2.1 Multichip joint analysis was conducted to screen critical genes involved in HBV-HCC

To identify key genetic factors related to HBV-HCC, we accessed the chip datasets GSE55092 and GSE121248 from the Gene Expression Omnibus (GEO) database. After merging and analyzing the datasets, a total of 4840 genes were obtained. Filtering was carried out using a threshold of p < 0.05, resulting in the selection of 47 differentially expressed genes. Subsequently, volcano plots and heatmaps were generated to visualize the findings (Figure 1A,B). The proteins encoded by the 47 genes that showed differential expression underwent analysis for protein–protein interactions (PPI), resulting in the identification of 17 highly correlated key genes. Utilizing the cytoHubba plugin in Cytoscape, these genes were ranked based on their degree values in descending order. The top 10 genes included CDKN3, ANLN, PTGS2, SERPINE1, ACSL4, MAD2L1, SPP1, IDO2, THRSP, and TPR, with degree values of 7, 5, 5, 5, 4, 4, 3, 2, 2, and 2, respectively (Figure 1C). These genes have a pivotal function in the progression of hepatic fibrosis and HBV-HCC.

Gene set enrichment analysis (GSEA) revealed pathways that exhibited significant associations with the specified 10 genes, including SIGNALING_BY_ROBO_RECEPTORS, METABOLISM_OF_RNA, INFECTIOUS_DISEASE, SRP_DEPENDENT_COTRANSLATIONAL_PROTEIN_TARGETING_TO_MEMBRANE, and NERVOUS_SYSTEM_DEVELOPMENT (Figure 1D). Further literature review revealed a close correlation between HBV-HCC and the METABOLISM_OF_RNA pathway.^{32, 33}

2.2 Analysis of immune infiltration reveals the correlation between M2 macrophages and HBV-HCC

To explore the molecular basis for the influence of M2 polarization of macrophages on HBV-HCC, we conducted an immune infiltration analysis of the HBV-HCC dataset in the GEO database and analyzed the correlation between critical genes and M2 macrophages. Immunoinfiltration analysis results show that in HBV-HCC samples, there is a higher relative abundance of M2 macrophages (Figure 2A); M2 macrophages have a strong correlation with M1 macrophages (Figure 2B).

The above results indicate that immunoinfiltration analysis reveals a specific correlation between M2 macrophages and the occurrence and development of HBV-HCC.

2.3 Clinical experiments verify that ACSL4 regulates BA metabolism and FXR influences M2 macrophage polarization

In a multichip integrated analysis aimed at identifying key genes and pathway factors involved in HBV-HCC development, we conducted a thorough literature search. Our findings revealed that ACSL4,^{34, 35} CDKN3,^{36, 37} SERPINE1,^{38, 39} PTGS2,⁴⁰ ANLN,^{41, 42} SPP1,⁴³ TPR,⁴⁴ MAD2L1,⁴⁵ IDO2,⁴⁶ and THRSP⁴⁷ are implicated in metabolism. Subsequently, we gathered samples of cancerous tissue from HBV-HCC patients along with paired adjacent normal tissue for analysis.

Examination through RT-qPCR and Western blot assays revealed that in HBV-HCC tissues, the expression levels of ACSL4, CDKN3, SERPINE1, ANLN, MAD2L1, and THRSP were upregulated, while the expression levels of PTGS2, SPP1, TPR, and IDO2 were downregulated. Among these 10 genes, the expression level of ACSL4 is higher than other genes (Figure 3A,B). After reviewing the literature, it was found that the development and evolution of HBV-HCC are intricately linked to ACSL4 and BAs.^{34, 35, 48} We also performed survival analysis applying the GEPIA database (http://gepia.cancer-pku.cn/index.html). Within TCGA-LIHC (liver HCC) dataset, both the p value from the Logrank test and the significance test p value for HR indicated that the expression level of ACSL4 significantly impacts patient survival rates. High ACSL4 expression was significantly associated with poorer overall survival. Therefore, ACSL4 may serve as a potential prognostic marker guiding clinical treatment strategies (Figure S1J).

Therefore, we conducted PPI analysis of ACSL4 with proteins encoded by BA genes and FXR, revealing that ACSL4 interacts with BAs and FXR, suggesting a regulatory relationship (Figure 3C). Mass spectrometry results indicated elevated BA levels in HBV-HCC compared with normal tissues, while FXR mRNA and protein expression was downregulated as demonstrated by RT-qPCR and Western blot analysis in HBV-HCC compared with normal tissues (Figure 3D,F). Furthermore, correlation analysis between key genes, pathway factors, and BAs demonstrated a positive correlation between ACSL4 and BA levels (Figures 3G and S1).

