Biomarkers for Hepatocellular Carcinoma

Diagnostic value of expressions of cancer stem cell markers for adverse outcomes of hepatocellular carcinoma and their associations with prognosis: A Bayesian network meta‑analysis

The expression of cancer stem cell (CSC) markers adversely affect the survival prognosis of patients with hepatocellular carcinoma (HCC), but it is not clear which cancer stem cell marker has the best predictive effect on the survival prognosis and diagnostic value indicators of patients with HCC. Therefore, the present study performed a network meta-analysis to compare the prognostic and diagnostic value of the expressions of several CSC markers for patients with HCC and to identify the most efficient CSC marker. Studies on the associations of positive CSC markers with the overall survival (OS) rate, disease-free survival (DFS) rate, recurrence-free survival (RFS) rate, recurrence rate, differentiation, microvascular invasion and metastasis in patients with HCC were included in the network meta-analysis following searches on the PubMed, Embase, Elsevier and The Cochrane Library databases from January 1, 2013 to November 17, 2023. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the quality assessment of studies, and R (version 4.3.1), Stata (version 15.0) and Review Manager (version 5.3) were used for analysis. A total of 37 studies involving 3,980 participants were included. For patients with HCC, simultaneous positivity of cytokeratin 19 (CK19) and epithelial cell adhesion molecule (EpCAM) was the strongest predictor of the OS rate [surface under the cumulative ranking curve (SUCRA), 78.65%], positive keratin 19 (K19) was the strongest predictor of the RFS and DFS rates (SUCRA, 98.93 and 84.95%, respectively), and simultaneous positivity of EpCAM and cluster of differentiation (CD)90 was the strongest predictor of the recurrence rate (SUCRA, 5.61%). In addition, positivity of CD56, K19 and CD133 had the best diagnostic efficacy for poor differentiation [superiority index, 7.4498; 95% confidence interval (CI): 0.3333, 13.0000], microvascular invasion (superiority index, 8.4777; 95% CI: 0.2308, 17.0000), and metastasis (superiority index, 5.6097; 95% CI: 0.3333, 11.0000), respectively. In conclusion, no single CSC marker possessed the best predictive effect on all indexes of survival prognosis and diagnosis of patients with HCC. In terms of survival prognosis, simultaneous positivity of CK19 and EpCAM demonstrated the strongest predictive effect on the OS rate, suggesting an association with a low OS rate in patients with HCC; positive K19 revealed the strongest predictive effect on the RFS rate and DFS rate, suggesting an association with low RFS and DFS rates in patients with HCC; and simultaneous positivity of EpCAM and CD90 had the strongest predictive effect on the recurrence rate, suggesting a high recurrence rate in patients with HCC patients. In terms of diagnostic value, CD56, K19 and CD133 were the strongest predictors of poor differentiation, microvascular invasion and metastasis, respectively. In the future, well-designed randomized controlled trials are required to further confirm these findings.

PGK1 is a potential biomarker for early diagnosis and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a common type of liver cancer, is increasing in incidence worldwide. An early diagnosis of hepatocellular carcinoma (HCC) is still challenging: Currently, few biomarkers are available to diagnose the early stage of HCC, therefore, additional prognostic biomarkers are required to identify potential risk factors. The present study analyzed gene expression levels of HCC tissue samples and the protein expression levels obtained from the GSE46408 HCC dataset using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The metabolically associated differentially expressed genes (DEGs), including DEGs involved in the glucose metabolism pathway, were selected for further analysis. Phosphoglycerate kinase 1 (PGK1), a glycolytic enzyme, was determined as a potential prognostic biomarker through Kaplan-Meier curve and clinical association variable analyses. This was also verified based on the expression levels of PGK1 in tumor tissue and protein expression levels in several liver cancer cell lines. PGK1 mRNA demonstrated a high level of expression in HCC tissue and was significantly associated with a poor prognosis, showing a negative association with survival time. In addition, as an independent risk factor, PGK1 may potentially be a valuable prognostic biomarker for patients with HCC. Furthermore, expression of PGK1 was associated with the early stages (stage I and T1) of HCC. Moreover, PGK1 mRNA expression levels demonstrated a positive association with progression of liver cancer. The results suggested that PGK1 mRNA may be involved in the degree of HCC malignancy and may be a future potential prognostic biomarker for HCC progression.

A new portable toluidine blue/aptamer complex-on-polyethyleneimine-coated gold nanoparticles-based sensor for label-free electrochemical detection of alpha-fetoprotein

The quantification of alpha-fetoprotein (AFP) as a potential liver cancer biomarker which is generally found in ultratrace level is of significance in biomedical diagnostics. Therefore, it is challenging to find a strategy to fabricate a highly sensitive electrochemical device towards AFP detection through electrode modification for signal generation and amplification. This work shows the construction of a simple, reliable, highly sensitive, and label-free aptasensor based on polyethyleneimine-coated gold nanoparticles (PEI-AuNPs). A disposable ItalSens screen-printed electrode (SPE) is employed for fabricating the sensor by successive modifying with PEI-AuNPs, aptamer, bovine serum albumin (BSA), and toluidine blue (TB), respectively. The AFP assay is easily performed when the electrode is inserted into a small Sensit/Smart potentiostat connected to a smartphone. The readout signal of the aptasensor derives from the electrochemical response of TB intercalating into the aptamer-modified electrode after binding with the target. The decrease in current response of the proposed sensor is proportional to the AFP concentration due to the restriction of the electron transfer pathway of TB by a number of insulating AFP/aptamer complexes on the electrode surface. PEI-AuNPs improve SPE's reactivity and provide a large surface area for aptamer immobilization whereas aptamer provides selectivity to the target AFP. Consequently, this electrochemical biosensor is highly sensitive and selective for AFP analysis. The developed assay reveals a linear range of detection from 10 to 50000 pg mL^-1 with R ² = 0.9977 and provided a limit of detection (LOD) of 9.5 pg mL^-1 in human serum. With its simplicity and robustness, it is anticipated that this electrochemical-based aptasensor will be a benefit for the clinical diagnosis of liver cancer and further developed for other biomarkers analysis.

Discovering the digital biomarker of hepatocellular carcinoma in serum with SERS-based biosensors and intelligence vision

By its many virtues, non-biomarker-reliant molecular detection has recently shown bright prospects for cancer screening but its clinical application is hindered by the shortage of measurable criteria that are analogous to biomarkers. Here, we report a digital biomarker, as a new-concept serum biomarker, of hepatocellular carcinoma (HCC) found with SERS-based biosensors and a deep neural network "digital retina" for visualizing and explicitly defining spectral fingerprints. We validate the discovered digital biomarker (a collection of 10 characteristic peaks in the serum SERS spectra) with unsupervised clustering of spectra from an independent sample batch comprised normal individuals and HCC cases; the validation results show clustering accuracies of 95.71% and 100.00%, respectively. Furthermore, we find that the digital biomarker of HCC shares a few common peaks with three clinically applied serum biomarkers, which means it could convey essential biomolecular information similar to these biomarkers. Accordingly, we present an intelligent method for early HCC detection that leverages the digital biomarker with similar traits as biomarkers. Employing the digital biomarker, we could accurately stratify HCC, hepatitis B, and normal populations with linear classifiers, exhibiting accuracies over 92% and area under the receiver operating curve values above 0.93. It is anticipated that this non-biomarker-reliant molecular detection method will facilitate mass cancer screening.

Key Members of the CmPn as Biomarkers Distinguish Histological and Immune Subtypes of Hepatic Cancers

Liver cancer, comprising hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), is a leading cause of cancer-related deaths worldwide. The liver is a primary metabolic organ for progesterone (PRG) and PRG exerts its effects through classic nuclear PRG receptors (nPRs) and non-classic membrane PRG receptors (mPRs) or a combination of both. Previous studies have shown that the CCM signaling complex (CSC) couples both nPRs and mPRs to form the CmPn (CSC-mPR-PRG-nPR) signaling network, which is involved in multiple cellular signaling pathways, including tumorigenesis of various cancers. Despite advances in treatment, 5-year survival rates for liver cancer patients remain low, largely due to the chemoresistant nature of HCCs. The lack of sensitive and specific biomarkers for liver cancer diagnosis and prognosis emphasizes the need for identifying new potential biomarkers. We propose the potential use of CmPn members’ expression data as prognostic biomarkers or biomarker signatures for the major types of hepatic cancer, including HCCs and CCAs, as well as rare subtypes such as undifferentiated pleomorphic sarcoma (UPS) and hepatic angiosarcoma (HAS). In this study, we investigated the CmPn network through RNAseq data and immunofluorescence techniques to measure alterations to key cancer pathways during liver tumorigenesis. Our findings reveal significant differential expression of multiple CmPn members, including CCM1, PAQR7, PGRMC1, and nPRs, in both HCCs and CCAs, highlighting the crucial roles of mPRs, nPRs, and CSC signaling during liver tumorigenesis. These key members of the CmPn network may serve as potential biomarkers for the diagnosis and prognosis of liver cancer subtypes, including rare subtypes.

