Biomarkers for Hepatocellular Carcinoma

Origin and role of hepatic myofibroblasts in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is the second leading cause of cancer-related death worldwide. Fibrosis and cirrhosis are important risk factors for the development of HCC. Hepatic myofibroblasts are the cells responsible for extracellular matrix deposition, which is the hallmark of liver fibrosis. It is believed that myofibroblasts are predominantly derived from hepatic stellate cells (HSCs), also known as Ito cells. Nevertheless, depending on the nature of insult to the liver, it is thought that myofibroblasts may also originate from a variety of other cell types such as the portal fibroblasts (PFs), fibrocytes, hepatocytes, hepatic progenitor cells (HPCs), and mesothelial cells. Liver myofibroblasts are believed to transform into cancer-associated fibroblasts (CAFs) while HCC is developing. There is substantial evidence suggesting that activated HSCs (aHSCs)/cancer-associated fibroblasts (CAFs) may play an important role in HCC initiation and progression. In this paper, we aim to review current literature on cellular origins of myofibroblasts with a focus on hepatitis B virus (HBV)- and hepatitis C virus (HCV)-induced hepatic fibrosis. We also address the role of aHSCs/CAFs in HCC progression through the regulation of immune cells as well as mechanisms of evolvement of drug resistance.

Origin and role of hepatic myofibroblasts in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is the second leading cause of cancer-related death worldwide. Fibrosis and cirrhosis are important risk factors for the development of HCC. Hepatic myofibroblasts are the cells responsible for extracellular matrix deposition, which is the hallmark of liver fibrosis. It is believed that myofibroblasts are predominantly derived from hepatic stellate cells (HSCs), also known as Ito cells. Nevertheless, depending on the nature of insult to the liver, it is thought that myofibroblasts may also originate from a variety of other cell types such as the portal fibroblasts (PFs), fibrocytes, hepatocytes, hepatic progenitor cells (HPCs), and mesothelial cells. Liver myofibroblasts are believed to transform into cancer-associated fibroblasts (CAFs) while HCC is developing. There is substantial evidence suggesting that activated HSCs (aHSCs)/cancer-associated fibroblasts (CAFs) may play an important role in HCC initiation and progression. In this paper, we aim to review current literature on cellular origins of myofibroblasts with a focus on hepatitis B virus (HBV)- and hepatitis C virus (HCV)-induced hepatic fibrosis. We also address the role of aHSCs/CAFs in HCC progression through the regulation of immune cells as well as mechanisms of evolvement of drug resistance.

Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma

The threat of Hepatocellular Carcinoma (HCC) is a growing problem, with incidence rates anticipated to near double over the next two decades. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis (CIRR) to better understand the mechanistic differences between HCC and CIRR. Through pathway and network analysis, we are able to take a systems biology approach to conduct multi-omic analysis of transcriptomic, glycoproteomic, and metabolomic data acquired through various platforms. As a result, we are able to identify the FXR/RXR Activation pathway as being represented by molecules spanning multiple molecular compartments in these samples. Specifically, serum metabolites deoxycholate and chenodeoxycholic acid and serum glycoproteins C4A/C4B, KNG1, and HPX are biomarker candidates identified from this analysis that are of interest for future targeted studies. These results demonstrate the integrative power of multi-omic analysis to prioritize clinically and biologically relevant biomarker candidates that can increase understanding of molecular mechanisms driving HCC and make an impact in patient care.

Predicting Clinical Efficacy of Vascular Disrupting Agents in Rodent Models of Primary and Secondary Liver Cancers: An Overview with Imaging-Histopathology Correlation

Vascular disrupting agents (VDAs) have entered clinical trials for over 15 years. As the leading VDA, combretastatin A4 phosphate (CA4P) has been evaluated in combination with chemotherapy and molecular targeting agents among patients with ovarian cancer, lung cancer and thyroid cancer, but still remains rarely explored in human liver cancers. To overcome tumor residues and regrowth after CA4P monotherapy, a novel dual targeting pan-anticancer theragnostic strategy, i.e., OncoCiDia, has been developed and shown promise previously in secondary liver tumor models. Animal model of primary liver cancer is time consuming to induce, but of value for more closely mimicking human liver cancers in terms of tumor angiogenesis, histopathological heterogeneity, cellular differentiation, tumor components, cancer progression and therapeutic response. Being increasingly adopted in VDA researches, multiparametric magnetic resonance imaging (MRI) provides imaging biomarkers to reflect in vivo tumor responses to drugs. In this article as a chapter of a doctoral thesis, we overview the construction and clinical relevance of primary and secondary liver cancer models in rodents. Target selection for CA4P therapy assisted by enhanced MRI using hepatobiliary contrast agents (CAs), and therapeutic efficacy evaluated by using MRI with a non-specific contrast agent, dynamic contrast enhanced (DCE) imaging, diffusion weighted imaging (DWI) are also described. We then summarize diverse responses among primary hepatocellular carcinomas (HCCs), secondary liver and pancreatic tumors to CA4P, which appeared to be related to tumor size, vascularity, and cellular differentiation. In general, imaging-histopathology correlation studies allow to conclude that CA4P tends to be more effective in secondary liver tumors and in more differentiated HCCs, but less effective in less differentiated HCCs and implanted pancreatic tumor. Notably, cirrhotic liver may be responsive to CA4P as well. All these could be instructive for future clinical trials of VDAs.

