Longitudinal Assessment of Three Serum Biomarkers to Detect Very Early-Stage Hepatocellular Carcinoma

Diagnostic value of alpha-fetoprotein and prothrombin induced by vitamin K absence-II in serum, bile, and feces in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common pathological type of liver cancer and was the third leading cause of cancer-related deaths worldwide in 2020.

AIM

To evaluate the diagnostic potential of key tumor markers in serum, bile, and fecal samples for detecting HCC.

METHODS

Blood, bile, and fecal samples were collected from patients (n = 265) with HCC and cholecystitis from Guangxi Medical University’s First Affiliated Hospital. Immunohistochemistry was performed on 69 HCC samples, and 16S ribosomal RNA sequencing was conducted on 166 fecal samples. Tumor marker cut-off values in bile and feces were determined using the Youden index, while serum biomarkers followed hospital standards. Diagnostic performance was evaluated using receiver operating characteristic analysis.

RESULTS

The areas under the curve (AUCs) for distinguishing HCC were 0.898, 0.904, and 0.859 for serum alpha-fetoprotein (AFP), prothrombin induced by vitamin K absence-II (PIVKA-II), and bile AFP, respectively. Serum AFP had the highest diagnostic value (80%) for early-stage HCC. Combination analysis found that bile AFP and serum PIVKA-II achieved the highest AUC of 0.965 (P < 0.001), suggesting that bile AFP may serve as a valuable complementary biomarker, particularly in cases where serum AFP is not significantly elevated. Additionally, bile AFP was positively correlated with Actinomyces, which plays a significant role in promoting tumorigenesis; and was negatively correlated with Faecalibacterium, which was associated with robust anticancer immune responses (P < 0.05). These findings suggest the potential role of gut microbiota in modulating AFP levels and HCC progression.

CONCLUSION

Bile AFP improved the sensitivity of HCC detection, with the combination of bile AFP and PIVKA-II demonstrating the highest AUC for HCC diagnosis. AFP is associated with poorer clinical outcomes.

Performance of the GALAD Model in an Asian Cohort Undergoing Hepatocellular Carcinoma Surveillance: A Prospective Cohort Study

BACKGROUND AND AIM

Current hepatocellular carcinoma (HCC) surveillance strategy has its limitations, consequently delaying early detection. The GALAD model has been validated in retrospective studies, with two published cut-off values yielding different sensitivities for HCCs of different etiologies. We evaluated the performance of GALAD model in HCC surveillance and determined the ideal cut-off value for our cohort.

METHODS

Patients undergoing 6-monthly HCC surveillance in Singapore General Hospital were recruited between December 2017-October 2018. Study serum specimens were prospectively collected and retrospectively tested using the μTASWako alpha-fetoprotein (AFP), AFP-L3, and protein induced by vitamin K antagonism-II (PIVKA-II) kits. GALAD score was calculated and compared with individual biomarkers using area under the curve (AUC) analysis. Published GALAD cut-offs of -0.63 and -1.95 were compared for their performance in HCC detection.

RESULTS

There were 207 patients (median age 59 years, 55.1% males). Hepatitis B was the commonest etiology (72.9%). By February 2023, with a median follow-up of 48.9 months, 20 patients had developed HCC. Eight patients developed HCC within 1 year from specimen collection. For HCC developing within 1 year, GALAD model detected HCC with an AUC of 0.84, greater than AFP (AUC 0.77), AFP-L3 (AUC 0.60), and PIVKA-II (AUC 0.67). GALAD at cut-off -1.95 achieved sensitivity and specificity of 75% and 92.5% for HCCs detected within 1 year, superior to cut-off -0.63 (sensitivity 12.5%, specificity 100%).

CONCLUSION

In this prospective study of HCC surveillance, the GALAD model performed better than individual biomarkers. The cut-off of -1.95 was more useful in our predominantly chronic hepatitis B cohort.

Pathogenesis and Systemic Treatment of Hepatocellular Carcinoma: Current Status and Prospects

Hepatocellular carcinoma (HCC) remains one of the major threats to human health worldwide. The emergence of systemic therapeutic options has greatly improved the prognosis of patients with HCC, particularly those with advanced stages of the disease. In this review, we discussed the pathogenesis of HCC, genetic alterations associated with the development of HCC, and alterations in the tumor immune microenvironment. Then, important indicators and emerging technologies related to the diagnosis of HCC are summarized. Also, we reviewed the major advances in treatments for HCC, offering insights into future prospects for next-generation managements.

