Anti-malarial drug dihydroartemisinin downregulates the expression levels of CDK1 and CCNB1 in liver cancer

Target prediction and potential application of dihydroartemisinin on hepatocarcinoma treatment

With high incidence of hepatocarcinoma and limited effective treatments, most patients suffer in pain. Antitumor drugs are single-targeted, toxicity, causing adverse side effects and resistance. Dihydroartemisinin (DHA) inhibits tumor through multiple mechanisms effectively. This study explores and evaluates safety and potential mechanism of DHA towards human hepatocarcinoma based on network pharmacology in a comprehensive way. Adsorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of DHA were evaluated with pkCSM, SwissADME, and ADMETlab. Potential targets of DHA were obtained from SwissTargetPrediction, Drugbank, TargetNET, and PharmMapper. Target gene of hepatocarcinoma was obtained from OMIM, GeneCards, and DisGeNET. Overlapping targets and hub genes were identified and analyzed for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway. Molecular docking was utilized to investigate the interactions sites and hydrogen bonds. Cell counting kit-8 (CCK8), wound healing, invasion, and migration assays on HepG2 and SNU387 cell proved DHA inhibits malignant biological features of hepatocarcinoma cell. DHA is safe and desirable for clinical application. A total of 131 overlapping targets were identified. Biofunction analysis showed targets were involved in kinase activity, protein phosphorylation, intracellular reception, signal transduction, transcriptome dysregulation, PPAR pathway, and JAK-STAT signaling axis. Top 9 hub genes were obtained using MCC (Maximal Clique Centrality) algorithm, namely CDK1, CCNA2, CCNB1, CCNB2, KIF11, CHEK1, TYMS, AURKA, and TOP2A. Molecular docking suggests that all hub genes form a stable interaction with DHA for optimal binding energy were all less than - 5 kcal/mol. Dihydroartemisinin might be a potent and safe anticarcinogen based on its biological safety and effective therapeutic effect.

Dihydroartemisinin breaks the positive feedback loop of YAP1 and GLUT1-mediated aerobic glycolysis to boost the CD8+ effector T cells in hepatocellular carcinoma

Aerobic glycolysis is a hallmark of hepatocellular carcinoma (HCC). Dihydroartemisinin (DHA) exhibits antitumor activity towards liver cancer. Our previous studies have shown that DHA inhibits the Warburg effect in HCC cells. However, the mechanism still needs to be clarified. Our study aimed to elucidate the interaction between YAP1 and GLUT1-mediated aerobic glycolysis in HCC cells and focused on the underlying mechanisms of DHA inhibiting aerobic glycolysis in HCC cells. In this study, we confirmed that inhibition of YAP1 expression lowers GLUT1-mediated aerobic glycolysis in HCC cells and enhances the activity of CD8+T cells in the tumor niche. Then, we found that DHA was bound to cellular YAP1 in HCC cells. YAP1 knockdown inhibited GLUT1-mediated aerobic glycolysis, whereas YAP1 overexpression promoted GLUT1-mediated aerobic glycolysis in HCC cells. Notably, liver-specific Yap1 knockout by AAV8-TBG-Cre suppressed HIF-1α and GLUT1 expression in tumors but not para-tumors in DEN/TCPOBOP-induced HCC mice. Even more crucial is that YAP1 forms a positive feedback loop with GLUT1-mediated aerobic glycolysis, which is associated with HIF-1α in HCC cells. Finally, DHA reduced GLUT1-aerobic glycolysis in HCC cells through YAP1 and prevented the binding of YAP1 and HIF-1α. Collectively, our study revealed the mechanism of DHA inhibiting glycolysis in HCC cells from a perspective of a positive feedback loop involving YAP1 and GLUT1 mediated-aerobic glycolysis and provided a feasible therapeutic strategy for targeting enhanced aerobic glycolysis in HCC.

Study on the mechanism of quercetin in Sini Decoction Plus Ginseng Soup to inhibit liver cancer and HBV virus replication through CDK1

BACKGROUND

To explore the anti-tumor and anti-virus key active ingredients of Sini Decoction Plus Ginseng Soup (SNRS) and their mechanisms.

