FBP1 as a key regulator of focal adhesion kinase-mediated hepatic stellate cell activation: Multi-omics and experimental validation

Abstract

BACKGROUND

Inhibiting hepatic stellate cell (HSC) activation is a key therapeutic strategy in liver fibrosis (LF). During activation, aerobic glycolysis is upregulated to meet increased energy demands. Although focal adhesion kinase (FAK) has been implicated in regulating HSC glycolysis, its precise role in activation remains unclear.

AIM

To investigate the effects of FAK and fructose-1, 6-bisphosphatase 1 (FBP1) on LF through the modulation of aerobic glycolysis in HSCs.

METHODS

Eighteen mice were randomly assigned to three groups: Control, carbon tetrachloride (CCl₄)-induced LF, and CCl₄ with FAK inhibitor treatment. Liver tissues were analyzed using transcriptomic and proteomic sequencing. Differential gene expression, Mfuzz clustering, and protein interaction network analyses identified key regulatory factors. Immunohistochemistry (IHC) and Western blot (WB) analysis were used to assess FAK and FBP1 expression, along with glycolysis-related enzymes. The migratory behavior of HSCs was evaluated using Transwell migration and scratch assays.

RESULTS

Transcriptomic and proteomic analyses revealed significantly reduced FBP1 expression in CCl₄-induced fibrosis, which was restored upon FAK inhibition. Histological staining (hematoxylin and eosin, Masson’s trichrome, Sirius red) confirmed reduced fibrosis following FAK inhibition. WB analysis demonstrated suppression of glycolysis-related enzymes. In LX-2 cells, FAK inhibition attenuated HSC activation and glycolysis while upregulating FBP1. Exogenous recombinant FBP1 inhibited HSC activation and glycolysis. Transwell and scratch assays showed that FBP1 significantly impaired HSC migration. In addition, WB and IHC analyses confirmed lower FBP1 expression in fibrotic liver tissues from patients compared to healthy controls.

CONCLUSION

FAK inhibitors and increased FBP1 expression inhibit aerobic glycolysis in HSCs, thereby improving LF. Thus, FAK and FBP1 may be potential targets for LF treatment.

Key Words: Liver fibrosis; Hepatic stellate cells; Focal adhesion kinase; Aerobic glycolysis; Fructose-1,6-bisphosphatase

Core Tip: In this study, we showed that focal adhesion kinase (FAK) inhibitors suppress hepatic stellate cell (HSC) activation and aerobic glycolysis, thereby alleviating liver fibrosis (LF). Fructose-1, 6-bisphosphatase 1 (FBP1) inhibits HSC activation and migration by regulating aerobic glycolysis. FAK can affect the expression of FBP1. Therefore, both FAK and FBP1 may serve as potential therapeutic targets for LF.

INTRODUCTION

Liver fibrosis (LF) represents a universal histopathological consequence of chronic hepatopathies, with its progression to hepatic cirrhosis constituting a major determinant of global disease burden and all-cause mortality[1,2]. A key driver of fibrosis is the activation of hepatic stellate cells (HSCs), which acquire proliferative, migratory and contractile properties that promote extracellular matrix deposition and fibrosis progression[3-5].

HSC activation is accompanied by metabolic reprogramming, resembling shifts observed in cancer cells. Even under aerobic conditions, activated HSCs enhance glycolysis to meet heightened energy demands[6-9]. However, the regulatory mechanisms governing glycolytic and gluconeogenic gene expression during HSCs activation remain poorly understood.

Focal adhesion kinase (FAK) regulates cell signaling and responses to external stimuli[10-12]. In cancer cells, FAK enhances aerobic glycolysis by upregulating glycolytic enzymes, facilitating pyruvate-to-lactate conversion to support rapid proliferation[13]. FAK has also been implicated in HSC activation and fibrosis progression[14]; however, its specific role in promoting glycolysis during HSCs activation remains unclear.

