Biomarkers in Hepatocellular Carcinoma: Current Status and Future Perspectives

Hepatocellular Carcinoma Surveillance Strategies: Major Guidelines and Screening Advances

BACKGROUND/OBJECTIVES

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, with prognosis and treatment outcomes that are significantly influenced by the stage at diagnosis. Early detection through regular surveillance is crucial for improving patient outcomes, especially in high-risk groups such as those with cirrhosis or chronic hepatitis B. Geographic variations in HCC risk factors, including viral hepatitis and non-alcoholic fatty liver disease (NAFLD), have led to the development of different international surveillance guidelines. This review aims to compare and evaluate the surveillance strategies proposed by the Asian Pacific Association for the Study of the Liver (APASL), the American Association for the Study of Liver Diseases (AASLD), and the European Association for the Study of the Liver and European Organization for Research and Treatment of Cancer (EASL-EORTC).

METHODS

The review examined and compared major international guidelines on HCC surveillance, focusing on patient selection, imaging modalities, and the integration of biomarkers. We also explored recent advancements in screening techniques, including artificial intelligence and emerging biomarkers, to identify future directions for improving surveillance strategies.

RESULTS

Our analysis identified key differences in the guidelines, particularly in imaging modality preferences and the use of biomarkers for early detection. While all guidelines place emphasis on high-risk populations, the inclusion criteria and surveillance intervals vary. Additionally, novel technologies such as artificial intelligence show potential to enhance the accuracy and efficiency of HCC detection.

CONCLUSIONS

This review highlights the need to harmonize the international guidelines, particularly in regard to patients with non-cirrhotic NAFLD who remain under-represented in current surveillance protocols. Future research should focus on integrating emerging technologies and biomarkers to improve early detection and overall patient outcomes.

Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach

Translational research in toxicology has significantly benefited from transcriptomic profiling, particularly in drug safety. However, its application has predominantly focused on limited organs, notably the liver, due to resource constraints. This paper presents TransTox, an innovative AI model using a generative adversarial network (GAN) method to facilitate the bidirectional translation of transcriptomic profiles between the liver and kidney under drug treatment. TransTox demonstrates robust performance, validated across independent datasets and laboratories. First, the concordance between real experimental data and synthetic data generated by TransTox was demonstrated in characterizing toxicity mechanisms compared to real experimental settings. Second, TransTox proved valuable in gene expression predictive models, where synthetic data could be used to develop gene expression predictive models or serve as "digital twins" for diagnostic applications. The TransTox approach holds the potential for multi-organ toxicity assessment with AI and advancing the field of precision toxicology.

Unveiling Endogenous Serum Peptides as Potential Biomarkers for Hepatocellular Carcinoma in Patients with Liver Cirrhosis

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, mainly associated with liver cirrhosis. Current diagnostic methods for HCC have limited sensitivity and specificity, highlighting the need for improved early detection and intervention. In this study, we used a comprehensive approach involving endogenous peptidome along with bioinformatics analysis to identify and evaluate potential biomarkers for HCC. Serum samples from 40 subjects, comprising 20 HCC cases and 20 patients with liver cirrhosis (CIRR), were analyzed. Among 2568 endogenous peptides, 67 showed significant differential expression between the HCC vs CIRR. Further analysis revealed three endogenous peptides (VMHEALHNHYTQKSLSLSPG, NRFTQKSLSLSPG, and SARQSTLDKEL) that showed far better performance compared to AFP in terms of area under the receiver operating characteristic curve (AUC), showcasing their potential as biomarkers for HCC. Additionally, endogenous peptide IAVEWESNGQPENNYKT that belongs to the precursor protein Immunoglobulin heavy constant gamma 4 was detected in 100% of the HCC group and completely absent in the CIRR group, suggesting a promising diagnostic biomarker. Gene ontology and pathway analysis revealed the potential involvement of these dysregulated peptides in HCC. These findings provide valuable insights into the molecular basis of HCC and may contribute to the development of improved diagnostic methods and therapeutic targets for HCC.

Dual role of Nrf2 signaling in hepatocellular carcinoma: promoting development, immune evasion, and therapeutic challenges

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and ranks as the third leading cause of cancer-related mortality globally. The liver performs a wide range of tasks and is the primary organ responsible for metabolizing harmful substances and foreign compounds. Oxidative stress has a crucial role in growth and improvement of hepatocellular carcinoma (HCC). Nuclear factor erythroid 2 (1)-related factor 2 (Nrf2) is an element that regulates transcription located in the cytoplasm. It controls the balance of redox reactions by stimulating the expression of many genes that depend on antioxidant response elements. Nrf2 has contrasting functions in the normal, healthy liver and HCC. In the normal liver, Nrf2 provides advantageous benefits, while in HCC it promotes harmful effects that support the growth and survival of HCC. Continuous activation of Nrf2 has been detected in HCC and promotes its advancement and aggressiveness. In addition, Activation of Nrf2 may lead to immune evasion, weakening the immune cells' ability to attack tumors and thereby promoting tumor development. Furthermore, chemoresistance in HCC, which is considered a form of stress response to chemotherapy medications, significantly impedes the effectiveness of HCC treatment. Stress management is typically accomplished by activating specific signal pathways and chemical variables. One important element in the creation of chemoresistance in HCC is nuclear factor-E2-related factor 2 (Nrf2). Nrf2 is a transcription factor that regulates the activation and production of a group of genes that encode proteins responsible for protecting cells from damage. This occurs through the Nrf2/ARE pathway, which is a crucial mechanism for combating oxidative stress within cells.

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

A new label free spiral sensor using impedance spectroscopy to characterize hepatocellular carcinoma in tissue and serum samples

Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer, predominantly affecting patients with chronic liver diseases such as hepatitis B or C-induced cirrhosis. Diagnosis typically involves blood tests (assessing liver functions and HCC biomarkers), imaging procedures such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), and liver biopsies requiring the removal of liver tissue for laboratory analysis. However, these diagnostic methods either entail lengthy lab processes, require expensive imaging equipment, or involve invasive techniques like liver biopsies. Hence, there exists a crucial need for rapid, cost-effective, and noninvasive techniques to characterize HCC, whether in serum or tissue samples. In this study, we developed a spiral sensor implemented on a printed circuit board (PCB) technology that utilizes impedance spectroscopy and applied it to 24 tissues and sera samples as proof of concept. This newly devised circuit has successfully characterized HCC and normal tissue and serum samples. Utilizing the distinct dielectric properties between HCC cells and serum samples versus the normal samples across a specific frequency range, the differentiation between normal and HCC samples is achieved. Moreover, the sensor effectively characterizes two HCC grades and distinguishes cirrhotic/non-cirrhotic samples from tissue specimens. In addition, the sensor distinguishes cirrhotic/non-cirrhotic samples from serum specimens. This pioneering study introduces Electrical Impedance Spectroscopy (EIS) spiral sensor for diagnosing HCC and liver cirrhosis in clinical serum-an innovative, low-cost, rapid (< 2 min), and precise PCB-based technology without elaborate sample preparation, offering a novel non-labeled screening approach for disease staging and liver conditions.

