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

Identification of senescence-associated long non-coding RNAs to predict prognosis and immune microenvironment in patients with hepatocellular carcinoma

Background: Cellular senescence plays a complicated and vital role in cancer development because of its divergent effects on tumorigenicity. However, the long non-coding RNAs (lncRNAs) associated with tumor senescence and their prognostic value in hepatocellular carcinoma (HCC) remain unexplored. Methods: The trans-cancer oncogene-induced senescence (OIS) signature was determined by gene set variation analysis (GSVA) in the cancer genome atlas (TCGA) dataset. The OIS-related lncRNAs were identified by correlation analyses. Cox regression analyses were used to screen lncRNAs associated with prognosis, and an optimal predictive model was created by regression analysis of the least absolute shrinkage and selection operator (LASSO). The performance of the model was evaluated by Kaplan-Meier survival analyses, nomograms, stratified survival analyses, and receiver operating characteristic curve (ROC) analyses. Gene set enrichment analysis (GSEA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) were carried out to explore the functional relevance and immune cell infiltration, respectively. Results: Firstly, we examined the pan-cancer OIS signature, and found several types of cancer with OIS strongly associated with the survival of patients, including HCC. Subsequently, based on the OIS signature, we identified 76 OIS-related lncRNAs with prognostic values in HCC. We then established an optimal prognostic model based on 11 (including NRAV, AC015908.3, MIR100HG, AL365203.2, AC009005.1, SNHG3, LINC01138, AC090192.2, AC008622.2, AL139423.1, and AC026356.1) of these lncRNAs by LASSO-Cox regression analysis. It was then confirmed that the risk score was an independent and potential risk indicator for overall survival (OS) (HR [95% CI] = 4.90 [2.74-8.70], p < 0.001), which outperforms those traditional clinicopathological factors. Furthermore, patients with higher risk scores also showed more advanced levels of a proinflammatory senescence-associated secretory phenotype (SASP), higher infiltration of regulatory T (Treg) cells and lower infiltration of naïve B cells, suggesting the regulatory effects of OIS on immune microenvironment. Additionally, we identified NRAV as a representative OIS-related lncRNA, which is over-expressed in HCC tumors mainly driven by DNA hypomethylation. Conclusion: Based on 11 OIS-related lncRNAs, we established a promising prognostic predictor for HCC patients, and highlighted the potential immune microenvironment-modulatory roles of OIS in HCC, providing a broad molecular perspective of tumor senescence.

Association between serum midkine levels and tumor size in Indonesian hepatocellular carcinoma patients: a cross-sectional study

Background: The incidence of liver cancer is increased worldwide with 75%–85% are diagnosed as hepatocellular carcinoma (HCC). Current practice has low sensitivity limitations to diagnose the early stages of HCC, thus urging the need for a biomarker with higher sensitivity to detect HCC, specifically in the early stage. This study aimed to determine the association between Midkine levels and progressiveness of hepatocellular carcinoma (HCC), according to tumor size, Barcelona Clinic Liver Cancer (BCLC), and presence of portal venous thrombosis.

Methods: This cross-sectional study involved 100 patients in Adam Malik General Hospital diagnosed with HCC, collected with a consecutive sampling method, whose diagnosis were confirmed by findings of hypervascular on arterial phase imaging and portal vein or delayed phase washout triple-phase CT Scan. Samples are later categorized according to Barcelona Clinic Liver Cancer (BCLC) stages, tumor size, and presence of portal venous thrombosis. Blood samples were drawn to measure serum Midkine using ELISA. Kruskal-Wallis and Mann-Whitney U tests were conducted to determine the difference of Midkine levels based on tumor size, BCLC staging, and presence of portal venous thrombosis.

Results: Serum Midkine level shows a significant difference over tumor size (p=0.014), no significant difference found compared to BCLC stages and presence of portal venous thrombosis.

Conclusion: Serum Midkine levels are associated with the tumor size of HCC, thus helping physicians determine treatment plans.

Identifying Potential Tumor Antigens and Antigens-Related Subtypes in Hepatocellular Carcinoma for mRNA Vaccine Development

Background

The mRNA vaccine has become a promising platform for cancer therapy. Lots of studies have been focusing on discovering novel potent cancer-associated antigens to develop mRNA vaccines against cancers. Besides, immunotyping shows the immune status, and immune microenvironment of immunotyping is related with therapeutic reaction. However, potential antigens for mRNA vaccines and immunotyping of liver hepatocellular carcinoma (LIHC) remain far from being understood.