Fructose-1, 6-bisphosphatase 1 (FBP1), a rate-limiting enzyme in gluconeogenesis, not only facilitates glucose production but also suppresses glycolysis[15]. Accumulating experimental data indicate that FBP1 exerts tumor-suppressive effects through glycolysis suppression mediated by its cytoplasmic enzymatic function[16]. FBP1 downregulation has been linked to enhanced glycolysis and proliferation in liver and lung cancers[17-19]. However, its role in HSC activation and metabolic regulation in LF remains largely unexplored.

The hepatic tissues of mice from three experimental groups (control, LF model, and FAK inhibitor administration) were subjected to comprehensive transcriptomic profiling and proteomic profiling in the present study. Differential gene expression analysis, Mfuzz clustering, and protein interaction network analysis identified FBP1 as a key regulatory factor, exhibiting a negative correlation with FAK. Additional analysis demonstrated a significant decrease in FBP1 expression at both the transcript and protein levels in LF tissues. Western blot (WB) and immunohistochemistry (IHC) confirmed reduced FBP1 expression in liver tissues from both fibrotic mice and patients. Our experimental findings revealed that FBP1 significantly suppressed cellular activation, migration, and glycolytic metabolism in LX-2 cells. Both and in vitro and in vivo experiments further indicated that FAK modulated FBP1 expression, suggesting that FAK promotes HSC activation and glycolytic reprogramming by suppressing FBP1. In conclusion, our findings propose a model in which FAK drives HSC activation and glycolysis via FBP1 downregulation, offering novel directions and insights for future research in LF.

MATERIALS AND METHODS

Transcriptomic and proteomic sequencing

Liver tissue samples were collected from the three groups of mice. Upon verification of RNA integrity and purity, the isolated mRNA underwent controlled fragmentation and was utilized as a template for reverse transcription initiation with random hexamer oligonucleotides to generate first-strand cDNA. Second-strand cDNA was then synthesized and purified. The generated double-stranded cDNA was subjected to end repair, adenylation, and adapter ligation, followed by size selection. Finally, polymerase chain reaction amplification was performed to generate the cDNA library. For proteomic analysis, the workflow included protein extraction, peptide digestion, and data acquisition via liquid chromatography-tandem mass spectrometry. All experimental data underwent rigorous quality control and were analyzed using bioinformatics approaches. The software utilized was Cytoscape version 3.10.3 and R Studio 4.3.2 (https://cn.string-db.org). Transcriptomic and proteomic data were adjusted for false discovery rate (FDR) using the Benjamini-Hochberg method, with significance defined as adjusted P < 0.05. Differentially expressed genes (DEGs) and proteins were identified using |log₂fold change| > 1 and adjusted P < 0.05 (Benjamini-Hochberg FDR correction). Principal component analysis (PCA) was performed with R package ‘DESeq2’ after variance-stabilizing transformation. Raw RNA sequencing data were normalized by transcripts per million, and proteomic data were processed with MaxQuant (v 2.0.3) using label-free quantification.

Reagents and antibodies

Carbon tetrachloride (CCl₄; CAS No. 56-23-5) and corn oil were purchased from MedChemExpress. The following primary antibodies were purchased from Proteintech (Wuhan, China): lactate dehydrogenase A (LDHA) rabbit polyclonal antibodies (19987-1-AP), 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) rabbit polyclonal antibodies (13763-1-AP), FAK mouse monoclonal antibodies (66258-1-Ig), FBP1 mouse monoclonal antibodies (12842-1-AP), collagen type I (COL1) mouse monoclonal antibodies (66761-1-Ig), alpha smooth muscle actin (α-SMA) rabbit polyclonal antibodies (14395-1-AP), hexokinase 2 (HK2) mouse monoclonal antibodies (66974-1-Ig), pyruvate kinase M2 (PKM2) mouse monoclonal antibodies (60268-1-Ig), and β-actin (23660-1-AP). pY397-FAK (AF3398) rabbit polyclonal antibody was obtained from Affinity Biosciences (Cincinnati, OH, United States). Recombinant FBP1 protein (HY-P70275) and PF562271 were obtained from MedChemExpress. All other chemicals and reagents were obtained from Servicebio (Wuhan, China).

