Hepatitis B Virus X Protein Induces RHAMM-Dependent Motility in Hepatocellular Carcinoma Cells via PI3K-Akt-Oct-1 Signaling

CD44 and RHAMM Are Microenvironmental Sensors with Dual Metastasis Promoter and Suppressor Functions

The progression of primary tumors to metastases remains a significant roadblock to the treatment of most cancers. Emerging evidence has identified genes that specifically affect metastasis and are potential therapeutic targets for managing tumor progression. However, these genes can have dual tumor promoter and suppressor functions that are contextual in manifestation, and that complicate their development as targeted therapies. CD44 and RHAMM/HMMR are examples of multifunctional proteins that can either promote or suppress metastases, as demonstrated in experimental models. These two proteins can be viewed as microenvironmental sensors and this minireview addresses the known mechanistic underpinnings that may determine their metastasis suppressor versus promoter functions. Leveraging this mechanistic knowledge for CD44, RHAMM, and other multifunctional proteins is predicted to improve the precision of therapeutic targeting to achieve more effective management of metastasis.

Oncoviruses: Induction of cancer development and metastasis by increasing anoikis resistance

The phenomenon of cell death is a vital aspect in the regulation of aberrant cells such as cancer cells. Anoikis is a kind of cell death that occurs when cells get separated from the extracellular matrix. Some cancer cells can inhibit anoikis in order to progress metastasis. One of the key variables that might be implicated in anoikis resistance (AR) is viral infections. The most important viruses involved in this process are Epstein-Barr virus, human papillomavirus, hepatitis B virus, human herpes virus 8, human T-cell lymphotropic virus type 1, and hepatitis C virus. A better understanding of how carcinogenic viruses suppress anoikis might be helpful in developing an effective treatment for virus-associated cancers. In the current study, we review the role of the mentioned viruses and their gene products in anoikis inhibition.

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.

Hyaluronan in liver fibrosis: basic mechanisms, clinical implications, and therapeutic targets

Hyaluronan (HA), also known as hyaluronic acid, is a glycosaminoglycan that is a critical component of the extracellular matrix (ECM). Production and deposition of ECM is a wound-healing response that occurs during chronic liver disease, such as cirrhosis. ECM production is a sign of the disease progression of fibrosis. Indeed, the accumulation of HA in the liver and elevated serum HA levels are used as biomarkers of cirrhosis. However, recent studies also suggest that the ECM, and HA in particular, as a functional signaling molecule, facilitates disease progression and regulation. The systemic and local levels of HA are regulated by de novo synthesis, cleavage, endocytosis, and degradation of HA, and the molecular mass of HA influences its pathophysiological effects. However, the regulatory mechanisms of HA synthesis and catabolism and the functional role of HA are still poorly understood in liver fibrosis. This review summarizes the role of HA in liver fibrosis at molecular levels as well as its clinical implications and discusses the potential therapeutic uses of targeting HA in liver fibrosis.

ANTXR1 as a potential prognostic biomarker for hepatitis B virus-related hepatocellular carcinoma identified by a weighted gene correlation network analysis

BACKGROUND

With high incidence and mortality rates, hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors worldwide. Chronic hepatitis B virus (HBV) infection is a leading cause of HCC, especially for Asians and blacks. However, the molecular mechanisms underlying HBV-related HCC are unclear. This study sought to identify novel prognostic biomarkers and explore the potential pathogenesis of HBV-related HCC.

METHODS

The gene expression profiles and corresponding clinical information of HCC from The Cancer Genome Atlas Liver Hepatocellular Carcinoma data set were analyzed by a weighted gene co-expression network analysis. Correlations between the co-expression modules and clinical traits were calculated. Next, key modules associated with HBV infection were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted for the genes in the key modules. The hub genes were identified based on the protein-protein interaction (PPI) network via the Cytoscape. Finally, an overall survival (OS) analysis was performed.

