Abstract The intricate relationship between bile acid (BA) metabolism, M2 macrophage polarization, and hepatitis B virus‐hepatocellular carcinoma (HBV‐HCC) necessitates a thorough investigation of ACSL4's (acyl‐CoA synthetase long‐chain family member 4) role. This study combines advanced bioinformatics and experimental methods to elucidate ACSL4's significance in HBV‐HCC development. Using bioinformatics, we identified differentially expressed genes in HBV‐HCC. STRING and gene set enrichment analysis analyses were employed to pinpoint critical genes and pathways. Immunoinfiltration analysis, along with in vitro and in vivo experiments, assessed M2 macrophage polarization and related factors. ACSL4 emerged as a pivotal gene influencing HBV‐HCC. In HBV‐HCC liver tissues, ACSL4 exhibited upregulation, along with increased levels of M2 macrophage markers and BA. Silencing ACSL4 led to heightened farnesoid X receptor (FXR) expression, reduced BA levels, and hindered M2 macrophage polarization, thereby improving HBV‐HCC conditions. This study underscores ACSL4's significant role in HBV‐HCC progression. ACSL4 modulates BA‐mediated M2 macrophage polarization and FXR expression, shedding light on potential therapeutic targets and novel insights into HBV‐HCC pathogenesis. Keywords: ACSL4, bile acid metabolism, farnesoid X receptor, hepatitis B virus‐hepatocellular carcinoma, M2 macrophage polarization __________________________________________________________________ Molecular mechanisms of ACSL4‐mediated bile acid metabolism and nuclear receptor‐mediated M2 macrophage polarization in HBV‐HCC development. graphic file with name MCO2-5-e706-g002.jpg 1. INTRODUCTION The infection of hepatitis B virus (HBV) poses a significant worldwide public health challenge, as certain cases may progress to HBV‐related hepatocellular carcinoma (HBV‐HCC).[34] ^1 , [35]^2 , [36]^3 , [37]^4 Hepatocellular carcinoma (HCC) is a prevalent malignancy associated with a grave prognosis, especially in Asia.[38] ^5 , [39]^6 , [40]^7 , [41]^8 Although the promotion of the HBV vaccine has reduced the number of new infections, the incidence of HBV‐HCC continues to rise annually.[42] ^9 Understanding the pathological mechanisms of HBV‐HCC is a challenging task due to the complexity of HBV infection and its intricate interactions with liver cancer.[43] ^2 The elevated occurrence and fatality rates of HBV‐related liver cancer in clinical settings[44] ^10 make it crucial to study the disease progression and adverse prognosis in HBV‐HCC patients for effective HCC treatment. Research has shown that the involvement of M2 macrophages is pivotal in shaping the tumor microenvironment, with a significant focus on the initiation and advancement of liver malignancy.[45] ^11 , [46]^12 , [47]^13 , [48]^14 , [49]^15 Signals released by tumor cells and other immune cells can polarize macrophages into the M2 subtype, forming tumor‐associated macrophages. These M2 macrophages have been found to promote tumor growth and metastasis.[50] ^14 , [51]^16 , [52]^17 Bile acids (BAs), as essential digestive components secreted by the liver, also have notable implications in the pathogenesis of liver conditions and liver malignancies.[53] ^18 , [54]^19 , [55]^20 Research has shown that in pathological liver conditions, there are abnormal changes in the total BA levels in the body. Some of these BA alterations can impact the activity of specific BA receptors, subsequently influencing the occurrence and progression of HCC through mechanisms such as immune inflammation or cell apoptosis. For instance, the farnesoid X receptor (FXR), G protein‐coupled receptors 1, pregnane X receptor, constitutive androstane receptor, and sphingosine‐1‐phosphate receptor 2 have all been confirmed to affect the development of HCC through various pathways.[56] ^21 Recent studies have further elucidated the connection between BA metabolism and M2 macrophage polarization, although the underlying molecular mechanisms remain incompletely understood.[57] ^22 The enzyme acyl‐CoA synthetase long‐chain family member 4 (ACSL4), associated with fatty acid metabolism, has emerged as a key player in the progression of liver cancer in recent studies.[58] ^23 , [59]^24 ACSL4 regulates various biological processes, including fatty acid oxidation and synthesis, thereby influencing cell proliferation, migration, and invasion.[60] ^25 , [61]^26 , [62]^27 Simultaneously, the nuclear receptor FXR is also considered a crucial factor in regulating BA metabolism.