Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers

Hepatitis B virus DNA integration: Implications for diagnostics, therapy, and outcome

Hepatitis B virus (HBV) DNA integration - originally recognised as a non-functional byproduct of the HBV life cycle - has now been accepted as a significant contributor to HBV pathogenesis and hepatitis D virus (HDV) persistence. Integrated HBV DNA is derived from linear genomic DNA present in viral particles or produced from aberrantly processed relaxed circular genomic DNA following an infection, and can drive expression of hepatitis B surface antigen (HBsAg) and HBx. DNA integration events accumulate over the course of viral infection, ranging from a few percent during early phases to nearly 100 percent of infected cells after prolonged chronic infections. HBV DNA integration events have primarily been investigated in the context of hepatocellular carcinoma development as they can activate known oncogenes and other growth promoting genes, cause chromosomal instability and, presumably, induce epigenetic alterations, promoting tumour growth. More recent evidence suggests that HBsAg expression from integrated DNA might contribute to HBV pathogenesis by attenuating the immune response. Integrated DNA provides a source for envelope proteins required for HDV replication and hence represents a means for HDV persistence. Because integrated DNA is responsible for persistence of HBsAg in the absence of viral replication it impacts established criteria for the resolution of HBV infection, which rely on HBsAg as a diagnostic marker. Integrated HBV DNA has been useful in assessing the turnover of infected hepatocytes which occurs during all phases of chronic hepatitis B including the initial phase of infection historically termed immune tolerant. HBV DNA integration has also been shown to impact the development of novel therapies targeting viral RNAs.

Comparative Whole-Genome Sequencing Analysis of In-situ and Invasive Acral Lentiginous Melanoma: Markedly Increased Copy Number Gains of GAB2 , PAK1 , UCP2 , and CCND1 are Associated with Melanoma Invasion

Acral lentiginous melanoma (ALM) is the most common subtype of acral melanoma. Even though recent genetic studies are reported in acral melanomas, the genetic differences between in-situ and invasive ALM remain unclear. We aimed to analyze specific genetic changes in ALM and compare genetic differences between in-situ and invasive lesions to identify genetic changes associated with the pathogenesis and progression of ALM. We performed whole genome sequencing of 71 tissue samples from 29 patients with ALM. Comparative analyses were performed, pairing in-situ ALMs with normal tissues and, furthermore, invasive ALMs with normal and in-situ tissues. Among 21 patients with in-situ ALMs, 3 patients (14.3%) had SMIM14 , SLC9B1 , FRG1 , FAM205A , ESRRA , and ESPN mutations, and copy number (CN) gains were identified in only 2 patients (9.5%). Comparing 13 invasive ALMs with in-situ tissues, CN gains were identified in GAB2 in 8 patients (61.5%), PAK1 in 6 patients (46.2%), and UCP2 and CCND1 in 5 patients (38.5%). Structural variants were frequent in in-situ and invasive ALM lesions. Both in-situ and invasive ALMs had very low frequencies of common driver mutations. Structural variants were common in both in-situ and invasive ALMs. Invasive ALMs had markedly increased CN gains, such as GAB2 , PAK1 , UCP2 , and CCND1 , compared with in-situ lesions. These results suggest that they are associated with melanoma invasion.

Dysregulation of RNA splicing in early non-alcoholic fatty liver disease through hepatocellular carcinoma

While changes in RNA splicing have been extensively studied in hepatocellular carcinoma (HCC), no studies have systematically investigated changes in RNA splicing during earlier liver disease. Mouse studies have shown that disruption of RNA splicing can trigger liver disease and we have shown that the splicing factor SRSF3 is decreased in the diseased human liver, so we profiled RNA splicing in liver samples from twenty-nine individuals with no-history of liver disease or varying degrees of non-alcoholic fatty liver disease (NAFLD). We compared our results with three publicly available transcriptome datasets that we re-analyzed for splicing events (SEs). We found many changes in SEs occurred during early liver disease, with fewer events occurring with the onset of inflammation and fibrosis. Many of these early SEs were enriched for SRSF3-dependent events and were associated with SRSF3 binding sites. Mapping the early and late changes to gene ontologies and pathways showed that the genes harboring these early SEs were involved in normal liver metabolism, whereas those harboring late SEs were involved in inflammation, fibrosis and proliferation. We compared the SEs with HCC data from the TCGA and observed that many of these early disease SEs are found in HCC samples and, furthermore, are correlated with disease survival. Changes in splicing factor expression are also observed, which may be associated with distinct subsets of the SEs. The maintenance of these SEs through the multi-year oncogenic process suggests that they may be causative. Understanding the role of these splice variants in metabolic liver disease progression may shed light on the triggers of liver disease progression and the pathogenesis of HCC.

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.

Hepatocellular Carcinoma Genetic Classification

ABSTRACT

Hepatocellular carcinoma (HCC) represents a significant global burden, with management complicated by its heterogeneity, varying presentation, and relative resistance to therapy. Recent advances in the understanding of the genetic, molecular, and immunological underpinnings of HCC have allowed a detailed classification of these tumors, with resultant implications for diagnosis, prognostication, and selection of appropriate treatments. Through the correlation of genomic features with histopathology and clinical outcomes, we are moving toward a comprehensive and unifying framework to guide our diagnostic and therapeutic approach to HCC.

Precise characterization of somatic complex structural variations from tumor/control paired long-read sequencing data with nanomonsv

We present our novel software, nanomonsv, for detecting somatic structural variations (SVs) using tumor and matched control long-read sequencing data with a single-base resolution. The current version of nanomonsv includes two detection modules, Canonical SV module, and Single breakend SV module. Using tumor/control paired long-read sequencing data from three cancer and their matched lymphoblastoid lines, we demonstrate that Canonical SV module can identify somatic SVs that can be captured by short-read technologies with higher precision and recall than existing methods. In addition, we have developed a workflow to classify mobile element insertions while elucidating their in-depth properties, such as 5' truncations, internal inversions, as well as source sites for 3' transductions. Furthermore, Single breakend SV module enables the detection of complex SVs that can only be identified by long-reads, such as SVs involving highly-repetitive centromeric sequences, and LINE1- and virus-mediated rearrangements. In summary, our approaches applied to cancer long-read sequencing data can reveal various features of somatic SVs and will lead to a better understanding of mutational processes and functional consequences of somatic SVs.

