Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma

A new risk score based on twelve hepatocellular carcinoma-specific gene expression can predict the patients' prognosis

A large panel of molecular biomarkers have been identified to predict the prognosis of hepatocellular carcinoma (HCC), yet with limited clinical application due to difficult extrapolation. We here generated a genetic risk score system comprised of 12 HCC-specific genes to better predict the prognosis of HCC patients. Four genomics profiling datasets (GSE5851, GSE28691, GSE15765 and GSE14323) were searched to seek HCC-specific genes by comparisons between cancer samples and normal liver tissues and between different subtypes of hepatic neoplasms. Univariate survival analysis screened HCC-specific genes associated with overall survival (OS) in the training dataset for next-step risk model construction. The prognostic value of the constructed HCC risk score system was then validated in the TCGA dataset. Stratified analysis indicated this scoring system showed better performance in elderly male patients with HBV infection and preoperative lower levels of creatinine, alpha-fetoprotein and platelet and higher level of albumin. Functional annotation of this risk model in high-risk patients revealed that pathways associated with cell cycle, cell migration and inflammation were significantly enriched. In summary, our constructed HCC-specific gene risk model demonstrated robustness and potentiality in predicting the prognosis of HCC patients, especially among elderly male patients with HBV infection and relatively better general conditions.

Topology Consistency of Disease-specific Differential Co-regulatory Networks

Background

Sets of differentially expressed genes often contain driver genes that induce disease processes. However, various methods for identifying differentially expressed genes yield quite different results. Thus, we investigated whether this affects the identification of key players in regulatory networks derived by downstream analysis from lists of differentially expressed genes.

Results

While the overlap between the sets of significant differentially expressed genes determined by DESeq, edgeR, voom and VST was only 26% in liver hepatocellular carcinoma and 28% in breast invasive carcinoma, the topologies of the regulatory networks constructed using the TFmiR webserver for the different sets of differentially expressed genes were found to be highly consistent with respect to hub-degree nodes, minimum dominating set and minimum connected dominating set.

Conclusions

The findings suggest that key genes identified in regulatory networks derived by systematic analysis of differentially expressed genes may be a more robust basis for understanding diseases processes than simply inspecting the lists of differentially expressed genes.

Circulating-Free DNA Analysis in Hepatocellular Carcinoma: A Promising Strategy to Improve Patients' Management and Therapy Outcomes

Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide, representing the third leading cause of cancer-related deaths. HCC genetic characterization at the tumor level has been recently completed, highlighting how a number of genes are frequently mutated in this pathology. Actionable somatic mutations found in a HCC tumor may represent targets for innovative drugs as well as prognostic/predictive markers. Nonetheless, surgical or bioptic tissue is hardly accessible in HCC and a single tumor sample is poorly representative of the tumor genetic heterogeneity. In this context, analyzing the circulating cell-free DNA (ccfDNA) and its tumor-derived fraction (ctDNA) could represent a promising strategy of liquid biopsy. Recent data suggested that the fluctuation of the ccfDNA quantity in the plasma of HCC patients could anticipate the detection of tumor progression. The presence of somatic mutations in p53 signaling, Wnt/β-catenin, chromatin remodeling, response to oxidative stress and telomerase maintenance pathways can also be studied in ccfDNA bypassing the need to perform a tumor biopsy. The profiling of ccfDNA fragmentation and the methylation pattern could further improve the clinical management of HCC patients. Performing a dynamic monitoring in the course of systemic treatment with sorafenib or regorafenib is a possible way to provide insights into the resistance mechanism, and to identify predictive and prognostic genetic alterations, helping the clinicians in terms of treatment decision making. This review will discuss the most recent literature data about the use of ccfDNA to monitor and improve the treatment of HCC.

Hepatitis B Virus X Protein-Induced RORγ Expression to Promote the Migration and Proliferation of Hepatocellular Carcinoma

Aberrant expression of RORγ is implicated in cancer development. A previous study identified that RORγ functions as a tumor promoter to drive hepatocellular carcinoma (HCC) growth. However, its expression and significance in HCC remain unclear. The central finding of this work is that RORγ was overexpressed in HCC due to its dysfunction of promoter methylation, and hepatitis B virus X protein (HBx) can remarkably induce the expression of RORγ in hepatocellular carcinoma through enhancing the transcriptional function. Also, the HBx-induced RORγ could promote the migration and proliferation of hepatoma cells. Hence, these results suggest that RORγ was an important regulator in HCC, and our finding provides new insights into the significance of RORγ in HCC.

Circulating Tumor DNA and Hepatocellular Carcinoma

There is a clear and unmet need for biomarkers in hepatocellular carcinoma (HCC). Circulating cell free deoxyribonucleic acid (cfDNA) is a fragmented DNA subtype, found in the blood circulation. Circulating tumor DNA (ctDNA) is the fraction of total cfDNA, which originates from the primary tumor or metastases in patients with cancer. Earlier studies reported that quantitative measurement cfDNA has diagnostic and prognostic role for HCC. More recently, improvement in next-generation sequencing technology and better understanding of genetic or epigenetic alteration of HCC have allowed comprehensive analysis of mutational and methylation landscape of ctDNA. Hotspot mutation panels and methylation panels have both shown promising performance. None of these tests have yet been validated in longitudinal cohorts for preclinical detection of HCC. In this article, the authors discuss the currently available ctDNA detection technologies, their diagnostic and prognostic performance in HCC, and future research directions.

SNAI1 Promotes the Cholangiocellular Phenotype, but not Epithelial-Mesenchymal Transition, in a Murine Hepatocellular Carcinoma Model

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has limited treatment options. Snail family transcriptional repressor 1 (SNAI1) is a master regulator of epithelial-mesenchymal transition (EMT) and has been implicated in HCC initiation and progression. However, the precise role of SNAI1 and the way it contributes to hepatocarcinogenesis have not been investigated in depth, especially in vivo. Here, we analyzed the functional relevance of SNAI1 in promoting hepatocarcinogenesis in the context of the AKT/c-Met-driven mouse liver tumor model (AKT/c-Met/SNAI1). Overexpression of SNAI1 did not accelerate AKT/c-Met-induced HCC development or induce metastasis in mice. Elevated SNAI1 expression rather led to the formation of cholangiocellular (CCA) lesions in the mouse liver, a phenotype that was paralleled by increased activation of Yap and Notch. Ablation of Yap strongly inhibited AKT/c-Met/SNAI-induced HCC and CCA development, whereas inhibition of the Notch pathway specifically blocked the CCA-like phenotype in mice. Intriguingly, overexpression of SNAI1 failed to induce EMT, indicated by strong E-cadherin expression and lack of vimentin expression by AKT/c-Met/SNAI tumor cells. SNAI1 mRNA levels strongly correlated with the expression of CCA markers, including SOX9, CK19, and EPCAM, but not with EMT markers such as E-CADHERIN and ZO-1, in human HCC samples. Overall, our findings suggest SNAI1 regulates the CCA-like phenotype in hepatocarcinogenesis via regulation of Yap and Notch. SIGNIFICANCE: These findings report a new function of SNAI1 to promote cholangiocellular transdifferentiation instead of epithelial-mesenchymal transition in hepatocellular carcinoma.

Dynamics of Genomic, Epigenomic, and Transcriptomic Aberrations during Stepwise Hepatocarcinogenesis

Hepatocellular carcinoma (HCC) undergoes a stepwise progression from liver cirrhosis to low-grade dysplastic nodule (LGDN), high-grade dysplastic nodule (HGDN), early HCC (eHCC), and progressed HCC (pHCC). Here, we profiled multilayered genomic, epigenomic, and transcriptomic aberrations in the stepwise hepatocarcinogenesis. Initial DNA methylation was observed in eHCC (e.g., DKK3, SALL3, and SOX1) while more extensive methylation was observed in pHCC. In addition, eHCCs showed an initial loss of DNA copy numbers of tumor suppressor genes in the 4q and 13q regions, thereby conferring survival benefits to cancer cells. Transcriptome analysis revealed that HGDNs expressed endoplasmic reticulum (ER) stress-related genes, while eHCC started to express oncogenes. Furthermore, integrative analysis indicated that expression of the serine peptidase inhibitor, Kazal type 1 (SPINK1), played a pivotal role in eHCC development. Significant demethylation of SPINK1 was observed in eHCC compared to HGDN. The study also demonstrated that ER stress may induce SPINK1 demethylation and expression in liver cancer cells. In conclusion, these results reveal the dynamics of multiomic aberrations during malignant conversion of liver cancer, thus providing novel pathobiological insights into hepatocarcinogenesis. SIGNIFICANCE: Multiomics profiling and integrative analyses of stepwise hepatocarcinogenesis reveal novel mechanistic and clinical insights into hepatocarcinogenesis.

