A pilot systematic genomic comparison of recurrence risks of hepatitis B virus-associated hepatocellular carcinoma with low- and high-degree liver fibrosis

Epitranscriptomic cytidine methylation of the hepatitis B viral RNA is essential for viral reverse transcription and particle production

Epitranscriptomic RNA modifications have emerged as important regulators of the fate and function of viral RNAs. One prominent modification, the cytidine methylation 5-methylcytidine (m5C), is found on the RNA of HIV-1, where m5C enhances the translation of HIV-1 RNA. However, whether m5C functionally enhances the RNA of other pathogenic viruses remains elusive. Here, we surveyed a panel of commonly found RNA modifications on the RNA of hepatitis B virus (HBV) and found that HBV RNA is enriched with m5C as well as ten other modifications, at stoichiometries much higher than host messenger RNA (mRNA). Intriguingly, m5C is mostly found on the epsilon hairpin, an RNA element required for viral RNA encapsidation and reverse transcription, with these m5C mainly deposited by the cellular methyltransferase NSUN2. Loss of m5C from HBV RNA due to NSUN2 depletion resulted in a partial decrease in viral core protein (HBc) production, accompanied by a near-complete loss of the reverse transcribed viral DNA. Similarly, mutations introduced to remove the methylated cytidines resulted in a loss of HBc production and reverse transcription. Furthermore, pharmacological disruption of m5C deposition led to a significant decrease in HBV replication. Thus, our data indicate m5C methylations as a critical mediator of the epsilon elements' function in HBV virion production and reverse transcription, suggesting the therapeutic potential of targeting the m5C methyltransfer process on HBV epsilon as an antiviral strategy.

NFKBIZ regulates NFκB signaling pathway to mediate tumorigenesis and metastasis of hepatocellular carcinoma by direct interaction with TRIM16

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence and mortality rates. NFKBIZ, a member of the nuclear factor kappa B inhibitory family, is closely related to tumor progression. However, the precise role of NFKBIZ in HCC remains unclear. To explore this, we conducted a series of experiments from clinic to cells. Western blot and qPCR revealed a significant downregulation of NFKBIZ in human HCC tissues. Clinical character analysis showed that the patients with lower NFKBIZ expression had poorer prognosis and higher clinical stage. By using CCK-8, wound healing, transwell invasion and migration assay, we discovered that NFKBIZ expression was reversely associated with the proliferation, invasion, and migration ability of HCC cells in vitro. Additionally, the results obtained from xenograft assay and lung metastasis models showed that NFKBIZ overexpression inhibited the growth and metastasis of HCC cells in vivo. Western blot and immunofluorescence assay further revealed that NFKBIZ mediated HCC cell growth and migration by regulating NFκB signaling transduction. Finally, flow cytometry, protein degradation assay and Co-immunoprecipitation indicated that TRIM16 can enhance NFKBIZ ubiquitination by direct interactions at its K48 site, which may thereby alleviate HCC cell apoptosis to induce the insensitivity to sorafenib. In conclusion, our study demonstrated that NFKBIZ regulated HCC tumorigenesis and metastasis by mediating NFκB signal transduction and TRIM16/NFKBIZ/NFκB axis may be the underlying mechanism of sorafenib insensitivity in HCC.

LncRNA NKILA inhibits HBV replication by repressing NF-κB signalling activation

Hepatitis B virus (HBV) infection results in liver cirrhosis and hepatocellular carcinoma (HCC). HBx/nuclear factor (NF)-κB pathway plays a role in HBV replication. However, whether NF-κB-interacting long noncoding RNA (NKILA), a suppressor of NF-κB activation, regulates HBV replication remains largely unknown. In this study, gain-and-loss experiments showed that NKILA inhibited HBV replication by inhibiting NF-κB activity. In turn, HBV infection down-regulated NKILA expression. In addition, expression levels of NKILA were lower in the peripheral blood-derived monocytes (PBMCs) of HBV-positive patients than in healthy individuals, which were correlated with HBV viral loads. And a negative correlation between NKILA expression level and HBV viral loads was observed in blood serum from HBV-positive patients. Lower levels of endogenous NKILA were also observed in HepG2 cells expressing a 1.3-fold HBV genome, HBV-infected HepG2-NTCP cells, stable HBV-producing HepG2.2.15 and HepAD38 ​cells, compared to those HBV-negative cells. Furthermore, HBx was required for NKILA-mediated inhibition on HBV replication. NKILA decreased HBx-induced NF-κB activation by interrupting the interaction between HBx and p65, whereas NKILA mutants lack of essential domains for NF-ĸB inhibition, lost the ability to inhibit HBV replication. Together, our data demonstrate that NKILA may serve as a suppressor of HBV replication via NF-ĸB signalling.

Identification of differentially methylated regions associated with both liver fibrosis and hepatocellular carcinoma

BACKGROUND

Liver fibrosis is a major risk factor for hepatocellular carcinoma (HCC). We have previously reported that differentially methylated regions (DMRs) are correlated with the fibrosis stages of metabolic dysfunction-associated steatotic liver disease (MASLD). In this study, the methylation levels of those DMRs in liver fibrosis and subsequent HCC were examined.

METHODS

The methylation levels of DMRs were investigated using alcoholic cirrhosis and HCC (GSE60753). The data of hepatitis C virus-infected cirrhosis and HCC (GSE60753), and two datasets (GSE56588 and GSE89852) were used for replication analyses. The transcriptional analyses were performed using GSE114564, GSE94660, and GSE142530.

RESULTS

Hypomethylated DMR and increased transcriptional level of zinc finger and BTB domain containing 38 (ZBTB38) were observed in HCC. Hypermethylated DMRs, and increased transcriptional levels of forkhead box K1 (FOXK1) and zinc finger CCCH-type containing 3 (ZC3H3) were observed in HCC. The methylation levels of DMR of kazrin, periplakin interacting protein (KAZN) and its expression levels were gradually decreased as cirrhosis progressed to HCC.

CONCLUSIONS

Changes in the methylation and transcriptional levels of ZBTB38, ZC3H3, FOXK1, and KAZN are important for the development of fibrosis and HCC; and are therefore potential therapeutic targets and diagnostic tools for cirrhosis and HCC.

Long-read transcriptome landscapes of primary and metastatic liver cancers at transcript resolution

BACKGROUND

The liver ranks as the sixth most prevalent site of primary cancer in humans, and it frequently experiences metastases from cancers originating in other organs. To facilitate the development of effective treatments and improve survival rates, it is crucial to comprehend the intricate and diverse transcriptome landscape of primary and metastatic liver cancers.

METHODS

We conducted long-read isoform sequencing and short-read RNA sequencing using a cohort of 95 patients with primary and secondary liver cancer who underwent hepatic resection. We compared the transcriptome landscapes of primary and metastatic liver cancers and systematically investigated hepatocellular carcinoma (HCC), paired primary tumours and liver metastases, and matched nontumour liver tissues.

RESULTS

We elucidated the full-length isoform-level transcriptome of primary and metastatic liver cancers in humans. Our analysis revealed isoform-level diversity in HCC and identified transcriptome variations associated with liver metastatis. Specific RNA transcripts and isoform switching events with clinical implications were profound in liver cancer. Moreover, we defined metastasis-specific transcripts that may serve as predictors of risk of metastasis. Additionally, we observed abnormalities in adjacent paracancerous liver tissues and characterized the immunological and metabolic alterations occurring in the liver.

CONCLUSIONS

Our findings underscore the power of full-length transcriptome profiling in providing novel biological insights into the molecular mechanisms underlying tumourigenesis. These insights will further contribute to improving treatment strategies for primary and metastatic liver cancers.