Hepatitis B Virus DNA Integration Drives Carcinogenesis and Provides a New Biomarker for HBV-related HCC

Hepatitis B virus (HBV) DNA integration is an incidental event in the virus replication cycle and occurs in less than 1% of infected hepatocytes during viral infection. However, HBV DNA is present in the genome of approximately 90% of HBV-related HCCs and is the most common somatic mutation. Whole genome sequencing of liver tissues from chronic hepatitis B patients showed integration occurring at random positions in human chromosomes; however, in the genomes of HBV-related HCC patients, there are integration hotspots. Both the enrichment of the HBV-integration proportion in HCC and the emergence of integration hotspots suggested a strong positive selection of HBV-integrated hepatocytes to progress to HCC. The activation of HBV integration hotspot genes, such as telomerase (TERT) or histone methyltransferase (MLL4/KMT2B), resembles insertional mutagenesis by oncogenic animal retroviruses. These candidate oncogenic genes might shed new light on HBV-related HCC biology and become targets for new cancer therapies. Finally, the HBV integrations in individual HCC contain unique sequences at the junctions, such as virus-host chimera DNA (vh-DNA) presumably being a signature molecule for individual HCC. HBV integration may thus provide a new cell-free tumor DNA biomarker to monitor residual HCC after curative therapies or to track the development of de novo HCC.

Constructing a Cancer Patient-Specific Network Based on Second-Order Partial Correlations of Gene Expression and DNA Methylation

Typically patient-specific gene networks are constructed with gene expression data only. Such networks cannot distinguish direct gene interactions from indirect interactions via others such as the effect of epigenetic events to gene activity. There is an increasing evidence of inter-individual variations not only in gene expression but also in epigenetic events such as DNA methylation. In this paper we propose a new method for constructing a cancer patient-specific gene correlation network using both gene expression and DNA methylation data. We derive a patient-specific network from differential second-order partial correlations of gene expression and DNA methylation between normal samples and the patient sample. The network represents direct interactions between genes by controlling the effect of DNA methylation. Using this method, we constructed 4,000 patient-specific networks for 10 types of cancer. The networks are highly effective in classifying different types of cancer and in deriving potential prognostic gene pairs. In particular, potential prognostic gene pairs derived from the networks were powerful in predicting the survival time of cancer patients. This approach will help identify patient-specific gene correlations and predict prognosis of cancer patients.

RNA splicing: a dual-edged sword for hepatocellular carcinoma

RNA splicing is the fundamental process that brings diversity at the transcriptome and proteome levels. The spliceosome complex regulates minor and major processes of RNA splicing. Aberrant regulation is often associated with different diseases, including diabetes, stroke, hypertension, and cancer. In the majority of cancers, dysregulated alternative RNA splicing (ARS) events directly affect tumor progression, invasiveness, and often lead to poor survival of the patients. Alike the rest of the gastrointestinal malignancies, in hepatocellular carcinoma (HCC), which alone contributes to ~ 75% of the liver cancers, a large number of ARS events have been observed, including intron retention, exon skipping, presence of alternative 3'-splice site (3'SS), and alternative 5'-splice site (5'SS). These events are reported in spliceosome and non-spliceosome complexes genes. Molecules such as MCL1, Bcl-X, and BCL2 in different isoforms can behave as anti-apoptotic or pro-apoptotic, making the spliceosome complex a dual-edged sword. The anti-apoptotic isoforms of such molecules bring in resistance to chemotherapy or cornerstone drugs. However, in contrast, multiple malignant tumors, including HCC that target the pro-apoptotic favoring isoforms/variants favor apoptotic induction and make chemotherapy effective. Herein, we discuss different splicing events, aberrations, and antisense oligonucleotides (ASOs) in modulating RNA splicing in HCC tumorigenesis with a possible therapeutic outcome.

Comprehensive analysis of full-length transcripts reveals novel splicing abnormalities and oncogenic transcripts in liver cancer

Genes generate transcripts of various functions by alternative splicing. However, in most transcriptome studies, short-reads sequencing technologies (next-generation sequencers) have been used, leaving full-length transcripts unobserved directly. Although long-reads sequencing technologies would enable the sequencing of full-length transcripts, the data analysis is difficult. In this study, we developed an analysis pipeline named SPLICE and analyzed cDNA sequences from 42 pairs of hepatocellular carcinoma (HCC) and matched non-cancerous livers with an Oxford Nanopore sequencer. Our analysis detected 46,663 transcripts from the protein-coding genes in the HCCs and the matched non-cancerous livers, of which 5,366 (11.5%) were novel. A comparison of expression levels identified 9,933 differentially expressed transcripts (DETs) in 4,744 genes. Interestingly, 746 genes with DETs, including the LINE1-MET transcript, were not found by a gene-level analysis. We also found that fusion transcripts of transposable elements and hepatitis B virus (HBV) were overexpressed in HCCs. In vitro experiments on DETs showed that LINE1-MET and HBV-human transposable elements promoted cell growth. Furthermore, fusion gene detection showed novel recurrent fusion events that were not detected in the short-reads. These results suggest the efficiency of full-length transcriptome studies and the importance of splicing variants in carcinogenesis.

Genes generate transcripts of various functions by alternative splicing. However, in most transcriptome studies, short-reads sequencing technologies (next-generation sequencers) have been used, leaving full-length transcripts unobserved directly. In this study, we developed an analysis pipeline named SPLICE for long-read transcriptome sequencing and analyzed cDNA sequences from 42 pairs of hepatocellular carcinoma (HCC), and matched non-cancerous livers with an Oxford Nanopore sequencer. Our analysis detected 5,366 novel transcripts and 9,933 differentially expressed transcripts in 4,744 genes between HCCs and non-cancerous livers. An analysis of hepatitis B virus (HBV) transcripts showed that fusion transcripts of the HBV gene and human transposable elements were overexpressed in HBV-infected HCCs. We also identified fusion genes that were not found in the short-reads. These results suggest that long-reads sequencing technologies provide a fuller understanding of cancer transcripts and that our method contributes to the analysis of transcriptome sequences by such technologies.