Chemical Biopsy for GNMT as Noninvasive and Tumorigenesis-Relevant Diagnosis of Liver Cancer

Early diagnosis of hepatocellular carcinoma (HCC) is difficult; the lack of convenient biomarker-based diagnostic modalities renders high-risk HCC patients burdened by life-long periodical examinations. Here, a new chemical biopsy approach was developed for noninvasive diagnosis of HCC using urine samples. Bioinformatic screening for tumor suppressors yielded glycine N-methyltransferase (GNMT) as a biomarker with clinical relevance to HCC tumorigenesis. A liquid chromatography-mass spectrometry (LC-MS)-based chemical biopsy detecting nonradioactive ¹³C-sarcosine from ¹³C-glycine was designed to noninvasively assess liver GNMT activity extrahepatically. ¹³C-Sarcosine showed a strong correlation with GNMT in normal and cancerous liver cells. In an autochthonous animal model developing visible cancer nodules at 17 weeks, the urinary ¹³C-sarcosine chemical biopsy exhibited notable changes as early as 8 weeks, showing significant correlations with liver GNMT and molecular pathological changes. Our chemical biopsy approach should facilitate early and noninvasive diagnosis of HCC, with direct relevance to tumorigenesis, which can be straightforwardly applied to other diseases.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis

BACKGROUND

Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management.

METHODS

Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened.

RESULTS

Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM.

CONCLUSIONS

Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

Biomarkers in Liver Disease

Symptoms and signs of liver diseases are highly variable depending on the etiology, disease stage, and type of liver involvement. There are different types of liver diseases; causes of liver diseases may be viral, toxic, metabolic, or autoimmune. However, in some cases, liver disease can develop as a result of diseases of other organs or systems. It is almost impossible to differentiate all of these solely on the basis of clinical symptoms and findings. Furthermore, the early stages of liver disease may be completely asymptomatic, or in some cases, the disease may progress with only subtle and non-specific symptoms. Therefore, biomarkers have a critical role in screening, diagnosis, staging, and evaluation of therapeutic response to treatment in liver diseases.

Imaging ligands targeting glypican-3 receptor expression in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality. Early detection of HCC is important since potentially curative therapies exist in the initial stages of HCC; no curative therapies exist for late-stage HCC. However, the initial detection of HCC remains challenging due to the lack of symptoms during the early stage of the disease. Other methods of screening and detecting HCC, including blood serum tests and conventional imaging methods, remain inadequate due to genetic differences between patients and the high background activity of liver tissues. Thus, there is a need for an accurate imaging agent for the diagnosis, staging, and prognosis of HCC. Glypican-3 (GPC3) is an oncofetal receptor responsible for regulating cell division, growth, and survival. GPC3 is a clinically relevant biomarker for imaging and therapeutics, as its expression is HCC tumor-specific and absent from normal and other pathological liver tissues. The development of novel GPC3-targeting imaging agents has encompassed three classes of biomolecules: peptides, antibodies, and aptamers. These biomolecules serve as constructs for diagnostic imaging (demonstrating potential as positron emission tomography [PET], single-photon emission tomography [SPECT], and optical imaging agents) and HCC treatment delivery. More than 20 unique ligands have been identified in the literature as showing specificity for the GPC3 receptor. Although several ligands are currently under clinical investigation as therapies for HCC, clinical translation of GPC3-targeting ligands as imaging agents is lacking. This review highlights the current landscape of ligands targeting GPC3 and describes their promising possibilities as imaging agents for HCC.

Simultaneous Homogeneous Fluorescence Detection of AFP and GPC3 in Hepatocellular Carcinoma Clinical Samples Assisted by Enzyme-Free Catalytic Hairpin Assembly

Simultaneous sensitive and cost-effective detection of multiple tumor markers has shown great potential for cancer diagnostics. Herein, we reported a simple enzyme-free parallel catalytic hairpin assembly (CHA) amplification strategy with N-methyl mesoporphyrin IX (NMM) and quantum dots (QDs) as signal reporters for the homogeneous fluorescent simultaneous detection of alpha-fetoprotein (AFP) and glypican-3 (GPC3). Upon selective binding, the released single-stranded DNA (ssDNA) from the two-aptamer double-stranded DNA (dsDNA) probes triggers CHA amplification, further releasing the G-quadruplex sequence and Ag⁺ from the C-Ag⁺-C structures at the same time. Then, NMM and CdTe QDs selectively recognize G-quadruplex and Ag⁺, respectively. Under optimized conditions, limits of detections (LODs) as low as 3 fg/mL for AFP and 0.25 fg/mL for GPC3 were achieved using fluorescence readout. Using color- and distance-based visual readouts, an LOD of 1 fg/mL for GPC3 was reached. This method was applied to quantitatively analyze AFP and GPC3 in 41 clinical serum samples of hepatocellular carcinoma (HCC) patients. The quantitative test results for AFP and GPC3 were consistent with those obtained using the electrochemiluminescence immunoassay (ECL-IA) clinical kit and correlated with radiological and pathological findings. The results of clinical tests demonstrated the potential of GPC3 as a tumor biomarker, and we propose a cut-off value of 2 ng/mL GPC3 for HCC.

Roles of circRNAs in the Tumorigenesis and Metastasis of HCC: A Mini Review

Circular RNAs (circRNAs) are a class of non-coding RNAs with loop structures that are stable and widely distributed in different tumor tissues. The development of high-throughput sequencing and in silico tools has enabled the discovery of numerous functional circRNAs. Hepatocellular carcinoma (HCC) is a malignant tumor, and the mechanism involved in its progression has remained unclear. In recent years, an increasing number of circRNAs have been identified in HCC, contributing to tumorigenesis and metastasis and with the potential role as biomarkers through competitive endogenous RNAs (ceRNAs) as miRNA sponges or by interacting with RNA binding proteins (RBPs). In this review, we summarize the regulatory roles of circRNAs in HCC development as well as the use of bioinformatics tools in the annotation and prioritization of circRNA and highlight the participation of exosomal circRNAs in HCC metastasis and drug resistance.

Breakthroughs and Applications of Organ-on-a-Chip Technology

Organ-on-a-chip (OOAC) is an emerging technology based on microfluid platforms and in vitro cell culture that has a promising future in the healthcare industry. The numerous advantages of OOAC over conventional systems make it highly popular. The chip is an innovative combination of novel technologies, including lab-on-a-chip, microfluidics, biomaterials, and tissue engineering. This paper begins by analyzing the need for the development of OOAC followed by a brief introduction to the technology. Later sections discuss and review the various types of OOACs and the fabrication materials used. The implementation of artificial intelligence in the system makes it more advanced, thereby helping to provide a more accurate diagnosis as well as convenient data management. We introduce selected OOAC projects, including applications to organ/disease modelling, pharmacology, personalized medicine, and dentistry. Finally, we point out certain challenges that need to be surmounted in order to further develop and upgrade the current systems.

