The use of minimally invasive biomarkers for the diagnosis and prognosis of hepatocellular carcinoma

Tumour-specific activation of a tumour-blood transport improves the diagnostic accuracy of blood tumour markers in mice

BACKGROUND

The accuracy of blood-based early tumour recognition is compromised by signal production at non-tumoral sites, low amount of signal produced by small tumours, and variable tumour production. Here we examined whether tumour-specific enhancement of vascular permeability by the particular tumour homing peptide, iRGD, which carries dual function of binding to integrin receptors overexpressed in the tumour vasculature and is known to promote extravasation via neuropilin-1 receptor upon site-specific cleavage, might be useful to improve blood-based tumour detection by inducing a yet unrecognised vice versa tumour-to-blood transport.

METHODS

To detect an iRGD-induced tumour-to-blood transport, we examined the effect of intravenously injected iRGD on blood levels of α-fetoprotein (AFP) and autotaxin in several mouse models of hepatocellular carcinoma (HCC) or in mice with chronic liver injury without HCC, and on prostate-specific antigen (PSA) levels in mice with prostate cancer.

FINDINGS

Intravenously injected iRGD rapidly and robustly elevated the blood levels of AFP in several mouse models of HCC, but not in mice with chronic liver injury. The effect was primarily seen in mice with small tumours and normal basal blood AFP levels, was attenuated by an anti-neuropilin-1 antibody, and depended on the concentration gradient between tumour and blood. iRGD treatment was also able to increase blood levels of autotaxin in HCC mice, and of PSA in mice with prostate cancer.

INTERPRETATION

We conclude that iRGD induces a tumour-to-blood transport in a tumour-specific fashion that has potential of improving diagnosis of early stage cancer.

FUNDING

Deutsche Krebshilfe, DKTK, LOEWE-Frankfurt Cancer Institute.

Risks and Clinical Predictors of Hepatocellular Carcinoma in Chinese Populations: A Real-World Study of 10,359 Patients in Six Medical Centers

Purpose

Early detection of hepatocellular carcinoma (HCC) through surveillance could reduce this cancer-associated mortality. We aimed to develop and validate algorithms using panel serum biomarkers to identify HCC in a real-world multi-center study in China.

Patients and Methods

A total of 10,359 eligible subjects, including HCCs and benign liver diseases (BLDs), were recruited from six Chinese medical centers. The three nomograms were built using logistic regression and their sensitivities and specificities were carefully assessed in training and validation cohorts. HCC patients after surgical resection were followed to determine the prognostic values of these algorithms. Prospective surveillance performance was assessed in a cohort of chronic hepatitis B patients during 144 weeks follow-up.

Results

Independent risk factors such as alpha-fetoprotein (AFP), lens cuinaris agglutinin-reactive fraction of AFP (AFP-L3), des-gamma-carboxy prothrombin (DCP), albumin (ALB), and total bilirubin (TBIL) obtained from train cohort were used to construct three nomograms (LAD, C-GALAD, and TAGALAD) using logistic regression. In the training and two validation cohorts, their AUCs were all over 0.900, and the higher AUCs appeared in TAGALAD and C-GALAD. Furthermore, the three nomograms could effectively stratify HCC into two groups with different survival and recurrence outcomes in follow-up validation. Notably, TAGALAD could predict HCC up to 48 weeks (AUC: 0.984) and 24 weeks (AUC: 0.900) before clinical diagnosis.

Conclusion

The proposed nomograms generated from real-world Chinese populations are effective and easy-to use for HCC surveillance, diagnosis, as well as prognostic evaluation in various clinical scenarios based on data feasibility.

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

BACKGROUND

Hepatocellular carcinoma (HCC) accounts for 75% of primary liver tumors. Controlling risk factors associated with its development and implementing screenings in risk populations does not seem sufficient to improve the prognosis of these patients at diagnosis. The development of a predictive prognostic model for mortality at the diagnosis of HCC is proposed.

METHODS

In this retrospective multicenter study, the analysis of data from 191 HCC patients was conducted using machine learning (ML) techniques to analyze the prognostic factors of mortality that are significant at the time of diagnosis. Clinical and analytical data of interest in patients with HCC were gathered.

RESULTS

Meeting Milan criteria, Barcelona Clinic Liver Cancer (BCLC) classification and albumin levels were the variables with the greatest impact on the prognosis of HCC patients. The ML algorithm that achieved the best results was random forest (RF).

CONCLUSIONS

The development of a predictive prognostic model at the diagnosis is a valuable tool for patients with HCC and for application in clinical practice. RF is useful and reliable in the analysis of prognostic factors in the diagnosis of HCC. The search for new prognostic factors is still necessary in patients with HCC.

Application of Machine Learning Techniques to Assess Alpha-Fetoprotein at Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver tumor and is associated with high mortality rates. Approximately 80% of cases occur in cirrhotic livers, posing a significant challenge for appropriate therapeutic management. Adequate screening programs in high-risk groups are essential for early-stage detection. The extent of extrahepatic tumor spread and hepatic functional reserve are recognized as two of the most influential prognostic factors. In this retrospective multicenter study, we utilized machine learning (ML) methods to analyze predictors of mortality at the time of diagnosis in a total of 208 patients. The eXtreme gradient boosting (XGB) method achieved the highest values in identifying key prognostic factors for HCC at diagnosis. The etiology of HCC was found to be the variable most strongly associated with a poorer prognosis. The widely used Barcelona Clinic Liver Cancer (BCLC) classification in our setting demonstrated superiority over the TNM classification. Although alpha-fetoprotein (AFP) remains the most commonly used biological marker, elevated levels did not correlate with reduced survival. Our findings suggest the need to explore new prognostic biomarkers for individualized management of these patients.

