Viral expression and molecular profiling in liver tissue versus microdissected hepatocytes in hepatitis B virus-associated hepatocellular carcinoma

Identification of key exosomes-related genes in hepatitis B virus-related hepatocellular carcinoma

One of the primary risk factors for hepatocellular carcinoma (HCC) is the hepatitis B virus (HBV). Exosomes have a significant impact on the dissemination of HBV-infected HCC. This study aimed to screen HBV exosome-related hub genes in HCC for a better understanding of the HCC pathogenic mechanism. First, multiple HBV-induced HCC datasets were collected from the Gene Expression Omnibus (GEO) database, and the exosome-related gene set was obtained from relevant literature. Nine HBV-related HCC exosome hub genes (HP, C9, APOA1, PON1, TTR, LPA, FCN2, FCN3, and MBL2) were selected through differential analysis and network analysis. An analysis of the receiver operation characteristic (ROC) revealed that these genes had good diagnostic value. These hub genes were primarily enriched in biological processes such as the citrate cycle tca cycle, phenylalanine metabolism, and fatty acid metabolism, according to gene set enrichment analysis (GSEA). Furthermore, this study predicted the miRNA (hsa-miR-590-5p) targeting LPA, as well as 12 lncRNAs (AL121655, SAP30-DT, LINC00472, etc.) targeting hsa-miR-590-5p. Finally, nelarabine, methylprednisolone, and methylprednisolone were predicted to be possible medications that target the hub gene based on the CellMiner database. To sum up, this work was crucial for discovering new biomarkers and comprehending the function of exosome-related genes in the growth of HBV-infected HCC.

Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma

Hepatitis B virus (HBV) causes liver cancer, which is the third most common cause of cancer-related death worldwide. Chronic inflammation via HBV in the host hepatocytes causes hepatocyte remodeling (hepatocyte transformation and immortalization) and hepatocellular carcinoma (HCC). Recognizing cancer stages accurately to optimize early screening and diagnosis is a primary concern in the outlook of HBV-induced hepatocyte remodeling and liver cancer. Genomic signatures play important roles in addressing this issue. Recently, machine learning (ML) models and bioinformatics analysis have become very important in discovering novel genomic signatures for the early diagnosis, treatment, and prognosis of HBV-induced hepatic cell remodeling and HCC. We discuss the recent literature on the ML approach and bioinformatics analysis revealed novel genomic signatures for diagnosing and forecasting HBV-associated hepatocyte remodeling and HCC. Various genomic signatures, including various microRNAs and their associated genes, long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs), have been discovered to be involved in the upregulation and downregulation of HBV-HCC. Moreover, these genetic biomarkers also affect different biological processes, such as proliferation, migration, circulation, assault, dissemination, antiapoptosis, mitogenesis, transformation, and angiogenesis in HBV-infected hepatocytes.

Mapping the knowledge domains of literature on hepatocellular carcinoma and liver failure: a bibliometric approach

Background

Hepatocellular carcinoma (HCC) accounts for 75-85% of primary liver cancers, with its incidence continually rising, posing a threat to socio-economic development. Currently, liver resection is the standard treatment for HCC. However, post-hepatectomy liver failure (PHLF) is a severe and formidable postoperative complication that increases patients' medical expenses and mortality risk. Additionally, liver failure can occur at any stage of HCC development, severely affecting patients' quality of life and prognosis.

Method

Using the Web of Science Core Collection, this bibliometric study analyzed English articles and reviews on HCC and liver failure from 2003 to 2023. Bibliometric tools like CiteSpace, VOSviewer, and R-studio were employed for data visualization and analysis, focusing on publication trends, citation metrics, explosive intensity, and collaborative networks. Use the Comparative Toxicogenomics and Genecards databases to screen for genes related to liver failure, and perform enrichment analyses using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PubMed on the identified differentially expressed genes.

Results

The study identified a significant increase in publications on HCC and liver failure, with key contributions from journals such as the World Journal of Gastroenterology and the Journal of Hepatology. The United States, China, and Japan were the leading countries in research output. Prominent authors and institutions, including Kudo Masatoshi and Sun Yat-sen University, were identified. Enrichment analysis showed drug metabolism, oxidative stress, lipid metabolism, and other pathways are closely related to this field. Research hotspots included risk prediction models and novel therapies.

Conclusion

This bibliometric analysis highlights the growing research interest and advancements in HCC and liver failure. Future research should focus on improving risk prediction, developing new therapies, and enhancing international collaboration to address these critical health issues.

TMPRSS2 as a Key Player in Viral Pathogenesis: Influenza and Coronaviruses

TMPRSS2, a human transmembrane protease enzyme, plays a crucial role in the spread of certain viruses, including influenza and coronaviruses. This enzyme promotes viral infection by cleaving viral glycoproteins, which helps viruses like SARS-CoV-2 and influenza A enter cells more effectively. Genetic differences in TMPRSS2 may affect people's susceptibility to COVID-19, underscoring the need for studies that consider diverse populations. Beyond infectious diseases, TMPRSS2 has also been linked to some cancers, suggesting it could be a valuable target for drug development. This review provides a summary of TMPRSS2 inhibitors currently under study, with some already in clinical trials to test their effectiveness against viral infections. As we uncover more about TMPRSS2's role in pathogenesis, it could open new doors for therapies to combat future outbreaks.

Exploring potential key genes and pathways associatedwith hepatocellular carcinoma prognosis through bioinformatics analysis, followed by experimental validation

BACKGROUND

Liver Hepatocellular Carcinoma (LIHC) is a prevalent and aggressive liver cancer with limited therapeutic options. Identifying key genes involved in LIHC can enhance our understanding of its molecular mechanisms and aid in the development of targeted therapies. This study aims to identify differentially expressed genes (DEGs) and key hub genes in LIHC using bioinformatics approaches and experimental validation.

METHOD

We analyzed two LIHC-related datasets, GSE84598 and GSE19665, from the Gene Expression Omnibus (GEO) database to identify DEGs. Differential expression analysis was performed using the limma package in R to identify DEGs between cancerous and non-cancerous liver tissues. A Protein-Protein Interaction (PPI) network was constructed using STRING to determine key hub genes. Further validation of these hub genes was conducted through UALCAN, OncoDB, and the Human Protein Atlas (HPA) databases for mRNA and protein expression levels. Promoter methylation and mutational analyses were performed using cBioPortal. Kaplan-Meier survival analysis assessed the impact of hub gene expression on patient survival. Correlations with immune cell abundance and drug sensitivity were explored using GSCA. Finally, AURKA was knocked down in HepG2 cells, and cell proliferation, colony formation, and wound healing assays were performed.

RESULTS

Analysis identified 180 DEGs, with four key hub genes, including AURKA, BUB1B, CCNA2, and PTTG1 showing significant overexpression and hypomethylation in LIHC tissues. AURKA knockdown in HepG2 cells led to decreased cell proliferation, reduced colony formation, and impaired wound healing, confirming its role in LIHC progression. These hub genes were also hypomethylated and their elevated expression correlated with poor overall survival.

CONCLUSION

AURKA, BUB1B, CCNA2, and PTTG1 are crucial for LIHC pathogenesis and may serve as potential biomarkers or therapeutic targets. Our findings provide new insights into LIHC mechanisms and suggest promising avenues for future research and therapeutic development.

From metabolism to malignancy: the multifaceted role of PGC1α in cancer

PGC1α, a central player in mitochondrial biology, holds a complex role in the metabolic shifts seen in cancer cells. While its dysregulation is common across major cancers, its impact varies. In some cases, downregulation promotes aerobic glycolysis and progression, whereas in others, overexpression escalates respiration and aggression. PGC1α's interactions with distinct signaling pathways and transcription factors further diversify its roles, often in a tissue-specific manner. Understanding these multifaceted functions could unlock innovative therapeutic strategies. However, challenges exist in managing the metabolic adaptability of cancer cells and refining PGC1α-targeted approaches. This review aims to collate and present the current knowledge on the expression patterns, regulators, binding partners, and roles of PGC1α in diverse cancers. We examined PGC1α's tissue-specific functions and elucidated its dual nature as both a potential tumor suppressor and an oncogenic collaborator. In cancers where PGC1α is tumor-suppressive, reinstating its levels could halt cell proliferation and invasion, and make the cells more receptive to chemotherapy. In cancers where the opposite is true, halting PGC1α's upregulation can be beneficial as it promotes oxidative phosphorylation, allows cancer cells to adapt to stress, and promotes a more aggressive cancer phenotype. Thus, to target PGC1α effectively, understanding its nuanced role in each cancer subtype is indispensable. This can pave the way for significant strides in the field of oncology.