Metabolomic and Lipidomic Biomarkers for Premalignant Liver Disease Diagnosis and Therapy

In recent years, there has been a plethora of attempts to discover biomarkers that are more reliable than α-fetoprotein for the early prediction and prognosis of hepatocellular carcinoma (HCC). Efforts have involved such fields as genomics, transcriptomics, epigenetics, microRNA, exosomes, proteomics, glycoproteomics, and metabolomics. HCC arises against a background of inflammation, steatosis, and cirrhosis, due mainly to hepatic insults caused by alcohol abuse, hepatitis B and C virus infection, adiposity, and diabetes. Metabolomics offers an opportunity, without recourse to liver biopsy, to discover biomarkers for premalignant liver disease, thereby alerting the potential of impending HCC. We have reviewed metabolomic studies in alcoholic liver disease (ALD), cholestasis, fibrosis, cirrhosis, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH). Specificity was our major criterion in proposing clinical evaluation of indole-3-lactic acid, phenyllactic acid, N-lauroylglycine, decatrienoate, N-acetyltaurine for ALD, urinary sulfated bile acids for cholestasis, cervonoyl ethanolamide for fibrosis, 16α-hydroxyestrone for cirrhosis, and the pattern of acyl carnitines for NAFL and NASH. These examples derive from a large body of published metabolomic observations in various liver diseases in adults, adolescents, and children, together with animal models. Many other options have been tabulated. Metabolomic biomarkers for premalignant liver disease may help reduce the incidence of HCC.

Sequential Circulating Tumor Cell Counts in Patients with Locally Advanced or Metastatic Hepatocellular Carcinoma: Monitoring the Treatment Response

Hepatocellular carcinoma (HCC) is among the most common causes of cancer death in men. Whether or not a longitudinal follow-up of circulating tumor cells (CTCs) before and at different time points during systemic/targeted therapy is useful for monitoring the treatment response of patients with locally advanced or metastatic HCC has been evaluated in this study. Blood samples (n = 104) were obtained from patients with locally advanced or metastatic HCC (n = 30) for the enrichment of CTCs by a negative selection method. Analysis of the blood samples from patients with defined disease status (n = 81) revealed that those with progressive disease (PD, n = 37) had significantly higher CTC counts compared to those with a partial response (PR) or stable disease (SD; n = 44 for PR + SD, p = 0.0002). The median CTC count for patients with PD and for patients with PR and SD was 50 (interquartile range 21-139) and 15 (interquartile range 4-41) cells/mL of blood, respectively. A longitudinal analysis of patients (n = 17) after a series of blood collections demonstrated that a change in the CTC count correlated with the patient treatment response in most of the cases and was particularly useful for monitoring patients without elevated serum alpha-fetoprotein (AFP) levels. Sequential CTC enumeration during treatment can supplement standard medical tests and benefit the management of patients with locally advanced or metastatic HCC, in particular for the AFP-low cases.

Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data

The high mortality rate of hepatocellular carcinoma (HCC) is primarily due to its late diagnosis. In the past, numerous attempts have been made to design genetic biomarkers for the identification of HCC; unfortunately, most of the studies are based on small datasets obtained from a specific platform or lack reasonable validation performance on the external datasets. In order to identify a universal expression-based diagnostic biomarker panel for HCC that can be applicable across multiple platforms, we have employed large-scale transcriptomic profiling datasets containing a total of 2,316 HCC and 1,665 non-tumorous tissue samples. These samples were obtained from 30 studies generated by mainly four types of profiling techniques (Affymetrix, Illumina, Agilent, and High-throughput sequencing), which are implemented in a wide range of platforms. Firstly, we scrutinized overlapping 26 genes that are differentially expressed in numerous datasets. Subsequently, we identified a panel of three genes (FCN3, CLEC1B, and PRC1) as HCC biomarker using different feature selection techniques. Three-genes-based HCC biomarker identified HCC samples in training/validation datasets with an accuracy between 93 and 98%, Area Under Receiver Operating Characteristic curve (AUROC) in a range of 0.97 to 1.0. A reasonable performance, i.e., AUROC 0.91–0.96 achieved on validation dataset containing peripheral blood mononuclear cells, concurred their non-invasive utility. Furthermore, the prognostic potential of these genes was evaluated on TCGA-LIHC and GSE14520 cohorts using univariate survival analysis. This analysis revealed that these genes are prognostic indicators for various types of the survivals of HCC patients (e.g., Overall Survival, Progression-Free Survival, Disease-Free Survival). These genes significantly stratified high-risk and low-risk HCC patients (p-value <0.05). In conclusion, we identified a universal platform-independent three-genes-based biomarker that can predict HCC patients with high precision and also possess significant prognostic potential. Eventually, we developed a web server HCCpred based on the above study to facilitate scientific community (http://webs.iiitd.edu.in/raghava/hccpred/).