Identification of ABCC3 and its isoforms as potential biomarker in hepatocellular carcinoma

Liver diseases preceding the occurrence of hepatocellular carcinoma (HCC) play a crucial role in the progression and establishment of HCC, a malignancy ranked as the third deadliest cancer worldwide. Late diagnosis, alongside ineffective treatment, leads patients to a poor survival rate. This scenario argues for seeking novel alternatives for detecting liver alterations preceding the early occurrence of HCC. Experimental studies have reported that ABCC3 protein increases within HCC tumors but not in adjacent tissue. Therefore, we analyzed ABCC3 expression in public databases and investigated the presence of ABCC3 and its isoforms in plasma, urine and its release in extracellular vesicles (EVs) cargo from patients bearing cirrhosis and HCC. The UALCAN and GEPIA databases were used to analyze the expression of ABCC3 in HCC. The results were validated in a case-control study including 41 individuals bearing cirrhosis and HCC, and the levels of ABCC3 in plasma and urine samples, as well as EVs, were analyzed by ELISA and western blot. Our data showed that ABCC3 expression was higher in HCC tissues than in normal tissues and correlated with HCC grade and stage. ABCC3 protein levels were highly increased in both plasma and urine and correlated with liver disease progression and severity. The isoforms MRP3A and MRP3B of ABCC3 were significantly increased in both EVs and plasma/urine of patients bearing HCC. ABCC3 expression gradually increases in HCC tissues, and its protein levels are increased in both plasma and urine of patients with cirrhosis and HCC. MRP3A and MRP3B isoforms have the potential to be prognostic biomarkers of HCC.

Biomarker in Hepatocellular Carcinoma

Liver cancer is one of the most prevalent types of cancer and a major contributor to the socioeconomic burden worldwide. The pathogenesis of hepatocellular carcinoma (HCC) is contributed by various etiological factors like virus infection, excessive alcohol consumption, exposure to toxins, or metabolic disorders. Majority of patients are diagnosed with late-stage HCC, which restricts its management to only palliative care. HCC, if diagnosed early, increases the survival and quality of life. Currently available biomarker (alpha-fetoproteins) have several limitations, that impede the early diagnosis and staging of cancer. This warrants the continous search in pursuit of a novel biomarker. Several research works in diverse areas have contributed to the identification of various novel biomarkers that have shown multifaceted application in early disease diagnosis, which further aid in targeted and effective therapy that can prevent cancer progression. This improves the overall health status of the patient along with significant reduction in caretaker's burden. With the aid of novel technologies, several biomarkers have been investigated and validated in mutliple preliminary research works. Therefore in this review, we have outlined various novel biomarkers that showed promising outcomes in their trials and we have highlighted the developing areas that act as game changers in cancer diagnosis and management.

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.

Biomarker discovery and validation for gastrointestinal tumors: A comprehensive review of colorectal, gastric, and liver cancers

Gastrointestinal (GI) malignancies, encompassing gastric, hepatic, colonic, and rectal cancers, are prevalent forms of cancer globally and contribute substantially to cancer-related mortality. Although there have been improvements in methods for diagnosing and treating GI cancers, the chances of survival for these types of cancers are still extremely low. According to the World Cancer Research International Fund's most recent figures, stomach cancer was responsible for roughly one million deaths worldwide in 2020. This emphasizes the importance of developing more effective tools for detecting, diagnosing, and predicting the outcome of these cancers at an early stage. Biomarkers, quantitative indications of biological processes or disease states, have emerged as promising techniques for enhancing the diagnosis and prognosis of GI malignancies. Recently, there has been a considerable endeavor to discover and authenticate biomarkers for various GI cancers by the utilization of diverse methodologies, including genomics, proteomics, and metabolomics. This review provides a thorough examination of the current state of biomarker research in the field of gastrointestinal malignancies, with a specific emphasis on colorectal, stomach, and liver cancers. A thorough literature search was performed on prominent databases such as PubMed, Scopus, and Web of Science to find pertinent papers published until November, 2023 for the purpose of compiling this review. The diverse categories of biomarkers, encompassing genetic, epigenetic, and protein-based biomarkers, and their potential utility in the fields of diagnosis, prognosis, and treatment selection, are explored. Recent progress in identifying and confirming biomarkers, as well as the obstacles that persist in employing biomarkers in clinical settings are emphasized. The utilization of biomarkers in GI cancers has significant potential in enhancing patient outcomes. Ongoing research is expected to uncover more efficient biomarkers for the diagnosis and prognosis of these cancers.

Existing and emerging biomarkers in hepatocellular carcinoma: relevance in staging, determination of minimal residual disease, and monitoring treatment response: a narrative review

Background and Objective

With the development of novel active systemic therapies, the landscape of hepatocellular carcinoma (HCC) management is rapidly changing. However, HCC lacks sensitive and specific biomarkers to predict prognosis, monitor for minimal residual disease after locoregional therapy, and predict treatment response. In this review, we aim to summarize the best supporting evidence for refining existing, and development of novel biomarkers for staging, prognosis, determination of minimal residual disease and monitoring treatment response in HCC, focusing on those with evidence in clinical trials.

Methods

PubMed and Embase databases were searched using the keywords; hepatocellular carcinoma, biomarker, minimal residual disease, surveillance, prognosis, staging, alpha-fetoprotein (AFP), liquid biopsy, treatment response, adjuvant, immunotherapy. Relevant clinical studies were included.

Key Content and Findings

AFP remains the major workhorse as the most widely used biomarker in HCC, however, its lack of wide applicability due to the high proportion of patients with HCC who are AFP negative, limits its value throughout all stages of HCC management. Significant work has been done to combine AFP with other clinical and serologic factors to increase its accuracy and utility as a biomarkers. However, it is likely that other more novel biomarkers such as those obtained through liquid biopsy will provide the prognostic power necessary for applications such as detecting recurrence and predicting treatment response. Liquid biopsy provides not only a wealth of potential biomarkers including circulating tumor cells and cell-free RNA/DNA, but also the ability to examine the mutational characteristics of the tumor with next generation sequencing. While early evidence supports the potential impact of many new biomarkers, validation in large clinical trials is lacking.

Conclusions

This review highlights the paucity of sensitive and specific, widely applicable biomarkers, throughout all phases of management of HCC and summarizes evidence on biomarkers currently in use, as well as those in development and validation. Inclusion of biomarker analysis through clinical trials in HCC is critical to development of optimal therapeutic regimens, and improve patient outcomes.