A New Approach to Deriving Prognostic Gene Pairs From Cancer Patient-Specific Gene Correlation Networks

Many of the known prognostic gene signatures for cancer are individual genes or combination of genes, found by the analysis of microarray data. However, many of the known cancer signatures are less predictive than random gene expression signatures, and such random signatures are significantly associated with proliferation genes. With the availability of RNA-seq gene expression data for thousands of human cancer patients, we have analyzed RNA-seq and clinical data of cancer patients and constructed gene correlation networks specific to individual cancer patients. From the patient-specific gene correlation networks, we derived prognostic gene pairs for three types of cancer. In this paper, we propose a new method for inferring prognostic gene pairs from patient-specific gene correlation networks. The main difference of our method from previous ones includes (1) it is focused on finding prognostic gene pairs rather than prognostic genes, (2) it can identify prognostic gene pairs from RNA-seq data even when no significant prognostic genes exist, and (3) prognostic gene pairs can serve as robust prognostic biomarkers in the sense that most prognostic gene pairs show little association with proliferation genes, the major boosting factor of the predictive power of random gene signatures. Evaluation of our method with extensive data of three types of cancer (liver cancer, pancreatic cancer, and stomach cancer) showed that our approach is general and that gene pairs can serve as more reliable prognostic signatures for cancer than genes. Analysis of patient-specific gene networks suggests that prognosis of individual cancer patients is affected by the existence of prognostic gene pairs in the patient-specific network and by the size of the patient-specific network. Although preliminary, our approach will be useful for finding gene pairs to predict survival time of patients and to tailor treatments to individual characteristics. The program for dynamically constructing patient-specific gene networks and for finding prognostic gene pairs is available at http://bclab.inha.ac.kr/LPS.

Inhibition of Viral Replication Reduces Transcriptionally Active Distinct Hepatitis B Virus Integrations With Implications on Host Gene Dysregulation

BACKGROUND & AIMS

Hepatocellular carcinogenesis of hepatitis B virus (HBV) infection may arise from integration of viral DNA into the host genome. We aimed to gauge the effect of viral inhibition on transcriptionally active HBV-host integration events and explore the correlation of viral integrations with host gene dysregulation.

METHODS

We leveraged data and biospecimens from an interventional trial, in which patients with HBV viremia above 2000 IU/mL and minimally raised serum liver enzyme were randomized to receive tenofovir disoproxil fumarate (TDF) or placebo for 3 years. Total RNA-sequencing was performed on paired liver biopsies taken before and after the 3-year intervention in 119 patients. Virus-host chimeric reads were captured to quantify the number of distinct viral integrations. Dysregulation of a host gene disrupted by viral integration was defined by aberrant expression >2 standard deviations away from samples without viral integration.

RESULTS

The TDF (n = 64) and placebo groups (n = 55) were comparable at baseline. Expressed viral integrations were detected in all pre- and posttreatment samples. The number of distinct viral integrations significantly correlated with circulatory biomarkers indicative of viral activities including HBV DNA, RNA, and viral antigens (P < .0003 for all correlations). Moreover, TDF vs placebo achieved a significantly greater reduction in distinct viral integrations, with 3.28-fold and 1.81-fold decreases in the expressed integrations per million reads, respectively (analysis of covariance, P = .037). Besides, viral integrations significantly correlated with host gene dysregulation.

CONCLUSION

Inhibition of viral replication reduces the number of transcriptionally active distinct HBV-host DNA integrations in patients with substantial viremia. Given the mutagenic potentials of viral integrations, such treatment effects should be considered in patient management.

Roles of fusion genes in digestive system cancers: dawn for cancer precision therapy

For advanced and advanced tumors of the digestive system, personalized, precise treatment could be a lifesaving medicine. With the development of next-generation sequencing technology, detection of fusion genes in solid tumors has become more extensive. Some fusion gene targeting therapies have been written into the guidelines for digestive tract tumors, such as for neurotrophic receptor tyrosine kinase, fibroblast growth factor receptor 2. There are also many fusion genes being investigated as potential future therapeutic targets. This review focuses on the current detection methods for fusion genes, fusion genes written into the digestive system tumor guidelines, and potential fusion gene therapy targets in different organs to discuss the possibility of clinical treatments for these targets in digestive system tumors.

Kinetics of atrial and brain natriuretic peptides during hemodialysis are regulated in association with different cardiac functional changes

The blood levels of atrial and brain natriuretic peptides (ANP and BNP) are both increased markedly in hemodialysis patients, but the kinetics of the two are not always parallel. The present study investigated the association of changes in ANP and BNP levels before and after dialysis with changes in cardiac function in hemodialysis patients. A total of 57 patients (mean age 64 years, 47 males and 10 females) on maintenance hemodialysis with sinus rhythm were enrolled. Blood samples were taken at the beginning and end of dialysis, and plasma levels of ANP and BNP were measured. Changes in cardiac function during dialysis were examined by echocardiography performed just before and after dialysis. Both plasma ANP and BNP concentrations decreased significantly after hemodialysis, but the rate of decrease in BNP [mean ± SD, 555 ± 503 to 519 ± 477 pg/mL (- 6.4%), P = 0.011] was much smaller than that in ANP [233 ± 123 to 132 ± 83 pg/mL (- 43.4%), P < 0.001]. As for the relation to the changes in echocardiographic parameters before and after dialysis, the decrease in inferior vena cava diameter had a close correlation with the decrease in ANP (r = 0.528, P < 0.001), but not BNP. In contrast, the decrease in left ventricular end-diastolic volume index was correlated only with the decrease in BNP (r = 0.297, P = 0.035). The peak velocity ratio of early diastolic to atrial filling decreased with preload reduction by dialysis, and its decrease was more strongly correlated with the decrease in BNP (r = 0.407, P = 0.002) than that in ANP (r = 0.273, P = 0.040). These results demonstrated that in hemodialysis patients, the decrease in plasma ANP by a single dialysis was essentially caused by blood volume reduction, while BNP decrease was mainly induced by the reduction of left ventricular overload. Our findings indicate that the kinetics of both peptides during dialysis are regulated by different cardiac and hemodynamic factors.