The flow cytometry findings indicated increased expression of Arg1, CD163, and CD206 in HBV-HCC tissues in contrast to normal tissue samples (Figure 3H), suggesting the presence of polarized M2 macrophages in HBV-HCC. In addition, an investigation was performed to assess the correlation between ACSL4 mRNA expression levels and the markers indicating polarization toward M2 macrophages. A robust positive correlation was observed between ACSL4 expression levels and the expression levels of Arg1, CD163, and CD206 in the study results (Figure 3I). The above results indicate that ACSL4 may affect the polarization of M2 macrophages and lead to the occurrence of HBV-HCC by supervising the BAs metabolism and influencing the FXR expression.

2.4 ACSL4 regulates BAs and FXR to influence the occurrence and progression of HCC cells

To authenticate the regulatory function of ACSL4 in the initiation and progression of HCC through BAs and the FXR, we conducted experiments using human hepatic stellate cells (LX-2) to measure the levels of ACSL4, BAs, and FXR, as well as their effects on the proliferation, migration, and invasive potential of HCC cells. Examination was conducted on the presence of ACSL4 and FXR in HBV-infected hepatic stellate cells (HBV-LX-2) using Western blot.

The outcomes revealed an upsurge in ACSL4 protein expression in HBV-LX-2 cells as opposed to LX-2 cells, while the expression of FXR was downregulated (Figure 4A). ELISA detected human hepatitis B virus surface antigen (HBsAg), hepatitis B e antigen (HBeAg), and HBV DNA levels in LX-2 and HBV-LX-2 cells. It was observed that there was a rise in the presence of HBsAg, HBeAg, and HBV DNA in the HBV-LX-2 cells compared with LX-2 cells (Figure 4B,C). The concentrations of BAs in HBV-LX-2 cells were detected using mass spectrometry analysis, and it was found that the BA levels were increased in HBV-LX-2 cells relative to LX-2 cells (Figure 4D).

The results of Transwell and MTT assays demonstrate that in contrast with LX-2 cells, HBV-LX-2 cells exhibit enhanced proliferation, migration, and invasion ability (Figure 4E–G). In addition, the impact of ACSL4 overexpression or downregulation in HBV-infected LX-2 cells was assessed through RT-qPCR analysis. The results show that we successfully overexpressed or silenced ACSL4, with the most significant silencing efficiency observed in sh-ACSL4-1, paving the way for subsequent experiments (Figure 4H).

Through Western blot examination, it was observed that upregulation of ACSL4 led to a reduction in the levels of FXR, whereas downregulation of ACSL4 resulted in an elevation of FXR expression (Figure 4I). Mass spectrometry analysis showed that overexpression of ACSL4 increased the levels of BAs while silencing ACSL4 decreased the levels of BAs (Figure 4J). Transwell and MTT experiments showed that the upregulation of ACSL4 enhanced HCC cells’ proliferation, migration, and invasion abilities, while silencing ACSL4 diminished these abilities (Figure 4K–M).

The above results indicate that ACSL4's regulation of BAs and FXR pathways is instrumental in stimulating the proliferation, migration, and invasion behaviors of HCC cells.

2.5 FXR mediates M2 macrophage polarization to promote the emergence and progression of HCC

To examine the effects of FXR on the modulation of M2 macrophage polarization regarding the proliferative, migratory, and invasive potentials of hepatic cancer cells, we silenced or overexpressed FXR within the coculture setting with HBV-LX-2 and THP-1 macrophages. Western blot analysis confirmed successful FXR silencing or overexpression (Figure 5A). Flow cytometry results demonstrated that FXR silencing led to an upregulation of indicators for M2 macrophage polarization, including Arg1, CD163, and CD206, whereas FXR overexpression led to their downregulation (Figure 5B).

Furthermore, to investigate the impact of M2 macrophage polarization on the cellular capacities for proliferation, migration, and invasion in liver cancer, we treated the HBV-LX-2 and THP-1 macrophage coculture system with M2 polarization activators or inhibitors. The findings obtained through flow cytometry demonstrated that when contrasted with the DMSO control group, IL-4/IL-13, which are recognized as agents inducing M2 polarization, elevated the levels of markers associated with M2 macrophage polarization, including Arg1, CD163, and CD206, while PLX3397 (M2 polarization inhibitor) downregulated their expression (Figure 5C).