Human liver tissues

Non-tumorous liver tissue samples were obtained from liver transplant patients undergoing hepatobiliary surgery. Inclusion criteria: Patients aged 18-70 years with LF, diagnosed via imaging and confirmed by two pathologists. Exclusion criteria: Patients with diabetes mellitus, liver glycogen deposition, and other diseases affecting glucose metabolism were excluded. Patients who had used insulin or antidiabetic drugs in the past 3 months, and those with thyroid diseases and other diseases affecting metabolism were also excluded. The research received approval from the Biomedical Ethics Committee of Guizhou Medical University (Guizhou, China), and all procedures were conducted in accordance with the Declaration of Helsinki principles. Informed consent was obtained from all subjects and/or their legal guardian(s) for the use of human liver tissues.

Animal studies

The experimental protocols involving animals were performed in strict compliance with the Animal Research: Reporting of In Vivo Experiments (ARRIVE) criteria and received ethical clearance from the Institutional Animal Care and Use Committee at Guizhou Medical University (Ethical Approval No: 2403086). Adult male C57BL/6 mice were acquired from Tengxin Biotechnology (Chongqing, China) and maintained in specific pathogen-free facilities with the following regulated environmental parameters: Temperature maintained at 22 ± 2 °C and a 12/12-hour photoperiod. Six mice were housed per cage with soft bedding and acclimated for 2 days before the experiments. To induce LF, healthy male mice (8-11 weeks old, 20 ± 3 g) were intraperitoneally injected with a 10% CCl₄-corn oil solution (15 μL/g) three times a week for 6 weeks. Control mice received corn oil injections (15 μL/g) following the same schedule. Animals receiving PF562271 (administered orally at 30 mg/kg daily, suspended in methylcellulose solution) were maintained on a standard diet[20].

Hematoxylin and eosin, Masson, and Sirius red staining

Hematoxylin and eosin, Masson's trichrome, and Sirius red staining kits were purchased from Solarbio Life Sciences (Beijing, China), with all procedures performed according to the manufacturer's instructions. Briefly, hepatic tissues were fixed in formaldehyde, embedded in paraffin wax, and processed through a series of steps including rinsing and dehydration. Fibrosis and morphological changes were assessed under an orthogonal microscope (Axio Imager; Carl Zeiss, Oberkochen, Germany) at magnification.

IHC

Hepatic tissue specimens were immersion-fixed in 40 g/L paraformaldehyde solution, subsequently processed through graded ethanol dehydration, embedded in paraffin wax, and sectioned for IHC examination using standard histopathological protocols. Tissue specimens were incubated with primary antisera, and subsequently labeled with peroxidase-linked secondary antisera. For visualization, 3,3'-diaminobenzidine tetrahydrochloride was employed, with subsequent hematoxylin counterstaining. Images were obtained with the Zeiss Axioskop microscope (Carl Zeiss), and ImageJ software (National Institutes of Health, Bethesda, MD, United States) was used to quantify protein expression areas in various experimental groups.

Cell line culture and treatment

The LX-2 cell line, a human HSC model obtained from Pricella Biotechnology (Wuhan, China), was maintained in high-glucose Dulbecco’s Modified Eagle Medium (4.5 g/L) containing 10% heat-inactivated fetal bovine serum (Pricella). Cells were maintained at 37 °C in a humidified incubator with 50 mL/L carbon dioxide (CO₂). For inhibitor treatment, LX-2 cells were exposed to PF562271 (2.5 μM, 5 μM, and 10 μM) or HY-P70275 (12.5 ng/mL, 25 ng/mL, 50 ng/mL, and 100 ng/mL) for 48 hours. After treatment, the cells were collected for subsequent analyses (Supplementary material).

WB analysis

WB analysis was carried out following the method outlined earlier[14]. Briefly, total liver tissue or whole-cell lysates were extracted using RIPA buffer (Beyotime, Beijing, China). Equal protein amounts were separated via sodium dodecyl sulfate polyacrylamide gel electrophoresis, and transferred to PVDF membranes. Protein levels were normalized to β-actin as an internal loading control. Membranes were incubated overnight at 4 °C with primary antibodies, followed by incubation with secondary antibodies. Protein bands were visualized using enhanced chemiluminescence (Millipore, Burlington, MA, United States). The analysis was performed with ImageJ software (National Institutes of Health), following the provided protocol. Band intensities were normalized to β-actin for comparative analysis.