Hepatitis B virus DNA integration as a novel biomarker of hepatitis B virus-mediated pathogenetic properties and a barrier to the current strategies for hepatitis B virus cure

Chronic infection with Hepatitis B Virus (HBV) is a major cause of liver-related morbidity and mortality worldwide. HBV-DNA integration into the human genome is recognized as a frequent event occurring during the early phases of HBV infection and characterizing the entire course of HBV natural history. The development of refined molecular biology technologies sheds new light on the functional implications of HBV-DNA integration into the human genome, including its role in the progression of HBV-related pathogenesis and in triggering the establishment of pro-oncogenic mechanisms, promoting the development of hepatocellular carcinoma. The present review provides an updated and comprehensive overview of the current body of knowledge on HBV-DNA integration, focusing on the molecular mechanisms underlying HBV-DNA integration and its occurrence throughout the different phases characterizing the natural history of HBV infection. Furthermore, here we discuss the main clinical implications of HBV integration as a biomarker of HBV-related pathogenesis, particularly in reference to hepatocarcinogenesis, and how integration may act as a barrier to the achievement of HBV cure with current and novel antiviral therapies. Overall, a more refined insight into the mechanisms and functionality of HBV integration is paramount, since it can potentially inform the design of ad hoc diagnostic tools with the ability to reveal HBV integration events perturbating relevant intracellular pathways and for identifying novel therapeutic strategies targeting alterations directly related to HBV integration.

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.

Advances in Multi-Omics Applications in HBV-Associated Hepatocellular Carcinoma

Hepatitis B virus (HBV) specifically infects liver cells, leading to progressive liver cirrhosis and significantly increasing the risk of hepatocellular carcinoma (HCC). The maturity of sequencing technology, improvement in bioinformatics data analysis and progress of omics technologies had improved research efficiency. The occurrence and progression of HCC are affected by multisystem and multilevel pathological changes. With the application of single-omics technologies, including genomics, transcriptomics, metabolomics and proteomics in tissue and body fluid samples, and even the novel development of multi-omics analysis on a single-cell platform, HBV-associated HCC changes can be better analyzed. The review summarizes the application of single omics and combined analysis of multi-omics data in HBV-associated HCC and proposes the importance of multi-omics analysis in the type of HCC, which provide the possibility for the precise diagnosis and therapy of HBV-associated HCC.

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.

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.

Hepatocellular carcinoma (HCC): Epidemiology, etiology and molecular classification

Hepatocellular carcinoma (HCC), the primary malignancy of hepatocytes, is a diagnosis with bleak outcome. According to National Cancer Institute's SEER database, the average five-year survival rate of HCC patients in the US is 19.6% but can be as low as 2.5% for advanced, metastatic disease. When diagnosed at early stages, it is treatable with locoregional treatments including surgical resection, Radio-Frequency Ablation, Trans-Arterial Chemoembolization or liver transplantation. However, HCC is usually diagnosed at advanced stages when the tumor is unresectable, making these treatments ineffective. In such instances, systemic therapy with tyrosine kinase inhibitors (TKIs) becomes the only viable option, even though it benefits only 30% of patients, provides only a modest (~3months) increase in overall survival and causes drug resistance within 6months. HCC, like many other cancers, is highly heterogeneous making a one-size fits all option problematic. The selection of liver transplantation, locoregional treatment, TKIs or immune checkpoint inhibitors as a treatment strategy depends on the disease stage and underlying condition(s). Additionally, patients with similar disease phenotype can have different molecular etiology making treatment responses different. Stratification of patients at the molecular level would facilitate development of the most effective treatment option. With the increase in efficiency and affordability of "omics"-level analysis, considerable effort has been expended in classifying HCC at the molecular, metabolic and immunologic levels. This review examines the results of these efforts and the ways they can be leveraged to develop targeted treatment options for HCC.

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.

A Novel RNA Binding Protein-Related Prognostic Signature for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly malignant and aggressive cancer with high recurrence rates and mortality. Some studies have illustrated that RNA binding proteins (RBPs) were involved in the carcinogenesis and development of multiple cancers, but the roles in HCC were still unclear. We downloaded the RNA-seq and corresponding clinical information of HCC from The Cancer Genome Atlas (TCGA) database, and 330 differentially expressed RBPs were identified between normal and HCC tissues. Through series of the univariate, the least absolute shrinkage selection operator (LASSO), and the stepwise multivariate Cox regression analyses, six prognosis-related key RBPs (CNOT6, UPF3B, MRPL54, ZC3H13, IFIT5, and PPARGC1A) were screened out from DE RBPs, and a six-RBP gene risk score signature was constructed in training set. Survival analysis indicated that HCC patients with high-risk scores had significantly worse overall survival than low-risk patients, and furthermore, the signature can be used as an independent prognostic indicator. The good accuracy of this prognostic signature was confirmed by the ROC curve analysis and was further validated in the International Cancer Genome Consortium (ICGC) HCC cohort. Besides, a nomogram based on six RBP genes was established and internally validated in the TCGA cohort. Gene set enrichment analysis demonstrated some cancer-related phenotypes were significantly gathered in the high-risk group. Overall, our study first identified an RBP-related six-gene prognostic signature, which could serve as a promising prognostic biomarker and provide some potential therapeutic targets for HCC.

The genomic landscape of Mongolian hepatocellular carcinoma

Mongolia has the highest incidence of hepatocellular carcinoma (HCC) in the world, but its causative factors and underlying tumor biology remain unknown. Here, we describe molecular characteristics of HCC from 76 Mongolian patients by whole-exome and transcriptome sequencing. We present a comprehensive analysis of mutational signatures, driver genes, and molecular subtypes of Mongolian HCC compared to 373 HCC patients of different races and ethnicities and diverse etiologies. Mongolian HCC consists of prognostic molecular subtypes similar to those found in patients from other areas of Asia, Europe, and North America, as well as other unique subtypes, suggesting the presence of distinct etiologies linked to Mongolian patients. In addition to common driver mutations (TP53, CTNNB1) frequently found in pan-cancer analysis, Mongolian HCC exhibits unique drivers (most notably GTF2IRD2B, PNRC2, and SPTA1), the latter of which is associated with hepatitis D viral infection. These results suggest the existence of new molecular mechanisms at play in Mongolian hepatocarcinogenesis.