Genomic profiling of well-differentiated hepatocellular neoplasms with diffuse glutamine synthetase staining reveals similar genetics across the adenoma to carcinoma spectrum

Well-differentiated hepatocellular neoplasms are currently classified in the World Health Organization scheme as hepatocellular adenoma or hepatocellular carcinoma. There is no recognized diagnostic category for atypical cases with borderline features, and we have designated these as atypical hepatocellular neoplasms. Diffuse glutamine synthetase staining is used as a surrogate marker to detect β-catenin activation, a well-recognized high risk feature in hepatocellular tumors. This study examined 27 well-differentiated hepatocellular neoplasms with diffuse glutamine synthetase staining, including 7 atypical hepatocellular neoplasms with no cytoarchitectural atypia, 6 atypical hepatocellular neoplasms with focal cytoarchitectural atypia, and 14 well-differentiated hepatocellular carcinomas. Capture-based next-generation sequencing was performed, and alterations in WNT pathway genes (CTNNB1, APC, AXIN1) were seen in 81% of cases (10/13 atypical hepatocellular neoplasms and 12/14 of hepatocellular carcinomas), while the molecular basis of diffuse glutamine synthetase staining was unclear in the remaining 19% of cases. Additional non-WNT pathway mutations (TP53, TSC1, DNMT3A, CREBBP) or copy number alterations were present in 56% of atypical hepatocellular neoplasms, with no significant difference in cases with or without focal cytoarchitectural atypia, supporting that all cases with β-catenin activation should be classified as atypical irrespective of atypia. Atypical hepatocellular neoplasm and hepatocellular carcinoma also demonstrated largely similar genomic profiles, but TERT promoter mutations were restricted to hepatocellular carcinoma (21%) and copy number alterations were more common in hepatocellular carcinoma (64 vs 31%). Mutational and copy number analysis may be helpful in characterization and risk stratification of atypical hepatocellular neoplasms when morphology and glutamine synthetase staining yield ambiguous results.

The mTORC2-Akt1 Cascade Is Crucial for c-Myc to Promote Hepatocarcinogenesis in Mice and Humans

Hepatocellular carcinoma (HCC) is a deadly form of liver cancer with limited treatment options. The c-Myc transcription factor is a pivotal player in hepatocarcinogenesis, but the mechanisms underlying c-Myc oncogenic activity in the liver remain poorly delineated. Mammalian target of rapamycin complex 2 (mTORC2) has been implicated in cancer by regulating multiple AGC kinases, especially AKT proteins. In the liver, AKT1 and AKT2 are widely expressed. While AKT2 is the major isoform downstream of activated phosphoinositide 3-kinase and loss of phosphatase and tensin homolog-induced HCC, the precise function of AKT1 in hepatocarcinogenesis is largely unknown. In the present study, we demonstrate that mTORC2 is activated in c-Myc-driven mouse HCC, leading to phosphorylation/activation of Akt1 but not Akt2. Ablation of Rictor inhibited c-Myc-induced HCC formation in vivo. Mechanistically, we discovered that loss of Akt1, but not Akt2, completely prevented c-Myc HCC formation in mice. Silencing of Rictor or Akt1 in c-Myc HCC cell lines inhibited phosphorylated forkhead box o1 expression and strongly suppressed cell growth in vitro. In human HCC samples, c-MYC activation is strongly correlated with phosphorylated AKT1 expression. Higher expression of RICTOR and AKT1, but not AKT2, is associated with poor survival of patients with HCC. In c-Myc mice, while rapamycin, an mTORC1 inhibitor, had limited efficacy at preventing c-Myc-driven HCC progression, the dual mTORC1 and mTORC2 inhibitor MLN0128 effectively promoted tumor regression by inducing apoptosis and necrosis. Conclusion: Our study indicates the functional contribution of mTORC2/Akt1 along c-Myc-induced hepatocarcinogenesis, with AKT1 and AKT2 having distinct roles in HCC development and progression; targeting both mTORC1 and mTORC2 may be required for effective treatment of human HCC displaying c-Myc amplification or overexpression.

Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas

OBJECTIVE

Hepatocellular carcinoma (HCC) is heterogeneous, especially in multifocal tumours, which decreases the efficacy of clinical treatments. Understanding tumour heterogeneity is critical when developing novel treatment strategies. However, a comprehensive investigation of tumour heterogeneity in HCC is lacking, and the available evidence regarding tumour heterogeneity has not led to improvements in clinical practice.

DESIGN

We harvested 42 samples from eight HCC patients and evaluated tumour heterogeneity using whole-exome sequencing, RNA sequencing, mass spectrometry-based proteomics and metabolomics, cytometry by time-of-flight, and single-cell analysis. Immunohistochemistry and quantitative polymerase chain reactions were performed to confirm the expression levels of genes. Three independent cohorts were further used to validate the findings.

RESULTS

Tumour heterogeneity is considerable with regard to the genomes, transcriptomes, proteomes, and metabolomes of lesions and tumours. The immune status of the HCC microenvironment was relatively less heterogenous. Targeting local immunity could be a suitable intervention with balanced precision and practicability. By clustering immune cells in the HCC microenvironment, we identified three distinctive HCC subtypes with immunocompetent, immunodeficient, and immunosuppressive features. We further revealed the specific metabolic features and cytokine/chemokine expression levels of the different subtypes. Determining the expression levels of CD45 and Foxp3 using immunohistochemistry facilitated the correct classification of HCC patients and the prediction of their prognosis.

CONCLUSION

There is comprehensive intratumoral and intertumoral heterogeneity in all dimensions of HCC. Based on the results, we propose a novel immunophenotypic classification of HCCs that facilitates prognostic prediction and may support decision making with regard to the choice of therapy.

RTNsurvival: an R/Bioconductor package for regulatory network survival analysis

MOTIVATION

Transcriptional networks are models that allow the biological state of cells or tumours to be described. Such networks consist of connected regulatory units known as regulons, each comprised of a regulator and its targets. Inferring a transcriptional network can be a helpful initial step in characterizing the different phenotypes within a cohort. While the network itself provides no information on molecular differences between samples, the per-sample state of each regulon, i.e. the regulon activity, can be used for describing subtypes in a cohort. Integrating regulon activities with clinical data and outcomes would extend this characterization of differences between subtypes.

RESULTS

We describe RTNsurvival, an R/Bioconductor package that calculates regulon activity profiles using transcriptional networks reconstructed by the RTN package, gene expression data, and a two-tailed Gene Set Enrichment Analysis. Given regulon activity profiles across a cohort, RTNsurvival can perform Kaplan-Meier analyses and Cox Proportional Hazards regressions, while also considering confounding variables. The Supplementary Information provides two case studies that use data from breast and liver cancer cohorts and features uni- and multivariate regulon survival analysis.

AVAILABILITY AND IMPLEMENTATION

RTNsurvival is written in the R language, and is available from the Bioconductor project at http://bioconductor.org/packages/RTNsurvival/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Jak-Stat Signaling Induced by Interleukin-6 Family Cytokines in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. It can be caused by chronic liver cell injury with resulting sustained inflammation, e.g., triggered by infections with hepatitis viruses B (HBV) and C (HCV). Death of hepatocytes leads to the activation of compensatory mechanisms, which can ultimately result in liver fibrosis and cirrhosis. Another common feature is the infiltration of the liver with inflammatory cells, which secrete cytokines and chemokines that act directly on the hepatocytes. Among several secreted proteins, members of the interleukin-6 (IL-6) family of cytokines have emerged as important regulatory proteins that might constitute an attractive target for therapeutic intervention. The IL-6-type cytokines activate multiple intracellular signaling pathways, and especially the Jak/STAT cascade has been shown to be crucial for HCC development. In this review, we give an overview about HCC pathogenesis with respect to IL-6-type cytokines and the Jak/STAT pathway. We highlight the role of mutations in genes encoding several proteins involved in the cytokine/Jak/STAT axis and summarize current knowledge about IL-6 family cytokines in this context. We further discuss possible anti-cytokine therapies for HCC patients in comparison to already established therapies.