Insights into the history and tendency of liver transplantation for liver cancer: a bibliometric-based visual analysis

Research on liver transplantation (LT) for liver cancer has gained increasing attention. This paper has comprehensively described the current status, hotspots and trends in this field. A total of 2991 relevant articles from 1 January 1963 to 28 February 2023 were obtained from the Web of Science Core Collection. VOSviewer and CiteSpace software were utilized as bibliometric tools to analyze and visualize knowledge mapping. Between 1963 and 2023, the number of papers in the area of LT for liver cancer increased continuously. A total of 70 countries/regions, 2303 institutions and 14 840 researchers have published research articles, with the United States and China being the two most productive countries. Our bibliometric-based visual analysis revealed the expansion of LT indications for liver cancer and the prevention/treatment of cancer recurrence as ongoing research hotspots over the past decades. Meanwhile, emerging studies also focus on downstaging/bridging treatments before LT and the long-term survival of LT recipient, in particular the precise application of immunosuppressants.

Detection of Circulating Cell-free DNA to Diagnose Hepatocellular Carcinoma in Chinese Population: A Systematic Review and Meta-analysis

BACKGROUND

Cell-free circulating DNA has been known for many years, but this knowledge has not been beneficial for diagnosis. In this meta-analysis, we examine the diagnostic role of circulating cell-free DNA in HCC patients to find a reliable biomarker for the early detection of HCC.

MATERIALS AND METHODS

We performed a systematic literature search using Science Direct, Web of Science, PubMed/Medline, Scopus, Google Scholar, and Embase, up to April 1st, 2022. Meta-Disc V.1.4 and Comprehensive Meta-Analysis V.3.3 software calculated the pooled specificity, sensitivity, area under the curve (AUC), diagnostic odds ratio (DOR), positive likelihood ratio (PLR), negative likelihood ratio (NLR) Q*index, and summary receiver-- operating characteristic (SROC) for the role of cfDNA as a biomarker for HCC patients. Moreover, the subgroup analyses have been performed based on sample types (serum/plasma) and detection methods (MS-PCR/methylation).

RESULTS

A total of 7 articles (9 studies) included 697 participants (485 cases and 212 controls). The overall pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were 0.706 (95% CI: 0.671 - 0.739), 0.905 (95% CI: 0.865 - 0.937), 6.66 (95% CI: 4.36 - 10.18), 0.287 (95% CI: 0.185 - 0.445), 28.40 (95% CI: 13.01 - 62.0), and 0.93, respectively. We conducted a subgroup analysis of diagnostic value, which showed that the plasma sample had a better diagnostic value compared to the serum.

CONCLUSION

This meta-analysis showed that cfDNA could be a fair biomarker for diagnosing HCC patients.

DNA damage repair-related gene signature for identifying the immune status and predicting the prognosis of hepatocellular carcinoma

The heterogeneity of hepatocellular carcinoma (HCC) poses a challenge for accurate prognosis prediction. DNA damage repair genes (DDRGs) have an impact on a wide range of malignancies. However, the relevance of these genes in HCC prognosis has received little attention. In this study, we aimed to develop a prognostic signature to identify novel therapy options for HCC. We acquired mRNA expression profiles and clinical data for HCC patients from The Cancer Genome Atlas (TCGA) database. A polygenic prognostic model for HCC was constructed using selection operator Cox analysis and least absolute shrinkage. The model was validated using International Cancer Genome Consortium (ICGC) data. Overall survival (OS) between the high-risk and low-risk groups was compared using Kaplan‒Meier analysis. Independent predictors of OS were identified through both univariate and multivariate Cox analyses. To determine immune cell infiltration scores and activity in immune-related pathways, a single-sample gene set enrichment analysis was performed. The protein and mRNA expression levels of the prognostic genes between HCC and normal liver tissues were also examined by immunohistochemistry (IHC), immunofluorescence (IF) and quantitative real-time PCR (qRT-PCR). A novel ten-gene signature (CHD1L, HDAC1, KPNA2, MUTYH, PPP2R5B, NEIL3, POLR2L, RAD54B, RUVBL1 and SPP1) was established for HCC prognosis prediction. Patients in the high-risk group had worse OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the predictive ability of this prognostic gene signature. Multivariate Cox analysis showed that the risk score was an independent predictor of OS. Functional analysis revealed a strong association with cell cycle and antigen binding pathways, and the risk score was highly correlated with tumor grade, tumor stage, and types of immune infiltrate. High expression levels of the prognostic genes were significantly correlated with increased sensitivity of cancer cells to antitumor drugs. IHC, IF and qRT-PCR all indicated that the prognostic genes were highly expressed in HCC relative to normal liver tissue, consistent with the results of bioinformatics analysis. Ten DDRGs were utilized to create a new signature for identifying the immunological state of HCC and predicting prognosis. In addition, blocking these genes could represent a promising treatment.