Gene expression signatures of stepwise progression of Hepatocellular Carcinoma

The molecular pathogenesis of Hepatocellular Carcinoma (HCC) is a complex process progressing from premalignant stages to cancer in a stepwise manner. Mostly, HCC is detected at advanced stages, leading to high mortality rates. Hence, characterising the molecular underpinnings of HCC from normal to cancer state through precancerous state may help in early detection and improve its prognosis and treatment. In this work, we analysed the transcriptomic profile of tumour and premalignant samples from HCC or chronic liver disease patients, who had undergone either total or partial hepatectomy. The normal samples from patients with metastatic cancer/polycystic liver disease/ cholangiocarcinoma were also included. A gene co-expression network approach was applied to identify hierarchical changes: modules, pathways, and genes related to different trajectories of HCC and patient survival. Our analysis shows that the progression from premalignant conditions to tumour is accompanied by differences in the downregulation of genes associated with HNF4A activity and the immune system and upregulation of cell cycle genes, bringing about variability in patient outcomes. However, an increase in immune and cell cycle activity is observed in premalignant samples. Interestingly, co-expression modules and genes from premalignant stages are associated with survival. THBD, a classical marker for dendritic cells, is a predictor of survival at the premalignant stage. Further, genes linked to microtubules, kinetochores, and centromere are altered in both premalignant and tumour conditions and are associated with survival. Our analysis revealed a three-way molecular axis of liver function, immune pathways, and cell cycle driving HCC pathogenesis.

A versatile method to profile hepatitis B virus DNA integration

BACKGROUND

HBV DNA integration into the host genome is frequently found in HBV-associated HCC tissues and is associated with hepatocarcinogenesis. Multiple detection methods, including hybrid capture-sequencing, have identified integration sites and provided clinical implications; however, each has advantages and disadvantages concerning sensitivity, cost, and throughput. Therefore, methods that can comprehensively and cost-effectively detect integration sites with high sensitivity are required. Here, we investigated the efficiency of RAISING (Rapid Amplification of Integration Site without Interference by Genomic DNA contamination) as a simple and inexpensive method to detect viral integration by amplifying HBV-integrated fragments using virus-specific primers covering the entire HBV genome.

METHODS AND RESULTS

Illumina sequencing of RAISING products from HCC-derived cell lines (PLC/PRF/5 and Hep3B cells) identified HBV-human junction sequences as well as their frequencies. The HBV-human junction profiles identified using RAISING were consistent with those determined using hybrid capture-sequencing, and the representative junctions could be validated by junction-specific nested PCR. The comparison of these detection methods revealed that RAISING-sequencing outperforms hybrid capture-sequencing in concentrating junction sequences. RAISING-sequencing was also demonstrated to determine the sites of de novo integration in HBV-infected HepG2-NTCP cells, primary human hepatocytes, liver-humanized mice, and clinical specimens. Furthermore, we made use of xenograft mice subcutaneously engrafted with PLC/PRF/5 or Hep3B cells, and HBV-human junctions determined by RAISING-sequencing were detectable in the plasma cell-free DNA using droplet digital PCR.

CONCLUSIONS

RAISING successfully profiles HBV-human junction sequences with smaller amounts of sequencing data and at a lower cost than hybrid capture-sequencing. This method is expected to aid basic HBV integration and clinical diagnosis research.

Establishment of a prognostic signature based on fatty acid metabolism genes in HCC associated with hepatitis B

BACKGROUND

Hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) is one of the most common and deadly cancer and often accompanied by varying degrees of liver damage, leading to the dysfunction of fatty acid metabolism (FAM). This study aimed to investigate the relationship between FAM and HBV-associated HCC and identify FAM biomarkers for predicting the prognosis of HBV-associated HCC.

METHODS

Gene Set Enrichment Analysis (GSEA) was used to analyze the difference of FAM pathway between paired tumor and adjacent normal tissue samples in 58 HBV-associated HCC patients from the Gene Expression Omnibus (GEO) database. Next, 117 HBV-associated HCC patients from The Cancer Genome Atlas (TCGA) database were analyzed to establish a prognostic signature based on 42 FAM genes. Then, the prognostic signature was validated in an external cohort consisting of 30 HBV-associated HCC patients. Finally, immune infiltration analysis was performed to evaluate the FAM-related immune cells in HBV-associated HCC.

RESULTS

As a result, FAM pathway was clearly downregulated in tumor tissue of HBV-associated HCC, and survival analysis demonstrated that 12 FAM genes were associated with the prognosis of HBV-associated HCC. Lasso-penalized Cox regression analysis identified and established a five-gene signature (ACADVL, ACAT1, ACSL3, ADH4 and ECI1), which showed effective discrimination and prediction for the prognosis of HBV-associated HCC both in the TCGA cohort and the validation cohort. Immune infiltration analysis showed that the high-risk group, identified by FAM signature, of HBV-associated HCC had a higher ratio of Tregs, which was associated with the prognosis.

CONCLUSIONS

Collectively, these findings suggest that there is a strong connection between FAM and HBV-associated HCC, indicating a potential therapeutic strategy targeting FAM to block the accumulation of Tregs into the tumor microenvironment of HBV-associated HCC.

Integrated HBV DNA and cccDNA maintain transcriptional activity in intrahepatic HBsAg-positive patients with functional cure following PEG-IFN-based therapy

BACKGROUND

Hepatitis B surface antigen (HBsAg) seroclearance marks regression of hepatitis B virus (HBV) infection. However, more than one-fifth of patients with functional cure following pegylated interferon-based therapy may experience HBsAg seroreversion. The mechanisms causing the HBV relapse remain unclear.

AIM

To investigate the level and origin of HBV transcripts in patients with functional cure and their role in predicting relapse.

METHODS

Liver tissue obtained from patients with functional cure, as well as uncured and treatment-naïve HBeAg-negative patients with chronic hepatitis B (CHB) were analysed for intrahepatic HBV markers. HBV capture and RNA sequencing were used to detect HBV integration and chimeric transcripts.

RESULTS

Covalently closed circular DNA (cccDNA) levels and the proportion of HBsAg-positive hepatocytes in functionally cured patients were significantly lower than those in uncured and treatment-naïve HBeAg-negative patients. Integrated HBV DNA and chimeric transcripts declined in functionally cured patients compared to uncured patients. HBsAg-positive hepatocytes present in 25.5% of functionally cured patients, while intrahepatic HBV RNA remained in 72.2%. The levels of intrahepatic HBV RNA, integrated HBV DNA, and chimeric transcripts were higher in functionally cured patients with intrahepatic HBsAg than in those without. The residual intrahepatic HBsAg in functionally cured patients was mainly derived from transcriptionally active integrated HBV DNA; meanwhile, trace transcriptional activity of cccDNA could also remain. Two out of four functionally cured patients with intrahepatic HBsAg and trace active cccDNA experienced HBV relapse.

CONCLUSION

Integrated HBV DNA and cccDNA maintain transcriptional activity and maybe involved in HBsAg seroreversion in intrahepatic HBsAg-positive patients with functional cure and linked to virological relapse.

Detection of fibrotic changes in the progression of liver diseases by label-free multiphoton imaging

Collagen fibers play an important role in the progression of liver diseases. The formation and progression of liver fibrosis is a dynamic pathological process accompanied by morphological changes in collagen fibers. In this study, we used multiphoton microscopy for label-free imaging of liver tissues, allowing direct detection of various components including collagen fibers, tumors, blood vessels, and lymphocytes. Then, we developed a deep learning classification model to automatically identify tumor regions, and the accuracy reaches 0.998. We introduced an automated image processing method to extract eight collagen morphological features from various stages of liver diseases. Statistical analysis showed significant differences between them, indicating the potential use of these quantitative features for monitoring fibrotic changes during the progression of liver diseases. Therefore, multiphoton imaging combined with automatic image processing method would hold a promising future in rapid and label-free diagnosis of liver diseases.