Identification of Two Distinct Immune Subtypes in Hepatitis B Virus (HBV)-Associated Hepatocellular Carcinoma (HCC)

HBV is the most common risk factor for HCC development, accounting for almost 50% of cases worldwide. Despite significant advances in immunotherapy, there is limited information on the HBV-HCC tumor microenvironment (TME), which may influence the response to checkpoint inhibitors. Here, we characterize the TME in a unique series of liver specimens from HBV-HCC patients to identify who might benefit from immunotherapy. By combining an extensive immunohistochemistry analysis with the transcriptomic profile of paired liver samples (tumor vs. nontumorous tissue) from 12 well-characterized Caucasian patients with HBV-HCC, we identified two distinct tumor subtypes that we defined immune-high and immune-low. The immune-high subtype, seen in half of the patients, is characterized by a high number of infiltrating B and T cells in association with stromal activation and a transcriptomic profile featuring inhibition of antigen presentation and CTL activation. All the immune-high tumors expressed high levels of CTLA-4 and low levels of PD-1, while PD-L1 was present only in four of six cases. In contrast, the immune-low subtype shows significantly lower lymphocyte infiltration and stromal activation. By whole exome sequencing, we documented that four out of six individuals with the immune-low subtype had missense mutations in the CTNNB1 gene, while only one patient had mutations in this gene in the immune-high subtype. Outside the tumor, there were no differences between the two subtypes. This study identifies two distinctive immune subtypes in HBV-associated HCC, regardless of the microenvironment observed in the surrounding nontumorous tissue, providing new insights into pathogenesis. These findings may be instrumental in the identification of patients who might benefit from immunotherapy.

The management and outcomes of hepatocellular carcinoma in sub-Saharan Africa: a systematic review

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of mortality in sub-Saharan Africa (SSA). This systematic review aimed to appraise all population-based studies describing the management and outcomes of HCC in SSA.

METHODS

A systematic review based on a search in PubMed, PubMed Central, Scopus, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), AfricaWide and Cochrane up to June 2023 was performed. PRISMA guidelines for systematic reviews were followed. The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (registration no: CRD42022363955).

RESULTS

Thirty-nine publications from 15 of 48 SSA countries were identified; 3989 patients were studied. The majority (74%) were male, with median ages ranging from 28 to 54 years. Chronic Hepatitis B infection was a leading aetiology and non-cirrhotic HCC was frequently reported. Curative treatment (liver resection, transplantation and ablation) was offered to 6% of the cohort. Most patients (84%) received only best supportive care (BSC), with few survivors at one year.

CONCLUSION

The majority of SSA countries do not have data reporting outcomes for HCC. Most patients receive only BSC, and curative treatment is seldom available in the region. Outcomes are poor compared to high-income countries.

Exosome-Related FTCD Facilitates M1 Macrophage Polarization and Impacts the Prognosis of Hepatocellular Carcinoma

BACKGROUND

Exosomes are essential for hepatocellular carcinoma (HCC) progression and have garnered significant interest as novel targets for diagnostic, prognostic, and therapeutic approaches. This study aims to identify potential exosome-related biomarkers for the development of useful strategies for HCC diagnosis and therapy.

METHODS

Three datasets obtained from the Gene Expression Omnibus (GEO) were utilized to identify differentially expressed genes (DEGs) in HCC. Through Gene Ontology (GO) analysis and protein-protein interaction (PPI) network, overall survival (OS) analysis, Cox analyses, and diethylnitrosamine (DEN)-induced HCC mouse model detection, exosome-related hub gene was screened out, followed by a prognostic value assessment and immune-correlates analysis based on the Cancer Genome Atlas (TCGA) dataset. The hub gene-containing exosomes derived from Hepa1-6 cells were isolated and characterized using differential ultracentrifugation, transmission electron microscopy scanning, and Western blot. Ultrasound-guided intrahepatic injection, cell co-culture, CCK-8, and flow cytometry were performed to investigate the effects of the hub gene on macrophage infiltration and polarization in HCC.

RESULTS

A total of 83 DEGs enriched in the extracellular exosome term, among which, FTCD, HRA, and C8B showed the strongest association with the progression of HCC. FTCD was independently associated with a protective effect in HCC and selected as the hub gene. The presence of FTCD in exosomes was confirmed. FTCD-stimulated macrophages were polarized towards the M1 type and suppressed HCC cells proliferation.

CONCLUSIONS

FTCD is a potential exosome-related biomarker for HCC diagnosis, prognosis, and treatment. The crosstalk between FTCD-containing exosomes and macrophages in HCC progression deserves further investigation.

Identification of KNOP1 as a prognostic marker in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. This study aimed to evaluate the role and molecular mechanism of lysine-rich nucleolar protein 1 (KNOP1) in HCC.

Methods

Data from The Cancer Genome Atlas (TCGA), genotype-tissue expression (GTEx), and Gene Expression Omnibus (GEO) databases were used to compare KNOP1 expression in normal and HCC tissues. The Human Protein Atlas (HPA) database was used to verify KNOP1 protein expression. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment, protein-protein and gene-gene interaction network, DNA methylation, genetic alteration, and immune cell infiltration analyses were used to analyze the function and pathway enrichment of KNOP1. Finally, receiver operating characteristic (ROC) curves, Kaplan-Meier (KM) analysis, univariate/multivariate Cox regression analyses, and nomograms were used to predict the clinical and prognostic significance of KNOP1.

Results

KNOP1 expression was higher in HCC tissue samples than in normal specimens. Additionally, high KNOP1 expression was positively correlated with T helper 2 (Th2) cells and immune checkpoints. KM analysis, Cox regression analysis, and nomogram prognostic model prediction suggested that high KNOP1 expression is a risk factor for poor HCC prognosis.

Conclusions

KNOP1 overexpression is associated with poor HCC prognosis and increased proportions of immune cell infiltration and checkpoints. KNOP1 is a potential biomarker for evaluating HCC prognosis.

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.

N6 -methyladenosine-modified lncRNA ARHGAP5-AS1 stabilises CSDE1 and coordinates oncogenic RNA regulons in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) ranks fourth among the malignancies leading to cancer-related deaths all around the world. It is increasingly evident that long non-coding RNAs (lncRNAs) are a key mode of hepatocarcinogenesis. As the most prevalent mRNA modification form, N6 -methyladenosine (m6 A) regulates gene expression by impacting multiple aspects of mRNA metabolism. However, there are still no reports on genome-wide screening and functional annotation of m6 A-methylated lncRNAs in HCC.

METHODS

The m6 A modification and biologic functions of ARHGAP5-AS1 in HCC were investigated through a series of biochemical assays. Clinical implications of ARHGAP5-AS1 were examined in tissues from HCC patients.

RESULTS

After systematically analysing the m6 A-seq data of HCC cells, we identified 22 candidate lncRNAs with evidently dysregulated m6 A levels. Among these lncRNAs, we found that ARHGAP5-AS1 is the lncRNA with the highest levels of m6 A modification and significantly increased expression in HCC specimens. METTL14 acts as the m6 A writer of ARHGAP5-AS1 and IGF2BP2 stabilises the lncRNA as its m6 A reader. ARHGAP5-AS1 remarkably promotes malignant behaviours of HCC cells ex vivo and in vivo. We identified oncoprotein CSDE1 working as the interacting protein of the lncRNA and TRIM28 as the E3 ligase of CSDE1 in HCC. Interestingly, ARHGAP5-AS1 could attenuate interactions between CSDE1 and TRIM28, which prevents the degradation of CSDE1 via the ubiquitin-proteasome pathway. Elevated levels of CSDE1 coordinate oncogenic RNA regulons, promote translation of VIM and RAC1 and activate the ERK pathway, which contributes to HCC prognosis.

CONCLUSIONS

Our study reveals a new paradigm in m6 A-modified lncRNAs controlling CSDE1-mediated oncogenic RNA regulons and highlights lncRNAs as potential targets for future therapeutics against HCC.

Dissecting novel mechanisms of hepatitis B virus related hepatocellular carcinoma using meta-analysis of public data

BACKGROUND

Hepatitis B virus (HBV) is a cause of hepatocellular carcinoma (HCC). Interestingly, this process is not necessarily mediated through cirrhosis and may in fact involve oncogenic processes. Prior studies have suggested specific oncogenic gene expression pathways were affected by viral regulatory proteins. Thus, identifying these genes and associated pathways could highlight predictive factors for HCC transformation and has implications in early diagnosis and treatment.

AIM

To elucidate HBV oncogenesis in HCC and identify potential therapeutic targets.

METHODS

We employed our Search, Tag, Analyze, Resource platform to conduct a meta-analysis of public data from National Center for Biotechnology Information’s Gene Expression Omnibus. We performed meta-analysis consisting of 155 tumor samples compared against 185 adjacent non-tumor samples and analyzed results with ingenuity pathway analysis.

RESULTS

Our analysis revealed liver X receptors/retinoid X receptor (RXR) activation and farnesoid X receptor/RXR activation as top canonical pathways amongst others. Top upstream regulators identified included the Ras family gene rab-like protein 6 (RABL6). The role of RABL6 in oncogenesis is beginning to unfold but its specific role in HBV-related HCC remains undefined. Our causal analysis suggests RABL6 mediates pathogenesis of HBV-related HCC through promotion of genes related to cell division, epigenetic regulation, and Akt signaling. We conducted survival analysis that demonstrated increased mortality with higher RABL6 expression. Additionally, homeobox A10 (HOXA10) was a top upstream regulator and was strongly upregulated in our analysis. HOXA10 has recently been demonstrated to contribute to HCC pathogenesis in vitro. Our causal analysis suggests an in vivo role through downregulation of tumor suppressors and other mechanisms.

CONCLUSION

This meta-analysis describes possible roles of RABL6 and HOXA10 in the pathogenesis of HBV-related HCC. RABL6 and HOXA10 represent potential therapeutic targets and warrant further investigation.