Methods

In this study, we collected gene expression data and clinical information data from ICGC and TCGA databases. Using GEPIA2, we calculated differential expression genes and prognostic indices. We applied TIMER to calculate the correlation coefficient between immune infiltrating cells and each gene. Consensus cluster was used for immunotyping of LIHC.

Results

We uncovered four most potential candidates including PES1, MCM3, PPM1G, and KPNA2, which were all related with antigen-presenting cell (APC) infiltration and poor survival in LIHC in two independent datasets. Furthermore, three immune-related subtypes (IS1-IS3) of LIHC were identified. All these results were validated in two independent datasets. Furthermore, we validated our results in vitro.

Conclusions

The above candidates will be expected to be potential antigen genes for developing anti-LIHC mRNA vaccine, and furthermore, patients with IS2 and IS3 tumors are supposed to be appropriate for mRNA vaccine in LIHC.

Safety and Efficacy of Sintilimab and Anlotinib as First Line Treatment for Advanced Hepatocellular Carcinoma (KEEP-G04): A Single-Arm Phase 2 Study

Purpose

Immune checkpoint inhibitors plus antiangiogenic tyrosine kinase inhibitors may offer a first-line treatment for advanced hepatocellular carcinoma (HCC). In this phase 2 trial [registered with clinicaltrials.gov (NCT04052152)], we investigated the safety and efficacy of first-line anti-PD-1 antibody sintilimab plus antiangiogenic TKI anlotinib for advanced HCC.

Methods and Materials

Pathologically-proven advanced HCC patients received sintilimab (200 mg) on day 1 and anlotinib (12 mg) once daily on days 1 to 14 every 3 weeks, with a safety run-in for the first six participants to assess dose-limiting toxicities (DLTs). The primary endpoints were safety and objective response rate (ORR) per RECIST v1.1.

Results

Twenty advanced HCC patients were enrolled. No DLTs occurred in the safety run-in. All patients had treatment-related adverse events (TRAEs). Grade 3 TRAEs occurred in 8 (40.0%) patients, the most common being decreased platelet count (10.0%) and increased γ-glutamyl transferase (10.0%). No grade 4/5 TRAEs occurred. Five (25%) patients developed immune-related AEs. The ORR was 35.0% (95%CI 15.4%-59.2%) per RECIST v1.1 and 55.0% (95%CI 31.5%-76.9%) per modified RECIST. At data cutoff (March 31, 2021), the median progression-free survival was 12.2 months (95%CI, 3.8 to not reached). The median PFS was significantly longer in patients with lower LDH levels (not reached [NR], 95% CI, 8.7 to NR vs. higher LDH levels 5.2 months, 95% CI 3.4 to NR; P=0.020) and a CONUT score ≤2 (NR, 95% CI 5.1 to NR vs. CONUT score >2 6.2 months, 95% CI 1.8 to NR; P=0.020). Furthermore, patients showing tumor response had a significantly higher median proportion of CD16⁺CD56⁺ NK cells than patients who had stable or progressive disease (21.6% vs. 14.6%; P=0.026).

Conclusion

Sintilimab plus anlotinib showed promising clinical activities with manageable toxicity as first-line treatment of advanced HCC.

Early Predictive Value of Circulating Biomarkers for Sorafenib in Advanced Hepatocellular Carcinoma

INTRODUCTION

Sorafenib is currently the first-line therapeutic regimen for patients with advanced hepatocellular carcinoma (HCC). However, many patients did not experience any benefit and suffered extreme adverse events and heavy economic burden. Thus, the early identification of patients who are most likely to benefit from sorafenib is needed.

AREAS COVERED

This review focused on the clinical application of circulating biomarkers (including conventional biomarkers, immune biomarkers, genetic biomarkers, and some novel biomarkers) in advanced HCC patients treated with sorafenib. An online search on PubMed, Web of Science, Embase, and Cochrane Library was conducted from the inception to Aug 15, 2021. Studies investigating the predictive or prognostic value of these biomarkers were included.

