Evaluation of the Combined Application of AFP, AFP-L3%, and DCP for Hepatocellular Carcinoma Diagnosis: A Meta-analysis

Immunotherapy and liver transplantation for hepatocellular carcinoma: Current and future challenges

Despite existing curative options like surgical removal, tissue destruction techniques, and liver transplantation for early-stage hepatocellular carcinoma (HCC), the rising incidence and mortality rates of this global health burden necessitate continuous exploration of novel therapeutic strategies. This review critically assesses the dynamic treatment panorama for HCC, focusing specifically on the burgeoning role of immunotherapy in two key contexts: early-stage HCC and downstaging advanced HCC to facilitate liver transplant candidacy. It delves into the unique immunobiology of the liver and HCC, highlighting tumor-mediated immune evasion mechanisms. Analyzing the diverse immunotherapeutic approaches including checkpoint inhibitors, cytokine modulators, vaccines, oncolytic viruses, antigen-targeting antibodies, and adoptive cell therapy, this review acknowledges the limitations of current diagnostic markers alpha-fetoprotein and glypican-3 and emphasizes the need for novel biomarkers for patient selection and treatment monitoring. Exploring the rationale for neoadjuvant and adjuvant immunotherapy in early-stage HCC, current research is actively exploring the safety and effectiveness of diverse immunotherapeutic approaches through ongoing clinical trials. The review further explores the potential benefits and challenges of combining immunotherapy and liver transplant, highlighting the need for careful patient selection, meticulous monitoring, and novel strategies to mitigate post-transplant complications. Finally, this review delves into the latest findings from the clinical research landscape and future directions in HCC management, paving the way for optimizing treatment strategies and improving long-term survival rates for patients with this challenging malignancy.

Construction of a survival prediction model for patients with hepatocellular carcinoma (HCC) based on real clinical data: a single-center retrospective study

Background

Given the rising incidence of hepatocellular carcinoma (HCC) globally, especially in China, information about independent risk factors for survival and disease prognosis of the illness is scarce. In the field of HCC research, there is an urgent need for a scientific basis to enhance the accuracy of clinical diagnosis, optimize the course of therapy, and accurately predict the prognosis. Against this backdrop, the objective of this work was to develop a scientific, efficient, and methodical nomogram to forecast the survival prognosis of HCC.

Methods

A real-world study collected clinical data from January 1, 2011, to December 31, 2019, for individuals with HCC. Overall survival (OS) was determined using Kaplan-Meier analysis. Independent risk variables were identified using Cox proportional hazards regression. A nomogram predicting 1-, 3-, and 5-year OS was created. The reliability of the predictions of the model was assessed using receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA).

Results

Data from 1,128 HCC cases showed 1-, 3-, and 5-year OS rates were 86.3%, 65.3%, and 43.1%, respectively. Univariate Cox regression identified 13 variables influencing HCC survival including age, HCC screening status, hepatitis C virus (HCV) status, nonalcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) status, liver cirrhosis, elevated alpha-fetoprotein (AFP), Child-Pugh grade, tumor size, tumor number, treatment method, tumor thrombus, and extrahepatic metastasis (P<0.05). Multivariate analysis confirmed HCC screening status, tumor size, ALD, Child-Pugh classification, and therapy method as independent prognostic factors (P<0.05). The nomogram achieved an area under the ROC curve (AUC) of 0.868. Calibration curves of the 1-, 3-, and 5-year survival times and the DCA curve confirmed its predictive accuracy.

Conclusions

Patients without HCC screening, tumor size >5 cm, ALD, Child-Pugh grade C, and conservative treatment had a poor survival prognosis. A nomogram based on these risk variables provides a reliable tool for predicting the survival chances of patients with HCC.

Advances in application of serum biomarkers for screening and early diagnosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a major global health challenge, with early detection through surveillance of high-risk populations remaining critical for improving clinical outcomes. Serum biomarkers play a crucial role in the early detection of HCC. Currently, commonly used serological markers for HCC include alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin, and the Lens culinaris agglutinin-reactive fraction of AFP. Other potential biomarkers under investigation include glypican-3, osteopontin, alpha-L-fucosidase, Dickkopf-1, heat shock protein 90α, and Golgi protein 73. With the advancement of liquid biopsy technologies, novel markers such as circulating tumor DNA, circulating tumor cells, microRNAs, and long non-coding RNAs have emerged as promising tools for early screening and diagnosis of HCC. This review aims to summarize the research progress and clinical applications of these biomarkers related to liver cancer, providing scientific evidence to enhance early diagnosis rates, improve prognosis, and ultimately reduce HCC-related mortality.

Somatic Copy Number Alterations in Circulating Cell-Free DNA as a Prognostic Biomarker for Hepatocellular Carcinoma: Insights from a Proof-of-Concept Study

BACKGROUND/OBJECTIVES

Despite advances in hepatocellular carcinoma (HCC) management, prognosis remains poor. Advanced-stage diagnosis often excludes curative treatments, and current biomarkers (e.g., alpha-fetoprotein [AFP]) have limited utility in early detection. Liquid biopsy has emerged as a promising cancer detection tool, with circulating cell-free DNA (ccfDNA) showing significant diagnostic potential. This proof-of-concept study aimed to investigate the potential role of tumor fraction (TF) within ccfDNA as a biomarker in HCC patients.