Integrating Machine Learning and Follow-Up Variables to Improve Early Detection of Hepatocellular Carcinoma in Tyrosinemia Type 1: A Multicenter Study

Hepatocellular carcinoma (HCC) is a major complication of tyrosinemia type 1 (HT-1), an inborn error of metabolism affecting tyrosine catabolism. The risk of HCC is higher in late diagnoses despite treatment. Alpha-fetoprotein (AFP) is widely used to detect liver cancer but has limitations in early-stage HCC detection. This study aimed to implement a machine-learning (ML) approach to identify the most relevant laboratory variables to predict AFP alteration using constrained multidimensional data from Chilean and Italian HT-1 cohorts. A longitudinal retrospective study analyzed 219 records from 35 HT-1 patients, including 8 with HCC and 5 diagnosed through newborn screening. The dataset contained biochemical and demographic variables that were analyzed using the eXtreme Gradient Boosting algorithm, which was trained to predict abnormal AFP levels (>5 ng/mL). Four key variables emerged as significant predictors: alanine transaminase (ALT), alkaline phosphatase, age at diagnosis, and current age. ALT emerged as the most promising indicator of AFP alteration, potentially preceding AFP level changes and improving HCC detection specificity at a cut-off value of 29 UI/L (AUROC = 0.73). Despite limited data from this rare disease, the ML approach successfully analyzed follow-up biomarkers, identifying ALT as an early predictor of AFP elevation and a potential biomarker for HCC progression.

Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma

Hepatitis B virus (HBV) causes liver cancer, which is the third most common cause of cancer-related death worldwide. Chronic inflammation via HBV in the host hepatocytes causes hepatocyte remodeling (hepatocyte transformation and immortalization) and hepatocellular carcinoma (HCC). Recognizing cancer stages accurately to optimize early screening and diagnosis is a primary concern in the outlook of HBV-induced hepatocyte remodeling and liver cancer. Genomic signatures play important roles in addressing this issue. Recently, machine learning (ML) models and bioinformatics analysis have become very important in discovering novel genomic signatures for the early diagnosis, treatment, and prognosis of HBV-induced hepatic cell remodeling and HCC. We discuss the recent literature on the ML approach and bioinformatics analysis revealed novel genomic signatures for diagnosing and forecasting HBV-associated hepatocyte remodeling and HCC. Various genomic signatures, including various microRNAs and their associated genes, long noncoding RNAs (lncRNAs), and small nucleolar RNAs (snoRNAs), have been discovered to be involved in the upregulation and downregulation of HBV-HCC. Moreover, these genetic biomarkers also affect different biological processes, such as proliferation, migration, circulation, assault, dissemination, antiapoptosis, mitogenesis, transformation, and angiogenesis in HBV-infected hepatocytes.

Risk Factors for Intrahepatic Distant Recurrence After Radiofrequency Ablation for Hepatocellular Carcinoma

AIM

The incidence of intrahepatic distant recurrence (IDR) of hepatocellular carcinoma (HCC) still remains high after radiofrequency ablation (RFA). However, serum alpha-fetoprotein (AFP) has insufficient screening power. This study aimed to identify risk factors for IDR in patients with post-RFA HCC.

METHOD

A total of 112 patients with early-stage HCC who underwent RFA were divided into the IDR (n = 51) and non-IDR groups (n = 61). Serum samples were analyzed within 2 months after RFA.

RESULTS

The mean follow-up duration was 30.1 months. The recurrence-free survival rates at 1, 3, and 5 years were 20.8%, 42.4%, and 54.2%, respectively. The 1- and 5-year overall survival rates were 97.3% and 87.3%, respectively. Univariate and multivariate analyses revealed that the neutrophil-to-lymphocyte ratio [NLR, hazard ratio (HR) 2.40; 95% confidence interval (CI) 1.44-3.99] and lens culinaris agglutinin a-reactive fraction of alpha-fetoprotein (AFP-L3, (HR 1.02; 95% CI 1.01-1.04) were independently associated with post-RFA IDR. The cumulative recurrence rates at 5 years in the high NLR (≥ 2.24) and high AFP-L3 (≥ 0.2 ng/mL) groups were significantly higher than those in the low NLR (< 2.24) and low AFP-L3 (< 0.2 ng/mL) groups, respectively. The predictive accuracies of NLR, AFP-L3, and a composite index based on AFP-L3, and NLR for IDR were 66.2% (37.3% sensitivity, 95.1% specificity), 64.3% (47.1% sensitivity, 80.3% specificity), and 75.6% (68.6% sensitivity, 75.4% specificity), respectively.

CONCLUSION

The combined model had significantly better prediction performance than either NLR or AFP-L3 alone. The NLR combined with an absolute AFP-L3 level is an effective marker for IDR in patients with post-RFA HCC.