Evaluation of click chemistry microarrays for immunosensing of alpha-fetoprotein (AFP)

The level of cancer biomarkers in cells, tissues or body fluids can be used for the prediction of the presence of cancer or can even indicate the stage of the disease. Alpha-fetoprotein (AFP) is the most commonly used biomarker for early screening and diagnosis of hepatocellular carcinoma (HCC). Here, a combination of three techniques (click chemistry, the biotin-streptavidin-biotin sandwich strategy and the use of antigen-antibody interactions) were combined to implement a sensitive fluorescent immunosensor for AFP detection. Three types of functionalized glasses (dibenzocyclooctyne- (DBCO-), thiol- and epoxy-terminated surfaces) were biotinylated by employing the respective adequate click chemistry counterparts (biotin-thiol or biotin-azide for the first class, biotin-maleimide or biotin-DBCO for the second class and biotin-amine or biotin-thiol for the third class). The anti-AFP antibody was immobilized on the surfaces via a biotin-streptavidin-biotin sandwich technique. To evaluate the sensing performance of the differently prepared surfaces, fluorescently labeled AFP was spotted onto them via microchannel cantilever spotting (µCS). Based on the fluorescence measurements, the optimal microarray design was found and its sensitivity was determined.

Individualized Ablation of Hepatocellular Carcinoma: Tailored Approaches across the Phenotype Spectrum

Ablation is now recommended by international guidelines for the definitive treatment of hepatocellular carcinoma (HCC). Extensive clinical studies have demonstrated outcomes comparable to surgical resection with shorter hospital stays, decreased costs, and improved quality of life. Successful ablation requires complete treatment of both tumor and margin while preserving critical adjacent structures. HCC exhibits highly variable presentations in both anatomic involvement and biology which have significant implications on choice of ablative therapy. There are now abundant ablation modalities and adjunctive techniques which can be used to individualize ablation and maximize curative results. This article provides a patient-centered summary of approaches to HCC ablation in the context of patient performance, hepatic reserve, tumor phenotype and biology, intra- and extrahepatic anatomy, and ablation technology.

Study on Diagnostic Values of Astrocyte Elevated Gene 1 (AEG-1) and Glypican 3 (GPC-3) in Hepatocellular Carcinoma

OBJECTIVES

To investigate the diagnostic potential of AEG-1 and GPC-3 in hepatocellular carcinoma (HCC).

METHODS

AEG-1 and GPC-3 immunohistochemistry were performed on HCC, adjacent nontumor tissue (ANT), and dysplastic nodules (DN).

RESULTS

H score of AEG-1 or GPC-3 in HCC was significantly higher than in ANT or DN. In HCC, 92% and 54% showed AEG-1 and GPC-3 positivity, respectively. In ANT, 16.2% were AEG-1 and 7.6% GPC-3 positive. AEG-1 staining was mostly diffuse, whereas GPC-3 frequently showed focal staining. AEG-1 alone showed high sensitivity but low specificity and accuracy. GPC-3, on the other hand, showed high specificity but low sensitivity and accuracy. Combination of both stains boosted the sensitivity, specificity, and accuracy to 94.6%, 89.5%, and 90.5%, respectively, when only diffuse staining was considered as positive.

CONCLUSIONS

AEG-1 or GPC-3 alone seemed not an ideal marker for HCC. The combination of AEG-1 and GPC-3 might improve early diagnosis of HCC.

Classification of early and late stage liver hepatocellular carcinoma patients from their genomics and epigenomics profiles

Background

Liver Hepatocellular Carcinoma (LIHC) is one of the major cancers worldwide, responsible for millions of premature deaths every year. Prediction of clinical staging is vital to implement optimal therapeutic strategy and prognostic prediction in cancer patients. However, to date, no method has been developed for predicting the stage of LIHC from the genomic profile of samples.