METHODS

A total of sixty patients were recruited, including thirteen with chronic liver disease (CLD), twenty-four with cirrhosis, and twenty-three with HCC. Plasma samples were collected, and ccfDNA was extracted for shallow whole genome sequencing (sWGS) analysis. The TF was calculated by focusing on somatic copy number alterations (SCNAs) within the ccfDNA.

RESULTS

Among patients with CLD and cirrhosis (n = 37), ctDNA was undetectable in all but one cirrhotic patient who exhibited a significant tumor fraction (TF) of 17% and subsequently developed HCC. Conversely, five out of twenty-three HCC patients (21.7%) displayed detectable ctDNA with TF levels ranging from 3.0% to 32.6%. Patients with detectable ctDNA were characterized by more aggressive oncological features, including a higher number of nodules (p = 0.005), advanced-stage disease (60% BCLC C, p = 0.010), and poorer response to therapy (80% PD, p = 0.001). Moreover, the overall survival (OS) was significantly reduced in patients with detectable ctDNA (median OS: 17 months; CI 95% 4.5-26.5) compared to those without (median OS: 24.0 months; CI 95% 7.0-66.0; log-rank p = 0.002).

CONCLUSIONS

Our results suggest that the analysis of TF by sWGS is a promising non-invasive tool for the identification of HCC with aggressive clinical behavior, whereas it is not sensitive enough for early HCC detection. This molecular assay can improve prognostic stratification in HCC patients.

Porous Silicon Particle-Assisted Mass Spectrometry Technology Unlocks Serum Metabolic Fingerprints in the Progression From Chronic Hepatitis B to Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignancy and generally develops from liver cirrhosis (LC), which is primarily caused by the chronic hepatitis B (CHB) virus. Reliable liquid biopsy methods for HCC screening in high-risk populations are urgently needed. Here, we establish a porous silicon-assisted laser desorption ionization mass spectrometry (PSALDI-MS) technology to profile metabolite information hidden in human serum in a high throughput manner. Serum metabolites can be captured in the pore channel of APTES-modified porous silicon (pSi) particles and well-preserved during storage or transportation. Furthermore, serum metabolites captured in the APTES-pSi particles can be directly detected on the LDI-MS without the addition of an organic matrix, thus greatly accelerating the acquisition of metabolic fingerprints of serum samples. The PSALDI-MS displays the capability of high throughput (5 min per 96 samples), high reproducibility (coefficient of variation <15%), high sensitivity (LOD ∼ 1 pmol), and high tolerance to background salt and proteins. In a multicenter cohort study, 1433 subjects including healthy controls (HC), CHB, LC, and HCC volunteers were enrolled and nontargeted serum metabolomic analysis was performed on the PSALDI-MS platform. After the selection of feature metabolites, a stepwise diagnostic model for the classification of different liver disease stages was constructed by the machine learning algorithm. In external testing, the accuracy of 91.2% for HC, 71.4% for CHB, 70.0% for LC, and 95.3% for HCC was achieved by chemometrics. Preliminary studies indicated that the diagnostic model constructed from serum metabolic fingerprint also displays good predictive performance in a prospective observation. We believe that the combination of PSALDI-MS technology and machine learning may serve as an efficient tool in clinical practice.

Hepatocellular Carcinoma: The Search for an Optimal Screening Test

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third leading cause of cancer-related death, with a 5-year survival rate of 10%-12%. It usually develops in the setting of chronic liver disease (CLD), with chronic viral hepatitis, alcohol, and non-alcoholic fatty liver disease (NAFLD) being the most common risk factors. Some patients are at higher risk of developing hepatocellular cancer, so it is important to screen them regularly to diagnose the disease at an early stage and improve their chances for curative treatment. Six-monthly ultrasound with or without alpha-fetoprotein (AFP) is the currently recommended surveillance method. AFP has been used as a biomarker for liver cancer; however, it has low sensitivity and specificity, which necessitates the search for other, more accurate biomarkers. Promising biomarkers include lens culinaris agglutinin-reactive AFP, des-gamma-carboxy prothrombin, methylated DNA markers, plasma microRNA expression, circulating tumor DNA, and circulating tumor cells. In addition, combinations of biomarkers, like the GALAD score and the Doylestown algorithm, may help in the early detection of HCC. In this review, we summarize the screening tests for early detection of HCC that have been studied over the last decade.