Re-analysis of hepatitis B virus integration sites reveals potential new loci associated with oncogenesis in hepatocellular carcinoma

BACKGROUND

Hepatitis B virus (HBV) is a major cause of hepatocellular carcinoma (HCC). HBV DNA can get integrated into the hepatocyte genome to promote carcinogenesis. However, the precise mechanism by which the integrated HBV genome promotes HCC has not been elucidated.

AIM

To analyze the features of HBV integration in HCC using a new reference database and integration detection method.

METHODS

Published data, consisting of 426 Liver tumor samples and 426 paired adjacent non-tumor samples, were re-analyzed to identify the integration sites. Genome Reference Consortium Human Build 38 (GRCh38) and Telomere-to-Telomere Consortium CHM13 (T2T-CHM13 (v2.0)) were used as the human reference genomes. In contrast, human genome 19 (hg19) was used in the original study. In addition, GRIDSS VIRUSBreakend was used to detect HBV integration sites, whereas high-throughput viral integration detection (HIVID) was applied in the original study (HIVID-hg19).

RESULTS

A total of 5361 integration sites were detected using T2T-CHM13. In the tumor samples, integration hotspots in the cancer driver genes, such as TERT and KMT2B, were consistent with those in the original study. GRIDSS VIRUSBreakend detected integrations in more samples than by HIVID-hg19. Enrichment of integration was observed at chromosome 11q13.3, including the CCND1 pro-moter, in tumor samples. Recurrent integration sites were observed in mitochondrial genes.

CONCLUSION

GRIDSS VIRUSBreakend using T2T-CHM13 is accurate and sensitive in detecting HBV integration. Re-analysis provides new insights into the regions of HBV integration and their potential roles in HCC development.

GepLiver: an integrative liver expression atlas spanning developmental stages and liver disease phases

Chronic liver diseases usually developed through stepwise pathological transitions under the persistent risk factors. The molecular changes during liver transitions are pivotal to improve liver diagnostics and therapeutics yet still remain elusive. Cumulative large-scale liver transcriptomic studies have been revealing molecular landscape of various liver conditions at bulk and single-cell resolution, however, neither single experiment nor databases enabled thorough investigations of transcriptomic dynamics along the progression of liver diseases. Here we establish GepLiver, a longitudinal and multidimensional liver expression atlas integrating expression profiles of 2469 human bulk tissues, 492 mouse samples, 409,775 single cells from 347 human samples and 27 liver cell lines spanning 16 liver phenotypes with uniformed processing and annotating methods. Using GepLiver, we have demonstrated dynamic changes of gene expression, cell abundance and crosstalk harboring meaningful biological associations. GepLiver can be applied to explore the evolving expression patterns and transcriptomic features for genes and cell types respectively among liver phenotypes, assisting the investigation of liver transcriptomic dynamics and informing biomarkers and targets for liver diseases.

Single-nucleus RNA sequencing of pre-malignant liver reveals disease-associated hepatocyte state with HCC prognostic potential

Current approaches to staging chronic liver diseases have limited utility for predicting liver cancer risk. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to characterize the cellular microenvironment of healthy and pre-malignant livers using two distinct mouse models. Downstream analyses unraveled a previously uncharacterized disease-associated hepatocyte (daHep) transcriptional state. These cells were absent in healthy livers but increasingly prevalent as chronic liver disease progressed. Copy number variation (CNV) analysis of microdissected tissue demonstrated that daHep-enriched regions are riddled with structural variants, suggesting these cells represent a pre-malignant intermediary. Integrated analysis of three recent human snRNA-seq datasets confirmed the presence of a similar phenotype in human chronic liver disease and further supported its enhanced mutational burden. Importantly, we show that high daHep levels precede carcinogenesis and predict a higher risk of hepatocellular carcinoma development. These findings may change the way chronic liver disease patients are staged, surveilled, and risk stratified.

Effect of nanoparticle macroalgae in the treatment of fatty liver disease using logistic regression, and support vector machine

One of the major health issues facing people worldwide is liver fibrosis. Liver fibrosis may be brought on by long-term exposure to harmful substances, medicines, and microorganisms. The development of liver fibrosis in children was particularly worrying due to their longer life-span, which was possibly related to a great risk of developing long-term complications. Marine algae species have provided a biological variety in the research phase of novel approaches to the treatment of numerous ailments. Marine macroalgae have recently been the subject of research due to their rich bioactive chemical composition and potential for the production of various nutraceuticals. Macroalgae are potentially excellent sources of bioactive substances with particular and distinct biological activity when compared to their terrestrial equivalents. Macroalgae in diverse marine cases offer a few biologically active metabolites, comprising sterols, polyunsaturated fatty acids, carotenoids, oligosaccharides, polysaccharides, proteins, polyphenols, vitamins, and minerals. Accordingly, there is great interest in their high potential for supporting immunomodulatory, antimicrobial, antidiabetic, antitumoral, anti-inflammatory, antiangiogenic, and neuroprotective properties. Using an experimental model, the current research intends to collect data on the therapeutic value of macroalgae nanoparticles for fatty liver disease. The researchers' goal of predicting illnesses from the extensive medical datasets is quite difficult. The purpose of this research is to assess the protective effects of a seaweed, Padina pavonia (PP), on liver fibrosis caused by carbon tetrachloride (CCl4). This research presents two models of logistic regression (LR) and support vector machines (SVM) for predicting the likelihood of liver disease incidence. The performance of the model was evaluated using a dataset. PP macro-algae considerably reduce the high blood concentrations of aminotransferases, alkaline phosphatases, and lactate dehydrogenases, as well as causing a considerable (p < 0.05) decrease in serum bilirubin levels. In addition to improving kidney function (urea and creatinine), algal extracts enhance fat metabolism (triglycerides and cholesterol). With an accuracy rate of 70.2%, a sensitivity of 92.3%, a specificity of 74.7%, a type I error of 9.1%, and a type II error of 21.0%, the predictive model has demonstrated excellent performance. The model validated laboratory tests' ability to predict illness (age; direct bilirubin (DB), total proteins (TP), and albumin (ALB). These classifier methods are compared on the basis of their execution time and classification accuracy.

MicroRNA-155 and 194 alter expression of Th17 and T regulatory-related transcription factors in the patients with severe coronavirus disease 2019 (COVID-19)

INTRODUCTION

It has been demonstrated that the patients with severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) suffer from severe inflammation. Due to the ethnics, the immune responses may be different. Additionally, microRNAs may alter immune responses in the patients. The current study was aimed to evaluate the expression of T helper subsets-related transcription factors, some T helper 17 (Th17) products, and two microRNAs, including miR-155 and miR-194, in the Iranian hospitalized patients.

METHODS

In this study, T-box expressed in T cells (T-bet), GATA binding protein 3, The retinoid orphan receptor gamma t (RORγt), forkhead box P3 (FOXP3), interleukin (IL)-17A, IL-8, and CC ligand 20 (CCL20) mRNA levels and, miR-155 and miR-194 levels were evaluated in 70 patients suffered from severe coronavirus disease 2019 (COVID-19) and 70 healthy subjects using Real-Time qPCR technique.

RESULTS

The findings showed that RORγt, and FOXP3 mRNA levels were significantly increased, while IL-17A, IL-8, and CCL20 mRNA levels were significantly decreased in the hospitalized SARS-CoV-2 infected patients. Although the levels of miR-155 and miR-194 were not different between groups, miR-194 has negative and positive correlations with RORγt and IL-17A in the Iranian healthy controls.