Evaluation of tumoral glypican 3 mRNA level as a diagnostic and prognostic biomarker for hepatitis-b virus-associated hepatocellular carcinoma by an integrative transcriptomic meta-analysis and bioinformatics

Aim: The aim of this study is to evaluate the potential of GPC3 mRNA level as a diagnostic and prognostic biomarker for HBV-associated HCC. Materials and Methods: GPC3 mRNA expression in HBV-associated HCC tumor tissues compared to matched adjacent tissues was evaluated by integrative transcriptomic meta-analysis. The results were validated in a different patient cohort and the possible associations between GPC3 mRNA level and the clinical variables were evaluated. Results: Transcriptomic data of HBV-associated HCC tissues (n=61) and matched adjacent tissues (n=61) from four datasets (GSE19665;GSE84402;GSE121248;GSE55092) were included in the meta-analysis. GPC3 mRNA level was found to be higher in tumors than adjacent tissues (fold change=12.88; p= 0;FDR=0). The result was validated in GSE14520, (HBV-associated HCC(n)=203; matched adjacent tissue(n)=203), (log-fold-change= 4.82; adj.p=1.43E-79). It was found that GPC3 mRNA level could distinguish HCC from adjacent tissues with high specificity and sensitivity (AUC=0.9108;95%CI=0.08792-0.9424;p

Overexpressed GNAZ predicts poor outcome and promotes G0/G1 cell cycle progression in hepatocellular carcinoma

AIMS

We aimed to investigate the role of G protein subunit alpha Z(GNAZ) in the progression and prognosis of patients with hepatocellular carcinoma (HCC).

METHODS

Oncomine, GEO, TCGA, GEPIA2, Kaplan-Meier Plotter, TIMER2, Metascape, CCLE, LinkedOmics, and UALCAN databases were used to analyze the differential expression of GNAZ in HCC and normal liver tissues, relationship between GNAZ expression and prognosis of patients with HCC, and expression of GNAZ in common human HCC cell lines. Western blotting was performed to analyze GNAZ expression, while the Cell Counting Kit 8 assay was used to determine cell proliferation, and flow cytometry was used to evaluate the cell cycle and apoptosis. Wound healing and transwell invasion assays were used to investigate cell metastasis and invasion.

RESULTS

Using Oncomine, Gene Expression Omnibus (GEO), and GEPIA2 databases, GNAZ was found to be overexpressed in HCC tissues compared with that in adjacent normal liver tissues, and western blotting analysis showed GNAZ overexpression in seven patients with HCC who underwent surgical resection of HCC and para-cancerous tissues (p < 0.01). Survival analysis revealed that high GNAZ expression was negatively associated with overall survival (OS), recurrence-free survival, progression-free survival, and disease-specific survival in patients with HCC (p < 0.05). GNAZ overexpression was associated with worse 4- month, 6- month, 12- month, 24- month, 36- month, 48- month, and 60-month OS, as well as with different clinicopathological characteristics of patients with HCC, including hepatitis virus infection state; alcohol consumption state; male; female; Asian; microvascular invasion, Stage I-II, Stage II-III, and Stage III-IV; and grade II (Cox regression, p < 0.05). KEGG/GO biological process enrichment indicated that the genes similar to GNAZ in HCC were mainly enriched in the cell cycle, cell cycle phase transition, DNA replication checkpoint, and regulation of G0 to G1 transition. siRNA-GNAZ significantly reduced the viability of JHH-2 and SNU-761 cells from 12 to 96 h; increased the percentage of cells in the G0/G1 phase and decreased that of cells in the S and G2/M phases (p < 0.05); and markedly downregulated the expression of cyclin D, cyclin E, and CDK2 protein. siRNA-GNAZ also significantly increased the percentage of JHH-2 and SNU-761 cell apoptosis at late stages, while the number of surviving cells decreased (p < 0.05), and upregulated the expression of apoptosis-related proteins Bax and caspase 3 protein. Furthermore, siRNA-GNAZ remarkably reduced the healing of scratch wounds in JHH-2 and SNU-761 cells and the number of invasive cells compared with that in the control group (p < 0.001).

CONCLUSION

Our study demonstrated that GNAZ plays a pivotal role as a potential oncogene and predicts poor prognosis in patients with HCC. It promotes tumor proliferation via cell cycle arrest, apoptosis, migration, and invasion. Thus, GNAZ may be a potential candidate biomarker providing useful insight into hepatocarcinogenesis and aggressiveness.

Molecular Signature and Immune Landscape of HCV-Associated Hepatocellular Carcinoma (HCC): Differences and Similarities with HBV-HCC

Introduction

HCC is the third leading cause of cancer-related death worldwide, with chronic viral hepatitis accounting for more than 70% of the cases. Therapeutic options are limited and ineffective. The increasing use of immune-based therapies in solid tumors highlights the need to expand our knowledge on the immunologic microenvironment of HCC.

Methods

Access to liver samples from 20 well-characterized patients with HCC associated with HCV (n = 9) or HBV (n = 11) gave us the opportunity to study the immunologic landscape in these tumors. For each patient, RNA-sequencing was performed on the tumor and surrounding nontumorous tissue.

Results

We found that both HCV- and HBV-HCC are associated with a predominance of downregulated genes (74% and 67%, respectively). Analysis of the immune landscape using a curated gene list showed 216 of 2481 (9%) immune genes in HCV-HCC and 164 of 2560 (6%) in HBV-HCC. However, only 8 immune genes (4%) were upregulated in HCV-HCC and 27 (16.5%) in HBV-HCC. HCV-HCC was characterized by an enrichment of downregulated genes related to T-cell activation and oxidative stress. The dramatic downregulation of immune genes related to T-cell activation in HCV-HCC prompted us to perform an extensive immunohistochemistry analysis on paraffin-embedded liver specimen. Interestingly, we found a significant reduction of immune-cell infiltration (CD3, CD8 and CD20 positive cells) within the tumor. Moreover, we observed that HCV-HCC is characterized by an enrichment of M2-like CD68-positive cells. These data are consistent with the dramatic downregulation of immune-cell infiltration seen in HCV-HCC. Conversely, HBV-HCC was characterized by upregulation of genes related to monocyte/macrophage activation and cell cycle control, and downregulation of genes involved in various cell metabolisms.

Conclusion

This study demonstrates a distinctive molecular signature and immune landscape in HCC of different viral etiology, which could provide new insights into pathogenesis and lead to the development of novel immune-based therapies.

Hepatitis B/D-Related Hepatocellular Carcinoma. A Clinical Literature Review

AIM

Given the current literature data, this article aims to shed light on the epidemiological and clinical effects of HBV, as well as its impact on the development of hepatocellular carcinoma (HCC).

METHODS

A review of the English language literature based on a MEDLINE (PubMed) database was searched. The keywords were cirrhosis, hepatocellular carcinoma, epidemiology, hepatitis delta virus, hepatitis B virus, and co-infection. All references from retrieved papers were reviewed systematically to find additional collection of reports.

RESULTS

The study has broadly confirmed the contribution of HDV viremia to liver disease and cirrhosis. However, uncertainty over the mechanism of action on HCC development remains. As the recent data has demonstrated, the HCC-HDV has a unique molecular profile which is distinct from that of HBV-HCC.

CONCLUSION

Owing to the dependence of HDV on HBV, it is not clear whether HCC is a consequence of the cumulative effect of both HBV and HDV, an effect of the underlying cirrhosis, or a direct oncogenic effect of HDV. Many questions concerning the oncogenic role of HDV remain unanswered. To better understand the role of HDV in carcinogenesis, studies at the molecular level that consider genotype differences should be increased. Multicenter, high-volume, and prospective studies that compare HBV/HDV co-infected and HBV-infected individuals will be pivotal in determining the oncogenic role of HDV.

Absent in melanoma 1-like (AIM1L) serves as a novel candidate for overall survival in hepatocellular carcinoma

Identifying biomarkers for hepatocellular carcinoma (HCC) survival is of great importance for the early detection, monitoring, and predicting for prognosis. This study aimed to investigate the candidate biomarkers for predicting overall survival (OS) in HCC patients. Using RTCGAToolbox, top 50 upregulated differential expressed genes (DEGs) were identified. The least absolute shrinkage and selection operator (LASSO) and Cox models were used to select powerful candidate genes, and log rank method was used to address the survivor functions of potential biomarkers. Selected by LASSO model, ANLN, TTK, AIM1L and person neoplasm cancer status might be candidate parameters associated with OS in HCC patients. After adjusting person neoplasm cancer status, ANLN and TTK levels in Cox model, AIM1L was identified as a risk factor for predicting OS in HCC patients (HR = 1.5, P = 0.037). Validated in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) series, AIM1L was significantly overexpressed in tumor tissues compared to nontumor tissues (all P < 0.0001). HCC patients with high AIM1L in tumor tissues had significantly unfavorable OS compared to those with low AIM1L in TCGA, ICGC, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter datasets (all P < 0.05). Conclusively, AIM1L is upregulated in tumor samples and serves as a novel candidate for predicting unfavorable OS in HCC patients.