GALAD, or des-gamma-carboxy prothrombin compared with alpha-foetoprotein for the diagnosis of hepatocellular carcinoma in people with chronic liver disease

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To estimate the diagnostic accuracy of des-gamma-carboxy prothrombin, GALAD (Gender, Age, Lens culinaris agglutinin-reactive AFP, AFP and DCP), and alpha-foetoprotein for the diagnosis of hepatocellular carcinoma of any size, and at any stage, in adults with chronic liver disease, in either a surveillance programme or a clinical setting. We acknowledge the possibility that theoretically, the accuracy of the tests in a surveillance programme may differ from that in a clinical setting due to variation in inclusion criteria and the prevalence of the target condition. However, we do not plan a separate analysis for surveillance and clinical settings, as they are not clearly distinct in current clinical practice (Forner 2018; Poustchi 2011). In routine evaluation of people with chronic liver disease, index tests, as well as ultrasound, are already part of standard procedure. Given that HCC typically presents with no symptoms and is often asymptomatic, suspicion of the disease is typically based solely on the presence of advanced chronic liver disease. However, we do plan to consider the study setting as a potential source of heterogeneity. To compare the diagnostic accuracy of des-gamma-carboxy prothrombin (DCP) alone or GALAD alone versus alpha-foetoprotein (AFP), for the diagnosis of hepatocellular carcinoma (HCC) of any size, at any stage; in adults with chronic liver disease, either in a surveillance programme or a clinical setting. Secondary objectives To estimate the diagnostic accuracy of DCP or GALAD versus AFP, for resectable HCC in people with chronic liver disease, in a surveillance programme and a clinical setting. To investigate the following predefined sources of heterogeneity for each of the index tests: study design (case-control studies compared to cross-sectional studies); inclusion of participants without cirrhosis (studies including more than 10% of participants without cirrhosis compared to studies including less than 10% of participants without cirrhosis); study location (population differences): studies conducted in North and South America and Europe compared to Asia and Africa; prevalence of the target condition (studies with hepatocellular carcinoma prevalence more than 10% compared to studies with hepatocellular carcinoma prevalence less than 10%); participant selection (participants recruited from planned surveillance programmes compared to clinical cohorts); different reference standards (histology of the explanted liver compared to liver biopsy compared to another reference standard); different aetiology: studies including at least 90% of participants with chronic viral hepatitis compared to studies including less than 90% of participants with chronic viral hepatitis.

Establishment of prognosis model of hepatocellular carcinoma based on prognosis related gene analysis and study on gene regulation mechanism of model

Objective

To analyze the expression and mechanism of prognosis related differentially expressed genes (DEGs) in hepatocellular carcinoma (HCC), and establish a prognosis risk model of prognosis related DEGs.

Methods

Transcriptome data and clinical information of 374 HCC samples were downloaded from TCGA data. Kaplan-Meier (KM) survival analysis screened prognostic genes in DEGs. Protein-protein interaction (PPI) network was constructed based on prognostic genes and key genes were screened. Cox regression was used to analyze the key genes and construct the prognostic risk model, calculate the risk score of each patient, divide the patients into low-risk group and high-risk group according to the median risk value, use KM analysis method for survival analysis and draw the survival curve, and use receiver operating characteristic (ROC) curve to evaluate the prognostic risk model, The relationship between risk score and clinicopathological features of HCC patients was analyzed. GEPIA and the human protein atlas (HPA) databases were used for expression verification of model genes. The mirDIP database is used to analyze the regulatory network of model genes. GSCAlite platform is used to analyze the mechanism and drug sensitivity of model genes.

Results

A total of 1987 DEGs were extracted from the transcriptome data of HCC and normal samples, of which 258 were related to the prognosis of HCC (P < 0.01). Six key genes (CDK1, CCNA2, BUB1, CDC20, CCNB1 and TOP2A) were screened from the PPI network based on prognostic related genes, and the prognostic risk model was established. Survival analysis showed that the overall survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.01). The AUC values of 1, 3 and 5 years in the prognostic risk model were 0.716, 0.678 and 0.633. Multivariate Cox regression analysis showed that patient age and patient risk score were independent risk factors for the prognosis of HCC. The model gene is highly expressed in HCC and can promote apoptosis, cell cycle and EMT pathway. In addition, the high expression of model gene produced drug resistance to trametinib, selumetinib and RDEA119 (refametinib).

Conclusion

The prognostic risk model based on six prognostic related DEGs is an independent prognostic factor of HCC, which can effectively predict the survival and prognosis of HCC patients.

Alpha-fetoprotein, glypican-3, and kininogen-1 as biomarkers for the diagnosis of hepatocellular carcinoma

The hepatocarcinoma (HCC) is the most important liver tumor. It represents 90% of liver cancer cases. One of the main problems is the limited prompt cancer diagnosis and the advanced stages where the chances of treatment are limited. The main diagnostic methods for HCC are imaging techniques and liver biopsy. With advances in technology, proteins as significant diagnostic biomarkers have increased. The objective of this review is to describe the role of Alpha-fetoprotein (AFP), Glipican 3 (GPC-3), and Kininogen 1 (KNG-1) as biomarkers for the diagnosis of hepatocellular carcinoma. A systematic search of studies was carried out in the literature and the diagnostic values of these proteins were compared. The results showed that the combined use of biomarkers increases the diagnostic capacity for the detection of hepatocellular carcinoma.

Evaluating the diagnostic accuracy of heat shock proteins and their combination with Alpha-Fetoprotein in the detection of hepatocellular carcinoma: a meta-analysis

BACKGROUND

A growing body of research suggests that heat shock proteins (HSPs) may serve as diagnostic biomarkers for hepatocellular carcinoma (HCC), but their results are still controversial. This meta-analysis endeavors to evaluate the diagnostic accuracy of HSPs both independently and in conjunction with alpha-fetoprotein (AFP) as novel biomarkers for HCC detection.