The Biological Function of POLA2 in Hepatocellular Carcinoma

INTRODUCTION

The role and prognostic value of POLA2 in liver cancer were comprehensively analyzed through TCGA, GEO, and ICGC databases, and the role of POLA2 in liver cancer cells and the regulatory mechanism involved were further verified through cell experiments. Hepatocellular carcinoma (HCC) is the most prevalent malignancy with high morbidity and mortality. Consequently, it is critical to identify robust and reliable predictive biomarkers and therapeutic targets for HCC patients. POLA2 is involved in the regulation of various tumors, but the specific role of POLA2 in HCC has not been reported. The regulatory role and prognostic value of POLA2 in HCC were determined by bioinformatics techniques and cell experiments.

METHODS

The specific role and prognostic value of POLA2 in HCC were comprehensively analyzed by combining the expression data of POLA2 in TCGA, GEO, and ICGC databases and clinical data. In clinical samples, the expression of POLA2 in liver cancer was verified by QPCR. Further, the regulatory role of POLA2 in HCC was explored through cell experiments such as CCK-8, clonal formation experiment, EDU cell proliferation experiment, and flow cytometry. In terms of mechanism exploration, western blot was used to verify the specific regulatory mechanism that POLA2 participated in. Finally, the relationship between POLA2 and immune invasion of HCC was analyzed by using the TIMER database.

RESULTS

A POLA2 expression and prognosis analysis of HCC patients was conducted using the TCGA, GEO, and ICGC databases. We hypothesized that POLA2 might be one of the key factors contributing to the HCC progression. According to a combined analysis of TCGA, ICGC, and GEO databases, POLA2 was highly expressed in HCC. This was further confirmed in clinical samples using the qPCR. POLA2 knockdown was also performed in vitro on HCC cell lines to study the changes in their biological behavior. We confirmed that POLA2 was associated with HCC proliferation by CCK-8, Colony Formation, and EDU assay. We verified the POLA2's involvement in cell cycle regulation using flow techniques. The relationship between POLA2 and PI3K/AKT/mTOR pathway was explored using Western Blotting experiments regarding its mechanism. Further analysis revealed that the POLA2 expression was significantly associated with HCC immune infiltration.

CONCLUSION

Our study demonstrated POLA2's importance in HCC development and progression and its potential role as a biomarker for disease progression on multiple levels. POLA2 has an important role in regulating the cell cycle and cell proliferation. By interfering with the cell cycle and proliferation, HCC cell growth is inhibited. Furthermore, POLA2 expression was significantly associated with immune infiltration. POLA2 may play a role in HCC immunotherapy based on its correlation with several immune cell types' genetic markers. The findings of this study are expected to lead to new anticancer strategies for HCC.

The Current Status of the Liver Liquid Biopsy in MASH Related HCC: Overview and Future Directions

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.

Detection of sFas, sCD137, and IL-27 Cytokines as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Purpose

Hepatocellular carcinoma (HCC), a prevalent type of liver cancer, is mainly diagnosed in the advanced stage, leading to a high mortality rate. Recent advances have identified peripheral cytokines as a potential tool to predict disease outcomes and inform therapeutic decisions. Hence, in this study, we aim to build a predictive model for HCC based on serum levels of different cytokines.

Patients and Methods

We used immunoassay to quantify the concentrations of IL-27, MIP-1β, Perforin, sCD137, sFas, and TNF-α in the serum of 38 HCC patients and 15 healthy controls. Logistic regression was then used to construct classification models detecting HCC based on these cytokines. A nomogram of the best-performing model was generated to visualize HCC prediction.

Results

sFas and MIP-1β were found to be significantly higher in HCC patients compared to controls. Predictive models based on cytokine levels combining sFas, sCD137, and IL-27 performed the best in distinguishing HCC patients from healthy controls. This model has a bias-corrected area under the receiver operating characteristic (ROC) curve (AUC) of 0.948, a sensitivity of 92.11%, a specificity of 93.33%, and an accuracy of 0.925.

Conclusion

Our findings suggest that serum cytokines have the potential to be utilized in HCC screening to improve detection rates.

An Overview of Hepatocellular Carcinoma Surveillance Focusing on Non-Cirrhotic NAFLD Patients: A Challenge for Physicians

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of liver disease worldwide and it ranges from simple steatosis to hepatocellular carcinoma (HCC). HCC represents the first liver tumor and the third source of cancer death. In the next few years, the prevalence of NAFLD and consequently of HCC is estimated to increase, becoming a major public health problem. The NAFLD-HCC shows several differences compared to other causes of chronic liver disease (CLD), including the higher percentage of patients that develop HCC in the absence of liver cirrhosis. In HCC surveillance, the international guidelines suggest a six months abdominal ultrasound (US), with or without alpha-fetoprotein (AFP) evaluation, in patients with cirrhosis and in a subgroup of patients with chronic hepatitis B infection. However, this screening program reveals several limitations, especially in NAFLD patients. Thus, new biomarkers and scores have been proposed to overcome the limits of HCC surveillance. In this narrative review we aimed to explore the differences in the HCC features between NAFLD and non-NAFLD patients, and those between NAFLD-HCC developed in the cirrhotic and non-cirrhotic liver. Finally, we focused on the limits of tumor surveillance in NAFLD patients, and we explored the new biomarkers for the early diagnosis of HCC.

Upregulated SSB Is Involved in Hepatocellular Carcinoma Progression and Metastasis through the Epithelial-Mesenchymal Transition, Antiapoptosis, and Altered ROS Level Pathway

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with high morbidity and mortality. Therefore, finding new diagnostic and therapeutic targets is vital for HCC patients. Recent studies have shown that dysregulation of RNA-binding proteins is often associated with cancer progression. Several studies have reported that the RNA-binding protein SSB can promote cancer occurrence and progression and is linked to tumor epithelial-mesenchymal transition (EMT), which could be a new diagnostic marker and therapeutic target. However, the expression and function of SSB in HCC remain to be elucidated. Therefore, this study is aimed at clarifying the expression and biological function of SSB in HCC through bioinformatics analysis combined with in vitro experiments. We found that SSB is highly expressed in HCC and is associated with the poor prognosis of HCC patients, and it can serve as an independent unfavorable prognostic factor. Knockdown of SSB can inhibit the growth of HCC cells in vitro, increase the level of apoptosis and the expression of pro-apoptosis-related proteins, and decrease the expression of antiapoptotic proteins. Meanwhile, SSB knockdown reduced HCC cell invasiveness, and the expression of EMT-related proteins changed significantly. We also found that the gene SSB was associated with the level of oxidative stress in liver cancer cells, and the level of intracellular reactive oxygen species (ROS) increased after knockdown of SSB. The results of bioinformatics analysis also showed that high expression of SSB may affect the effect of checkpoint blockade (ICB) therapy. In conclusion, we found that SSB is highly expressed in HCC and that upregulated SSB can promote the proliferation and metastasis of HCC through antiapoptotic, altered intracellular oxidative stress level, and EMT pathways, which can serve as a new diagnostic marker and therapeutic target, and patients with high SSB expression may not have obvious ICB therapy effect.