The immune niche of the liver

The liver is an essential organ that is critical for the removal of toxins, the production of proteins, and the maintenance of metabolic homeostasis. Behind each liver functional unit, termed lobules, hides a heterogeneous, complex, and well-orchestrated system. Despite parenchymal cells being most commonly associated with the liver's primary functionality, it has become clear that it is the immune niche of the liver that plays a central role in maintaining both local and systemic homeostasis by propagating hepatic inflammation and orchestrating its resolution. As such, the immunological processes that are at play in healthy and diseased livers are being investigated thoroughly in order to understand the underpinnings of inflammation and the potential avenues for restoring homeostasis. This review highlights recent advances in our understanding of the immune niche of the liver and provides perspectives for how the implementation of new transcriptomic, multimodal, and spatial technologies can uncover the heterogeneity, plasticity, and location of hepatic immune populations. Findings from these technologies will further our understanding of liver biology and create a new framework for the identification of therapeutic targets.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

BACKGROUND

The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.

METHODS

GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.

RESULTS

By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.

CONCLUSIONS

Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.

Identification and Validation of Hub Genes Associated With Hepatocellular Carcinoma Via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is the most common malignant tumor of the liver, with high morbidity and mortality, yet its molecular mechanisms of tumorigenesis are still unclear. In this study, gene expression profile of GSE62232 was downloaded from the Gene Expression Omnibus (GEO). The RNA-seq expression data and relative clinical information were retrieved from the Cancer Genome Atlas (TCGA) database. The datasets were analyzed by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain the overlapping genes. Then, we performed a functional enrichment analysis to understand the potential biological functions of these co-expression genes. Finally, we constructed the protein-protein interaction (PPI) analysis combined with survival analysis. MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3 and FOXO1 were identified as the candidate hub genes using the CytoHubba plugin of Cytoscape. Based on survival analysis, the lower expression of FCN3 and FOXO1 were associated with worse overall survival (OS) in HCC patients. Furthermore, the expression levels of FCN3 and FOXO1 were validated by the Human Protein Atlas (HPA) database and the qRT-PCR. In summary, our findings contribute new ideas for the precise early diagnosis, clinical treatment and prognosis of HCC in the future.

Role of chromosome 1q copy number variation in hepatocellular carcinoma

Chromosome 1q often has been observed to be amplified in hepatocellular carcinoma. This review summarizes literature reports of multiple genes that have been proposed as possible 1q amplification drivers. These largely fall within 1q21-1q23. In addition, publicly available copy number alteration data from The Cancer Genome Atlas project were used to identify additional candidate genes involved in carcinogenesis. The most frequent location for gene amplification was 1q22, consistent with the results of the literature search. The genes TPM3 and NUF2 were found to be candidates whose amplification and/or mRNA up-regulation was most highly associated with poorer hepatocellular carcinoma outcomes.

Hepatitis D Virus and Hepatocellular Carcinoma

Hepatitis D virus (HDV) is a small, defective RNA virus that depends on hepatitis B virus (HBV) for virion assembly and transmission. It replicates within the nucleus of hepatocytes and interacts with several cellular proteins. Chronic hepatitis D is a severe and progressive disease, leading to cirrhosis in up to 80% of cases. A high proportion of patients die of liver decompensation or hepatocellular carcinoma (HCC), but the lack of large prospective studies has made it difficult to precisely define the rate of these long-term complications. In particular, the question of whether HDV is an oncogenic virus has been a matter of debate. Studies conducted over the past decade provided evidence that HDV is associated with a significantly higher risk of developing HCC compared to HBV monoinfection. However, the mechanisms whereby HDV promotes liver cancer remain elusive. Recent data have demonstrated that the molecular profile of HCC-HDV is unique and distinct from that of HBV-HCC, with an enrichment of upregulated genes involved in cell-cycle/DNA replication, and DNA damage and repair, which point to genome instability as an important mechanism of HDV hepatocarcinogenesis. These data suggest that HBV and HDV promote carcinogenesis by distinct molecular mechanisms despite the obligatory dependence of HDV on HBV.

Chitinase 3-like 1 is a profibrogenic factor overexpressed in the aging liver and in patients with liver cirrhosis

Older age at the time of infection with hepatitis viruses is associated with an increased risk of liver fibrosis progression. We hypothesized that the pace of fibrosis progression may reflect changes in gene expression within the aging liver. We compared gene expression in liver specimens from 54 adult donors without evidence of fibrosis, including 36 over 40 y old and 18 between 18 and 40 y old. Chitinase 3-like 1 (CHI3L1), which encodes chitinase-like protein YKL-40/CHI3L1, was identified as the gene with the greatest age-dependent increase in expression in liver tissue. We investigated the cellular source of CHI3L1 in the liver and its function using liver tissue specimens and in vitro models. CHI3L1 expression was significantly higher in livers of patients with cirrhosis of diverse etiologies compared with controls represented by patients who underwent liver resection for hemangioma. The highest intrahepatic CHI3L1 expression was observed in cirrhosis due to hepatitis D virus, followed by hepatitis C virus, hepatitis B virus, and alcohol-induced cirrhosis. In situ hybridization of CHI3L1 messenger RNA (mRNA) identified hepatocytes as the major producers of CHI3L1 in normal liver and in cirrhotic tissue, wherein hepatocytes adjacent to fibrous septa showed higher CHI3L1 expression than did those in more distal areas. In vitro studies showed that recombinant CHI3L1 promotes proliferation and activation of primary human hepatic stellate cells (HSCs), the major drivers of liver fibrosis. These findings collectively demonstrate that CHI3L1 promotes liver fibrogenesis through a direct effect on HSCs and support a role for CHI3L1 in the increased susceptibility of aging livers to fibrosis progression.

Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, CDCA5, CENPH, and MCM7, and 4 novel genes, namely, CDC6, CDC45, CDCA8, and MCM4, which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The CDCA8 and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

Transcriptomic identification of HBx-associated hub genes in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies around the world. Among the risk factors involved in liver carcinogenesis, hepatitis B virus (HBV) X protein (HBx) is considered to be a key regulator in hepatocarcinogenesis. Whether HBx promotes or protects against HCC remains controversial, therefore exploring new HBx-associated genes is still important.

METHODS

HBx was overexpressed in HepG2, HepG2.2.15 and SMMC-7721 cell lines, primary mouse hepatocytes and livers of C57BL/6N mice. High-throughput RNA sequencing profiling of HepG2 cells with HBx overexpression and related differentially-expressed genes (DEGs), pathway enrichment analysis, protein-protein interaction networks (PPIs), overlapping analysis were conducted. In addition, Gene Expression Omnibus (GEO) and proteomic datasets of HBV-positive HCC datasets were used to verify the expression and prognosis of selected DEGs. Finally, we also evaluated the known oncogenic role of HBx by oncogenic array analysis.

RESULTS

A total of 523 DEGs were obtained from HBx-overexpressing HepG2 cells. Twelve DEGs were identified and validated in cells transiently transfected with HBx and three datasets of HBV-positive HCC transcription profiles. In addition, using the Kaplan-Meier plotter database, the expression levels of the twelve different genes were further analyzed to predict patient outcomes.

CONCLUSION

Among the 12 identified HBx-associated hub genes, HBV-positive HCC patients expressing ARG1 and TAT showed a good overall survival (OS) and relapse-free survival (RFS). Thus, ARG1 and TAT expression could be potential prognostic markers.

Polymeric immunoglobulin receptor (PIGR) exerts oncogenic functions via activating ribosome pathway in hepatocellular carcinoma

Objective: This report aimed to investigate the potential mechanism of polymeric immunoglobulin receptor (PIGR) in promoting cancer development in hepatocellular carcinoma (HCC). Methods: PIGR expression was investigated in Gene Expression Omnibus (GEO), Oncomine, The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) databases. Relationships between PIGR and HCC survival and clinico-pathological features were conducted in TCGA. RNAseq of PIGR overexpression and knockdown samples in Bel-7404 cells were performed for identifying potential mechanisms. Results: PIGR was significantly overexpressed in tumors compared to nontumors and in HCC serum peripheral blood mononuclear cells (PBMC) than in healthy individuals (all p < 0.05). In TCGA, PIGR was highly altered in 14% HCC patients. PIGR upregulation was significantly associated with poor disease-free survival (p < 0.05). More patients recurred/progressed in PIGR altered group compared to unaltered group (p < 0.01). PIGR was significantly higher in HCC patients with incomplete cirrhosis (p < 0.001) and established cirrhosis (p < 0.05). Fewer patients had N0 lymph node stage in PIGR altered group than those in the unaltered group (p < 0.05). PIGR RNAseq revealed that ribosome signaling was the common pathway in PIGR overexpression and PIGR knockdown samples. RNAseq analysis indicated that RPL10, RPL10A, RPL12, RPL19, RPL36, RPL38, RPL41, RPL6, RPL8, RPS12, RPS14, RPS15A, RPS2, RPS27A and RPSA were significantly upregulated in PIGR overexpression group and downregulated in PIGR underexpression group (all p < 0.05). Conclusions: Aberrant PIGR was associated with HCC recurrence, and PIGR stimulated ribosome pathway might be a potential mechanism.