CONCLUSION

This study reports although RORγt was up-regulated, IL-17A, IL-8, and CCL20 mRNA levels were significantly decreased in the hospitalized SARS-CoV-2 infected patients. It may be concluded that up-regulation of FOXP3, via development of T regulatory lymphocytes suppresses Th17 functions and neutralizes Th17 activities. MiR-194 may play crucial roles in regulation of RORγt and IL-17A expression in healthy people, the phenomenon that is disrupted in the severe SARS-CoV-2 infected patients.

Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma

The high incidence of hepatocellular carcinoma (HCC) recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies. Over the past few decades, the emergence of transcriptome analysis tools, including real-time quantitative reverse transcription PCR, microarrays, and RNA sequencing, has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures. In recent years, the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment, which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets. In the present article, we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains: primary cancer cells; carcinogenic stimuli; and tumor microenvironment. We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics, surveillance, and treatment of HCC recurrence.

Retinoic acid-inducible gene 1 (RIG-1) and IFN-β promoter stimulator-1 (IPS-1) significantly down-regulated in the severe coronavirus disease 2019 (COVID-19)

INTRODUCTION

Retinoic acid-inducible gene 1 (RIG-1) and melanoma differentiation-associated protein 5 (MDA5) are the well-known cytoplasmic sensors that recognize microbial DNA or RNA and active down-stream molecules, including IFN-β promoter stimulator-1 (IPS-1) and receptor interacting protein 1 (RIP1). The roles played by the networked molecules on the infection with SARS-CoV-2 needs more investigations.

MATERIAL AND METHOD

In this project MDA5, RIG-1, IPS-1 and RIP1 mRNA levels were evaluated in 45 hospitalized patients suffering from coronavirus disease of 2019 (COVID-19) and 45 healthy subjects using Real Time-qPCR technique.

RESULT

The results showed significant decreased RIG-1 and IPS-1 in the SARS-CoV-2 infected patients when compared to healthy cases. MDA5 and RIP1 did not change when compared two groups. Male patients had similar expression of MDA5, RIG-1, IPS-1 and RIP1 when compared to female patients.

CONCLUSION

Based on the results, it seems that RIG-1 and its signaling molecule, IPS-1, play key roles in the peripheral blood immune cells against SARS-CoV-2 and, their down-regulation may be induced by the virus to escape from immune responses.

Comprehensive analysis of a TPX2-related TRHDE-AS1/PKIA ceRNA network involving prognostic signatures in Hepatitis B virus-infected hepatocellular carcinoma

Hepatitis B virus (HBV) infection is a main carcinogenic factor of hepatocellular carcinoma (HCC). TPX2 microtubule nucleation factor is recently recommended as a novel prognostic biomarker in HBV-infected HCC tissues. This study aimed to explore a TPX2-related ceRNA regulatory network in HBV-infected HCC and the potential impact on HCC prognosis. We comprehensively identified 541 differential expressed lncRNAs (DElncRNAs), 37 DEmiRNAs and 439 DEmRNAs from HBV-related TCGA-HCC cohorts in TPX2low and TPX2high groups. Based on their RNA-RNA interaction and expression analysis, four DElncRNAs (TRHDE-AS1, DLX6-AS1, SNHG14, HOXA11-AS), four DEmiRNAs (miR-23b, miR-320a, miR-589, miR-126) and five DEmRNAs (PKIA, PCDHA2, SHCBP1, PRSS16, KIF18A) in HCC tumor vs normal groups were subjected to the hub regulatory networks analysis and further prognostic value analysis. Importantly, the TRHDE-AS1/miR-23b/PKIA ceRNA network was associated with HCC prognosis. Furthermore, cellular location analysis and base-base interaction analysis indicated that the cytoplasmic lncRNA TRHDE-AS1 was regarded as a ceRNA to sponging miR-23b and then regulating PKIA. Interestingly, correlation analysis suggested the expression correlation between TRHDE-AS1 and PKIA in HCC. Finally, we further performed the methylation and immune infiltration analysis to explore the functional process of PKIA in HCC. We proposed a ceRNA regulatory network may help elucidate the mechanism by which TPX2 contributes to the prognosis of HBV-related HCC.

Long noncoding RNA LINC01132 enhances immunosuppression and therapy resistance via NRF1/DPP4 axis in hepatocellular carcinoma

Background

Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and play fundamental roles in various types of cancer. Current developments in transcriptome analyses unveiled the existence of lncRNAs; however, their functional characterization remains a challenge.

Methods

A bioinformatics screen was performed by integration of multiple omics data in hepatocellular carcinoma (HCC) prioritizing a novel oncogenic lncRNA, LINC01132. Expression of LINC01132 in HCC and control tissues was validated by qRT-PCR. Cell viability and migration activity was examined by MTT and transwell assays. Finally, our results were confirmed in vivo mouse model and ex vivo patient derived tumor xenograft experiments to determine the mechanism of action and explore LINC01132-targeted immunotherapy.

Results

Systematic investigation of lncRNAs genome-wide expression patterns revealed LINC01132 as an oncogene in HCC. LINC01132 is significantly overexpressed in tumor and associated with poor overall survival of HCC patients, which is mainly driven by copy number amplification. Functionally, LINC01132 overexpression promoted cell growth, proliferation, invasion and metastasis in vitro and in vivo. Mechanistically, LINC01132 acts as an oncogenic driver by physically interacting with NRF and enhancing the expression of DPP4. Notably, LINC01132 silencing triggers CD8+ T cells infiltration, and LINC01132 knockdown combined with anti-PDL1 treatment improves antitumor immunity, which may prove a new combination therapy in HCC.

Conclusions

LINC01132 functions as an oncogenic driver that induces HCC development via the NRF1/DPP4 axis. Silencing LINC01132 may enhance the efficacy of anti-PDL1 immunotherapy in HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02478-z.

Artificial intelligence in liver ultrasound

Artificial intelligence (AI) is playing an increasingly important role in medicine, especially in the field of medical imaging. It can be used to diagnose diseases and predict certain statuses and possible events that may happen. Recently, more and more studies have confirmed the value of AI based on ultrasound in the evaluation of diffuse liver diseases and focal liver lesions. It can assess the severity of liver fibrosis and nonalcoholic fatty liver, differentially diagnose benign and malignant liver lesions, distinguish primary from secondary liver cancers, predict the curative effect of liver cancer treatment and recurrence after treatment, and predict microvascular invasion in hepatocellular carcinoma. The findings from these studies have great clinical application potential in the near future. The purpose of this review is to comprehensively introduce the current status and future perspectives of AI in liver ultrasound.

HBV genome-enriched single cell sequencing revealed heterogeneity in HBV-driven hepatocellular carcinoma (HCC)

BACKGROUND

Hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is heterogeneous and frequently contains multifocal tumors, but how the multifocal tumors relate to each other in terms of HBV integration and other genomic patterns is not clear.

METHODS

To interrogate heterogeneity of HBV-HCC, we developed a HBV genome enriched single cell sequencing (HGE-scSeq) procedure and a computational method to identify HBV integration sites and infer DNA copy number variations (CNVs).