METHODS

Pooled statistical indices, including sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals (CI), were computed to assess the diagnostic accuracy of HSPs, AFP, and their combinations. Additionally, the area under the summary receiver operating characteristic (SROC) curve (AUC) was determined.

RESULTS

A total of 2013 HCC patients and 1031 control subjects from nine studies were included in this meta-analysis. The summary estimates for HSPs and AFP are as follows: sensitivity of 0.78 (95% CI: 0.69-0.85) compared to 0.73 (95% CI: 0.65-0.80); specificity of 0.89 (95% CI: 0.81-0.95) compared to 0.86 (95% CI: 0.77-0.91); PLR of 7.4 (95% CI: 3.7-14.9) compared to 5.1 (95% CI: 3.3-8.1); NLR of 0.24 (95% CI: 0.16-0.37) compared to 0.31 (95% CI: 0.24-0.41); DOR of 30.19 (95% CI: 10.68-85.37) compared to 16.34 (95% CI: 9.69-27.56); and AUC of 0.90 (95% CI: 0.87-0.92) compared to 0.85 (95% CI: 0.82-0.88). The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.90 (95% CI: 0.82-0.95), 0.94 (95% CI: 0.82-0.98), 14.5 (95% CI: 4.6-45.4), 0.11 (95% CI: 0.06-0.20), 133.34 (95% CI: 29.65-599.61), and 0.96 (95% CI: 0.94-0.98) for the combination of HSPs and AFP.

CONCLUSION

Our analysis suggests that HSPs have potential as a biomarker for clinical use in the diagnosis of HCC, and the concurrent utilization of HSPs and AFP shows notable diagnostic effectiveness for HCC.

Diagnostic and prognostic performances of GALAD score in staging and 1-year mortality of hepatocellular carcinoma: A prospective study

BACKGROUND

The GALAD score has improved early hepatocellular carcinoma (HCC) detection rate. The role of the GALAD score in staging and predicting tumor characteristics or clinical outcome of HCC remains of particular interest.

AIM

To determine the diagnostic/prognostic performances of the GALAD score at various phases of initial diagnosis, tumor features, and 1-year mortality of HCC and compare the performance of the GALAD score with those of other serum biomarkers.

METHODS

This prospective, diagnostic/prognostic study was conducted among patients with newly diagnosed HCC at the liver center of Vajira Hospital. Eligible patients had HCC staging allocation using the Barcelona Clinic Liver Cancer (BCLC) categorization. Demographics, HCC etiology, and HCC features were recorded. Biomarkers and the GALAD score were obtained at baseline. The performance of the GALAD score and biomarkers were prospectively assessed.

RESULTS

Exactly 115 individuals were diagnosed with HCC. The GALAD score increased with disease severity. Between BCLC-0/A and BCLC-B/C/D, the GALAD score predicted HCC staging with an area under the curve (AUC) of 0.868 (95%CI: 0.80-0.93). For identifying the curative HCC, the AUC of GALAD score was significantly higher than that of Alpha-fetoprotein (AFP) (0.753) and Lens culinaris agglutinin-reactive fraction of AFP-L3 (0.706), and as good as that of Protein induced by vitamin K absence-II (PIVKA-II) (0.897). For detecting aggressive features, the GALAD score gave an AUC of 0.839 (95%CI: 0.75-0.92) and significantly outperformed compared to that of AFP (0.761) and AFP-L3 (0.697), with a trend of superiority to that of PIVKA-II (0.772). The performance to predict 1-year mortality of GALAD score (AUC: 0.711, 95%CI: 0.60-0.82) was better than that of AFP (0.541) and as good as that of PIVKA-II (0.736). The optimal cutoff value of GALAD score was ≥ 6.83, with a specificity of 72.63% for exhibiting substantial reduction in the 1-year mortality.

CONCLUSION

The GALAD model can diagnose HCC at the curative stage, including the characteristic of advanced disease, more than that by AFP and AFP-L3, but not PIVKA-II. The GALAD score can be used to predict the 1-year mortality of HCC.

Clinical practice guidelines for molecular tumor marker, 2nd edition review part 2

In recent years, rapid advancement in gene/protein analysis technology has resulted in target molecule identification that may be useful in cancer treatment. Therefore, "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" was published in Japan in September 2021. These guidelines were established to align the clinical usefulness of external diagnostic products with the evaluation criteria of the Pharmaceuticals and Medical Devices Agency. The guidelines were scoped for each tumor, and a clinical questionnaire was developed based on a serious clinical problem. This guideline was based on a careful review of the evidence obtained through a literature search, and recommendations were identified following the recommended grades of the Medical Information Network Distribution Services (Minds). Therefore, this guideline can be a tool for cancer treatment in clinical practice. We have already reported the review portion of "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" as Part 1. Here, we present the English version of each part of the Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition.

Utility of Alpha-Fetoprotein and Ultrasound in the Diagnosis and Prognosis of Patients with Hepatocellular Liver Cancer

Objective

To investigate the utility of alpha-fetoprotein (AFP) and ultrasound in the diagnosis and prognosis of patients with hepatocellular liver cancer (HCC).