Identification of miR-4644 as a suitable endogenous normalizer for circulating miRNA quantification in hepatocellular carcinoma

Background: Circulating microRNAs (miRNAs) have proved to be promising biomarkers for early diagnosis and therapeutic monitoring in cancers. Particularly for hepatocellular carcinoma (HCC), detection of circulating miRNA biomarkers as a new diagnostic approach has been written into the latest Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China (2019 edition). However, no general consensus on an ideal endogenous normalizer for circulating miRNAs quantification has been reached, so it will affect the accuracy of quantitative results. In this study, we aim to identify a stable endogenous normalizer for analyzing circulating miRNAs.

Methods: Candidate miRNAs were selected by screening dataset GSE104310, as well as data statistics and analysis. Five commonly reference genes were chosen for further comparison and verification. Then, the expression levels of these genes in serum were analyzed by quantitative reverse transcription PCR (RT-qPCR) among four groups, including patients diagnosed with HCC, chronic hepatitis B (CHB), liver cirrhosis, and healthy subjects. Furthermore, the stability of target genes was evaluated using geNorm, NormFinder, comparative ΔCq programs, and validated by database. We also explored the availability of the miRNA combination, and compared the performance difference between combination and individuals, as well as the selectivity of miRNA references in the combinations.

Results: 11 candidate miRNAs were obtained, and miR-4644 stood out among these miRNAs, and proved to be much more stable than other endogenous miRNAs. Further study showed that miR-4644 exhibited higher stability and expression abundance than other commonly miRNA reference controls. Finally, we discovered the combination of miR-4644 and miR-16 revealed high performance in stability when compared to miRNA individuals. Furthermore, the combination consisted of references with closer nature could give rise to amplification effects in stability.

Conclusions: Our findings demonstrated that miR-4644 is an ideal endogenous normalizer for circulating microRNA quantification in hepatocellular carcinoma. Besides, combining miR-4644 with miR-16 into a whole as a reference control would greatly improve the accuracy of quantification.

Screening and Functional Prediction of Key Candidate Genes in Hepatitis B Virus-Associated Hepatocellular Carcinoma

Background

The molecular mechanism by which hepatitis B virus (HBV) induces hepatocellular carcinoma (HCC) is still unknown. The genomic expression profile and bioinformatics methods were used to investigate the potential pathogenesis and therapeutic targets for HBV-associated HCC (HBV-HCC).

Methods

The microarray dataset GSE55092 was downloaded from the Gene Expression Omnibus (GEO) database. The data was analyzed by the bioinformatics software to find differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, ingenuity pathway analysis (IPA), and protein-protein interaction (PPI) network analysis were then performed on DEGs. The hub genes were identified using Centiscape2.2 and Molecular Complex Detection (MCODE) in the Cytoscape software (Cytoscape_v3.7.2). The survival data of these hub genes was downloaded from the Gene Expression Profiling Interactive Analysis (GEPIA).

Results

A total of 2264 mRNA transcripts were differentially expressed, including 764 upregulated and 1500 downregulated in tumor tissues. GO analysis revealed that these DEGs were related to the small-molecule metabolic process, xenobiotic metabolic process, and cellular nitrogen compound metabolic process. KEGG pathway analysis revealed that metabolic pathways, complement and coagulation cascades, and chemical carcinogenesis were involved. Diseases and biofunctions showed that DEGs were mainly associated with the following diseases or biological function abnormalities: cancer, organismal injury and abnormalities, gastrointestinal disease, and hepatic system disease. The top 10 upstream regulators were predicted to be activated or inhibited by Z-score and identified 25 networks. The 10 genes with the highest degree of connectivity were defined as the hub genes. Cox regression revealed that all the 10 genes (CDC20, BUB1B, KIF11, TTK, EZH2, ZWINT, NDC80, TPX2, MELK, and KIF20A) were related to the overall survival.

Conclusion

Our study provided a registry of genes that play important roles in regulating the development of HBV-HCC, assisting us in understanding the molecular mechanisms that underlie the carcinogenesis and progression of HCC.

Identification of potential key genes and pathways in hepatitis B virus-associated hepatocellular carcinoma by bioinformatics analyses

Chronic hepatitis B virus (HBV) is one of the leading causes of hepatocellular carcinoma (HCC). The precise molecular mechanisms by which HBV contributes to HCC development are not fully understood. The key genes and pathways involved in the transformation of nontumor hepatic tissues into HCC tissues in patients with HBV infection are essential to guide the treatment of HBV-associated HCC. Five datasets were collected from the Gene Expression Omnibus database to form a large cohort. Differentially expressed genes (DEGs) were identified between HCC tissues and nontumor hepatic tissues from HBV-infected patients using the ‘limma’ package. The top 50 upregulated and top 50 downregulated DEGs in HCC vs. nontumor tissues were demonstrated in subsets by heat maps. Based on the DEGs, Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathways enrichment analyses were performed. Several key pathways of the up- and downregulated DEGs were identified and presented by protein-protein interaction (PPI) networks. A total of 1,934 DEGs were identified. The upregulated DEGs were primarily associated with the ‘cell cycle’. Among the DEGs enriched in the ‘cell cycle’ pathway, 6 genes had a log₂-fold change >2: SFN, BUB1B, TTK, CCNB1, CDK1 and CDC20. The downregulated DEGs were primarily associated with the metabolic pathways, such as ‘carbon metabolism’, ‘glycine, serine and threonine metabolism’, ‘tryptophan metabolism’, ‘retinol metabolism’ and ‘alanine, aspartate and glutamate metabolism’. The DEGs in the ‘cell cycle’ and ‘metabolic pathways’ were presented by the PPI networks respectively. Overall, the present study provides new insights into the specific etiology of HCC and molecular mechanisms for the transformation of nontumor hepatic tissues into HCC tissues in patients with a history of HBV infection and several potential therapeutic targets for targeted therapy in these patients.

Integrated analysis of the E2F transcription factors across cancer types

E2F transcription factors are associated with the development of cancer. However, the E2F family genes have not yet been studied in a comprehensive manner. Using The Cancer Genome Atlas, the present study analyzed the functions of the E2F family genes across different types of tumor. It was revealed that compared with normal tissues, the E2F family genes are highly expressed in several types of tumor tissue. Furthermore, E2F transcription factors were significantly enriched in tumor samples across different types of tumor. The high expression levels of E2F family genes were associated with an unfavorable prognosis in liver hepatocellular carcinoma (LIHC) and lung adenocarcinoma (LUAD). Furthermore, patients with pathological T1 stage and iCluster2 molecular subtype of LIHC expressed particularly low levels of E2F family genes. The present study demonstrated that hypo-DNA methylation, DNA amplification and TP53 mutation contributed to the high expression levels of E2F family genes in cancer cells. Finally, the present study revealed that, compared with other types of tumor, the E2F family genes were specifically downregulated in patients with LIHC. The expression levels and prognostic effects of the E2F family genes were validated using the Gene Expression Omnibus database. The results of the present study revealed the biological functions of E2F family genes in the development of cancer and provided potential biomarkers for further therapeutic studies, particularly for patients with LIHC and LUAD.

PXR: a center of transcriptional regulation in cancer

Pregnane X receptor (PXR, NR1I2) is a prototypical member of the nuclear receptor superfamily. PXR can be activated by both endobiotics and xenobiotics. As a key xenobiotic receptor, the cellular function of PXR is mostly exerted by its binding to the regulatory gene sequences in a ligand-dependent manner. Classical downstream target genes of PXR participate in xenobiotic responses, such as detoxification, metabolism and inflammation. Emerging evidence also implicates PXR signaling in the processes of apoptosis, cell cycle arrest, proliferation, angiogenesis and oxidative stress, which are closely related to cancer. Here, we discussed, in addition to the characterization of PXR per se, the biological function and regulatory mechanism of PXR signaling in cancer, and its potential for the targeted prevention and therapeutics.

Oncogenic Roles of RAD51AP1 in Tumor Tissues Related to Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma

OBJECTIVE

This study aimed to investigate the associations between RAD51AP1 and the outcomes of hepatocellular carcinoma (HCC).

METHODS

RAD51AP1 expression levels were compared in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. The Liver Hepatocellular Carcinoma (TCGA, Provisional) and GSE36376 datasets were used for survival analysis. RAD51AP1 associations with clinicopathological features were determined with the GSE36376 dataset.

RESULTS

RAD51AP1 mRNA expression was significantly upregulated in advanced liver fibrosis samples (S3-4 vs. S0-2 and G3-4 vs. G0-2) from hepatitis B virus (HBV)-related liver fibrosis patients and in tumor tissues and peripheral blood mononuclear cells (PBMCs) from HCC patients (all P < 0.05). HCC patients with high RAD51AP1 expression had significantly worse overall survival (OS) and disease-free survival (DFS) than those with low RAD51AP1 expression (P = 0.0034 and P = 0.0012, respectively) in the TCGA dataset, and these findings were validated with the GSE36376 dataset (P = 0.0074 and P = 0.0003, respectively). A Cox regression model indicated that RAD51AP1 was a risk factor for OS and DFS in HCC patients in GSE36376 (HR = 1.54, 95% CI = 1.02-2.32, P = 0.04 and HR = 1.71, 95% CI = 1.22-2.39, P = 0.002, respectively). Moreover, RAD51AP1 mRNA expression increased gradually with increasing tumor stage, including stratification by American Joint Committee on Cancer (AJCC) stages, Barcelona Clinic Liver Cancer (BCLC) stages and Edmondson grades. In addition, RAD51AP1 was overexpressed in HCC patients with intrahepatic metastasis, major portal vein invasion, vascular invasion and/or an alpha-fetoprotein (AFP) level > 300 ng/ml.