Strategies for discovering novel hepatocellular carcinoma biomarkers

Liver cancer, particularly hepatocellular carcinoma (HCC), remains a significant global health challenge due to its high mortality rate and late-stage diagnosis. The discovery of reliable biomarkers is crucial for improving early detection and patient outcomes. This review provides a comprehensive overview of current and emerging biomarkers for HCC, including alpha-fetoprotein, des-gamma-carboxy prothrombin, glypican-3, Golgi protein 73, osteopontin, and microRNAs. Despite advancements, the diagnostic limitations of existing biomarkers underscore the urgent need for novel markers that can detect HCC in its early stages. The review emphasizes the importance of integrating multi-omics approaches, combining genomics, proteomics, and metabolomics, to develop more robust biomarker panels. Such integrative methods have the potential to capture the complex molecular landscape of HCC, offering insights into disease mechanisms and identifying targets for personalized therapies. The significance of large-scale validation studies, collaboration between research institutions and clinical settings, and consideration of regulatory pathways for clinical implementation is also discussed. In conclusion, while substantial progress has been made in biomarker discovery, continued research and innovation are essential to address the remaining challenges. The successful translation of these discoveries into clinical practice will require rigorous validation, standardization of protocols, and cross-disciplinary collaboration. By advancing the development and application of novel biomarkers, we can improve the early detection and management of HCC, ultimately enhancing patient survival and quality of life.

Surveillance for Hepatocellular Carcinoma

This article reviews surveillance for the detection of early stage hepatocellular carcinoma, covering the rationale for surveillance, optimal selection of persons needing surveillance, methods and frequency of screening, strategies for addressing barriers to surveillance, and trends for future improvement in surveillance leading to more effective cancer control and improved patient outcomes. The importance of integrating liver cancer surveillance as a core component of national public health programs is emphasized. The impact of emerging technologies for identifying persons at risk, stratifying individual risk to improve the cost-effectiveness of surveillance programs, and improving the performance, accessibility, and convenience of surveillance are discussed.

Diagnostic Performance of PIVKA-II in Italian Patients with Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) represents the second leading cause of cancer deaths worldwide. Six-month imaging along with alpha-fetoprotein (AFP) serum levels detection are the current gold standard to exclude HCC. Protein induced by vitamin K absence (PIVKA-II) has been proposed as a potential screening biomarker for HCC. This study was designed to evaluate the role of PIVKA-II as diagnostic HCC marker, and the correlation between PIVKA-II levels and HCC stage.

METHODS

PIVKA-II levels were assessed on serum samples of Italian patients. The study population included 80 patients with HCC, 111 with liver cirrhosis (LC), and 111 with chronic hepatitis C (CHC).

RESULTS

PIVKA-II serum levels progressively increase from patients with CHC to patients with HCC. In the HCC group, PIVKA-II values are higher in the more advanced stages of the disease, assessed by the Barcelona Clinic Liver Cancer (BCLC) staging system (BCLC-B vs. BCLC-A vs. BCLC-0). Youden's index analysis identified a value >37 mAU/mL as the optimal threshold for the best combination of sensitivity and specificity (80% and 76%, respectively) and, at the best cut-off of 5.2 ng/mL, AFP yielded 53% specificity and 78% sensitivity. The combination of PIVKA-II and AFP reached positive and negative predictive values of 73.9% and 94.2%, respectively.

CONCLUSIONS

PIVKA-II levels are increased in the HCC patients, compared to control groups. The increase is more evident in patients with advanced HCC. The diagnostic performance of PIVKA-II seems more sensitive than AFP while the combination of PIVKA-II and AFP resulted in the best diagnostic accuracy, reaching 73.9% positive predictive value and 94.2% negative predictive value, thus improving the diagnostic capability of the single marker.

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.

Current status and new directions for hepatocellular carcinoma diagnosis

Liver cancer ranks as the sixth most common cancer globally, with hepatocellular carcinoma (HCC) accounting for approximately 75%-85% of cases. Most patients present with moderately advanced disease, while those with advanced HCC face limited and ineffective treatment options. Despite diagnostic efforts, no ideal tumor marker exists to date, highlighting the urgent clinical need for improved early detection of HCC. A key research objective is the development of assays that target specific pathways involved in HCC progression. This review explores the pathological origin and development of HCC, providing insights into the mechanistic rationale, clinical statistics, and the advantages and limitations of commonly used diagnostic tumor markers. Additionally, it discusses the potential of emerging biomarkers for early diagnosis and offers a brief overview of relevant assay methodologies. This review aims to summarize existing markers and investigate new ones, providing a basis for subsequent research.

Cell Cycle-Related LncRNA-Based Prognostic Model for Hepatocellular Carcinoma: Integrating Immune Microenvironment and Treatment Response

OBJECTIVE

Hepatocellular carcinoma (HCC) presents substantial genetic and phenotypic diversity, making it challenging to predict patient outcomes. There is a clear need for novel biomarkers to better identify high-risk individuals. Long non-coding RNAs (lncRNAs) are known to play key roles in cell cycle regulation and genomic stability, and their dysregulation has been closely linked to HCC progression. Developing a prognostic model based on cell cycle-related lncRNAs could open up new possibilities for immunotherapy in HCC patients.