Methods

The Cancer Genome Atlas (TCGA) dataset of 173 early stage (stage-I), 177 late stage (stage-II, Stage-III and stage-IV) and 50 adjacent normal tissue samples for 60,483 RNA transcripts and 485,577 methylation CpG sites, was extensively analyzed to identify the key transcriptomic expression and methylation-based features using different feature selection techniques. Further, different classification models were developed based on selected key features to categorize different classes of samples implementing different machine learning algorithms.

Results

In the current study, in silico models have been developed for classifying LIHC patients in the early vs. late stage and cancerous vs. normal samples using RNA expression and DNA methylation data. TCGA datasets were extensively analyzed to identify differentially expressed RNA transcripts and methylated CpG sites that can discriminate early vs. late stages and cancer vs. normal samples of LIHC with high precision. Naive Bayes model developed using 51 features that combine 21 CpG methylation sites and 30 RNA transcripts achieved maximum MCC (Matthew’s correlation coefficient) 0.58 with an accuracy of 78.87% on the validation dataset in discrimination of early and late stage. Additionally, the prediction models developed based on 5 RNA transcripts and 5 CpG sites classify LIHC and normal samples with an accuracy of 96–98% and AUC (Area Under the Receiver Operating Characteristic curve) 0.99. Besides, multiclass models also developed for classifying samples in the normal, early and late stage of cancer and achieved an accuracy of 76.54% and AUC of 0.86.

Conclusion

Our study reveals stage prediction of LIHC samples with high accuracy based on the genomics and epigenomics profiling is a challenging task in comparison to the classification of cancerous and normal samples. Comprehensive analysis, differentially expressed RNA transcripts, methylated CpG sites in LIHC samples and prediction models are available from CancerLSP (http://webs.iiitd.edu.in/raghava/cancerlsp/).

Serum Serotonin as a Potential Diagnostic Marker for Hepatocellular Carcinoma

To assess the potential role of serum serotonin level in hepatocellular carcinoma (HCC) diagnosis. A case-control study that involved 100 Egyptian adults. Subjects were divided into 4 groups: Group I: 21 patients with late-stage HCC on top of liver cirrhosis, Group II: 28 patients with early-stage HCC on top of liver cirrhosis, Group III: 26 patients with cirrhosis with no evidence of HCC, and Group IV: 25 healthy age- and sex-matched subjects were as a control group. Serum serotonin level was determined in all recruited subjects using high-performance liquid chromatography-fluorescent detection method. Alpha-fetoprotein had a statistically significant elevation in group I with a median of 1300 ng/L (195-2544 ng/L) compared to groups II and III (P ≤ 0.01). Regarding serum serotonin level, it had a statistically significant elevation in group II with a median of 275 ng/μL (204.7-400 ng/μL) compared to groups I, III, and IV with median of 33 ng/μL (30-50 ng/μL), 50 ng/μL (30-60 ng/μL), and 102 (85-150 ng/μL), respectively (P = 0.001). Receiver operating characteristic curve showed that serum serotonin at cutoff value of 108 ng/μL had a sensitivity of 100% and specificity of 92.3% in discriminating early-stage HCC from cirrhosis. Serum serotonin level is a rapid, sensitive, noninvasive diagnostic biomarker for the detection of early-stage HCC.

Hepatocellular carcinoma: Therapeutic advances in signaling, epigenetic and immune targets

Hepatocellular carcinoma (HCC) remains a global medical burden with rising incidence due to chronic viral hepatitis and non-alcoholic fatty liver diseases. Treatment of advanced disease stages is still unsatisfying. Besides first and second generation tyrosine kinase inhibitors, immune checkpoint inhibitors have become central for the treatment of HCC. New modalities like epigenetic therapy using histone deacetylase inhibitors (HDACi) and cell therapy approaches with chimeric antigen receptor T cells (CAR-T cells) are currently under investigation in clinical trials. Development of such novel drugs is closely linked to the availability and improvement of novel preclinical and animal models and the identification of predictive biomarkers. The current status of treatment options for advanced HCC, emerging novel therapeutic approaches and different preclinical models for HCC drug discovery and development are reviewed here.

Biomarkers vs imaging in the early detection of hepatocellular carcinoma and prognosis

Hepatocellular carcinoma (HCC) is the 5^th most frequently diagnosed cancer in the world, according to the World Health Organization. The incidence of HCC is between 3/100000 and 78.1/100000, with a high incidence reported in areas with viral hepatitis B and hepatitis C, thus affecting Asia and Africa predominantly. Several international clinical guidelines address HCC diagnosis and are structured according to the geographical area involved. All of these clinical guidelines, however, share a foundation of diagnosis by ultrasound surveillance and contrast imaging techniques, particularly computed tomography, magnetic resonance imaging, and sometimes contrast-enhanced ultrasound. The primary objective of this review was to systematically summarize the recent published studies on the clinical utility of serum biomarkers in the early diagnosis of HCC and for the prognosis of this disease.