EXPERT OPINION

The distinction of patients who may benefit from sorafenib treatment is of utmost importance. The predictive roles of circulating biomarkers could solve this problem. Many biomarkers can be obtained by liquid biopsy, which is a less or non-invasive approach. The short half-life of sorafenib could reflect the dynamic changes of tumor progression and monitor the treatment response. Circulating biomarkers obtained from liquid biopsy resulted as a promising assessment method in HCC, allowing for better treatment decisions in the near future.

Novel Molecular Targets for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer globally. Indeed, only a few treatments are available, most of which are effective only for the early stages of the disease. Therefore, there is an urgent needing for potential markers for a specifically targeted therapy. Candidate proteins were selected from datasets of The Human Protein Atlas, in order to identify specific tumor-associated proteins overexpressed in HCC samples associated with poor prognosis. Potential epitopes were predicted from such proteins, and homology with peptides derived from viral proteins was assessed. A multiparametric validation was performed, including recognition by PBMCs from HCC-patients and healthy donors, showing a T-cell cross-reactivity with paired epitopes. These results provide novel HCC-specific tumor-associated antigens (TAAs) for immunotherapeutic anti-HCC strategies potentially able to expand pre-existing virus-specific CD8⁺ T cells with superior anticancer efficacy.

Up-regulation of GINS1 highlighted a good diagnostic and prognostic potential of survival in three different subtypes of human cancer

Cancer is a fatal malignancy and its increasing worldwide prevalence demands the discovery of more sensitive and reliable molecular biomarkers. To investigate the GINS1 expression level and its prognostic value in distinct human cancers using a series of multi-layered in silico approach may help to establish it as a potential shared diagnostic and prognostic biomarker of different cancer subtypes. The GINS1 mRNA, protein expression, and promoter methylation were analyzed using UALCAN and Human Protein Atlas (HPA), while mRNA expression was further validated via GENT2. The potential prognostic values of GINS1 were evaluated through KM plotter. Then, cBioPortal was utilized to examine the GINS1-related genetic mutations and copy number variations (CNVs), while pathway enrichment analysis was performed using DAVID. Moreover, a correlational analysis between GINS1 expression and CD8+ T immune cells and a the construction of gene-drug interaction network was performed using TIMER, CDT, and Cytoscape. The GINS1 was found down-regulated in a single subtypes of human cancer while commonly up-regulated in 23 different other subtypes. The up-regulation of GINS1 was significantly correlated with the poor overall survival (OS) of Liver Hepatocellular Carcinoma (LIHC), Lung Adenocarcinoma (LUAD), and Kidney renal clear cell carcinoma (KIRC). The GINS1 was also found up-regulated in LIHC, LUAD, and KIRC patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of GINS1 in two diverse pathways, while few interesting correlations were also documented between GINS1 expression and its promoter methylation level, CD8+ T immune cells level, and CNVs. Moreover, we also predicted few drugs that could be used in the treatment of LIHC, LUAD, and KIRC by regulating the GINS1 expression. The expression profiling of GINS1 in the current study has suggested it a novel shared diagnostic and prognostic biomarker of LIHC, LUAD, and KIRC.

Evaluation of tumor mutational burden in small early hepatocellular carcinoma and progressed hepatocellular carcinoma

While researchers know that tumor mutational burden (TMB) is low in hepatocellular carcinoma (HCC), prior studies have not investigated TMB in cirrhosis, small early HCC and progressed HCC. HCC (n = 18) and cirrhosis (n = 6) cases were identified. TMB was determined by a 1.7 megabase, 409-gene next-generation sequencing panel. TMB values were defined as the number of nonsynonymous variants per megabase of sequence. There was no significant difference between cirrhosis versus small early HCC or between cohorts when stratified by size, early versus progressed, differentiation or morphology. There was a significant difference between cirrhosis and small early HCC versus progressed HCC (p = 0.045), suggesting TMB may be related to HCC progression. TMB similarities in small early HCC and background cirrhosis suggest TMB is not a useful tool for diagnosing small early HCC. Additional study is needed to address TMB in histological and molecular subsets of HCC.