METHODS

Transcriptomic data and clinical samples were obtained from the TCGA-HCC dataset. Cell cycle-related gene sets were sourced from existing studies, and coexpression analysis identified relevant lncRNAs (correlation coefficient >0.4, P<0.001). Univariate analysis identified prognostic lncRNAs, which were then used in a LASSO regression model to create a risk score. This model was validated via cross-validation. HCC samples were classified on the basis of their risk scores. Correlations between the risk score and tumor mutational burden (TMB), tumor immune infiltration, immune checkpoint gene expression, and immunotherapy response were evaluated via R packages and various methods (TIMER, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, MCP-COUNTER, XCELL, and EPIC).

RESULTS

Four cell cycle-related lncRNAs (AC009549.1, AC090018.2, PKD1P6-NPIPP1, and TMCC1-AS1) were significantly upregulated in HCC. These lncRNAs were used to create a risk score (risk score=0.492×AC009549.1+1.390×AC090018.2+1.622×PKD1P6-NPIPP1+0.858×TMCC1-AS1). This risk score had superior predictive value compared to traditional clinical factors (AUC=0.738). A nomogram was developed to illustrate the 1-year, 3-year, and 5-year overall survival (OS) rates for individual HCC patients. Significant differences in TMB, immune response, immune cell infiltration, immune checkpoint gene expression, and drug responsiveness were observed between the high-risk and low-risk groups.

CONCLUSION

The risk score model we developed enhances the prognostication of HCC patients by identifying those at high risk for poor outcomes. This model could lead to new immunotherapy strategies for HCC patients.

LI-RADS US Surveillance Version 2024 for Surveillance of Hepatocellular Carcinoma: An Update to the American College of Radiology US LI-RADS

In 2017, the American College of Radiology introduced the US Liver Imaging Reporting and Data System (LI-RADS) as a framework for US surveillance of patients at risk for developing hepatocellular carcinoma. This has aided in the standardization of technique, clinical reporting, patient management, data collection, and research. Emerging evidence has helped inform changes to the algorithm, now released as LI-RADS US Surveillance version 2024. The updated algorithm, the rationale for changes, and its alignment with the 2023 American Association for the Study of Liver Diseases Practice Guidance are presented.

The methylation signature of hepatocellular carcinoma trajectory based on pseudotime and chronological time for predicting precancerous patients

BACKGROUND

Early screening of hepatocellular carcinoma (HCC) is strongly recommended for hepatitis B virus (HBV)-infected patients. We aimed to develop and validate a predictive nomogram based on HCC occurrence trajectory for screening precancerous patients with HCC.

METHODS

Peripheral blood mononuclear cells (PBMC) samples from 22 patients with HCC with their precancerous stage (n = 55) and 18 healthy controls were measured using HumanMethylation EPIC BeadChip assay. HCC trajectory was assessed by pseudotime based on TimeAx algorithm and chronological time. The 43 candidate CpG sites were selected from the methylation signature and measured using multiplex bisulfite sequencing in a retrospective cohort of HBV-infected patients (n = 604). A 5-CpG-classifier was built using the LASSO Cox regression model, based on the association between the methylation level of every CpG and the duration from enrollment to HCC occurrence of individual patient. We validated the risk stratification and predictive accuracy of this classifier in both the primary cohort (n = 300) and independent validation cohort (n = 304).

RESULTS

Pseudotime and chronological time of HCC trajectory analysis revealed that the PD-1/PD-L1 pathway underwent changes in the precancerous stage. Based on the trajectory of methylation signature, we built a 5-CpG-classifier which remained powerful and independent predictive efficiency after stratified analysis by clinicopathological risk factors in both primary cohort and independent validation cohort. A predicting nomogram including the 5-CpG-classifier was constructed after multivariate analysis. One-year cumulative hazard of HCC in low- and high-risk groups of HBV-infected patients was 3.0% (0.1%-5.8%) and 17.90% (11.00%-24.3%) (P < .0001) in primary cohort, 4.5% (1.20%-7.80%) and 27.3 (18.90-34.90) (P < .0001) in the independent validation cohort.

CONCLUSIONS

One-year before HCC was a critical period of transitional time when parts of the methylation profile underwent shifting toward HCC like. The nomogram could identify precancerous stage patients with HCC who should be screened for early diagnosis and intervention.