A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome

The collection of proteins secreted from a cell-the secretome-is of particular interest in cancer pathophysiology due to its diagnostic potential and role in tumorigenesis. However, cancer secretome studies are often limited to one tissue or cancer type or focus on biomarker prediction without exploring the associated functions. We therefore conducted a pan-cancer analysis of secretome gene expression changes to identify candidate diagnostic biomarkers and to investigate the underlying biological function of these changes. Using transcriptomic data spanning 32 cancer types and 30 healthy tissues, we quantified the relative diagnostic potential of secretome proteins for each cancer. Furthermore, we offer a potential mechanism by which cancer cells relieve secretory pathway stress by decreasing the expression of tissue-specific genes, thereby facilitating the secretion of proteins promoting invasion and proliferation. These results provide a more systematic understanding of the cancer secretome, facilitating its use in diagnostics and its targeting for therapeutic development.

Systems Challenges of Hepatic Carcinomas: A Review

Hepatocellular Carcinoma (HCC) is ubiquitous in its prevalence in most of the developing countries. In the era of systems biology, multi-omics has evinced an extensive approach to define the underlying mechanism of disease progression. HCC is a multifactorial disease and the investigation of progression of liver cirrhosis becomes much extensive with cultivating omics approaches. We have performed a comprehensive review about such challenges in multi-omics approaches that are concerned to identify the immunological, genetics and epidemiological factors associated with HCC.

Identification of Protein Abundance Changes in Hepatocellular Carcinoma Tissues Using PCT-SWATH

PURPOSE

To rapidly identify protein abundance changes in biopsy-level fresh-frozen hepatocellular carcinoma (HCC).

EXPERIMENTAL DESIGN

The pressure-cycling technology (PCT) is applied and sequential window acquisition of all theoretical mass spectra (SWATH-MS) workflow is optimized to analyze 38 biopsy-level tissue samples from 19 HCC patients. Each proteome is analyzed with 45 min LC gradient. MCM7 is validated using immunohistochemistry (IHC).

RESULTS

A total of 11 787 proteotypic peptides from 2579 SwissProt proteins are quantified with high confidence. The coefficient of variation (CV) of peptide yield using PCT is 32.9%, and the R² of peptide quantification is 0.9729. Five hundred forty-one proteins showed significant abundance change between the tumor area and its adjacent benign area. From 24 upregulated pathways and 13 suppressed ones, enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues are observed. Protein changes based on α-fetoprotein expression and hepatitis B virus infection are further analyzed. The data altogether highlight 16 promising tumor marker candidates. The upregulation of minichromosome maintenance complex component 7 (MCM7) is further observed in multiple HCC tumor tissues by IHC.

CONCLUSIONS AND CLINICAL RELEVANCE

The practicality of rapid proteomic analysis of biopsy-level fresh-frozen HCC tissue samples with PCT-SWATH has been demonstrated and promising tumor marker candidates including MCM7 are identified.

NRAGE is a potential diagnostic biomarker of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common cancers and a leading cause of cancer-related deaths worldwide. Early diagnosis of HCC remains a great challenge in clinic. Novel and effective biomarkers are in urgent need in early diagnosis of HCC.Serum levels of neurotrophin-receptor-interacting melanoma antigen-encoding gene homolog (NRAGE) were measured for 107 patients with HCC, 98 patients with benign liver diseases, and 89 healthy controls using quantitative real-time polymerase chain reaction. Receiver operating characteristic curve was applied to evaluate the diagnostic capacity of serum NRAGE in HCC.NRAGE expression was significantly higher in patients with HCC than in controls (all, P < .05). Moreover, its expression was tightly correlated with TNM stage (P = .004). NRAGE could distinguish patients with HCC from healthy controls with the area under the curve (AUC) of 0.874, yielding a sensitivity of 81.3% and a specificity of 78.7%. Additionally, in differentiation between benign liver diseases and HCC, the AUC value of NRAGE was 0.726, with a sensitivity of 63.6% and a specificity of 73.5%. Meanwhile, alpha-fetoprotein also could distinguish patients with HCC from benign liver disease cases, with an AUC of 0.677, a sensitivity of 64.4%, and a specificity of 60.2%.NRAGE could be a potential biomarker for HCC early diagnosis.