Value of heat shock protein 90 combined with alpha-fetoprotein in early diagnosis of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the sixth most common cancer in the world, and early diagnosis mainly relies on serological examination. With the deepening of molecular research of heat shock protein 90 (HSP90) in hepatocellular carcinoma, this study innovatively explored the value of HSP90 combined with alpha-fetoprotein (AFP) in early diagnosis of HCC.

AIM

To evaluate the diagnostic value of HSP90 combined with AFP in HCC.

METHODS

A total of 383 subjects, including patients with primary liver cancer, those with posthepatitic cirrhosis (types B and C), and healthy subjects, were selected from August 2017 to July 2020. The serum concentration of AFP was measured by electrochemical method, the serum concentration of HSP90 was measured by ELLISA, and the results were processed and analyzed using statistical software.

RESULTS

When AFP or HSP90 alone was used for the diagnosis of HCC, the sensitivity of HSP90 was higher than that of AFP, while the specificity of AFP was higher than that of HSP90. The sensitivity and specificity of AFP combined with HSP90 in the diagnosis of HCC were 87.8% and 91.2%, respectively.

CONCLUSION

AFP combined with HSP90 can significantly improve the diagnostic value of either of them alone in HCC.

Serum Cartilage Oligomeric Matrix Protein and Golgi Protein-73: New Diagnostic and Predictive Tools for Liver Fibrosis and Hepatocellular Cancer?

Simple Summary

Hepatocellular carcinoma (HCC) ranks as the sixth most common malignancy and represents the fourth leading cause of cancer-related deaths. However, most HCC cases are insidious in the early stages leading to a delay in diagnosis with limited treatment options. In patients with chronic liver diseases, advanced liver fibrosis and cirrhosis are the leading risk factors for the development of HCC. Cartilage oligomeric matrix protein (COMP) and Golgi protein-73 (GP73) are two biomarkers that have been associated with the progression of chronic liver disease, including inflammation, fibrosis, and HCC. The aim of our study was to assess the performance of the combination of these biomarkers. We confirmed, in a large cohort of 288 patients with chronic liver diseases, that the combination of GP73 and COMP had a high discriminative ability to detect severe fibrosis/cirrhosis and is efficient in predicting the development of HCC.

Abstract

The cartilage oligomeric matrix protein (COMP) and Golgi-protein-73 (GP73) have been proposed as markers of liver fibrosis and hepatocellular carcinoma (HCC). Our aim was to assess the performance of the combination of these markers in diagnosing cirrhosis and predicting HCC development. Sera from 288 consecutive patients with chronic liver diseases were investigated by using COMP and GP73-ELISAs. Dual positivity for COMP (>15 U/L) and GP73 (>20 units) was observed in 24 (8.3%) patients, while 30 (10.4%) were GP73(+)/COMP(−), 37/288 (12.8%) GP73(−)/COMP(+), and 197 (68.5%) GP73(−)/COMP(−). Positivity for both markers was associated with cirrhosis [23/24 (95.8%) for GP73(+)/COMP(+) vs. 22/30 (73.3%) for GP73(+)/COMP(−) vs. 25/37 (67.6%) for GP73(−)/COMP(+) vs. 46/197 (23.4%) for GP73(−)/COMP(−); P < 0.001]. The combination of GP73, COMP, the aspartate aminotransferase/platelets ratio index, and the Fibrosis-4 score had even higher diagnostic accuracy to detect the presence of cirrhosis [AUC (95% CI): 0.916 (0.878–0.946)] or significant liver fibrosis (METAVIR ≥ F2) [AUC (95% CI): 0.832 (0.768–0.883)] than each marker alone. Kaplan-Meier analysis showed that positivity for both GP73 and COMP was associated with higher rates of HCC development (P < 0.001) and liver-related deaths (P < 0.001) during follow-up. In conclusion, the combination of GP73 and COMP seems efficient to detect cirrhosis and predict worse outcomes and the development of HCC in patients with chronic liver diseases.

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.

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.