Optimization of Microflow LC Coupled with Scanning SWATH and Its Application in Hepatocellular Carcinoma Tissues

Scanning SWATH coupled with normal-flow LC has been recently introduced for high-content, high-throughput proteomics analysis, which requires a relatively large amount of sample injection. Here we established the microflow LC coupled with Scanning SWATH for samples with relatively small quantities. First, we optimized several key parameters of the LC and MS settings, including C18 particle size for the analytical column, LC gradient and flow rate, as well as effective ion accumulation time and isolation window width for MS acquisition. We then compared the optimized Scanning SWATH method with the conventional variable window SWATH (referred to as SWATH) method. Results showed that the total ion chromatogram signals in Scanning SWATH were 10 times higher than that of SWATH, and Scanning SWATH identified 12.2-22.2% more peptides than SWATH. Finally, we employed 120 min Scanning SWATH to acquire the proteomes of 62 formalin-fixed, paraffin-embedded (FFPE) tissue samples from 31 patients with hepatocellular carcinoma (HCC). Altogether, 92 334 peptides and 8516 proteins were quantified. Besides the reported biomarkers, including ANXA2, MCM7, SUOX, and AKR1B10, we identified new potential HCC biomarkers such as CST5, TP53, CEBPB, and E2F4. Taken together, we present an optimal workflow integrating microflow LC and Scanning SWATH that effectively improves the protein identification and quantitation.

Smart nanomaterials for cancer diagnosis and treatment

Innovations in nanomedicine has guided the improved outcomes for cancer diagnosis and therapy. However, frequent use of nanomaterials remains challenging due to specific limitations like non-targeted distribution causing low signal-to-noise ratio for diagnostics, complex fabrication, reduced-biocompatibility, decreased photostability, and systemic toxicity of nanomaterials within the body. Thus, better nanomaterial-systems with controlled physicochemical and biological properties, form the need of the hour. In this context, smart nanomaterials serve as promising solution, as they can be activated under specific exogenous or endogenous stimuli such as pH, temperature, enzymes, or a particular biological molecule. The properties of smart nanomaterials make them ideal candidates for various applications like biosensors, controlled drug release, and treatment of various diseases. Recently, smart nanomaterial-based cancer theranostic approaches have been developed, and they are displaying better selectivity and sensitivity with reduced side-effects in comparison to conventional methods. In cancer therapy, the smart nanomaterials-system only activates in response to tumor microenvironment (TME) and remains in deactivated state in normal cells, which further reduces the side-effects and systemic toxicities. Thus, the present review aims to describe the stimulus-based classification of smart nanomaterials, tumor microenvironment-responsive behaviour, and their up-to-date applications in cancer theranostics. Besides, present review addresses the development of various smart nanomaterials and their advantages for diagnosing and treating cancer. Here, we also discuss about the drug targeting and sustained drug release from nanocarriers, and different types of nanomaterials which have been engineered for this intent. Additionally, the present challenges and prospects of nanomaterials in effective cancer diagnosis and therapeutics have been discussed.

Cutting-Edge Platforms for Analysis of Immune Cells in the Hepatic Microenvironment-Focus on Tumor-Associated Macrophages in Hepatocellular Carcinoma

The role of tumor-associated macrophages (TAMs) in the pathogenesis of hepatocellular carcinoma (HCC) is poorly understood. Most studies rely on platforms that remove intrahepatic macrophages from the microenvironment prior to evaluation. Cell isolation causes activation and phenotypic changes that may not represent their actual biology and function in situ. State-of-the-art methods provides new strategies to study TAMs without losing the context of tissue architecture and spatial relationship with neighboring cells. These technologies, such as multispectral imaging (e.g., Vectra Polaris), mass cytometry by time-of-flight (e.g., Fluidigm CyTOF), cycling of fluorochromes (e.g., Akoya Biosciences CODEX/PhenoCycler-Fusion, Bruker Canopy, Lunaphore Comet, and CyCIF) and digital spatial profiling or transcriptomics (e.g., GeoMx or Visium, Vizgen Merscope) are being utilized to accurately assess the complex cellular network within the tissue microenvironment. In cancer research, these platforms enable characterization of immune cell phenotypes and expression of potential therapeutic targets, such as PDL-1 and CTLA-4. Newer spatial profiling platforms allow for detection of numerous protein targets, in combination with whole transcriptome analysis, in a single liver biopsy tissue section. Macrophages can also be specifically targeted and analyzed, enabling quantification of both protein and gene expression within specific cell phenotypes, including TAMs. This review describes the workflow of each platform, summarizes recent research using these approaches, and explains the advantages and limitations of each.

Generation of An Induced Pluripotent Stem Cell Line from Human Liver Fibroblasts from A Patient with Combined Hepatocellular-Cholangiocarcinoma

Objective

Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare type of primary liver cancer with characteristics of both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC). The pathogenesis of cHCCCC is poorly understood due to a shortage of suitable in vitro models. Due to scarce availability of human liver tissue, induced pluripotent stem cells (iPSCs) are a useful alternative source to produce renewable liver cells. For use in the development of liver pathology models, here we successfully developed and evaluated iPSCs from liver fibroblasts of a patient with cHCC-CC.

Materials and Methods

In this experimental study, human liver fibroblasts (HLFs) were obtained from the liver biopsy of a 69-year-old male patient with cHCC-CC and transduced with a retroviral cocktail that included four factors - OCT4, SOX2, KLF4, and c-MYC (OSKM). Pluripotency of the iPSCs was determined by alkaline phosphatase (AP) staining, quantitative real-time polymerase chain reaction (PCR), and immunofluorescence. We induced in vitro embryoid body (EB) formation and performed an in vivo teratoma assay to confirm their differentiation capacity into the three germ layers.

Results

HLF iPSCs derived from the cHCC-CC patient displayed typical iPSC-like morphology and pluripotency marker expression. The proficiency of the iPSCs to differentiate into three germ layers was assessed both in vitro and in vivo. Compared to normal control iPSCs, differentiated HLF iPSCs showed increased expressions of HCC markers alpha-fetoprotein (AFP) and Dickkopf-1 (DKK1) and the CC marker cytokeratin 7 (CK7), and a decreased expression of the CC tumour suppressor SRY-related HMG-box 17 (SOX17).

Conclusion

We established HLF iPSCs using liver fibroblasts from a patient with cHCC-CC for the first time. The HLF iPSCs maintained marker expression in the patient when differentiated into EBs. Therefore, HLF iPSCs may be a sustainable cell source for modelling cHCC-CC and beneficial for understanding liver cancer pathology and developing therapies for cHCC-CC treatment.

Quantitative Expression of Key Cancer Markers in the AS-30D Hepatocarcinoma Model

Hepatocellular carcinoma is one of the cancers with the highest mortality rate worldwide. HCC is often diagnosed when the disease is already in an advanced stage, making the discovery and implementation of biomarkers for the disease a critical aim in cancer research. In this study, we aim to quantify the transcript levels of key signaling molecules relevant to different pathways known to participate in tumorigenesis, with special emphasis on those related to cancer hallmarks and epithelial-mesenchymal transition, using as a model the murine transplantable hepatocarcinoma AS-30D. Using qPCR to quantify the mRNA levels of genes involved in tumorigenesis, we found elevated levels for Tgfb1 and Spp1, two master regulators of EMT. A mesenchymal signature profile for AS-30D cells is also supported by the overexpression of genes encoding for molecules known to be associated to aggressiveness and metastatic phenotypes such as Foxm1, C-met, and Inppl1. This study supports the use of the AS-30D cells as an efficient and cost-effective model to study gene expression changes in HCC, especially those associated with the EMT process.

A novel model based on interleukin 6 and insulin-like growth factor II for detection of hepatocellular carcinoma associated with hepatitis C virus

BACKGROUND

The coexistence of cirrhosis complicates the early detection of hepatocellular carcinoma (HCC). Thus, novel biomarkers for HCC early detection are needed urgently. Traditionally, HCC detection is carried out by evaluating alpha-fetoprotein (AFP) levels combined with imaging techniques. This work aimed to assess interleukin (IL-6) and insulin-like growth factor 2 (IGF 2) as possible HCC markers in comparison to AFP in patients with and without HCC.

RESULTS

ROC analysis showed that IGF2 had the highest area under the curve (AUC) for discriminating HCC from liver cirrhosis (0.86), followed by IL6 (0.82), AFP (0.72), and platelet count (0.6). A four-marker model was developed and discriminated HCC from liver cirrhosis with an AUC of 0.97. The best cut-off was 1.28, at which sensitivity and specificity were 90% and 85%, respectively. For small tumor (< 2 cm), the model had an AUC of 0.95 compared to AFP (0.72). Also, the model achieved perfect performance with AUC of 0.93, 0.94, and 0.95 for BCLC (0-A), CLIP (0-1), and Okuda (stage I), respectively, compared to AFP (AUC of 0.71, 0.69, and 0.67, respectively).