Methods

Using retrospective convenience sampling, 401 patients with HCC who underwent transarterial chemoembolisation at the Department of Oncology of The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University between June 2015 and January 2020 were recruited and assigned to the case group. Simultaneously, patients matched to the case group in terms of gender and age but excluded for HCC were enrolled at a 1:1 ratio and classified as the control group. Relevant parameters were collected from both groups for comparison.

Results

Both AFP levels and ultrasound results demonstrated diagnostic value for patients with HCC (P < 0.05). Their combined use exhibited the highest diagnostic accuracy for the cancer, with an area under the curve of 0.896 (95% confidence interval [CI]: 0.876, 0.923), a sensitivity of 67.65% and a specificity of 91.22%. In terms of overall survival (OS), statistically significant differences in the OS rates were observed between the low-AFP (L-AFP) group and high-AFP (H-AFP) group as well as between the low-tumour-diameter (LTD) group and high-tumour-diameter (HTD) group (81.31% vs 52.22% and 85.11% vs 63.41%, respectively; P < 0.05). Regarding the progression-free survival (PFS), significant differences in the PFS rates were also noted between the L-AFP and H-AFP groups and between the LTD and HTD groups (81.31% vs 52.22% and 85.11% vs 63.41%, respectively; P < 0.05).

Conclusion

Ultrasound and AFP display notable distinctions when used in the diagnosis of HCC. The sensitivity of ultrasound as a standalone diagnostic tool surpasses that of AFP alone. However, their combined use results in much higher specificity than the use of either test individually. In addition, both techniques hold predictive value for patients' OS and PFS, enabling timely prognostic assessment.

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.

The GALAD score and the BALAD-2 score correlate with transarterial and systemic treatment response and survival in patients with hepatocellular carcinoma

PURPOSE

The GALAD score and the BALAD-2 score are biomarker-based scoring systems used to detect hepatocellular carcinoma (HCC). Both incorporate levels of alpha-fetoprotein (AFP), lens culinaris agglutinin-reactive AFP (AFP-L3), and des-gamma-carboxy prothrombin (DCP). Our objective was to examine the relationship between the GALAD score as well as the BALAD-2 score and treatment response to transarterial or systemic treatments in patients with HCC.

METHODS

A total of 220 patients with HCC treated with either transarterial (n = 121) or systemic treatments (n = 99; mainly Sorafenib) were retrospectively analyzed. The GALAD score and the BALAD-2 score were calculated based on AFP-L3, AFP, and DCP levels measured in serum samples collected before treatment. The results were correlated with 3-month treatment efficacy based on radiologic mRECIST criteria.

RESULTS

The GALAD score showed a strong correlation with BCLC stage (p < 0.001) and total tumor diameter before treatment (p < 0.001).The GALAD score at baseline was significantly lower in patients with a 3-month response to transarterial (p > 0.001) than in refractory patients. Among patients receiving systemic treatment, the median BALAD-2 score at baseline showed a strong association with response at month 3 (p < 0.001). In the transarterial treatment group, the GALAD score (AUC = 0.715; p < 0.001) as well as the BALAD score (AUC = 0.696; p < 0.001) were associated with overall survival, hereby outperforming AFP, AFP-L3 and DCP.

CONCLUSION

The GALAD score as well as the BALAD-2 score hold significant promise as a prognostic tool for patients with early or intermediate-stage HCC who are undergoing transarterial or systemic treatments.

Prevention in Hepatology

The prevention of liver disease has improved significantly in the last few decades, to the point that it can now be considered a true success story. The wide variety of interventions, including comprehensive vaccination strategies, novel medications, lifestyle changes, and even preventive surgeries, have reduced the morbidity and mortality of chronic liver diseases. However, the prevalence of chronic liver diseases is increasing worldwide. Currently, fatty liver disease alone is estimated to be present in as much as 30% of the adult population. Furthermore, there is a trend towards increasing incidences of chronic hepatitis B, and a global lack of success in efforts to eliminate chronic hepatitis C. Thus, improving and efficiently rolling out existing and successful prevention strategies for chronic liver diseases will play an essential role in healthcare throughout the upcoming decades. In this review, we summarize the current options and concepts for preventing chronic liver diseases, highlight their limitations, and provide an outlook on probable future developments to improve awareness, integrated care, and the analysis of big data.

Meta-analysis of the GALAD model for diagnosing primary hepatocellular carcinoma

BACKGROUND

Ever since the GALAD (gender-age-Lens culinaris agglutinin-reactive alpha-fetoprotein-alpha-fetoprotein-des-gamma-carboxy prothrombin) logistic regression model was established to diagnose hepatocellular carcinoma (HCC), there has been no high-level evidence that evaluates and summarizes it.

OBJECTIVE

This meta-analysis was performed to assess the diagnostic ability of the GALAD model.

METHODS

The following databases were systematically searched for original diagnostic studies on HCC: PubMed, Embase, Medline, the Web of Science, Cochrane Library, China National Knowledge Infrastructure Wanfang (China), Wiper and the Chinese BioMedical Literature Database. After screening the search results according to our criteria, the Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to evaluate the methodologic qualities, and statistical software were used to output the statistics.

