ABSTRACT
Lung metastasis, the most frequent metastatic pattern in hepatocellular carcinoma, is an important contributor to poor prognosis. However, the mechanisms responsible for lung metastasis in hepatocellular carcinoma remain unknown. Aiming to explore these mechanisms, weighted gene coexpression network analysis (WGCNA) was firstly used to find hub genes related to lung metastasis. Then, we obtained 67 genes related to lung metastasis in hepatocellular carcinoma which were mainly related to ribosomal pathways and functions, and a protein interaction network analysis identified that fibrillarin (FBL) might be an important hub gene. Furthermore, we found that FBL is highly expressed in hepatocellular carcinoma and that its high expression increases the rate of lung metastasis and indicates a poor prognosis. Knockdown of FBL could significantly reduce proliferation and stemness as well as inhibiting the migration and invasion of hepatocellular carcinoma cells. Moreover, we found that FBL might be involved in the regulation of MYC and E2F pathways in hepatocellular carcinoma. Finally, we demonstrated that the knockdown of FBL could suppress hepatocellular carcinoma cell growth in vivo. In conclusion, ribosome-biogenesis-related proteins, especially Fibrillarin, play important roles in lung metastasis from hepatocellular carcinoma.
ABSTRACT
Background: Hepatitis B virus (HBV) infection is a major risk factor causing hepatocellular carcinoma (HCC) development, but the molecular mechanisms are not fully elucidated. It has been reported that virus infection induces ectonucleotide pyrophosphatase-phosphodiesterase 2 (ENPP2) expression, the latter participates in tumor progression. Therefore, the aim of the present study was to investigate whether HBV induced HCC malignancy via ENPP2. Methods: HCC patient clinical data were collected and prognosis was analyzed. Transient transfection and stable ectopic expression of the HBV genome were established in hepatoma cell lines. Immunohistochemical staining, RT-qPCR, western blot, and ELISA assays were used to detect the expression and secretion of ENPP2. Finally, CCK-8, colony formation, and migration assays as well as a subcutaneous xenograft mouse model were used to investigate the influence of HBV infection, ENPP2 expression, and activated hepatic stellate cells (aHSCs) on HCC progression in vitro and in vivo. Results: The data from cancer databases indicated that the level of ENPP2 was significant higher in HCC compared within normal liver tissues. Clinical relevance analysis using 158 HCC patients displayed that ENPP2 expression was positively correlated with poor overall survival and disease-free survival. Statistical analysis revealed that compared to HBV-negative HCC tissues, HBV-positive tissues expressed a higher level of ENPP2. In vitro, HBV upregulated ENPP2 expression and secretion in hepatoma cells and promoted hepatoma cell proliferation, colony formation, and migration via enhancement of ENPP2; downregulation of ENPP2 expression or inhibition of its function suppressed HCC progression. In addition, aHSCs strengthened hepatoma cell proliferation, migration in vitro, and promoted tumorigenesis synergistically with HBV in vivo; a loss-function assay further verified that ENPP2 is essential for HBV/aHSC-induced HCC progression. Conclusion: HBV enhanced the expression and secretion of ENPP2 in hepatoma cells, combined with aHSCs to promote HCC progression via ENPP2.
ABSTRACT
EZH2, a histone methyltransferase, has been shown to involve in cancer development and progression via epigenetic regulation of tumor suppressor microRNAs, whereas BMI1, a driver of hepatocellular carcinoma (HCC), is a downstream target of these microRNAs. However, it remains unclear whether EZH2 can epigenetically regulate microRNA expression to modulate BMI1-dependent hepatocarcinogenesis. Here, we established that high EZH2 expression correlated with enhanced tumor size, elevated metastasis, increased relapse, and poor prognosis in HCC patients. Further clinical studies revealed that EZH2 overexpression was positively correlated to its gene copy number gain/amplification in HCC. Mechanistically, EZH2 epigenetically suppressed miR-200c expression both in vitro and in vivo, and more importantly, miR-200c post-transcriptionally regulated BMI1 expression by binding to the 3'-UTR region of its mRNA. Furthermore, miR-200c overexpression inhibits the growth of HCC cells in vivo. Silencing miR-200c rescued the tumorigenicity of EZH2-depleted HCC cells, whereas knocking down BMI1 reduced the promoting effect of miR-200c depletion on HCC cell migration. Finally, combination treatment of EZH2 and BMI1 inhibitors further inhibited the viability of HCC cells compared with the cells treated with EZH2 or BMI1 inhibitor alone. Our findings demonstrated that alteration of EZH2 gene copy number status induced BMI1-mediated hepatocarcinogenesis via epigenetically silencing miR-200c, providing novel therapeutic targets for HCC treatment.
ABSTRACT
BACKGROUND: Hepatocellular carcinoma (HCC) is a common cancer with a poor prognosis. Previous studies revealed that the tumor microenvironment (TME) plays an important role in HCC progression, recurrence, and metastasis, leading to poor prognosis. However, the effects of genes involved in TME on the prognosis of HCC patients remain unclear. Here, we investigated the HCC microenvironment to identify prognostic genes for HCC. AIM: To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC. METHODS: We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm. Additionally, a risk score model was established based on Differentially Expressed Genes (DEGs) between high- and low-immune/stromal score patients. RESULTS: The risk score model consisting of eight genes was constructed and validated in the HCC patients. The patients were divided into high- or low-risk groups. The genes (Disabled homolog 2, Musculin, C-X-C motif chemokine ligand 8, Galectin 3, B-cell-activating transcription factor, Killer cell lectin like receptor B1, Endoglin and adenomatosis polyposis coli tumor suppressor) involved in our risk score model were considered to be potential immunotherapy targets, and they may provide better performance in combination. Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway, respectively, related to the immune-related genes in the DEGs between high- and low-risk groups. The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the risk score prognostic model. Moreover, we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database. A nomogram was established to predict the overall survival of HCC patients. CONCLUSION: The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.
