Does hepatitis B virus therapy reduce the risk of hepatocellular carcinoma?

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.

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.

Integrated analysis of multiple transcriptomic data identifies ST8SIA6‑AS1 and LINC01093 as potential biomarkers in HBV‑associated liver cancer

The mechanisms of long-non-coding RNAs (lncRNAs) in hepatitis B virus (HBV) infection-associated liver cancer remain largely unclear. Therefore, the aim of the present study was to investigate the regulatory mechanisms of lncRNAs in this disease. HBV-liver cancer related transcriptome expression profile data (GSE121248 and GSE55092) from the Gene Expression Omnibus database and survival prognosis information from The Cancer Genome Atlas (TCGA) database were obtained for analysis. The limma package was used to identify the overlapped differentially expressed RNAs (DERs), including DElncRNAs and DEmRNAs, in the GSE121248 and GSE55092 datasets. The screened optimized lncRNA signatures were used to develop a nomogram model based on the GSE121248 dataset, which was validated using the GSE55092 and TCGA datasets. A competitive endogenous RNA (ceRNA) network was constructed based on the screened prognosis-associated lncRNA signatures from TCGA dataset. In addition, the levels of specific lncRNAs were evaluated in HBV-infected human liver cancer tissues and cells, and Cell Counting Kit-8, ELISA and Transwell assays were performed to evaluate the effects of the lncRNAs in HBV-expressing liver cancer cells. A total of 535 overlapped DERs, including 30 DElncRNAs and 505 DEmRNAs, were identified in the GSE121248 and GSE55092 datasets. An optimized DElncRNA signature comprising 10 lncRNAs was used to establish a nomogram. ST8SIA6-AS1 and LINC01093 were identified as lncRNAs associated with HBV-liver cancer prognosis in TCGA dataset, and were applied to construct a ceRNA network. Reverse transcription-quantitative PCR analysis showed that ST8SIA6-AS1 was upregulated and LINC01093 was downregulated in HBV-infected human liver cancer tissues and HBV-expressing liver cancer cells compared with non-HBV-infected controls. ST8SIA6-AS1 knockdown and LINC01093 overexpression independently reduced the number of copies of HBV DNA, the levels of hepatitis B surface antigen and hepatitis B e antigen, as well as cell proliferation, migration and invasion. In summary, the present study identified ST8SIA6-AS1 and LINC01093 as two potential biomarkers that may be effective therapeutic targets for HBV-associated liver cancer.

Identification and validation of three core genes in p53 signaling pathway in hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus (HBV) infection. We aimed to identify some core genes and pathways for HBV-related HCC.

METHODS

Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus (GEO). The GSE62232 and GSE121248 profiles were the analysis datasets and GSE94660 was the validation dataset. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes between HBV-related HCC tissues and normal tissues. Then, functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of these three core genes in tumor tissues and adjacent non-tumor liver tissues from 12 HBV related HCC patients, HBV-associated liver cancer cell lines and normal liver cell lines, and HepG2 with p53 knockdown or deletion, respectively.

RESULTS

Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed that samples highly expressing three core genes were all enriched in the p53 signaling pathway in a validation dataset (P < 0.0001). The expression of these three core genes in tumor tissue samples was higher than that in relevant adjacent non-tumor liver tissues (P < 0.0001). Furthermore, we also found that the above genes were highly expressed in liver cancer cell lines compared with normal liver cells. In addition, we found that the expression of these three core genes in p53 knockdown or knockout HCC cell lines was lower than that in negative control HCC cell lines (P < 0.05).

CONCLUSIONS

CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

Hepatitis B virus treatment in hepatocellular carcinoma patients prolongs survival and reduces the risk of cancer recurrence

Chronic hepatitis B virus (HBV) infection and HBV-related liver disease are estimated to affect about 240 million people worldwide. Now that a vaccine is available, the number of new HBV infection cases has plummeted. Yet, there are still regions with very high incidence of HBV. Hepatocellular carcinoma (HCC) is the fourth to six most common malignancy in men and the ninth most common malignancy in women worldwide. 54% of all HCC cases are HBV-associated, making it the most common cause of cancer worldwide. Hepatitis B therapy prevents progression of chronic hepatitis to cirrhosis and HCC development, but even with the best HBV treatment, such patients are still at risk of HCC. Also in patients after transarterial chemoembolization (TACE), liver resection (hepatectomy) or liver transplant, suppression of hepatitis B virus (HBV) improves patient survival. In this paper we present current possibilities of HCC and HBV treatment, which lead to improved survival and quality of life.

Long Non-Coding RNAs in Hepatitis B Virus-Related Hepatocellular Carcinoma: Regulation, Functions, and Underlying Mechanisms

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the third leading cause of cancer death in the world. Hepatitis B virus (HBV) and its X gene-encoded protein (HBx) play important roles in the progression of HCC. Although long non-coding RNAs (lncRNAs) cannot encode proteins, growing evidence indicates that they play essential roles in HCC progression, and contribute to cell proliferation, invasion and metastasis, autophagy, and apoptosis by targeting a large number of pivotal protein-coding genes, miRNAs, and signaling pathways. In this review, we briefly outline recent findings of differentially expressed lncRNAs in HBV-related HCC, with particular focus on several key lncRNAs, and discuss their regulation by HBV/HBx, their functions, and their underlying molecular mechanisms in the progression of HCC.