METHODS

The main ingredients of SNRS were analyzed by network pharmacology, and quercetin was identified as the key active ingredient. Then, we obtained the targets of quercetin by using Drugbank, PharmMapper, and SwissTargetPrediction databases. Then, the targets of HBV-related hepatocellular carcinoma (HBV-related HCC) were obtained by using Genecards database. In addition, using the gene expression profiles of HBV-related HCC patients in GEO database and the genes with the greatest survival difference in GEPIA 2 database identified the potential targets of quercetin. In addition, the mechanism of potential genes was studied through GO, KEGG analysis, and PPI network. Using AUC and survival analysis to evaluate the diagnostic and prognostic value of cyclin-dependent kinase 1 (CDK1) and CCNB1. Finally, the effects of quercetin on proliferation of Hep3B and HepG2215 cells and the level of CDK1 and CCNB1 were verified in vitro. ELISA was used to measure the expression levels of hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) after the intervention by quercetin for 24 h and 48 h in HepG2215 cell.

RESULTS

The first 10 key ingredients of SNRS were identified, and quercetin was the most key ingredient. The 101 potential quercetin targets were identified for the treatment of HBV-related HCC. GO and KEGG showed that 101 potential target enrichment in cancer and cell cycle regulation. By Venn analysis, CDK1 and CCNB1 were intersection targets, which could be used as potential targets for the action of quercetin on HBV-related HCC. Moreover, the expression of CDK1 and CCNB1 was highly expressed in the high-risk group, while the OS rate was low. The 1-year, 3-year and 5-year area under the curve (AUC) curves of CDK1 and CCNB1 were 0.724, 0.676, 0.622 and 0.745, 0.678, 0.634, respectively. Moreover, experimental results also showed that quercetin inhibited cell proliferation and reduced CDK1 expression in Hep3B and HepG2215 cells. The expressions of HBsAg and HBeAg in HepG2215 cell supernatant and cell gradually decreased with the increase of intervention time of quercetin and CDK1 inhibitor.

CONCLUSIONS

Quercetin is a key ingredient of anti-HBV-related HCC activity and inhibits HBV replication in SNRS by inhibiting CDK1.

Coptidis rhizoma and evodiae fructus against lipid droplet deposition in nonalcoholic fatty liver disease-related liver cancer by AKT

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease in the world. NAFLD has become one of the major factors contributing to hepatocellular carcinoma (HCC) development. However, there are no clear targets and therapeutic drugs for NAFLD-related liver cancer. This study explored the active compounds, target and mechanism of coptidis rhizoma and evodiae fructus in the treatment of NAFLD-related liver cancer based on the network pharmacology and experimental verification. There were 455 intersection targets of NAFLD-related liver cancer, and 65 drug-disease common targets. AKT1 has the highest degree, indicating that it may be a key target of coptidis rhizoma and evodiae fructus in the treatment of NAFLD-related liver cancer. The expression level of AKT1 was high in high-risk group, and the overall survival rate was lower than that in low-risk group. After oleic acid induction, p-AKT expression and lipid droplet deposition were promoted in HepG2 cells. Quercetin and resveratrol reduced lipid droplet deposition in vivo. Moreover, quercetin inhibited p-AKT expression, resveratrol both reduced the expression of p-AKT and AKT. The overall findings suggested that quercetin inhibited AKT in the treatment of NAFLD-related liver cancer.

KNTC1 knockdown inhibits proliferation and metastases of liver cancer

To investigate the mechanism of kinetochore-associated protein 1 (KNTC1) in hepatocellular carcinoma. To query the TCGA database for KNTC1 expression in hepatocellular carcinoma. Detection of protein and mRNA levels of KNTC1 in hepatocellular carcinoma cell lines SK-Hep-1, Huh7, HepG2 and SNU449. Cell proliferation, migration and invasion ability were examined after KNTC1 knockdown in SK-Hep-1 and Huh7. Proteins related to KNTC1 were identified through protein interregulation, and their role in hepatocellular carcinoma was investigated. Our results showed that KNTC1 was significantly upregulated in hepatocellular carcinoma tissues and was associated with poorer prognostic survival. The expression of KNTC1 in hepatocellular carcinoma cell lines SK-Hep-1, Huh7, HepG2 and SNU449 was significantly higher than that in normal hepatocyte line L02. Knockdown of KNTC1 in SK-Hep-1 and Huh7 significantly inhibited cell viability, migration ability and invasion ability. KNTC1 is involved in the regulation of hepatocellular carcinoma through its interaction with cyclin-dependent kinase 1 (CDK1). Knockdown of KNTC1 inhibited CDK1 expression, while CDK1 overexpression was able to rescue the regulation of KNTC1 on the viability, migration and invasive ability of hepatocellular carcinoma cell lines. Knockdown of KNTC1 was found to resulted a cell cycle arrest at the S-phase, potentially through the modulation of CDK1, leading to decreased migration and invasion of hepatocellular carcinoma cells. Moreover, knockdown of KNTC1 in mouse transplanted tumors significantly inhibits tumor growth. Inhibition of high expression of KNTC1 in hepatocellular carcinoma was effective in suppressing the progression of hepatocellular carcinoma cells after knockdown. It may be a potential target for the treatment of hepatocellular carcinoma.