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma

Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti-PD-1/PD-L1 outcomes centered on the cGAS-STING pathway in HCC. We identified classical pathways highly correlated with cGAS-STING pathway and constructed transformer survival model preserving raw structure of pathways. We also developed explainable XGBoost model for predicting anti-PD-1/PD-L1 outcomes using SHAP algorithm. We trained and validated transformer survival model on pan-cancer cohort and tested it on three independent HCC cohorts. Using 0.5 as threshold across cohorts, we divided each HCC cohort into two groups and calculated P values with log-rank test. TCGA-LIHC: C-index = 0.750, P = 1.52e-11; ICGC-LIRI-JP: C-index = 0.741, P = .00138; GSE144269: C-index = 0.647, P = .0233. We trained and validated [area under the receiver operating characteristic curve (AUC) = 0.777] XGBoost model on immunotherapy datasets and tested it on GSE78220 (AUC = 0.789); we also tested XGBoost model on HCC anti-PD-L1 cohort (AUC = 0.719). Our deep learning model and XGBoost model demonstrate potential in predicting survival risks and anti-PD-1/PD-L1 outcomes in HCC. We deployed these two prediction models to the GitHub repository and provided detailed instructions for their usage: deep learning survival model, https://github.com/mlwalker123/CSP_survival_model; XGBoost immunotherapy model, https://github.com/mlwalker123/CSP_immunotherapy_model.

Risk-stratified hepatocellular carcinoma screening according to the degree of obesity and progression to cirrhosis for diabetic patients with metabolic dysfunction-associated steatotic liver disease (MASLD) in Japan: a cost-effectiveness study

OBJECTIVE

To evaluate the cost-effectiveness of risk-stratified hepatocellular carcinoma (HCC) screening in diabetic patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

DESIGN

A state-transition model from a healthcare payer perspective on a lifetime horizon.

SETTING

Japan.

POPULATION

A hypothetical cohort of 50-year-old diabetic patients with MASLD risk-stratified according to degree of obesity and progression to cirrhosis. Metabolic dysfunction-associated steatotic liver (MASL), metabolic dysfunction-associated steatohepatitis (MASH) and MASH cirrhosis are progressive manifestations of this specific type of liver disease.

INTERVENTION

Abdominal ultrasound (US), US with alpha-fetoprotein (AFP), US with AFP and lectin-reactive alpha-fetoprotein (AFP-L3), CT, extracellular contrast-media-enhanced MRI (ECCM-MRI), gadoxetic acid-enhanced MRI (EOB-MRI) and no screening.

MAIN OUTCOME MEASURE

Costs, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), early-stage HCC cases, advanced-stage HCC cases and HCC-related deaths.

RESULTS

EOB-MRI is the most cost-effective screening method for non-obese diabetic patients with MASH cirrhosis and for obese diabetic patients with MASH and MASH cirrhosis. Cost-effectiveness was sensitive to HCC incidence in non-obese diabetic patients with MASH cirrhosis and obese diabetic patients with MASH, and the adherence rate of HCC screening in obese diabetic patients with MASH. When the semiannual HCC incidence was between 0.008 and 0.0138 in non-obese diabetic patients with MASH cirrhosis, US with AFP was more cost-effective than EOB-MRI. Cost-effectiveness acceptability curves showed that EOB-MRI was 50.7%, 96.0% and 99.9% cost-effective in obese diabetic patients with MASH and non-obese diabetic patients with MASH cirrhosis, and obese diabetic patients with MASH cirrhosis at a willingness-to-pay level of $50 000 per QALY gained. Compared with no screening in 100 000 non-obese diabetic patients with MASH cirrhosis and obese diabetic patients with MASH cirrhosis, EOB-MRI reduced total costs by US$69 million and by US$142 million, increased lifetime effectiveness by 12 546 QALYs and by 15 815 QALYs, detected 17 873 and 21 014 early-stage HCC cases, and averted 2068 and 2471 HCC-related deaths, respectively.

CONCLUSIONS

Of all HCC screening methods for diabetic patients with MASH cirrhosis, EOB-MRI yields the greatest cost-saving with the highest QALYs, detects the greatest number of early-stage HCC cases and averts the greatest number of advanced-stage HCC cases and HCC-related deaths. The findings provide important insights for the precise implementation of risk-stratified HCC surveillance to reduce morbidity and mortality and improve the quality of life in diabetic patients with MASLD.