Peripheral Blood Genetic Biomarkers for the Early Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and has high mortality. Biomarkers related to HCC, such as alpha-fetoprotein, and imaging technology, such as ultrasound and computed tomography, have been used to screen and monitor HCC, but HCC is still difficult to diagnose effectively in the early stage due to the low sensitivity of the above mentioned traditional methods. There is an urgent need for noninvasive biomarkers to facilitate the screening and early diagnosis of HCC. With the advancement of next-generation sequencing, genetic biomarkers are becoming the core of cancer diagnosis. Genetic biomarkers such as peripheral blood circulating tumor DNA, microRNAs, long noncoding RNAs, circular RNAs, and exosomes have become the focus of early HCC diagnostics. HCC genetic biomarkers have been implemented in clinical practice. In this review, we describe the available literature on peripheral blood genetic biomarkers in the diagnosis of early HCC.

Serum Golgi protein 73 as a sensitive biomarker for early detection of hepatocellular carcinoma among Egyptian patients with hepatitis C virus-related cirrhosis

Background

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy. Early detection of HCC is always a challenging task for physicians. Serum Golgi protein 73 (GP73) is considered a potential tumor marker for the detection of HCC. However, the diagnostic value of GP73 for the HCC diagnosis is still controversial. This research was designed to assess the diagnostic efficacy of GP73 as a diagnostic tool for HCC in cases with hepatitis C virus-related cirrhosis.

Methods

Eighty-seven subjects were allocated into four different groups in this prospective research (HCC, liver cirrhosis, chronic hepatitis C, and healthy control group). Serum alpha-fetoprotein (AFP) and GP73 were tested for all subjects in the study. Detection of focal hepatic lesions was based on imaging by abdominal ultrasonography and triphasic computed tomography.

Results

The cut-off values for GP73 and AFP were 534.5 ng/L and 32 ng/mL, respectively. The specificity of GP73 was 87%, and the sensitivity was 88%, while the specificity and sensitivity of AFP levels were 80% and 72%, respectively. The negative predictive value of GP73 was 87.5%, and the positive predictive value of GP73 was 84.6%, while the same parameters of AFP were 73.1% and 75%, respectively.

Conclusion

Serum Golgi protein 73 could be a valuable biomarker and a useful diagnostic tool for the early diagnosis of HCC in cases of hepatitis C virus-related cirrhosis.

CancerLivER: a database of liver cancer gene expression resources and biomarkers

Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

Multi-Phase Cross-modal Learning for Noninvasive Gene Mutation Prediction in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the fourth most common cause of cancer-related death worldwide. Understanding the underlying gene mutations in HCC provides great prognostic value for treatment planning and targeted therapy. Radiogenomics has revealed an association between non-invasive imaging features and molecular genomics. However, imaging feature identification is laborious and error-prone. In this paper, we propose an end-to-end deep learning framework for mutation prediction in APOB, COL11A1 and ATRX genes using multiphasic CT scans. Considering intra-tumour heterogeneity (ITH) in HCC, multi-region sampling technology is implemented to generate the dataset for experiments. Experimental results demonstrate the effectiveness of the proposed model.

Establishing peripheral PD-L1 as a prognostic marker in hepatocellular carcinoma patients: how long will it come true?

BACKGROUND

The prognostic role of intratumoral programmed cell death ligand 1 (PD-L1) expression in hepatocellular carcinoma (HCC) has been investigated by several meta-analyses. However, the prognostic value of pretreatment peripheral PD-L1 (PPPD-L1) level in HCC remains undetermined. Thus, this systemic review aimed to establish PPPD-L1 as a new prognostic marker in HCC according to available evidence.

METHODS

Case-control studies investigating the prognostic role of PPPD-L1 in HCC were systemically sought in the database of PubMed and Web of Science until March 25th, 2020. Our main concern is survival results, including overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS). The combined results were summarized in narrative form according to data extracted from each included study.

RESULTS

Finally, nine studies published from 2011 to 2019, were incorporated into this systemic review. Among these, six studies evaluated the PD-L1 expression by enzyme-linked immunosorbent assay (ELISA) from blood serum, and three studies evaluated the PD-L1 expression by flow cytometric analysis from peripheral blood mononuclear cells (PBMC). According to the extracted evidence, high PPPD-L1 expression, measured in either blood serum or PBMC, is associated with poor OS, poor DFS, and poor PFS. Meanwhile, PPPD-L1 was also correlated with enlarged tumor size and more likely with advanced tumor stage as well as vascular invasion.

CONCLUSION

High PPPD-L1 level is associated with increased mortality rate and increased recurrence rate in HCC. As a convenient serum marker, PPPD-L1 could be a promising marker of prognosis in HCC patients.