Insights into Hepatitis B Virus DNA Integration-55 Years after Virus Discovery

Hepatitis B virus (HBV), which was discovered in 1965, is a threat to global public health. HBV infects human hepatocytes and leads to acute and chronic liver diseases, and there is no cure. In cells infected by HBV, viral DNA can be integrated into the cellular genome. HBV DNA integration is a complicated process during the HBV life cycle. Although HBV integration normally results in replication-incompetent transcripts, it can still act as a template for viral protein expression. Of note, it is a primary driver of hepatocellular carcinoma (HCC). Recently, with the development of detection methods and research models, the molecular biology and the pathogenicity of HBV DNA integration have been better revealed. Here, we review the advances in the research of HBV DNA integration, including molecular mechanisms, detection methods, research models, the effects on host and viral gene expression, the role of HBV integrations in the pathogenesis of HCC, and potential treatment strategies. Finally, we discuss possible future research prospects of HBV DNA integration.

Transcriptome analysis offers a comprehensive illustration of the genetic background of pediatric acute myeloid leukemia

Recent advances in the genetic understanding of acute myeloid leukemia (AML) have improved clinical outcomes in pediatric patients. However, ∼40% of patients with pediatric AML relapse, resulting in a relatively low overall survival rate of ∼70%. The objective of this study was to reveal the comprehensive genetic background of pediatric AML. We performed transcriptome analysis (RNA sequencing [RNA-seq]) in 139 of the 369 patients with de novo pediatric AML who were enrolled in the Japanese Pediatric Leukemia/Lymphoma Study Group AML-05 trial and investigated correlations between genetic aberrations and clinical information. Using RNA-seq, we identified 54 in-frame gene fusions and 1 RUNX1 out-of-frame fusion in 53 of 139 patients. Moreover, we found at least 258 gene fusions in 369 patients (70%) through reverse transcription polymerase chain reaction and RNA-seq. Five gene rearrangements were newly identified, namely, NPM1-CCDC28A, TRIP12-NPM1, MLLT10-DNAJC1, TBL1XR1-RARB, and RUNX1-FNBP1. In addition, we found rare gene rearrangements, namely, MYB-GATA1, NPM1-MLF1, ETV6-NCOA2, ETV6-MECOM, ETV6-CTNNB1, RUNX1-PRDM16, RUNX1-CBFA2T2, and RUNX1-CBFA2T3. Among the remaining 111 patients, KMT2A-PTD, biallelic CEBPA, and NPM1 gene mutations were found in 11, 23, and 17 patients, respectively. These mutations were completely mutually exclusive with any gene fusions. RNA-seq unmasked the complexity of gene rearrangements and mutations in pediatric AML. We identified potentially disease-causing alterations in nearly all patients with AML, including novel gene fusions. Our results indicated that a subset of patients with pediatric AML represent a distinct entity that may be discriminated from their adult counterparts. Based on these results, risk stratification should be reconsidered.

From genome sequencing to the discovery of potential biomarkers in liver disease

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.

Clinical application of next-generation sequencing to the practice of neurology

Next-generation sequencing technologies allow for rapid and inexpensive large-scale genomic analysis, creating unprecedented opportunities to integrate genomic data into the clinical diagnosis and management of neurological disorders. However, the scale and complexity of these data make them difficult to interpret and require the use of sophisticated bioinformatics applied to extensive datasets, including whole exome and genome sequences. Detailed analysis of genetic data has shown that accurate phenotype information is essential for correct interpretation of genetic variants and might necessitate re-evaluation of the patient in some cases. A multidisciplinary approach that incorporates bioinformatics, clinical evaluation, and human genetics can help to address these challenges. However, despite numerous studies that show the efficacy of next-generation sequencing in establishing molecular diagnoses, pathogenic mutations are generally identified in fewer than half of all patients with genetic neurological disorders, exposing considerable gaps in the understanding of the human genome and providing opportunities to focus research on improving the usefulness of genomics in clinical practice. Looking forward, the emergence of precision health in neurological care will increasingly apply genomic data analysis to pharmacogenetics, preventive medicine, and patient-targeted therapies.

Alternative Splicing in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for the majority of primary liver cancer cases, with more than 850,000 new diagnoses per year globally. Recent trends in the United States have shown that liver cancer mortality has continued to increase in both men and women, while 5-year survival remains below 20%. Understanding key mechanisms that drive chronic liver disease progression to HCC can reveal new therapeutic targets and biomarkers for early detection of HCC. In that regard, many studies have underscored the importance of alternative splicing as a source of novel HCC prognostic markers and disease targets. Alternative splicing of pre-mRNA provides functional diversity to the genome, and endows cells with the ability to rapidly remodel the proteome. Genes that control fundamental processes, such as metabolism, cell proliferation, and apoptosis, are altered globally in HCC by alternative splicing. This review highlights the major splicing factors, RNA binding proteins, transcriptional targets, and signaling pathways that are of key relevance to HCC. We highlight primary research from the past 3-5 years involving functional interrogation of alternative splicing in rodent and human liver, using both large-scale transcriptomic and focused mechanistic approaches. Because this is a rapidly advancing field, we anticipate that it will be transformative for the future of basic liver biology, as well as HCC diagnosis and management.

The Roles of Cyclin-Dependent Kinases in Cell-Cycle Progression and Therapeutic Strategies in Human Breast Cancer

Cyclin-dependent kinases (CDKs) are serine/threonine kinases whose catalytic activities are regulated by interactions with cyclins and CDK inhibitors (CKIs). CDKs are key regulatory enzymes involved in cell proliferation through regulating cell-cycle checkpoints and transcriptional events in response to extracellular and intracellular signals. Not surprisingly, the dysregulation of CDKs is a hallmark of cancers, and inhibition of specific members is considered an attractive target in cancer therapy. In breast cancer (BC), dual CDK4/6 inhibitors, palbociclib, ribociclib, and abemaciclib, combined with other agents, were approved by the Food and Drug Administration (FDA) recently for the treatment of hormone receptor positive (HR+) advanced or metastatic breast cancer (A/MBC), as well as other sub-types of breast cancer. Furthermore, ongoing studies identified more selective CDK inhibitors as promising clinical targets. In this review, we focus on the roles of CDKs in driving cell-cycle progression, cell-cycle checkpoints, and transcriptional regulation, a highlight of dysregulated CDK activation in BC. We also discuss the most relevant CDK inhibitors currently in clinical BC trials, with special emphasis on CDK4/6 inhibitors used for the treatment of estrogen receptor-positive (ER+)/human epidermal growth factor 2-negative (HER2−) M/ABC patients, as well as more emerging precise therapeutic strategies, such as combination therapies and microRNA (miRNA) therapy.