A systematic study on the treatment of hepatitis B-related hepatocellular carcinoma with drugs based on bioinformatics and key target reverse network pharmacology and experimental verification

BACKGROUND

Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC). However, the mechanism of hepatitis B-related hepatocellular carcinoma (HBV-related HCC) is still unclear. Therefore, understanding the pathogenesis and searching for drugs to treat HBV-related HCC was an effective strategy to treat this disease.

PURPOSE

Bioinformatics was used to predict the potential targets of HBV-related HCC. The reverse network pharmacology of key targets was used to analyze the clinical drugs, traditional Chinese medicine (TCM) and small molecules of TCM in the treatment of HBV-related HCC.

METHODS

In this study, three microarray datasets totally containing 330 tumoral samples and 297 normal samples were selected from the GEO database. These microarray datasets were used to screen DEGs. And the expression profile and survival of 6 key genes were analyzed. In addition, Comparative Toxicogenomics Database and Coremine Medical database were used to enrich clinical drugs and TCM of HBV-related HCC by the 6 key targets. Then the obtained TCM were classified based on the Chinese Pharmacopoeia. Among these top 6 key genes, CDK1 and CCNB1 had the most connection nodes and the highest degree and were the most significantly expressed. In general, CDK1 and CCNB1 tend to form a complex, which is conducive to cell mitosis. Hence, this study mainly studied CDK1 and CCNB1. HERB database was used to predict small molecules TCM. The inhibition effect of quercetin, celastrol and cantharidin on HepG2.2.15 cells and Hep3B cells was verified by CCK8 experiment. The effects of quercetin, celastrol and cantharidin on CDK1 and CCNB1 of HepG2.2.15 cells and Hep3B cells were determined by Western Blot.

RESULTS

In short, 272 DEGs (53 upregulated and 219 downregulated) were identified. Among these DEGs, 6 key genes with high degree were identified, which were AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS. Kaplan-Meier plotter analysis showed that higher expression levels of AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS were associated with poor OS. According to the first 6 key targets, a variety of drugs and TCM were identified. These results showed that clinical drugs included targeted drugs, such as sorafenib, palbociclib and Dasatinib. and chemotherapy drugs, such as cisplatin and doxorubicin. TCM, such as the TCM flavor was mainly warm and bitter, and the main meridians were liver and lung. Small molecules of TCM included flavonoids, terpenoids, alkaloids and glycosides, such as quercetin, celastrol, cantharidin, hesperidin, silymarin, casticin, berberine and ursolic acid, which have great potential in anti-HBV-related HCC. For molecular docking of chemical components, the molecules with higher scores were flavonoids, alkaloids, etc. Three representative types of TCM small molecules were verified respectively, and it was found that quercetin, celastrol and cantharidin inhibited the proliferation of HepG2.2.15 cells and Hep3B cells along concentration gradient. Quercetin, celastrol and cantharidin decreased CDK1 expression in HepG2.2.15 and Hep3B cells, but for CCNB1, only cantharidin decreased CCNB1 expression in the two strains of cells.

CONCLUSION

In conclusion, AURKA, BIRC5, CCNB1, CDK1, CDKN3 and TYMS could be potential targets for the diagnosis and prognosis of HBV-related HCC. Clinical drugs include chemotherapeutic and targeted drug, traditional Chinese medicine is mainly bitter and warm TCM. Small molecular of TCM including flavonoids, terpenoids and glycosides and alkaloids, which have great potential in anti-HBV-related HCC. This study provides potential therapeutic targets and novel strategies for the treatment of HBV-related HCC.

