Serum Levels of α-Fetoprotein Increased More Than 10 Years Before Detection of Hepatocellular Carcinoma

High accuracy model for HBsAg loss based on longitudinal trajectories of serum qHBsAg throughout long-term antiviral therapy

OBJECTIVE

Hepatitis B surface antigen (HBsAg) loss is the optimal outcome for patients with chronic hepatitis B (CHB) but this rarely occurs with currently approved therapies. We aimed to develop and validate a prognostic model for HBsAg loss on treatment using longitudinal data from a large, prospectively followed, nationwide cohort.

DESIGN

CHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up.

RESULTS

In total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6-107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3-3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5-84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%-10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%-29.1%) and was able to exclude 89.6%-91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups.

CONCLUSION

The novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.

EASL-EASD-EASO Clinical Practice Guidelines on the Management of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is defined as steatotic liver disease (SLD) in the presence of one or more cardiometabolic risk factor(s) and the absence of harmful alcohol intake. The spectrum of MASLD includes steatosis, metabolic dysfunction-associated steatohepatitis (MASH, previously NASH), fibrosis, cirrhosis and MASH-related hepatocellular carcinoma (HCC). This joint EASL-EASD-EASO guideline provides an update on definitions, prevention, screening, diagnosis and treatment for MASLD. Case-finding strategies for MASLD with liver fibrosis, using non-invasive tests, should be applied in individuals with cardiometabolic risk factors, abnormal liver enzymes, and/or radiological signs of hepatic steatosis, particularly in the presence of type 2 diabetes (T2D) or obesity with additional metabolic risk factor(s). A stepwise approach using blood-based scores (such as FIB-4) and, sequentially, imaging techniques (such as transient elastography) is suitable to rule-out/in advanced fibrosis, which is predictive of liver-related outcomes. In adults with MASLD, lifestyle modification - including weight loss, dietary changes, physical exercise and discouraging alcohol consumption - as well as optimal management of comorbidities - including use of incretin-based therapies (e.g. semaglutide, tirzepatide) for T2D or obesity, if indicated - is advised. Bariatric surgery is also an option in individuals with MASLD and obesity. If locally approved and dependent on the label, adults with non-cirrhotic MASH and significant liver fibrosis (stage ≥2) should be considered for a MASH-targeted treatment with resmetirom, which demonstrated histological effectiveness on steatohepatitis and fibrosis with an acceptable safety and tolerability profile. No MASH-targeted pharmacotherapy can currently be recommended for the cirrhotic stage. Management of MASH-related cirrhosis includes adaptations of metabolic drugs, nutritional counselling, surveillance for portal hypertension and HCC, as well as liver transplantation in decompensated cirrhosis.

EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD)

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed non-alcoholic fatty liver disease (NAFLD), is defined as steatotic liver disease (SLD) in the presence of one or more cardiometabolic risk factor(s) and the absence of harmful alcohol intake. The spectrum of MASLD includes steatosis, metabolic dysfunction-associated steatohepatitis (MASH, previously NASH), fibrosis, cirrhosis and MASH-related hepatocellular carcinoma (HCC). This joint EASL-EASD-EASO guideline provides an update on definitions, prevention, screening, diagnosis and treatment for MASLD. Case-finding strategies for MASLD with liver fibrosis, using non-invasive tests, should be applied in individuals with cardiometabolic risk factors, abnormal liver enzymes, and/or radiological signs of hepatic steatosis, particularly in the presence of type 2 diabetes (T2D) or obesity with additional metabolic risk factor(s). A stepwise approach using blood-based scores (such as FIB-4) and, sequentially, imaging techniques (such as transient elastography) is suitable to rule-out/in advanced fibrosis, which is predictive of liver-related outcomes. In adults with MASLD, lifestyle modification - including weight loss, dietary changes, physical exercise and discouraging alcohol consumption - as well as optimal management of comorbidities - including use of incretin-based therapies (e.g. semaglutide, tirzepatide) for T2D or obesity, if indicated - is advised. Bariatric surgery is also an option in individuals with MASLD and obesity. If locally approved and dependent on the label, adults with non-cirrhotic MASH and significant liver fibrosis (stage ≥2) should be considered for a MASH-targeted treatment with resmetirom, which demonstrated histological effectiveness on steatohepatitis and fibrosis with an acceptable safety and tolerability profile. No MASH-targeted pharmacotherapy can currently be recommended for the cirrhotic stage. Management of MASH-related cirrhosis includes adaptations of metabolic drugs, nutritional counselling, surveillance for portal hypertension and HCC, as well as liver transplantation in decompensated cirrhosis.