Scratch assay

LX-2 cells were plated in 6-well tissue culture plates at a density allowing 90% confluency. Mechanical wounding was then introduced using a sterile 200 μL pipette tip to create a standardized scratch. In the experimental design, vehicle control samples were administered dimethyl sulfoxide, and the treatment group was exposed to recombinant human FBP1 protein at a concentration of 100 ng/mL. Cell cultures were incubated in an optimal growth environment, with wound healing progression quantitatively assessed at predetermined intervals (0 hour, 24 hours, and 48 hours) following scratch induction. The distance between wound edges was quantified using a pre-calibrated optical system with standardized magnification parameters.

Transwell assay

Cell migration assays were conducted utilizing 8.0-µm pore polycarbonate membranes (Corning, Corning, NY, United States) in accordance with standardized protocols. The experimental protocols followed the manufacturer's guidelines. LX-2 cells (1 × 10⁵) were resuspended in serum-free medium and placed in the upper chamber, while complete medium was added to the lower chamber. After incubating for 48 hours at 37 °C with 50 mL/L CO₂, cells that migrated to the bottom of the membrane were fixed with 40 g/L paraformaldehyde for 15 minutes, stained with crystal violet for 20 minutes, and then examined under a light microscope.

Statistical analyses

Statistical analyses was performed with GraphPad Prism version 9.0 software (GraphPad Software, San Diego, CA, United States). Data that followed a normal distribution (Shapiro-Wilk, P > 0.05) were analyzed using the unpaired t-test (for two groups) or analysis of variance with Tukey’s post hoc test (for ≥ 3 groups). Values are presented as the mean ± SD from a minimum of three independent biological replicates. Statistical significance was set at P < 0.05.

RESULTS

Transcriptomic and proteomic sequencing of FAK inhibitor-treated mice revealed increases FBP1 expression

Transcriptomic and proteomic sequencing were performed in normal mice, LF model mice, and mice treated with the FAK inhibitor PF562271. PCA of the transcriptomic data revealed distinct gene expression patterns among the normal, CCl₄ and FAK inhibitor groups, with the first principal component (PC1) and PC2 explaining 59% and 8% of the variance, respectively (Figure 1A). Volcano plots identified significantly upregulated and downregulated genes in the CCl₄ group vs the control and in the FAK inhibitor group vs the CCl₄ group, confirming transcriptional alterations induced by CCl₄ and the FAK inhibitor (Figure 1B and C). Gene clustering using Mfuzz identified six clusters with differential expression across groups (Figure 1D). We selected Cluster 2, Cluster 4, and Cluster 5, which exhibited consistent expression trends between the treatment group and the control group, for subsequent analysis. Using Upset analysis, we identified 1321 overlapping genes consistently regulated across the normal vs CCl₄, and CCl₄vs PF groups, consistent with the clustering pattern (Figure 1E). Venn diagram analysis identified 1321 overlapping genes, with 13 glucose metabolism-related genes exhibiting altered expression (Figure 1F). Similarly, PCA of the proteomic data revealed distinct protein expression profiles across the three groups (PC1: 39.3%, PC2: 9.5%; Figure 2A). Volcano plots highlighted significant protein expression changes in the CCl₄ and FAK inhibitor groups compared to controls (Figure 2B and C). Mfuzz clustering identified six protein clusters with differential expression (Figure 2D). We selected Cluster 1, Cluster 3, and Cluster 4, which exhibited consistent expression trends between the treatment group and the control group, for subsequent analysis. Using Upset analysis, we identified 2187 overlapping genes consistently regulated across the normal vs CCl₄ and CCl₄ vs PF groups, consistent with the clustering pattern (Figure 2E). Venn diagram analysis identified 2187 overlapping genes, with 27 glucose metabolism-related genes exhibiting altered expression (Figure 2F). Finally, through integrated transcriptomic and proteomic analyses, we identified common DEGs associated with glucose metabolism. The genes were utilized to build a protein-protein interaction network in STRING, and key genes were subsequently identified using Cytoscape. Based on their significance and centrality, FBP1 was identified as a key protein upregulated in the FAK inhibitor-treated group (Figure 3). A list of key differential glucose metabolism genes is provided in Supplementary Table 1.