Point-of-care testing for early-stage liver cancer diagnosis and personalized medicine: Biomarkers, current technologies and perspectives

Liver cancer is a highly prevalent and lethal form of cancer worldwide. In the absence of early diagnosis, treatment options for this disease are severely restricted. Recent advancements in genomics and bioinformatics have facilitated the discovery of a multitude of novel biomarkers that accurately depict an individual's disease diagnosis, progression, and treatment response. Leveraging these breakthroughs, personalized medicine employs an individual's biomarker profile to enable early detection of liver cancer and inform decisions regarding treatment selection, dosage determination, and prognosis assessment. The current lack of readily applicable, timely, and economically viable tools for biomarker analysis has hindered the incorporation of personalized medicine into regular clinical procedures. Over the past decade, significant advancements have been achieved in the field of molecular point-of-care testing (POCT) and amplification techniques, leading to substantial improvements in the diagnosis of liver cancer and the implementation of precision medicine. Instrument-free PCR technology or plasma PCR technology can shorten the complex procedure of in vitro detection of nucleic acid-based biomarkers. Also, compared to traditional ELISA, various nanomaterials modified with monoclonal antibodies to target proteins for recognition, capture, and detection have improved the efficiency of protein-based biomarker detection. These advances have reduced the time and cost of clinical detection of early-stage hepatocellular carcinoma and improved the efficiency of timely diagnosis and survival of suspected patients while reducing unnecessary testing costs and procedures. This review aims to provide a comprehensive overview of the current and emerging biomarkers employed in the early detection of liver cancer, as well as the advancements in point-of-care molecular testing technology and platforms. The primary objective is to assess their potential in facilitating the implementation of personalized medicine. This review ultimately revealed that the diagnosis of early-stage hepatocellular carcinoma not only requires sensitive biomarkers, but its various modifications and changes during the progression of cirrhosis to early-stage hepatocellular carcinoma will be a greater focus of our attention in the future. The rapid development of POCT has facilitated the opportunity to readily detect liver cancer in the general population in the future, and the integration of multi-pathway multiplexing and intelligent algorithms has improved the sensitivity and accuracy of early liver cancer biomarker detection. It is expected that the integration of point-of-care technology will be instrumental in the widespread adoption of personalized medicine in the foreseeable future.

Novel Biomarkers for Early Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally. Most patients present with late diagnosis, leading to poor prognosis. This narrative review explores novel biomarkers for early HCC detection. We conducted a comprehensive literature review analyzing protein, circulating nucleic acid, metabolite, and quantitative proteomics-based biomarkers, evaluating the advantages and limitations of each approach. While established markers like alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin, and AFP-L3 remain relevant, promising candidates include circulating tumor DNA, microRNAs, long noncoding RNAs, extracellular vesicle, and metabolomic biomarkers. Multi-biomarker panels like the GALAD score, Oncoguard, and Helio liver test show promise for improved diagnostic accuracy. Non-invasive approaches like urine and gut microbiome analysis are also emerging possibilities. Integrating these novel biomarkers with current screening protocols holds significant potential for earlier HCC detection and improved patient outcomes. Future research should explore multi-biomarker panels, omics technologies, and artificial intelligence to further enhance early HCC diagnosis and management.

The expression and clinical significance of syncytin-1 in serum exosomes of hepatocellular carcinoma patients

This study aimed to investigate the expression and clinical significance of syncytin-1 in the serum exosomes of hepatocellular carcinoma (HCC) patients. Serum samples were collected from 61 patients with newly diagnosed HCC and 61 healthy individuals. Exosomes were extracted from serum samples and identified using transmission electron microscopy and Western blot. The relative expression levels of syncytin-1 in exosomes were determined by real-time quantitative PCR. The protein expression levels of alpha-fetoprotein and syncytin-1 in HCC patients were detected using enzyme-linked immunosorbent assay (ELISA). Statistical analysis was performed to evaluate the sensitivity and specificity of serum exosomal syncytin-1 in diagnosing HCC. The relationships between syncytin-1 expression and clinical pathological features were analyzed using receiver operating characteristic curve analysis. The results showed that the expression level of syncytin-1 in the serum of patients with newly diagnosed HCC was significantly higher than that in the normal control group (P < 0.0001). Using pathological diagnosis as the gold standard, the sensitivity and specificity of syncytin-1 for the auxiliary diagnosis of HCC were 91.3% and 75.5%, respectively, which were significantly higher than those of alpha-fetoprotein (P < 0.0001). The relative expression level of serum exosomal syncytin-1 was significantly associated with lymph node metastasis, degree of differentiation, and CNLC staging of HCC patients (P < 0.05). In conclusion, syncytin-1 in serum exosomes has high sensitivity and specificity for diagnosing HCC and can serve as a novel tumor marker for early screening, detection, and staging of HCC.