A network pharmacology and bioinformatics exploration of the possible molecular mechanisms of Fuzheng Xiaoliu Granule for the treatment of hepatocellular carcinoma

Background and Aim

Hepatocellular carcinoma (HCC) is one of the ten most common malignant tumors in the world, and it is a major problem in the world. Traditional Chinese medicine (TCM) has many advantages in the prevention and treatment of HCC, but its complicated mechanism of action is difficult to clarify, which limits its research and development. The continuous development of bioinformation technology provides new methods and opportunities for the research of TCM. This study used modern network pharmacology and bioinformatic methods to explore the possible molecular mechanism of the Chinese herbal compound Fuzheng Xiaoliu Granule (FZXLG) to treat HCC, to provide a theoretical basis for their clinical application and basic research, to promote the modernization of TCM, and to promote its worldwide application.

Methods

The active ingredients of FZXLG were collected and screened through TCMSP, BATMAN-TCM, and other databases. The targets of FZXLG were predicted by PubChem and SwissTargetPrediction; HCC disease-related targets were obtained by GeneCards, OMIM, and other disease databases, and the potential gene targets of FZXLG for HCC treatment were screened. The "Prescription-TCMs-Ingredients-Targets" network of FZXLG for the treatment of HCC was constructed, along with the screening of core effective components. The differentially expressed genes (DEGs) of HCC tumor and non-tumor adjacent tissues combined with clinical data in the TCGA database were analyzed to obtain the prognostic genes of HCC. Then, FZXLG genes affecting HCC prognosis were screened and further screening the core target genes. The correlation between core gene expression with prognosis, immune cell infiltration, and immunohistochemical changes in HCC patients was studied. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Ontology enrichment analysis of the FZXLG genes affecting HCC prognosis were performed using DAVID database. AutoDockTools software was then used for molecular docking verification.

Results

The ten core effective ingredients of FZXLG for HCC treatment included multiple flavonoids ingredients such as quercetin, luteolin, and formononetin. 11 core targets of FZXLG affecting the prognosis of HCC were screened, among which estrogen receptor 1 (ESR1) and catalase (CAT) were favorable prognostic factors, while EGF, MMP9, CCNA2, CCNB1, CDK1, CHEK1, and E2F1 were adverse prognostic factors. MMP9 and EGF were positively correlated with six TIIC subsets. The different expression levels of CAT, PLG, AR, MMP9, CCNA2, CCNB1, CDK1, and E2F1 were correlated with the immunohistochemical staining changes in normal liver and liver cancer. KEGG pathway enrichment analysis yielded 33 pathways including cell cycle, p53, hepatitis B, and other signaling pathways. Molecular docking verified that the main core components had good binding to the protective prognostic core targets ESR1 and CAT.

Conclusions

FZXLG may treat HCC through multiple ingredients, multiple targets, and multiple pathways, affecting the prognosis, immune microenvironment, and immunohistochemical changes of HCC.

Relevance for Patients

FZXLG is a Chinese herbal compound for the treatment of HCC, with significant clinical efficacy. However, the mechanism of action is unclear and lacks theoretical support, which limits its popularization application. This study preliminarily revealed its molecular mechanism, providing a theoretical basis for its clinical application, which can better guide its clinical popularization application, and also provide a new strategy for the treatment of HCC.

Dihydroartemisinin broke the tumor immunosuppressive microenvironment by inhibiting YAP1 expression to enhance anti-PD-1 efficacy

The efficacy of anti-PD-1 therapy is not as expected in hepatocellular carcinoma (HCC). YAP1 was overexpressed and activated in HCC. The mechanism of YAP1 in HCC immune escape is unclear. Anti-PD-1 treatment increased YAP1 expression in liver tumor cells, and exhausted CD4+ and CD8+ T cells in the blood and spleen of liver tumor mice. YAP1 knockdown suppressed PD-L1 expression, which was involved in JAK1/STAT1, 3 pathways. Moreover, Yap1 knockout elevated CD4+ and CD8+ T cells in liver tumor niche. Consistently, verteporfin, YAP1 inhibitor, decreased TGF-β and IFN-γ in liver tumor niche and exhausted CD8+ T cell in the spleen. DHA suppressed YAP1 expression and break immune evasion in liver tumor niche, characterized by decreased PD-L1 in liver tumor cells and increased CD8+ T cell infiltration. Furthermore, DHA combined with anti-PD-1 treatment promoted CD4+ T cell infiltration in the spleen and CD8+ T cell in tumor tissues of mice. In summary, YAP1 knockdown in liver tumor cells suppressed PD-L1 expression and recruited cytotoxic T lymphocytes (CTLs), leading to break immune evasion in tumor niche. Mechanistically, YAP1 knockdown suppressed PD-L1 expression, which was involved in JAK1/STAT1, 3 pathways. Finally, DHA inhibited YAP1 expression, which not only inhibited liver tumor proliferation but also break the immunosuppressive niche in liver tumor tissues and improve the effect of anti-PD-1 therapy.