CONCLUSIONS

The four markers may serve as a diagnostic model for HCC early stages and help overcome AFP poor sensitivity.

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

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

Identifying novel transcript biomarkers for hepatocellular carcinoma (HCC) using RNA-Seq datasets and machine learning

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death in the world owing to limitations in its prognosis. The current prognosis approaches include radiological examination and detection of serum biomarkers, however, both have limited efficiency and are ineffective in early prognosis. Due to such limitations, we propose to use RNA-Seq data for evaluating putative higher accuracy biomarkers at the transcript level that could help in early prognosis.

METHODS

To identify such potential transcript biomarkers, RNA-Seq data for healthy liver and various HCC cell models were subjected to five different machine learning algorithms: random forest, K-nearest neighbor, Naïve Bayes, support vector machine, and neural networks. Various metrics, namely sensitivity, specificity, MCC, informedness, and AUC-ROC (except for support vector machine) were evaluated. The algorithms that produced the highest values for all metrics were chosen to extract the top features that were subjected to recursive feature elimination. Through recursive feature elimination, the least number of features were obtained to differentiate between the healthy and HCC cell models.

RESULTS

From the metrics used, it is demonstrated that the efficiency of the known protein biomarkers for HCC is comparatively lower than complete transcriptomics data. Among the different machine learning algorithms, random forest and support vector machine demonstrated the best performance. Using recursive feature elimination on top features of random forest and support vector machine three transcripts were selected that had an accuracy of 0.97 and kappa of 0.93. Of the three transcripts, two were protein coding (PARP2-202 and SPON2-203) and one was a non-coding transcript (CYREN-211). Lastly, we demonstrated that these three selected transcripts outperformed randomly taken three transcripts (15,000 combinations), hence were not chance findings, and could then be an interesting candidate for new HCC biomarker development.

CONCLUSION

Using RNA-Seq data combined with machine learning approaches can aid in finding novel transcript biomarkers. The three biomarkers identified: PARP2-202, SPON2-203, and CYREN-211, presented the highest accuracy among all other transcripts in differentiating the healthy and HCC cell models. The machine learning pipeline developed in this study can be used for any RNA-Seq dataset to find novel transcript biomarkers. Code: www.github.com/rajinder4489/ML_biomarkers.

Landscape of Prognostic m6A RNA Methylation Regulators in Hepatocellular Carcinoma to Aid Immunotherapy

Background: Hepatocellular carcinoma (HCC) is the sixth most common malignancy with a high mortality worldwide. N6-methyladenosine (m6A) may participate extensively in tumor progression.

Methods: To reveal the landscape of tumor immune microenvironment (TIME), ESTIMATE analysis, ssGSEA algorithm, and the CIBERSORT method were used. Taking advantage of consensus clustering, two different HCC categories were screened. We analyzed the correlation of clustering results with TIME and immunotherapy. Then, we yielded a risk signature by systematical bioinformatics analyses. Immunophenoscore (IPS) was implemented to estimate the immunotherapeutic significance of risk signature.

Results: The m6A-based clusters were significantly correlated with overall survival (OS), immune score, immunological signature, immune infiltrating, and ICB-associated genes. Risk signature possessed robust prognostic validity and significantly correlated with TIME context. IPS was employed as a surrogate of immunotherapeutic outcome, and patients with low-risk scores showed significantly higher immunophenoscores.

Conclusion: Collectively, m6A-based clustering subtype and signature was a robust prognostic indicator and correlated with TIME and immunotherapy, providing novel insight into antitumor management and prognostic prediction in HCC.

Tumor metabolism and associated serum metabolites define prognostic subtypes of Asian hepatocellular carcinoma

Treatment effectiveness in hepatocellular carcinoma (HCC) depends on early detection and precision-medicine-based patient stratification for targeted therapies. However, the lack of robust biomarkers, particularly a non-invasive diagnostic tool, precludes significant improvement of clinical outcomes for HCC patients. Serum metabolites are one of the best non-invasive means for determining patient prognosis, as they are stable end-products of biochemical processes in human body. In this study, we aimed to identify prognostic serum metabolites in HCC. To determine serum metabolites that were relevant and representative of the tissue status, we performed a two-step correlation analysis to first determine associations between metabolic genes and tissue metabolites, and second, between tissue metabolites and serum metabolites among 49 HCC patients, which were then validated in 408 additional Asian HCC patients with mixed etiologies. We found that certain metabolic genes, tissue metabolites and serum metabolites can independently stratify HCC patients into prognostic subgroups, which are consistent across these different data types and our previous findings. The metabolic subtypes are associated with β-oxidation process in fatty acid metabolism, where patients with worse survival outcome have dysregulated fatty acid metabolism. These serum metabolites may be used as non-invasive biomarkers to define prognostic tumor molecular subtypes for HCC.

Identification of Cancer Cell Stemness-Associated Long Noncoding RNAs for Predicting Prognosis of Patients with Hepatocellular Carcinoma

Long noncoding RNAs (lncRNAs) are emerging as crucial contributors to the development of hepatocellular carcinoma (HCC) and are involved in the stemness regulation of liver cancer stem cells (LCSCs). However, cancer cell stemness-associated lncRNAs and their relevance in prediction of clinical prognosis remain largely unexplored. In this study, through the transcriptome-wide screen, we identified a total of 136 LCSC-associated lncRNAs. We evaluated the prognostic value of these lncRNAs and optimally established an 11-lncRNA (including AC008622.2, AC015908.3, AC020915.2, AC025176.1, AC026356.2, AC099850.3, CYTOR, DDX11-AS1, HTR2A-AS1, LINC02870, and SNHG3) prognostic risk model. Multivariate analysis revealed that the risk score is an independent prognostic predictor for HCC patients, which outperforms the traditional clinical pathological factors. Gene set enrichment analysis suggested that the high-risk score reflects the alteration of pathways involved in cell cycle, oxidative phosphorylation, and metabolism. Furthermore, functional studies on SNHG12, the leading candidate of the risk lncRNAs, revealed that knockdown of SNHG12 reduces the abilities of HCC cells stemness, proliferation, migration, and invasion. In summary, we constructed a prognostic risk model based on 11 LCSC-associated lncRNAs, which might be a promising prognostic predictor for HCC patients and highlight the involvement of lncRNAs in LCSC-associated treatment strategy in clinical practice.

Identification of Seven-Gene Hypoxia Signature for Predicting Overall Survival of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is ranked fifth among the most common cancer worldwide. Hypoxia can induce tumor growth, but the relationship with HCC prognosis remains unclear. Our study aims to construct a hypoxia-related multigene model to predict the prognosis of HCC.

Methods

RNA-seq expression data and related clinical information were download from TCGA database and ICGC database, respectively. Univariate/multivariate Cox regression analysis was used to construct prognostic models. KM curve analysis, and ROC curve were used to evaluate the prognostic models, which were further verified in the clinical traits and ICGC database. GSEA analyzed pathway enrichment in high-risk groups. Nomogram was constructed to predict the personalized treatment of patients. Finally, real-time fluorescence quantitative PCR (RT-qPCR) was used to detect the expressions of KDELR3 and SCARB1 in normal hepatocytes and 4 HCC cells. The expressions of SCARB1 in hepatocellular carcinoma tissue in 46 patients were detected by immunohistochemistry, and the correlation between its expressions and disease free survival of patient was calculated.

Results

Through a series of analyses, seven prognostic markers related to HCC survival were constructed. HCC patients were divided into the high and low risk group, and the results of KM curve showed that there was a significant difference between the two groups. Stratified analysis, found that there were significant differences in risk values of different ages, genders, stages and grades, which could be used as independent predictors. In addition, we assessed the risk value in the clinical traits analysis and found that it could accelerate the progression of cancer, while the results of GSEA enrichment analysis showed that the high-risk group patients were mainly distributed in the cell cycle and other pathways. Then, Nomogram was constructed to predict the overall survival of patients. Finally, RT-qPCR showed that KDELR3 and SCARB1 were highly expressed in HepG2 and L02, respectively. Results of IHC staining showed that SCARB1 was highly expressed in cancer tissues compared to adjacent normal liver tissues and its expression was related to hepatocellular carcinoma differentiation status. The Kaplan-Meier survival showed a poor percent survival in the SCARB1 high group compared to that in the SCARB1 low group.