Serial increase and high alpha-fetoprotein levels predict the development of hepatocellular carcinoma in 6 months

AIM

Alpha-fetoprotein (AFP) checkup with abdominal ultrasonography for hepatocellular carcinoma (HCC) surveillance remains controversial. We evaluated a serial AFP-increase and high AFP levels in the prediction of HCC.

METHODS

At-risk patients with chronic liver disease underwent HCC surveillance with trimonthly AFP measurement were included and categorized into HCC and non-HCC groups. Their AFP levels at 12, 9, and 6 months (-6M) before the outcome date were evaluated. Group-based trajectory analysis and multivariable regression analysis were performed to identify AFP trajectories as risk predictors for HCC.

RESULTS

Overall, 2776 patients were included in the HCC (n = 326) and non-HCC (n = 2450) groups. Serial AFP levels were significantly higher in the HCC than the non-HCC groups. Trajectory analysis identified AFP-increase group (11%) increased 24-fold risks of HCC compared with the AFP-stable (89%) group. Compared with patients without the AFP-increase, a serial 3-month AFP-increase ≥10% elevated HCC risk by 12.1-fold (95% CI: 6.5-22.4) in 6 months, and the HCC risks increased 13-60 fold in patients with cirrhosis, hepatitis B, or C receiving antiviral therapy, or AFP levels <20 ng/ml. Combining serial AFP-increase ≥10% and AFP ≥20 ng/ml at -6M significantly increased 41.7-fold (95% CI: 13.8-126.2) HCC risks. In patients who underwent biannual AFP checkups, those with both 6-month AFP-increase ≥10% and AFP ≥20 ng/ml increased 22.1-fold (95% CI: 12.52-39.16) HCC risks in 6 months. Most HCCs were detected at an early stage.

CONCLUSIONS

Serial 3-6-month AFP-increase of ≥10% previously and AFP level of ≥20 ng/ml significantly increased HCC risks in 6 months.

Novel, high accuracy models for hepatocellular carcinoma prediction based on longitudinal data and cell-free DNA signatures

BACKGROUND & AIMS

Current hepatocellular carcinoma (HCC) risk scores do not reflect changes in HCC risk resulting from liver disease progression/regression over time. We aimed to develop and validate two novel prediction models using multivariate longitudinal data, with or without cell-free DNA (cfDNA) signatures.

METHODS

A total of 13,728 patients from two nationwide multicenter prospective observational cohorts, the majority of whom had chronic hepatitis B, were enrolled. aMAP score, as one of the most promising HCC prediction models, was evaluated for each patient. Low-pass whole-genome sequencing was used to derive multi-modal cfDNA fragmentomics features. A longitudinal discriminant analysis algorithm was used to model longitudinal profiles of patient biomarkers and estimate the risk of HCC development.

RESULTS

We developed and externally validated two novel HCC prediction models with a greater accuracy, termed aMAP-2 and aMAP-2 Plus scores. The aMAP-2 score, calculated with longitudinal data on the aMAP score and alpha-fetoprotein values during an up to 8-year follow-up, performed superbly in the training and external validation cohorts (AUC 0.83-0.84). The aMAP-2 score showed further improvement and accurately divided aMAP-defined high-risk patients into two groups with 5-year cumulative HCC incidences of 23.4% and 4.1%, respectively (p = 0.0065). The aMAP-2 Plus score, which incorporates cfDNA signatures (nucleosome, fragment and motif scores), optimized the prediction of HCC development, especially for patients with cirrhosis (AUC 0.85-0.89). Importantly, the stepwise approach (aMAP -> aMAP-2 -> aMAP-2 Plus) stratified patients with cirrhosis into two groups, comprising 90% and 10% of the cohort, with an annual HCC incidence of 0.8% and 12.5%, respectively (p <0.0001).

CONCLUSIONS

aMAP-2 and aMAP-2 Plus scores are highly accurate in predicting HCC. The stepwise application of aMAP scores provides an improved enrichment strategy, identifying patients at a high risk of HCC, which could effectively guide individualized HCC surveillance.