Transwell and MTT assays demonstrated that the proliferation, migration, and invasion capabilities of liver carcinoma cells were augmented by IL-4 and IL-13 contrasted with the DMSO control group, whereas PLX3397 weakened these abilities (Figure 5D–F).

These results suggest that silencing FXR can promote M2 macrophage polarization, which in turn enhances the proliferative, migratory, and invasive traits of liver malignancy cells.

2.6 ACSL4 regulates BA and FXR-mediated M2 macrophage polarization, promoting the occurrence and development of HBV-HCC

ACSL4 regulates BAs and FXR-mediated M2 macrophage polarization to promote the progression of HBV-HCC. Furthermore, following HBV infection, we utilized the OHO-2 adhesive system to coculture LX-2 cells and THP-1 macrophages (HBV-LX-2 + THP-1 macrophages).

The analysis of Western blot results showed that in comparison with the sh-NC + sh-NC group, the sh-ACSL4 + sh-NC group exhibited downregulation of ACSL4 expression and upregulation of FXR expression. When juxtaposed with the sh-ACSL4 + sh-NC group, ACSL4 expression levels did not vary within the sh-ACSL4 + sh-FXR group, although a decrease in FXR expression was evident (Figure 6A). Mass spectrometry analysis of BA levels revealed decreased BA levels in the sh-ACSL4 + sh-NC group as opposed to the sh-NC + sh-NC group. The BA levels in the sh-ACSL4 + sh-FXR group did not change when compared with the sh-ACSL4 + sh-NC group (Figure 6B).

Assessment through flow cytometry indicated a decrease in the expression of M2 macrophage polarization markers Arg1, CD163, and CD206 in the sh-ACSL4 + sh-NC group when contrasted with the sh-NC + sh-NC group. Compared with the sh-ACSL4 + sh-NC group, the levels of Arg1, CD163, and CD206 expression was increased in the sh-ACSL4 + sh-FXR group (Figure 6C). MTT and Transwell experiments showed that in contrast with the sh-NC + sh-NC group, a reduction in cell proliferation, migration, and invasion was observed in the sh-ACSL4 + sh-NC experimental group. Amplified cell proliferation, migration, and invasiveness were observed in the sh-ACSL4 + sh-FXR group contrasted with the sh-ACSL4 + sh-NC group (Figure 6D–F).

The previously mentioned data points to the conclusion that ACSL4 regulates BAs and FXR-mediated M2 macrophage polarization and promotes HCC cell proliferation, migration, and invasion.

2.7 Spontaneous mouse model of HBV-HCC (HBs-HepR mice)

The cell experiments of the spontaneous HBV-HCC mouse model (HBs-HepR mice) demonstrated the impact of overexpression or depletion of ACSL4 on the advancement of HBV-HCC. Therefore, we constructed a spontaneous HBV-HCC mouse model to verify further the effect of ACSL4 regulation on BA and FXR-mediated macrophage polarization in the molecular mechanism of HBV-HCC. HBs-Tg mice are transgenic mice that contain the human HBsAg gene. HBsAg is one of the leading indicators of HBV infection. We isolated hepatocytes (HBsAg+ liver cells) from HBs-Tg mice and transferred these cells to immune-competent Fah-deficient mice via splenic injection for liver cell reconstitution. Ultimately, we successfully generated HBs-HepR mice.^{49, 50}

After constructing the HBs-HepR mouse model, we found that relative to the control group, the ALT and AST serum levels in the model group mice were elevated throughout the injection process (Figure S2A,B). Furthermore, the levels of HBsAg, HBeAg, and HBV-DNA were upregulated (Figure S2C,D). H&E staining showed diffuse necrotizing inflammation in liver tissue sections of the model group mice, with visible infiltrates of mononuclear cells and deep infiltration of liver cells (Figure S2E). Evaluation of liver fibrosis involved the application of Sirius Red staining to examine collagen deposition/accumulation. The model group of mice exhibited severe fibrosis (Figure S2F). Therefore, we assessed the quantities of CD8+ T cells and the expression levels of IL-2, TNF-α, and IFN-γ in HBs-HepR mice.