Molecular Mechanisms of Hepatocarcinogenesis Following Sustained Virological Response in Patients with Chronic Hepatitis C Virus Infection

Despite the success of direct-acting antiviral (DAA) agents in treating chronic hepatitis C virus (HCV) infection, the number of cases of HCV-related hepatocellular carcinoma (HCC) is expected to increase over the next five years. HCC develops over the span of decades and is closely associated with fibrosis stage. HCV both directly and indirectly establishes a pro-inflammatory environment favorable for viral replication. Repeated cycles of cell death and regeneration lead to genomic instability and loss of cell cycle control. DAA therapy offers >90% sustained virological response (SVR) rates with fewer side effects and restrictions than interferon. While elimination of HCV helps to restore liver function and reverse mild fibrosis, post-SVR patients remain at elevated risk of HCC. A series of studies reporting higher than expected rates of HCC development among DAA-treated patients ignited debate over whether use of DAAs elevates HCC risk compared to interferon. However, recent prospective and retrospective studies based on larger patient cohorts have found no significant difference in risk between DAA and interferon therapy once other factors are taken into account. Although many mechanisms and pathways involved in hepatocarcinogenesis have been elucidated, our understanding of drivers specific to post-SVR hepatocarcinogenesis is still limited, and lack of suitable in vivo and in vitro experimental systems has hampered efforts to examine etiology-specific mechanisms that might serve to answer this question more thoroughly. Further research is needed to identify risk factors and biomarkers for post-SVR HCC and to develop targeted therapies based on more complete understanding of the molecules and pathways implicated in hepatocarcinogenesis.

Biomarkers for hepatocellular carcinoma: What’s new on the horizon?

Treatment of advanced hepatocellular carcinoma remains unsatisfying and so far only prognostic biomarkers like α-fetoprotein have been established. No clear predictive biomarker is currently available for standard of care therapies, including targeted therapies like sorafenib. Novel therapeutic options like immune checkpoint inhibitors may pose new challenges to identification and validation of such markers. Currently, PD-L1 expression via immunohistochemistry and tumor mutational burden via next-generation sequencing are explored as predictive biomarkers for these novel treatments. Limited tissue availability due to lack of biopsies still restricts the use of tissue based approaches. Novel methods exploring circulating or cell free nucleic acids (DNA, RNA or miRNA-containing exosomes) could provide a new opportunity to establish predictive biomarkers. Epigenetic profiling and next-generation sequencing approaches from liquid biopsies are under development. Sample size, etiologic and geographical background need to be carefully addressed in such studies to achieve meaningful results that could be translated into clinical practice. Proteomics, metabolomics and molecular imaging are further emerging technologies.

Loci-specific differences in blood DNA methylation in HBV-negative populations at risk for hepatocellular carcinoma development

Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed. We used the Illumina HumanMethylation450 BeadChip microarray to test whether white blood cell DNA, an easily accessible source of DNA, exhibits site-specific changes in DNA methylation in blood of diagnosed HCC patients (post-diagnostic, 24 cases, 24 controls) and in prospectively collected blood specimens of HCC patients who were cancer-free at blood collection (pre-diagnostic, 21 cases, 21 controls). Out of 22 differentially methylated loci selected for validation by pyrosequencing, 19 loci with neighbouring CpG sites (probes) were confirmed in the pre-diagnostic study group and subjected to verification in a prospective cirrhotic cohort (13 cases, 23 controls). We established for the first time 9 probes that could distinguish HBV-negative cirrhotic patients who subsequently developed HCC from those who stayed cancer-free. These probes were identified within regulatory regions of BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210, and LSP1. Methylation levels within DPPA5, KIAA1210, and LSP1 were higher in prospective samples from HCC cases vs. cirrhotic controls. The remaining probes were hypomethylated in cases compared with controls. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established probes have potential to be developed into a routine clinical test after validation in larger cohorts.

Direct comparison of five serum biomarkers in early diagnosis of hepatocellular carcinoma

BACKGROUND

Although a number of serum biomarkers for detection of hepatocellular carcinoma (HCC) have been explored, their exact diagnostic value remains unclear. We aimed to conduct a direct comparison of five representative serum biomarkers for detecting HCC and to derive multi-marker prediction algorithms.

PATIENTS AND METHODS

In total, 846 patients were recruited from three hospitals in China, including 202 HCC patients, 226 liver cirrhosis patients, 215 chronic hepatitis B virus-infected patients, and 203 healthy volunteers. Serum levels of alpha-fetoprotein (AFP), lens culinaris agglutinin-reactive AFP (AFP-L3), des-gamma-carboxyprothrombin (DCP), squamous cell carcinoma antigen, and centromere protein F autoantibody were measured by ELISA. The diagnostic performances of individual biomarkers and multi-marker combinations were evaluated by receiver operating characteristics analysis. The bootstrapping method was adopted to adjust for potential overfitting of all diagnostic indicators.