A comparability study of immunohistochemical assays for PD-L1 expression in hepatocellular carcinoma

Programmed death ligand 1 (PD-L1) protein expression by immunohistochemistry is a promising biomarker for PD-1/PD-L1 blockade in hepatocellular carcinoma. There are a number of commercially available PD-L1 assays. Our study aimed to compare the analytical performance of different PD-L1 assays and evaluate the reliability of pathologists in PD-L1 scoring. Consecutive sections from tumor samples from 55 patients with surgically resected primary hepatocellular carcinoma were stained with four standardized PD-L1 assays (22C3, 28-8, SP142, and SP263). We also correlated the PD-L1 protein level by immunohistochemistry with the mRNA level of those genes associated with tumor immune microenvironment by the NanoString platform. Five pathologists independently assessed PD-L1 expression on tumor cells [tumor proportion score] together with tumor-infiltrating immune cells (combined positive score). The 22C3, 28-8, and SP263 assays had comparable sensitivity in detecting PD-L1 expression, whereas the SP142 assay was the least sensitive assay. The inter-assay agreement measured by intraclass correlation coefficients for the tumor proportion score and combined positive score were 0.646 and 0.780, respectively. The inter-rater agreement was good to excellent (the overall intraclass correlation coefficient for the tumor proportion score and combined positive score was 0.946 and 0.809, respectively). Pathologists were less reliable in scoring combined positive score than tumor proportion score, particularly when using the SP142 assay. Up to 18% of samples were misclassified by individual pathologists in comparison to the consensus score at the cutoff of combined positive score ≥ 1. The combined positive score by the 22C3 assay demonstrated the strongest correlation with immune-related gene mRNA signatures, closely followed by combined positive scores by the 28-8 and SP263 assays. In conclusion, the 22C3, 28-8, and SP263 assays are highly concordant in PD-L1 scoring and suggest the interchangeability of these three assays. Further improvement of the accuracy in assessing PD-L1 expression at a low cutoff is still necessary.

Hepatocellular carcinoma with non-B and non-C hepatitis origin: epidemiology in Japan and surgical outcome

During the last two decades, there has been a dramatic increase in so-called non-B non-C hepatocellular carcinoma (NBNC HCC) in Japan. Majority of NBNC HCC are considered as so-called metabolic HCC and some could be related to occult HBV infection. Although there have been some reports on histological features predominant in metabolic HCC, very few specific driver genes for NBNC HCC have been reported. Most of the NBNC HCC are found incidentally and are relatively large in size. Since liver function is generally normal or subnormal, such patients have a higher chance for undergoing curative surgery. Although there has been slightly conflicting long-term outcomes reported for NBNC HCC, slightly better outcomes may be expected compared to other etiologies after curative surgery. However, risk of recurrence depends on the background liver. NBNC HCC in cirrhotic patients have a persistently higher risk of tumor recurrence requiring a long-term postoperative surveillance. It would be safe to conclude at this moment that NBNC HCCs should be treated using the same surgical strategy as HCCs with viral origin, same operative indications and same follow-up protocol.

Hepatocellular carcinoma with non-B and non-C hepatitis origin: epidemiology in Japan and surgical outcome

During the last two decades, there has been a dramatic increase in so-called non-B non-C hepatocellular carcinoma (NBNC HCC) in Japan. Majority of NBNC HCC are considered as so-called metabolic HCC and some could be related to occult HBV infection. Although there have been some reports on histological features predominant in metabolic HCC, very few specific driver genes for NBNC HCC have been reported. Most of the NBNC HCC are found incidentally and are relatively large in size. Since liver function is generally normal or subnormal, such patients have a higher chance for undergoing curative surgery. Although there has been slightly conflicting long-term outcomes reported for NBNC HCC, slightly better outcomes may be expected compared to other etiologies after curative surgery. However, risk of recurrence depends on the background liver. NBNC HCC in cirrhotic patients have a persistently higher risk of tumor recurrence requiring a long-term postoperative surveillance. It would be safe to conclude at this moment that NBNC HCCs should be treated using the same surgical strategy as HCCs with viral origin, same operative indications and same follow-up protocol.

Molecular harvesting with electroporation for tissue profiling

Recent developments in personalized medicine are based on molecular measurement steps that guide personally adjusted medical decisions. A central approach to molecular profiling consists of measuring DNA, RNA, and/or proteins in tissue samples, most notably in and around tumors. This measurement yields molecular biomarkers that are potentially predictive of response and of tumor type. Current methods in cancer therapy mostly use tissue biopsy as the starting point of molecular profiling. Tissue biopsies involve a physical resection of a small tissue sample, leading to localized tissue injury, bleeding, inflammation and stress, as well as to an increased risk of metastasis. Here we developed a technology for harvesting biomolecules from tissues using electroporation. We show that tissue electroporation, achieved using a combination of high-voltage short pulses, 50 pulses 500 V cm-1, 30 µs, 1 Hz, with low-voltage long pulses 50 pulses 50 V cm-1, 10 ms, delivered at 1 Hz, allows for tissue-specific extraction of RNA and proteins. We specifically tested RNA and protein extraction from excised kidney and liver samples and from excised HepG2 tumors in mice. Further in vivo development of extraction methods based on electroporation can drive novel approaches to the molecular profiling of tumors and of tumor environment and to related diagnosis practices.

Expression levels and prognostic values of annexins in liver cancer

Annexins are a superfamily of calcium-dependent phospholipid-binding proteins that are implicated in a wide range of biological processes. The annexin superfamily comprises 13 members in humans (ANXAs), the majority of which are frequently dysregulated in cancer. However, the expression patterns and prognostic values of ANXAs in liver cancer are currently largely unknown. The present study aimed to analyze the expression levels of ANXAs and survival data in patients with liver cancer from the Oncomine, GEPIA, Kaplan-Meier plotter and cBioPortal for Cancer Genomics databases. The results demonstrated that ANXA1, A2, A3, A4 and A5 were upregulated, whereas ANXA10 was downregulated in liver cancer compared with normal liver tissues. The expression of ANXA10 was associated with pathological stage. High expression levels of ANXA2 and A5 were significantly associated with poor overall survival (OS) rate whereas ANXA7 and A10 were associated with increased OS. The prognostic values of ANXAs in liver cancer were determined based on sex and clinical stage, which revealed that ANXA2, A5, A7 and A10 were associated with OS in male, but not in female patients. In addition, the potential biological functions of ANXAs were identified by Gene Ontology functional annotation and Kyoto Encyclopedia of Genes Genomes pathway analysis; the results demonstrated that ANXAs may serve a role in liver cancer through the neuroactive ligand-receptor interaction pathway. In conclusion, the results of the present study suggested that ANXA1, A2, A3, A4, A5 and A10 may be potential therapeutic targets for liver cancer treatment, and that ANXA2, A5, A7 and A10 may be potential prognostic biomarkers of liver cancer.