[63] ^28 , [64]^29 , [65]^30 , [66]^31 However, the mechanism by which ACSL4 regulates BA metabolism through FXR and further impacts M2 macrophage polarization and liver cancer progression remains unclear. To gain a deeper understanding of how ACSL4 regulates BA metabolism and its impact on HBV‐HCC, this study plans to explore its mechanisms using bioinformatics analysis, in vitro cell experiments, and in vivo mouse models. The research aims to uncover the interactions between ACSL4, BAs, FXR, and M2 macrophage polarization, and how these factors collectively influence the occurrence and development of HBV‐HCC. The results of this study may provide fresh tactics and goals for thwarting and managing HBV‐HCC. In summary, by delving into the interaction between ACSL4 and BA metabolism, and how these interactions affect the occurrence and development of HBV‐HCC through FXR and macrophage polarization, this study will offer fresh perspectives into the intricate molecular mechanisms underlying liver cancer and may guide future therapeutic approaches for this disease. 2. RESULTS 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 [67]GSE55092 and [68]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 [69]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 [70]1C). These genes have a pivotal function in the progression of hepatic fibrosis and HBV‐HCC. FIGURE 1. FIGURE 1 [71]Open in a new tab Identification of essential genes related to HBV‐HCC through bioinformatics analysis. (A and B) Heatmap and volcano plot of the merged datasets [72]GSE55092 and [73]GSE121248 comparing normal control samples (normal group, n = 63) with liver cancer tissue samples (HBV‐HCC group, n = 107). (C) PPI analysis of differentially expressed genes from the combined analysis of [74]GSE55092 and [75]GSE121248 datasets, where red indicates the highest degree value and yellow signifies lower degree values. (D) Pathway enrichment analysis of GSEA from the combined analysis of [76]GSE55092 and [77]GSE121248 datasets. HBV‐HCC, hepatitis B virus‐hepatocellular carcinoma; GSEA, gene set enrichment analysis; PPI, protein–protein interaction. 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 [78]1D). Further literature review revealed a close correlation between HBV‐HCC and the METABOLISM_OF_RNA pathway.[79] ^32 , [80]^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 [81]2A); M2 macrophages have a strong correlation with M1 macrophages (Figure [82]2B). FIGURE 2. FIGURE 2 [83]Open in a new tab Immune infiltration analysis of HBV‐HCC and M2 macrophages. (A) Immune infiltration plot comparing standard control samples (normal group, n = 7) with hepatocellular carcinoma samples (HBV‐HCC group, n = 11) in dataset [84]GSE121248. The x‐axis represents the differences in immune cell populations between samples, and the height of the bars represents the expression level of immune infiltration in different samples. Higher bars indicate higher levels of immune cells or immune‐related gene expression, while lower bars indicate lower levels of immune infiltration. (B) Correlation analysis heatmap of immune cells, where *p < 0.05, red represents positive correlation and blue represents negative correlation. HBV‐HCC, hepatitis B virus‐hepatocellular carcinoma. 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,[85] ^34 , [86]^35 CDKN3,[87] ^36 , [88]^37 SERPINE1,[89] ^38 , [90]^39 PTGS2,[91] ^40 ANLN,[92] ^41 , [93]^42 SPP1,[94] ^43 TPR,[95] ^44 MAD2L1,[96] ^45 IDO2,[97] ^46 and THRSP[98] ^47 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 [99]3A,B). After reviewing the literature, it was found that the development and evolution of HBV‐HCC are intricately linked to ACSL4 and BAs.[100] ^34 , [101]^35 , [102]^48 We also performed survival analysis applying the GEPIA database ([103]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 [104]S1J). FIGURE 3. FIGURE 3 [105]Open in a new tab Levels of ACSL4, BAs, FXR, and M2 macrophage polarization markers in normal and HCC tissues. (A and B) mRNA and protein levels of critical genes in adjacent normal tissue (normal group) and cancer tissue (HBV‐HCC group) of HBV‐HCC patients, detected by RT‐qPCR and Western blot respectively, n = 20, indicating statistical significance between the two groups at p < 0.05. (C) Protein interaction analysis of ACSL4 with BA‐related proteins encoded by genes such as CYP7A1, CYP27A1, CYP8B1, and with FXR, where the outer circle represents genes associated with ACSL4, and NR1H4 is the scientific name for FXR. (D) Total BA levels detected by mass spectrometry in adjacent normal tissue (normal group) and cancer tissue (HBV‐HCC group), n = 20, indicating statistical significance between the two groups at p < 0.05. (E) Expression levels of FXR detected by RT‐qPCR in adjacent normal tissue (normal group) and cancer tissue (HBV‐HCC group), n = 20, indicating statistical significance between the two groups at p < 0.05. (F) WB to detect the protein expression levels of FXR in adjacent normal tissues (normal group) and cancer tissues (HBV‐HCC group), with n = 20, demonstrating a significant difference between the two groups, p < 0.05. (G) The correlation analysis between the mRNA levels of the key gene ACSL4 and BA levels, where p < 0.05 indicates a statistical