonEBP-deficient cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF\u0026ndash;G), and mutation of the NF-κB binding site abrogated promoter activation by both stimuli (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH\u0026ndash;I). These findings indicate that TonEBP facilitates NF-κB recruitment to these promoters under metabolic stress.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eDisruption of the TonEBP–NFκB interaction recapitulates TonEBP deficiency\u003c/h3\u003e\n\u003cp\u003eTo assess the functional significance of the TonEBP\u0026ndash;NF-κB interaction, we disrupted the complex using cerulenin, a known inhibitor of TonEBP\u0026ndash;NF-κB binding [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Co-immunoprecipitation confirmed that cerulenin impaired TonEBP\u0026ndash;p65 interaction in HepG2 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Cerulenin treatment significantly reduced PA-induced \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, \u003cem\u003eCXCL2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB), and \u003cem\u003eTNFα\u003c/em\u003e (Fig. S15) expression, and decreased promoter activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). Cerulenin also attenuated chemokine induction by TNFα and H₂O₂ (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD\u0026ndash;E). These effects mirrored those of TonEBP knockdown, confirming that the TonEBP\u0026ndash;NF-κB complex is essential for maximal inflammatory gene activation in hepatocytes under metabolic stress. A schematic model summarizing our findings is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF, illustrating how hepatocyte TonEBP, through interaction with NF-κB, promotes transcription of ELR⁺ CXC chemokines, thereby driving immune cell infiltration, hepatic inflammation, and progression of steatohepatitis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study identifies hepatocyte TonEBP as a central transcriptional regulator that links metabolic stress to hepatic fibroinflammation through induction of ELR⁺ CXC chemokines, including \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e. These chemokines are potent neutrophil chemoattractants and can also recruit macrophages under inflammatory conditions. We show that TonEBP acts in hepatocytes by forming a complex with NF-κB, enabling transcriptional activation of chemokine genes in response to lipotoxic, oxidative, and cytokine stress. This defines a hepatocyte-intrinsic mechanism by which metabolic stress drives immune cell infiltration and inflammation in metabolic liver diseases.\u003c/p\u003e\u003cp\u003eThe transition from MASLD to MASH is characterized by persistent inflammation with infiltration of neutrophils and macrophages [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which form crown-like structures associated with advanced fibrosis and worse outcomes. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These cells exacerbate liver injury by releasing reactive oxygen species, proinflammatory cytokines, and extracellular traps, thereby sustaining a pro-fibrogenic milieu [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In our models, hepatocyte-specific TonEBP deletion reduced both neutrophil and macrophage accumulation, accompanied by suppression of chemokine expression and fibroinflammatory gene programs. This effect was observed in both lipotoxic (MCD) and obesity-associated (HFHC) models, indicating a conserved role for TonEBP in metabolic stress\u0026ndash;induced hepatic inflammation.\u003c/p\u003e\u003cp\u003eChronic liver inflammation reflects coordinated interactions among hepatocytes, Kupffer cells, hepatic stellate cells (HSCs), and sinusoidal endothelial cells [25, 41\u0026minus;43]. Under metabolic stress, hepatocytes release chemokines and danger signals that activate Kupffer cells and HSCs. Activated Kupffer cells secrete cytokines to amplify inflammation, while HSCs differentiate into myofibroblasts, leading to extracellular matrix deposition. Our findings place hepatocyte TonEBP at the upstream point of this network: its deletion not only suppresses chemokine expression, but also reduces immune cell infiltration, fibrosis, and hepatocellular injury, highlighting the pivotal intrinsic role of hepatocytes in shaping the liver\u0026rsquo;s response to metabolic stress and inflammation. Notably, the protective effects of TonEBP deletion were consistently observed across multiple models of steatohepatitis, suggesting that this mechanism is conserved and broadly applicable, regardless of the specific metabolic or dietary challenge.