Immunohistochemistry and ELISA outcomes indicated that, when contrasted with the control group, the quantity of CD8+ T cells in the model group of mice increased, while the levels of IL-2, TNF-α, and IFN-γ expression showed a reduction (Figure S2G-H). At 40 weeks of injection, we observed large liver tumor nodules (≥3 mm²) on the surface of the liver in the model group of mice, while only four mice in the control group showed 1 or 2 smaller tumor nodules (≤2 mm²). The cumulative quantity of tumor nodules in the liver increased after H&E staining of liver sections (Figure S2I).

The above results indicate that by transferring hepatocytes (HBsAg+ liver cells) to immunocompetent Fah-deficient mice via splenic injection, liver cell reconstruction could be induced, resulting in pathological liver damage, fibrosis and HCC, suggesting that we successfully constructed a spontaneous HBs-HepR mouse model.

2.8 ACSL4 regulates BA and FXR-mediated M2 macrophage polarization in the context of HBV-HCC progression, as confirmed by in vivo animal experiments

Experimental studies conducted on animals have validated that ACSL4 regulates BA and FXR-mediated M2 macrophage polarization, which contributes to the progression of HBV-HCC. To further investigate the effects of ACSL4 regulation on BA and FXR-mediated macrophage polarization in the molecular mechanisms of HBV-HCC, we treated HBs-HepR mice by silencing ACSL4 alone or silencing both ACSL4 and FXR simultaneously.

ELISA results showed that in contrast with the sh-NC + sh-NC group, the serum ALT and AST concentrations experienced a decline in the sh-ACSL4 + sh-NC group of mice. However, as opposed to the sh-ACSL4 + sh-NC group, the serum showed heightened levels of ALT and AST in the sh-ACSL4 + sh-FXR group of mice (Figure 7A,B).

Protein levels of ACSL4 in the liver tissue of mice were found to be lower in the sh-ACSL4 + sh-NC group when contrasted with the sh-NC + sh-NC group according to Western blot analysis, while FXR protein levels were increased. In comparison with the sh-ACSL4 + sh-NC group, no disparity was observed in the ACSL4 protein levels of mouse liver tissue in the sh-ACSL4 + sh-FXR group, but FXR protein levels were decreased (Figure 7C).

Analysis via mass spectrometry revealed a decrease in the quantity of BAs present in the liver tissue of mice within the sh-ACSL4 + sh-NC experimental group in contrast to the sh-NC + sh-NC control group. There was no change in BA levels in the liver tissue of mice in the sh-ACSL4 + sh-FXR group as opposed to the sh-ACSL4 + sh-NC group (Figure 7D).

Flow cytometry results showed that the sh-ACSL4 + sh-NC group showed decreased expression of M2 macrophage polarization markers Arg1, CD163, and CD206 in liver samples, whereas the sh-NC + sh-NC group did not exhibit such reductions; in contrast with the sh-ACSL4 + sh-NC group, the expression levels of M2 macrophage polarization markers Arg1, CD163, and CD206 in the liver tissues of mice in the sh-ACSL4 + sh-FXR group were upregulated (Figure 7E).

H&E staining results showed that when juxtaposed with the sh-NC + sh-NC group, the cellular inflammation and infiltration in the liver tissue of mice in the sh-ACSL4 + sh-NC group were alleviated. The sh-ACSL4 + sh-FXR group exhibited elevated levels of cellular inflammation and infiltration in the liver tissue, in contrast to the sh-ACSL4 + sh-NC group's presentation (Figure 7F).

Sirius Red staining analysis revealed a decrease in collagen deposition/fibrosis in the liver tissue of mice in the sh-ACSL4 + sh-NC group contrasted with the sh-NC + sh-NC group and an increase in collagen deposition/fibrosis in the liver tissue of mice in the sh-ACSL4 + sh-FXR group as opposed to the sh-ACSL4 + sh-NC group (Figure 7G).

The tumor volume and total number of tumor nodules in the liver tissue of mice in the sh-ACSL4 + sh-NC group were reduced when juxtaposed with the sh-NC + sh-NC group, while the tumor volume and total number of tumor nodules in the liver tissue of mice in the sh-ACSL4 + sh-FXR group were increased in comparison with the sh-ACSL4 + sh-NC group (Figure 7H).

In summary, the results demonstrate that ACSL4 regulates BAs and FXR-mediated M2 macrophage polarization, which is implicated in the onset and progression of HBV-HCC.