Conclusion

This study provides a potential diagnostic indicator for HCC patients, and help clinicians to deepen the comprehension in HCC pathogenesis so as to make personalized medical decisions.

Additional Inhibition of Wnt/β-Catenin Signaling by Metformin in DAA Treatments as a Novel Therapeutic Strategy for HCV-Infected Patients

Chronic hepatitis C virus (HCV) infection causes hepatocellular carcinoma (HCC). Although HCV clearance has been improved by the advent of direct-acting antiviral agents (DAA), retrospective studies have shown that the risk of subsequent HCC, while considerably decreased compared with active HCV infection, persists after DAA regimens. However, either the mechanisms of how chronic HCV infection causes HCC or the factors responsible for HCC development after viral eradication in patients with DAA treatments remain elusive. We reported an in vitro model of chronic HCV infection and determined Wnt/β-catenin signaling activation due to the inhibition of GSK-3β activity via serine 9 phosphorylation (p-ser9-GSK-3β) leading to stable non-phosphorylated β-catenin. Immunohistochemical staining demonstrated the upregulation of both β-catenin and p-Ser9-GSK-3β in HCV-induced HCC tissues. Chronic HCV infection increased proliferation and colony-forming ability, but knockdown of β-catenin decreased proliferation and increased apoptosis. Unexpectedly, Wnt/β-catenin signaling remained activated in chronic HCV-infected cells after HCV eradication by DAA, but metformin reversed it through PKA/GSK-3β-mediated β-catenin degradation, inhibited colony-forming ability and proliferation, and increased apoptosis, suggesting that DAA therapy in combination with metformin may be a novel therapy to treat HCV-associated HCC where metformin suppresses Wnt/β-catenin signaling for HCV-infected patients.

Galectin-3 is not useful for hepatocellular carcinoma surveillance in cirrhotic patients but it may be a marker of cirrhosis development

Aim of the study

Ultrasound surveillance for hepatocellular carcinoma (HCC) among cirrhotic patients is the currently used modality but it is operator dependent. Combining a tumor marker with ultrasound may improve sensitivity for early HCC detection. Our aim was to assess the galectin-3 level among HCC and cirrhotic patients on top of chronic hepatitis C to evaluate its possible role as a tumor marker for HCC surveillance among cirrhotic patients.

Material and methods

The study was conducted on 160 subjects. They were grouped as follows: group 1: 40 patients with HCC secondary to liver cirrhosis on top of chronic hepatitis C; group 2: 40 patients with cirrhosis secondary to chronic hepatitis C; group 3: 40 patients with chronic hepatitis C without advanced fibrosis; group 4: 40 healthy controls. Serum galectin-3 levels were determined in all subjects using ELISA.

Results

Serum galectin-3 level was significantly higher in HCC patients than in those with chronic hepatitis C (p < 0.001). Also it was significantly higher among cirrhotic patients than in patients with chronic hepatitis C (p < 0.001). But on comparing HCC patients with cirrhotic patients, serum galectin-3 levels were not significantly different (p = 0.926).

Conclusions: Galectin-3 levels cannot be used as an additional method for surveillance of HCC among cirrhotic patients.

High Expression of LINC01268 is Positively Associated with Hepatocellular Carcinoma Progression via Regulating MAP3K7

Objective

As one of the most common neoplastic diseases, hepatocellular carcinoma (HCC) has a high morbidity and mortality, which seriously threatens human health and places a heavy burden on society and medical care. At present, effective early diagnosis, prognosis and treatment of HCC are limited. Altered gene expression patterns of lncRNA are associated with the occurrence, development and prognosis of various malignancies, including HCC. The aim of this study was to investigate the correlation between the expression of LINC01268 and HCC, and to elucidate the potential underlying molecular mechanism.

Methods

Expression level and localization of LINC01268 in human liver cancer cells and HCC tissues were investigated using RT-qPCR and fluorescent in situ hybridization (FISH), respectively. Correlation of expression levels of LINC01268 and MAP3K7 with differentiation and poor overall patient survival of HCC were analyzed using in house collected and publicly available HCC tissue data. RT-qPCR and Western blot were applied to inspect the effects of depletion and overexpression of LINC01268 on MAP3K7 expression. HCC cell proliferation and apoptosis were also investigated by simultaneous overexpression of LINC01268 and knockdown of MAP3K7, in order to delineate that MAP3K7 is a downstream effector of LINC01268.

Results

In this study, we identified that LINC01268 was highly expressed in HCC cell lines and tissues. High LINC01268 expression level was associated with lower HCC nodule number, moderate/poor differentiation and poor overall survival. Knockdown of LINC01268 inhibited the proliferation of HCC cells, which was enhanced by overexpression of LINC01268. Co-expression analysis implied an interaction between LINC01268 and MAP3K7. Similar to LINC01268, MAP3K7 was highly expressed in HCC cells, and positively correlated with moderate/poor differentiation as well as poor prognosis. Knockdown of LINC01268 in HCC cell lines led to reduction of MAP3K7 at both mRNA and protein levels. Phenotypic effects due to LINC01268 overexpression in HCC cells were reversed by knockdown of MAP3K7.

Conclusion

Taken together, the abnormal high expression of LINC01268 is associated with HCC progression via regulating MAP3K7, suggesting LINC01268 as a novel marker for HCC prognosis and potentially a new therapeutic target.

Serum Angiopoietin 2 acts as a diagnostic and prognostic biomarker in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is typically accompanied by abundant arterial blood flow. Although angiogenic growth factors such as Angiopoietin 2 (Ang2) play a central role in tumor angiogenesis in HCC, the role of serum Ang2 as a biomarker in HCC remains unclear. In this study, we aimed to investigate the potential of Ang2 as a diagnostic and prognostic biomarker in HCC using a sandwich enzyme-linked immunosorbent assay (ELISA). The median Ang2 levels in controls (n=20), chronic liver disease patients (n=98), and HCC patients (n=275) were 1.58, 2.33, and 3.53 ng/mL, respectively. The optimal cut-off value of Ang2 was determined as 3.5 ng/mL by receiver operating curve analysis. The sensitivity, specificity, and accuracy of Ang2 for HCC detection were 50.9, 83.7, and 59.5%, respectively. Spearman's rank correlation coefficient analysis demonstrated only a weak correlation between Ang2 serum levels and alpha-fetoprotein (AFP) or des-gamma-carboxy prothrombin (DCP) serum levels. The diagnostic value of Ang2 was comparable to those of other existing markers. In addition, 24 out of 73 patients with normal AFP and DCP levels (32.9%) demonstrated abnormally high Ang2 levels (≥3.5 ng/mL). Although no significant difference in overall survival was found between Ang2^high and Ang2^low patients with curative ablation therapy, recurrence-free survival (RFS) in Ang2^high patients was observed to be significantly shorter than those in Ang2^low patients. Multivariate analysis demonstrated that high serum Ang2 levels (≥3.5 ng/mL) and the presence of multiple tumors were poor prognostic factors. In conclusion, our findings indicate that serum Ang2 is a potential novel biomarker for both diagnosis and prognosis in HCC.

Profibrotic Signaling and HCC Risk during Chronic Viral Hepatitis: Biomarker Development

Despite breakthroughs in antiviral therapies, chronic viral hepatitis B and C are still the major causes of liver fibrosis and hepatocellular carcinoma (HCC). Importantly, even in patients with controlled infection or viral cure, the cancer risk cannot be fully eliminated, highlighting a persisting oncogenic pressure imposed by epigenetic imprinting and advanced liver disease. Reliable and minimally invasive biomarkers for early fibrosis and for residual HCC risk in HCV-cured patients are urgently needed. Chronic infection with HBV and/or HCV dysregulates oncogenic and profibrogenic signaling within the host, also displayed in the secretion of soluble factors to the blood. The study of virus-dysregulated signaling pathways may, therefore, contribute to the identification of reliable minimally invasive biomarkers for the detection of patients at early-stage liver disease potentially complementing existing noninvasive methods in clinics. With a focus on virus-induced signaling events, this review provides an overview of candidate blood biomarkers for liver disease and HCC risk associated with chronic viral hepatitis and epigenetic viral footprints.