difference. R denotes the correlation coefficient, where R > 0 signifies a positive correlation and R < 0 indicates a negative correlation. The closer the value is to 0, the weaker the correlation. The external curve represents the marginal histogram of a single variable. (H) Flow cytometry to measure the expression levels of the M2 macrophage polarization markers Arg1, CD163, and CD206, showing a significant difference between the two groups with p < 0.05. (I) Represents the correlation analysis between the mRNA levels of ACSL4 and the expression levels of the M2 macrophage polarization markers Arg1, CD163, and CD206, where p < 0.05 indicates a statistical difference. R denotes the correlation coefficient, and the external curve represents the marginal histogram of a single variable. HBV‐HCC, hepatitis B virus‐hepatocellular carcinoma; FXR, farnesoid X receptor. 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 [106]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 [107]3D,F). Furthermore, correlation analysis between key genes, pathway factors, and BAs demonstrated a positive correlation between ACSL4 and BA levels (Figures [108]3G and [109]S1). The flow cytometry findings indicated increased expression of Arg1, CD163, and CD206 in HBV‐HCC tissues in contrast to normal tissue samples (Figure [110]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 [111]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 [112]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 [113]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 [114]4D). FIGURE 4. FIGURE 4 [115]Open in a new tab The regulation of ACSL4 in BAs and FXR in HCC cells. (A) Expression levels of ACSL4 and FXR in human hepatic stellate cells (LX‐2) and HBV‐infected LX‐2 cells detected by Western blot, with statistical significance between the two groups at p < 0.05. (B and C) Levels of HBsAg, HBeAg, and HBV DNA in LX‐2 cells and HBV‐infected LX‐2 cells detected by ELISA, with statistical significance between the two groups at p < 0.05. (D) BA levels in LX‐2 cells and HBV‐infected LX‐2 cells detected by mass spectrometry, with statistical significance between the two groups at p < 0.05. (E–G) Cell proliferation, migration, and invasive properties of HBV‐infected LX‐2 cells assessed by Transwell and MTT assays, with a scale of 50 µm, and statistical significance between the two groups at p < 0.05. (H) Overexpression and knockdown efficiency of ACSL4 in HBV‐LX‐2 cells detected by RT‐qPCR, compared with oe‐NC, # indicates comparison with sh‐NC, with statistical significance at p < 0.05. (I) Expression levels of ACSL4 and FXR in the supernatant of HBV‐LX‐2 cells detected by Western blot, compared with oe‐NC, # indicates comparison with sh‐NC, with statistical significance at p < 0.05. (J) BA levels in HBV‐LX‐2 cells detected by mass spectrometry, * indicates comparison with oe‐NC, # indicates comparison with sh‐NC, with statistical significance at p < 0.05. (K–M) Cell proliferation, migration, and invasive properties of HBV‐LX‐2 cells assessed by Transwell and MTT assays, with a scale of 50 µm. The cell experiments were independently repeated six times. FXR, farnesoid X receptor; HBV, hepatitis B virus; HCC, hepatocellular carcinoma. 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 [116]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 [117]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 [118]4I). Mass spectrometry analysis showed that overexpression of ACSL4 increased the levels of BAs while silencing ACSL4 decreased the levels of BAs (Figure [119]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 [120]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 [121]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 [122]5B). FIGURE 5. FIGURE 5 [123]Open in a new tab The FXR promotes the proliferation, migration, and invasion of HCC cells by influencing the polarization of M2 macrophages. (A) Western blot in the detection of FXR expression levels in the coculture system of HBV‐LX‐2 and THP‐1 macrophages. # represents comparison with oe‐NC, with significance level p < 0.05 compared with sh‐NC. (B) Flow cytometry in observing the expression of M2 macrophage polarization markers Arg1, CD163, and CD206 in the coculture of HBV‐LX‐2 and THP‐1 macrophages; (C) Flow cytometry for detecting the expression of M2 macrophage polarization markers Arg1, CD163, and CD206 in the coculture of HBV‐LX‐2 and THP‐1 macrophages. (D–F) Transwell and MTT assays for assessing the proliferation, migration, and invasion capacities of liver cancer cells in the coculture system of HBV‐LX‐2 and THP‐1 macrophages. The scale bar in the images indicates 50 µm, with p < 0.05 significance level. Each cell experiment was repeated six times. FXR, farnesoid X receptor; HBV, hepatitis B virus. 