CONCLUSIONS

Contributing to an advanced tumor stage, intrahepatic metastasis, vascular invasion and AFP level elevation, RAD51AP1 upregulation was significantly associated with OS and DFS in HCC patients.

mTOR/HDAC1 Crosstalk Mediated Suppression of ADH1A and ALDH2 Links Alcohol Metabolism to Hepatocellular Carcinoma Onset and Progression in silico

Hepatocellular carcinoma (HCC) is ranked the third deadliest cancer worldwide whose molecular pathogenesis is not fully understood. Although deregulated metabolic pathways have been implicated in HCC onset and progression, the mechanisms triggering this metabolic imbalance are yet to be explored. Here, we identified a gene signature coding catabolic enzymes (Cat-GS) involved in key metabolic pathways like amino acid, lipid, carbohydrate, drug, and retinol metabolism as suppressed in HCC. A higher expression of deregulated Cat-GS is associated with good survival and less aggressive disease state in HCC patients. On the other hand, we identified mTOR signaling as a key determinant in HCC onset and progression, whose hyperactivation is found associated with poor survival and aggressive disease state in HCC patients. Next, out of Cat-GS, we established two key regulators of alcohol metabolism, alcohol dehydrogenase 1A (ADH1A) and aldehyde dehydrogenase 2 (ALDH2), as being transcriptionally suppressed by histone deacetylase 1 (HDAC1) at the downstream of mTORC1 signaling. Suppressed ADH1A and ALDH2 expression aligns well with HCC-specific molecular profile and can efficiently predict disease onset and progression, whereas higher ADH1A and ALDH2 expression is associated with good survival and less aggressive disease state in HCC patients. Overall, our in silico findings suggest that transcriptional suppression of alcohol metabolism regulators, ADH1A and ALDH2, at the downstream of mTOR signaling is, in part, responsible for triggering oncogenic transformation of hepatocytes resulting in disease onset and progression in HCC.

Identification of significant gene and pathways involved in HBV-related hepatocellular carcinoma by bioinformatics analysis

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor affecting the digestive system and causes serious financial burden worldwide. Hepatitis B virus (HBV) is the main causative agent of HCC in China. The present study aimed to investigate the potential mechanisms underlying HBV-related HCC and to identify core biomarkers by integrated bioinformatics analyses.

Methods

In the present study, HBV-related HCC GSE19665, GSE55092, GSE94660 and GSE121248 expression profiles were downloaded from the Gene Expression Omnibus database. These databases contain data for 299 samples, including 145 HBV-related HCC tissues and 154 non-cancerous tissues (from patients with chronic hepatitis B). The differentially expressed genes (DEGs) from each dataset were integrated and analyzed using the RobustRankAggreg (RRA) method and R software, and the integrated DEGs were identified. Subsequently, the gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool, and the protein-protein interaction (PPI) network was constructed using STRING and visualized using Cytoscape software. Finally, hub genes were identified, and the cBioPortal online platform was used to analyze the association between the expression of hub genes and prognosis in HCC.

Results

First, 341 DEGs (117 upregulated and 224 downregulated) were identified from the four datasets. Next, GO analysis showed that the upregulated genes were mainly involved in cell cycle, mitotic spindle, and adenosine triphosphate binding. The majority of the downregulated genes were involved in oxidation reduction, extracellular region, and electron carrier activity. Signaling pathway analysis showed that the integrated DEGs shared common pathways in retinol metabolism, drug metabolism, tryptophan metabolism, caffeine metabolism, and metabolism of xenobiotics by cytochrome P450. The integrated DEG PPI network complex comprised 288 nodes, and two important modules with high degree were detected using the MCODE plug-in. The top ten hub genes identified from the PPI network were SHCBP1, FOXM1, KIF4A, ANLN, KIF15, KIF18A, FANCI, NEK2, ECT2, and RAD51AP1. Finally, survival analysis revealed that patients with HCC showing altered ANLN and KIF18A expression profiles showed worse disease-free survival. Nonetheless, patients with FOXM1, NEK2, RAD51AP1, ANLN, and KIF18A alterations showed worse overall survival.

Conclusions

The present study identified key genes and pathways involved in HBV-related HCC, which improved our understanding of the mechanisms underlying the development and recurrence of HCC and identified candidate targets for the diagnosis and treatment of HBV-related HCC.

A 9‑lncRNA risk score system for predicting the prognosis of patients with hepatitis B virus‑positive hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and can be induced by hepatitis B virus (HBV) infection. The aim of the present study was to screen prognosis‑associated long noncoding RNAs (lncRNAs) and construct a risk score system for the disease. The RNA‑sequencing data of patients with HCC (including 100 HCC samples and 26 normal samples) were extracted from The Cancer Genome Atlas (TCGA) database. In addition, GSE55092, GSE19665 and GSE10186 datasets were downloaded from the Gene Expression Omnibus database. Combined with weighted gene co‑expression network analysis, the identification and functional annotation of stable modules was performed. Using the MetaDE package, the consensus differentially expressed RNAs (DE‑RNAs) were analyzed. To construct a risk score system, prognosis‑associated lncRNAs and the optimal lncRNA combination were separately analyzed by survival and penalized packages. Finally, pathway enrichment analysis for the nodes in an lncRNA‑mRNA network was conducted via Gene Set Enrichment Analysis. A total of four stable modules and 3,051 consensus DE‑RNAs were identified. The stable modules were significantly associated with the histological grades of HCC, tumor, node and metastasis stage, pathological stage, recurrence and exposure to radiation therapy. A 9‑lncRNA optimal combination [DiGeorge syndrome critical region gene 9, glucosidase, β, acid 3 (GBA3), HLA complex group 4, N‑acetyltransferase 8B, neighbor of breast cancer 1 gene 2, prostate androgen‑regulated transcript 1, ret finger protein like 1 antisense RNA 1, solute carrier family 22 member 18 antisense and T‑cell leukemia/lymphoma 6] was selected from the 14 prognosis‑associated lncRNAs, and was further supported by the validation dataset, GSE10186. The lncRNA‑mRNA co‑expression network revealed lncRNA GBA3 as a positive regulator of phosphoenolpyruvate carboxykinase 2, an important enzyme in the metabolic pathway of gluconeogenesis. A risk score system was established based on the optimal 9 lncRNAs, which may be valuable for predicting the prognosis of patients with HBV‑positive HCC and improving understanding of mechanisms associated with the pathogenesis of this disease. On the contrary, a larger, independent cohort of patients is required to further validate the risk‑score system.

Use of Expression Profiles of HBV-DNA Integrated Into Genomes of Hepatocellular Carcinoma Cells to Select T Cells for Immunotherapy

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) is often associated with hepatitis B virus (HBV) infection. Cells of most HBV-related HCCs contain HBV-DNA fragments that do not encode entire HBV antigens. We investigated whether these integrated HBV-DNA fragments encode epitopes that are recognized by T cells and whether their presence in HCCs can be used to select HBV-specific T-cell receptors (TCRs) for immunotherapy.

METHODS

HCC cells negative for HBV antigens, based on immunohistochemistry, were analyzed for the presence of HBV messenger RNAs (mRNAs) by real-time polymerase chain reaction, sequencing, and Nanostring approaches. We tested the ability of HBV mRNA-positive HCC cells to generate epitopes that are recognized by T cells using HBV-specific T cells and TCR-like antibodies. We then analyzed HBV gene expression profiles of primary HCCs and metastases from 2 patients with HCC recurrence after liver transplantation. Using the HBV-transcript profiles, we selected, from a library of TCRs previously characterized from patients with self-limited HBV infection, the TCR specific for the HBV epitope encoded by the detected HBV mRNA. Autologous T cells were engineered to express the selected TCRs, through electroporation of mRNA into cells, and these TCR T cells were adoptively transferred to the patients in increasing numbers (1 × 10⁴-10 × 10⁶ TCR+ T cells/kg) weekly for 112 days or 1 year. We monitored patients' liver function, serum levels of cytokines, and standard blood parameters. Antitumor efficacy was assessed based on serum levels of alpha fetoprotein and computed tomography of metastases.

RESULTS

HCC cells that did not express whole HBV antigens contained short HBV mRNAs, which encode epitopes that are recognized by and activate HBV-specific T cells. Autologous T cells engineered to express TCRs specific for epitopes expressed from HBV-DNA in patients' metastases were given to 2 patients without notable adverse events. The cells did not affect liver function over a 1-year period. In 1 patient, 5 of 6 pulmonary metastases decreased in volume during the 1-year period of T-cell administration.

CONCLUSIONS

HCC cells contain short segments of integrated HBV-DNA that encodes epitopes that are recognized by and activate T cells. HBV transcriptomes of these cells could be used to engineer T cells for personalized immunotherapy. This approach might be used to treat a wider population of patients with HBV-associated HCC.