IMPACT AND IMPLICATIONS

In this multicenter nationwide cohort study, we developed and externally validated two novel hepatocellular carcinoma (HCC) risk prediction models (called aMAP-2 and aMAP-2 Plus scores), using longitudinal discriminant analysis algorithm and longitudinal data (i.e., aMAP and alpha-fetoprotein) with or without the addition of cell-free DNA signatures, based on 13,728 patients from 61 centers across mainland China. Our findings demonstrated that the performance of aMAP-2 and aMAP-2 Plus scores was markedly better than the original aMAP score, and any other existing HCC risk scores across all subsets, especially for patients with cirrhosis. More importantly, the stepwise application of aMAP scores (aMAP -> aMAP-2 -> aMAP-2 Plus) provides an improved enrichment strategy, identifying patients at high risk of HCC, which could effectively guide individualized HCC surveillance.

Risk stratification and early detection biomarkers for precision HCC screening

Hepatocellular carcinoma (HCC) mortality remains high primarily due to late diagnosis as a consequence of failed early detection. Professional societies recommend semi-annual HCC screening in at-risk patients with chronic liver disease to increase the likelihood of curative treatment receipt and improve survival. However, recent dynamic shift of HCC etiologies from viral to metabolic liver diseases has significantly increased the potential target population for the screening, whereas annual incidence rate has become substantially lower. Thus, with the contemporary HCC etiologies, the traditional screening approach might not be practical and cost-effective. HCC screening consists of (i) definition of rational at-risk population, and subsequent (ii) repeated application of early detection tests to the population at regular intervals. The suboptimal performance of the currently available HCC screening tests highlights an urgent need for new modalities and strategies to improve early HCC detection. In this review, we overview recent developments of clinical, molecular, and imaging-based tools to address the current challenge, and discuss conceptual framework and approaches of their clinical translation and implementation. These encouraging progresses are expected to transform the current "one-size-fits-all" HCC screening into individualized precision approaches to early HCC detection and ultimately improve the poor HCC prognosis in the foreseeable future.

Ionic liquid functionalized trapezoidal Zn-MOF nanosheets integrated with gold nanoparticles for photoelectrochemical immunosensing alpha-fetoprotein

An imidazolium based ionic liquid was successfully prepared and used as an organic ligand to coordinate with Zn²⁺ to prepare trapezoidal metal-organic frameworks (Zn-MOF) nanosheets. Then, gold nanoparticles (AuNPs) were integrated onto Zn-MOF nanosheets surface to produce AuNPs@Zn-MOF nanocomposites by in-situ reduction of chloroauric acid. AuNPs with size less than 5 nm were uniformly dispersed on the entire surface of Zn-MOF nanosheets. AuNPs can significantly promote the photocurrent response of Zn-MOF nanosheets and supply an efficient photoelectrochemical sensing platform for fabricating an immunosensor for alpha-fetoprotein (AFP). For AFP determination, the photocurrent response of the immunosensor was linearly related to the logarithm of AFP concentration in the range of 0.005-15.0 ng/mL. The detection limit was calculated to be 1.88 pg/mL. The PEC immunosensor can be facilely fabricated, and provided some superior analytical characteristics such as excellent selectivity, sensitivity, stability and reproducibility for AFP determination. Practicability of the photoelectrochemical immunosensor was demonstrated by using it in assaying AFP in clinical serum samples.

Loss of liver function in chronic liver disease: An identity crisis

Adult hepatocyte identity is constructed throughout embryonic development and fine-tuned after birth. A multinodular network of transcription factors, along with pre-mRNA splicing regulators, define the transcriptome, which encodes the proteins needed to perform the complex metabolic and secretory functions of the mature liver. Transient hepatocellular dedifferentiation can occur as part of the regenerative mechanisms triggered in response to acute liver injury. However, persistent downregulation of key identity genes is now accepted as a strong determinant of organ dysfunction in chronic liver disease, a major global health burden. Therefore, the identification of core transcription factors and splicing regulators that preserve hepatocellular phenotype, and a thorough understanding of how these networks become disrupted in diseased hepatocytes, is of high clinical relevance. In this context, we review the key players in liver differentiation and discuss in detail critical factors, such as HNF4α, whose impairment mediates the breakdown of liver function. Moreover, we present compelling experimental evidence demonstrating that restoration of core transcription factor expression in a chronically injured liver can reset hepatocellular identity, improve function and ameliorate structural abnormalities. The possibility of correcting the phenotype of severely damaged and malfunctional livers may reveal new therapeutic opportunities for individuals with cirrhosis and advanced liver disease.