Roles of clinical application of lenvatinib and its resistance mechanism in advanced hepatocellular carcinoma (Review)

Lenvatinib (LEN) is a multi-target TKI, which plays a pivotal role in the treatment of advanced hepatocellular carcinoma (HCC). The inevitable occurrence of drug resistance still prevents curative potential and is deleterious for the prognosis, and a growing body of studies is accumulating, which have devoted themselves to unveiling its underlying resistance mechanism and made some progress. The dysregulation of crucial signaling pathways, non-coding RNA and RNA modifications were proven to be associated with LEN resistance. A range of drugs were found to influence LEN therapeutic efficacy. In addition, the superiority of LEN combination therapy has been shown to potentially overcome the limitations of LEN monotherapy in a series of research, and a range of promising indicators for predicting treatment response and prognosis have been discovered in recent years. In this review, we summarize the latest developments in LEN resistance, the efficacy and safety of LEN combination therapy as well as associated indicators, which may provide new insight into its resistance as well as ideas in the treatment of advanced HCC.

Diagnostic performance of AI-based models versus physicians among patients with hepatocellular carcinoma: a systematic review and meta-analysis

Background

Hepatocellular carcinoma (HCC) is a common primary liver cancer that requires early diagnosis due to its poor prognosis. Recent advances in artificial intelligence (AI) have facilitated hepatocellular carcinoma detection using multiple AI models; however, their performance is still uncertain.

Aim

This meta-analysis aimed to compare the diagnostic performance of different AI models with that of clinicians in the detection of hepatocellular carcinoma.

Methods

We searched the PubMed, Scopus, Cochrane Library, and Web of Science databases for eligible studies. The R package was used to synthesize the results. The outcomes of various studies were aggregated using fixed-effect and random-effects models. Statistical heterogeneity was evaluated using I-squared (I2) and chi-square statistics.

Results

We included seven studies in our meta-analysis;. Both physicians and AI-based models scored an average sensitivity of 93%. Great variation in sensitivity, accuracy, and specificity was observed depending on the model and diagnostic technique used. The region-based convolutional neural network (RCNN) model showed high sensitivity (96%). Physicians had the highest specificity in diagnosing hepatocellular carcinoma(100%); furthermore, models-based convolutional neural networks achieved high sensitivity. Models based on AI-assisted Contrast-enhanced ultrasound (CEUS) showed poor accuracy (69.9%) compared to physicians and other models. The leave-one-out sensitivity revealed high heterogeneity among studies, which represented true differences among the studies.

Conclusion

Models based on Faster R-CNN excel in image classification and data extraction, while both CNN-based models and models combining contrast-enhanced ultrasound (CEUS) with artificial intelligence (AI) had good sensitivity. Although AI models outperform physicians in diagnosing HCC, they should be utilized as supportive tools to help make more accurate and timely decisions.

Circulating tumor DNA in management of primary liver malignancy: A review of the literature and future directions

Primary liver malignancies are a serious and challenging global health concern. The most common primary tumors are hepatocellular carcinoma and cholangiocarcinoma. These diseases portend poor prognosis when presenting with progressive, extensive disease. There is a critical need for improved diagnosis, therapeutic intervention, and monitoring surveillance in liver-related malignancies. Liquid biopsy using ctDNA provides an opportunity for growth within these domains for liver-related malignancy. However, ctDNA is relatively understudied in this field compared with other solid tumor types, possibly due to the complex nature of the pathology. In this review, we aim to discuss ctDNA, the current literature, and future directions of this technology within primary liver malignancies.

Clinical potential of serum prostaglandin A2 as a novel diagnostic biomarker for hepatocellular cancer

BACKGROUND

Hepatocellular cancer (HCC) is one of the most harmful tumors to human health. Currently, there is still a lack of highly sensitive and specific HCC biomarkers in clinical practice. In this study, we aimed to explore the diagnostic performance of prostaglandin A2 (PGA2) for the early detection of HCC.

METHODS

Untargeted metabolomic analyses on normal control (NC) and HCC participants in the discovery cohort were performed, and PGA2 was identified to be dysregulated in HCC. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for detecting serum PGA2 was established and applied to validate the dysregulation of PGA2 in another independent validation cohort. Receiver operating characteristic (ROC), decision curve analysis (DCA) and some other statistical analyses were performed to evaluate the diagnostic performance of PGA2 for HCC.

RESULTS

At first, PGA2 was found to be dysregulated in HCC in untargeted metabolomic analyses. Then a precise quantitative LC-MS/MS method for PGA2 has been established and has passed rigorous method validation. Targeted PGA2 analyses confirmed that serum PGA2 was decreased in HCC compared to normal-risk NC and high-risk cirrhosis group. Subsequently, PGA2 was identified as a novel biomarker for the diagnosis of HCC, with an area under the ROC curve (AUC) of 0.911 for differentiating HCC from the combined NC + cirrhosis groups. In addition, PGA2 exhibited high performance for differentiating small-size (AUC = 0.924), early-stage (AUC = 0.917) and AFP (-) HCC (AUC = 0.909) from the control groups. The combination of PGA2 and AFP might be useful in the surveillance of risk population for HCC and early diagnosis of HCC.