4.1 Public database chip data acquisition

Data on HBV infection leading to LIHC was retrieved from the GEO database, specifically from chip datasets GSE121248 and GSE55092, with sample sizes of 37 normal and 70 HBV-HCC, and 26 normal and 37 HBV-HCC, respectively.

Analysis of differential gene expression in these datasets was executed through the application of the “limma” package in the R software using standard control samples as references. Identification of DEGs was achieved with an adjusted p value filter threshold of <0.05. For visual representation, creation of expression heatmaps and volcano plots representing the DEGs was accomplished through the utilization of the “pheatmap” package in the R programming language. To identify common DEGs between the GSE121248 and GSE55092 datasets, the “VennDiagram” package in R software was employed, resulting in a comprehensive intersection of differentially expressed genes from both chip datasets.

The chip datasets GSE121248 and GSE55092 were subjected to data correction, and data merging was performed using a Perl script. Perform differential analysis on the merged dataset and conduct PPI analysis for the differentially expressed genes using the STRING website for further research.⁵⁹ Subsequently, the merged genes were subjected to GSEA enrichment analysis using GSEA_4.3.2 software to identify metabolic-related pathways.

4.2 Examination of infiltration by immune cells

Utilization of the CIBERSORT algorithm was implemented on datasets retrieved from the GEO database, using R software and known expression profiles of 22 immune cell-specific genes. The result was the relative abundance of varied immune cell types in the tissue samples. Filter the matrix data of diverse immune cell types in the organizational samples using Perl scripts, with the filtering condition as pvalueOpt < 0.05, followed by visualization analysis.⁶⁰

4.3 Collection of samples from HBV-HCC patients

Cancer and adjacent standard tissues were collected from 20 HBV-HCC patients, aged 40−65 years, averaging 55 years, undergoing surgery at our hospital. None received presurgery chemotherapy or radiotherapy. The adjacent normal tissues, obtained from the same patients, were situated at a distance exceeding 5 cm from the tumor margin. The gathered tissues were divided in two: one part was promptly preserved in liquid nitrogen, and the other was preserved in a 10% formaldehyde solution and subsequently encased in paraffin for sectioning. This study received approval from Shenzhen People's Hospital (NO. XYZ-2023-04-21), the Second Clinical Medical College, Jinan University's Clinical Ethics Committee and informed consent was obtained from the patients, aligning with the Helsinki Declaration's provisions.⁶¹

4.4 Cell culture and transfection

Cultivation of the human normal hepatic stellate cell line LX-2 (SNL-206) was carried out in DMEM (11965092, USA) containing 10% fetal bovine serum (FBS500-S; AusgeneX) under standard conditions of 37°C and 5% CO₂. The complete genome of the HBV C2 subtype and the 1.2-fold gene sequence of the pAAV/HBV1.2 plasmid was constructed.

pAAV-MCS (kl-zl-0986-01) was used as the vector to construct the pAAV/HBV1.2C2 recombinant using gene synthesis and homologous recombination (completed by BGI Genomics and Huada Gene Technology Co., Ltd.). Extract plasmids using the high-purity Midiprep Kit (ZP104-1; Zoman). To transfer pAAV/HBV1.2C2 into LX-2 cells, lipofectamine transfection reagent (L3000015; Invitrogen™) was utilized in the experiment. The supernatant was collected after 36 h. HBsAg expression in the cell culture supernatant of pAAV/HBV1.2C2-transfected cells using HBsAg diagnostic kit (TL16962; China) was detetcted.^{62, 63}

LX-2 cells infected with HBV were divided into several groups according to different treatment methods: oe-NC group (overexpression lentiviral negative control group), oe-ACSL4 group (overexpression lentiviral ACSL4 group), sh-NC group (shRNA lentiviral negative control group), and sh-ACSL4 group (shRNA ACSL4 lentiviral group). See Table S1 for knockdown sequences. The lentiviruses expressing overexpression and repression were constructed and provided by Shanghai Genomics, a Genemill Biological Engineering Co. Ltd. subsidiary in Shanghai, China.