Figure 1 Transcriptomics analysis of differential gene expression. A: Principal component analysis (PCA) of normalized counts PCA showing gene expression variance among normal, carbon tetrachloride (CCl₄), and PF562271 (PF) conditions. The first principal component (PC1) explains 59% of the variance, and PC2 explains 8%; B: Volcano plot showing differentially expressed genes (DEGs) between the normal and CCl₄ groups. Significant genes (log2 fold change > 1 or < -1, P < 0.05) are highlighted; C: Volcano plot comparing gene expression between the CCl₄ and PF groups. Significant genes are marked similarly; D: Mfuzz clustering of gene expression. Six gene clusters showing expression changes across the normal, CCl₄, and PF groups, highlighting condition-specific gene regulation; E: UpSet plot showing the overlap of DEGs between comparisons; F: Venn diagram showing unique and shared DEGs between the normal vs CCl₄ and CCl₄vs PF groups.

Figure 2 Proteomics analysis of differential protein expression. A: Principal component analysis (PCA) of normalized protein counts PCA of protein expression across normal, carbon tetrachloride (CCl₄) and PF562271 (PF) conditions. The first principal component (PC1) explains 39.3% of variance, while PC2 explains 9.5%. The three conditions show clear separation; B: Volcano plot showing differentially expressed proteins between the normal and CCl₄ groups. Significant proteins (P < 0.05, log2 fold change > 1 or < -1) are highlighted; C: Volcano plot comparing the CCl₄ and PF groups. Significant proteins are marked, indicating differential expression between these two conditions (P < 0.05); D: Mfuzz clustering of protein expression profiles. Clusters 1, 3, and 4 are shown, highlighting distinct expression trends in normal, CCl₄, and PF conditions; E: UpSet plot showing overlaps of differentially expressed proteins between comparisons (normal vs CCl₄, CCl₄ vs PF) and clusters from Mfuzz analysis; F: Venn diagram showing overlap of differentially expressed proteins between the normal vs CCl₄ and CCl₄ vs PF groups. The diagram indicates unique and shared proteins across the conditions.

Figure 3 Identification of shared proteins between transcriptomics (purple) and proteomics (red) data. Nodes represent genes or proteins and the size of the node reflects the importance or centrality of each protein/gene in the network.

FAK inhibitor alleviates LF and aerobic glycolysis in mice

Histological analysis of liver tissues following administration of FAK inhibitor showed reduced inflammatory cell infiltration, preserved hepatic architecture and minimal portal area enlargement compared to the LF model group. Masson and Sirius red staining revealed significantly reduced COL deposition in periportal areas in the FAK inhibitor group (Figure 4A; P < 0.05). IHC analysis demonstrated that FBP1 expression was significantly lower in the LF model group compared to controls but was markedly increased following FAK inhibitor treatment (Figure 4B; P < 0.05). WB analysis further confirmed reduced α-SMA expression in the FAK inhibitor-treated group compared to the fibrosis model group, indicating decreased fibrosis progression (Figure 4C and D; P < 0.05). Additionally, glycolysis markers LDHA, PKM2, PFKFB3, and HK2 were downregulated, while FBP1 protein expression was significantly upregulated in the FAK inhibitor-treated group (Figure 4E and F; P < 0.05).