Development of a clinical scoring model to predict the overall and relapse‑free survival of patients with hepatocellular carcinoma following a hepatectomy

Hepatocellular carcinoma (HCC) is a highly lethal disease, and surgical resection is one of the major treatment methods used. However, to date, at least to the best of our knowledge, there is no effective prognostic scoring system for the overall survival (OS) and relapse-free survival (RFS) of patients following hepatectomy. The present study developed a low-cost and easy-to-use model based on the clinicopathological characteristics of patients with HCC for assessment of outcome prediction and risk stratification. A total of 690 patients with HCC undergoing surgery were included and randomly divided into two cohorts (n=345). Cox regression analysis was conducted to investigate the association between the clinicopathological and treatment features, and patient survival. Multivariate analysis revealed that ascites, vascular tumor thrombus, low tumor differentiation and extrahepatic metastasis were independent risk factors for OS. Extrahepatic metastasis and multiple tumors were independent risk factors to predict tumor recurrence. These variables were weighted to construct the ascites, vascular tumor thrombus, low tumor differentiation, extrahepatic metastasis and multiple tumors (AVLEM) score based on the cumulative incidence (CuI) of the aforementioned variables, and the patients were classified into grade 0 (CuI=0), grade 1 (CuI=1 for OS and CuI ≥1 for RFS), and grade 2 (CuI ≥2) subgroups, respectively. Kaplan-Meier analysis revealed that the OS and RFS differed significantly among the subgroups; however, the survival rate between the two cohorts did not exhibit any marked differences. On the whole, the present study demonstrates that with this AVLEM scoring system, patients with HCC with a high score had a poor OS and RFS; thus, it is suggested that such patients undergo imaging examinations following a hepatectomy more frequently.

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a primary liver cancer characterized by hepatocellular differentiation. HCC is molecularly heterogeneous with a wide spectrum of histopathology. The prognosis of patients with HCC is generally poor, especially in those with advanced stages. HCC remains a diagnostic challenge for pathologists because of its morphological and phenotypic diversity. However, recent advances have enhanced our understanding of the molecular genetics and histological subtypes of HCC. Accurate diagnosis of HCC is important for patient management and prognosis. This review provides an update on HCC pathology, focusing on molecular genetics, histological subtypes, and diagnostic approaches.

Differentially expressed non-coding RNAs and their regulatory networks in liver cancer

The vast majority of human transcriptome is represented by various types of small RNAs with little or no protein-coding capability referred to as non-coding RNAs (ncRNAs). Functional ncRNAs include microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which are expressed at very low, but stable and reproducible levels in a variety of cell types. ncRNAs regulate gene expression due to miRNA capability of complementary base pairing with mRNAs, whereas lncRNAs and circRNAs can sponge miRNAs off their target mRNAs to act as competitive endogenous RNAs (ceRNAs). Each miRNA can target multiple mRNAs and a single mRNA can interact with several miRNAs, thereby creating miRNA-mRNA, lncRNA-miRNA-mRNA, and circRNA-miRNA-mRNA regulatory networks. Over the past few years, a variety of differentially expressed miRNAs, lncRNAs, and circRNAs (DEMs, DELs, and DECs, respectively) have been linked to cancer pathogenesis. They can exert both oncogenic and tumor suppressor roles. In this review, we discuss the recent advancements in uncovering the roles of DEMs, DELs, and DECs and their networks in aberrant cell signaling, cell cycle, transcription, angiogenesis, and apoptosis, as well as tumor microenvironment remodeling and metabolic reprogramming during hepatocarcinogenesis. We highlight the potential and challenges in the use of differentially expressed ncRNAs as biomarkers for liver cancer diagnosis and prognosis.

Roles of Extracellular Vesicles on the Progression and Metastasis of Hepatocellular Carcinoma

Liver cancer is a global health challenge as it is the third leading cause of cancer death worldwide. Hepatocellular carcinoma (HCC) is the most common type of liver cancer and is often found in liver cells, where it is associated with high morbidity and mortality rates. Recent studies have shown that extracellular vesicles (EVs) secreted by HCC cells play a critical role in HCC progression and metastasis. EVs contain proteins, nucleic acids, lipids, and metabolites as cargos. EVs derived from HCC cells can transfer oncogenic factors to surrounding cells leading to increased tumor growth, cell invasion, and angiogenesis. In this review, we summarize the roles that EVs play and the specific effects of their cargos on HCC progression and metastasis and identify potential therapeutic targets for HCC treatment.

Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma

BACKGROUND

Necroptosis is a necrotic programmed cell death with potent immunogenicity. Due to the dual effects of necroptosis on tumor growth, metastasis and immunosuppression, we evaluated the prognostic value of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC).

METHODS

We first analyzed RNA sequencing and clinical HCC patient data obtained to develop an NRG prognostic signature based on the TCGA dataset. Differentially expressed NRGs were further evaluated by GO and KEGG pathway analyses. Next, we conducted univariate and multivariate Cox regression analyses to build a prognostic model. We also used the dataset obtained from the International Cancer Genome Consortium (ICGC) database to verify the signature. The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the immunotherapy response. Furthermore, we investigated the relationship between the prediction signature and chemotherapy treatment response in HCC.