Effects of Sodium Chromate Exposure on Gene Expression Profiles of Primary Rat Hepatocytes (In Vitro)

Chromium exposure has adverse impacts on human health and the environment, whereas chromate-induced hepatotoxicity's detailed mechanism is still unclear. Therefore, the purpose of the current study was to reveal the crucial signaling pathways and genes linked to sodium chromate-induced hepatotoxicity. GSE19662, a gene expression microarray, was obtained from Gene Expression Omnibus (GEO). Six primary rat hepatocyte (PRH) samples from GSE19662 include sodium chromate-treated (n = 3) and the control PRH samples (n = 3). A total of 2,525 differentially expressed genes (DEGs) were obtained, especially 962, and 1,563 genes were up- and downregulated in sodium chromate-treated PRHs compared to the control. Gene ontology (GO) enrichment analysis suggested that those DEGs were involved in multiple biological processes, including the response to toxic substances, the positive regulation of apoptotic process, lipid and cholesterol metabolic process, and others. Signaling pathway enrichment analysis indicated that the DEGs were mainly enriched in MAPK, PI3K-Akt, PPAR, AMPK, cellular senescence, hepatitis B, fatty acid biosynthesis, etc. Moreover, many genes, including CYP2E1, CYP1A2, CYP2C13, CDK1, NDC80, and CCNB1, might contribute to sodium chromate-induced hepatotoxicity. Taken together, this study enhances our knowledge of the potential molecular mechanisms of sodium chromate-induced hepatotoxicity.

Dihydroartemisinin inhibited the Warburg effect through YAP1/SLC2A1 pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) was the third most common cause of cancer death. But it has only limited therapeutic options, aggressive nature, and very low overall survival. Dihydroartemisinin (DHA), an anti-malarial drug approved by the Food and Drug Administration (FDA), inhibited cell growth in HCC. The Warburg effect was one of the ten new hallmarks of cancer. Solute carrier family 2 member 1 (SLC2A1) was a crucial carrier for glucose to enter target cells in the Warburg effect. Yes-associated transcriptional regulator 1 (YAP1), an effector molecule of the hippo pathway, played a crucial role in promoting the development of HCC. This study sought to determine the role of DHA in the SLC2A1 mediated Warburg effect in HCC. In this study, DHA inhibited the Warburg effect and SLC2A1 in HepG2215 cells and mice with liver tumors in situ. Meanwhile, DHA inhibited YAP1 expression by inhibiting YAP1 promoter binding protein GA binding protein transcription factor subunit beta 1 (GABPB1) and cAMP responsive element binding protein 1 (CREB1). Further, YAP1 knockdown/knockout reduced the Warburg effect and SLC2A1 expression by shYAP1-HepG2215 cells and Yap1^LKO mice with liver tumors. Taken together, our data indicated that YAP1 knockdown/knockout reduced the SLC2A1 mediated Warburg effect by shYAP1-HepG2215 cells and Yap1^LKO mice with liver tumors induced by DEN/TCPOBOP. DHA, as a potential YAP1 inhibitor, suppressed the SLC2A1 mediated Warburg effect in HCC.

Identification of the hub and prognostic genes in liver hepatocellular carcinoma via bioinformatics analysis