Circulating biomarkers in the diagnosis and management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal causes of cancer-related death worldwide. The treatment of HCC remains challenging and is largely predicated on early diagnosis. Surveillance of high-risk groups using abdominal ultrasonography, with or without serum analysis of α-fetoprotein (AFP), can permit detection of early, potentially curable tumours, but is limited by its insensitivity. Reviewed here are two current approaches that aim to address this limitation. The first is to use old re-emerged empirically derived biomarkers such as AFP, now applied within statistical models. The second is to use circulating nucleic acid biomarkers, which include cell-free DNA (for example, circulating tumour DNA, cell-free mitochondrial DNA and cell-free viral DNA) and cell-free RNA, applying modern molecular biology-based technologies and machine learning techniques closely allied to the underlying biology of cancer. Taken together, these approaches are likely to be complementary. Both hold considerable promise for achieving earlier diagnosis as well as offering additional functionalities including improved monitoring of therapy and prediction of response thereto.

The Combination of AFP and “Up-To-Seven” Criteria May Be a Better Strategy for Liver Transplantation in Chinese Cirrhotic HCC Patients

Background

Orthotopic liver transplantation (OLT) is a life-saving option for patients with hepatocellular carcinoma (HCC), but the expanded OLT criteria remain controversial.

Objective

The study aimed to explore whether expanded OLT criteria can be applied to Chinese cirrhotic patients with HCC.

Methods

This retrospective study analyzed risk factors for HCC recurrence and death and compared patients’ tumor characteristics and outcomes in groups of Milan, “Up-to-seven,” and Hangzhou criteria, and groups between met and unmet the combinative criteria of “Up-to-seven” and AFP of < 1000 ng/mL.

Results

Among 153 patients who underwent OLT for HCC from January 2015 to February 2019 in 4 years of follow-up, 20 (13.1%) patients had HCC recurrence, and 11 (7.2%) had HCC-related death. Multivariate Cox regression analysis showed that preoperative alpha-fetoprotein (AFP) of > 1000 ng/mL (hazard ratio [HR]: 10.05, 95% confidence interval [CI]: 2.45–41.13, P = 0.001) was an independent risk factor for HCC recurrence and HCC-related death (HR: 6.63, 95%CI: 1.31–33.52, P = 0.022). Patients who did not meet Milan criteria but satisfied the “Up-to-seven” criteria had no differences in overall survival (OS) (P = 0.69) and disease-free survival (DFS) (P = 0.35) than patients who met the Milan criteria. The combination of “Up-to-seven” criteria and AFP of < 1000 ng/mL differed significantly (HR: 18.9; 95% CI: 4.0–89.2; P < 0.001). Patients with HCC who met the “Up-to-seven” criteria and AFP of < 1000 ng/mL (n = 121) had excellent survival with 4-year OS of 91.6% (P < 0.001) and DFS of 90.8% (P < 0.001), which is significantly better compared to the other group (n = 32) (OS of 67.5% and DFS of 46.5%) and patients who met the Milan criteria (n = 108, OS of 89.8%, DFS of 89.6%), allowing 28.9% (13/45) of patients who did not meet the Milan criteria to benefit from OLT.

Conclusion

Chinese cirrhotic patients with HCC who met the combinative criteria of “Up-to-seven” and AFP of < 1000 ng/mL had better survival than those who met the Milan criteria, and these combinative criteria benefited more patients and may become a better option for OLT.

Prognostic models for outcome prediction in patients with advanced hepatocellular carcinoma treated by systemic therapy: a systematic review and critical appraisal

Objective

To describe and analyze the predictive models of the prognosis of patients with hepatocellular carcinoma (HCC) undergoing systemic treatment.

Design

Systematic review.

Data sources

PubMed and Embase until December 2020 and manually searched references from eligible articles.

Eligibility criteria for study selection

The development, validation, or updating of prognostic models of patients with HCC after systemic treatment.