Identification of immune-related lncRNA signature for predicting immune checkpoint blockade and prognosis in hepatocellular carcinoma

BACKGROUND

An increasing body of evidence has supported that long non-coding RNAs (lncRNAs) can play as essential roles of various physiological process and pathological diseases. We aimed to construct a robust immune-associated lncRNA signature associated with the prognosis for HCC survival prediction.

METHODS

7 immune-associated lncRNAs presenting significant correlation with survival were screened through stepwise univariate Cox regression and LASSO algorithm, and multivariate Cox regression. Kaplan-Meier analysis, proportional hazards model, and ROC analyses further conducted. Gene set enrichment analysis (GSEA) was applied for functional annotation. We conducted quantitative real-time polymerase chain reaction to determine NRAV expression and preliminarily explored the latent role of NRAV in prognosis of HCC patients.

RESULTS

Finally, 7 immune-related lncRNA signature composed of AC007405.3, AC023157.3, NRAV, CASC19, MSC-AS1, GASAL1, and LINC00942 were validated. This lncRNAs signature can serve as an independent predictive biomolecular factor. This signature was further confirmed in the validation group and the entire cohort. We demonstrated that NRAV was significantly upregulated in HCC cell lines and it may serve as a key regulator in HCC. Our signature was associated to apoptosis and immunologic characteristics. This signature mediated immune cell infiltration (i.e., Dendritic, etc.,) and immune checkpoint blockade (ICB) immunotherapy-related molecules (i.e., CD274, etc.,).

CONCLUSION

This immune-related lncRNA signature possesses promising prognostic value in HCC and may have the potentiality to predict clinical outcome of ICB immunotherapy.

SUMO-Activating Enzyme Subunit 1 (SAE1) Is a Promising Diagnostic Cancer Metabolism Biomarker of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most diagnosed malignancies and a leading cause of cancer-related mortality globally. This is exacerbated by its highly aggressive phenotype, and limitation in early diagnosis and effective therapies. The SUMO-activating enzyme subunit 1 (SAE1) is a component of a heterodimeric small ubiquitin-related modifier that plays a vital role in SUMOylation, a post-translational modification involving in cellular events such as regulation of transcription, cell cycle and apoptosis. Reported overexpression of SAE1 in glioma in a stage-dependent manner suggests it has a probable role in cancer initiation and progression. In this study, hypothesizing that SAE1 is implicated in HCC metastatic phenotype and poor prognosis, we analyzed the expression of SAE1 in several cancer databases and to unravel the underlying molecular mechanism of SAE1-associated hepatocarcinogenesis. Here, we demonstrated that SAE1 is over-expressed in HCC samples compared to normal liver tissue, and this observed SAE1 overexpression is stage and grade-dependent and associated with poor survival. The receiver operating characteristic analysis of SAE1 in TCGA−LIHC patients (n = 421) showed an AUC of 0.925, indicating an excellent diagnostic value of SAE1 in HCC. Our protein-protein interaction analysis for SAE1 showed that SAE1 interacted with and activated oncogenes such as PLK1, CCNB1, CDK4 and CDK1, while simultaneously inhibiting tumor suppressors including PDK4, KLF9, FOXO1 and ALDH2. Immunohistochemical staining and clinicopathological correlate analysis of SAE1 in our TMU-SHH HCC cohort (n = 54) further validated the overexpression of SAE1 in cancerous liver tissues compared with ‘normal’ paracancerous tissue, and high SAE1 expression was strongly correlated with metastasis and disease progression. The oncogenic effect of upregulated SAE1 is associated with dysregulated cancer metabolic signaling. In conclusion, the present study demonstrates that SAE1 is a targetable cancer metabolic biomarker with high potential diagnostic and prognostic implications for patients with HCC.

Multi-omics analysis of hiPSCs-derived HLCs matured on-chip revealed patterns typical of liver regeneration

Maturation of human-induced pluripotent stem cells (hiPSCs)-derived hepatocytes-like cells (HLCs) toward a complete hepatocyte phenotype remains a challenge as primitiveness patterns are still commonly observed. In this study, we propose a modified differentiation protocol for those cells which includes a prematuration in Petri dishes and a maturation in microfluidic biochip. For the first time, a large range of biomolecular families has been extracted from the same sample to combine transcriptomic, proteomic, and metabolomic analysis. After integration, these datasets revealed specific molecular patterns and highlighted the hepatic regeneration profile in biochips. Overall, biochips exhibited processes of cell proliferation and inflammation (via TGFB1) coupled with anti-fibrotic signaling (via angiotensin 1-7, ATR-2, and MASR). Moreover, cultures in this condition displayed physiological lipid-carbohydrate homeostasis (notably via PPAR, cholesterol metabolism, and bile synthesis) coupled with cell respiration through advanced oxidative phosphorylation (through the overexpression of proteins from the third and fourth complex). The results presented provide an original overview of the complex mechanisms involved in liver regeneration using an advanced in vitro organ-on-chip technology.

Detection of Circulating Tumor Cells and Their Implications as a Biomarker for Diagnosis, Prognostication, and Therapeutic Monitoring in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is among the leading causes of worldwide cancer-related morbidity and mortality. Poor prognosis of HCC is attributed primarily to tumor presentation at an advanced stage when there is no effective treatment to achieve the long term survival of patients. Currently available tests such as alpha-fetoprotein have limited accuracy as a diagnostic or prognostic biomarker for HCC. Liver biopsy provides tissue that can reveal tumor biology but it is not used routinely due to its invasiveness and risk of tumor seeding, especially in early-stage patients. Liver biopsy is also limited in revealing comprehensive tumor biology due to intratumoral heterogeneity. There is a clear need for new biomarkers to improve HCC detection, prognostication, prediction of treatment response, and disease monitoring with treatment. Liquid biopsy could be an effective method of early detection and management of HCC. Circulating tumor cells (CTCs) are cancer cells in circulation derived from the original tumor or metastatic foci, and their measurement by liquid biopsy represents a great potential in facilitating the implementation of precision medicine in patients with HCC. CTCs can be detected by a simple peripheral blood draw and potentially show global features of tumor characteristics. Various CTC detection platforms using immunoaffinity and biophysical properties have been developed to identify and capture CTCs with high efficiency. Quantitative abundance of CTCs, as well as biological characteristics and genomic heterogeneity among the CTCs, can predict disease prognosis and response to therapy in patients with HCC. This review article will discuss the currently available technologies for CTC detection and isolation, their utility in the clinical management of HCC patients, their limitations, and future directions of research.

Hepatitis B virus precore/core region mutations and genotypes among hepatitis B virus chronic carriers in South-Eastern, Nigeria

OBJECTIVES

The study aimed at detecting the prevailing hepatitis B virus (HBV) genotypes and the presence of clinically relevant mutations in the precore/core gene of the HBV DNA, among patients with chronic infection in South-eastern, Nigeria.

METHODS

A total of 72 participants with chronic HBV infection were enrolled into the study. Plasma samples from those with detectable HBV DNA were subjected to nested Polymerase Chain Reaction amplification using the precore/core specific primers. This resulted to the successful amplification and sequencing of the HBV precore/core region DNA from 16 participants. Mutation analysis on the precore/core region detected the presence of certain HBV precore/core gene mutations. Genotyping was carried out by phylogenetic analysis.

RESULTS

The precore region mutation at nucleotide position 1896, which is a G to A change resulting to a nonsense mutation, was detected in 6.25% of the participants. Other HBV precore region mutations that were detected include: G1899A, T1846A, G1862C, G1888A, T1821C, C1826T, A1827C, A1850T, C1858T, precore start codon Kozak sequence mutations and some novel core region mutations such as G/A1951T and G1957A. Genotyping revealed the existence of HBV genotype/subgenotype A1 (87.5%) and D (12.5%) among the participants. There was no significant difference in the occurrence of specific precore/core mutations among the HBV/hepatitis C virus dually infected and HBV mono-infected participants.

CONCLUSION

The data suggest the likelihood of a more severe outcome of hepatitis caused by HBV in South-eastern Nigeria due to the occurrence of a variety of precore/core mutation, which resulted to HBeAg-negative chronic HBV infection among the participants.