RESULTS

We first identified 36 differentially expressed genes out of 159 NRGs in hepatocellular carcinoma. Enrichment analysis showed that they were mainly enriched in the necroptosis pathway. Four NRGs were screened by Cox regression analysis to establish a prognostic model. The survival analysis revealed that the overall survival of patients with high-risk scores was significantly shorter than that of patients with low-risk scores. The nomogram demonstrated satisfactory discrimination and calibration. The calibration curves validated a fine concordance between the nomogram prediction and actual observation. The efficacy of the necroptosis-related signature was also validated by an independent dataset and immunohistochemistry experiments. TIDE analysis revealed that patients in the high-risk group were possibly more susceptible to immunotherapy. Furthermore, high-risk patients were found to be more sensitive to conventional chemotherapeutic medicines such as bleomycin, bortezomib, and imatinib.

CONCLUSION

We identified 4 necroptosis-related genes and established a prognostic risk model that could potentially predict prognosis and response to chemotherapy and immunotherapy in HCC patients in the future.

Potential Value and Application of Liquid Biopsy in Tumor, Neurodegeneration, and Muscle Degenerative Diseases

Liquid biopsy provides a promising alternative for the detection of disease-specific markers due to its superior noninvasive and original tissue representativeness. Liquid biopsies have a wide range of health and disease applications involving components ranging from circulating cells to acellular nucleic acid molecules and other metabolites. Here, we review the different components of liquid biopsy and investigate the most advanced noninvasive methods for detecting these components as well as their existing problems and trends. In particular, we emphasize the importance of analyzing liquid biopsy data from extracellular vesicles and small nucleic acids in neurological and muscle degeneration, with the aim of using this technique to enhance personalized healthcare. Although previous reviews have focused on cancer, this review mainly emphasizes the potential application of extracellular vesicles and microRNAs in liquid biopsy in neurodegeneration and muscle degeneration.

Conductive metal-organic framework based label-free electrochemical detection of circulating tumor DNA

An ultrasensitive electrochemical biosensor was designed for the rapid label-free detection of circulating tumor DNA (ctDNA, EGFR 19 Dels for non-small cell lung cancer, NSCLC). We linked the highly conjugated tricatecholate, 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) with Ni(II) ions into the two-dimensional porous conductive metal-organic frameworks (MOFs), which is termed Ni-catecholates (Ni-CAT). Then, the AuNPs/Ni-catecholates/carbon black/polarized pencil graphite electrode (AuNPs/Ni-CAT/CB/PPGE) was obtained by electrodeposition of AuNPs on the surface of PPGE modified with Ni-CAT/CB composite materials. The AuNPs/Ni-CAT/CB/PPGE were used for label-less detection of ctDNA, with a total detection time of only 30 min. Under optimal detection conditions, the AuNPs/Ni-CAT/CB/PPGE sensor exhibited excellent detection performance with good linear response to ctDNA over a wide concentration range and the detection limit down to the femtomolar level. The sensor was applied to the determination of ctDNA in serum samples with high sensitivity. This simple, efficient, and expeditious method has practical value in liquid biopsy of ctDNA and has potential for development in early detection, treatment, and prognosis of tumors. Herein, an ultrasensitive electrochemical biosensor was designed for the rapid label-free detection of ctDNA (EGFR 19 Dels for non-small cell lung cancer, NSCLC). We linked the highly conjugated tricatecholate, 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) with Ni(II) ions into the two-dimensional porous conductive metal-organic frameworks (MOFs), which is termed as Ni-catecholates (Ni-CAT). Then, the AuNPs/Ni-catecholates/carbon black/polarized pencil graphite electrode (AuNPs/Ni-CAT/CB/PPGE) was obtained by electrodeposition of AuNPs on the surface of PPGE modified with Ni-CAT/CB composite materials. The AuNPs/Ni-CAT/CB/PPGEs were used for label-less detection of ctDNA, with a total detection time of only 30 min. Under optimal detection conditions, the AuNPs/Ni-CAT/CB/PPGE sensor exhibited excellent detection performance with good linear response to ctDNA in the concentration range of 1 × 10^-15 M to 1 × 10^-6 M and with a detection limit as low as 0.32 fM. The sensor was applied for determination of ctDNA in serum samples and gave high sensitivity. This simple, efficient and expeditious method has practical value in liquid biopsy of ctDNA and has potential for development in early detection, treatment and prognosis of tumors.

Combined Hepatocellular-Cholangiocarcinoma: An Update on Pathology and Diagnostic Approach

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare primary liver carcinoma displaying both hepatocytic and cholangiocytic differentiation within the same tumor. Relative to classic hepatocellular carcinoma (HCC), cHCC-CCA has more aggressive behavior and a poorer prognosis. Though recent advances have improved our understanding of the biology underlying cHCC-CCAs, they remain diagnostically challenging for pathologists because of their morphologic and phenotypic diversity. Accurate diagnosis of cHCC-CCA is important for patient management and prognostication. Herein, we review recent updates on cHCC-CCA, focusing on tumor classification, pathology, and diagnostic approach.

Roles of lncRNAs Mediating Wnt/β-Catenin Signaling in HCC

Hepatocellular carcinoma (HCC) is considered the second most deadly cancer worldwide. Due to the absence of early diagnostic markers and effective therapeutic approaches, distant metastasis and increasing recurrence rates are major difficulties in the clinical treatment of HCC. Further understanding of its pathogenesis has become an urgent goal in HCC research. Recently, abnormal expression of long noncoding RNAs (lncRNAs) was identified as a vital regulator involved in the initiation and development of HCC. Activation of the Wnt/β-catenin pathway has been reported to obviously impact cell proliferation, invasion, and migration of HCC. This article reviews specific interactions, significant mechanisms and molecules related to HCC initiation and progression to provide promising strategies for treatment.