Hepatocellular carcinoma (HCC) is a common malignancy. However, the molecular mechanisms of the progression and prognosis of HCC remain unclear. In the current study, we merged three Gene Expression Omnibus (GEO) datasets and combined them with The Cancer Genome Atlas (TCGA) dataset to screen differentially expressed genes. Furthermore, protein‒protein interaction (PPI) and weighted gene coexpression network analysis (WGCNA) were used to identify key gene modules in the progression of HCC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that the terms were associated with the cell cycle and DNA replication. Then, four hub genes were identified (AURKA, CCNB1, DLGAP5, and NCAPG) and validated via the expression of proteins and transcripts using online databases. In addition, we established a prognostic model using univariate Cox proportional hazards regression and least absolute shrinkage and selection operator (LASSO) regression. Eight genes were identified as prognostic genes, and four genes (FLVCR1, HMMR, NEB, and UBE2S) were detrimental gens. The areas under the curves (AUCs) at 1, 3 and 5 years were 0.622, 0.69, and 0.684 in the test dataset, respectively. The effective of prognostic model was also validated using International Cancer Genome Consortium (ICGC) dataset. Moreover, we performed multivariate independent prognostic analysis using multivariate Cox proportional hazards regression. The results showed that the risk score was an independent risk factor. Finally, we found that all prognostic genes had a strong positive correlation with immune infiltration. In conclusion, this study identified the key hub genes in the development and progression of HCC and prognostic genes in the prognosis of HCC, which was significant for the future diagnosis and prognosis of HCC.

Identification and validation of real hub genes in hepatocellular carcinoma based on weighted gene co-expression network analysis

BACKGROUND

Hepatocellular Carcinoma (HCC) is one of the most common liver malignancies in the world. With highly invasive biological characteristics and a lack of obvious clinical manifestations, hepatocellular Carcinoma usually has a poor prognosis and ranks fourth in cancer mortality. The etiology and exact molecular mechanism of primary hepatocellular carcinoma are still unclear.

OBJECTIVE

This work aims to help identify biomarkers of early HCC diagnosis or prognosis based on weighted gene co-expression network analysis (WGCNA).

METHODS

Expression data and clinical information of HTSEQ-Counts were downloaded from The Cancer Genome Atlas (TCGA) database, and Gene Expression map GSE121248 was downloaded from Gene Expression Omnibus (GEO). By differentially expressed genes (DEGs) and Weighted Gene co-expression Network Analysis (WGCNA) searched for modules in the two databases that had the same effect on the biological characteristics of HCC, and extracted the module genes with the highest positive correlation with HCC from two databases, and finally obtained overlapping genes. Then, we performed functional enrichment analysis on the overlapping genes to understand their potential biological functions. The top ten hub genes were screened according to MCC through the String database and Cytoscape software and then subjected to survival analysis.

RESULTS

High expression of CDK1, CCNA2, CDC20, KIF11, DLGAP5, KIF20A, ASPM, CEP55, and TPX2 was associated with poorer overall survival (OS) of HCC patients. The DFS curve was plotted using the online website GEPIA2. Finally, based on the enrichment of these genes in the KEGG pathway, real hub genes were screened out, which were CDK1, CCNA2, and CDC20 respectively.

CONCLUSIONS

High expression of these three genes was negatively correlated with survival time in HCC, and the expression of CDK1, CCNA2, and CDC20 were significantly higher in tumor tissues of HCC patients than in normal liver tissues as verified again by the HPA database. All in all, this provides a new feasible target for early and accurate diagnosis of HCC, clinical diagnosis, treatment, and prognosis.

Dihydroartemisinin promoted FXR expression independent of YAP1 in hepatocellular carcinoma

Loss of FXR, one of bile acid receptors, enlarged livers. Yes-associated protein 1 (YAP1), a dominant oncogene, promotes hepatocellular carcinoma (HCC). However, the relationship between FXR and YAP1 was unspecified in bile acid homeostasis in HCC. Here, we used TIMER2.0, the Cancer Genome Atlas (TCGA) Database, and Kaplan-Meier Plotter Database and discovered that FXR was positively correlated with better prognosis in liver cancer patients. Our previous research showed that dihydroartemisinin (DHA) inhibited cell proliferation in HepG2 and HepG22215 cells. However, the relationship of YAP1 and the bile acid receptor FXR remains elusive during DHA treatment. Furthermore, we showed that DHA improved FXR and reduced YAP1 in the liver cancer cells and mice. Additionally, the expression of nucleus protein FXR was enhanced in Yap1^LKO mice with liver cancer. DHA promoted the expression level of whole and nuclear protein FXR independent of YAP1 in Yap1^LKO mice with liver cancer. DHA declined cholesterol 7α-hydroxylase, but not sterol 27-hydroxylase, and depressed cholic acid and chenodeoxycholic acid of liver tissue in Yap1^LKO mice with liver cancer. Generally, our results suggested that DHA improved FXR and declined YAP1 to suppress bile acid metabolism. Thus, we suggested that FXR acted as a potential therapeutic target in HCC.