LX-2 cells in the state of logarithmic growth were accumulated and then resuspended with a density of 5 × 10⁴ cells/mL. Placed in a six-well tray (2 mL per well), the suspension underwent overnight incubation at a temperature of 37°C. The addition of recombinant lentivirus (at a final concentration of 1 × 10⁸ TU/mL), with either silenced or overexpressed genes, took place in each well followed by a 24-h postinfection incubation period. The infection efficiency of GFP was observed using a fluorescence microscope, and cells exhibiting high infection efficiency were singled out for additional experimentation. This process was reiterated thrice.⁶²

4.5 Cooperative education system

The HBV-LX-2 and THP-1 macrophage (FSX6345) cell lines were cultivated as follows: THP-1 macrophage cells were cultivated in RPMI-1640 medium containing 10% FBS, 0.05 mM β-mercaptoethanol, and 1% P/S (CM-0233). These cells were kept at 37°C in a 5% CO₂ setting. To induce differentiation into macrophages, THP-1 macrophage cells underwent treatment with 100 ng/ml PMA (Sigma–Aldrich, USA) for a 24-h period.

Silence or overexpression of FXR was performed in HBV-LX-2 cells, followed by coculturing with THP-1 macrophage cells in a six-well Transwell coculture system (FCP060; BeyoGold). The groups were divided as follows: sh-NC group (silenced lentivirus control group), sh-FXR group (silenced FXR lentivirus group), oe-NC group (overexpression lentivirus control group), and or-FXR group (overexpression FXR lentivirus group).

After adding M2 polarization activators or inhibitors to THP-1 macrophage cells, coculture with HBV-LX-2 was performed with the following groups: DMSO group (control group, added with DMSO solution) (MFCD00002089), IL-4 (20 ng/mL, dissolved in DMSO solution)/IL-13 group (20 ng/mL, solution prepared in DMSO) (M2 polarization activators) (two activator products numbers SRP4137 and SRP4166), and PLX3397 (10 mmol/L, dissolved in DMSO solution) (M2 polarization inhibitor) (A15520).⁶⁴

After silencing ACSL4 alone and simultaneously silencing ACSL4 and FXR in HBV-LX-2 cells, coculturing was performed with THP-1 macrophage macrophage cells, and groups were as follows: sh-NC + sh-NC group (silencing lentiviral control group + silencing lentiviral control group), sh-ACSL4 + sh-NC group (silencing lentiviral ACSL4 + silencing lentiviral control group), and sh-ACSL4 + sh-FXR group (silencing lentiviral ACSL4 + silencing lentiviral FXR group). The FXR silencing sequence is shown in (Table S1).^{65, 66} The transfection method is the same as mentioned above.

4.6 Transwell experiments

The upper chamber of Transwell was filled with THP-1 macrophages (2 × 10⁴ cells per well) and RPMI1640 (R8758) medium. The lower well of the Transwell contained HBV-LX-2 cells cultured in DMEM medium supplemented with 10% FBS (FBS500-S; AusgeneX). After culturing for 24 h at 37°C, the cells in the upper chamber were gently swiped using a cotton swab. Then, 4% glutaraldehyde was applied to fix the cells, use 0.1% crystal violet for staining, then wash with PBS three times. Finally, the migration and invasion of HCC cells using an optical microscope were observed.^{62, 67}

4.7 MTT proliferation experiment

The experiment involved introducing 5 × 10³ HCC cells into a 24-well plate. Initially, each well was supplemented with 500 µL of 0.5 mg/mL MTT solution (T10182; Shangbao) and cultured at 37°C, 5% CO₂, for a duration of 2−4 h. Following this, the solution was discarded and 200−500 µL of DMSO were included in every well. After agitating on the oscillator for 20 min, spectrophotometric analysis was employed to assess cell absorbance at 570 nm. Every sample was replicated in a set of three wells.⁶⁸

4.8 Spontaneous HBV-HCC mouse model acquisition and other treatments

HBV transgenic mice C57BL/6J-TgN (AlblHBV) 44Bri (HBs-Tg) and Fah^−/− mice on a C57BL/6J background, as well as normal C57BL/6J mice, were sourced from Beijing Vecto Biotechnology Co., Ltd. SPF-grade animal facilities are utilized for housing all mice, ensuring they are situated in an environment with humidity levels of 60–65% and temperatures ranging between 22 and 25°C. The trial commenced subsequent to a week of acclimatization to the feeding regimen, during which the mice's health status was assessed ahead of the commencement of the experiment. The experimental procedures on animals adhere to the protocols set forth in the “Guide for the Care and Use of Laboratory Animals” and have been authorized by the Institutional Animal Ethics Committee.