Sex-biased differences in the correlation between epithelial-to-mesenchymal transition-associated genes in cancer cell lines

There is a wide disparity in the incidence, malignancy and mortality of different types of cancer between each sex. The sex-specificity of cancer seems to be dependent on the type of cancer. Cancer incidence and mortality have been demonstrated as sex-specific in a number of different types of cancer, such as liver cancer, whereas sex-specificity is not noticeable in certain other types of cancer, including colon and lung cancer. The present study aimed to elucidate the molecular basis for sex-biased gene expression in cancer. The mRNA expression of the epithelial-to-mesenchymal transition-associated genes was investigated, including E-cadherin (also termed CDH1), vimentin (VIM), discoidin domain receptor 1 (DDR1) and zinc finger E-box binding homeobox 1 (ZEB1) in female- and male-derived cancer cell lines by reverse transcription (RT)-PCR and the Broad-Novartis Cancer Cell Line Encyclopedia (CCLE) database analysis. A negative correlation was observed between DDR1 and ZEB1 only in the female-derived cancer cell lines via RT-PCR analysis. A negative correlation between DDR1 index (defined by the logarithmic value of DDR1 divided by ZEB1, based on the mRNA data from the RT-PCR analysis) and an invasive phenotype was observed in cancer cell lines in a sex-specific manner. Analysis of the CCLE database demonstrated that DDR1 and ZEB1, which are already known to be sex-biased, were negatively correlated in female-derived liver cancer cell lines, but not in male-derived liver cancer cell lines. In contrast, cell lines of colon and lung cancer did not reveal any sex-dependent difference in the correlation between DDR1 and ZEB1. Kaplan-Meier survival curves using the transcriptomic datasets such as Gene Expression Omnibus, European Genome-phenome Archiva and The Cancer Genome Atlas databases suggested a sex-biased difference in the correlation between DDR1 expression pattern and overall survival in patients with liver cancer. The results of the present study indicate that sex factors may affect the regulation of gene expression, contributing to the sex-biased progression of the different types of cancer, particularly liver cancer. Overall, these findings suggest that analyses of the correlation between DDR1 and ZEB1 may prove useful when investigating sex-biased cancers.

Genetic profiling using plasma-derived cell-free DNA in therapy-naïve hepatocellular carcinoma patients: a pilot study

Background

Hepatocellular carcinomas (HCCs) are not routinely biopsied, resulting in a lack of tumor materials for molecular profiling. Here we sought to determine whether plasma-derived cell-free DNA (cfDNA) captures the genetic alterations of HCC in patients who have not undergone systemic therapy.

Patients and methods

Frozen biopsies from the primary tumor and plasma were synchronously collected from 30 prospectively recruited, systemic treatment-naïve HCC patients. Deep sequencing of the DNA from the biopsies, plasma-derived cfDNA and matched germline was carried out using a panel targeting 46 coding and non-coding genes frequently altered in HCCs.

Results

In 26/30 patients, at least one somatic mutation was detected in biopsy and/or cfDNA. Somatic mutations in HCC-associated genes were present in the cfDNA of 63% (19/30) of the patients and could be detected 'de novo' without prior knowledge of the mutations present in the biopsy in 27% (8/30) of the patients. Mutational load and the variant allele fraction of the mutations detected in the cfDNA positively correlated with tumor size and Edmondson grade. Crucially, among the seven patients in whom the largest tumor was ≥5 cm or was associated with metastasis, at least one mutation was detected 'de novo' in the cfDNA of 86% (6/7) of the cases. In these patients, cfDNA and tumor DNA captured 87% (80/92) and 95% (87/92) of the mutations, suggesting that cfDNA and tumor DNA captured similar proportions of somatic mutations.

Conclusion

In patients with high disease burden, the use of cfDNA for genetic profiling when biopsy is unavailable may be feasible. Our results support further investigations into the clinical utility of cfDNA in a larger cohort of patients.

Genomic Perspective on Mouse Liver Cancer Models

Selecting the most appropriate mouse model that best recapitulates human hepatocellular carcinoma (HCC) allows translation of preclinical mouse studies into clinical studies. In the era of cancer genomics, comprehensive and integrative analysis of the human HCC genome has allowed categorization of HCC according to molecular subtypes. Despite the variety of mouse models that are available for preclinical research, there is a lack of evidence for mouse models that closely resemble human HCC. Therefore, it is necessary to identify the accurate mouse models that represent human HCC based on molecular subtype as well as histologic aggressiveness. In this review, we summarize the mouse models integrated with human HCC genomic data to provide information regarding the models that recapitulates the distinct aspect of HCC biology and prognosis based on molecular subtypes.

Mutational Landscape of the BAP1 Locus Reveals an Intrinsic Control to Regulate the miRNA Network and the Binding of Protein Complexes in Uveal Melanoma

The BAP1 (BRCA1-associated protein 1) gene is associated with a variety of human cancers. With its gene product being a nuclear ubiquitin carboxy-terminal hydrolase with deubiquitinase activity, BAP1 acts as a tumor suppressor gene with potential pleiotropic effects in multiple tumor types. Herein, we focused specifically on uveal melanoma (UM) in which BAP1 mutations are associated with a metastasizing phenotype and decreased survival rates. We identified the ubiquitin carboxyl hydrolase (UCH) domain as a major hotspot region for the pathogenic mutations with a high evolutionary action (EA) score. This also includes the mutations at conserved catalytic sites and the ones overlapping with the phosphorylation residues. Computational protein interaction studies revealed that distant BAP1-associated protein complexes (FOXK2, ASXL1, BARD1, BRCA1) could be directly impacted by this mutation paradigm. We also described the conformational transition related to BAP1-BRCA-BARD1 complex, which may pose critical implications for mutations, especially at the docking interfaces of these three proteins. The mutations affect - independent of being somatic or germline - the binding affinity of miRNAs embedded within the BAP1 locus, thereby altering the unique regulatory network. Apart from UM, BAP1 gene expression and survival associations were found to be predictive for the prognosis in several (n = 29) other cancer types. Herein, we suggest that although BAP1 is conceptually a driver gene in UM, it might contribute through its interaction partners and its regulatory miRNA network to various aspects of cancer. Taken together, these findings will pave the way to evaluate BAP1 in a variety of other human cancers with a shared mutational spectrum.

A machine learning approach for somatic mutation discovery

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. To address this issue, we developed a somatic mutation discovery approach based on machine learning that outperformed existing methods in identifying experimentally validated tumor alterations (sensitivity of 97% versus 90 to 99%; positive predictive value of 98% versus 34 to 92%). Analysis of paired tumor-normal exome data from 1368 TCGA (The Cancer Genome Atlas) samples using this method revealed concordance for 74% of mutation calls but also identified likely false-positive and false-negative changes in TCGA data, including in clinically actionable genes. Determination of high-quality somatic mutation calls improved tumor mutation load-based predictions of clinical outcome for melanoma and lung cancer patients previously treated with immune checkpoint inhibitors. Integration of high-quality machine learning mutation detection in clinical next-generation sequencing (NGS) analyses increased the accuracy of test results compared to other clinical sequencing analyses. These analyses provide an approach for improved identification of tumor-specific mutations and have important implications for research and clinical management of cancer patients.

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.

Molecular Profiling of Hepatocellular Carcinoma Using Circulating Cell-Free DNA

PURPOSE

Molecular profiling has been used to select patients for targeted therapy and determine prognosis. Noninvasive strategies are critical to hepatocellular carcinoma (HCC) given the challenge of obtaining liver tissue biopsies.

EXPERIMENTAL DESIGN

We analyzed blood samples from 206 patients with HCC using comprehensive genomic testing (Guardant Health) of circulating tumor DNA (ctDNA).

RESULTS

A total of 153/206 (74.3%) were men; median age, 62 years (range, 18-91 years). A total of 181/206 patients had ≥1 alteration. The total number of alterations was 680 (nonunique); median number of alterations/patient was three (range, 1-13); median mutant allele frequency (% cfDNA), 0.49% (range, 0.06%-55.03%). TP53 was the common altered gene [>120 alterations (non-unique)] followed by EGFR, MET, ARID1A, MYC, NF1, BRAF, and ERBB2 [20-38 alterations (nonunique)/gene]. Of the patients with alterations, 56.9% (103/181) had ≥1 actionable alterations, most commonly in MYC, EGFR, ERBB2, BRAF, CCNE1, MET, PIK3CA, ARID1A, CDK6, and KRAS. In these genes, amplifications occurred more frequently than mutations. Hepatitis B (HBV)-positive patients were more likely to have ERBB2 alterations, 35.7% (5/14) versus 8.8% HBV-negative (P = 0.04).

CONCLUSIONS

This study represents the first large-scale analysis of blood-derived ctDNA in HCC in United States. The genomic distinction based on HCC risk factors and the high percentage of potentially actionable genomic alterations suggests potential clinical utility for this technology.