Epigenetics of alcohol-related liver diseases

Alcohol-related liver disease (ARLD) is a primary cause of chronic liver disease in the United States. Despite advances in the diagnosis and management of ARLD, it remains a major public health problem associated with significant morbidity and mortality, emphasising the need to adopt novel approaches to the study of ARLD and its complications. Epigenetic changes are increasingly being recognised as contributing to the pathogenesis of multiple disease states. Harnessing the power of innovative technologies for the study of epigenetics (e.g., next-generation sequencing, DNA methylation assays, histone modification profiling and computational techniques like machine learning) has resulted in a seismic shift in our understanding of the pathophysiology of ARLD. Knowledge of these techniques and advances is of paramount importance for the practicing hepatologist and researchers alike. Accordingly, in this review article we will summarise the current knowledge about alcohol-induced epigenetic alterations in the context of ARLD, including but not limited to, DNA hyper/hypo methylation, histone modifications, changes in non-coding RNA, 3D chromatin architecture and enhancer-promoter interactions. Additionally, we will discuss the state-of-the-art techniques used in the study of ARLD (e.g. single-cell sequencing). We will also highlight the epigenetic regulation of chemokines and their proinflammatory role in the context of ARLD. Lastly, we will examine the clinical applications of epigenetics in the diagnosis and management of ARLD.

Expression of IER3 in hepatocellular carcinoma: clinicopathology, prognosis, and potential regulatory pathways

Background

Immediate early response 3 (IER3) is correlated to the prognosis of several cancers, but the precise mechanisms underlying the regulation by IER3 of the occurrence and development of hepatocellular carcinoma (HCC) remain unknown.

Methods

The expression level of IER3 was examined by using in-house immunohistochemistry (IHC), public gene chip, and public RNA-sequencing (RNA-seq). The standardized mean difference (SMD) was calculated to compare the expression levels of IER3 between HCC patients and controls. The summary receiver operating characteristics (sROC) was plotted to comprehensively understand the discriminatory capability of IER3 between HCC and non-HCC group. The Kaplan-Meier curves and the combined hazard ratios (HRs) were used to determine the prognostic value of IER3 in HCC. Moreover, differentially expressed genes (DEGs) and co-expression genes (CEGs) were used to explored the molecular mechanisms of IER3 underlying HCC. hTFtarget was used to predict the transcription factors (TFs) of IER3. The binding site of TFs and the IER3 promoter region was forecasted using the JASPAR website. The relevant ChIP-seq data were used to determine whether TF peaks were present in the IER3 transcription initiation.

Results

A significantly increased expression of IER3 protein was found in HCC tissue relative to non-HCC tissue as detected by IHC (p < 0.001). Compared to 1,263 cases of non-HCC tissues, IER3 in 1483 cases of HCC tissues was upregulated (SMD = 0.42, 95% confidence interval [CI] [0.09-0.76]). The sROC showed that IER3 had a certain ability at differentiating HCC tissues (area under the curve (AUC) = 0.65, 95% CI [0.61-0.69]). Comprehensive analysis of the effect of IER3 on the prognosis of patients with HCC demonstrated that higher IER3 expression was associated with poor prognosis in HCC (HRs = 1.30, 95% CI [1.03-1.64]). Pathway enrichment analysis revealed that IER3-related genes were mostly enriched in the PI3K-Akt signaling pathway, cancer-related signaling pathways, the p53 signaling pathway, and other signaling pathways. Regulatory factor X5 (RFX5) was identified as a possible regulator of IER3-related TF.

Conclusion

IER3 may be a potential prognostic marker for HCC. The molecular mechanisms of IER3 in HCC warrant further study.

HOXA-AS3 Promotes Proliferation and Migration of Hepatocellular Carcinoma Cells via the miR-455-5p/PD-L1 Axis

Hepatocellular carcinoma (HCC) is the most prevalent type of hepatic carcinoma. Long noncoding RNAs (lncRNAs) are considered crucial regulators of gene expression; however, their functions in HCC are not well understood. Thus, the present study is aimed at elucidating the functions of the lncRNA HOXA-AS3 in HCC. The functions of the HOXA-AS3/miR-455-5p/programmed death-ligand 1 (PD-L1) axis were investigated in vitro via qRT-PCR and dual-luciferase reporter assays. The effect of HOXA-AS3 expression on tumor growth and metastasis was assessed using a mouse xenograft model. High HOXA-AS3 expression was observed in the HCC cell lines. Furthermore, overexpression of HOXA-AS3 in HCC cells enhanced proliferation, migration, and invasion, regulated the cell cycle, and retarded apoptosis. We also identified an miR-455-5p binding site in HOXA-AS3. By sponging miR-455-5p, HOXA-AS3 increased the expression of PD-L1. Additionally, both the inhibition of PD-L1 and overexpression of miR-455-5p reversed the effects on cell proliferation and invasion triggered by the overexpression of HOXA-AS3. In conclusion, HOXA-AS3 modulated the functions of HCC cells through the miR-455-5p/PD-L1 axis. Therefore, HOXA-AS3 may be a novel therapeutic target for HCC.