Results

The systematic search yielded 42 eligible articles: 28 articles described the development of 28 prognostic models of patients with HCC treated with systemic therapy, and 14 articles described the external validation of 32 existing prognostic models of patients with HCC undergoing systemic treatment. Among the 28 prognostic models, six were developed based on genes, of which five were expressed in full equations; the other 22 prognostic models were developed based on common clinical factors. Of the 28 prognostic models, 11 were validated both internally and externally, nine were validated only internally, two were validated only externally, and the remaining six models did not undergo any type of validation. Among the 28 prognostic models, the most common systemic treatment was sorafenib (n = 19); the most prevalent endpoint was overall survival (n = 28); and the most commonly used predictors were alpha-fetoprotein (n = 15), bilirubin (n = 8), albumin (n = 8), Child–Pugh score (n = 8), extrahepatic metastasis (n = 7), and tumor size (n = 7). Further, among 32 externally validated prognostic models, 12 were externally validated > 3 times.

Conclusions

This study describes and analyzes the prognostic models developed and validated for patients with HCC who have undergone systemic treatment. The results show that there are some methodological flaws in the model development process, and that external validation is rarely performed. Future research should focus on validating and updating existing models, and evaluating the effects of these models in clinical practice.

Systematic review registration

PROSPERO CRD42020200187.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09841-5.

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Identification of the suitable candidates for EOB-MRI with the high risk of the presence of non-hypervascular hypointense nodules in patients with HCV infection

OBJECTIVES

Non-hypervascular hypointense nodules (NHHNs) depicted by gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid-enhanced magnetic resonance imaging (EOB-MRI) have a high likelihood of progressing to hepatocellular carcinoma (HCC). The presence of NHHNs is a strong risk factor for HCC development in patients with chronic hepatitis C virus (HCV) infection after the achievement of sustained virologic response (SVR). However, it is difficult for all patients with HCV infection to undergo EOB-MRI for NHHN detection. We therefore explored serum markers that potentially indicate the presence of NHHNs.

METHODS

Three serum markers, alpha-fetoprotein (AFP), FIB-4 index, and Wisteria floribunda agglutinin-positive Mac-2 binding protein glycan isomer (M2BPGi), were measured in 481 patients with HCV infection and no history of HCC who underwent EOB-MRI. The associations between these serum marker levels and the presence of NHHNs were investigated.

RESULTS

All three markers were associated with the presence of NHHNs. M2BPGi predicted the presence of NHHNs more accurately than AFP and FBB-4 index; M2BPGi had the highest area under the receiver operating characteristic curve. Multivariate analysis identified male gender and high M2BPGi as factors associated with the presence of NHHNs. When patients were stratified by the degree of liver fibrosis, M2BPGi increased with the progression of fibrosis. In addition, NHHNs were more prevalently detected in patients with higher M2BPGi (COI > 3.46) in patients with similar fibrosis degree.

CONCLUSIONS

M2BPGi is a serum marker that potentially identifies HCV patients with high risk of the presence of NHHNs, for whom EOB-MRI should be considered.

KEY POINTS

• Non-hypervascular hypointense nodule on EOB-DTPA-enhanced MRI is pre-HCC nodule with high likelihood of progressing to HCC, which is a strong predictor for HCC that develops after the eradication of HCV in patients with HCV infection. • It is difficult for all patients with HCV infection to undergo EOB-MRI for NHHN detection due to limited access, limited availability of MRI equipment, and high costs. • Serum Wisteria floribunda agglutinin-positive Mac-2 binding protein glycan isomer (M2BPGi) levels effectively indicate the presence of NHHNs and can be used to identify patients with high risk of their presence, for whom EOB-DTPA-enhanced MRI should be considered.

The Emerging Influences of Alpha-Fetoprotein in the Tumorigenesis and Progression of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide, and its mortality rate is the third-highest, after lung cancer and colorectal cancer. Currently, systematic targeted therapies for HCC mainly include multiple kinase inhibitors and immunotherapy. However, these drugs carry a black-box warning about the potential for inducing severe toxicity, and they do not significantly prolong the survival period of patients due to the highly heterogeneous characteristics of HCC etiology. In order to improve the prediction, effective treatment and prognosis of HCC, the tools and different biomarkers in clinical practices are recommended. Alpha-fetoprotein (AFP) is the earliest and the most widely used serum marker in the detection of HCC. Interestingly, serum AFP and cytoplasmic AFP show different, even opposite, roles in the cancer progression of HCC. This review focuses on biological characteristics, regulatory mechanisms for gene expression, emerging influences of AFP in HCC and its possible implications in HCC-targeted therapy.