RESULTS

Ultimately, 10 studies were included and analyzed. The results revealed the pooled sensitivity and specificity of the GALAD model to be 0.86 (95% confidence interval [CI]: 0.82, 0.90) and 0.90 (95% CI: 0.87, 0.92), respectively, for all-stage HCC. The area under the curve (AUC) was 0.94. For early-stage HCC, the pooled sensitivity and specificity of the GALAD model were 0.83 (95% CI: 0.78, 0.87) and 0.81 (95% CI: 0.78, 0.83), respectively. The AUC was 0.90.

CONCLUSION

This meta-analysis confirmed that the GALAD model has excellent diagnostic performance for early-stage and all-stage HCC and can maintain high sensitivity and specificity in early-stage HCC. Therefore, the GALAD model is qualified for screening early-stage canceration from chronic liver disease.

Development and application of hepatocellular carcinoma risk prediction model based on clinical characteristics and liver related indexes

BACKGROUND

Hepatocellular carcinoma (HCC) is difficult to diagnose with poor therapeutic effect, high recurrence rate and has a low survival rate. The survival of patients with HCC is closely related to the stage of diagnosis. At present, no specific serological indicator or method to predict HCC, early diagnosis of HCC remains a challenge, especially in China, where the situation is more severe.

AIM

To identify risk factors associated with HCC and establish a risk prediction model based on clinical characteristics and liver-related indicators.

METHODS

The clinical data of patients in the Affiliated Hospital of North Sichuan Medical College from 2016 to 2020 were collected, using a retrospective study method. The results of needle biopsy or surgical pathology were used as the grouping criteria for the experimental group and the control group in this study. Based on the time of admission, the cases were divided into training cohort (n = 1739) and validation cohort (n = 467). Using HCC as a dependent variable, the research indicators were incorporated into logistic univariate and multivariate analysis. An HCC risk prediction model, which was called NSMC-HCC model, was then established in training cohort and verified in validation cohort.

RESULTS

Logistic univariate analysis showed that, gender, age, alpha-fetoprotein, and protein induced by vitamin K absence or antagonist-II, gamma-glutamyl transferase, aspartate aminotransferase and hepatitis B surface antigen were risk factors for HCC, alanine aminotransferase, total bilirubin and total bile acid were protective factors for HCC. When the cut-off value of the NSMC-HCC model joint prediction was 0.22, the area under receiver operating characteristic curve (AUC) of NSMC-HCC model in HCC diagnosis was 0.960, with sensitivity 94.40% and specificity 95.35% in training cohort, and AUC was 0.966, with sensitivity 90.00% and specificity 94.20% in validation cohort. In early-stage HCC diagnosis, the AUC of NSMC-HCC model was 0.946, with sensitivity 85.93% and specificity 93.62% in training cohort, and AUC was 0.947, with sensitivity 89.10% and specificity 98.49% in validation cohort.

CONCLUSION

The newly NSMC-HCC model was an effective risk prediction model in HCC and early-stage HCC diagnosis.

Methylated SEPT9 combined with AFP and PIVKA-II is effective for the detection of HCC in high-risk population

BACKGROUND

The methylation SEPT9 (mSEPT9) appeared to be effective for hepatocellular carcinoma (HCC) detection. However, its performance in high-risk population has not been validated. We designed a pilot study and aimed to investigate the performance of mSEPT9, AFP, PIVKA-II and their combination in hepatic cirrhosis (HC) population.

METHODS

A training cohort was established including 103 HCC and 114 HC patients. 10 ml blood was collected from each patient with K₂EDTA tubes, and 3-4 ml plasma was extracted for subsequent tests. The performance of mSEPT9, AFP, PIVKA-II and their combination was optimized by the training cohort. Test performance was prospectively validated with a validation cohort, including 51 HCC and 121 HC patients.

RESULTS

At the optimal thresholds in the training cohort, the sensitivity, specificity and area under curve (AUC) was 72.82%, 89.47%, 0.84, and 48.57%, 89.92%, 0.79, and 63.64%, 95.95%, 0.79 for mSEPT9, AFP and PIVKA-II, respectively. The combined test significantly increased the sensitivity to 84.47% (P < 0.05) at the specificity of 86.84% with an AUC of 0.91. Stage-dependent performance was observed with all single markers and their combination in plasma marker levels, positive detection rate (PDR) and AUC. Moderate correlation was found between mSEPT9 and AFP plasma levels (r = 0.527, P < 0.0001). Good complementarity was found between any two of the three markers, providing optimal sensitivity in HCC detection when used in combination. Subsequent validation achieved a sensitivity, specificity and AUC of 65.31%, 92.86%, 0.80, and 44.24%, 89.26%, 0.75, and 62.22%, 95.27%, 0.78 for mSEPT9, AFP and PIVKA-II, respectively. The combined test yielded a significantly increased sensitivity of 84.00% (P < 0.05) at 85.57% specificity, with an AUC at 0.89.

CONCLUSIONS

The performance was optimal by the combination of mSEPT9, AFP, PIVKA-II compared with any single marker, and the combination may be effective for HCC opportunistic screening in HC population.