Diagnostic value of RNA for hepatocellular carcinoma: a network meta-analysis

Aim: The aim of this study was to evaluate the capacity of RNA in the diagnosis of hepatocellular carcinoma (HCC). Methods: A systematic review was conducted from PubMed, Cochrane Library, EMBASE and Web of Science databases via well-designed retrieval strategy. Subsequently, the network meta-analysis was performed by the STATA software. Results: Through statistical analysis, the three hypotheses of the network meta-analysis were established. In view of these hypotheses, the diagnostic efficacy of the three markers in HCC (HCC vs healthy people) may be consistent, and the cumulative ranking results showed such a trend: circular RNA >long noncoding RNA >microRNA. Conclusion: Circular RNA may be most effective for diagnosing HCC across the three types of RNA.

Liquid Biopsy in Hepatocellular Carcinoma: Opportunities and Challenges for Immunotherapy

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types worldwide. HCC is often diagnosed at a late stage when the therapeutic options are very limited. However, even at the earlier stages, the best treatment is liver transplantation, surgical resection or ablation. Surgical resection and ablation may carry a high risk of tumor recurrence. The recent introduction of immunotherapies resulted in clinical responses for a subgroup of patients, but there were still no effective predictive markers for response to immunotherapy or for recurrence after surgical therapy. The identification of biomarkers that could correlate and predict response or recurrence would require close monitoring of the patients throughout and after the completion of treatment. However, this would not be performed efficiently by repeated and invasive tissue biopsies. A better approach would be to use liquid biopsies including circulating tumor DNA (ctDNA), circulating RNA (e.g., microRNAs), circulating tumor cells (CTC) and extracellular vesicles (EVs) (e.g., exosomes) for disease monitoring in a non-invasive manner. In this review, we discuss the currently available technology that can enable the use of liquid biopsy as a diagnostic and prognostic tool. Moreover, we discuss the opportunities and challenges of the clinical application of liquid biopsy for immunotherapy of HCC.

MiR-466 Inhibits the Progression of Severe Hepatocellular Carcinoma via Regulating FMNL2-Mediated Activation of NF-κB and Wnt/β-Catenin Pathways

Hepatocellular carcinoma (HCC) has threatened the health of humans, and some evidence has indicated that miR-466 involves the progressions of some cancers. This study focused on the role of miR-466 in the formation and development of HCC. The expression levels of miR-466 in the tissues of patients and HCC cell lines were measured by qRT-PCR, and CCK-8, transwell assay, and flow cytometry assay were used to observe the functions of miR-466 on the HCC cells. Moreover, the miRNA databases, dual-luciferase reporter assay, and Western blot were used for the investigation of the regulation mechanism of miR-466 on HCC cells. The results showed that miR-466 was significantly downregulated in HCC tissues and cell lines, and inhibited proliferation, invasion, and high apoptosis were found in HCC cells when miR-466 was overexpressed. The results confirmed that FMNL2 was a target of miR-466, and increased FMNL2 could reverse the effects of miR-466 on the phenotype of HCC cells. Besides, it was also found that miR-466 was involved in the regulation of NF-κB and Wnt/β-catenin pathways in HCC cells via targeting FMNL2. In conclusion, the results of this study suggest that miR-466 regulates the activities of NF-κB and Wnt/β-catenin pathways to inhibit the progression of HCC cells via targeting FMNL2.

The Need for Alternatives to Liver Biopsies: Non-Invasive Analytics and Diagnostics

Histology remains essential for the diagnosis and management of many disorders affecting the liver. However, the biopsy procedure itself is associated with a low risk of harm to the patient and cost to the health services; samples may not be adequate and are subject to sampling variation. Furthermore, interpretation often depends on the skill of the pathologist. Increasingly, new techniques are becoming available that are altering the indications for liver biopsy. Many diseases of the liver can be diagnosed and managed using serological and radiological techniques; the degree of fibrosis and fat can often be assessed by serological or imaging techniques and the nature of space occupying lesions defined by serology, imaging and use of liquid biopsy. However, these techniques, too, are subject to limitations: sensitivity and specificity is not always adequate for diagnosis or management; some techniques are expensive and often also require expert interpretation. Although there may be less need for liver biopsy today, histology remains the gold standard as well as an essential tool for the diagnosis and management of many conditions, especially where there are multiple pathologies, or where a diagnosis cannot or has not been made by alternative approaches. Until less invasive techniques become more reliable and accessible, liver histology will remain a key investigation.

Biomarkers in Hepatobiliary Cancers: What is Useful in Clinical Practice?

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.

Exosomal DLX6-AS1 from hepatocellular carcinoma cells induces M2 macrophage polarization to promote migration and invasion in hepatocellular carcinoma through microRNA-15a-5p/CXCL17 axis

Background

Hepatocellular carcinoma (HCC) cells-secreted exosomes (exo) could stimulate M2 macrophage polarization and promote HCC progression, but the related mechanism of long non-coding RNA distal-less homeobox 6 antisense 1 (DLX6-AS1) with HCC-exo-mediated M2 macrophage polarization is largely ambiguous. Thereafter, this research was started to unearth the role of DLX6-AS1 in HCC-exo in HCC through M2 macrophage polarization and microRNA (miR)-15a-5p/C-X-C motif chemokine ligand 17 (CXCL17) axis.