\u003c/p\u003e\u003cp\u003eThe ELR⁺ CXC chemokines\u0026mdash; \u003cem\u003eIL-8\u003c/em\u003e, \u003cem\u003eCXCL1\u003c/em\u003e, and \u003cem\u003eCXCL2\u003c/em\u003e\u0026mdash;and \u003cem\u003eCCL2\u003c/em\u003e are clinically relevant in both animal models and human MASH, correlating with immune cell infiltration, disease activity, and fibrosis stage. Elevated serum IL-8 and CCL2 levels associate with advanced fibrosis and poor prognosis in MASH patients [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. IL-8 levels are particularly elevated in chronic liver diseases, including cirrhosis, and have been shown to be associated with macrophage accumulation in the liver [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Furthermore, \u003cem\u003eCXCR1\u003c/em\u003e expression is elevated in circulating monocytes from cirrhotic patients [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], which further suggests the clinical relevance of this chemokine signaling axis in disease progression. In our study, \u003cem\u003eCxcl1\u003c/em\u003e and \u003cem\u003eCxcl2\u003c/em\u003e serve as functional analogs of \u003cem\u003eIL-8\u003c/em\u003e in mice, mediating neutrophil recruitment. We demonstrate that TonEBP regulates the expression of these chemokines in hepatocytes, and its deletion results in reduced neutrophil migration \u003cem\u003ein vitro\u003c/em\u003e and immune cell infiltration \u003cem\u003ein vivo\u003c/em\u003e. Importantly, our study shows that TonEBP does not activate these promoters via its canonical DNA-binding motif, but by facilitating NF-κB p65 recruitment, thereby amplifying transcription. This was supported by loss-of-function (TonEBP knockdown) and pharmacologic disruption of the TonEBP\u0026ndash;NF-κB complex, both of which impaired chemokine induction and neutrophil chemotaxis. This finding extends previous studies showing that TonEBP activates NF-κB signaling in immune cells, demonstrating a similar cooperative effect in hepatocytes under metabolic stress.\u003c/p\u003e\u003cp\u003eOur study also highlights the potential of TonEBP as a therapeutic target for metabolic liver diseases. TonEBP is known to promote pro-inflammatory programs in various tissues, including adipose tissue and macrophages [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Here, we extend its role to hepatocytes, identifying the TonEBP\u0026ndash;NF-κB complex as a key integrator of metabolic and inflammatory signals that converge on chemokine gene regulation. Inhibition of this axis attenuates immune cell infiltration and fibrosis, supporting the idea that TonEBP may be a viable therapeutic target for neutrophil-dominant MASH phenotypes.\u003c/p\u003e\u003cp\u003eSeveral limitations should be considered. First, while we observed reduced neutrophil infiltration and chemokine expression, the functional properties of infiltrating neutrophils, such as ROS production and NET formation, were not assessed. Second, species-specific differences in chemokine repertoires, notably the absence of IL-8 in mice, may limit the direct translation of our findings to humans. Third, although TonEBP deletion improved glucose metabolism in both HFHC and HFD models, insulin signaling in peripheral tissues was not evaluated. Finally, clinical validation using patient-derived samples is essential to confirm the relevance of our findings in human MASLD/MASH.\u003c/p\u003e\u003cp\u003eIn conclusion, TonEBP emerges as a key hepatocyte-intrinsic regulator of chemokine-driven inflammation and fibrosis in metabolic liver diseases. Targeting the TonEBP\u0026ndash;NF-κB axis represents a promising therapeutic approach for treating MASH and other metabolically driven liver diseases.