RESULTS

DCP exhibited the best diagnostic performance, with areas under the curve (AUC) for detecting HCC of 0.82 (95% CI 0.64-0.80) and sensitivity of 65.2% (95% CI 63.3-82.1%) at 90% specificity. Of note, DCP showed similar diagnostic efficacy for detecting AFP-positive and AFP-negative HCC. After a comprehensive search for multi-marker combinations, a two-marker prediction algorithm including AFP and DCP was constructed and yielded an AUC of 0.87 (95% CI 0.68-0.84) for detecting HCC. In addition, the combination showed good ability in discriminating early-stage HCC and decompensated liver cirrhosis, with an AUC of 0.81 (95% CI 0.75-0.86).

CONCLUSION

DCP could be a complementary biomarker in the early diagnosis of HCC. The constructed multi-marker prediction algorithms could contribute toward distinguishing HCC from non-malignant chronic liver diseases.

Performance of protein induced by vitamin K absence or antagonist-II assessed by chemiluminescence enzyme immunoassay for hepatocellular carcinoma detection: a meta-analysis

OBJECTIVES

In the setting of surveillance for hepatocellular carcinoma (HCC) detection, the use of serum biomarkers in addition to ultrasonography (US) is still a matter of debate. Hence, we performed a meta-analysis to evaluate the diagnostic accuracy of protein induced by vitamin K absence or antagonist-II (PIVKA-II) and alpha-fetoprotein (AFP) alone or in combination for HCC detection in patients at risk of tumor development.

MATERIALS AND METHODS

We performed a systematic search in PubMed and Scopus database for original articles published in English from 2011 to 2017, investigating the accuracy of PIVKA-II alone or in combination with AFP (reported as area under the curve [AUC]) for HCC detection among patients at risk of tumor development. Furthermore, we focused on studies in which serum PIVKA-II was assessed by highly sensitive chemiluminescence immunoassay (CLEIA).

RESULTS

A total of 11 studies (873 patients with HCC and 1244 patients with advanced liver disease/cirrhosis) were included in the meta-analysis. The weighted summary AUC (sAUC) of PIVKA-II and AFP for the discrimination between patients with HCC and those without was 0.791 (0.746-0.837) and 0.767 (0.732-0.803), respectively. The combination of PIVKA-II + AFP results in a sAUC of 0.859 (0.837-0.882). The performance for HCC detection of PIVKA-II + AFP was significantly superior to each biomarker used alone (ΔsAUC = 0.068, p = .032 and ΔsAUC = 0.092, p < .001, respectively).

CONCLUSION

In clinical practice, the use of PIVKA-II + AFP in addition to US examination may improve the effectiveness of surveillance among patients at risk for HCC development.

Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma

Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer prognosis. Among patients with recurred tumors, we found the correlation of higher modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients' survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.

The potential value of CDV3 in the prognosis evaluation in Hepatocellular carcinoma

CDV3 is correlated with tumorigenesis and may affect some biological process in cancer. In this study, we explore the role of CDV3 in HCC. According to the TCGA data base, CDV3 is over-expressed in HCC tissues. Up-regulation of CDV3 is correlated with lower over-all survival rate in HCC patients. In HCC samples from our hospital, CDV3 is also enriched in cancer tissues and CDV3 expression associated with HCC pathological T stage. What is more, higher CDV3 expression could forecast poor survival rate in HCC patients. In conclusion, CDV3 is a biomarker of HCC and could be a potential therapeutic target.

The Changing Face of the Diagnosis of Chronic and Malignant Liver Diseases: Potential New Biomarkers

The early diagnosis of primary sclerosing cholangitis, hepatocellular carcinoma, and cholangiocarcinoma is often challenging. In a recent study in 134 patients (Arbelaiz, Hepatology 2017; 66:1125-1143), it was reported that specific proteins found in serum extracellular vesicles of patients with primary sclerosing cholangitis, hepatocellular carcinoma,orcholangiocarcinomamay be useful as noninvasive diagnostic and prognostic tools. This current article critically appraises this study.