Tumor Cell Biodiversity Drives Microenvironmental Reprogramming in Liver Cancer

Cellular diversity in tumors is a key factor for therapeutic failures and lethal outcomes of solid malignancies. Here, we determined the single-cell transcriptomic landscape of liver cancer biospecimens from 19 patients. We found varying degrees of heterogeneity in malignant cells within and between tumors and diverse landscapes of tumor microenvironment (TME). Strikingly, tumors with higher transcriptomic diversity were associated with patient's worse overall survival. We found a link between hypoxia-dependent vascular endothelial growth factor expression in tumor diversity and TME polarization. Moreover, T cells from higher heterogeneous tumors showed lower cytolytic activities. Consistent results were found using bulk genomic and transcriptomic profiles of 765 liver tumors. Our results offer insight into the diverse ecosystem of liver cancer and its impact on patient prognosis.

KIFC1 promotes the proliferation of hepatocellular carcinoma in vitro and in vivo

Hepatocellular carcinoma (HCC) is a common type of malignant tumor worldwide with a high mortality rate. In the past 20 years, the morbidity rate of HCC has increased. Progress has been made in the clinical diagnosis and therapy for HCC. However, due to the high heterogeneity and metastasis targeted therapy for HCC exhibits great promise, and novel therapeutic targets for HCC are urgently required. Kinesin family member C1 (KIFC1) is a member of the kinesin superfamily of proteins. Previous studies have indicated a potential association between KIFC1 and cancer progression. However, the potential role of KIFC1 in the development of HCC remains unclear. The present study aimed to explore the function of KIFC1 in HCC. Immunohistochemical (IHC) assays were performed to explore the KIF15 expression levels in 74 samples of HCC and corresponding non-tumor tissues. The potential association between KIF15 expression levels and clinical features was analyzed, and the effects of KIF15 on cell proliferation of HCC were detected by colony formation and MTT assays. In addition, the proliferation-related proteins Ki67 and PCNA were detected by western blotting. The possible effects of KIF15 on tumor growth were measured in mice. The results demonstrated that a high expression level of KIFC1 was associated with poor prognosis of HCC. Further results indicated that KIFC1 promoted cell proliferation of HCC in vitro. In addition, knockdown of KIFC1 suppressed tumor formation and growth in mice. Therefore, these results provide a potential therapeutic target for the treatment of HCC.

Tracking Dynamics of Spontaneous Tumors in Mice Using Photon-Counting Computed Tomography

Computed tomography is a powerful medical imaging modality for longitudinal studies in cancer to follow neoplasia progression and evaluate anticancer therapies. Here, we report the generation of a photon-counting micro-computed tomography (PC-CT) method based on hybrid pixel detectors with enhanced sensitivity and precision of tumor imaging. We then applied PC-CT for longitudinal imaging in a clinically relevant liver cancer model, the Alb-R26^Met mice, and found a remarkable heterogeneity in the dynamics for tumors at the initiation phases. Instead, the growth curve of evolving tumors exhibited a comparable exponential growth, with a constant doubling time. Furthermore, longitudinal PC-CT imaging in mice treated with a combination of MEK and BCL-XL inhibitors revealed a drastic tumor regression accompanied by a striking remodeling of macrophages in the tumor microenvironment. Thus, PC-CT is a powerful system to detect cancer initiation and progression, and to monitor its evolution during treatment.

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Development of photon-counting micro-computed tomography (PC-CT) with hybrid pixels

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PC-CT allows longitudinal imaging of tumor dynamics in mouse cancer models

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RTK-driven tumors are heterogeneous at onset, but grow steadily during progression

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MEK + BCL-XL targeting leads to tumor regression and microenvironment remodeling

The U1 spliceosomal RNA is recurrently mutated in multiple cancers

Cancers are caused by genomic alterations known as drivers. Hundreds of drivers in coding genes are known but, to date, only a handful of noncoding drivers have been discovered-despite intensive searching^1,2. Attention has recently shifted to the role of altered RNA splicing in cancer; driver mutations that lead to transcriptome-wide aberrant splicing have been identified in multiple types of cancer, although these mutations have only been found in protein-coding splicing factors such as splicing factor 3b subunit 1 (SF3B1)^3-6. By contrast, cancer-related alterations in the noncoding component of the spliceosome-a series of small nuclear RNAs (snRNAs)-have barely been studied, owing to the combined challenges of characterizing noncoding cancer drivers and the repetitive nature of snRNA genes^1,7,8. Here we report a highly recurrent A>C somatic mutation at the third base of U1 snRNA in several types of tumour. The primary function of U1 snRNA is to recognize the 5' splice site via base-pairing. This mutation changes the preferential A-U base-pairing between U1 snRNA and the 5' splice site to C-G base-pairing, and thus creates novel splice junctions and alters the splicing pattern of multiple genes-including known drivers of cancer. Clinically, the A>C mutation is associated with heavy alcohol use in patients with hepatocellular carcinoma, and with the aggressive subtype of chronic lymphocytic leukaemia with unmutated immunoglobulin heavy-chain variable regions. The mutation in U1 snRNA also independently confers an adverse prognosis to patients with chronic lymphocytic leukaemia. Our study demonstrates a noncoding driver in spliceosomal RNAs, reveals a mechanism of aberrant splicing in cancer and may represent a new target for treatment. Our findings also suggest that driver discovery should be extended to a wider range of genomic regions.

Clinicopathological correlation of immune response in human cancers

Background:

The clinicopathologic association of tumor immune response is largely unknown. We systematically investigated this matter in human cancers.

Results:

Different cancer types exhibited distinct immune gene profiling. Four cancer types exhibited a significant and positive correlation of immune response with patient age. Significant but inconsistent correlation of immune response was observed with gender, surgical stage, and TNM stage in a small number of cancer types. In contrast, the histological grade appears to have much stronger and more consistent association with immune response as compared to the other clinicopathologic factors. Specifically, patients with high grade had significantly higher immune responses than those with low grade in 5 out of 12 analyzed cancer types. In addition, both histological and molecular classifications had a significant and strong association with tumor immune response.

Methods:

t-distributed stochastic neighbor embedding was used to assess similarity of immune gene profiling in human cancers. The Mann-Whitney or Kruskal-Wallis test was, respectively, used to compare the tumor immune response in two or more groups that were stratified by patient clinicopathological characteristics, such as gender, grade, stage (including surgical and TNM stage), histology, and molecular subtypes. Spearman correlation with student’s t-test was used to examine the association of patient age with immune response. Multiple tests with the Benjamini-Hochberg correction also were performed.

Conclusions:

Tumor grade should be taken into account in selection of patient candidates for immunotherapy. Prospective verification is needed before use of the findings for clinical practice.

Inducing and exploiting vulnerabilities for the treatment of liver cancer

Liver cancer remains difficult to treat due to a paucity of drugs that target critical dependencies^1,2 and broad spectrum kinase inhibitors like sorafenib provide only modest benefit to hepatocellular carcinoma (HCC) patients³. Induction of senescence may represent a promising strategy for the treatment of cancer, especially when such pro-senescence therapy is combined with a second drug that selectively eliminates senescent cancer cells (senolysis)^4,5. Through a kinome-focused genetic screen, we report here that pharmacological inhibition of the DNA replication kinase CDC7 induces senescence selectively in TP53 mutant liver cancer cells. A follow-up chemical screen identified the anti-depressant sertraline as an agent that kills HCC cells rendered senescent by CDC7 inhibition. Sertraline supressed mTOR signalling, and selective drugs targeting this pathway were highly effective in causing apoptotic cell death of CDC7 inhibitor-treated HCC cells. Mechanistically, we report that the feedback re-activation of mTOR signalling following its inhibition⁶ is blocked in CDC7-inhibitor treated cells, leading to sustained mTOR inhibition and cell death. Using multiple in vivo liver cancer models, we show that combination of CDC7 and mTOR inhibitors results in dramatic tumour growth inhibition. More generally, our data indicate that exploiting an induced vulnerability could be an effective treatment of liver cancer.

ESM1 as a Marker of Macrotrabecular-Massive Hepatocellular Carcinoma

PURPOSE

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a novel morphological subtype of HCC associated with early relapse after resection or percutaneous ablation, independently of classical clinical and radiological prognostic factors. The aim of the present study was to identify immunohistochemical markers of MTM-HCC, to ease its diagnosis and implementation into clinical practice.