Immunological Basis of Genesis of Hepatocellular Carcinoma: Unique Challenges and Potential Opportunities through Immunomodulation

A majority of hepatocellular carcinoma (HCC) develops in the setting of persistent chronic inflammation as immunological mechanisms have been shown to play a vital role in the initiation, growth and progression of tumours. The index review has been intended to highlight ongoing immunological changes in the hepatic parenchyma responsible for the genesis and progression of HCC. The in-situ vaccine effect of radiofrequency (RF) is through generation tumour-associated antigens (TAAs), following necrosis and apoptosis of tumour cells, which not only re-activates the antitumour immune response but can also act in synergism with checkpoint inhibitors to generate a superlative effect with intent to treat primary cancer and distant metastasis. An improved understanding of oncogenic responses of immune cells and their integration into signaling pathways of the tumour microenvironment will help in modulating the antitumour immune response. Finally, we analyzed contemporary literature and summarised the recent advances made in the field of targeted immunotherapy involving checkpoint inhibitors along with RF application with the intent to reinstate antitumour immunity and outline future directives in very early and early stages of HCC.

Golgi Protein 73 versus Alpha-Fetoprotein as a New Biomarker in Early Diagnosis of Hepatocellular Carcinoma

Background

Screening of early hepatocellular carcinoma (HCC) diagnosis is the greatest challenge for hepatologists. Alpha-fetoprotein (AFP) is the most common non-invasive biomarker used in HCC diagnosis.

Objectives and Aims

To make a comparison between the new biomarker Golgi protein 73 (GP73) versus the standard biomarker AFP in the diagnosis of HCC.

Methods

Our study was a case-control study, and 60 patients were included in the study. They were divided into two groups: 1) HCC patients with either chronic HBV or HCV infection (n=30); and 2) non-HCC patients with HBV or HCV infection who had either chronic hepatitis or liver cirrhosis (n=30). In addition, 30 healthy volunteers were included as a control group. Patients were subjected to liver function tests, kidney function tests, serum Golgi protein 73 and AFP levels. Imaging diagnosis of HCC was done by computed tomography (CT) or magnetic resonance imaging (MRI) based on American Association for the Study of Liver Diseases (AASLD) practice guidelines.

Results

Statistically significant differences between groups in terms of serum AFP (p<0.001) and GP73 (p<0.001) were found. Non-HCC patients (chronic hepatitis and liver cirrhosis) and HCC patients had significantly higher AFP and GP73 than the control group. In addition, patients with HCC had significantly higher AFP and GP73 than chronic hepatitis and cirrhotic patients. GP73 had higher diagnostic performance than AFP. At a cut-off value of ≥8.4 ng/mL, GP73 yielded a sensitivity of 86.7% and specificity of 89% for the discrimination between HCC and normal populations. Similarly, at a cut-off value of ≥8.45 ng/mL, GP73 yielded a sensitivity of 83.3% and specificity of 84% for the discrimination between HCC patients and non-HCC patients. On the other hand, AFP at a cut-off value of ≥2.4 ng/mL yielded a sensitivity of 75.4% and specificity of 90% for the discrimination between HCC and normal populations; and at a cut-off value of ≥20.85 ng/mL, AFP yielded a sensitivity of 72.2% and specificity of 86.2% for the discrimination between HCC and non-HCC patients.

Conclusion

Golgi protein 73 is a promising and accurate biomarker for early detection of HCC.

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

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

Comparison of immune profiles between hepatocellular carcinoma subtypes

Immunotherapy, especially immune checkpoint inhibitors, is becoming a promising treatment for hepatocellular carcinoma (HCC). However, the response rate remains limited due to the heterogeneity of HCC samples. Molecular subtypes of HCC vary in genomic background, clinical features, and prognosis. This study aims to compare the immune profiles between HCC subtypes and find subtype-specific immune characteristics that might contribute to the prognosis and potential of immunotherapy. The immune profiles consist of immune-related genes, cytolytic activity, immune pathways, and tumor-infiltrating lymphocytes. HCC-c1 samples showed an overall higher activation level of immune genes and pathways, and this pattern was consistent in validation sets. We associated the difference in immune profiles with the activation level of cancer hallmarks and genomic mutations. There was a negative correlation between most of the metabolism pathway and immune-related pathways in HCC samples. CTNNB1/WNT signaling pathway mutation, one of the common mutations in HCC, appears to be associated with the expression of immune genes as well. These results reveal the difference of immune profiles between HCC subtypes and possible reasons and influence, which may also deepen our understanding of the carcinogenesis process.