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 [124]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 [125]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 [126]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 [127]6B). FIGURE 6. FIGURE 6 [128]Open in a new tab The effects of ACSL4 silence or FXR silence on the occurrence and development of HBV‐HCC. (A) In the coculture system of HBV‐LX‐2 cells and THP‐1 macrophages, silencing ACSL4 or silencing both ACSL4 and FXR simultaneously, Western blot was used to detect the expression levels of ACSL4 and FXR in liver cancer cells, compared with the sh‐NC + sh‐NC group, where # indicates comparison with the sh‐ACSL4 + sh‐NC group, with significance level p < 0.05. (B) In the coculture system of HBV‐LX‐2 cells and THP‐1 cells, silencing ACSL4 or silencing both ACSL4 and FXR simultaneously, mass spectrometry was used to measure the levels of BAs in liver cancer cells, compared with the sh‐NC + sh‐NC group, where ns indicates comparison with the sh‐ACSL4 + sh‐NC group, with significance level p < 0.05. (C) In the coculture system of HBV‐LX‐2 cells and THP‐1 cells, silencing ACSL4 or silencing both ACSL4 and FXR simultaneously, flow cytometry was used to detect the expression levels of M2 macrophage polarization markers Arg1, CD163, CD206, in comparison with the sh‐NC + sh‐NC group, where # indicates comparison with the sh‐ACSL4 + sh‐NC group, with p < 0.05 significance level. (D–F) In the coculture system of HBV‐LX‐2 + THP‐1 macrophages, silencing ACSL4 or silencing both ACSL4 and FXR simultaneously, Transwell assay was used to evaluate the proliferation, migration, and invasiveness of liver cancer cells. The scale bar in the images represents 50 µm, with comparison with the sh‐NC + sh‐NC group, where # represents comparison with the sh‐ACSL4 + sh‐NC group, at p < 0.05 significance level. The experiment was repeated six times. FXR, farnesoid X receptor; HBV, hepatitis B virus; sh‐NC, short hairpin negative control. 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 [129]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 [130]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.[131] ^49 , [132]^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 [133]S2A,B). Furthermore, the levels of HBsAg, HBeAg, and HBV‐DNA were upregulated (Figure [134]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 [135]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 [136]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 [137]S2G‐H). At 40 weeks of injection, we observed large liver tumor nodules (≥3 mm^2) 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 mm^2). The cumulative quantity of tumor nodules in the liver increased after H&E staining of liver sections (Figure [138]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 [139]7A,B). FIGURE 7. FIGURE 7 [140]Open in a new tab Regulation of BAs and FXR‐mediated M2 macrophage polarization by ACSL4 in HBV‐HCC development. (A and B) Levels of alanine transaminase (ALT) and aspartate transaminase (AST) in mouse serum measured by ELISA, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, p < 0.05. (C) Protein expression levels of ACSL4 and FXR in mouse liver tissue detected by Western blot, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, p < 0.05. (D) BA levels in mouse liver tissue measured by mass spectrometry analysis, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, ns, p > 0.05. (E) Expression of M2 macrophage polarization markers Arg1, CD163, and CD206 detected by flow cytometry assay, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, p < 0.05. (F) Histopathological changes in mouse liver observed by H&E staining, scale bar: 50 µm. (G) Fibrosis analysis of collagen deposition in mouse liver using Sirius Red staining, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, scale bar: 50 µm, p < 0.05. (H) Nodule formation in mouse liver observed by H&E staining, black arrows indicate nodules, scale bar: 100 and 50 µm, n = 6. Comparative analysis: sh‐NC + sh‐NC versus sh‐ACSL4 + sh‐NC, p < 0.05. ALT, alanine transaminase; AST, aspartate transaminase; FXR, farnesoid X receptor; H&E, hematoxylin and eosin. 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 [141]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 [142]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 [143]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 [144]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 [145]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 [146]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. 3. DISCUSSION This study highlighted the vital function of ACSL4 in the occurrence and progression of hepatitis HBV‐HCC. Through bioinformatics analysis and clinical sample testing, ACSL4 was determined to be a key gene affecting HBV‐HCC. This discovery aligns with previous research on the regulatory role of ACSL4 in other cancer types but, for the first time, highlights the central role of ACSL4 in HBV‐HCC.