Systematic scoping review evaluating the potential of wastewater-based epidemiology for monitoring cardiovascular disease and cancer

Cardiovascular disease (CVD) and cancer are collectively responsible for tens of millions of global deaths each year. These rates are projected to intensify as the COVID-19 pandemic has caused delays in individualized diagnostics, or exacerbated prevalence due to Post Acute Coronavirus (COVID-19) Syndrome. Wastewater-based epidemiology (WBE) has successfully been employed as a useful tool for generating population-level health assessments, and was examined here in this systematic scoping literature review to (i) identify endogenous human biomarkers reported to indicate CVD or cancer in clinical practice, (ii) assess specificity to the indicated diseases, (iii) evaluate the utility for estimating population-level disease prevalence in community wastewater, and (iv) contextualize the obtained information for monitoring CVD and cancer presence via WBE. A total of 48 peer-reviewed papers were critically examined identifying five urinary protein biomarkers: cardiac troponin I (cTnI) (heart attack/heart failure), cystatin C (atherosclerosis), normetanephrine (tumor presence), α-fetoprotein (prostate and liver cancer), and microtubule assisted serine/threonine kinase 4 (MAST4) (breast cancer). Next, urinary excretion information was utilized to predict biomarker concentrations extant in community wastewater, resulting in average healthy concentrations ranging from 0.02 to 1159 ng/L, and disease-indicating thresholds from 0.16 to 3041 ng/L. Finally, estimating prevalence-adjusted wastewater measurements was explored in order to assess community-level CVD and cancer presence utilizing U.S. reported prevalence rates. Results obtained suggest that WBE can serve as a viable tool in support of current methods for CVD and cancer assessment to reduce morbidities and mortalities worldwide.

Identification and analysis of C17orf53 as a prognostic signature for hepatocellular carcinoma

C17orf53 is a novel gene for DNA synthesis and homologous recombination. However, the exact role of C17orf53 in hepatocellular carcinoma (HCC) remains unclear. In this study, we analyzed it using a set of public datasets. UALCAN, Human Protein Atlas (HPA), Kaplan‒Meier Plotter, Tumor Immune Estimation Resource (TIMER), cBioPortal, GEPIA, GeneMANIA, and LinkedOmics were used. Functional analysis was conducted in SK-Hep-1 cells by using small interfering RNA (siRNA). C17orf53 was highly expressed and predicted unfavorable survival in HCC patients. Moreover, it showed positive correlations with the abundance of B cells, macrophages and dendritic cells. In addition, we identified 126 genes that were positively correlated with C17orf53 and its coeffector minichromosome maintenance 8 (MCM8). These genes were mainly enriched in the cell cycle, DNA replication and Fanconi anemia pathways. Knockdown of C17orf53 significantly inhibited the proliferation of SK-Hep-1 cells and decreased the expression of MCM8, cyclin D1 and proliferating cell nuclear antigen (PCNA). Overall, C17orf53 is a novel prognostic signature for HCC.

An Insight into Hepatitis C Virus: In Search of Promising Drug Targets

Hepatitis C Virus (HCV) is a global health concern, chronically infecting over 70 million people worldwide. HCV is a bloodborne pathogen that primarily affects the liver, and chronic HCV infection can lead to cirrhosis, liver cancer, and liver failure over time. There is an urgent need for more effective approaches to prevent and treat HCV. This review summarizes current knowledge on the virology, transmission, diagnosis, and management of HCV infection. It also provides an in-depth analysis of HCV proteins as promising targets for antiviral drug and vaccine development. Specific HCV proteins discussed as potential drug targets include the NS5B polymerase, NS3/4A protease, entry receptors like CD81, and core proteins. The implications of HCV proteins as diagnostic and prognostic biomarkers are also explored. Current direct-acting antiviral therapies are effective but have cost, genotype specificity, and resistance limitations. This review aims to synthesize essential information on HCV biology and pathogenesis to inform future research on improved preventive, diagnostic, and therapeutic strategies against this global infectious disease threat.

Identification of key snoRNAs serves as biomarkers for hepatocellular carcinoma by bioinformatics methods

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy with high mortality and poor prognosis due to a lack of predictive markers. However, research on small nuclear RNAs (snoRNAs) in HCC were very little. This study aimed to identify a potential diagnostic and prognostic snoRNA signature for HCC.

METHODS

HCC datasets from the cancer genome atlas (TCGA) and international cancer genome consortium (ICGC) cohorts were used. Differentially expressed snoRNA (DEs) were identified using the limma package. Based on the DEs, diagnostic and prognostic models were established by the least absolute shrinkage and selection operator (LASSO) regression and COX analysis, and Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the efficiency of signatures. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to analyze the risk score and further explore the potential correlation between the risk groups and tumor immune status in TCGA. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to determine the functions of key snoRNAs.

RESULTS

We constructed a 6-snoRNAs signature which could classify patients into high- or low-risk groups and found that patients in the high-risk group had a worse prognosis than those in the low-risk group and were significantly involved in p53 processes. Tumor immune status analysis revealed that CTLA4 and PDCD1 (PD1) were highly expressed in the high-risk group, which responded to PD1 inhibitor therapy. Additionally, a 25-snoRNAs diagnostic signature was constructed with an area under the curve (AUC) of 0.933 for distinguishing HCCs from normal controls. Finally, 3 key snoRNAs (SNORA11, SNORD124, and SNORD46) were identified with both diagnostic and prognostic efficacy, some of which were closely related to the spliceosome and Notch signaling pathways.

CONCLUSIONS

Our study identified 6 snoRNAs that may serve as novel prognostic models and 3 key snoRNAs with both diagnostic and prognostic efficacy for HCC.

Role of exosomal microRNAs in cancer therapy and drug resistance mechanisms: focus on hepatocellular carcinoma

Extracellular vesicles (EVs), defined as intercellular messengers that carry their cargos between cells, are involved in several physiological and pathological processes. These small membranous vesicles are released by most cells and contain biological molecules, including nucleic acids, proteins and lipids, which can modulate signaling pathways of nearby or distant recipient cells. Exosomes, one the most characterized classes of EVs, include, among others, microRNAs (miRNAs), small non-coding RNAs able to regulate the expression of several genes at post-transcriptional level. In cancer, exosomal miRNAs have been shown to influence tumor behavior and reshape tumor microenvironment. Furthermore, their possible involvement in drug resistance mechanisms has become evident in recent years. Hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for 75-85% of all liver tumors. Although the improvement in HCC treatment approaches, low therapeutic efficacy in patients with intermediate-advanced HCC is mainly related to the development of tumor metastases, high risk of recurrence and drug resistance. Exosomes have been shown to be involved in pathogenesis and progression of HCC, as well as in drug resistance, by regulating processes such as cell proliferation, epithelial-mesenchymal transition and immune response. Herein, we summarize the current knowledge about the involvement of exosomal miRNAs in HCC therapy, highlighting their role as modulators of therapeutic response, particularly chemotherapy and immunotherapy, as well as possible therapeutic tools.