The Fah^−/− mice were treated and divided into two groups, each containing six mice. The groups were as follows: control group (standard group) and model group (treated with HBsAg+ liver cells). HBsAg+ hepatocytes, extracted from HBs-Tg mice, were transplanted into immunocompetent receptor Fah^−/− mice in the model group. This transfer successfully generated HBs-HepR mice.⁴⁹

The isolation and culture of HBsAg+ liver cells involved several detailed steps. Initially, HBs-Tg mice were anesthetized by injecting 5% pentobarbital into their peritoneal cavity. Once anesthetized, the mice were positioned prone on the operating table, and their livers were surgically removed under sterile conditions. The excised livers were then thoroughly rinsed with cold PBS to eliminate any remaining blood. Following this, the livers were minced into smaller sections and subjected to digestion with a buffer solution infused with digestive enzymes (3-0002, OptiTDS™; Qiagen) for cell segregation. The separated cells underwent multiple cold PBS washes to remove any leftover enzymes. After discarding dead and fragmented cells, cultivation of primary cells was conducted in DMEM medium (11965092; USA) enriched with 10% FBS (FBS500-S; AusgeneX) at a consistent 37°C temperature under 5% CO₂ conditions.

Subsequently, 1 × 10⁶ hepatocyte suspension was injected into the spleen of Fah^−/− mice using a syringe to ensure the cells were accurately injected into the spleen rather than into the splenic vessels. Inject liver cells isolated from normal C57BL/6J mice into the control group. At 14 weeks, evaluation was conducted using methods such as testing the concentrations of ALT, AST, and HBV-DNA in blood samples, as well as assessing the count of CD8+ T cells and the expression levels of IL-2, TNF-α, and IFN-γ in tissue samples, the pathological changes in mouse liver, the fibrosis situation of collagen deposition/accumulation, and the condition of tumor nodules.^{10, 49}

The HBs-HepR mice were managed and classified into three groups, with six mice allocated to each group. The animal grouping is as follows: sh-NC + sh-NC group (silencing lentivirus control + silencing lentivirus control), sh-ACSL4 + sh-NC group (silencing lentivirus ACSL4 + silencing lentivirus control), sh-ACSL4 + sh-FXR group (silencing lentivirus ACSL4 + silencing lentivirus FXR). The titer of the slow virus is 1 × 1011 PFU. It was purchased from Jima Biology. The injection volume per mouse via the tail vein is approximately 50 µL. The therapy is given biweekly for a period of 7 weeks continuously.

Blood samples were gathered from groups of six mice at the 40-week mark for the assessment of ALT and AST enzyme concentrations. Liver tissue was also collected to assess BA levels, pathological changes, fibrosis, and nodules.^{10, 69}

4.9 RT-qPCR

After isolation using TRIzol (15596026; ThermoFisher, USA), the total RNA was converted into cDNA by employing the High-Capacity cDNA Reverse Transcription Kit (4368813; Invitrogen, USA). Using GAPDH as an internal reference, we conducted RT-PCR experiments on the ABI7500 quantitative PCR instrument (ABI, USA) using the SYBR Green reagent kit (K0222; Thermo Scientific). The PCR reaction mixture undergoes PCR amplification on a real-time fluorescence quantitative PCR device. Utilizing the 2^−ΔΔCt technique, the ultimate data underwent comprehensive analysis. The primer sequences are available in Table S2, with the primers being manufactured by Shanghai Biotech Co., Ltd.⁷⁰

4.10 Western blot

The extraction of total protein from cell groups was carried out with the protein extraction kit (ab113476; Abcam) and the protein concentration in the samples was assessed using the BCA assay kit (BCA1; Sigma–Aldrich). We prepared a 10% SDS-PAGE gel (P0012A; Biyun Biosciences Institute, Shanghai, China). The protein samples, 50 µg in each well, were loaded and electrophoresed under constant voltages of 80 and 120 V for 2 h. Then, we transferred the protein onto a PVDF membrane (ISEQ00010; Millipore, Billerica, MA, USA) employing a wet transfer method and subjected it to a constant current of 250 mA for 90 min. The PVDF membrane was treated by immersing it in TBST buffer with an addition of 5% skim milk powder for a time period of 2 h. The blocking solution was drained, washed once with TBST, and the primary antibody was added and incubated overnight at 4°C (refer to antibody details listed in Table S3). The membrane was then washed three times with TBST, each time for 10 min. Next, the goat anti-rabbit IgG was added to secondary antibody conjugated with horseradish peroxidase (HRP), ab6721, and incubated at ambient temperature for 60 min, and was washed three times with PBST, each time for 10 min. Finally, the membrane was immersed into the ECL reaction solution (MA0186-3; Meilunbio) for color development and was exposed in a dark box for autoradiography. Using GAPDH as a reference, the calculation of the protein's relative expression level involves assessing the grayscale value of the target band relative to the reference band.⁷¹