RESULTS

The two modules (i.e., the brown and yellow modules) most relevant to HBV infection were constructed. A functional enrichment analysis revealed that the genes in the two modules were mainly enriched in HCC-related pathways, such as the phosphatidylinositol-3-kinase and protein kinase B signaling pathway, focal adhesion, human papillomavirus infection, the Rap1 signaling pathway, and the cyclic guanosine monophosphate-dependent protein kinase (cGMP-PKG) signaling pathway. Ten hub genes [i.e., COL3A1, ANTXR1, COL14A1, THBS2, ADAMTS2, AEBP1, PRELP, EMILIN1, DCN and PODN] in the brown module, and 10 hub genes [i.e., USP34, SEC24C, ZNF770, STAG1, TSTD2, PKD1P6, CCNK, GFT2I, NT5C2 and SMG6] in the yellow module were identified. Among the hub genes, ANTXR1 (Anthrax-toxin receptor 1) was significantly correlated with HBV-related HCC patients' OS.

CONCLUSIONS

ANTXR1 represents a potential therapeutic target for HBV-related HCC. This study offers novel insights into the molecular mechanisms of HBV-induced tumorigenesis, which needs to be further validated by basic experiments and large-scale cohort studies.

Potential lncRNA Biomarkers for HBV-Related Hepatocellular Carcinoma Diagnosis Revealed by Analysis on Coexpression Network

Background

Increasing evidence demonstrated that long noncoding RNA (lncRNA) could affect inflammatory tumor immune microenvironment by modulating gene expression and could be used as a biomarker for HBC-related hepatocellular carcinoma (HCC) but still needs further research. The aim of the present study was to determine an lncRNA signature for the diagnosis of HBV-related HCC.

Methods

HBV-related HCC expression profiles (GSE55092, GSE19665, and GSE84402) were abstracted from the GEO (Gene Expression Omnibus) data resource, and R package limma and RobustRankAggreg were employed to identify common differentially expressed genes (DEGs). Using machine learning, optimal diagnostic lncRNA molecular markers for HBV-related HCC were identified. The expression of candidate lncRNAs was cross-validated in GSE121248, and an ROC (receiver operating characteristic) curve of lncRNA biomarkers was carried out. Additionally, a coexpression network and functional annotation was built, after which a PPI (protein-protein interaction) network along with module analysis were conducted with the Cytoscape open source software.

Result

A total of 38 DElncRNAs and 543 DEmRNAs were identified with a fold change larger than 2.0 and a P value < 0.05. By machine learning, AL356056.2, AL445524.1, TRIM52-AS1, AC093642.1, EHMT2-AS1, AC003991.1, AC008040.1, LINC00844, and LINC01018 were screened out as optional diagnostic lncRNA biosignatures for HBV-related HCC. The AUC (areas under the curve) of the SVM (support vector machine) model and random forest model were 0.957 and 0.904, respectively, and the specificity and sensitivity were 95.7 and 100% and 94.3 and 86.5%, respectively. The results of functional enrichment analysis showed that the integrated coexpressed DEmRNAs shared common cascades in the p53 signaling pathway, retinol metabolism, PI3K-Akt signaling cascade, and chemical carcinogenesis. The integrated DEmRNA PPI network complex was found to be comprised of 87 nodes, and two vital modules with a high degree were selected with the MCODE app.

Conclusion

The present study identified nine potential diagnostic biomarkers for HBV-related HCC, all of which could potentially modulated gene expression related to inflammatory conditions in the tumor immune microenvironment. The functional annotation of the target DEmRNAs yielded novel evidence in evaluating the precise functions of lncRNA in HBV-related HCC.