Identification of KRBA1 as a Potential Prognostic Biomarker Associated with Immune Infiltration and m6A Modification in Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HCC) is a malignancy with high incidence, but its prognosis is not optimistic. KRBA1 is a member of the KRAB family and participates in the regulation of gene transcription. However, no studies have focused on the role of KRBA1 in HCC.

Patients and Methods

In this study, we first analyzed the expression of KRBA1 in HCC using TCGA and ICGC databases and validated by Immunohistochemistry in clinical HCC samples. The Wilcoxon rank-sum test was used to determine the relationship between KRBA1 expression and clinicopathological features. Subsequently, we used Kaplan-Meier online website analysis and Cox regression model to predict the prognostic value of KRBA1 in HCC patients. Furthermore, the functions of KRBA1 were identified by enrichment analysis. TIMER and GSCALite were used to investigate the relationship between KRBA1 expression in HCC and immune infiltration and drug targets, respectively. Finally, the relationship between KRBA1 expression and m6A modification in HCC was analyzed using the TCGA and ICGA datasets.

Results

The results showed that KRBA1 was upregulated in HCC and was associated with many clinicopathological features. High KRBA1 causes poor overall survival and may be an independent risk factor for HCC. KRBA1 tends to be hypermethylated and associated with poor prognosis in HCC compared with normal tissues. Enrichment analysis indicates that KRBA1 is associated with cell cycle and immune processes, and TIMER analysis shows that KRBA1 expression is associated with infiltration levels and immune characteristics of various immune cells. Silenced KRBA1 evidently reduced three chemokine expression in HCC cells. Drug sensitivity analysis showed that KRBA1 was sensitive to 39 drug small molecules. KRBA1 showed a strong positive correlation with five m6A related genes.

Conclusion

KRBA1 is a prognostic biomarker associated with HCC immunity and m6a modification, serving as an effective target for the diagnosis and treatment of HCC.

Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study

BACKGROUND

There is a growing need for new improved classifiers of prognosis in hepatocellular carcinoma (HCC) patients to stratify them effectively.

METHODS

A deep learning model was developed on a total of 1118 patients from 4 independent cohorts. A nucleus map set (n = 120) was used to train U-net to capture the nuclear architecture. The training set (n = 552) included HCC patients that had been treated by resection. The liver transplantation (LT) set (n = 144) contained patients with HCC that had been treated by LT. The train set and its nuclear architectural information extracted by U-net were used to train the MobileNet V2-based classifier (MobileNetV2_HCC_class). The classifier was then independently tested on the LT set and externally validated on the TCGA set (n = 302). The primary outcome was recurrence free survival (RFS).

RESULTS

The MobileNetV2_HCC_class was a strong predictor of RFS in both LT set and TCGA set. The classifier provided a hazard ratio of 3.44 (95% CI 2.01-5.87, p < 0.001) for high risk versus low risk in the LT set, and 2.55 (95% CI 1.64-3.99, p < 0.001) when known prognostic factors, remarkable in univariable analyses on the same cohort, were adjusted. The MobileNetV2_HCC_class maintained a relatively higher discriminatory power [time-dependent accuracy and area under curve (AUC)] than other factors after LT or resection in the independent validation set (LT and TCGA set). Net reclassification improvement (NRI) analysis indicated MobileNetV2_HCC_class exhibited better net benefits for the Stage_AJCC beyond other independent factors. A pathological review demonstrated that tumoral areas with the highest recurrence predictability featured the following features: the presence of stroma, a high degree of cytological atypia, nuclear hyperchromasia, and a lack of immune cell infiltration.

CONCLUSION

A prognostic classifier for clinical purposes had been proposed based on the use of deep learning on histological slides from HCC patients. This classifier assists in refining the prognostic prediction of HCC patients and identifies patients who have been benefited from more intensive management.

Nanotechnology in the Diagnostic and Therapy of Hepatocellular Carcinoma

Hepatocellular carcinoma is the most common liver malignancy and is among the top five most common cancers. Despite the progress of surgery and chemotherapy, the results are often disappointing, in part due to chemoresistance. This type of tumor has special characteristics that allow the improvement of diagnostic and treatment techniques used in clinical practice, by combining nanotechnology. This article presents a brief review of the literature focused on nano-conditioned diagnostic methods, targeted therapy, and therapeutic implications for the pathology of hepatocellular carcinoma. Within each subdomain, several modern technologies with significant impact were highlighted: serological, imaging, or histopathological diagnosis; intraoperative detection; carrier-type nano-conditioned therapy, thermal ablation, and gene therapy. The prospects offered by nanomedicine will strengthen the hope of more efficient diagnoses and therapies in the future.

Biomarkers for the Detection and Management of Hepatocellular Carcinoma in Patients Treated with Direct-Acting Antivirals

Simple Summary

Chronic Hepatitis C virus (HCV) represents the main etiological factor for hepatocellular carcinoma (HCC) in developed countries. The introduction of direct-acting antivirals (DAAs) improved the eradication of the hepatitis C virus (HCV) but not the reduction in the incidence of HCV-associated HCC. Some patients still develop HCC, even after reaching a sustained virological response (SVR). This review is a summary of pre-clinical studies that investigated predictive biomarkers for HCC occurrence and recurrence in HCV-infected patients treated with DAAs. The presented biomarkers are found dysregulated in serum or tissue at specific time points (before, during, after DAA treatment or post SVR) and correlated with HCC-predisposing conditions. Thus, this review aims to improve the management of patients developing HCV-induced HCC.

Abstract

Hepatocellular carcinoma (HCC) is the sixth-most common type of cancer worldwide and chronic Hepatitis C virus (HCV) represents the main etiological factor in developed countries. HCV promotes hepatocarcinogenesis through persistent liver inflammation and dysregulation of cell signaling pathways. The introduction of direct-acting antivirals (DAAs) resulted in a significant improvement in the eradication of the virus, with an expected reduction of HCC incidence. However, the risk of HCC development can persist after DAA treatment. Recent studies have investigated the potential use of molecular biomarkers that predict HCC occurrence or recurrence helping the stratification of patients under surveillance. This review aimed to summarize all pre-clinical exploration of predictive biomarkers to identify DAA-treated patients at risk for HCC development. Dysregulated microRNAs, lncRNAs, histone modifications, cytokines, proteins, and sphingolipids represent various classes of HCC risk predictors identified in two different biological sources (tissue and serum). The non-invasive serum markers can provide a more accessible means to perform clinical monitoring and predict the risk of HCC. In addition, conditions like cirrhosis, predisposing to HCC, strongly correlate with most of the molecular predictors identified, supporting the value of these molecules as possible biomarkers of HCC in DAA-treated patients.