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eAnimal studies\u003c/h2\u003e\u003cp\u003eMale C57BL/6J mice (7\u0026ndash;8 weeks) were used in all experiments. All animal studies were conducted using male C57BL/6J mice aged 7\u0026ndash;8 weeks. Hepatocyte-specific TonEBP knockout (HKO) mice were generated by crossing \u003cem\u003eTonEBP\u003c/em\u003e\u003csup\u003e\u003cem\u003efl/fl\u003c/em\u003e\u003c/sup\u003e mice [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] with \u003cem\u003eAlb-Cre\u003c/em\u003e transgenic mice (Jackson Laboratory, Bar Harbor, ME) (Supplementary Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA). To validate hepatocyte-specific deletion, TonEBP protein levels were assessed in liver, kidney, spleen, and lung. TonEBP was selectively ablated in the liver of \u003cem\u003eCre\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e mice (Fig. S16A). Under chow diet (CD) conditions, no significant differences in body weight, liver weight, or fasting glucose were observed between \u003cem\u003eCre\u003c/em\u003e\u003csup\u003e\u003cem\u003e+\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eCre\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;\u003c/em\u003e\u003c/sup\u003e mice (Fig. S16B), indicating no baseline phenotype. Age-matched littermates were randomly assigned to experimental groups based on body weight and fed one of the following diets obtained from Research Diets (New Brunswick, NJ), each accompanied by a model-specific control diet: (1) MCD diet for 8 weeks; (2) HFHC diet for 16 weeks, with drinking water supplemented with high-fructose corn syrup (42 g/L total carbohydrates, composed of 55% fructose and 45% sucrose by weight; Sigma-Aldrich, St. Louis, MO); or (3) HFD (60% kcal from fat) for 14 weeks. Mice were euthanized for tissue collection, and liver injury, fibrosis, and inflammation were assessed using histological analysis, serum markers, and transcriptome analysis.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eHistology and Immunohistochemistry\u003c/h3\u003e\n\u003cp\u003eLiver tissues were fixed in paraformaldehyde, embedded in paraffin, and stained with Hematoxylin and Eosin (H\u0026amp;E) and Sirius Red for histological evaluation of liver fibrosis and inflammation. Immunohistochemistry (IHC) for MPO and F4/80 (neutrophil and macrophage markers) was performed using standard protocols. Fluorescence images were captured using a Cytation 7 imaging system (NFEC-2025-02-303179). Staining intensity and positive cell counts were quantified using ImageJ software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.nih.gov/ij/\u003c/span\u003e\u003cspan address=\"https://imagej.nih.gov/ij/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eGlucose tolerance test\u003c/h3\u003e\n\u003cp\u003eFollowing a 16-hour fasting period, mice were injected intraperitoneally with glucose (2 g/kg). Blood samples were collected at various time points and glucose levels were measured using a glucometer.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eImmunoblot and chemokine analyses\u003c/h2\u003e\u003cp\u003eProtein extraction and immunoblotting were performed using standard methods [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Protein concentrations were determined using the BCA assay (Pierce, Rockford, IL). Equal amounts of protein were separated by SDS-PAGE and probed with primary antibodies. HRP-conjugated secondary antibodies were used for detection via enhanced chemiluminescence (GE Healthcare, Buckinghamshire, UK). Primary antibodies used included anti-TonEBP [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], anti-NF-κB p65 (Abcam, #ab16502), and anti-Hsc70 (Rockland, #200-301-A28, Limerick, PA, USA).\u003c/p\u003e\u003cp\u003eThe levels of CXC chemokines Cxcl1 and Cxcl2 in mouse serum and cell culture media were quantified using ELISA kits (R\u0026amp;D Systems, Minneapolis, MN). IL-8 (CXCL8), CXCL1, and CXCL2 levels in human cell culture media were measured using Human Quantikine ELISA Kits (R\u0026amp;D Systems), following the manufacturer\u0026rsquo;s protocol.