Current and Emerging Tools for Hepatocellular Carcinoma Surveillance

Hepatocellular carcinoma (HCC) is a leading cause of cancer‐related mortality worldwide. Early detection of HCC enables patients to avail curative therapies that can improve patient survival. Current international guidelines advocate for the enrollment of patients at high risk for HCC, like those with cirrhosis, in surveillance programs that perform ultrasound every 6 months. In recent years, many studies have further characterized the utility of established screening strategies and have introduced new promising tools for HCC surveillance. In this review, we provide an overview of the most promising new imaging modalities and biomarkers for the detection of HCC. We discuss the role of imaging tools like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) in the early detection of HCC, and describe recent innovations which can potentially enhance their applicability, including contrast enhanced ultrasound, low‐dose CT scans, and abbreviated MRI. Next, we outline the data supporting the use of three circulating biomarkers (i.e., alpha‐fetoprotein [AFP], AFP lens culinaris agglutinin‐reactive fraction, and des‐gamma‐carboxy prothrombin) in HCC surveillance, and expand on multiple emerging liquid biopsy biomarkers, including methylated cell‐free DNA (cfDNA), cfDNA mutations, extracellular vesicles, and circulating tumor cells. These promising new imaging modalities and biomarkers have the potential to improve early detection, and thus improve survival, in patients with HCC.

GALAD Score Detects Early-Stage Hepatocellular Carcinoma in a European Cohort of Chronic Hepatitis B and C Patients

Despite vaccination programs and direct antiviral treatments, the incidence of virus-related hepatocellular carcinoma (HCC) remains high, while ultrasound-based detection rates for early-stage HCC is continuously low. To address this insufficiency, we set out to characterize whether the GALAD score, which incorporates gender, age, and serum levels of AFP, AFP isoform L3 (AFP-L3), and des-gamma-carboxy-prothrombin (DCP), can improve early-stage HCC detection in a Caucasian HBV/HCV cohort. In a retrospective German single-center study, 182 patients with HBV, 223 with HCV and 168 with other etiology (OE) of chronic liver disease (CLD) were enrolled. HCC was confirmed in 52 HBV, 84 HCV and 60 OE CLD patients. The diagnostic performance of the single biomarkers in HCC detection was compared to the GALAD model. At initial diagnosis, most patients were at (very) early BCLC 0 (n = 14/7%) or A (n = 56/29%) or intermediate stage BCLC B (n = 93/47%) HCC in all three subgroups. In the BCLC 0/A cohort, GALAD exhibited an AUC of 0.94 discriminating HCC from non-HCC, surpassing AFP (AUC 0.86), AFP-L3 (AUC 0.83) and DCP (AUC 0.83). In the HBV population, GALAD achieved an AUC of 0.96, in HCV an AUC of 0.98 and in OE an AUC of 0.99, clearly superior to the biomarkers alone. Furthermore, in HCV patients GALAD showed a significantly higher specificity (89%) versus AFP (64%) alone. In chronic viral hepatitis, the GALAD model showed superior performance in detection of early-stage HCC, while exhibiting higher specificity in HCV patients compared to AFP alone. We conclude that the GALAD score shows potential for HCC surveillance in Caucasian HBV/HCV patients.

Knockdown of MUC16 (CA125) Enhances the Migration and Invasion of Hepatocellular Carcinoma Cells

As an important global medical problem, hepatocellular carcinoma (HCC) has been recognized as the most frequent primary liver cancer and a leading cause of death among patients with cirrhosis. Surveillance of HCC using serum markers aims to reduce the disease-related mortality of HCC. MUC16 (mucin 16, also known as carbohydrate antigen 125, CA125) has been predicted as a tumor biomarker for many cancer types. Based on the high frequency mutation rate in a database from the Cancer Genome Atlas (TCGA), we investigated the effects of MUC16 knockdown and the regulatory profile of MUC16 in HepG2 and Huh7 cell lines. Knockdown of MUC16 was conducted via siRNA transfection, and the proliferation of cells was not affected by CCK8 assay results. Moreover, decreasing the expression of MUC16 enhanced the migration and invasion of cells, as shown by wound healing and transwell assays. Furthermore, RNA-seq was used to investigate the effect of MUC16 knockdown on the gene expression profile of HepG2 and Huh7 cells. Our study demonstrated the significant role of MUC16 in the inhibition of the migration and invasion of HepG2 and Huh7 cells.