Diagnostic performance of clusterin in hepatocellular carcinoma: A meta-analysis

Introduction

Clusterin (CLU) is a pleiotropic protein with numerous functions. It has recently attracted considerable attention owing to its association with cancer progression and metastasis. However, its role in hepatocellular carcinoma (HCC) has not been investigated. This meta-analysis is the first evaluation of the diagnostic performance of CLU in HCC.

Methods

Articles published in PubMed, EMBASE, Web of Science, Wanfang Data Knowledge Service Platform, and China Science and Technology Journal Database until January 2022 were searched. Studies that reported the usefulness of CLU for the differentiation of HCC and non-HCC (e.g., liver cirrhosis, chronic hepatitis, and other benign liver disease) patients were selected. Alpha-fetoprotein (AFP) was used as a positive control in this study. The sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were compared between CLU and AFP.

Results

Eight articles including 811 participants were included. The pooled sensitivity (95% confidence interval (CI)), specificity (95% CI), DOR (95% CI), and AUC (95% CI) were: 0.86 (0.78–0.91), 0.85 (0.75–0.91), 35 (13–94), and 0.92 (0.89–0.94) for CLU; 0.74 (0.67–0.81), 0.89 (0.79–0.94), 22 (8–61), and 0.87 (0.84–0.90) for AFP; 0.93 (0.88–0.96), 0.85 (0.68–0.94), 75 (21–262), and 0.95 (0.92–0.96) for CLU + AFP, respectively. Compared with AFP, CLU showed higher sensitivity, DOR, and AUC, as well as similar specificity. The combination of CLU and AFP resulted in higher sensitivity, DOR, and AUC.

Conclusions

Serum CLU is a better biomarker versus AFP for the diagnosis of HCC. The combination of CLU and AFP improved diagnostic performance.

Outcomes of surgical resection of super-giant (≥15 cm) hepatocellular carcinoma: Volume does matter, if not the size

BACKGROUND AND AIM

Resection for giant hepatocellular carcinoma (HCC) (≥10 cm) is deemed safe and feasible. However, a super-giant HCC (≥15 cm) poses unique technical complexity for hepatectomy with limited data suggesting feasibility and oncologic efficiency. This study aims to evaluate the short-term and long-term outcomes of hepatectomy in patients with super-giant HCC.

METHODS

A retrospective review was conducted on patients with super-giant HCC who underwent hepatectomy from 2011 to 2021. We report perioperative and oncologic outcomes such as length of stay (LOS), 30-day readmission, 90-day mortality, and cumulative survival rate.

RESULTS

Of the 18 patients, the median tumor diameter was 172.5 mm (range 150-250). The most common risk factor was chronic hepatitis B virus (HBV) infection (n=7, 38.9%). Most of the patients were Barcelona Clinic Liver Cancer (BCLC) Stage B (n=14, 77.8%) and Hong Kong Liver Cancer (HKLC) Stage IIb (n=15, 83.3%). Extended right hepatectomy was the most common procedure. The median LOS was 11 days (range 3-90). The most common post-operative complication was pneumonia (n=4, 22.2%). Fourteen patients were discharged well without any need for invasive therapy (n=7, 38.9% no complications, n=1, 5.6% Clavien Grade I, n=6, 33.3% Clavien Grade II). Thirty-day readmission rate was 5.6% (n=1) and 90-day mortality rate was 5.6% (n=1). There were 12 patients (66.7%) with microvascular invasion and three patients (16.7%) with macrovascular invasion. Most patients had Grade III (poorly differentiated) HCC (n=9, 50%). At a median follow-up of 11 months (range 2-95), 12 (66.7%) patients had local recurrence, and 9 (50%) developed distant metastasis. The 1-, 2-, and 3-year cumulative disease-free survival (DFS) was 36%, 18%, and 18%, respectively. The 1-, 2-, and 3-year cumulative overall survival was 49% and 39%, and 29%, respectively.

CONCLUSION

Primary hepatic resection is safe in patients with super-giant HCC. However, long-term outcomes are poor, and high tumor volume may be associated with inferior oncological outcomes in HCC.

RELEVANCE FOR PATIENTS

The presentation of super-giant HCCs may be asymptomatic and some patients are diagnosed late with limited treatment options. In some centers, this group of patients are denied surgical resection and recommended for only locoregional therapies like TACE. This paper demonstrates that hepatic resection is safe and may be an option in patients who present at an advanced stage with a high tumor burden.

Diagnostic Value of hTERT mRNA and in Combination With AFP, AFP-L3%, Des-γ-carboxyprothrombin for Screening of Hepatocellular Carcinoma in Liver Cirrhosis Patients HBV or HCV-Related

Diagnosis of hepatocellular carcinoma (HCC) in early-stage, to give an effective treatment option and improve quality of life for cancer patients, is an important medical mission globally. Combination of AFP with some biomarkers may be more supportive in both diagnosis and screening of HCC, but the range value of these markers can be applied as daily markers were unclearly. In some studies, human telomerase reverse transcriptase (hTERT mRNA) was reported as an advantage marker to diagnose cancer. The present study identified serum of 340 patients that were infected chronic hepatitis B virus or hepatitis C virus and divided in 2 groups including Hepatocellular carcinoma (HCC) and liver cirrhosis (LC) to measure their values of hTERT mRNA, AFP, AFP-L3%, and DCP, as well as combination of them. As a result, the concentration of hTERT mRNA, AFP, AFP-L3%, and DCP in HCC groups were significantly higher than that in LC group (P < .01). For detecting HCC, hTERT mRNA had sensitivity of 88% and specificity of 96% (at the cutoff value of 31.5 copies/mL), AFP sensitivity of 73% and specificity of 92% (at the cutoff value of 5.1 ng/mL), AFP-L3% sensitivity of 69% and specificity of 90% (at the cutoff value of 1.05%), DCP sensitivity of 82% and specificity of 92% (at the cutoff value of 29.01 mAU/mL). The largest area under the curve (AUC) of combination hTERT mRNA with DCP was 0.932 (sensitivity of 98.2% and specificity of 88.2%). New combination of DCP with hTERT mRNA gave a useful choice for screening of HCC in chronic HBV or HCV patients associated liver cirrhosis.