Prognostic value of non-invasive serum Cytokeratin 18 detection in gastrointestinal cancer: a meta-analysis

Background: Gastrointestinal cancer is one of the most common neoplasms. Cytokeratin 18(CK18) is widely expressed in many different organs and cancers. Emerging data suggested conflicting results about the role of CK18 during carcinogenesis. The aim of this study is to systematically review the prognostic value of circulating CK18 (M65) and caspase-Cleaved CK18 (M30) in digestive cancers.

Materials and Methods: We searched major database for manuscripts reporting the effect of pretreatment CK18 on survival of digestive cancer patients. Revman5.3 and R were the software used for analysis. Pooled multivariable-adjusted hazard ratios (HR) for overall survival (OS) were calculated in all patients and many different subgroup analyses by stratifying on tumor type, metastasis stage, and ethnicity.

Results: 11 original studies were included for analysis. A low level of M30 and M65 were shown to be a protective factor for all cancer patients (HR 0.49, 95%CI 0.33-0.73, P=0.0003; HR 0.48, 95% CI 0.32-0.70, P =0.0001, respectively). The low M30 remained to be a protective factor for metastasized cancer patients while M65 had no statistically significant correlation with prognosis.

Conclusions: Non-invasive total and cleaved CK18 level detection by ELISA could be potentially a useful predictor of prognosis of digestive cancer patients. Further studies are warranted to investigate the molecular mechanisms of CK18.

Hsa_circ_0028502 and hsa_circ_0076251 are potential novel biomarkers for hepatocellular carcinoma

Circular RNAs (circRNAs) have been increasingly revealed to be desirable biomarkers for some tumors, including hepatocellular carcinoma (HCC). Combined with our previous microarray screening results, we aimed to determine the hsa_circ_0028502 and hsa_circ_0076251 expression features in HCC, analyze the relationship between their expression level and clinical and pathological characteristics, and investigate their diagnostic and prognostic values. Our data demonstrated that the hsa_circ_0028502 and hsa_circ_0076251 levels were considerably lower in HCC tissues than in adjacent paracancerous tissues (P < .001). Further study revealed that hsa_circ_0028502 expression levels were related to tumor node metastasis (TNM) stage (P = .015) and that hsa_circ_0076251 expression levels were related to Barcelona Clinic Liver Cancer (BCLC) stage (P = .038), comorbidity with type 2 diabetes mellitus (P = .023) and the presence of serum HbsAg (P = .044). Furthermore, the degree of expression of both hsa_circ_0028502 and hsa_circ_0076251 increased from HCC to liver cirrhosis (LC) to chronic hepatitis (CH). The receiver operating characteristic (ROC) curve demonstrated that hsa_circ_0028502 and hsa_circ_0076251 could serve as fairly accurate markers to distinguish HCC tissues from CH tissues and LC tissues, as well as distinguishing LC tissues from CH tissues. Cox regression analysis showed that low expression of has_circ_0076251 was associated with unfavorable survival rates in HCC (HR = 0.46; 95% CI = 0.22‐0.98; P < .05). These findings implied that hsa_circ_0028502 and hsa_circ_0076251 were potentially valuable biomarkers for HCC diagnosis, whereas hsa_circ_0076251 could be used as a prognostic indicator for HCC.

Current status of hepatocellular carcinoma detection: screening strategies and novel biomarkers

Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality worldwide. Delayed diagnosis is a major factor responsible for the poor prognosis of HCC. Several advances have been made in the field of liver imaging with the use of novel imaging contrasts, improving current imaging techniques with contrast-enhanced computed tomography (CT) and magnetic resonance imaging (MRI), introduction of new technologies such as contrast liver ultrasound, and development of novel biomarkers with the goal of early detection of HCC and improving outcomes of patients with HCC. This review focuses on current surveillance strategies and development of biomarkers with the goal of early detection of HCC.

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

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