An Unusually Short Latent Period of Therapy-Related Myeloid Neoplasm Harboring a Rare MLL-EP300 Rearrangement: Case Report and Literature Review

Therapy-related myeloid neoplasm (t-MN) is a late and lethal complication induced by chemotherapy and/or radiation therapy. Hematological malignancy is one of the most common primary diseases in patients with t-MN. However, the occurrence of t-MN in adult T-cell leukemia/lymphoma (ATL) patients is rarely reported, possibly due to the dismal prognosis of ATL per se. Here, we report a 62-year-old female who developed t-MN only three months after the completion of conventional chemotherapy and anti-CCR4 antibody for ATL acute type. The patient presented with persistent fever and monocytosis without any evidence of infectious diseases. Bone marrow examinations revealed chronic myelomonocytic leukemia-like disease with a chromosomal translocation of t(11;22)(q23;q13) as a solo cytogenetic abnormality, resulting in the diagnosis of t-MN. Next-generation sequencing analysis identified a rare chimeric transcript, MLL-EP300, without any additional somatic mutations. Although the patient underwent allogenic hematopoietic stem cell transplantation, she died of viral encephalomyelitis at 7 months after diagnosis of t-MN. Since recent therapeutic advances have extended the survival of patients with ATL, further evaluation of the long-term risks of developing t-MN in these patients is warranted.

Multi-omics Analysis of Microenvironment Characteristics and Immune Escape Mechanisms of Hepatocellular Carcinoma

The immune environment in primary tumor has a profound impact on immunotherapy. However, the clinical relevance of immune environment in hepatocellular carcinoma (HCC) is largely unknown. Here, the immune profile and its clinical response in HCC were investigated. The gene expression profiles of 569 HCCs from three cohorts (The Cancer Genome Atlas, TCGA, n = 257; Gene Expression Omnibus, GEO, n = 170; International Cancer Genome Consortium, ICGC, n = 142) were used in the current study. Five gene expression subtypes (C1-C5) responsible for global immune genes were identified in HCCs at stage I/II. It was found that subtype C4 was associated with upregulation and subtype C5 was associated with downregulation of immune profiles in most metagenes. Immune-correlation analysis of the five subtypes demonstrated that C3 and C4 had higher immune score and better prognostic outcome, as compared with other subtypes. Moreover, the mutation frequencies of TP53, CTNNB1, and AXIN1 had significant difference in the five subgroups. Further, the expression of PDCD1, CD274, PDCD1LG2, CTLA4, CD86, and CD80 was higher in subtype C4 in comparison with the other subtypes. The WGCNA of immune-related genes in the five subtypes revealed that blue and turquoise modules were positively correlated with subtype C4 and were associated with 12 common pathways in the KEGG database. These results were validated in external cohorts from the NCI (National Cancer Institute) cohort (GSE14520) and the ICGC (International Cancer Genome Consortium) cohort. In summary, one immune-enhanced subtype and one immune-decreased subtype having different immune and clinical characteristics may provide guidance for developing novel treatment strategies for immune system malfunction-related cancer.

Role of cyclin-dependent kinases (CDKs) in hepatocellular carcinoma: Therapeutic potential of targeting the CDK signaling pathway

Liver cancer is the fourth leading cause of cancer related mortality in the world, with hepatocellular carcinoma (HCC) representing the most common primary subtype. Two-thirds of HCC patients have advanced disease when diagnosed, and for these patients, treatment strategies remain limited. In addition, there is a high incidence of tumor recurrence after surgical resection with the current treatment regimens. The development of novel and more effective agents is required. Cyclin-dependent kinases (CDKs) constitute a family of 21 different protein kinases involved in regulating cell proliferation, apoptosis, and drug resistance, and are evaluated in preclinical and clinical trials as chemotherapeutics. To summarize and discuss the therapeutic potential of targeting CDKs in HCC, recent published articles identified from PubMed were comprehensively reviewed. The key words included hepatocellular carcinoma, cyclin-dependent kinases, and CDK inhibitors. This review focuses on the emerging evidence from studies describing the genetic and functional aspects of CDKs in HCC. We also present an overview of CDK inhibitors that have shown efficacy in laboratory studies of HCC. Although many of the studies assessing CDK-targeting therapies in HCC are at the preclinical stage, there is significant evidence that CDK inhibitors used alone or in combination with established chemotherapy drugs could have significant applications in HCC.

Comprehensive analysis of transcriptome profiles in hepatocellular carcinoma

Background

Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC.

Methods

Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed.

Results

Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis.

Conclusions

Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

HBV Integration-mediated Cell Apoptosis in HepG2.2.15

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the second leading cause of cancer deaths in the word. Hepatitis B virus (HBV) infection plays an important role in the development of HCC. However, the mechanisms by which HBV integration affects host cells remain poorly understood. HepG2.2.15 cell line is derived from HCC cell line HepG2 with stable transfection HBV expression. In this study, HepG2.2.15 cells showed decreased proliferation, G1 cell cycle arrest and increased apoptosis, when compared to HepG2 cells. HBV capture sequencing was conducted in both genome and transcriptome level, followed by RNA expression sequencing in HepG2.2.15. Here, CAMSAP2/CCDC12/DPP7/OR4F3 were found to be targets for HBV integration in both genome and transcriptome level, accompanied by alteration in their expression when compared to HepG2. Among these genes, DPP7 was the only one gene with HBV integration into its exon, meanwhile DPP7 expression level was also downregulated in HepG2.2.15 as compared to HepG2. Furthermore, DPP7 knockdown resulted in increased apoptosis through upregulation of the Bax/Bcl2 ratio in HepG2 cells. Our results suggest that HBV integration of DPP7 was involved in cell apoptosis.