A blood-based prognostic liver secretome signature and long-term hepatocellular carcinoma risk in advanced liver fibrosis

Background

Accurate non-invasive prediction of long-term hepatocellular carcinoma (HCC) risk in advanced liver fibrosis is urgently needed for cost-effective HCC screening; however, this currently remains an unmet need.

Methods

A serum-protein-based prognostic liver secretome signature (PLSec) was bioinformatically derived from previously validated hepatic transcriptome signatures and optimized in 79 patients with advanced liver fibrosis. We independently validated PLSec for HCC risk in 331 cirrhosis patients with mixed etiologies (validation set 1 [V1]) and thereafter developed a score with clinical prognostic variables. The score was then validated in two independent cohorts: validation set 2 (V2): 164 patients with advanced liver fibrosis due to hepatitis C virus (HCV) infection cured after direct-acting antiviral therapy; validation set 3 (V3): 146 patients with advanced liver fibrosis with successfully-treated HCC and cured HCV infection.

Findings

An 8-protein blood-based PLSec recapitulated transcriptome-based hepatic HCC risk status. In V1, PLSec was significantly associated with incident HCC risk (adjusted hazard ratio [aHR], 2.35; 95% confidence interval [CI], 1.30-4.23). A composite score with serum alpha-fetoprotein (PLSec-AFP) was defined in V1, and validated in V2 (adjusted odds ratio, 3.80 [95%CI, 1.66-8.66]) and V3 (aHR, 3.08 [95%CI, 1.78-5.31]; c-index, 0.74). PLSec-AFP outperformed AFP alone (Brier score, 0.165 vs. 0.186 in V2; 0.196 vs. 0.206 in V3, respectively).

Conclusions

The blood-based PLSec-AFP can accurately stratify patients with advanced liver fibrosis for long-term HCC risk and thereby guide risk-based tailored HCC screening.

Serum Biomarkers for the Prediction of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of global cancer death. Major etiologies of HCC relate to chronic viral infections as well as metabolic conditions. The survival rate of people with HCC is very low and has been attributed to late diagnosis with limited treatment options. Combining ultrasound and the biomarker alpha-fetoprotein (AFP) is currently one of the most widely used screening combinations for HCC. However, the clinical utility of AFP is controversial, and the frequency and operator-dependence of ultrasound lead to a variable degree of sensitivity and specificity across the globe. In this review, we summarize recent developments in the search for non-invasive serum biomarkers for early detection of HCC to improve prognosis and outcome for patients. We focus on tumor-associated protein markers, immune mediators (cytokines and chemokines), and micro-RNAs in serum or circulating extracellular vesicles and examine their potential for clinical application.

The effect of random-effects misspecification on classification accuracy

Mixed models are a useful way of analysing longitudinal data. Random effects terms allow modelling of patient specific deviations from the overall trend over time. Correlation between repeated measurements are captured by specifying a joint distribution for all random effects in a model. Typically, this joint distribution is assumed to be a multivariate normal distribution. For Gaussian outcomes misspecification of the random effects distribution usually has little impact. However, when the outcome is discrete (e.g. counts or binary outcomes) generalised linear mixed models (GLMMs) are used to analyse longitudinal trends. Opinion is divided about how robust GLMMs are to misspecification of the random effects. Previous work explored the impact of random effects misspecification on the bias of model parameters in single outcome GLMMs. Accepting that these model parameters may be biased, we investigate whether this affects our ability to classify patients into clinical groups using a longitudinal discriminant analysis. We also consider multiple outcomes, which can significantly increase the dimensions of the random effects distribution when modelled simultaneously. We show that when there is severe departure from normality, more flexible mixture distributions can give better classification accuracy. However, in many cases, wrongly assuming a single multivariate normal distribution has little impact on classification accuracy.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.