Figure 4 In mouse models of liver fibrosis, focal adhesion kinase inhibition ameliorates hepatic fibrosis. A: Liver tissues from mice in each group were stained with hematoxylin and eosin (HE) to observe inflammatory cell infiltration, cellular morphology, and lobular architecture; Masson’s trichrome staining and Sirius red staining were performed to assess fiber deposition; B: Immunohistochemical analysis was conducted to detect the expression of fructose-1,6-bisphosphatase 1 (FBP1) protein in the livers of mice from each group, and the number of positive cells in each group was statistically analyzed. Scale bar: 200 μm, 50 μm; C: Western blot (WB) analysis was used to detect the expression of liver fibrosis marker alpha smooth muscle actin (α-SMA), as well as focal adhesion kinase (FAK) and phosphorylated FAK (p-FAK) proteins, with β-actin as the internal control; D: Grayscale value analysis was performed, and statistical significance relative to the normal group or carbon tetrachloride (CCl₄) group was assessed; E: WB analysis was employed to detect the protein expression of aerobic glycolysis enzymes, including lactate dehydrogenase A (LDHA), hexokinase 2 (HK2), phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), pyruvate kinase M2 (PKM2), and FBP1, with β-actin as the internal control; F: Grayscale value analysis was conducted, and statistical significance relative to the normal group or CCl₄ group was evaluated. All data are from three independent samples. Data are represented as the mean ± SD. ^aNot significant; ^bP < 0.01, ^cP < 0.001, ^dP < 0.0001.

FAK inhibitor relieves LX-2 cell activation and aerobic glycolysis

LX-2 cells, an activated human HSCs line[21], were treated with varying concentrations of the FAK inhibitor PF562271 (2.5 μM, 5 μM, 10 μM) based on the IC₅₀ provided by MCE (MedChem Express). In comparison to the control group, administration of the FAK inhibitor markedly decreased the levels of α-SMA and COL1A1, which are biomarkers of hepatic fibrosis (Figure 5A and B; P < 0.05). Additionally, the expression of glycolytic enzymes HK2, PKM2, PFKFB3, and LDHA was downregulated, while FBP1 protein levels were significantly upregulated (Figure 5C and D; P < 0.05).

Figure 5 Focal adhesion kinase inhibitors can modulate the activation, migration, and aerobic glycolysis of hepatic stellate cells. A: After adding focal adhesion kinase (FAK) inhibitor at different concentrations (2.5 μM, 5 μM, 10 μM), proteins were extracted, and Western blot (WB) analysis was performed to detect the expression of liver fibrosis markers collagen type 1, alpha 1 (COL1A1) and alpha smooth muscle actin (α-SMA), as well as FAK and phosphorylated FAK (p-FAK) proteins, with β-actin serving as the internal control; B: Grayscale value analysis was conducted, and statistical significance relative to the control (dimethyl sulfoxide [DMSO]) group was assessed; C: WB analysis was employed to detect the protein expression of lactate dehydrogenase A (LDHA), hexokinase 2 (HK2), phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), pyruvate kinase M2 (PKM2), and fructose-1,6-bisphosphatase 1 (FBP1) in each group; D: Grayscale value analysis was performed for each proteome, and statistical significance relative to the control (DMSO) group was evaluated. All data are from three independent samples. Data are represented as the mean ± SD. ^aP < 0.05; ^bP < 0.01; ^cP < 0.001; ^dP < 0.0001; ^eNot significant.

Addition of recombinant FBP1 protein inhibits HSC activation and aerobic glycolysis in LX-2 cells

Our previous findings demonstrated that FAK inhibition alleviates LF and suppresses aerobic glycolysis in vivo, correlating inversely with FBP1 expression. FBP1 promotes gluconeogenesis and inhibits glycolysis in various tumor models[8,17]. As shown by Trivedi et al[22], metabolic reprogramming of activated HSCs involves increased glycolysis to support their transition into myofibroblasts, accompanied by downregulation of gluconeogenic enzymes such as FBP1. Based on the above screening results, we further validated the role of FBP1 in HSC activation. The concentration settings were designed on the basis of previous studies and Cell Counting Kit-8 results (Supplementary Figure 1)[23]. To examine the direct impact of FBP1 on HSC activation and aerobic glycolysis, recombinant FBP1 protein was administered to LX-2 cells at concentrations of 12.5 ng/mL, 25 ng/mL, 50 ng/mL, and 100 ng/mL. Compared to the control group, recombinant FBP1 significantly reduced the expression of hepatic fibrosis markers COL1A1 and α-SMA (Figure 6A and B) and inhibited glycolytic enzyme expression, including HK2, PKM2, PFKFB3, and LDHA (Figure 6C and D; P < 0.05). To assess the impact of recombinant FBP1 on the migration of activated HSCs, Transwell and scratch assays were performed. The Transwell assay revealed a marked decrease in the number of migrating cells compared to the control group (Figure 6E and F; P < 0.05). Similarly, the scratch assay revealed a larger wound area in the presence of recombinant FBP1, indicating impaired migratory ability (Figure 6G and H; P < 0.05).