Pathogenic mutations identified by a multimodality approach in 117 Japanese Fanconi anemia patients

Fanconi anemia is a rare recessive disease characterized by multiple congenital abnormalities, progressive bone marrow failure, and a predisposition to malignancies. It results from mutations in one of the 22 known FANC genes. The number of Japanese Fanconi anemia patients with a defined genetic diagnosis was relatively limited. In this study, we reveal the genetic subtyping and the characteristics of mutated FANC genes in Japan and clarify the genotype-phenotype correlations. We studied 117 Japanese patients and successfully subtyped 97% of the cases. FANCA and FANCG pathogenic variants accounted for the disease in 58% and 25% of Fanconi anemia patients, respectively. We identified one FANCA and two FANCG hot spot mutations, which are found at low percentages (0.04-0.1%) in the whole-genome reference panel of 3,554 Japanese individuals (Tohoku Medical Megabank). FANCB was the third most common complementation group and only one FANCC case was identified in our series. Based on the data from the Tohoku Medical Megabank, we estimate that approximately 2.6% of Japanese are carriers of disease-causing FANC gene variants, excluding missense mutations. This is the largest series of subtyped Japanese Fanconi anemia patients to date and the results will be useful for future clinical management.

Solving Mendelian Mysteries: The Non-coding Genome May Hold the Key

Despite revolutionary advances in sequencing approaches, many mendelian disorders have remained unexplained. In this issue of Cell, Aneichyk et al. combine genomic and cell-type-specific transcriptomic data to causally link a non-coding mutation in the ubiquitous TAF1 gene to X-linked dystonia-parkinsonism.

Genomic Medicine and Implications for Hepatocellular Carcinoma Prevention and Therapy

The pathogenesis of hepatocellular carcinoma (HCC) is poorly understood, but recent advances in genomics have increased our understanding of the mechanisms by which hepatitis B virus, hepatitis C virus, alcohol, fatty liver disease, and other environmental factors, such as aflatoxin, cause liver cancer. Genetic analyses of liver tissues from patients have provided important information about tumor initiation and progression. Findings from these studies can potentially be used to individualize the management of HCC. In addition to sorafenib, other multi-kinase inhibitors have been approved recently for treatment of HCC, and the preliminary success of immunotherapy has raised hopes. Continued progress in genomic medicine could improve classification of HCCs based on their molecular features and lead to new treatments for patients with liver cancer.

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.

Advances in genomic hepatocellular carcinoma research

Background

Hepatocellular carcinoma (HCC) is the cancer with the second highest mortality in the world due to its late presentation and limited treatment options. As such, there is an urgent need to identify novel biomarkers for early diagnosis and to develop novel therapies. The availability of next-generation sequencing (NGS) data from tumors of liver cancer patients has provided us with invaluable resources to better understand HCC through the integration of data from different sources to facilitate the identification of promising biomarkers or therapeutic targets.

Findings

Here, we review key insights gleaned from more than 20 NGS studies of HCC tumor samples, comprising approximately 582 whole genomes and 1,211 whole exomes mainly from the East Asian population. Through consolidation of reported somatic mutations from multiple studies, we identified genes with different types of somatic mutations, including single nucleotide variations, insertion/deletions, structural variations, and copy number alterations as well as genes with multiple frequent viral integration. Pathway analysis showed that this curated list of somatic mutations is critically involved in cancer-related pathways, viral carcinogenesis, and signaling pathways. Lastly, we addressed the future directions of HCC research as more NGS datasets become available.

Conclusions

Our review is a comprehensive resource for the current NGS research in HCC, consolidating published articles, potential gene candidates, and their related biological pathways.

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.

A comprehensive characterization of cis-acting splicing-associated variants in human cancer

Although many driver mutations are thought to promote carcinogenesis via abnormal splicing, the landscape of splicing-associated variants (SAVs) remains unknown due to the complexity of splicing abnormalities. Here, we developed a statistical framework to systematically identify SAVs disrupting or newly creating splice site motifs and applied it to matched whole-exome and transcriptome sequencing data from 8976 samples across 31 cancer types, generating a catalog of 14,438 SAVs. Such a large collection of SAVs enabled us to characterize their genomic features, underlying mutational processes, and influence on cancer driver genes. In fact, ∼50% of SAVs identified were those disrupting noncanonical splice sites (non-GT-AG dinucleotides), including the third and fifth intronic bases of donor sites, or newly creating splice sites. Mutation signature analysis revealed that tobacco smoking is more strongly associated with SAVs, whereas ultraviolet exposure has less impact. SAVs showed remarkable enrichment of cancer-related genes, and as many as 14.7% of samples harbored at least one SAVs affecting them, particularly in tumor suppressors. In addition to intron retention, whose association with tumor suppressor inactivation has been previously reported, exon skipping and alternative splice site usage caused by SAVs frequently affected tumor suppressors. Finally, we described high-resolution distributions of SAVs along the gene and their splicing outcomes in commonly disrupted genes, including TP53, PIK3R1, GATA3, and CDKN2A, which offers genetic clues for understanding their functional properties. Collectively, our findings delineate a comprehensive portrait of SAVs, novel insights into transcriptional de-regulation in cancer.

Characterization of HBV integration patterns and timing in liver cancer and HBV-infected livers

Integration of Hepatitis B virus (HBV) into the human genome can cause genetic instability, leading to selective advantages for HBV-induced liver cancer. Despite the large number of studies for HBV integration into liver cancer, little is known about the mechanism of initial HBV integration events owing to the limitations of materials and detection methods. We conducted an HBV sequence capture, followed by ultra-deep sequencing, to screen for HBV integrations in 111 liver samples from human-hepatocyte chimeric mice with HBV infection and human clinical samples containing 42 paired samples from non-tumorous and tumorous liver tissues. The HBV infection model using chimeric mice verified the efficiency of our HBV-capture analysis and demonstrated that HBV integration could occur 23 to 49 days after HBV infection via microhomology-mediated end joining and predominantly in mitochondrial DNA. Overall HBV integration sites in clinical samples were significantly enriched in regions annotated as exhibiting open chromatin, a high level of gene expression, and early replication timing in liver cells. These data indicate that HBV integration in liver tissue was biased according to chromatin accessibility, with additional selection pressures in the gene promoters of tumor samples. Moreover, an integrative analysis using paired non-tumorous and tumorous samples and HBV-related transcriptional change revealed the involvement of TERT and MLL4 in clonal selection. We also found frequent and non-tumorous liver-specific HBV integrations in FN1 and HBV-FN1 fusion transcript. Extensive survey of HBV integrations facilitates and improves the understanding of the timing and biology of HBV integration during infection and HBV-related hepatocarcinogenesis.