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eImmunoprecipitation assay\u003c/h2\u003e\u003cp\u003eTotal cell lysates were prepared using RIPA buffer on ice. Lysates were incubated overnight at 4\u0026deg;C with 5 \u0026micro;g of antibody under rotary agitation. Protein A/G agarose beads (40 \u0026micro;L, GE Healthcare) were then added and incubated for 2 h at 4\u0026deg;C. After centrifugation, the beads were washed with RIPA buffer. Immunoprecipitated proteins were eluted by adding 40 \u0026micro;L of sample buffer and boiling at 95\u0026deg;C for 5 min. Eluted samples were analyzed by immunoblotting using anti-TonEBP and anti-NF-κB p65 (Abcam, #ab16502) antibodies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eRNA-sequencing analysis\u003c/h2\u003e\u003cp\u003eRNA was extracted from liver tissues and processed for RNA sequencing on the Illumina HiSeq platform. Differential expression analysis and Gene Set Enrichment Analysis (GSEA) were performed using StringTie (v2.1.3b) and iDEP (v2.01) [49].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eCell culture, transfection, and adenovirus infection\u003c/h2\u003e\u003cp\u003ePrimary human hepatocytes (Lonza, Basel, Switzerland) were cultured on BioCoat Collagen I-coated plates (Corning, Steuben County, NY) using hepatocyte growth medium provided by Lonza. HepG2 cells (HB-8065; ATCC, Manassas, VA) were maintained in Eagle\u0026rsquo;s MEM supplemented with 10% fetal bovine serum (FBS). AML12 cells (CRL-2254; ATCC) were cultured in DMEM supplemented with 10% FBS, insulin (10 \u0026micro;g/mL), transferrin (5.5 \u0026micro;g/mL), selenium (5 ng/mL), and dexamethasone (40 ng/mL). HL-60 cells (CCL-240; ATCC) were cultured in RPMI 1640 medium with 10% FBS. All cells were maintained at 37\u0026deg;C in a humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e. Small interfering RNAs (siRNAs) were purchased from Integrated DNA Technologies (Coralville, IA). Human hepatocytes, HepG2, and AML12 cells were transfected with scrambled siRNA (siScr) or gene-specific siRNAs at equal concentrations using Lipofectamine RNAiMAX (Invitrogen, Carlsbad, CA) for 48 h. After transfection, cells were cultured in fresh medium, treated with indicated chemicals, and analyzed as described. For overexpression experiments, HepG2 cells were infected with adenovirus expressing TonEBP (Ad-TonEBP) or control empty vector (Ad-EV) at a multiplicity of infection (MOI) of 50 for 24 h.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003ePalmitate (saturated fatty acid) treatment in vitro\u003c/h2\u003e\u003cp\u003ePalmitate (PA) was conjugated to fatty acid-free bovine serum albumin (BSA) at a 6:1 molar ratio and added to the culture medium. Cells were treated with PA\u0026ndash;BSA or 0.5% BSA alone as a vehicle control for the indicated durations and concentrations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eReal-time PCR\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted using TRIzol\u0026reg; Reagent (Invitrogen), and cDNA was synthesized using M-MLV reverse transcriptase (Promega, Madison, WI). Quantitative real-time PCR was performed using a CFX384 Real-Time PCR Detection System (Bio-Rad, Hercules, CA). Gene expression was normalized to \u003cem\u003ecyclophilin A\u003c/em\u003e and calculated using the 2^\u0026minus;ΔΔCt method. Primer sequences are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eLuciferase reporter assay\u003c/h2\u003e\u003cp\u003eCells were transfected with promoter-driven firefly luciferase constructs along with Renilla luciferase as an internal control. After 24 h, cells were treated as indicated, lysed in Passive Lysis Buffer, and analyzed using a dual-luciferase reporter assay system (Promega).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eChromatin immunoprecipitation (ChIP)-qPCR\u003c/h2\u003e\u003cp\u003eHepG2 cells were treated as indicated. ChIP assays were performed using a commercial kit (Millipore, Bedford, MA). Cells were crosslinked with 1% formaldehyde, quenched with glycine, washed, and lysed in SDS lysis buffer. Chromatin was sonicated using a Bioruptor KRB-01 (BMS, Tokyo, Japan) to generate 400\u0026ndash;1000 bp DNA fragments. Immunoprecipitation was carried out overnight at 4\u0026deg;C using anti-TonEBP serum, anti-NF-κB p65 antibody (#510500, Thermo Fisher Scientific), normal rabbit serum, or normal rabbit IgG (ab171870, Abcam). DNA was purified using the QIAquick PCR Purification Kit (QIAGEN, Redwood, CA) and analyzed by qPCR. Primer sequences are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or standard error of the mean (SEM), as indicated. For comparisons between two groups, an unpaired two-tailed Student\u0026rsquo;s t-test was used. For comparisons involving more than two groups, one-way ANOVA followed by Tukey\u0026rsquo;s post hoc test was applied. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Analyses were performed using GraphPad Prism 10.0 (GraphPad Software, San Diego, CA).\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eDATA AVAILABILITY\u003c/h2\u003e\u003cp\u003eAll data supporting the conclusions in the paper are provided in the main text or the supplementary materials. Detailed datasets regarding RNA sequencing are available from the corresponding author upon reasonable request.\u003c/p\u003e\u003c/div\u003e\n\u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/h2\u003e\u003cp\u003e For animal studies, all experimental procedures were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of UNIST (UNISTACUC-20-27).\u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Research Foundation of Korea (NRF) funded by the Korean government (MSIT; Grant No. RS-2023-NR076466, RS-2024-NR00416052, RS-2025-00514468) and Ministry of Education (2019R1A6A1A10072987). This research was also supported by \"Regional Innovation Strategy (RIS)\" through NRF funded by the Ministry of Education (2023RIS-009).\u003c/p\u003e\u003ch2\u003eAUTHOR CONTRIBUTIONS\u003c/h2\u003e\u003cp\u003eJun Ho Lee, Hana Song, and Eun Jin Yoo contributed equally to writing the original draft, review \u0026amp; editing, conceptualization, investigation, data curation, validation, and visualization. Yeseul Jeong, Seung Mi Ko contributed to visualization, validation, and investigation. Go Woon Shin, Ji-Hyun Yun, and Mi-Kyoung Jang performed investigations and formal analysis. Gee Euhn Choi, Youngheun Jee, Minhyeok Kang, Jiwon Yang, Sung-Pyo Hur, Jong-Eun Park, Yunkyoung Lee, Hye-Kyung Park, and Whaseon Lee-Kwon provided resources and methodology. Hyug Moo Kwon and Soo Youn Choi supervised the project, reviewed \u0026amp; edited the manuscript, and secured funding. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYounossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat Rev Gastroenterol Hepatol. 2018;15:11\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBabu AF, Palomurto S, K\u0026auml;rj\u0026auml; V, K\u0026auml;kel\u0026auml; P, Lehtonen M, Hanhineva K, et al. Metabolic signatures of metabolic dysfunction-associated steatotic liver disease in severely obese patients. Dig Liver Dis. 2024;56:2103\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKazankov K, J\u0026oslash;rgensen SMD, Thomsen KL, M\u0026oslash;ller HJ, Vilstrup H, George J, et al. The role of macrophages in nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Nat Rev Gastroenterol Hepatol. 2019;16:145\u0026ndash;159.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHwang S, Yun H, Moon S, Cho YE, Gao B. Role of neutrophils in the pathogenesis of nonalcoholic steatohepatitis. Front Endocrinol (Lausanne). 2021;12:751802.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeex RCR, Watt MJ. Hepatokines: linking nonalcoholic fatty liver disease and insulin resistance. Nat Rev Endocrinol. 2017;13:509\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStefan N, Schick F, Birkenfeld AL, H\u0026auml;ring HU, White MF. The role of hepatokines in NAFLD. Cell Metab. 2023;35:236\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang X, Zheng Z, Caviglia JM, Corey KE, Herfel TM, Cai B, et al. Hepatocyte TAZ/WWTR1 promotes inflammation and fibrosis in nonalcoholic steatohepatitis. Cell Metab. 2016;24:848\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu C, Kim K, Wang X, Bartolome A, Salomao M, Dongiovanni P, et al. Hepatocyte Notch activation induces liver fibrosis in nonalcoholic steatohepatitis. Sci Transl Med. 2018;10:eaat0344.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchwabe RF, Tabas I, Pajvani UB. Mechanisms of fibrosis development in nonalcoholic steatohepatitis. Gastroenterology. 2020;158:1913\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi SY, Lee-Kwon W, Kwon HM. The evolving role of TonEBP as an immunometabolic stress protein. Nat Rev Nephrol. 