RESULTS

We performed HGE-scSeq on 269 cells from four tumor sites and two tumor thrombi of a HBV-HCC patient. HBV integrations were identified in 142 out of 269 (53%) cells sequenced, and were enriched in two HBV integration hotspots chr1:34,397,059 (CSMD2) and chr8:118,557,327 (MED30/EXT1). There were also 162 rare integration sites. HBV integration sites were enriched in DNA fragile sites and sequences around HBV integration sites were enriched for microhomologous sequences between human and HBV genomes. CNVs were inferred for each individual cell and cells were grouped into four clonal groups based on their CNVs. Cells in different clonal groups had different degrees of HBV integration heterogeneity. All of 269 cells carried chromosome 1q amplification, a recurrent feature of HCC tumors, suggesting that 1q amplification occurred before HBV integration events in this case study. Further, we performed simulation studies to demonstrate that the sequential events (HBV infecting transformed cells) could result in the observed phenotype with biologically reasonable parameters.

CONCLUSION

Our HGE-scSeq data reveals high heterogeneity of HCC tumor cells in terms of both HBV integrations and CNVs. There were two HBV integration hotspots across cells, and cells from multiple tumor sites shared some HBV integration and CNV patterns.

meGPS: a multi-omics signature for hepatocellular carcinoma detection integrating methylome and transcriptome data

MOTIVATION

Hepatocellular carcinoma (HCC) is a primary malignancy with poor prognosis. Recently, multi-omics molecular-level measurement enables HCC diagnosis and prognosis prediction, which is crucial for early intervention of personalized therapy to diminish mortality. Here, we introduce a novel strategy utilizing DNA methylation and RNA expression data to achieve a multi-omics gene pair signature (GPS) for HCC discrimination.

RESULTS

The immune genes with negative correlations between expression and promoter methylation are enriched in the highly connected cancer-related pathway network, which are considered as the candidates for HCC detection. After that, we separately construct a methylation GPS (mGPS) and an expression GPS (eGPS), and then assemble them as a meGPS with five gene pairs, in which the significant methylation and expression changes occur between HCC tumor and non-tumor groups. Reliable performance has been validated by independent tissue (age, gender, and etiology) and blood datasets. This study proposes a procedure for multi-omics GPS identification and develops a novel HCC signature using both methylome and transcriptome data, suggesting potential molecular targets for the detection and therapy of HCC.

AVAILABILITY AND IMPLEMENTATION

Models are available at https://github.com/bioinformaticStudy/meGPS.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hepatitis B virus integrations promote local and distant oncogenic driver alterations in hepatocellular carcinoma

OBJECTIVE

Infection by HBV is the main risk factor for hepatocellular carcinoma (HCC) worldwide. HBV directly drives carcinogenesis through integrations in the human genome. This study aimed to precisely characterise HBV integrations, in relation with viral and host genomics and clinical features.

DESIGN

A novel pipeline was set up to perform viral capture on tumours and non-tumour liver tissues from a French cohort of 177 patients mainly of European and African origins. Clonality of each integration event was determined with the localisation, orientation and content of the integrated sequence. In three selected tumours, complex integrations were reconstructed using long-read sequencing or Bionano whole genome mapping.

RESULTS

Replicating HBV DNA was more frequently detected in non-tumour tissues and associated with a higher number of non-clonal integrations. In HCC, clonal selection of HBV integrations was related to two different mechanisms involved in carcinogenesis. First, integration of viral enhancer nearby a cancer-driver gene may lead to a strong overexpression of oncogenes. Second, we identified frequent chromosome rearrangements at HBV integration sites leading to cancer-driver genes (TERT, TP53, MYC) alterations at distance. Moreover, HBV integrations have direct clinical implications as HCC with a high number of insertions develop in young patients and have a poor prognosis.

CONCLUSION

Deep characterisation of HBV integrations in liver tissues highlights new HBV-associated driver mechanisms involved in hepatocarcinogenesis. HBV integrations have multiple direct oncogenic consequences that remain an important challenge for the follow-up of HBV-infected patients.

Hepatitis B Virus Integration into Transcriptionally Active Loci and HBV-Associated Hepatocellular Carcinoma

Hepatitis B Virus (HBV) DNA integrations into the human genome are considered major causative factors to HBV-associated hepatocellular carcinoma development. In the present study, we investigated whether HBV preferentially integrates parts of its genome in specific genes and evaluated the contribution of the integrations in HCC development per gene. We applied dedicated in-house developed pipelines on all of the available HBV DNA integration data and performed a statistical analysis to identify genes that could be characterized as hotspots of integrations, along with the evaluation of their association with HBV-HCC. Our results suggest that 15 genes are recurrently affected by HBV integrations and they are significantly associated with HBV-HCC. Further studies that focus on HBV integrations disrupting these genes are mandatory in order to understand the role of HBV integrations in clonal advantage gain and oncogenesis promotion, as well as to determine whether inhibition of the HBV-disrupted genes can provide a therapy strategy for HBV-HCC.

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.

Nucleotide variants in hepatitis B virus preS region predict the recurrence of hepatocellular carcinoma

Background: Hepatitis B virus (HBV) variants in the preS region have been associated with hepatocellular carcinoma (HCC). However, the effect of the preS variants on HCC prognosis remains largely unknown. We aimed to identify the preS variants that reliably predict postoperative prognosis in HCC.

Methods: RNA-seq data of 203 HCC patients retrieved from public database were screened for the preS variants related to HCC prognosis. The variants in the sera and tumors were then validated in our prospective cohort enrolling 103 HBV-associated HCC patients.

Results: By analyzing prognosis-related gene sets in the RNA-seq data, 12 HBV preS variants were associated with HCC recurrence. Of those, G40C and C147T in the sera predicted an unfavorable recurrence-free survival in our cohort (hazard ratio [HR]=2.18, 95% confidence interval [CI]=1.37-3.47, p=0.001 for G40C; HR=1.84, 95% CI=1.15-2.92, p=0.012 for C147T). G40C and C147T were significantly associated with microscopic vascular invasion, larger tumor size, and abnormal liver function. Multivariate Cox regression analysis showed that G40C significantly increased the risk of HCC recurrence in patients with postoperative antiviral treatment. The HCC prognosis-prediction model consisting of α-fetoprotein and G40C in the sera achieved the best performance (sensitivity=0.80, specificity=0.70, and area under the curve=0.79). Functional analysis indicated that these two variants were associated with cell proliferation, chromosome instability, carcinogenesis, metastasis, and anticancer drug resistance.

Conclusions: G40C and C147T are serological biomarkers for HCC prognosis and the prognostic model consisting of serological α-fetoprotein and G40C achieved the best performance in predicting postoperative prognosis.

A human liver cell-based system modeling a clinical prognostic liver signature for therapeutic discovery

Chronic liver disease and hepatocellular carcinoma (HCC) are life-threatening diseases with limited treatment options. The lack of clinically relevant/tractable experimental models hampers therapeutic discovery. Here, we develop a simple and robust human liver cell-based system modeling a clinical prognostic liver signature (PLS) predicting long-term liver disease progression toward HCC. Using the PLS as a readout, followed by validation in nonalcoholic steatohepatitis/fibrosis/HCC animal models and patient-derived liver spheroids, we identify nizatidine, a histamine receptor H2 (HRH2) blocker, for treatment of advanced liver disease and HCC chemoprevention. Moreover, perturbation studies combined with single cell RNA-Seq analyses of patient liver tissues uncover hepatocytes and HRH2+, CLEC5Ahigh, MARCOlow liver macrophages as potential nizatidine targets. The PLS model combined with single cell RNA-Seq of patient tissues enables discovery of urgently needed targets and therapeutics for treatment of advanced liver disease and cancer prevention.