Pan-cancer analysis of somatic mutations and transcriptomes reveals common functional gene clusters shared by multiple cancer types

To discover functional gene clusters across cancers, we performed a systematic pan-cancer analysis of 33 cancer types. We identified genes that were associated with somatic mutations and were the cores of a co-expression network. We found that multiple cancer types have relatively exclusive hub genes individually; however, the hub genes cooperate with each other based on their functional relationship. When we built a protein-protein interaction network of hub genes and found nine functional gene clusters across cancer types, the gene clusters divided not only the region of the network map, but also the function of the network by their distinct roles related to the development and progression of cancer. This functional relationship between the clusters and cancers was underpinned by the high expression of module genes and enrichment of programmed cell death, and known candidate cancer genes. In addition to protein-coding hub genes, non-coding hub genes had a possible relationship with cancer. Overall, our approach of investigating cancer genes enabled finding pan-cancer hub genes and common functional gene clusters shared by multiple cancer types based on the expression status of the primary tumour and the functional relationship of genes in the biological network.

Comprehensive genomic transcriptomic tumor-normal gene panel analysis for enhanced precision in patients with lung cancer

A CMS approved test for lung cancer is based on tumor-only analysis of a targeted 35 gene panel, specifically excluding the use of the patient's normal germline tissue. However, this tumor-only approach increases the risk of mistakenly identifying germline single nucleotide polymorphisms (SNPs) as somatically-derived cancer driver mutations (false positives). 621 patients with 30 different cancer types, including lung cancer, were studied to compare the precision of tumor somatic variant calling in 35 genes using tumor-only DNA sequencing versus tumor-normal DNA plus RNA sequencing. When sequencing of lung cancer was performed using tumor genomes alone without normal germline controls, 94% of variants identified were SNPs and thus false positives. Filtering for common SNPs still resulted in as high as 48% false positive variant calling. With tumor-only sequencing, 29% of lung cancer patients had a false positive variant call in at least one of twelve genes with directly targetable drugs. RNA analysis showed 18% of true somatic variants were not expressed. Thus, sequencing and analysis of both normal germline and tumor genomes is necessary for accurate identification of molecular targets. Treatment decisions based on tumor-only analysis may result in the administration of ineffective therapies while also increasing the risk of negative drug-related side effects.

Genome sequencing analysis of liver cancer for precision medicine

Liver cancer is the third leading cause of cancer-related death worldwide. Some thousands of liver cancer genome have been sequenced globally so far and most of driver genes/mutations with high frequency are established in liver cancer, including Wnt/β-catenin pathway, TP53/cell-cycle pathways, telomere maintenance, and chromatin regulators. HBV integration into cancer-related genes is also a driver event in hepatocarcinogenesis. These genes are affected by structural variants, copy-number alterations and virus integrations as well as point mutations. Etiological factors of liver cancer is most understood among common cancers, such as hepatitis, aflatoxin, alcohol, and metabolic diseases, and mutational signatures of liver cancer can provide evidence of the association between specific etiological factors and mutational signatures. Molecular classifications based on somatic mutations profiles, RNA expression profiles, and DNA methylation profiles are related with patient prognosis. For precision medicine, several actionable mutations with solid evidence such as targets of multi-kinase inhibitors is observed in liver cancer, but there is few molecular target therapy so far. It is possible that rare actionable mutations in liver cancer can guide other specific molecular therapy and immune therapy.

Circulating Cell-Free DNA in Hepatocellular Carcinoma: Current Insights and Outlook

Over the past decade, the advancements in massively parallel sequencing have provided a new paradigm in biomedical research to uncover the genetic basis of human diseases. Integration of ‘omics information has begun transforming clinical management of cancer patients in terms of diagnostics and treatment options, giving rise to the era of precision medicine. Currently, nucleic acids for molecular profiling for patients diagnosed with hepatocellular carcinoma (HCC) are typically obtained from resected tumor materials or transplanted neoplastic liver and occasionally from biopsies. Given the intrinsic risks associated with such invasive procedures, circulating cell-free DNA (cfDNA) has been proposed as an alternative source for tumor DNA. Circulating cfDNA is a type of cell-free nucleic acid that derives from apoptotic, necrotic, as well as living eukaryotic cells. Importantly, the detection of abnormal forms of circulating cfDNA that originate from cancer cells provides a new tool for cancer detection, disease monitoring, and molecular profiling. Currently, cfDNA is beginning to be adopted into clinical practice as a non-invasive tool to monitor disease by tracking the evolution of disease-specific genetic alterations in several major cancer types. Moreover, cfDNA is demonstrating potential clinical value as a surrogate to assess the molecular makeup of tumors and to overcome the sampling biases inherent to intra-tumor genetic heterogeneity, especially in the metastatic setting. With the improvements in ‘omics and molecular biology techniques, coupled with the increasing understanding in the molecular pathogenesis of cancer, it can be anticipated that the detection and analysis of cfDNA will become more specific and sensitive and thus enable cfDNA analysis to be used as a diagnostic aid in patients with early-stage disease and perhaps even in a screening setting. In this review, we provide an overview of the latest findings on the role and potential utility of cfDNA analysis in the diagnosis, management, and screening of HCC.

Whole genome sequencing analysis for cancer genomics and precision medicine

Explosive advances in next-generation sequencer (NGS) and computational analyses have enabled exploration of somatic protein-altered mutations in most cancer types, with coding mutation data intensively accumulated. However, there is limited information on somatic mutations in non-coding regions, including introns, regulatory elements and non-coding RNA. Structural variants and pathogen in cancer genomes remain widely unexplored. Whole genome sequencing (WGS) approaches can be used to comprehensively explore all types of genomic alterations in cancer and help us to better understand the whole landscape of driver mutations and mutational signatures in cancer genomes and elucidate the functional or clinical implications of these unexplored genomic regions and mutational signatures. This review describes recently developed technical approaches for cancer WGS and the future direction of cancer WGS, and discusses its utility and limitations as an analysis platform and for mutation interpretation for cancer genomics and cancer precision medicine. Taking into account the diversity of cancer genomes and phenotypes, interpretation of abundant mutation information from WGS, especially non-coding and structure variants, requires the analysis of large-scale WGS data integrated with RNA-Seq, epigenomics, immuno-genomic and clinic-pathological information.