Systems biology based meth-miRNA-mRNA regulatory network identifies metabolic imbalance and hyperactive cell cycle signaling involved in hepatocellular carcinoma onset and progression

Background

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer associated deaths worldwide. Independent studies have proposed altered DNA methylation pattern and aberrant microRNA (miRNA) levels leading to abnormal expression of different genes as important regulators of disease onset and progression in HCC. Here, using systems biology approaches, we aimed to integrate methylation, miRNA profiling and gene expression data into a regulatory methylation-miRNA–mRNA (meth-miRNA–mRNA) network to better understand the onset and progression of the disease.

Methods

Patients’ gene methylation, miRNA expression and gene expression data were retrieved from the NCBI GEO and TCGA databases. Differentially methylated genes, and differentially expressed miRNAs and genes were identified by comparing respective patients’ data using two tailed Student’s t-test. Functional annotation and pathway enrichment, miRNA–mRNA inverse pairing and gene set enrichment analyses (GSEA) were performed using DAVID, miRDIP v4.1 and GSEA tools respectively. meth-miRNA–mRNA network was constructed using Cytoscape v3.5.1. Kaplan–Meier survival analyses were performed using R script and significance was calculated by Log-rank (Mantel-Cox) test.

Results

We identified differentially expressed mRNAs, miRNAs, and differentially methylated genes in HCC as compared to normal adjacent tissues by analyzing gene expression, miRNA expression, and methylation profiling data of HCC patients and integrated top miRNAs along with their mRNA targets and their methylation profile into a regulatory meth-miRNA–mRNA network using systems biology approach. Pathway enrichment analyses of identified genes revealed suppressed metabolic pathways and hyperactive cell cycle signaling as key features of HCC onset and progression which we validated in 10 different HCC patients’ datasets. Next, we confirmed the inverse correlation between gene methylation and its expression, and between miRNA and its targets’ expression in various datasets. Furthermore, we validated the clinical significance of identified methylation, miRNA and mRNA signatures by checking their association with clinical features and survival of HCC patients.

Conclusions

Overall, we suggest that simultaneous (1) reversal of hyper-methylation and/or oncogenic miRNA driven suppression of genes involved in metabolic pathways, and (2) induction of hyper-methylation and/or tumor suppressor miRNA driven suppression of genes involved in cell cycle signaling have potential of inhibiting disease aggressiveness, and predicting good survival in HCC.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0804-3) contains supplementary material, which is available to authorized users.

Cytochrome P450 family members are associated with fast-growing hepatocellular carcinoma and patient survival: An integrated analysis of gene expression profiles

BACKGROUND/AIMS

The biological heterogeneity of hepatocellular carcinoma (HCC) makes prognosis difficult. Although many molecular tools have been developed to assist in stratification and prediction of patients by using microarray analysis, the classification and prediction are still improvable because the high-through microarray contains a large amount of information. Meanwhile, gene expression patterns and their prognostic value for HCC have not been systematically investigated. In order to explore new molecular diagnostic and prognostic biomarkers, the gene expression profiles between HCCs and adjacent nontumor tissues were systematically analyzed in the present study.

MATERIALS AND METHODS

In this study, gene expression profiles were obtained by repurposing five Gene Expression Omnibus databases. Differentially expressed genes were identified by using robust rank aggregation method. Three datasets (GSE14520, GSE36376, and GSE54236) were used to validate the associations between cytochrome P450 (CYP) family genes and HCC. GSE14520 was used as the training set. GSE36376 and GSE54236 were considered as the testing sets.

RESULTS

From the training set, a four-CYP gene signature was constructed to discriminate between HCC and nontumor tissues with an area under curve (AUC) of 0.991. Accuracy of this four-gene signature was validated in two testing sets (AUCs for them were 0.973 and 0.852, respectively). Moreover, this gene signature had a good performance to make a distinction between fast-growing HCC and slow-growing HCC (AUC = 0.898), especially for its high sensitivity of 95%. At last, CYP2C8 was identified as an independent risk factor of recurrence-free survival (hazard ratio [HR] =0.865, 95% confidence interval [CI], 0.754-0.992, P = 0.038) and overall survival (HR = 0.849; 95% CI, 0.716-0.995, P = 0.033).

CONCLUSIONS

In summary, our results confirmed for the first time that a four-CYP gene (CYP1A2, CYP2E1, CYP2A7, and PTGIS) signature is associated with fast-growing HCC, and CYP2C8 is associated with patient survival. Our findings could help to identify HCC patients at high risk of rapid growth and recurrence.

Upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in Tumor Tissues Predicted Worse Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma Patients

OBJECTIVE

To evaluate the association between upregulated differentially expressed genes (DEGs) and the outcomes of patients with hepatocellular carcinoma (HCC).

METHODS

Using Gene Expression Omnibus (GEO) datasets including GSE45436, GSE55092, GSE60502, GSE84402, and GSE17548, we detected upregulated DEGs in tumors. KEGG, GO, and Reactome enrichment analysis of the DEGs was conducted to clarify their function. The impact of the upregulated DEGs on patients' survival was analyzed based on TCGA profile.

RESULTS

161 shared upregulated DEGs were identified among GSE45436, GSE55092, GSE60502, and GSE84402 profiles. Cell cycle was the shared pathway/biological process in the gene sets investigation among databases of KEGG, GO, and Reactome. After being validated in GSE17548, 13 genes including BUB1B, CCNA2, CCNB1, CCNE2, CDC20, CDC6, CDC7, CDK1, CDK4, CDKN2A, CHEK1, MAD2L1, and MCM3 in cell cycle pathway were shared in the three databases for enrichment. The expression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 was upregulated in HCC tissues when compared with adjacent normal tissues in 6.67%, 7.5%, 8.06%, 5.56%, and 9.72% of HCC patients, respectively. Overexpression of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues accounted for poorer overall survival (OS) and disease-free survival (DFS) in HCC patients (all log rank P < 0.05). BUB1B, CCNB1, CDC7, CDC20, and MCM3 were all overexpressed in HCC patients with neoplasm histologic grade G3-4 compared to those with G1-2 (all P < 0.05). BUB1B, CCNB1, and CDC20 were significantly upregulated in HCC patients with vascular invasion (all P < 0.05). Additionally, levels of BUB1B, CCNB1, CDC7, and CDC20 were significantly higher in HCC patients deceased, recurred, or progressed (all P < 0.05).

CONCLUSION

Correlated with advanced histologic grade and/or vascular invasion, upregulation of BUB1B, CCNB1, CDC7, CDC20, and MCM3 in HCC tissues predicted worse OS and DFS in HCC patients. These genes could be novel therapeutic targets for HCC treatment.

Kynurenic Acid Protects against Thioacetamide-Induced Liver Injury in Rats

Acute liver failure (ALF) is a life-threatening disorder of liver function. Kynurenic acid (KYNA), a tryptophan metabolite formed along the kynurenine metabolic pathway, possesses anti-inflammatory and antioxidant properties. Its presence in food and its potential role in the digestive system was recently reported. The aim of this study was to define the effect of KYNA on liver failure. The Wistar rat model of thioacetamide-induced liver injury was used. Morphological and biochemical analyses as well as the measurement of KYNA content in liver and hepatoprotective herbal remedies were conducted. The significant attenuation of morphological disturbances and aspartate and alanine transaminase activities, decrease of myeloperoxidase and tumor necrosis factor-α, and elevation of interleukin-10 levels indicating the protective effect of KYNA in thioacetamide (TAA) - induced liver injury were discovered. In conclusion, the hepatoprotective role of KYNA in an animal model of liver failure was documented and the use of KYNA in the treatment of ALF was suggested.

Novel tumor suppressor SPRYD4 inhibits tumor progression in hepatocellular carcinoma by inducing apoptotic cell death

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-associated deaths worldwide. Although recent studies have proposed different biomarkers for HCC progression and therapy resistance, a better understanding of the molecular mechanisms underlying HCC progression and recurrence, as well as the identification of molecular markers with a higher diagnostic accuracy, are necessary for the development of more effective clinical management strategies. Here, we aimed to identify novel players in HCC progression.

METHODS

SPRYD4 mRNA and protein expression analyses were carried out on a normal liver-derived cell line (HL-7702) and four HCC-derived cell lines (HepG2, SMMC7721, Huh-7, BEL-7402) using qRT-PCR and Western blotting, respectively. Cell proliferation Cell Counting Kit-8 (CCK-8) assays, protein expression analyses for apoptosis markers using Western blotting, and Caspase-Glo 3/7 apoptosis assays were carried out on the four HCC-derived cell lines. Expression comparison, functional annotation, gene set enrichment, correlation and survival analyses were carried out on patient data retrieved from the NCBI Gene module, the NCBI GEO database and the TCGA database.

RESULTS

Through a meta-analysis we found that the expression of SPRYD4 was downregulated in primary HCC tissues compared to non-tumor tissues. We also found that the expression of SPRYD4 was downregulated in HCC-derived cells compared to normal liver-derived cells. Subsequently, we found that the expression of SPRYD4 was inversely correlated with a gene signature associated with HCC cell proliferation. Exogenous SPRYD4 expression was found to inhibit HCC cell proliferation by inducing apoptotic cell death. We also found that SPRYD4 expression was associated with a good prognosis and that its expression became downregulated when HCCs progressed towards more aggressive stages and higher grades. Finally, we found that SPRYD4 expression may serve as a biomarker for a good overall and relapse-free survival in HCC patients.