Methods

DLX6-AS1, miR-15a-5p and CXCL17 expression in HCC tissues and cells were tested. Exosomes were isolated from HCC cells with overexpressed DLX6-AS1 and co-cultured with M2 macrophages. MiR-15a-5p/CXCL17 down-regulation assays were performed in macrophages. The treated M2 macrophages were co-cultured with HCC cells, after which cell migration, invasion and epithelial mesenchymal transition were examined. The targeting relationships between DLX6-AS1 and miR-15a-5p, and between miR-15a-5p and CXCL17 were explored. In vivo experiment was conducted to detect the effect of exosomal DLX6-AS1-induced M2 macrophage polarization on HCC metastasis.

Results

Promoted DLX6-AS1 and CXCL17 and reduced miR-15a-5p exhibited in HCC. HCC-exo induced M2 macrophage polarization to accelerate migration, invasion and epithelial mesenchymal transition in HCC, which was further enhanced by up-regulated DLX6-AS1 but impaired by silenced DLX6-AS1. Inhibition of miR-15a-5p promoted M2 macrophage polarization to stimulate the invasion and metastasis of HCC while that of CXCL17 had the opposite effects. DLX6-AS1 mediated miR-15a-5p to target CXCL17. DLX6-AS1 from HCC-exo promoted metastasis in the lung by inducing M2 macrophage polarization in vivo.

Conclusion

DLX6-AS1 from HCC-exo regulates CXCL17 by competitively binding to miR-15a-5p to induce M2 macrophage polarization, thus promoting HCC migration, invasion and EMT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01973-z.

Genomic Landscape of Liquid Biopsy for Hepatocellular Carcinoma Personalized Medicine

Hepatocellular carcinoma (HCC) is the sixth most frequently diagnosed cancer and the third leading cause of cancer-related deaths worldwide. Advanced-stage HCC patients have poor survival rates and this requires the discovery of novel clear biomarkers for HCC early diagnosis and prognosis, identifying risk factors, distinguishing HCC from non-HCC liver diseases, and assessment of treatment response. Liquid biopsy has emerged as a novel minimally invasive approach to enable monitoring tumor progression, metastasis, and recurrence. Since the liquid biopsy analysis has relatively high specificity and low sensitivity in cancer early detection, there is a risk of bias. Next-generation sequencing (NGS) technologies provide accurate and comprehensive gene expression and mutational profiling of liquid biopsies including cell-free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and genomic components of extracellular vesicles (EVs) including micro-RNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). Since HCC is a highly heterogeneous cancer, HCC patients can display various genomic, epigenomic, and transcriptomic patterns and exhibit varying sensitivity to treatment options. Identification of individual variabilities in genomic signatures in liquid biopsy has the potential to greatly enhance precision oncology capabilities. In this review, we highlight and critically discuss the latest progress in characterizing the genomic landscape of liquid biopsy, which can advance HCC personalized medicine.

Combined hepatocellular-cholangiocarcinoma: An update

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a tumour that exhibits both hepatocytic and biliary differentiation. Classical risk factors for hepatocellular carcinoma (HCC) seem to also predispose patients to the development of cHCC-CCA. The pathological definition of cHCC-CCA has significantly evolved over time. The last 2019 WHO classification highlighted that the diagnosis of cHCC-CCA should be primarily based on morphology using routine stainings, with additional immunostaining used to refine the identification of subtypes. Among them, "intermediate cell carcinoma" is recognised as a specific subtype, while "cholangiolocellular carcinoma" is now considered a subtype of iCCA. Increasing molecular evidence supports the clonal nature of cHCC-CCA and parallels its biphenotypic histological appearance, with genetic alterations that are classically observed in HCC and/or iCCA. That said, the morphological diagnosis of cHCC-CCA is still challenging for radiologists and pathologists, especially on biopsy specimens. Identification of cHCC-CCA's cell of origin remains an area of active research. Its prognosis is generally worse than that of HCC, and similar to that of iCCA. Resection with lymph node dissection is unfortunately the only curative option for patients with cHCC-CCA. Thus, there remains an urgent need to develop specific therapeutic strategies for this unique clinical entity.

Normal tissue adjacent to tumor expression profile analysis developed and validated a prognostic model based on Hippo-related genes in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common malignant disease worldwide. Although the diagnosis and treatment of HCC have greatly improved in the recent years, there is still a lack of accurate methods to predict the prognosis of patients. Evidence has shown that Hippo signaling in tissues adjacent to HCC plays a significant role in HCC development. In the present study, we aimed to construct a model based on the expression of Hippo‐related genes (HRGs) in tissues adjacent to HCC to predict the prognosis of HCC patients.

Methods

Gene expression data of paired normal tissues adjacent to HCC (PNTAH) and clinical information were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The HRG signature was constructed using four canonical Hippo‐related pathways. Univariate Cox regression analysis was used to screen survival‐related HRGs. LASSO and multivariate Cox regression analyses were used to construct the prognostic model. The true and false positive rates of the model were confirmed using receiver operating characteristic (ROC) analysis.

Results

The prognostic model was constructed based on the expression levels of five HRGs (NF2, MYC, BIRC3, CSNK1E, and MINK1) in PNTAH. The mortality rate of HCC patients increased as the risk score determined by the model increased. Furthermore, the risk score was found to be an independent risk factor for the survival of patients. ROC analysis showed that the prognostic model had a better predictive value than the other conventional clinical parameters. Moreover, the reliability of the prognostic model was confirmed in TCGA‐LIHC cohort. A nomogram was generated to predict patient survival. An exploration of the predictive value of the model in HCC tissues indicated that the model is PNTAH‐specific.