2020;16:352\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYoo EJ, Oh KH, Piao H, Kang HJ, Jeong GW, Park H, et al. Macrophage transcription factor TonEBP promotes systemic lupus erythematosus and kidney injury via damage-induced signaling pathways. Kidney Int. 2023;104:163\u0026ndash;180.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi M, Kim YM, Koh JH, Park J, Kwon HM, Park JH, et al. Serum amyloid A expression in liver promotes synovial macrophage activation and chronic arthritis via NFAT5. J Clin Invest. 2024;134:e167835.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee HH, Jeong GW, Ye BJ, et al. TonEBP in myeloid cells promotes obesity-induced insulin resistance and inflammation through adipose tissue remodeling. Diabetes. 2022;71:2557\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee HH, Jeong GW, Ye BJ, Yoo EJ, Son KS, Kim DK, et al. TonEBP/NFAT5 promotes obesity and insulin resistance by epigenetic suppression of white adipose tissue beiging. Nat Commun. 2019;10:3536.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi SY. The roles of TonEBP in the DNA damage response: From DNA damage bypass to R-loop resolution. DNA Repair (Amst). 2024;140:103697.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee JH, Suh JH, Choi SY, Kang HJ, Lee HH, Ye BJ, et al. et al. Tonicity-responsive enhancer-binding protein promotes hepatocellular carcinogenesis, recurrence and metastasis. Gut. 2019;68:347\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee JH, Suh JH, Kang HJ, Choi SY, Jung SW, Lee-Kwon W, et al. Tonicity-responsive enhancer-binding protein promotes stemness of liver cancer and cisplatin resistance. EBioMedicine. 2020;58:102926.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee HH, Sanada S, An SM, Ye BJ, Lee JH, Seo YK, et al. LPS-induced NFκB enhanceosome requires TonEBP/NFAT5 without DNA binding. Sci Rep. 2016;6:24921.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMachado MV, Michelotti GA, Xie G, Almeida Pereira T, Boursier J, Bohnic B, et al. Mouse models of diet-induced nonalcoholic steatohepatitis reproduce the heterogeneity of the human disease. PLoS One. 2015;10:e0127991.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVacca M, Kamzolas I, Harder LM, Andreassen M, Eriksen MB, Borrebaek J, et al. An unbiased ranking of murine dietary models based on their proximity to human metabolic dysfunction-associated steatotic liver disease (MASLD). Nat Metab. 2024;6:1178\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJensen T, Abdelmalek MF, Sullivan S, Nadeau KJ, Green M, Roncal C, et al. Fructose and sugar: a major mediator of non-alcoholic fatty liver disease. J Hepatol. 2018;68:1063\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHwang S, He Y, Xiang X, Seo W, Kim SJ, Ma J, et al. Interleukin-22 ameliorates neutrophil-driven nonalcoholic steatohepatitis through multiple targets. Hepatology. 2020;72:412\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark I, Kim N, Lee S, Park K, Son MY, Cho HS, et al. Characterization of signature trends across the spectrum of non-alcoholic fatty liver disease using deep learning method. Life Sci. 2023;314:121195.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuby T, Gautier EL. Immune cell-mediated features of non-alcoholic steatohepatitis. Nat Rev Immunol. 2022;22:429\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeiseler M, Schwabe R, Hampe J, Kubes P, Heikenw\u0026auml;lder M, Tacke F. Immune mechanisms linking metabolic injury to inflammation and fibrosis in fatty liver disease - novel insights into cellular communication circuits. J Hepatol. 2022;77:1136\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHammerich L, Tacke F. Hepatic inflammatory responses in liver fibrosis. Nat Rev Gastroenterol Hepatol. 2023;20:633\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJoshi-Barve S, Barve SS, Amancherla K, Gobejishvili L, Hill D, Cave M, et al. Palmitic acid induces production of proinflammatory cytokine interleukin-8 from hepatocytes. Hepatology. 2007;46:823\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBence KK, Birnbaum MJ. Metabolic drivers of non-alcoholic fatty liver disease. Mol Metab. 2021;50:101143.