CONCLUSIONS

Our data indicate that a decreased SPRYD4 expression may serve as an independent predictor for a poor prognosis in patients with HCC and that increased SPRYD4 expression may reduce HCC growth and progression through the induction of apoptotic cell death, thereby providing a potential therapeutic target.

DNA topoisomerase 1 and 2A function as oncogenes in liver cancer and may be direct targets of nitidine chloride

The aim of the present study was to determine the role of topoisomerase 1 (TOP1) and topoisomerase 2A (TOP2A) in liver cancer (LC), and to investigate the inhibitory effect of nitidine chloride (NC) on these two topoisomerases. Immunohistochemistry (IHC) staining and microarray or RNA sequencing data mining showed markedly higher expression of TOP1 and TOP2A at the protein and mRNA levels in LC tissues compared with that in control non-tumor tissues. The prognostic values of TOP1 and TOP2A expression were also estimated based on data from The Cancer Genome Atlas. The elevated expression levels of TOP1 and TOP2A were closely associated with poorer overall survival and disease-free survival rates. When patients with LC were divided into high- and low-risk groups according to their prognostic index, TOP1 and TOP2A were highly expressed in the high-risk group. Bioinformatics analyses conducted on the co-expressed genes of TOP1 and TOP2A revealed that the topoisomerases were involved in several key cancer-related pathways, including the 'p53 pathway', 'pathway in cancer' and 'apoptosis signaling pathway'. Reverse transcription-quantitative polymerase chain reaction and IHC performed on triplicate tumor tissue samples from LC xenografts in control or NC-treated nude mice showed that NC treatment markedly reduced the protein and mRNA expression of TOP1 and TOP2A in LC tissues. Molecular docking studies further confirmed the direct binding of NC to TOP1 and TOP2A. In conclusion, the present findings indicate that TOP1 and TOP2A are oncogenes in LC and could serve as potential biomarkers for the prediction of the prognosis of patients with LC and for identification of high-risk cases, thereby optimizing individual treatment management. More importantly, the findings support TOP1 and TOP2A as potential drug targets of NC for the treatment of LC.

FOXO1: Another avenue for treating digestive malignancy?

Digestive malignancies are the leading cause of mortality among all neoplasms, contributing to estimated 3 million deaths in 2012 worldwide. The mortality rate hassurpassed lung cancer and prostate cancer in recent years. The transcription factor Forkhead Box O1 (FOXO1) is a key member of Forkhead Box family, regulating diverse cellular functions during tumor initiation, progression and metastasis. In this review, we focus on recent studies investigating the antineoplastic role of FOXO1 in digestive malignancy. This review aims to serve as a guide for further research and implicate FOXO1 as a potent therapeutic target in digestive malignancy.

Molecular Signature and Mechanisms of Hepatitis D Virus-Associated Hepatocellular Carcinoma

There is limited data on the molecular mechanisms whereby hepatitis D virus (HDV) promotes liver cancer. Therefore, serum and liver specimens obtained at the time of liver transplantation from well-characterized patients with HDV-HCC (n = 5) and with non-HCC HDV cirrhosis (n = 7) were studied using an integrated genomic approach. Transcriptomic profiling was performed using laser capture-microdissected (LCM) malignant and nonmalignant hepatocytes, tumorous and nontumorous liver tissue from patients with HDV-HCC, and liver tissue from patients with non-HCC HDV cirrhosis. HDV-HCC was also compared with hepatitis B virus (HBV) HBV-HCC alone, and hepatitis C virus (HCV) HCV-HCC. HDV malignant hepatocytes were characterized by an enrichment of upregulated transcripts associated with pathways involved in cell-cycle/DNA replication, damage, and repair (Sonic Hedgehog, GADD45, DNA-damage-induced 14-3-3σ, cyclins and cell-cycle regulation, cell cycle: G₂-M DNA-damage checkpoint regulation, and hereditary breast cancer). Moreover, a large network of genes identified functionally relate to DNA repair, cell cycle, mitotic apparatus, and cell division, including 4 cancer testis antigen genes, attesting to the critical role of genetic instability in this tumor. Besides being overexpressed, these genes were also strongly coregulated. Gene coregulation was high not only when compared with nonmalignant hepatocytes, but also to malignant hepatocytes from HBV-HCC alone or HCV-HCC. Activation and coregulation of genes critically associated with DNA replication, damage, and repair point to genetic instability as an important mechanism of HDV hepatocarcinogenesis. This specific HDV-HCC trait emerged also from the comparison of the molecular pathways identified for each hepatitis virus-associated HCC. Despite the dependence of HDV on HBV, these findings suggest that HDV and HBV promote carcinogenesis by distinct molecular mechanisms.Implications: This study identifies a molecular signature of HDV-associated hepatocellular carcinoma and suggests the potential for new biomarkers for early diagnostics. Mol Cancer Res; 16(9); 1406-19. ©2018 AACR.

Development Of A Three-Gene Prognostic Signature For Hepatitis B Virus Associated Hepatocellular Carcinoma Based On Integrated Transcriptomic Analysis

Integration of public genome-wide gene expression data together with Cox regression analysis is a powerful weapon to identify new prognostic gene signatures for cancer diagnosis and prognosis. Hepatitis B virus (HBV) is a major cause of hepatocellular carcinoma (HCC), however, it remains largely unknown about the specific gene prognostic signature of HBV-associated HCC. Using Robust Rank Aggreg (RRA) method to integrate seven whole genome expression datasets, we identified 82 up-regulated genes and 577 down-regulated genes in HBV-associated HCC patients. Combination of several enrichment analysis, univariate and multivariate Cox proportional hazards regression analysis, we revealed that a three-gene (SPP2, CDC37L1, and ECHDC2) prognostic signature could act as an independent prognostic indicator for HBV-associated HCC in both the discovery cohort and the internal testing cohort. Gene set enrichment analysis showed that the high-risk group with lower expression levels of the three genes was enriched in bladder cancer and cell cycle pathway, whereas the low-risk group with higher expression levels of the three genes was enriched in drug metabolism-cytochrome P450, PPAR signaling pathway, fatty acid and histidine metabolisms. This indicates that patients of HBV-associated HCC with higher expression of these three genes may preserve relatively good hepatic cellular metabolism and function, which may also protect HCC patients from persistent drug toxicity in response to various medication. Our findings suggest a three-gene prognostic model that serves as a specific prognostic signature for HBV-associated HCC.

Infection with hepatitis C virus depends on TACSTD2, a regulator of claudin-1 and occludin highly downregulated in hepatocellular carcinoma

Entry of hepatitis C virus (HCV) into hepatocytes is a complex process that involves numerous cellular factors, including the scavenger receptor class B type 1 (SR-B1), the tetraspanin CD81, and the tight junction (TJ) proteins claudin-1 (CLDN1) and occludin (OCLN). Despite expression of all known HCV-entry factors, in vitro models based on hepatoma cell lines do not fully reproduce the in vivo susceptibility of liver cells to primary HCV isolates, implying the existence of additional host factors which are critical for HCV entry and/or replication. Likewise, HCV replication is severely impaired within hepatocellular carcinoma (HCC) tissue in vivo, but the mechanisms responsible for this restriction are presently unknown. Here, we identify tumor-associated calcium signal transducer 2 (TACSTD2), one of the most downregulated genes in primary HCC tissue, as a host factor that interacts with CLDN1 and OCLN and regulates their cellular localization. TACSTD2 gene silencing disrupts the typical linear distribution of CLDN1 and OCLN along the cellular membrane in both hepatoma cells and primary human hepatocytes, recapitulating the pattern observed in vivo in primary HCC tissue. Mechanistic studies suggest that TACSTD2 is involved in the phosphorylation of CLDN1 and OCLN, which is required for their proper cellular localization. Silencing of TACSTD2 dramatically inhibits HCV infection with a pan-genotype effect that occurs at the level of viral entry. Our study identifies TACSTD2 as a novel regulator of two major HCV-entry factors, CLDN1 and OCLN, which is strongly downregulated in malignant hepatocytes. These results provide new insights into the complex process of HCV entry into hepatocytes and may assist in the development of more efficient cellular systems for HCV propagation in vitro.

Adaptation of Laser Microdissection Technique to Nanostring RNA Analysis in the Study of a Spontaneous Metastatic Mammary Carcinoma Mouse Model

The mouse model characterized by spontaneous lung metastasis from JygMC (A) cells closely resembles the human triple negative breast cancer (TNBC) subtype. The primary tumors morphologically present both epithelial and spindle-like cells, but metastases in lung parenchyma display only adenocarcinoma properties. In the study of molecular signatures, laser capture microdissection (LCM) on frozen tissue sections was used to separate the following regions of interest: the epithelial-mesenchymal transition (EMT), mesenchymal-epithelial transition (MET), carcinoma, lung metastases, normal mammary gland and normal lung parenchyma. NanoString was selected for the study of molecular signatures in LCM targets as a reliable downstream gene expression platform allowing analysis of tissue lysates without RNA extraction and amplification. This chapter provides detailed protocols for the collection of tissue, LCM sample preparation and dissection, production of lysates, extraction, and quality control of RNA for NanoString analysis, as well as the methodology of Nanostring gene expression profiling experiment.