Aptamers and New Bioreceptors for the Electrochemical Detection of Biomarkers Expressed in Hepatocellular Carcinoma

Hepatocellular carcinoma is a malignancy associated with high mortality and increasing incidence. Early detection of this disease could help increase survival and overall patient benefit. Non-invasive strategies for the diagnosis of this medical condition are of utmost importance. In this scope, the detection of hepatocellular carcinoma biomarkers could provide a useful diagnostic tool. Aptamers represent as short, single-stranded DNAs or RNAs that can specifically bind selected analytes, and also as pseudo-biorecognition elements that can be employed for electrode functionalization. Also, other types of DNA sequences can be used for the construction of DNA-based biosensors applied for the quantification of hepatocellular carcinoma biomarkers. Herein, we will be analyzing recent examples of aptasensors and DNA biosensors for the detection of hepatocellular carcinoma biomarkers like micro-RNAs, long non-coding RNAs, exosomes, circulating tumor cells and proteins. The literature data is discussed comparatively in a critical manner highlighting the advantages of using electrochemical biosensors in diagnosis, as well as the use of nanomaterials and biocomponents in the functionalization of electrodes for improved sensitivity and selectivity.

Combined screening analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

BACKGROUND

Methylation plays an important role in hepatocellular carcinoma (HCC) by altering the expression of key genes. The aim of this study was to screen the aberrantly methylated-differentially expressed genes (DEGs) in HCC and elucidate their underlying molecular mechanism.

METHODS

Gene expression microarrays (GSE101685) and gene methylation microarrays (GSE44909) were selected. DEGs and differentially methylated genes (DMGs) were screened. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the Database for Annotation, Visualization, and Integrated discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to analyze the functional protein-protein interaction (PPI) network. Molecular Complex Detection (MCODE) analysis was performed using the Cytoscape software. Hub genes were verified in The Cancer Genome Atlas (TCGA) database.

RESULTS

A total of 80 hypomethylation-high expression genes (Hypo-HGs) were identified. Pathway enrichment analysis showed DNA replication, cell cycle, viral carcinogenesis, and the spliceosome. The top 5 hub genes were minichromosome maintenance complex component 3 (MCM3), checkpoint kinase 1 (CHEK1), kinesin family member 11 (KIF11), PDZ binding kinase (PBK), and Rac GTPase activating protein 1 (RACGAP1). In addition, 189 hypermethylation-low expression genes (Hyper-LGs) were identified. Pathway enrichment analysis indicated enrichment in metabolic pathways, drug metabolism-other enzymes, and chemical carcinogenesis. The top 5 hub genes were leukocyte immunoglobulin like receptor B2 (LILRB2), formyl peptide receptor 1 (FPR1), S100 calcium binding protein A9 (S100A9), S100 calcium binding protein A8 (S100A8), and myeloid cell nuclear differentiation antigen (MNDA). The methylation status and mRNA expression of MCM3, CHEK1, KIF11, PBK, and S100A9 were consistent in the TCGA database and significantly correlated with the prognosis of patients.

CONCLUSIONS

Combined screening of aberrantly methylated-DEGs based on bioinformatic analysis may provide new clues for elucidating the epigenetic mechanism in HCC. Hub genes, including MCM3, CHEK1, KIF11, PBK, and S100A9, may serve as biomarkers for the precise diagnosis of HCC.

ASF1B Serves as a Potential Therapeutic Target by Influencing Cell Cycle and Proliferation in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with high morbidity and mortality. Therefore, it is very important to find potential biomarkers that can effectively predict the prognosis and progression of HCC. Recent studies have shown that anti-silencing function 1B (ASF1B) may be a new proliferative marker for tumor diagnosis and prognosis. However, the expression and function of ASF1B in hepatocellular carcinoma remain to be determined. In this study, integrated analysis of the Cancer Genome Atlas (TCGA), genotypic tissue expression (GTEx), and Gene Expression Omnibus (GEO) databases revealed that ASF1B was highly expressed in HCC. Kaplan-Meier survival curve showed that elevated ASF1B expression was associated with poor survival in patients with liver cancer. Correlation analysis of immune infiltration suggested that ASF1B expression was significantly correlated with immune cell infiltration in HCC patients. Gene set enrichment analysis (GSEA) indicated that ASF1B regulated the cell cycle, DNA Replication and oocyte meiosis signaling. Our experiments confirmed that ASF1B was highly expressed in HCC tissues and HCC cell lines. Silence of ASF1B inhibited hepatocellular carcinoma cell growth in vitro. Furthermore, ASF1B deficiency induced apoptosis and cell cycle arrest. Mechanistically, ASF1B knockdown reduced the expression of proliferating cell nuclear antigen (PCNA), cyclinB1, cyclinE2 and CDK9.Moreover, ASF1B interacted with CDK9 in HCC cells. Taken together, these results suggest that the oncogenic gene ASF1B could be a target for inhibiting hepatocellular carcinoma cell growth.

Objective to identify and verify the regulatory mechanism of DTNBP1 as a prognostic marker for hepatocellular carcinoma

Although the overall survival of hepatocellular carcinoma (HCC) patients has been significantly improved, prognostic clinical evaluation remains a substantial problem owing to the heterogeneity and complexity of tumor. A reliable and accurate predictive biomarker may assist physicians in better monitoring of patient treatment outcomes and follow the overall survival of patients. Accumulating evidence has revealed that DTNBP1 plays functional roles in cancer prognosis. Therefore, the expression and function of DTNBP1in HCC was systematically investigated in our study. The expression and prognostic value of DTNBP1 were investigated using the data from Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) cohorts and clinical samples. A series of cellular function assays were performed to elucidate the effect of DTNBP1 on cellular proliferation, apoptosis and metastasis. Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment and Protein–protein interaction (PPI) network construction were performed to screen the genes with highest interaction scores with DTNBP1. Finally, the underlying mechanism was also analyzed using Gene Set Enrichment Analysis (GSEA) and confirmed using RT-qPCR and western blotting. DTNBP1 was upregulated in many types of cancers, especially in HCC. The DTNBP1 expression levels is associated with clinicopathologic variables and patient survival status. The differential expression of DTNBP1 could be used to determine the risk stratification of patients with HCC. DTNBP1 deficiency inhibited cell proliferation and metastasis, but promoted cell apoptosis. Mechanistically, DTNBP1 regulated the cell cycle progression through affecting the expression of cell cycle-related genes such as CDC25A, CCNE1, CDK2, CDC20, CDC25B, CCNB1, and CDK1. DTNBP1, which regulates the cell cycle progression, may be used as a prognostic marker for HCC.