[147] ^51 This finding provides a new direction for understanding the molecular mechanisms of liver cancer and potentially identifies a target for future therapies. Our research revealed elevated levels of BAs in liver tissues of HBV‐HCC patients. Evidence from in vitro and in vivo studies substantiated that silencing ACSL4 could reduce BA levels, thus improving the progression of HBV‐HCC. While previous studies have focused on the link between BA metabolism and liver diseases, the specific interaction and regulatory mechanisms between ACSL4 and BAs remain largely unknown.[148] ^52 Our findings fill this knowledge gap, revealing a novel regulatory pathway. Another significant discovery of our study is that ACSL4 influences the occurrence and progression of HBV‐HCC through FXR‐mediated polarization of M2 macrophages. M2 macrophages play a crucial role in promoting angiogenesis, tumor growth, immune evasion, and therapeutic resistance in HCC.[149] ^53 This mechanism has not been extensively explored in previous studies. Our experimental data indicate that the upregulation of ACSL4 and M2 macrophage polarization markers (Arg1, CD163, CD206) have a significant correlation with the development of HBV‐HCC, while the expression of M1 markers (CD86, CD80, CD11c) is significantly downregulated (Figure [150]S3). This new finding presents a unique viewpoint on interpreting the tumor microenvironment and immune response in liver cancer. Historically, research on BA metabolism and HBV‐HCC has primarily focused on in vitro observations, lacking a comprehensive understanding of these molecular mechanisms in living systems.[151] ^54 By utilizing the HBs‐HepR mouse model, our in vivo experimental evidence further strengthens the reliability and applicability of our findings. In conclusion, we propose that ACSL4 regulates BAs and FXR‐mediated polarization of M2 macrophages, thereby influencing the occurrence and progression of HBV‐HCC. This study reveals the critical role of ACSL4 in governing BAs and promoting FXR‐mediated M2 macrophage polarization in HBV‐HCC, unveiling a novel molecular regulatory network.[152] ^2 Through bioinformatics analysis and in vitro and in vivo experiments, our study establishes a comprehensive molecular mechanism model that may propose an innovative theoretical groundwork for tackling liver cancer prevention and therapy. It is worth noting the association between ACSL4 and ferroptosis. As early as 1997, Kang et al.[153] ^55 found that AA and Eicosapentaenoic acid (20:5) are major substrates of ACSL4. Knockout of the Acsl4 gene specifically in adipocytes in mice contributed to a marked decline in the amount of arachidonic acid or docosapentaenoic acid (22:5) in PL and an increase in LA,[154] ^56 highlighting the crucial role of ACSL4 in ferroptosis regulation.[155] ^57 We conducted a simple test by staining HBV‐LX‐2 cells with FerroOrange and found that ferrous ion accumulation showed a notable decrease in the ACSL4 silenced group when juxtaposed with the control group (Figure [156]S4). While the relationship between iron death and the occurrence and development of HBV‐HCC warrants further exploration due to experimental limitations, we plan to delve deeper into this in future studies. Clinically, the treatment of HBV‐HCC remains a challenge.[157] ^3 , [158]^9 , [159]^58 Our study suggests that silencing ACSL4 can enhance the onset and evolution of HBV‐HCC, potentially guiding the development of new drug targets. Furthermore, analyzing BA levels, M2 macrophage polarization markers, and FXR expression could serve as diagnostic and prognostic indicators for HBV‐HCC. A point to be emphasized is that the samples used in this study might differ from the general population and may not fully reflect the situation of all HBV‐HCC patients. While validations were performed using in vitro cell lines and mouse models, differences may exist in human contexts, necessitating further clinical trials to confirm these findings. Although our study primarily focuses on the regulatory mechanisms of ACSL4 and BAs, there may be other unknown regulatory networks that warrant further investigation. Despite achieving significant breakthroughs in many aspects, there are still several questions worth exploring further. These include the specific interaction mechanisms between ACSL4 and BA metabolism, detailed mechanisms of FXR action, and the deep‐seated mechanisms of ACSL4 regulating M2 macrophage polarization. Addressing these questions will deepen our understanding of the complex molecular mechanisms of HBV‐HCC and aid in the development of more effective treatment methodologies. 4. MATERIALS AND METHODS 4.1. Public database chip data acquisition Data on HBV infection leading to LIHC was retrieved from the GEO database, specifically from chip datasets [160]GSE121248 and [161]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