Downregulation of HBx Restrains Proliferation, Migration, and Invasion of HepG2 Cells

Liver cancer is a major contributor to cancer-related death with poor survival for sufferers. Meanwhile, Hepatic B virus X protein (HBx) and XB130 are likely to participate in the pathogenesis of liver cancer. However, the detailed mechanism of HBx/XB130 in liver cancer remains to be further investigated. Our study explored the effects of HBx/XB130 on liver cancer progression. HBx and XB130 expression was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and Western blot. Overexpression of HBx and XB130 was found in liver cancer tissues and cells. Mechanistic study revealed that HBx could bind to and positively regulate XB130 in HepG2 cells. Subsequently, HBx expression was knocked down, while XB130 was overexpressed in HepG2 cells in order to observe the specific role of HBx/XB130 in liver cancer in vitro. Results of CCK-8, Transwell, wound healing, and colony formation assays suggested that HBx could mediate biological function of HepG2 cells by activating the XB130-mediated PI3K/AKT pathway. In summary, our data illustrate that inhibition of HBx effectively suppressed proliferation and metastasis and induced apoptosis of liver cancer cells, which might be partially reversed by XB130. HBx and XB130 may be potential targets for liver cancer pathogenesis.

Extracellular matrix and its therapeutic potential for cancer treatment

The extracellular matrix (ECM) is one of the major components of tumors that plays multiple crucial roles, including mechanical support, modulation of the microenvironment, and a source of signaling molecules. The quantity and cross-linking status of ECM components are major factors determining tissue stiffness. During tumorigenesis, the interplay between cancer cells and the tumor microenvironment (TME) often results in the stiffness of the ECM, leading to aberrant mechanotransduction and further malignant transformation. Therefore, a comprehensive understanding of ECM dysregulation in the TME would contribute to the discovery of promising therapeutic targets for cancer treatment. Herein, we summarized the knowledge concerning the following: (1) major ECM constituents and their functions in both normal and malignant conditions; (2) the interplay between cancer cells and the ECM in the TME; (3) key receptors for mechanotransduction and their alteration during carcinogenesis; and (4) the current therapeutic strategies targeting aberrant ECM for cancer treatment.

Advances in Liver Cancer Stem Cell Isolation and their Characterization

Over the last decade research on cancer stem cells (CSC) significantly contributed to a better understanding of tumor biology. Given their similarity to normal stem cells, i.e. self-renewal and pluripotency the need arises to develop robust protocols for the isolation and characterization of CSCs. As with other malignancies, hepatic tumors are composed of a heterogeneous population of cells including liver cancer stem cells (LCSC). Yet, a precise understanding of why stem cells become cancerous is still lacking. There is unmet need to develop robust protocols for the successful isolation of LCSCs from human tissue resection material as to assist in the development of molecular targeted therapies. Here we review the research progress made in the isolation and characterization of LCSCs by considering a wide range of cell surface markers and sorting methods, as applied to side populations, microsphere cultures and the gradient centrifugation method. We emphasize the different fluorescence activated cell sorting methods and the possibility to enrich LCSCs by immunomagnetic beads. We review the specificity of functional assays by considering ABCG transporter and ALDH1 enzyme activities and evaluate the in vivo tumorigenicity of LCSCs in highly sensitive bioassays. Finally, we evaluate different LCSC markers in association with viral and non-viral liver disease and explore the potential of novel drug delivery systems targeting CD133, EpCAM, CD13 and CD90 for the development of molecular targeted therapies. Graphical Abstract.

Prognostic and clinicopathological significance of PD-1 expression in hepatocellular carcinoma: a meta-analysis

Objective

We performed a meta-analysis to evaluate the prognostic and clinicopathological significance of programmed cell death-1 (PD-1) expression in patients with hepatocellular carcinoma (HCC).

Methods

We searched the Wanfang, Chinese Biomedical Literature, CNKI, PubMed, Embase, and Web of Science databases for relevant articles from inception to 1 July 2020. Statistical analysis was performed using RevMan 5.3 (Cochrane, London, UK) and Stata 14.0 software (StataCorp LP, College Station, TX, USA).