EXPERIMENTAL DESIGN

To identify potential biomarkers of MTM-HCC, we first analyzed gene expression profiling data from The Cancer Genome Atlas study and further selected two candidate biomarkers. Performance of both biomarkers for diagnosis of MTM-HCC was further tested by immunohistochemistry in two independent series of 67 and 132 HCC biopsy samples.

RESULTS

Analysis of RNA sequencing data showed that MTM-HCC was characterized by a high expression of neoangiogenesis-related genes. Two candidate biomarkers, Endothelial-Specific Molecule 1 (ESM1) and Carbonic Anhydrase IX (CAIX), were selected. In the discovery series, sensitivity and specificity of ESM1 expression by stromal endothelial cells for the detection of MTM-HCC were 97% (28/29), and 92% (35/38), respectively. Sensitivity and specificity of CAIX were 48% (14/29) and 89% (34/38). In the validation set, sensitivity and specificity of ESM1 for the identification of MTM-HCC were 93% (14/15) and 91% (107/117), respectively. Interobserver agreement for ESM1 assessment was good in both series (Cohen Kappa 0.77 and 0.76).

CONCLUSIONS

Using a molecular-driven selection of biomarkers, we identified ESM1 as a reliable microenvironment immunohistochemical marker of MTM-HCC. The results represent a step toward the implementation of HCC morpho-molecular subtyping into clinical practice.

A global view of hepatocellular carcinoma: trends, risk, prevention and management

Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer-related death worldwide. Risk factors for HCC include chronic hepatitis B and hepatitis C, alcohol addiction, metabolic liver disease (particularly nonalcoholic fatty liver disease) and exposure to dietary toxins such as aflatoxins and aristolochic acid. All these risk factors are potentially preventable, highlighting the considerable potential of risk prevention for decreasing the global burden of HCC. HCC surveillance and early detection increase the chance of potentially curative treatment; however, HCC surveillance is substantially underutilized, even in countries with sufficient medical resources. Early-stage HCC can be treated curatively by local ablation, surgical resection or liver transplantation. Treatment selection depends on tumour characteristics, the severity of underlying liver dysfunction, age, other medical comorbidities, and available medical resources and local expertise. Catheter-based locoregional treatment is used in patients with intermediate-stage cancer. Kinase and immune checkpoint inhibitors have been shown to be effective treatment options in patients with advanced-stage HCC. Together, rational deployment of prevention, attainment of global goals for viral hepatitis eradication, and improvements in HCC surveillance and therapy hold promise for achieving a substantial reduction in the worldwide HCC burden within the next few decades.

Somatic mutations and clonal dynamics in healthy and cirrhotic human liver

The most common causes of chronic liver disease are excess alcohol intake, viral hepatitis and non-alcoholic fatty liver disease, with the clinical spectrum ranging in severity from hepatic inflammation to cirrhosis, liver failure or hepatocellular carcinoma (HCC). The genome of HCC exhibits diverse mutational signatures, resulting in recurrent mutations across more than 30 cancer genes1-7. Stem cells from normal livers have a low mutational burden and limited diversity of signatures8, which suggests that the complexity of HCC arises during the progression to chronic liver disease and subsequent malignant transformation. Here, by sequencing whole genomes of 482 microdissections of 100-500 hepatocytes from 5 normal and 9 cirrhotic livers, we show that cirrhotic liver has a higher mutational burden than normal liver. Although rare in normal hepatocytes, structural variants, including chromothripsis, were prominent in cirrhosis. Driver mutations, such as point mutations and structural variants, affected 1-5% of clones. Clonal expansions of millimetres in diameter occurred in cirrhosis, with clones sequestered by the bands of fibrosis that surround regenerative nodules. Some mutational signatures were universal and equally active in both non-malignant hepatocytes and HCCs; some were substantially more active in HCCs than chronic liver disease; and others-arising from exogenous exposures-were present in a subset of patients. The activity of exogenous signatures between adjacent cirrhotic nodules varied by up to tenfold within each patient, as a result of clone-specific and microenvironmental forces. Synchronous HCCs exhibited the same mutational signatures as background cirrhotic liver, but with higher burden. Somatic mutations chronicle the exposures, toxicity, regeneration and clonal structure of liver tissue as it progresses from health to disease.

A three-long non-coding RNA-expression-based risk score system can better predict both overall and recurrence-free survival in patients with small hepatocellular carcinoma

Growing evidence indicates that long non-coding RNAs (lncRNAs) may be potential biomarkers and therapeutic targets for many disease conditions, including cancer. In this study, we constructed a risk score system of three lncRNAs (LOC101927051, LINC00667 and NSUN5P2) for predicting the prognosis of small hepatocellular carcinoma (sHCC) (maximum tumor diameter ≤5 cm). The prognostic value of this sHCC risk model was confirmed in TCGA HCC samples (TNM stage I and II). Stratified survival analysis revealed that the suitable patient groups of the sHCC lncRNA-signature included HBV-infected and cirrhotic patients with better physical conditions yet lower levels of albumin and higher levels of alpha-fetoprotein preoperatively. Besides, Asian patients with no family history of HCC or history of alcohol consumption can be predicted more precisely. Molecular functional analysis indicated that PYK2 pathway was significantly enriched in the high-risk patients. Pathway enrichment analysis indicated that the two lncRNAs (LINC00667 and NSUN5P2) associated with poor prognosis were closely related to cell cycle. The nomogram based on the lncRNA-signature for RFS prediction in sHCC patients exhibited good performance in recurrence risk stratification. In conclusion, we identified a novel three-lncRNA-expression-based risk model for predicting the prognosis of sHCC.

Multilevel regulation of RUVBL2 expression predicts poor prognosis in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the second-most lethal cancer worldwide with a complex pathogenesis. RuvB-like 2 (RUVBL2) was previously found to contribute to hepatocarcinogenesis. However, its expression, regulation and clinical significance have not been systematically evaluated in a large number of clinical samples.

Methods

Here, we performed a comprehensive analysis of RUVBL2 based on multiple datasets from 371 liver cancer patients of The Cancer Genome Atlas (TCGA) and on immunohistochemical staining in 153 subjects. In addition, the aberrant signaling pathways caused by RUVBL2 overexpression were investigated.

Results

We demonstrated that promoter hypomethylation, copy number gain, MYC amplification and CTNNB1 mutation were all responsible for RUVBL2 overexpression in HCC. High levels of RUVBL2 mRNA were associated with shorter recurrence-free survival time (RFS) but not overall survival time (OS). Furthermore, RUVBL2 protein was overexpressed in the nucleus and cytoplasm of HCC samples. Univariate and multivariate survival analyses showed that strong nuclear and cytoplasmic staining of RUVBL2 independently predicted worse OS and RFS with a 2.03-fold and a 1.71-fold increase in the hazard ratio, respectively. High levels of RUVBL2 promoted carcinogenesis through the heat shock protein 90 (HSP90)-Cell Division Cycle 37 (CDC37), AKT serine/threonine kinase (AKT) and mitogen-activated protein kinase (ERK/MAPK) pathways.

Conclusion

The deregulation of RUVBL2 in HCC is influenced at the genomic, epigenetic and transcriptional levels. Our findings highlight the potential roles of RUVBL2 as a promising prognostic marker as well as a therapeutic target for HCC.

Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.

Systematic profiling of a novel prognostic alternative splicing signature in hepatocellular carcinoma

Alternative splicing (AS) is a pervasive and vital mechanism involved in the progression of cancer by expanding genomic encoding capacity and increasing protein complexity. However, the systematic analysis of AS in hepatocellular carcinoma (HCC) is lacking and urgently required. In the present study, genome‑wide AS events with corresponding clinical information were profiled in 290 patients with HCC from the Cancer Genome Atlas and SpliceSeq software. Functional enrichment analyses revealed the pivotal biological process of AS regulation. Univariate Cox regression analyses were performed, followed by stepwise forward multivariate analysis to develop the prognostic signatures. Spearman's correlation analyses were also used to construct potential regulatory network between the AS events and aberrant splicing factors. A total of 34,163 AS events were detected, among which 1,805 AS events from 1,314 parent genes were significantly associated with the overall survival (OS) of patients with HCC, and their parent genes serve crucial roles in HCC‑related oncogenic processes, including the p53 signaling pathway, AMPK signaling pathway and HIF‑1 signaling pathway. A prognostic AS signature was established that was found to be an independent prognostic factor for OS in stratified cohorts, harboring a noteworthy ability to distinguish between the distinct prognoses of patients with HCC (high‑risk vs. low‑risk, 827 vs. 3,125 days, P<2e‑16). Time‑dependent receiver‑-operator characteristic curves confirmed its robustness and clinical efficacy, with the area under the curves maintained >0.9 for short‑term and long‑term prognosis prediction. The splicing correlation network suggested a trend in the interactions between splicing factors and prognostic AS events, further revealing the underlying mechanism of AS in the oncogenesis of HCC. In conclusion, the present study provides a comprehensive portrait of global splicing alterations involved in the progression and HCC in addition to valuable prognostic factors for patients, which may represent as underappreciated hallmark and provide novel clues of therapeutic targets in HCC.