Hepatitis B Virus DNA Integration, Chronic Infections and Hepatocellular Carcinoma

Hepatitis B Virus (HBV) is an Old World virus with a high mutation rate, which puts its origins in Africa alongside the origins of Homo sapiens, and is a member of the Hepadnaviridae family that is characterized by a unique viral replication cycle. It targets human hepatocytes and can lead to chronic HBV infection either after acute infection via horizontal transmission usually during infancy or childhood or via maternal-fetal transmission. HBV has been found in ~85% of HBV-related Hepatocellular Carcinomas (HCC), and it can integrate the whole or part of its genome into the host genomic DNA. The molecular mechanisms involved in the HBV DNA integration is not yet clear; thus, multiple models have been described with respect to either the relaxed-circular DNA (rcDNA) or the double-stranded linear DNA (dslDNA) of HBV. Various genes have been found to be affected by HBV DNA integration, including cell-proliferation-related genes, oncogenes and long non-coding RNA genes (lincRNAs). The present review summarizes the advances in the research of HBV DNA integration, focusing on the evolutionary and molecular side of the integration events along with the arising clinical aspects in the light of WHO's commitment to eliminate HBV and viral hepatitis by 2030.

Recurrent HBV Integration Targets as Potential Drivers in Hepatocellular Carcinoma

Chronic hepatitis B virus (HBV) infection is the major etiology of hepatocellular carcinoma (HCC), frequently with HBV integrating into the host genome. HBV integration, found in 85% of HBV-associated HCC (HBV–HCC) tissue samples, has been suggested to be oncogenic. Here, we investigated the potential of HBV–HCC driver identification via the characterization of recurrently targeted genes (RTGs). A total of 18,596 HBV integration sites from our in-house study and others were analyzed. RTGs were identified by applying three criteria: at least two HCC subjects, reported by at least two studies, and the number of reporting studies. A total of 396 RTGs were identified. Among the 28 most frequent RTGs, defined as affected in at least 10 HCC patients, 23 (82%) were associated with carcinogenesis and 5 (18%) had no known function. Available breakpoint positions from the three most frequent RTGs, TERT, MLL4/KMT2B, and PLEKHG4B, were analyzed. Mutual exclusivity of TERT promoter mutation and HBV integration into TERT was observed. We present an RTG consensus through comprehensive analysis to enable the potential identification and discovery of HCC drivers for drug development and disease management.

Genomics of Viral Hepatitis-Associated Liver Tumors

Virus-related liver carcinogenesis is one of the main contributors of cancer-related death worldwide mainly due to the impact of chronic hepatitis B and C infections. Three mechanisms have been proposed to explain the oncogenic properties of hepatitis B virus (HBV) infection: induction of chronic inflammation and cirrhosis, expression of HBV oncogenic proteins, and insertional mutagenesis into the genome of infected hepatocytes. Hepatitis B insertional mutagenesis modifies the function of cancer driver genes and could promote chromosomal instability. In contrast, hepatitis C virus promotes hepatocellular carcinoma (HCC) occurrence mainly through cirrhosis development whereas the direct oncogenic role of the virus in human remains debated. Finally, adeno associated virus type 2 (AAV2), a defective DNA virus, has been associated with occurrence of HCC harboring insertional mutagenesis of the virus. Since these tumors developed in a non-cirrhotic context and in the absence of a known etiological factor, AAV2 appears to be the direct cause of tumor development in these patients via a mechanism of insertional mutagenesis altering similar oncogenes and tumor suppressor genes targeted by HBV. A better understanding of virus-related oncogenesis will be helpful to develop new preventive strategies and therapies directed against specific alterations observed in virus-related HCC.

Landscape of oncoviral genotype and co-infection via human papilloma and hepatitis B viral tumor in situ profiling

The role of oncoviral genotype and co-infection driving oncogenesis remains unclear. We have developed a scalable, high throughput tool for sensitive and precise oncoviral genotype deconvolution. Using tumor RNA sequencing data, we applied it to 537 virally infected liver, cervical, and head and neck tumors, providing the first comprehensive integrative landscape of tumor-viral gene expression, viral antigen immunogenicity, patient survival, and mutational profiling organized by tumor oncoviral genotype. We find that HBV and HPV genotype and co-infection serve as significant predictors of patient survival and immune activation. Finally, we demonstrate that HPV genotype is more associated with viral oncogene expression than cancer type, implying that expression may be similar across episomal and stochastic integration-based infections. While oncoviral infections are known risk factors for oncogenesis, viral genotype and co-infection are shown to strongly associate with disease progression, patient survival, mutational signatures, and putative tumor neoantigen immunogenicity, facilitating novel clinical associations with infections.

•

ViralMine parses oncoviral genotypes and co-infection from in situ tumor data

•

Oncoviral genotyping of TCGA CESC, HNSC, and LIHC cohorts

•

Tumor fitness, immunogenicity, and mutational signatures associate with oncoviral genotype

Hepatitis B Virus DNA Integration: In Vitro Models for Investigating Viral Pathogenesis and Persistence

Hepatitis B virus (HBV) is a globally-distributed pathogen and is a major cause of liver disease. HBV (or closely-related animal hepadnaviruses) can integrate into the host genome, but (unlike retroviruses) this integrated form is replication-defective. The specific role(s) of the integrated HBV DNA has been a long-standing topic of debate. Novel in vitro models of HBV infection combined with sensitive molecular assays now enable researchers to investigate this under-characterised phenomenon with greater ease and precision. This review covers the contributions these systems have made to understanding how HBV DNA integration induces liver cancer and facilitates viral persistence. We summarise the current findings into a working model of chronic HBV infection and discuss the clinical implications of this hypothetical framework on the upcoming therapeutic strategies used to curb HBV-associated pathogenesis.

Quantitative analysis of the splice variants expressed by the major hepatitis B virus genotypes

Hepatitis B virus (HBV) is a major human pathogen that causes liver diseases. The main HBV RNAs are unspliced transcripts that encode the key viral proteins. Recent studies have shown that some of the HBV spliced transcript isoforms are predictive of liver cancer, yet the roles of these spliced transcripts remain elusive. Furthermore, there are nine major HBV genotypes common in different regions of the world, these genotypes may express different spliced transcript isoforms. To systematically study the HBV splice variants, we transfected human hepatoma cells, Huh7, with four HBV genotypes (A2, B2, C2 and D3), followed by deep RNA-sequencing. We found that 13-28 % of HBV RNAs were splice variants, which were reproducibly detected across independent biological replicates. These comprised 6 novel and 10 previously identified splice variants. In particular, a novel, singly spliced transcript was detected in genotypes A2 and D3 at high levels. The biological relevance of these splice variants was supported by their identification in HBV-positive liver biopsy and serum samples, and in HBV-infected primary human hepatocytes. Interestingly the levels of HBV splice variants varied across the genotypes, but the spliced pregenomic RNA SP1 and SP9 were the two most abundant splice variants. Counterintuitively, these singly spliced SP1 and SP9 variants had a suboptimal 5' splice site, supporting the idea that splicing of HBV RNAs is tightly controlled by the viral post-transcriptional regulatory RNA element.

Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies.

Deep sequencing of liver explant transcriptomes reveals extensive expression from integrated hepatitis B virus DNA

Hepatitis B virus (HBV) is a major cause of hepatocellular carcinoma (HCC). Integration of HBV DNA into the human genome may contribute to oncogenesis and to the production of the hepatitis B surface antigen (HBsAg). Whether integrations contribute to HBsAg levels in the blood is poorly known. Here, we characterize the HBV RNA profile of HBV integrations in liver tissue in patients with chronic HBV infection, with or without concurrent hepatitis D infection, by transcriptome deep sequencing. Transcriptomes were determined in liver tissue by deep sequencing providing 200 million reads per sample. Integration points were identified using a bioinformatic pipeline. Explanted liver tissue from five patients with end-stage liver disease caused by HBV or HBV/HDV was studied along with publicly available transcriptomes from 21 patients. Almost all HBV RNA profiles were devoid of reads in the core and the 3' redundancy (nt 1830-1927) regions, and contained a large number of chimeric viral/human reads. Hence, HBV transcripts from integrated HBV DNA rather than from covalently closed circular HBV DNA (cccDNA) predominated in late-stage HBV infection, in particular in cases with hepatitis D virus co-infection. The findings support the suggestion that integrated HBV DNA can be a significant source of HBsAg in humans.