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRigamonti E, Fontaine C, Lefebvre B, Duhem C, Lefebvre P, Marx N, et al. Induction of CXCR2 receptor by peroxisome proliferator-activated receptor gamma in human macrophages. Arterioscler Thromb Vasc Biol. 2008;28:932\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZimmermann HW, Seidler S, Gassler N, Nattermann J, Luedde T, Trautwein C, et al. Interleukin-8 is activated in patients with chronic liver diseases and associated with hepatic macrophage accumulation in human liver fibrosis. PLoS One. 2011;6:e21381.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDong W, Simeonova PP, Gallucci R, Matheson J, Fannin R, Montuschi P, et al. Cytokine expression in hepatocytes: role of oxidant stress. J Interferon Cytokine Res. 1998;18:629\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFromenty B, Roden M. Mitochondrial alterations in fatty liver diseases. J Hepatol. 2023;78:415\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElliott CL, Allport VC, Loudon JA, Wu GD, Bennett PR. Nuclear factor-kappa B is essential for up-regulation of interleukin-8 expression in human amnion and cervical epithelial cells. Mol Hum Reprod. 2001;7:787\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWood LD, Farmer AA, Richmond A. HMGI(Y) and Sp1 in addition to NF-kappa B regulate transcription of the MGSA/GRO alpha gene. Nucleic Acids Res. 1995;23:4210\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu Z, Neufeld H, Torlakovic E, Xiao W. Uev1A-Ubc13 promotes colorectal cancer metastasis through regulating CXCL1 expression via NF-кB activation. Oncotarget. 2018;9:15952\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eItoh M, Kato H, Suganami T, Konuma K, Marumoto Y, Terai S, et al. Hepatic crown-like structure: a unique histological feature in non-alcoholic steatohepatitis in mice and humans. PLoS One. 2013;8:e82163.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan M, Song E, Zhang Y, Zhang P, Huang B, Yan K, et al. Metabolic dysfunction-associated steatohepatitis detected by neutrophilic crown-like structures in morbidly obese patients: a multicenter and clinicopathological study. Research (Wash D C). 2024;7:0382.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFabre T, Barron AMS, Christensen SM, Asano S, Bound K, Lech MP, et al. Identification of a broadly fibrogenic macrophage subset induced by type 3 inflammation. Sci Immunol. 2023;8:eadd8945.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaragetti A, Da Dalt L, Moregola A, Svecla M, Terenghi O, Mattavelli E, et al. Neutrophil aging exacerbates high fat diet-induced metabolic alterations. Metabolism. 2023;144:155576.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu K, Wang FS, Xu R. Neutrophils in liver diseases: pathogenesis and therapeutic targets. Cell Mol Immunol. 2021;18:38\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKostallari E, Schwabe RF, Guillot A. Inflammation and immunity in liver homeostasis and disease: a nexus of hepatocytes, nonparenchymal cells and immune cells. Cell Mol Immunol. 2025; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41423-025-01313-7\u003c/span\u003e\u003cspan address=\"10.1038/s41423-025-01313-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGe C, Tan J, Dai X, Kuang Q, Zhong S, Lai L, et al. Hepatocyte phosphatase DUSP22 mitigates NASH-HCC progression by targeting FAK. Nat Commun. 2022;13:5945.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoft A, Alfaro AJ, Schmidt SF, Pedersen FB, Terkelsen MK, Puglia M, et al. Liver-fibrosis-activated transcriptional networks govern hepatocyte reprogramming and intra-hepatic communication. Cell Metab. 2021;33:1685\u0026thinsp;\u0026ndash;\u0026thinsp;700.e9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGlass O, Henao R, Patel K, Guy CD, Gruss HJ, Syn WK, et al. Serum Interleukin-8, Osteopontin, and Monocyte Chemoattractant Protein 1 Are Associated With Hepatic Fibrosis in Patients With Nonalcoholic Fatty Liver Disease. Hepatol Commun. 2018;2:1344\u0026ndash;1355.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eK\u0026uuml;per C, Beck FX, Neuhofer W. Generation of a conditional knockout allele for the NFAT5 gene in mice. Front Physiol. 2015;5:507.