Figure 6 Fructose-1,6-bisphosphatase 1 recombinant protein (HY-P70275) inhibits the activation, migration, and aerobic glycolysis of hepatic stellate cells. A: At concentrations of 12.5 ng/mL, 25 ng/mL, 50 ng/mL, and 100 ng/mL of fructose-1,6-bisphosphatase 1 (FBP1) recombinant protein, Western blot (WB) analysis was conducted to detect the expression of FBP1, collagen type 1, alpha 1 (COL1A1), and alpha smooth muscle actin (α-SMA) proteins, which are markers of liver fibrosis, with β-actin serving as the internal control; B: Grayscale value statistics were performed for each protein group, and statistical significance relative to the control (dimethyl sulfoxide [DMSO]) group was evaluated; C: At the same concentrations of FBP1 recombinant protein, WB analysis was used to detect the expression of aerobic glycolysis enzymes, including lactate dehydrogenase A (LDHA), hexokinase 2 (HK2), phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3), and pyruvate kinase M2 (PKM2), with β-actin as the internal control; D: Grayscale value analysis was conducted for each proteome, and statistical significance relative to the control (DMSO) group was evaluated; E: At a concentration of 100 ng/mL of FBP1 recombinant protein, the migration ability of LX-2 cells in each group was assessed using a wound healing assay; F: The cell migration area relative to the control (DMSO) group was evaluated; G: At a concentration of 100 ng/mL of FBP1 recombinant protein, the migration ability of LX-2 cells in each group was assessed using a Transwell migration assay, observed under a light microscope at 100 × magnification; H: The number of cells that migrated through the membrane of the Transwell chamber relative to the control (DMSO) group was assessed. All data are from three independent samples. Data are represented as the mean ± SD. ^aNot significant; ^bP < 0.01, ^cP < 0.001, ^dP < 0.0001.

FBP1 expression is reduced in human liver tissue from patients with LF

We collected 17 clinical samples, comprising 12 cases of LF and 5 cases of normal liver tissue. Detailed patient information is provided in the Supplementary Data, Supplementary Table 2. The expression levels of FBP1 were examined in hepatic tissues obtained from individuals with LF. IHC analysis revealed significantly lower FBP1 expression in fibrotic liver tissues compared to normal liver tissues (Figure 7A and B; P < 0.05). WB analysis further confirmed reduced FBP1 expression in patients with LF, with a statistically significant difference (Figure 7C and D; P < 0.05).

Figure 7 Decreased expression of fructose-1,6-bisphosphatase 1 in patients with liver fibrosis. A: Hepatic fructose-1,6-bisphosphatase 1 (FBP1) expression was examined by immunohistochemistry in patients with liver fibrosis and controls; B: Immunohistochemical staining was statistically analyzed to quantify the number of positive cells in each group; C: Expression of hepatic fibrosis marker alpha smooth muscle actin (α-SMA) and FBP1 was detected by Western blot analysis in patients with liver fibrosis and controls; D: Grayscale values of the respective protein bands were analyzed, and statistical significance relative to the normal group was assessed. All data are from three independent samples. Data are represented as the mean ± SD. ^aP < 0.05; ^bP < 0.001.

DISCUSSION

HSCs are the primary contributors to extracellular matrix deposition during chronic liver injury[24]. Preventing HSCs activation is a key strategy in the treatment of LF; however, no specific therapeutic agents are currently available, highlighting the significance of LF research.