YTHDF1 Facilitates the Progression of Hepatocellular Carcinoma by Promoting FZD5 mRNA Translation in an m6A-Dependent Manner

Hepatocellular carcinoma (HCC), one of the most aggressive malignancies, ranks as the fourth leading cause of cancer-related deaths worldwide. Emerging evidence indicates that RNA N6-methyladenosine (m6A) plays a critical role in tumor progression. However, the biological function of YTHDF1 in HCC remains unclear. Here, we found that YTHDF1 expression was strikingly elevated in HCC tissues and cell lines and significantly associated with prognosis of HCC patients. Moreover, YTHDF1 expression was transcriptionally regulated by USF1 and c-MYC in HCC. Functional studies showed that YTHDF1 can promote HCC cell proliferation and metastasis both in vitro and in vivo. Multi-omics analysis revealed that YTHDF1 can accelerate the translational output of FZD5 mRNA in an m6A-dependent manner and function as an oncogene through the WNT/β-catenin pathway. Taken together, our study revealed an essential role of YTHDF1 in the progression of HCC cells, which indicated that targeting YTHDF1 may be a potential therapeutic strategy in HCC.

Landscape of active enhancers developed de novo in cirrhosis and conserved in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) patients always have a background of cirrhosis. Aberrant epigenetic changes in cirrhosis provide a conductive environment for HCC tumorigenesis. Active enhancers (AEs) are essential for epigenetic regulation and play an important role in cell development and the progression of many diseases. However, the role of AEs in the progression from cirrhosis to HCC remains unclear. We systemically constructed a landscape of AEs that developed de novo in cirrhosis and were conserved in HCC, referred to as CL-HCC AEs. We observed significant upregulation of these CL-HCC AE-associated genes in cirrhosis and HCC, with no other epigenetic changes. Enrichment analysis of these CL-HCC AE-associated genes revealed enrichment in both hepatocyte-intrinsic tumorigenesis and tumor immune response, which might contribute to HCC tumorigenesis. Analysis of the diagnostic ability of these CL-HCC AE-associated genes provided a five-gene (THBS4, OLFML2B, CDKN3, GABRE, and HDAC11) diagnostic biomarker for HCC. Molecular subtype (MS) identification based on the CL-HCC AE-associated genes identified 3 MSs. Samples representing the 3 MSs showed differences in CL-HCC AE-associated gene expression levels, prognosis, copy number variation (CNV)/mutation frequencies, functional pathways, tumor microenvironment (TME) cell subtypes, immunotherapy responses and putative drug responses. We also found that the BET bromodomain inhibitor JQ1 downregulated the expression of CL-HCC AE-associated genes. Collectively, our results suggest that CL-HCC AEs and their associated genes contribute to HCC tumorigenesis and evolution, and could be used to distinguish the different landscapes of HCC and help explore the mechanism, classification, prediction, and precision therapy of HCC.

Gene Biomarkers Derived from Clinical Data of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common cancer of high mortality, mainly due to the difficulty in diagnosis during its clinical stage. Here we aim to find the gene biomarkers, which are of important significance for diagnosis and treatment. In this work, 3682 differentially expressed genes on HCC were firstly differentiated based on the Cancer Genome Atlas database (TCGA). Co-expression modules of these differentially expressed genes were then constructed based on the weighted correlation network algorithm. The correlation coefficient between the co-expression module and clinical data from the Broad GDAC Firehose was thereafter derived. Finally, the interactive network of genes was then constructed. Then, the hub genes were used to implement enrichment analysis and pathway analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. Results revealed that the abnormally expressed genes in the module played an important role in the biological process including cell division, sister chromatid cohesion, DNA repair, and G1/S transition of mitotic cell cycle. Meanwhile, these genes also enriched in a few crucial pathways related to Cell cycle, Oocyte meiosis, and p53 signaling. Via investigating the closeness centrality of the interactive network, eight gene biomarkers including the CKAP2, TPX2, CDCA8, KIFC1, MELK, SGO1, RACGAP1, and KIAA1524 gene were discovered, whose functions had been indeed revealed to be correlated with HCC. This study, therefore, suggests that the abnormal expression of those eight genes may be taken as gene biomarkers of HCC.

Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The "Estimation of STromal and Immune cells in MAlignant Tumors using Expression data" algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.

Up-regulation of RIP1 and IPS-1 in chronic HBV infected patients

IPS-1 and RIP1 are the main downstream molecules of RIG1 and MDA5, as intracytoplasmic receptors, which are the main receptors involved in recognition of internal and external viral double-stranded RNA. In this project, mRNA levels of IPS-1 and RIP1 were investigated in the peripheral blood immune cells of chronic hepatitis B (CHB) patients. IPS-1 and RIP1 mRNA levels were measured in 60 CHB patients and 120 healthy subjects, using RT-qPCR technique. A significant increase in expression levels of IPS-1 and RIP1 was found in patients when compared to healthy individuals. There was no correlation between IPS-1 and RIP1expression levels with the serum levels of hepatitis B e-Antigen (HBeAg) and liver enzymes in patients. Based on the results, it seems that IPS-1 and RIP1 can participate in the induction of low chronic inflammation, which is a main cause of liver cirrhosis and hepatocellular carcinoma.

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.

Identification of long non-coding RNA-related and -coexpressed mRNA biomarkers for hepatocellular carcinoma

Background

While changes in mRNA expression during tumorigenesis have been used widely as molecular biomarkers for the diagnosis of a number of cancers, the approach has limitations. For example, traditional methods do not consider the regulatory and positional relationship between mRNA and lncRNA. The latter has been largely shown to possess tumor suppressive or oncogenic properties. The combined analysis of mRNA and lncRNA is likely to facilitate the identification of biomarkers with higher confidence.

Results

Therefore, we have developed an lncRNA-related method to identify traditional mRNA biomarkers. First we identified mRNAs that are differentially expressed in Hepatocellular Carcinoma (HCC) by comparing cancer and matched adjacent non-tumorous liver tissues. Then, we performed mRNA-lncRNA relationship and coexpression analysis and obtained 41 lncRNA-related and -coexpressed mRNA biomarkers. Next, we performed network analysis, gene ontology analysis and pathway analysis to unravel the functional roles and molecular mechanisms of these lncRNA-related and -coexpressed mRNA biomarkers. Finally, we validated the prediction and performance of the 41 lncRNA-related and -coexpressed mRNA biomarkers using Support Vector Machine model with five-fold cross-validation in an independent HCC dataset from RNA-seq.

Conclusions

Our results suggested that mRNAs expression profiles coexpressed with positionally related lncRNAs can provide important insights into early diagnosis and specific targeted gene therapy of HCC.

Integrated analysis of lncRNA-associated ceRNA network reveals potential biomarkers for the prognosis of hepatitis B virus-related hepatocellular carcinoma

Background

There is evidence that abnormal expression of lncRNAs is associated with hepatitis B virus (HBV) infection-induced hepatocellular carcinoma (HCC). However, the mechanisms remain not fully elucidated. The study aimed to identify novel lncRNAs and explore their underlying mechanisms based on the ceRNA hypothesis.