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahmood T, Yang PC. Western blot: technique, theory, and trouble shooting. N Am J Med Sci. 2012;4:429\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiyakawa H, Woo SK, Dahl SC, Handler JS, Kwon HM. Tonicity-responsive enhancer binding protein, a rel-like protein that stimulates transcription in response to hypertonicity. Proc Natl Acad Sci U S A. 1999;96:2538\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGe SX, Son EW, Yao R. iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics. 2018;19:534.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"MASLD, MASH, hepatocyte, TonEBP, inflammation, fibrosis, chemokines","lastPublishedDoi":"10.21203/rs.3.rs-7352787/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7352787/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMetabolic dysfunction-associated steatohepatitis (MASH), a progressive stage of metabolic dysfunction-associated steatotic liver disease (MASLD), is characterized by liver inflammation, fibrosis, and hepatocyte injury. Despite its clinical relevance, the molecular mechanisms linking metabolic stress to hepatic fibroinflammation remain poorly understood. In this study, we identify Tonicity-Responsive Enhancer-Binding Protein (TonEBP) as a key stress-responsive transcription factor that mediates the link between metabolic overload and liver inflammation in non-malignant hepatocytes. Using hepatocyte-specific TonEBP knockout (HKO) mice, we demonstrate that TonEBP deletion reduces liver injury, inflammation, and fibrosis in MASH and steatosis models. Mechanistically, TonEBP recruits nuclear factor-κB (NF-κB) to ELR⁺ CXC chemokine gene promoters, promoting neutrophil and macrophage recruitment. These findings underscore the hepatocyte-intrinsic TonEBP/NF-κB axis as a critical driver of immune cell infiltration and fibroinflammation in MASLD progression, revealing its pivotal role in the pathophysiology of liver disease. By highlighting this axis, we provide new insight into the molecular mechanisms that govern the transition from steatosis to steatohepatitis, emphasizing the importance of TonEBP in regulating inflammatory pathways within hepatocytes.\u003c/p\u003e","manuscriptTitle":"Hepatocyte TonEBP promotes metabolic stress-induced hepatic fibroinflammation involving transcriptional activation of ELR⁺ CXC chemokines","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 05:49:00","doi":"10.21203/rs.3.rs-7352787/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"transferred","content":"Cell Death Discovery","date":"2025-08-20T01:10:37+00:00","index":"","fulltext":""},{"type":"decision","content":"Reject before peer review","date":"2025-08-18T08:10:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cell Death \u0026 Differentiation","date":"2025-08-12T12:22:00+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2025-08-12T09:35:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-12T09:35:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-12T07:42:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cell-death-discovery","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"cddiscovery","sideBox":"Learn more about [Cell Death Discovery](http://www.nature.com/cddiscovery/)","snPcode":"41420","submissionUrl":"https://mts-cddiscovery.nature.com/","title":"Cell Death Discovery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9660b2da-09e6-4ea8-a9c5-740f129e757b","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53354158,"name":"Biological sciences/Genetics/Gene expression"},{"id":53354159,"name":"Health sciences/Medical research/Preclinical research"},{"id":53354160,"name":"Biological sciences/Genetics/Gene regulation"},{"id":53354161,"name":"Health sciences/Pathogenesis/Inflammation"},{"id":53354162,"name":"Health sciences/Diseases/Metabolic disorders"}],"tags":[],"updatedAt":"2026-03-15T07:07:55+00:00","versionOfRecord":{"articleIdentity":"rs-7352787","link":"https://doi.org/10.1038/s41420-026-02978-3","journal":{"identity":"cell-death-discovery","isVorOnly":false,"title":"Cell Death Discovery"},"publishedOn":"2026-02-26 05:00:00","publishedOnDateReadable":"February 26th, 2026"},"versionCreatedAt":"2025-08-19 05:49:00","video":"","vorDoi":"10.1038/s41420-026-02978-3","vorDoiUrl":"https://doi.org/10.1038/s41420-026-02978-3","workflowStages":[]},"version":"v1","identity":"rs-7352787","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7352787","identity":"rs-7352787","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}