Conclusions

We developed and validated a prognostic model based on the expression levels of five HRGs in PNTAH, and this model should be helpful in predicting the prognosis of patients with HCC.

An Inflammatory Response-Related Gene Signature Can Impact the Immune Status and Predict the Prognosis of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, which makes the prognostic prediction challenging. As part of the active cross-talk between the tumor and the host, inflammatory response in the tumor or its microenvironment could affect prognosis. However, the prognostic value of inflammatory response-related genes in HCC remains to be further elucidated.

Methods

In this study, the mRNA expression profiles and corresponding clinical data of HCC patients were downloaded from the public database. The least absolute shrinkage and selection operator Cox analysis was utilized to construct a multigene prognostic signature in the TCGA cohort. HCC patients from the ICGC cohort were used for validation. Kaplan Meier analysis was used to compare the overall survival (OS) between high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. Single-sample gene set enrichment analysis was utilized to calculate the immune cell infiltration score and immune related pathway activity. Gene set enrichment analysis was implemented to conduct GO terms and KEGG pathways. The qRT-PCR and immunohistochemistry were utilized to perform the mRNA and protein expression of prognostic genes between HCC tissues and normal liver tissues respectively.

Results

An inflammatory response-related gene signature model was constructed by LASSO Cox regression analysis. Compared with the low-risk group, patients in the high-risk group showed significantly reduced OS. Receiver operating characteristic curve analysis confirmed the predictive capacity of the prognostic gene signature. Multivariate Cox analysis revealed that the risk score was an independent predictor for OS. Functional analysis indicated that immune status was definitely different between two risk groups, and cancer-related pathways were enriched in high-risk group. The risk score was significantly correlated with tumor grade, tumor stage and immune infiltrate types. The expression levels of prognostic genes were significantly correlated with sensitivity of cancer cells to anti-tumor drugs. Furthermore, the expression of prognostic genes showed significant difference between HCC tissues and adjacent non-tumorous tissues in the separate sample cohort.

Conclusion

A novel signature constructed with eight inflammatory response-related genes can be used for prognostic prediction and impact the immune status in HCC. Moreover, inhibition of these genes may be a therapeutic alternative.

Circulating tumor cells detected with a microcavity array predict clinical outcome in hepatocellular carcinoma

The present study aimed to establish a novel isolation strategy for circulating tumor cells (CTCs) using a microcavity array (MCA) system and to evaluate the clinical significance of CTCs in hepatocellular carcinoma (HCC). We examined recovery rates of HCC cell lines spiked into whole blood in MCA assay. Circulating tumor cells were isolated from peripheral blood samples (3 mL) of 7 healthy donors (HD), 14 patients with liver cirrhosis (LC), and 31 patients with HCC using the MCA system. Additionally, we investigated the mRNA expression of liver‐specific genes in isolated CTCs using qPCR. The recovery rates were 65.1% (HepG2), 76.7% (HuH7), and 99.0% (PLC/PRF/5). In HD and patients with LC and HCC, the CTC positivity rate (CTCs ≥10) and average CTC number were as follows: HD 0% and 0.1, LC 14.3% and 5.3, HCC 54.8% and 47.6, respectively. The CTC positivity rate in HCC was significantly higher than that in LC (p < 0.05). The number of CTCs was significantly higher in metastatic HCC (102.2 ± 160.6) than in localized HCC (8.2 ± 7.7) (p < 0.05). The expression of AFP, glypican‐3, EpCAM, and albumin (ALB) genes was detected in isolated CTCs. The positive CTCs (CTCs ≥10) significantly reduced the cumulative survival in patients with HCC (p = 0.025), especially in localized patients with HCC (p = 0.046). The newly developed MCA system has the potential to isolate CTCs from HCC with high sensitivity, and mRNA expression could be measured from CTCs. Identification of positive CTCs can help predict clinical outcome of patients with HCC. Thus, analysis of CTCs in patients with HCC may provide important information as a novel biomarker in disease progression.

Integrated bioinformatics analysis identified MTHFD1L as a potential biomarker and correlated with immune infiltrates in hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC) is one of the most frequently occurring primary malignant liver tumors and seriously harms people’s health in the world. Methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L) has been shown to be associated with colon cancer cell proliferation, colony formation and invasion. In the present study, a total of 370 LIHC and 51 normal samples data were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatics and immunohistochemistry (IHC) analysis showed that MTHFD1L is highly expressed in liver tumors. Correlation analysis suggested the differences of vital status between high- and low-expression MTHFD1L groups of LIHC. Univariate and multivariate Cox proportional hazards regression were performed to identify the relationship between clinical characteristics and overall survival (OS). In addition, to explore whether MTHFD1L has an effect on the immune infiltration of LIHC. The correlation between MTHFD1L expression and 24 immune cells were analyzed by ImmuneCellAI database. Furthermore, we combined three databases CIBERSORT, TIMER and ImmuneCellAI to do a comprehensive validation and determined that dendritic cells (DCs) resting, macrophage M0 and macrophage M2 closely related to the expression of MTHFD1L. The results showed that MTHFD1L was a potential prognostic biomarker for LIHC, and could help to elucidate that how the immune microenvironment promotes liver cancer development.