Precision diagnosis of hepatocellular carcinoma

ABSTRACT

Hepatocellular carcinoma (HCC) is the most common type of primary hepatocellular carcinoma (PHC). Early diagnosis of HCC remains the key to improve the prognosis. In recent years, with the promotion of the concept of precision medicine and more in-depth analysis of the biological mechanism underlying HCC, new diagnostic methods, including emerging serum markers, liquid biopsies, molecular diagnosis, and advances in imaging (novel contrast agents and radiomics), have emerged one after another. Herein, we reviewed and analyzed scientific advances in the early diagnosis of HCC and discussed their application and shortcomings. This review aimed to provide a reference for scientific research and clinical practice of HCC.

Pathogenesis to management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver cancer whose incidence continues to rise in many parts of the world due to a concomitant rise in many associated risk factors, such as alcohol use and obesity. Although early-stage HCC can be potentially curable through liver resection, liver-directed therapies, or transplantation, patients usually present with intermediate to advanced disease, which continues to be associated with a poor prognosis. This is because HCC is a cancer with significant complexities, including substantial clinical, histopathologic, and genomic heterogeneity. However, the scientific community has made a major effort to better characterize HCC in those aspects via utilizing tissue sampling and histological classification, whole genome sequencing, and developing viable animal models. These efforts ultimately aim to develop clinically relevant biomarkers and discover molecular targets for new therapies. For example, until recently, there was only one approved systemic therapy for advanced or metastatic HCC in the form of sorafenib. Through these efforts, several additional targeted therapies have gained approval in the United States, although much progress remains to be desired. This review will focus on the link between characterizing the pathogenesis of HCC with current and future HCC management.

Identification of serum glycobiomarkers for Hepatocellular Carcinoma using lectin microarrays

Objective

Hepatocellular carcinoma (HCC) is the sixth most commonly occurring cancer and ranks third in mortality among all malignant tumors; as a result, HCC represents a major human health issue. Although aberrant glycosylation is clearly implicated in HCC, changes in serum immunoglobulin (Ig)G and IgM glycosylation have not been comprehensively characterized. In this study, we used lectin microarrays to evaluate differences in serum IgG and IgM glycosylation among patients with HCC, hepatitis B cirrhosis (HBC), or chronic hepatitis B (CHB), and healthy normal controls (NC) and aimed to establish a model to improve the diagnostic accuracy of HCC.

Methods

In total, 207 serum samples collected in 2019–2020 were used for lectin microarray analyses, including 97 cases of HCC, 50 cases of HBC, 30 cases of CHB, and 30 cases of NC. Samples were randomly divided into training and validation groups at a 2:1 ratio. Training group data were used to investigate the diagnostic value of the relative signal intensity for the lectin probe combined with alpha-fetoprotein (AFP). The efficacy of models for HCC diagnosis were analyzed by receiver operating characteristic (ROC) curves.

Results

In terms of IgG, a model combining three lectins and AFP had good diagnostic accuracy for HCC. The area under the ROC curve was 0.96 (P < 0.05), the sensitivity was 82.54%, and the specificity was 100%. In terms of IgM, a model including one lectin combined with AFP had an area under the curve of 0.90 (P < 0.05), sensitivity of 75.41%, and specificity of 100%.

Conclusion

Estimation of serum IgG and IgM glycosylation could act as complementary techniques to improve diagnosis and shed light on the occurrence and development of the HCC

Predictive Value of MRI with Serum Lectin-Reactive Alpha-Fetoprotein for Liver Cancer Recurrence after Percutaneous Radiofrequency Ablation

Objective

To explore the predictive value of magnetic resonance imaging (MRI) with serum lectin-reactive alpha-fetoprotein (AFP-L3) for liver cancer recurrence after percutaneous radiofrequency ablation (RFA).

Methods

This study included 94 liver cancer patients admitted for RFA treatment and 82 healthy subjects. MRI was performed to record the apparent diffusion coefficient (ADC). The serum concentrations of AFP-L3 were quantified in all participants. The correlation of the AFP-L3 serum level and ADC value with clinical efficacy following RFA was analyzed. Moreover, the prognostic factors affecting liver cancer recurrence were analyzed, as well as the predictive effect of the ADC value and AFP-L3 on liver cancer recurrence.

Results

The serum AFP-L3 level was higher in liver cancer patients than the healthy controls with a lower ADC value. Besides, the patients with tumor residuals had lower ADC values and higher serum AFP-L3 levels than those with complete ablated tumor. The combined detection of the ADC value and serum AFP-L3 level had a sensitivity of 87.50% and a specificity of 87.18% for diagnosing complete ablation after RFA treatment. The number of tumor nodules, tumor diameter, AFP, AFP-L3, and the presence of liver cirrhosis are all independent risk factors for liver cancer recurrence within one year. Meanwhile, the combined detection of the ADC value and serum AFP-L3 level had a good predictive effect on liver cancer recurrence with the sensitivity of 92.86% and a specificity of 69.62%.

Conclusion

The ADC values combined with serum AFP-L3 detection had good predictive effects on complete ablation and recurrence of liver cancer after RFA treatment.