Absent in melanoma 1-like (AIM1L) serves as a novel candidate for overall survival in hepatocellular carcinoma

Identifying biomarkers for hepatocellular carcinoma (HCC) survival is of great importance for the early detection, monitoring, and predicting for prognosis. This study aimed to investigate the candidate biomarkers for predicting overall survival (OS) in HCC patients. Using RTCGAToolbox, top 50 upregulated differential expressed genes (DEGs) were identified. The least absolute shrinkage and selection operator (LASSO) and Cox models were used to select powerful candidate genes, and log rank method was used to address the survivor functions of potential biomarkers. Selected by LASSO model, ANLN, TTK, AIM1L and person neoplasm cancer status might be candidate parameters associated with OS in HCC patients. After adjusting person neoplasm cancer status, ANLN and TTK levels in Cox model, AIM1L was identified as a risk factor for predicting OS in HCC patients (HR = 1.5, P = 0.037). Validated in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) series, AIM1L was significantly overexpressed in tumor tissues compared to nontumor tissues (all P < 0.0001). HCC patients with high AIM1L in tumor tissues had significantly unfavorable OS compared to those with low AIM1L in TCGA, ICGC, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter datasets (all P < 0.05). Conclusively, AIM1L is upregulated in tumor samples and serves as a novel candidate for predicting unfavorable OS in HCC patients.

Wnt/β-Catenin Signaling as a Driver of Hepatocellular Carcinoma Progression: An Emphasis on Molecular Pathways

Liver cancers cause a high rate of death worldwide and hepatocellular carcinoma (HCC) is considered as the most common primary liver cancer. HCC remains a challenging disease to treat. Wnt/β-catenin signaling pathway is considered a tumor-promoting factor in various cancers; hence, the present review focused on the role of Wnt signaling in HCC, and its association with progression and therapy response based on pre-clinical and clinical evidence. The nuclear translocation of β-catenin enhances expression level of genes such as c-Myc and MMPs in increasing cancer progression. The mutation of CTNNB1 gene encoding β-catenin and its overexpression can lead to HCC progression. β-catenin signaling enhances cancer stem cell features of HCC and promotes their growth rate. Furthermore, β-catenin prevents apoptosis in HCC cells and increases their migration via triggering EMT and upregulating MMP levels. It is suggested that β-catenin signaling participates in mediating drug resistance and immuno-resistance in HCC. Upstream mediators including ncRNAs can regulate β-catenin signaling in HCC. Anti-cancer agents inhibit β-catenin signaling and mediate its proteasomal degradation in HCC therapy. Furthermore, clinical studies have revealed the role of β-catenin and its gene mutation (CTNBB1) in HCC progression. Based on these subjects, future experiments can focus on developing novel therapeutics targeting Wnt/β-catenin signaling in HCC therapy.

A Five-Gene-Based Prognostic Signature for Hepatocellular Carcinoma

Objective: This study intends to identify potential prognostic marker genes associated with the prognosis of patients suffering from hepatocellular carcinoma (HCC) based on TCGA and GEO analysis.

Methods: TCGA-LIHC cohort was downloaded and the data related to HCC were extracted from The Cancer Genome Atlas (TCGA) database and subjected to differential analysis. HCC-related gene expression datasets were retrieved from the GEO database, followed by differential analysis. After intersection of the results of TCGA and GEO databases, gene interaction analysis was performed to obtain the core genes. To identify the genes related to the prognosis of HCC patients, we conducted univariate and multivariate Cox analyses.

Results: Based on differential analysis of TCGA database, 854 genes were differentially expressed in HCC, any of which might link to the occurrence and progression of HCC. Meanwhile, joint analysis of HCC-related gene expression datasets in the GEO database screened 214 genes. Five core genes CDC20, TOP2A, RRM2, UBE2C and AOX1 were significantly associated with the prognosis of HCC patients and the risk model based on these five genes effectively predicted the prognosis of HCC patients.

Conclusion: Collectively, our data suggest that CDC20, TOP2A, RRM2, UBE2C and AOX1 may be the key genes affecting the prognosis of patients with HCC. The five-gene signature could accurately predict the prognosis of HCC patients.

Molecular Mechanisms and Animal Models of HBV-Related Hepatocellular Carcinoma: With Emphasis on Metastatic Tumor Antigen 1

Hepatocellular carcinoma (HCC) is an important cause of cancer death worldwide, and hepatitis B virus (HBV) infection is a major etiology, particularly in the Asia-Pacific region. Lack of sensitive biomarkers for early diagnosis of HCC and lack of effective therapeutics for patients with advanced HCC are the main reasons for high HCC mortality; these clinical needs are linked to the molecular heterogeneity of hepatocarcinogenesis. Animal models are the basis of preclinical and translational research in HBV-related HCC (HBV-HCC). Recent advances in methodology have allowed the development of several animal models to address various aspects of chronic liver disease, including HCC, which HBV causes in humans. Currently, multiple HBV-HCC animal models, including conventional, hydrodynamics-transfection-based, viral vector-mediated transgenic, and xenograft mice models, as well as the hepadnavirus-infected tree shrew and woodchuck models, are available. This review provides an overview of molecular mechanisms and animal models of HBV-HCC. Additionally, the metastatic tumor antigen 1 (MTA1), a cancer-promoting molecule, was introduced as an example to address the importance of a suitable animal model for studying HBV-related hepatocarcinogenesis.

Biomarkers of Oncogenesis, Adipose Tissue Dysfunction and Systemic Inflammation for the Detection of Hepatocellular Carcinoma in Patients with Nonalcoholic Fatty Liver Disease

Current surveillance strategy for patients with nonalcoholic fatty liver disease (NAFLD) at risk of hepatocellular carcinoma (HCC) development is unsatisfactory. We aimed to investigate the diagnostic accuracy of alpha-fetoprotein (AFP), protein induced by vitamin K absence or antagonist-II (PIVKA-II), glypican-3 (GPC-3), adiponectin, leptin and interleukin-6 (IL-6), alone or in combination, for the discrimination between NAFLD patients with or without HCC. The biomarkers were investigated in a cohort of 191 NAFLD patients (median age 62, 54-68 years; 121 males and 70 females) with advanced fibrosis/cirrhosis, 72 of whom had a diagnosis of HCC. PIVKA-II showed the best performance for the detection of HCC with an area under the curve (AUC) of 0.853, followed by adiponectin (AUC = 0.770), AFP (AUC = 0.763), GPC-3 (AUC = 0.759) and by IL-6 (AUC = 0.731), while the leptin values were not different between patients with and without HCC. The accuracy of the biomarkers' combination was assessed by a stratified cross-validation approach. The combination of age, gender, PIVKA-II, GPC-3 and adiponectin further improved the diagnostic accuracy (AUC = 0.948); the model correctly identified the 87% of the patients. In conclusion, we developed a model with excellent accuracy for the detection of HCC that may be useful to improve the surveillance of NAFLD patients at risk of tumor development.