Uveal melanoma: Towards a molecular understanding

Uveal melanoma is an aggressive malignancy that originates from melanocytes in the eye. Even if the primary tumor has been successfully treated with radiation or surgery, up to half of all UM patients will eventually develop metastatic disease. Despite the common origin from neural crest-derived cells, uveal and cutaneous melanoma have few overlapping genetic signatures and uveal melanoma has been shown to have a lower mutational burden. As a consequence, many therapies that have proven effective in cutaneous melanoma -such as immunotherapy- have little or no success in uveal melanoma. Several independent studies have recently identified the underlying genetic aberrancies in uveal melanoma, which allow improved tumor classification and prognostication of metastatic disease. In most cases, activating mutations in the Gα11/Q pathway drive uveal melanoma oncogenesis, whereas mutations in the BAP1, SF3B1 or EIF1AX genes predict progression towards metastasis. Intriguingly, the composition of chromosomal anomalies of chromosome 3, 6 and 8, shown to correlate with an adverse outcome, are distinctive in the BAP1^mut, SF3B1^mut and EIF1AX^mut uveal melanoma subtypes. Expression profiling and epigenetic studies underline this subdivision in high-, intermediate-, or low-metastatic risk subgroups and suggest a different approach in the future towards prevention and/or treatment based on the specific mutation present in the tumor of the patients. In this review we discuss the current knowledge of the underlying genetic events that lead to uveal melanoma, their implication for the disease course and prognosis, as well as the therapeutic possibilities that arise from targeting these different aberrant pathways.

Genome-wide discovery and validation of diagnostic DNA methylation-based biomarkers for hepatocellular cancer detection in circulating cell free DNA

Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is growing in incidence but treatment options remain limited, particularly for late stage disease. As liver cirrhosis is the principal risk state for HCC development, markers to detect early HCC within this patient population are urgently needed. Perturbation of epigenetic marks, such as DNA methylation (5mC), is a hallmark of human cancers, including HCC. Identification of regions with consistently altered 5mC levels in circulating cell free DNA (cfDNA) during progression from cirrhosis to HCC could therefore serve as markers for development of minimally-invasive screens of early HCC diagnosis and surveillance. Methods: To discover DNA methylation derived biomarkers of HCC in the background of liver cirrhosis, we profiled genome-wide 5mC landscapes in patient cfDNA using the Infinium HumanMethylation450k BeadChip Array. We further linked these findings to primary tissue data available from TCGA and other public sources. Using biological and statistical frameworks, we selected CpGs that robustly differentiated cirrhosis from HCC in primary tissue and cfDNA followed by validation in an additional independent cohort. Results: We identified CpGs that segregate patients with cirrhosis, from patients with HCC within a cirrhotic liver background, through genome-wide analysis of cfDNA 5mC landscapes. Lasso regression analysis pinpointed a panel of probes in our discovery cohort that were validated in two independent datasets. A panel of five CpGs (cg04645914, cg06215569, cg23663760, cg13781744, and cg07610777) yielded area under the receiver operating characteristic (AUROC) curves of 0.9525, 0.9714, and 0.9528 in cfDNA discovery and tissue validation cohorts 1 and 2, respectively. Validation of a 5-marker panel created from combining hypermethylated and hypomethylated CpGs in an independent cfDNA set by bisulfite pyrosequencing yielded an AUROC of 0.956, compared to the discovery AUROC of 0.996. Conclusion: Our finding that 5mC markers derived from primary tissue did not perform well in cfDNA, compared to those identified directly from cfDNA, reveals potential advantages of starting with cfDNA to discover high performing markers for liquid biopsy development.

DNA methylation-driven genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma

In this study, we performed a comprehensively analysis of gene expression and DNA methylation data to establish diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).

Methods: We collected gene expression and DNA methylation datasets for over 1,200 clinical samples. Integrated analyses of RNA-sequencing and DNA methylation data were performed to identify DNA methylation-driven genes. These genes were utilized in univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to build a prognostic model. Recurrence and diagnostic models for HCC were also constructed using the same genes.

Results: A total of 123 DNA methylation-driven genes were identified. Two of these genes (SPP1 and LCAT) were chosen to construct the prognostic model. The high-risk group showed a markedly unfavorable prognosis compared to the low-risk group in both training (HR = 2.81; P < 0.001) and validation (HR = 3.06; P < 0.001) datasets. Multivariate Cox regression analysis indicated the prognostic model to be an independent predictor of prognosis (P < 0.05). Also, the recurrence model successfully distinguished the HCC recurrence rate between the high-risk and low-risk groups in both training (HR = 2.22; P < 0.001) and validation (HR = 2; P < 0.01) datasets. The two diagnostic models provided high accuracy for distinguishing HCC from normal samples and dysplastic nodules in the training and validation datasets, respectively.

Conclusions: We identified and validated prognostic, recurrence, and diagnostic models that were constructed using two DNA methylation-driven genes in HCC. The results obtained by integrating multidimensional genomic data offer novel research directions for HCC biomarkers and new possibilities for individualized treatment of patients with HCC.

Squalene epoxidase drives NAFLD-induced hepatocellular carcinoma and is a pharmaceutical target

Nonalcoholic fatty liver disease (NAFLD)-induced hepatocellular carcinoma (HCC) is an emerging malignancy in the developed world; however, mechanisms that contribute to its formation are largely unknown, and targeted therapy is currently not available. Our RNA sequencing analysis of NAFLD-HCC samples revealed squalene epoxidase (SQLE) as the top outlier metabolic gene overexpressed in NAFLD-HCC patients. Hepatocyte-specific Sqle transgenic expression in mice accelerated the development of high-fat, high-cholesterol diet-induced HCC. SQLE exerts its oncogenic effect via its metabolites, cholesteryl ester and nicotinamide adenine dinucleotide phosphate (NADP⁺). Increased SQLE expression promotes the biosynthesis of cholesteryl ester, which induces NAFLD-HCC cell growth. SQLE increased the NADP⁺/NADPH (reduced form of NADP⁺) ratio, which triggered a cascade of events involving oxidative stress-induced DNA methyltransferase 3A (DNMT3A) expression, DNMT3A-mediated epigenetic silencing of PTEN, and activation of AKT-mTOR (mammalian target of rapamycin). In human NAFLD-HCC and HCC, SQLE is overexpressed and its expression is associated with poor patient outcomes. Terbinafine, a U.S. Food and Drug Administration-approved antifungal drug targeting SQLE, markedly inhibited SQLE-induced NAFLD-HCC cell growth in NAFLD-HCC and HCC cells and attenuated tumor development in xenograft models and in Sqle transgenic mice. Suppression of tumor growth by terbinafine is associated with decreased cholesteryl ester concentrations, restoration of PTEN expression, and inhibition of AKT-mTOR, consistent with blockade of SQLE function. Collectively, we established SQLE as an oncogene in NAFLD-HCC and propose that repurposing SQLE inhibitors may be a promising approach for the prevention and treatment of NAFLD-HCC.