Biomarkers and Genetic Markers of Hepatocellular Carcinoma and Cholangiocarcinoma-What Do We Already Know

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with an increasing worldwide mortality rate. Cholangiocarcinoma (CCA) is the second most common primary liver cancer. In both types of cancers, early detection is very important. Biomarkers are a relevant part of diagnosis, enabling non-invasive detection and control of cancer recurrence, as well as in the application of screening tests in high-risk groups. Furthermore, some of these biomarkers are useful in controlling therapy and treatment selection. Detection of some markers presents higher sensitivity and specificity in combination with other markers when compared with a single detection. Some gene aberrations are also prognostic markers in the two types of cancers. In the following review, we discuss the most common biomarkers and genetic markers currently being used in the diagnosis of hepatocellular carcinoma and cholangiocarcinoma.

Update on the applications and limitations of alpha-fetoprotein for hepatocellular carcinoma

Alpha-fetoprotein (AFP) is an oncofetal glycoprotein that has been used as a tumor marker for hepatocellular carcinoma (HCC) in combination with ultrasound and other imaging modalities. Its utility is limited because of both low sensitivity and specificity, and discrepancies among the different methods of measurements. Moreover, its accuracy varies according to patient characteristics and the AFP cut-off values used. Combination of AFP with novel biomarkers such as AFP-L3, Golgi specific membrane protein (GP73) and des-gamma-carboxyprothrombin significantly improved its accuracy in detecting HCC. Increased AFP level could also signify severity of hepatic destruction and subsequent regeneration and is commonly observed in patients with acute and chronic liver conditions and cirrhosis. Hereditary and other non-hepatic disorders can also cause AFP elevation.

The Landscape Of Alpha Fetoprotein In Hepatocellular Carcinoma: Where Are We?

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and has been acknowledged as a leading cause of death among cirrhosis patients. Difficulties in early diagnosis and heterogeneity are obstacles to effective treatment, especially for advanced HCC. Liver transplantation (LT) is considered the best therapy for HCC. Although many biomarkers are being proposed, alpha-fetoprotein (AFP), which was identified over 60 years ago, remains the most utilized. Recently, much hope has been placed in the immunogenicity of AFP to develop novel therapies, such as AFP vaccines and AFP-specific adoptive T-cell transfer (ACT). This review summarizes the performance of AFP as a biomarker for HCC diagnosis and prognosis, as well as its correlation with molecular classes. In addition, the role of AFP in LT is also described. Finally, we highlight the mechanism and application prospects of two immune therapies (AFP vaccine and ACT) for HCC. In general, our review points out the prevalence of AFP in HCC, accompanied by some controversies and novel directions for future research.

Critical biomarkers of hepatocellular carcinoma in body fluids and gut microbiota

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer and one of the major causes of cancer-related death. The development of specific non-invasive or diagnostic markers from blood, urine and feces may represent a valuable tool for detecting HCC at an early stage. Biomarkers are considered novel potential targets for therapeutic intervention. It helps in the prediction of prognosis or recurrence of HCC, and also assist in the selection of appropriate treatment modality. We summarize the most relevant existing data about various biomarkers that play a key role in the progression of HCC.

Viral Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Occurrence and Recurrence

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the fourth leading cause of cancer-related death. The most common risk factor for developing HCC is chronic infection with hepatitis B virus (HBV). Early stages of HBV-related HCC (HBV-HCC) are generally asymptomatic. Moreover, while serum alpha-fetoprotein (AFP) and abdominal ultrasound are widely used to screen for HCC, they have poor sensitivity. Thus, HBV-HCC is frequently diagnosed at an advanced stage, in which there are limited treatment options and high mortality rates. Serum biomarkers with high sensitivity and specificity are crucial for earlier diagnosis of HCC and improving survival rates. As viral-host interactions are key determinants of pathogenesis, viral biomarkers may add greater diagnostic power for HCC than host biomarkers alone. In this review, we summarize recent research on using virus-derived biomarkers for predicting HCC occurrence and recurrence; including circulating viral DNA, RNA transcripts, and viral proteins. Combining these viral biomarkers with AFP and abdominal ultrasound could improve sensitivity and specificity of early diagnosis, increasing the survival of patients with HBV-HCC. In the future, as the mechanisms that drive HBV-HCC to become clearer, new biomarkers may be identified which can further improve early diagnosis of HBV-HCC.

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

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

MicroRNA polymorphism: A target for diagnosis and prognosis of hepatocellular carcinoma?

Hepatocellular carcinoma (HCC) is a life-threatening cancer of the digestive system, with complex pathogenesis affected by a broad spectrum of genetic and epigenetic factors. Among several factors, microRNAs (miRNAs), which are considered regulators of the post-transcriptional gene expression, play important roles in determining the malignant phenotype of HCC. In recent years, the advances in molecular genetics have resulted in the characterization of complex genetic factors and in the identification of epigenetic mechanisms of diseases. Accumulating data have suggested that miRNA polymorphisms are involved in tumorigenesis and prognosis, suggesting that the miRNAs may serve as a target for HCC with regard to pathogenesis and prognosis. In the present review, a comprehensive and detailed literature search was conducted and the role of miRNA polymorphisms in the pathogenesis and prognosis of HCC is summarized. The data proposed the use of miRNAs as targets for the diagnosis and treatment of HCC.