Previous studies have indicated that activated HSCs depend on aerobic glycolysis for proliferation and survival, resembling the Warburg effect seen in cancer cells[25]. Our earlier findings indicated that inhibition of FAK suppresses HSC activation and aerobic glycolysis, thereby attenuating LF progression[14,20]. In this study, we conducted transcriptomic and proteomic sequencing to further investigate the role of FAK in promoting aerobic glycolysis during LF. Differential gene expression analysis, including Mfuzz clustering, revealed an inverse correlation between FBP1 and p-FAK protein expression.

FBPase is a key enzyme in gluconeogenesis, with two isoforms in humans: FBP1 and FBP2. FBP1 is primarily expressed in the liver and kidneys, while FBP2 is involved in muscle metabolism. FBP1 enzymatically catalyzes the hydrolytic cleavage of F-1,6-BP into F-6-P and an inorganic phosphate moiety through a substrate-specific dephosphorylation reaction[26,27]. Increasing evidence supports the tumor-suppressive role of FBP1 in various cancers, including gastric cancer, renal cancer and hepatocellular carcinoma, where it inhibits tumor cell proliferation and aerobic glycolysis[17,28,29]. Studies have demonstrated that FBP1 deficiency and subsequent hepatic metabolic dysregulation promote hepatocellular carcinoma through the senescence-associated secretory phenotype of HSCs[30]. Importantly, the role of FBP1 in LF and HSC activation has not been thoroughly explored, making it a novel focus of our study. FBP1 is frequently downregulated in various pathologies, including malignancies, and our transcriptomic analysis revealed that its expression increased following FAK inhibition. Further validation confirmed that FBP1 expression was downregulated in LF models. Previous studies suggest that the rapid proliferation of HSCs depends on glycolysis for ATP production[25]. As a key enzyme in gluconeogenesis, FBP1 downregulation may disrupt the balance of aerobic glycolysis in HSCs, further promoting their activation[22]. Consistent with these findings, our results demonstrate that FBP1 expression is significantly reduced in LF tissues and HSCs lines; notably, exogenous recombinant FBP1 suppresses HSCs activation, migration and aerobic glycolysis. These results suggest that increased FBP1 expression alleviates aerobic glycolysis of HSCs, thereby reducing their proliferation and activation. These findings suggest that restoring FBP1 expression may provide a therapeutic strategy for LF by reducing HSC activation and glycolytic activity, while also offering new insights into its role beyond its known function in gluconeogenesis. Inhibition of FAK may alleviate LF and inhibit aerobic glycolysis by regulating FBP1. Finally, we further analyzed liver tissue samples from clinical LF patients using IHC, and the results also showed that FBP1 was downregulated. Therefore, we believe that inhibition of FAK can improve LF by up-regulating FBP1, which provides a new idea for the treatment of LF in clinical practice. At the same time, this study provides new evidence that FBP1 is involved in the activation of HSCs in LF by regulating aerobic glycolysis. However, a limitation of our study is the lack of experiments where both FAK and FBP1 were simultaneously knocked down. Investigating whether FBP1 acts as a key factor in FAK-mediated activation and aerobic glycolysis in HSCs is an important future direction. The exact mechanism by which FAK regulates FBP1 expression remains unclear. Previous studies have shown that FAK upregulates c-Myc, thereby promoting transcription and lactate production of the key glycolytic enzyme enolase 1. As lactate is one of the important precursors of gluconeogenesis, we hypothesized that lactate may act as a substrate of FBP1, and FBP1 may reduce aerobic glycolysis of HSCs by promoting lactate metabolism. Further studies are needed to elucidate the precise molecular pathways involved in FAK-dependent regulation of FBP1 activity. In addition, the clinical samples used in this study were limited, and a large number of clinical samples of human LF are needed for analysis in the future.

CONCLUSION

FAK and FBP1 inhibit aerobic glycolysis in HSCs, thereby improving LF. FAK and FBP1 may be potential targets in the treatment of LF.