Identifying functions and prognostic biomarkers of network motifs marked by diverse chromatin states in human cell lines

Epigenetic modifications play critical roles in modulating gene expression, yet their roles in regulatory networks in human cell lines remain poorly characterized. We integrated multiomics data to construct directed regulatory networks with nodes and edges labeled with chromatin states in human cell lines. We observed extensive association of diverse chromatin states and network motifs. The gene expression analysis showed that diverse chromatin states of coherent type-1 feedforward loop (C1-FFL) and incoherent type-1 feedforward loops (I1-FFL) contributed to the dynamic expression patterns of targets. Notably, diverse chromatin state compositions could help C1- or I1-FFL to control a large number of distinct biological functions in human cell lines, such as four different types of chromatin state compositions cooperating with K562-associated C1-FFLs controlling “regulation of cytokinesis,” “G1/S transition of mitotic cell cycle,” “DNA recombination,” and “telomere maintenance,” respectively. Remarkably, we identified six chromatin state-marked C1-FFL instances (HCFC1-NFYA-ABL1, THAP1-USF1-BRCA2, ZNF263-USF1-UBA52, MYC-ATF1-UBA52, ELK1-EGR1-CCT4, and YY1-EGR1-INO80C) could act as prognostic biomarkers of acute myelogenous leukemia though influencing cancer-related biological functions, such as cell proliferation, telomere maintenance, and DNA recombination. Our results will provide novel insight for better understanding of chromatin state-mediated gene regulation and facilitate the identification of novel diagnostic and therapeutic biomarkers of human cancers.

Comprehensive investigation of alternative splicing and development of a prognostic risk score for prostate cancer based on six-gene signatures

Purpose: To systematically document alternative splicing profiles of prostate cancer in relatively large populations in order to construct a prognostic predictors model for prostate cancer.

Methods: Splicing data and clinical information of 495 prostate cancer patients were obtained from The Cancer Genome Atlas (TCGA). The SpliceSeq database was used to extract information regarding splicing events. Multiple bioinformatic tools were used for functional and pathway enrichment analysis as well as for construction of gene interaction networks. Candidate gene expression profiles were verified with clinical samples using QRT-PCR.

Results: We detected a total of 44070 alternative splicing events of 10381 genes in prostate cancer. 7 and 14 KEGG pathways were enriched and were associated with overall and recurrence-free survival, respectively. The expression of 396 genes among the 1526 overall survival genes associated alternative splicing events were associated with overall survival. The expression of 483 genes among the 1916 recurrence-free survival genes associated alternative splicing events were associated with recurrence-free survival. Lastly, we constructed the prognosis risk score system based on the expression profiles of six-gene signatures which in combination had an AUC of 0.941 for overall survival associated alternative splicing events, followed by overall survival associated gene expressions with an AUC of 0.794, a recurrence-free survival associated gene expression with an AUC of 0.752 and recurrence-free survival associated alternative splicing events with an AUC of 0.735, indicating its strong ability to predict patient outcome. The expression profile of the six genes was also confirmed in different prostate cell lines and clinic samples.

Conclusion: Our comprehensive investigation of alternative splicing not only provided insight into the biological pathways of alternative splicing involved in the development of prostate cancer but also revealed new potential biomarkers for prognosticating as well as novel therapeutic targets for development of prostate cancer treatment.

Comprehensive investigation of key biomarkers and pathways in hepatitis B virus-related hepatocellular carcinoma

Objective: Our study is aim to explore potential key biomarkers and pathways in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) using genome-wide expression profile dataset and methods.

Methods: Dataset from the GSE14520 is used as the training cohort and The Cancer Genome Atlas dataset as the validation cohort. Differentially expressed genes (DEGs) screening were performed by the limma package. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and risk score model were used for pathway and genes identification.

Results: GSEA revealed that several pathways and biological processes are associated with hepatocarcinogenesis, such as the cell cycle, DNA repair, and p53 pathway. A total of 160 DEGs were identified. The enriched functions and pathways of the DEGs included toxic substance decomposition and metabolism processes, and the P450 and p53 pathways. Eleven of the DEGs were identified as hub DEGs in the WGCNA. In survival analysis of hub DEGs, high expression of PRC1 and TOP2A were significantly associated with poor clinical outcome of HBV-related HCC, and shown a good performance in HBV-related HCC diagnosis. The prognostic signature consisting of PRC1 and TOP2A also doing well in the prediction of HBV-related HCC prognosis. The diagnostic and prognostic values of PRC1 and TOP2A was confirmed in TCGA HCC patients.

Conclusions: Key biomarkers and pathways identified in the present study may enhance the comprehend of the molecular mechanisms underlying hepatocarcinogenesis. Additionally, mRNA expression of PRC1 and TOP2A may serve as potential diagnostic and prognostic biomarkers for HBV-related HCC.

Local delivery of arsenic trioxide nanoparticles for hepatocellular carcinoma treatment

Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. Surgery combined with chemotherapy has been recommended as a curative regimen for HCC. Nevertheless, the anticancer mechanisms of chemicals in hepatocellular carcinoma remain unclear. Pyroptosis is a type of programmed necrosis, and its mechanism in hepatocellular carcinoma is poorly understood. The efficacy and mechanism of arsenic trioxide nanoparticles in the treatment of HCC were explored in this research. Arsenic trioxide alone and arsenic trioxide nanoparticles were conveniently administered to mice intratumorally using a needle. Compared with As2O3, As2O3 nanoparticles (As2O3-NPs) showed better inhibition, promoted greater LDH release, and induced cell morphology indicative of pyroptosis in vitro. Compared with the free drug, As2O3-NPs increased GSDME-N expression and decreased Dnmt3a, Dnmt3b, and Dnmt1 expression in Huh7 cells. In vivo, As2O3-NPs induced a significant decrease in the expression of Dnmt3a, Dnmt3b and Dnmt1, but significantly upregulated the expression of GSDME-N (gasdermin E (GSDME) was originally found to be related to deafness; recently, it has been defined as a gasdermin family member associated with pyroptosis). As2O3-NPs inhibited tumor growth more strongly than As2O3 or control, a finding likely attributed to the downregulation of PCNA and DNMT-related proteins and the upregulation of GSDME-N.

Phenotype-Based Screens with Conformation-Specific Inhibitors Reveal p38 Gamma and Delta as Targets for HCC Polypharmacology

The approved kinase inhibitors for hepatocellular carcinoma (HCC) are not matched to specific mutations within tumors. This has presented a daunting challenge; without a clear target or mechanism, no straightforward path has existed to guide the development of improved therapies for HCC. Here, we combine phenotypic screens with a class of conformation-specific kinase inhibitors termed type II to identify a multikinase inhibitor, AD80, with antitumoral activity across a variety of HCC preclinical models, including mouse xenografts. Mass spectrometry profiling found a number of kinases as putative targets for AD80, including several receptor and cytoplasmic protein kinases. Among these, we found p38 gamma and delta as direct targets of AD80. Notably, a closely related analog of AD80 lacking p38δ/γ activity, but retaining several other off-target kinases, lost significant activity in several HCC models. Moreover, forced and sustained MKK6 → p38→ATF2 signaling led to a significant reduction of AD80 activity within HCC cell lines. Together with HCC survival data in The Cancer Genome Atlas and RNA-seq analysis, we suggest p38 delta and gamma as therapeutic targets in HCC and an "AD80 inhibition signature" as identifying those patients with best clinical outcomes.

The role of telomeres and telomerase in cirrhosis and liver cancer

Telomerase is a key enzyme for cell survival that prevents telomere shortening and the subsequent cellular senescence that is observed after many rounds of cell division. In contrast, inactivation of telomerase is observed in most cells of the adult liver. Absence of telomerase activity and shortening of telomeres has been implicated in hepatocyte senescence and the development of cirrhosis, a chronic liver disease that can lead to hepatocellular carcinoma (HCC) development. During hepatocarcinogenesis, telomerase reactivation is required to enable the uncontrolled cell proliferation that leads to malignant transformation and HCC development. Part of the telomerase complex, telomerase reverse transcriptase, is encoded by TERT, and several mechanisms of telomerase reactivation have been described in HCC that include somatic TERT promoter mutations, TERT amplification, TERT translocation and viral insertion into the TERT gene. An understanding of the role of telomeres and telomerase in HCC development is important to develop future targeted therapies and improve survival of this disease. In this Review, the roles of telomeres and telomerase in liver carcinogenesis are discussed, in addition to their potential translation to clinical practice as biomarkers and therapeutic targets.