Electrochemical Biosensors for Detection of MicroRNA as a Cancer Biomarker: Pros and Cons

Cancer is the second most fatal disease in the world and an early diagnosis is important for a successful treatment. Thus, it is necessary to develop fast, sensitive, simple, and inexpensive analytical tools for cancer biomarker detection. MicroRNA (miRNA) is an RNA cancer biomarker where the expression level in body fluid is strongly correlated to cancer. Various biosensors involving the detection of miRNA for cancer diagnosis were developed. The present review offers a comprehensive overview of the recent developments in electrochemical biosensor for miRNA cancer marker detection from 2015 to 2020. The review focuses on the approaches to direct miRNA detection based on the electrochemical signal. It includes a RedOx-labeled probe with different designs, RedOx DNA-intercalating agents, various kinds of RedOx catalysts used to produce a signal response, and finally a free RedOx indicator. Furthermore, the advantages and drawbacks of these approaches are highlighted.

Aglycosylated antibody-producing mice for aglycosylated antibody-lectin coupled immunoassay for the quantification of tumor markers (ALIQUAT)

Targeting aberrant glycoforms has been validated for in vitro cancer diagnostic development, and several assays are currently in routine clinical use. Because N-glycans in Fc region of antibodies show cross-reactivity with various lectins, high-quality aglycosylated antibodies are exceptionally important for immunoassay platform-based quantitative measurements. Previously, aglycosylated antibody acquisition relied on incomplete, uneconomical and onerous enzymatic and chemical methods. Here, we edited four murine immunoglobulin G genes using adenine base-editing and homology-directed recombination (HDR)-mediated gene editing methods to generate aglycosylated antibody-producing mice. Resulting aglycosylated antibodies showed required analytical performances without compromised protein stability. Thus, this aglycosylated monoclonal antibody-lectin coupled immunoassay for the quantification of tumour markers (ALIQUAT) method can provide a robust, versatile and accessible immunoassay platform to quantify specific glycoforms in precision cancer diagnostics. Moreover, the engineered mice can be used as a host to produce various aglycosylated antibodies in a convenient and robust fashion, thereby expanding in vitro diagnostic development opportunities that utilize glycoforms as a disease-specific biomarkers.

Lee et al. describe the generation of aglycosylated antibody-producing mice. These aglycosylated antibodies, lacking glycans prevent unwanted interactions with the lectins, and are used as reagents in a tool they developed called ALIQUAT. This aglycosylated antibody and lectin-based immunoassay diagnostic platform can be used to detect disease specific glycan biomarkers.

Recent progress on developing of plasmon biosensing of tumor biomarkers: Efficient method towards early stage recognition of cancer

Cancer is the second most extended disease with an improved death rate over the past several time. Due to the restrictions of cancer analysis methods, the patient's real survival rate is unknown. Therefore, early stage diagnosis of cancer is crucial for its strong detection. Bio-analysis based on biomarkers may help to overcome the problem Biosensors with high sensitivity and specificity, low-cost, high analysis speed and minimum limit of detection are practical alternatives for laboratory tests. Surface plasmon resonance (SPR) is reaching a maturity level sufficient for their application in detection and determination cancer biomarkers in clinical samples. This review discusses main concepts and performance characteristics of SPR biosensor. Mainly, it focuses on newly emerged enhanced SPR biosensors towards high-throughput and ultrasensitive screening of cancer biomarkers such as PSA, α-fetoprotein, CEA, CA125, CA 15-3, HER2, ctDNA, ALCAM, hCG, VEGF, TNF, Interleukin, IFN-γ, CD24, CD44, Ferritin, COLIV using labeling processes with focusing on the future application in biomedical research and clinical diagnosis. This article reviews current status of the field, showcasing a series of early successes in the application of SPR for clinical bioanalysis of cancer related biomolecules and detailing a series of considerations regarding sensing schemes, exposing issues with analysis in biofluids, while providing an outlook of the challenges currently associated with plasmonic materials, bioreceptor selection, microfluidics, and validation of a clinical bioassay for applying SPR biosensors to clinical samples. Research opportunities are proposed to further advance the field and transition SPR biosensors from research proof-of-concept stage to actual clinical usage.

Integrative Analysis to Identify Race-Associated Metabolite Biomarkers for Hepatocellular Carcinoma

Compared to European-Americans (EAs), the incidence of hepatocellular carcinoma (HCC) is higher in African-Americans (AAs) and is associated with more advanced tumor stage at diagnosis and lower survival rates. 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 to identify candidate biomarkers that distinguish HCC from cirrhotic patients in a race specific manner. Through integrative analysis of transcriptomic and metabolomic data, we investigated candidate metabolite biomarkers that are specific to AAs and EAs. The results from this demonstrate the utility of integrating transcriptomic and metabolomic data to prioritize clinically and biologically relevant metabolite biomarkers that can increase understanding of molecular mechanisms driving HCC in different racial groups.

Annona senegalensis extract demonstrates anticancer properties in N-diethylnitrosamine-induced hepatocellular carcinoma in male Wistar rats

BACKGROUND

Hepatocellular carcinoma (HCC) is a common and leading cancer around the globe. This study investigated the anticancer properties of extract of Annona senegalensis in N-diethylnitrosamine (DEN) - induced hepatocellular carcinoma in male Wistar rats.

METHODS

Rats were simultaneously induced with a combination of 100 mg/kg b.wt of DEN and 0.5 mL/kg of carbon tetrachloride (CCl₄) intraperitoneally once a week for three weeks in a row. Thereafter, animals were treated with 100 mg/kg and 200 mg/kg b.wt of A. senegalensis extract daily for 21days. Analysis using gas chromatography-mass spectrometry (GC-MS) was carried out to discover the phytoconstituents contained in the n-hexane extract of A. senegelensis. The levels of liver function parameters and antioxidant enzyme activities were determined via spectrophotometric analysis. Reverse transcriptase-polymerase chain reaction technique was used to assess the gene expression patterns of BCL-2, P53, P21, IL-6, FNTA, VEGF, HIF, AFP, XIAP, and EGFR mRNAs.

RESULTS

Treatment of DEN-induced hepatocellular carcinoma Wistar rats with the extract caused significant (p < 0.05) decrease in the activities of ALT and AST. It also resulted in a reduction of the concentration of MDA and a significant increase (p < 0.05) in SOD and GSH activities. IL-6, BCL-2, VEGF, EGFR, XIAP, FNTA, and P21 mRNAs expressions were significantly (p < 0.05) downregulated after treatment. Histopathological analysis revealed that the extract improved the liver architecture.

CONCLUSION

A. senegelensis n-hexane extract demonstrates its anticancer properties by improving the liver architecture, increasing the antioxidant defense systems, downregulating the pro-inflammatory, anti-apoptotic, angiogenic, alpha-fetoprotein and farnesyl transferase mRNAs expression and hitherto up-regulate the expression of tumor suppressor (P21 and P53) mRNAs.

Construction and Validation of Novel Diagnostic and Prognostic DNA Methylation Signatures for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent life-threatening human cancers and the leading cause of cancer-related mortality, with increased global incidence within the last decade. Identification of effective diagnostic and prognostic biomarkers would enable reliable risk stratification and efficient screening of high-risk patients, thereby facilitating clinical decision-making. Herein, we performed a comprehensive, robust DNA methylation analysis based on genome-wide DNA methylation profiling. We constructed a diagnostic signature with five DNA methylation markers, which precisely distinguished HCC patients from normal controls. Cox regression and LASSO analysis were applied to construct a prognostic signature with four DNA methylation markers. A one-to-one correlation analysis was carried out between genes of the whole genome and our prognostic signature. Exploration of the biological function and the role of the underlying significantly correlated genes was conducted. A mixed dataset of 463 HCC patients and 253 normal controls, derived from six independent datasets, was used to valid the diagnostic signature. Results showed a specificity of 96.84% and sensitivity of 96.77%. Class scores for the diagnostic signature were significantly different between normal controls, individuals with liver diseases, and HCC patients. The present signature has the potential to serve as a biomarker to monitor health in normal controls. Additionally, HCC patients were successfully separated into low-risk and high-risk groups by the prognostic signature, with a better prognosis for patients in the low-risk group. Kaplan-Meier and ROC analysis confirmed that the prognostic signature performed well. We found eight of the top ten genes to positively correlate with risk scores of the prognostic signature, and to be involved in cell cycle regulation. This eight-gene panel also served as a prognostic signature. The robust evidence presented in this study therefore demonstrates the effectiveness of the prognostic signature. In summary, we constructed diagnostic and prognostic signatures, which have potential for use in diagnosis, surveillance, and prognostic prediction for HCC patients. Eight genes that were significantly and positively correlated with the prognostic signature were strongly associated with cell cycle processes. Therefore, the prognostic signature can be used as a guide by which to measure responsiveness to cell-cycle-targeting agents.