Methods

The RNA and miRNA expression profiling in 20 tumor and matched adjacent tissues from HBV–HCC patients were retrieved from the Gene Expression Omnibus database under accession numbers GSE77509 and GSE76903, respectively. Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) were identified using the EdgeR package. Protein–protein interaction (PPI) network was constructed for DEGs followed by module analysis. The ceRNA network was constructed based on interaction relationships between miRNAs and mRNAs/lncRNAs. The functions of DEGs were predicted using DAVID and BinGO databases. The prognosis values (overall survival [OS] and recurrence-free survival [RFS]) of ceRNA network genes were determined using The Cancer Genome Atlas (TCGA) data with Cox regression analysis and Kaplan–Meier method.

Results

The present study screened 643 DELs, 83 DEMs, and 1,187 DEGs. PPI network analysis demonstrated that CDK1 and CCNE1 were hub genes and extracted in functionally related modules. E2F2, CDK1, and CCNE1 were significantly enriched into cell cycle pathway. FAM182B-miR-125b-5p-E2F2 and LINC00346-miR-10a-5p-CDK1/CCNE1 ceRNA axes were obtained by constructing the ceRNA network. Patients with high expressions of DELs and DEGs in the above ceRNA axes had poor OS, while patients with the high expression of DEMs possessed excellent OS. CDK1 was also an RFS-related biomarker, with its high expression predicting poor RFS. The upregulation of LINC00346 and CDK1 but the downregulation of miR-10a-5p in HCC was validated in other microarray datasets and TCGA database.

Conclusion

The LINC00346-miR-10a-5p-CDK1 axis may be an important mechanism for HBV-related HCC, and genes in this ceRNA axis may be potential prognostic biomarkers and therapeutic targets.

MicroRNA-197-3p acts as a prognostic marker and inhibits cell invasion in hepatocellular carcinoma

MicroRNAs (miRNAs) serve an important regulatory role in carcinogenesis and cancer progression. Aberrant expression of miR-197-3p has been reported in various human malignancies. However, the role of miR-197-3p in the progression and prognosis of hepatocellular carcinoma (HCC) remains unknown. The present study demonstrated that miR-197-3p was downregulated in HCC tissues and that the low level of miR-197-3p expression in HCC tumours correlated with aggressive clinicopathological characteristics; thus, miR-197-3p may serve as a predictor for poor prognosis in patients with HCC. Additionally, miR-197-3p markedly inhibited the metastasis of HCC cells in vitro and in vivo. Bioinformatics analysis further identified zinc finger protein interacted with K protein 1 (ZIK1) as a novel target of miR-197-3p in HCC cells. These findings suggest that miR-197-3p may regulate the survival of HCC cells, partially through the downregulation of ZIK1. Therefore, the miR-197-3p/ZIK1 axis may serve as a novel therapeutic target in patients with HCC.

Different types of viral‑host junction found in HBV integration breakpoints in HBV‑infected patients

The present study surveyed the characteristics of hepatitis B virus (HBV) integration in the liver genomes of patients with acute hepatitis B (AHB), carriers of inactive hepatitis B surface antigen (HBsAg), and patients with chronic hepatitis B (CHB) receiving antiviral treatment. 'Short‑read' whole genome sequencing (WGS) with an average of 4,879x coverage for HBV integration was performed in three patients with AHB, two carriers of inactive HBsAg, and 13 patients with CHB receiving antiviral treatment. Conventional polymerase chain reaction and Sanger sequencing were used to verify integration breakpoints supported by at least two paired‑end reads, and viral‑host chimeric transcripts were surveyed simultaneously. HBV integration breakpoints were 100% identified with an average of 138.2±379.9 breakpoints per sample. The numbers of HBV integration breakpoints were positively associated with the sequencing depth coverage numbers and levels of intrahepatic covalently closed circular DNA, respectively (P<0.0001 and P<0.0001). Four types of viral‑host junction in 14 HBV integration breakpoints were detected (two viral junctions mapped in the HBs gene, one in the Precore gene, and others within the HBx gene): Forward simple junction, reverse simple junction, forward and reverse complicated junction, and microhomology were found in many of the junctions. Expression of viral‑human chimeric transcripts was observed in several breakpoints, including the HBs gene. As a result, HBV can integrate into the host gene in the same manner as non‑homologous end joining and microhomology‑mediated end joining with numerous sites, and a close association may exist between HBV integration and patient prognosis. HBx integration may be indispensable for viral‑host chimeric transcription and HBsAg may be produced from integrated DNA.

Comprehensive review of Hepatitis B Virus-associated hepatocellular carcinoma research through text mining and big data analytics

PubMed was text mined to glean insights into the role of Hepatitis B virus (HBV) in hepatocellular carcinoma (HCC) from the massive number of publications (9249) available to date. Reports from ∼70 countries identified >1300 human genes associated with either the Core, Surface or X gene in HBV-associated HCC. One hundred and forty-three of these host genes, which can potentially yield 1180 biomolecular interactions, each were reported in at least three different publications to be associated with the same HBV. These 143 genes function in 137 pathways, involved mainly in the cell cycle, apoptosis, inflammation and signalling. Fourteen of these molecules, primarily transcriptional regulators or kinases, play roles in several pathways pertinent to the hallmarks of cancers. 'Chronic' was the most frequent word used across the 9249 abstracts. A key event in chronic HBV infection is the integration of HBV into the host genome. The advent of cost-effective, next-generation sequencing technology facilitated the employment of big-data analytics comprehensively to characterize HBV-host integration within HCC patients. A total of 5331 integration events were reported across seven publications, with most of these integrations observed between the Core/X gene and the introns of genes. Nearly one-quarter of the intergenic integrations are within repeats, especially long interspersed nuclear elements (LINE) repeats. Integrations within 13 genes were each reported by at least three different studies. The human gene with the most HBV integrations observed is the TERT gene where a total of 224 integrations, primarily at its promoter and within the tumour tissue, were reported by six of seven publications. This unique review, which employs state-of-the-art text-mining and data-analytics tools, represents the most complete, systematic and comprehensive review of nearly all the publications associated with HBV-associated HCC research. It provides important resources to either focus future research or develop therapeutic strategies to target key molecules reported to play important roles in key pathways of HCC, through the systematic analyses of the commonly reported molecules associated with the various HBV genes in HCC, including information about the interactions amongst these commonly reported molecules, the pathways in which they reside as well as detailed information regarding the viral and host genes associated with HBV integration in HCC patients. Hence this review, which highlights pathways and key human genes associated with HBV in HCC, may facilitate the deeper elucidation of the role of HBV in hepato-carcinogenesis, potentially leading to timely intervention against this deadly disease.

Cellular Genomic Sites of Hepatitis B Virus DNA Integration

Infection with the Hepatitis B Virus (HBV) is one of the strongest risk-factors for liver cancer (hepatocellular carcinoma, HCC). One of the reported drivers of HCC is the integration of HBV DNA into the host cell genome, which may induce pro-carcinogenic pathways. These reported pathways include: induction of chromosomal instability; generation of insertional mutagenesis in key cancer-associated genes; transcription of downstream cancer-associated cellular genes; and/or formation of a persistent source of viral protein expression (particularly HBV surface and X proteins). The contribution of each of these specific mechanisms towards carcinogenesis is currently unclear. Here, we review the current knowledge of specific sites of HBV DNA integration into the host genome, which sheds light on these mechanisms. We give an overview of previously-used methods to detect HBV DNA integration and the enrichment of integration events in specific functional and structural cellular genomic sites. Finally, we posit a theoretical model of HBV DNA integration during disease progression and highlight open questions in the field.