Results

Eight studies involving 732 patients with HCC were included. Higher expression of PD-1 predicted longer disease-free survival [hazard ratio (HR) 0.53, 95% confidence interval (CI): 0.38–0.72]. No significant correlation was observed between PD-1 expression and overall survival (HR 0.89, 95% CI: 0.58–1.35). PD-1 expression was correlated with age [odds ratio (OR) 0.66, 95% CI: 0.46–0.94] and alpha-fetoprotein level (OR 2.27, 95% CI: 1.45–3.55); no correlation was observed with sex, tumor size, tumor metastasis, hepatitis B virus history, tumor stage, or tumor multiplicity. Sensitivity analysis demonstrated no excessive effect on stability of the pooled results. No significant publication bias was found among the identified studies.

Conclusion

PD-1 overexpression predicted better disease-free survival in patients with HCC. Moreover, PD-1 expression was associated with age and alpha-fetoprotein level.

Cancer Stem Cell Functions in Hepatocellular Carcinoma and Comprehensive Therapeutic Strategies

Hepatocellular carcinoma (HCC) is a significant cause of cancer-related mortality owing to resistance to traditional treatments and tumor recurrence after therapy, which leads to poor therapeutic outcomes. Cancer stem cells (CSC) are a small subset of tumor cells with the capability to influence self-renewal, differentiation, and tumorigenesis. A number of surface markers for liver cancer stem cell (LCSC) subpopulations (EpCAM, CD133, CD44, CD13, CD90, OV-6, CD47, and side populations) in HCC have been identified. LCSCs play critical roles in regulating HCC stemness, self-renewal, tumorigenicity, metastasis, recurrence, and therapeutic resistance via genetic mutations, epigenetic disruption, signaling pathway dysregulation, or alterations microenvironment. Accumulating studies have shown that biomarkers for LCSCs contribute to diagnosis and prognosis prediction of HCC, supporting their utility in clinical management and development of therapeutic strategies. Preclinical and clinical analyses of therapeutic approaches for HCC using small molecule inhibitors, oncolytic measles viruses, and anti-surface marker antibodies have demonstrated selective, efficient, and safe targeting of LCSC populations. The current review focuses on recent reports on the influence of LCSCs on HCC stemness, tumorigenesis, and multiple drug resistance (MDR), along with LCSC-targeted therapeutic strategies for HCC.

Oncogenic super-enhancer formation in tumorigenesis and its molecular mechanisms

Super-enhancers (SEs) consist of a cluster of many enhancers bound to a great number of transcription factors. They are critical cis-regulatory elements that determine the identity of various human cell types. During tumorigenesis, DNA mutations and indels, chromosomal rearrangements, three-dimensional chromatin structural changes, and viral infections mediate oncogenic SE activation, and activated SEs have been found to regulate the expression of oncogenic genes. Inhibition specifically targeted to oncogenic SE assembly and activation provides a novel powerful therapeutic strategy for various cancers. In this paper, we first introduce the current understanding of oncogenic SE assembly and activation and then summarize the pathogenic factors and mechanism of oncogenic SE activation. Next, we elaborate on the oncogenic functions of SEs in cancers and the application of SEs as therapeutic targets. Finally, we turn our focus to the use of SEs in basic research and clinical trials.

Drugs that block the assembly and activation of large DNA segments involved in enhancing gene expression could help in the treatment of cancer. Faqing Tang of Hunan Cancer Hospital in Changsha, China, and colleagues review the ways in which cancer cells hijack clusters of gene-regulating sequences known as super-enhancers, regulatory gene regions that normally help determine a cell’s unique identity, to drive the aberrant gene activity that fuels tumor growth. The researchers describe how numerous factors, ranging from internal DNA alterations, both large and small, to viral infections and other external assaults, can spur the formation of cancer-causing super-enhancers, leading to out-of-control gene expression. Therapies that selectively target these super-enhancers are now in early clinical testing. However, more studies of super-enhancers and their role in cancer development are needed to inform future drug development.