Development and comprehensive characterization of porcine hepatocellular carcinoma for translational liver cancer investigation

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. New animal models that faithfully recapitulate human HCC phenotypes are required to address unmet clinical needs and advance standard-of-care therapeutics. This study utilized the Oncopig Cancer Model to develop a translational porcine HCC model which can serve as a bridge between murine studies and human clinical practice. Reliable development of Oncopig HCC cell lines was demonstrated through hepatocyte isolation and Cre recombinase exposure across 15 Oncopigs. Oncopig and human HCC cell lines displayed similar cell cycle lengths, alpha-fetoprotein production, arginase-1 staining, chemosusceptibility, and drug metabolizing enzyme expression. The ability of Oncopig HCC cells to consistently produce tumors in vivo was confirmed via subcutaneous (SQ) injection into immunodeficient mice and Oncopigs. Reproducible development of intrahepatic tumors in an alcohol-induced fibrotic microenvironment was achieved via engraftment of SQ tumors into fibrotic Oncopig livers. Whole-genome sequencing demontrated intrahepatic tumor tissue resembled human HCC at the genomic level. Finally, Oncopig HCC cells are amenable to gene editing for development of personalized HCC tumors. This study provides a novel, clinically-relevant porcine HCC model which holds great promise for improving HCC outcomes through testing of novel therapeutic approaches to accelerate and enhance clinical trials.

The Significance of Circulating Tumor Cells in Patients with Hepatocellular Carcinoma: Real-Time Monitoring and Moving Targets for Cancer Therapy

Hepatocellular carcinoma (HCC) is ranked as the sixth most common cancer around the world. With the emergence of the state-of-the-art modalities lately, such as liver transplantation, image-guided ablation, and chemoembolization, the death rate is still high due to high metastasis rate after therapy. Observation by biannual ultrasonography allows effective diagnosis at an early stage for candidates with no extrahepatic metastasis, but its effectiveness still remains unsatisfactory. Developing a new test with improved effectiveness and specificity is urgently needed for HCC diagnosis, especially for patients after first line therapy. Circulating tumor cells (CTCs) are a small sub-population of tumor cells in human peripheral blood, they release from the primary tumor and invade into the blood circulatory system, thereby residing into the distal tissues and survive. As CTCs have specific and aggressive properties, they can evade from immune defenses, induce gene alterations, and modulate signal transductions. Ultimately, CTCs can manipulate tumor behaviors and patient reactions to anti-tumor treatment. Given the fact that in HCC blood is present around the immediate vicinity of the tumor, which allows thousands of CTCs to release into the blood circulation daily, so CTCs are considered to be the main cause for HCC occurrence, and are also a pivotal factor for HCC prognosis. In this review, we highlight the characteristics and enrichment strategies of CTCs, and focus on the use of CTCs for tumor evaluation and management in patients with HCC.

Distribution and clinical relevance of phospholipids in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common liver cancer and featured with prominent disparity in incidence and mortality rate between male and female. It remains unclear whether alterations of phospholipids (PL) in hepatic tissues contribute to the pathogenesis, progression, and disparity of HCC.

Methods

Using electrospray ionization mass spectrometry (ESI–MS), PL profiles including 320 individual phospholipid species in 13 PL classes were determined in paired samples from HCC and adjacent benign hepatic tissues (BHT).

Results

(1) Concentrations of PLs in most of individual species, in subgroups and in total were decreased in HCC than in BHT in all studied population; (2) the number of individual PL species significantly different between HCC and BHT, and the number of PLs in six subgroups and in total decreased in HCC were more in male population than in female population; (3) panels of PL parameters (more in male population than in female population) were identified as biomarkers in differentiation of HCC from BHT, and in the prediction of pathological grade and clinical stage of HCC with high sensitivity, specificity, and accuracy.

Conclusion

It is concluded that alterations of PLs in hepatic tissues play important roles in pathogenesis, progression, and gender disparity of HCC.

Electronic supplementary material

The online version of this article (10.1007/s12072-020-10056-8) contains supplementary material, which is available to authorized users.

Serum miR-375 Levels Are Closely Related to Disease Progression from HBV Infection to HBV-Related Hepatocellular Carcinoma

Background

There is an urgent need to identify ideal serological biomarkers that not only are closely related to disease progression from hepatitis B virus (HBV) infection to hepatocellular carcinoma (HCC) but also have high specificity and sensitivity. We conducted this study to analyze whether miR-375 has a potential value in the early prediction of the progression from HBV-related hepatitis or cirrhosis to HCC.

Methods

A total of 177 participants were enrolled. Receiver operating characteristic (ROC) curve was used to evaluate the predictive capability of selected miR-375 for HBV-HCC. We upregulated the miR-375 expression in HepG2, HepG2.2.15, and HepAD38 cells to determine its effect on cellular proliferation and migration, in vitro using Cell Counting Kit-8 (CCK-8) assays.

Results

Serum miR-375 levels decreased in order from healthy controls to chronic hepatitis B (CHB) without cirrhosis, followed by cirrhosis, and finally, HBV-HCC patients. miR-375 levels were significantly lower in HBeAg-positive and HBV DNA-positive patients than negative (P < 0.05) and significantly lower in patients with elevated alpha-fetoprotein (AFP) and carcinoembryonic antigen (CEA) than normal levels (P < 0.05). miR-375 might be a biomarker for HBV-HCC, with a high area under the curve (AUC) of 0.838 (95% confidence interval (CI) 0.780 to 0.897; sensitivity: 73.9%; specificity: 93.0%). The AUC (0.768 vs. 0.584) and sensitivity (93.8% vs. 75.0%) for miR-375 were higher than those for AFP. The overexpression of miR-375 noticeably inhibited proliferation and migration in HepG2, HepG2.2.15, and HepAD38, especially in HepG2.2.15 and HepAD38, which are stably infected with HBV.

Conclusions

Serum miR-375 levels are closely related to disease progression from HBV-related hepatitis or cirrhosis to HCC.

Identification of Candidate Biomarkers for HCV Leading to Hepatocellular Carcinoma Differential Stages From Serum Samples

Background:

Hepatocellular carcinoma (HCC) is one of the most deadly liver malignancy found and Hepatitis C virus (HCV) is a prominent risk factor for this disease. Prognosis of HCC is poor; initiate the need of markers to discover therapeutic targets in HCC.

Introduction:

Clinical staging systems of HCC composed of tumor characteristics along with liver function test are important in prognosis but they are not precise. Molecular profiling can lead to a better understanding of the physiopathology of HCC and can help in the development of novel therapeutic approaches.

Methods:

64 HCC serum samples (shifted from HCV) were graded into stage I- IV; along with +ive (3 Hepatitis C) and -ive control (2 healthy persons). Proteins were separated by sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE) and differential mRNA expression from serum samples of different HCC stages was confirmed by Real Time Polymerase Chain Reaction (qPCR).

Results:

HCC serum proteins displayed differential expression of glutathione s-transferase (GST), glypican-3 (GPC3), vitronectin (VTN), and clusterin (CLU) by SDS-PAGE. GST was expressed in -ive control, while GPC3 was found in both -ive and +ive control. The qPCR analysis, display more than 0.07 fold decrease in GST in I-IV HCC stages. The highest increase in HCC stages was observed by GPC3; about 4 fold increase in I-IV stages. VTN show 1.7-3.4 fold; while CLU show 2-3.5 fold increase in four stages of HCC.

Conclusion:

GPC3, VTN and CLU in combination can be good potential markers for differentiating stages (I-IV) of HCC.

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.