4.11 MS testing total BA levels

4.12 Intracellular ferrous ion detection

Intracellular total ferrous ions in living cells were detected using FerroOrange (10 µM). Following treatment with experimental compounds for a specified period, cells in 24-well culture plates were stained with FerroOrange in HBSS at 37°C, for 30 min. After three washes, intracellular FerroOrange fluorescence was captured using fluorescent microscopy.

4.13 ELISA detection

The expression levels of HBsAg (AD20522; ADANTI, China), HBeAg (AD21696; ADANTI), HBV-DNA (AD21848; ADANTI), IL-2 (AD40139; ADANTI), TNF-α (AD40104; ADANTI), and IFN-γ (AD40155; ADANTI) were detected in the supernatant of the culture medium and mouse liver tissues using ELISA kits. The samples and control samples were added separately to different wells, incubated with the enzyme-linked antibody (Ab-HRP) (NRE25-0.5 mL) at 37°C for 1 h, and washed with PBST five times. The reaction was halted after the incubation of 100 mL substrate solution in each well for 15 min. Analyzing the absorbance at 450 nm was carried out with a microplate reader (BIO-RAD, USA).⁶³

4.14 Flow cytometry

The detection of macrophage polarization markers Arg1 (17-3697-82, 1.0 µg/test), CD163 (12-1631-82, 0.25 µg/test), and CD206 (17-2061-82, 0.25 µg/test) was performed utilizing flow cytometry. The macrophages (1 × 10⁶) were stained following the manufacturer's guidelines, using the F4/80 monoclonal antibody (MA1-91124, 1/100; Thermo Fisher). This staining procedure assisted in the effective marking of the macrophages for the intended analysis. The collected data were subsequently analyzed, deploying the BD FACSMelody™ 4-Way Cell Sorter from BD.⁷⁰

4.15 Biochemical testing

As per the instructions outlined by the manufacturer, commercially available reagent kits were utilized for assessing the concentrations of ALT (BA1561; Shangbao) and AST (LZ-S01109; Lianzhu).⁷³

4.16 Histopathological analysis

Liver tissues were meticulously harvested from each group of mice and processed into 5 µm sections for subsequent staining. The tissue sections were initially subjected to hematoxylin (517-28-2; JiSheng Biotech) staining at room temperature for 10 min for the H&E staining process, followed by a rinse with running water lasting 30−60 s. Differentiation was conducted by immersing the sample in 1% hydrochloric acid solution for 30 s, followed by a subsequent rinse under tap water for 5 min. Eosin staining was applied at ambient temperature for 1 min. The sections were then sequentially dehydrated with graded alcohol (70, 80, 90, 95, and 100%) for 1 min each. After immersion in xylene with stone coal for 1 min and two rounds of 1-min clarification, the sections were sealed with neutral resin. Poststaining, examination of liver tissue sections was conducted with a light microscope (BX50; Olympus) for analyzing morphological changes or counts across different groups, aiming to discern specific pathological changes in the liver.⁷⁴

Sirius Red staining protocol: Liver tissue samples were exposed to a saturated solution comprising 0.1% Sirius Red and 0.1% picric acid for a duration of 1 h to facilitate the staining process. Collagen protein's distribution area was measured through the application of Image Pro Plus software (Media Cybernetics, Bethesda, MD), where four continuous images (magnification ×40) were captured for each slide.⁶⁹

Immunohistochemical analysis of mouse liver tissue embedded in paraffin was performed by using CD8 antibody (ab217344) at a dilution of 1/2000, followed by labeling with goat anti-rabbit IgG H-1L (HRP) (ab127896) at a dilution of 1/1000.^{75, 76}

4.17 Statistical analysis

The analysis of all data was conducted utilizing Statistical Package for the Social Sciences 26.0 software (IBM, USA). Continuous variables were expressed as mean ± standard deviation. The comparison of differences between two groups was carried out with a t-test, whereas differences among multiple groups were analyzed through one-way ANOVA. When p < 0.05, it indicates that the difference is statistically significant.