MiR-1202 suppresses hepatocellular carcinoma cells migration and invasion by targeting cyclin dependent kinase 14

Currently, hepatocellular carcinoma (HCC) patients still have poor survival outcomes mainly due to the powerful mobility of HCC cells. Increasing evidences hint that abnormally expressed miRNAs are capable to modulate HCC cells invasion and migration. MiR-1202 has been proposed as a ponderable molecular tumor marker in a variety of tumors. Here, results from real-time PCR indicated the decreased expression of miR-1202 in HCC. Clinically, statistical analysis showed that miR-1202 under-expression was closely associated with metastasis-related clinicopathologic characteristics. In addition, 5-year overall survival (OS) and disease-free survival (DFS) rates of HCC patients with high miR-1202 expression were much better than that in low miR-1202 group. Functionally, gain- and loss-of -function studies were performed to investigate the roles of miR-1202. Intriguingly, Would healing assay and Transwell assays indicated that elevated miR-1202 weakened HCC cells migration and invasion abilities, while miR-1202 knockdown presented the contrary effects. Furthermore, cyclin dependent kinase 14 (CDK14) was identified as a downstream target of miR-1202 by bioinformatics analysis, Dual luciferase reporter assay, detection of CDK14 expression and Pearson correlation analysis. More importantly, rescue experiments demonstrated that CDK14 mediated miR-1202 to exert its anti-tumor effects, which further confirmed the above finding. Taken together, miR-1202 may act as a new biomarker and potential therapeutic target for HCC.

Variety and Dynamics of Proteoforms in the Human Proteome: Aspects of Markers for Hepatocellular Carcinoma

We have previously developed an approach, where two-dimensional gel electrophoresis (2DE) was used, followed by sectional analysis of the whole gel using high-resolution nano-liquid chromatography-mass spectrometry (ESI LC-MS/MS). In this study, we applied this approach on the panoramic analysis of proteins and their proteoforms from normal (liver) and cancer (HepG2) cells. This allowed us to detect, in a single proteome, about 20,000 proteoforms coded by more than 4000 genes. A set of 3D-graphs showing distribution of these proteoforms in 2DE maps (profiles) was generated. A comparative analysis of these profiles between normal and cancer cells showed high variability and dynamics of many proteins. Among these proteins, there are some well-known features like alpha-fetoprotein (FETA) or glypican-3 (GPC3) and potential hepatocellular carcinoma (HCC) markers. More detailed information about their proteoforms could be used for generation of panels of more specific biomarkers.

Lipophagy and liver disease: New perspectives to better understanding and therapy

Intracellular lipid droplets (LDs) are remarkably dynamic and complex organelles that enact regulated storage and release of lipids to fulfil their fundamental roles in energy metabolism, membrane synthesis and provision of lipid-derived signaling molecules. The recent finding that LDs can be selectively degraded by the lysosomal pathway of autophagy through a process termed lipophagy has opened up a new understanding of how lipid metabolism regulates cellular physiology and pathophysiology. Many new functions for autophagic lipid metabolism have now been defined in various diseases including liver disease. Lipophagy was originally described in hepatocytes, where it is critical for maintaining cellular energy homeostasis in obesity and metabolic syndrome. In vitro and in vivo studies have demonstrated the selective uptake of LDs by autophagosomes, and inhibition of autophagy has been shown to reduce the β-oxidation of free fatty acids due to the increased accumulation of lipids and LDs. The identification of lipophagy as a new process dedicated to cellular lipid removal has mapped autophagy as an emerging player in cellular lipid metabolism. Pharmacological or genetic modulation of lipophagy might point to possible therapeutic strategies for combating a broad range of liver diseases. This review summarizes recent work focusing on lipophagy and liver disease as well as highlighting challenges and future directions of research. On the other hand, it also offers a glimpse into different strategies that have been used in experimental models to counteract excessive pathological lipophagy in the prevention and treatment of liver disease.

Intrahepatic splenosis mimics hepatocellular carcinoma in a patient with chronic hepatitis B: A case report and literature review

BACKGROUND

Splenosis is a benign and relatively uncommon condition caused by trauma or splenectomy or other procedures involving splenic tissue. It is usually asymptomatic, and often diagnosed accidentally, especially misdiagnosed as malignant tumor.

METHODS

A 54-year-old man with prior history of chronic hepatitis B virus infection and underwent splenectomy for traumatic splenic rupture following a traffic accident 23 years previously was admitted to our hospital and found a hepatic mass in the right upper quadrant during an imaging examination. The diagnosis of his was not clear and finally he agreed to receive a surgical treatment.

RESULTS

During the operation, we found a mass in the right posterior lobe of the liver and a hard nodule on the right side of the diaphragm, both were completely resected, and postoperative histopathologic examination revealed that all excised tissues were proved to have histological structure typical for the spleen.

CONCLUSIONS

The occurrence of intrahepatic splenosis is rare with only few cases previously reported in the literature. It is a benign disease and sometimes difficult to distinguish from diseases of the liver. The need for positive surgical resection of splenosis is still controversial.