CONCLUSION

This study establishes that PGA2 might be a novel diagnostic biomarker for HCC.

Development and validation of a biomarker index for HCC treatment response

BACKGROUND

Serum AFP-L3%, AFP, and DCP are useful biomarkers for HCC detection, but their utility in assessing treatment response remains unknown. We aim to evaluate the accuracy of a biomarker model in the detection of posttreatment viable tumors.

METHODS

For model derivation, recipients with HCC undergoing liver transplant from 2018 to 2022 who had biomarkers collected within 3 months before transplant were included. We developed a generalized linear model for detecting posttreatment viable tumors with the 3 biomarkers as covariates, which we termed the "LAD Score." An independent cohort of 117 patients with HCC was used for external validation.

RESULTS

Among 205 recipients of transplant, 70.2% had evidence of viable tumor on explant. The median LAD score was higher among patients with viable versus nonviable tumors (1.06 vs. 0.465, p < 0.001). The LAD score had a sensitivity of 55.6% and a specificity of 85.1% at the cutoff of 0.927, which was more accurate than imaging for detecting posttreatment viable tumors (AUROC 0.736 vs. 0.643, respectively; p = 0.045). The superior performance of the LAD score over imaging is primarily driven by its greater accuracy in detecting tumors <2 cm in diameter (AUROC of the LAD score 0.721 vs. imaging 0.595, p = 0.02). In the validation data set, the LAD score had an AUROC of 0.832 (95% CI: 0.753, 0.911) with a sensitivity of 72.5% and a specificity of 89.4% at the cutoff of 0.927.

CONCLUSIONS

Our findings suggest the utility of LAD score in treatment response assessment after locoregional therapy for HCC, particularly in detecting small tumors. A larger prospective study is in progress to validate its accuracy and evaluate its performance in recurrence monitoring.

Latest insights into the epidemiology, characteristics, and therapeutic strategies of chronic hepatitis B patients in indeterminate phase

As a hepatotropic virus, hepatitis B virus (HBV) can establish a persistent chronic infection in the liver, termed, chronic hepatitis B (CHB), which causes a series of liver-related complications, including fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). HCC with HBV infection has a significantly increased morbidity and mortality, whereas it could be preventable. The current goal of antiviral therapy for HBV infection is to decrease CHB-related morbidity and mortality, and achieve sustained suppression of virus replication, which is known as a functional or immunological cure. The natural history of chronic HBV infection includes four immune phases: the immune-tolerant phase, immune-active phase, inactive phase, and reactivation phase. However, many CHB patients do not fit into any of these defined phases and are regarded as indeterminate. A large proportion of indeterminate patients are only treated with dynamic monitoring rather than recommended antiviral therapy, mainly due to the lack of definite guidelines. However, many of these patients may gradually have significant liver histopathological changes during disease progression. Recent studies have focused on the prevalence, progression, and carcinogenicity of indeterminate CHB, and more attention has been given to the prevention, detection, and treatment for these patients. Herein, we discuss the latest understanding of the epidemiology, clinical characteristics, and therapeutic strategies of indeterminate CHB, to provide avenues for the management of these patients.

Alpha-fetoprotein: Past, present, and future

Alpha-fetoprotein (AFP) is a glycoprotein that plays an important role in immune regulation with critical involvement in early human development and maintaining the immune balance during pregnancy. Postfetal development, the regulatory mechanisms controlling AFP undergo a shift and AFP gene transcription is suppressed. Instead, these enhancers refocus their activity to maintain albumin gene transcription throughout adulthood. During the postnatal period, AFP expression can increase in the setting of hepatocyte injury, regeneration, and malignant transformation. It is the first oncoprotein discovered and is routinely used as part of a screening strategy for HCC. AFP has been shown to be a powerful prognostic biomarker, and multiple HCC prognosis models confirmed the independent prognostic utility of AFP. AFP is also a useful predictive biomarker for monitoring the treatment response of HCC. In addition to its role as a biomarker, AFP plays important roles in immune modulation to promote tumorigenesis and thus has been investigated as a therapeutic target in HCC. In this review article, we aim to provide an overview of AFP, encompassing the discovery, biological role, and utility as an HCC biomarker in combination with other biomarkers and how it impacts clinical practice and future direction.

Biomarker in Hepatocellular Carcinoma

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

Emerging and Clinically Accepted Biomarkers for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death and the sixth most diagnosed malignancy worldwide. Serum alpha-fetoprotein (AFP) is the traditional, ubiquitous biomarker for HCC. However, there has been an increasing call for the use of multiple biomarkers to optimize care for these patients. AFP, AFP-L3, and prothrombin induced by vitamin K absence II (DCP) have described clinical utility for HCC, but unfortunately, they also have well established and significant limitations. Circulating tumor DNA (ctDNA), genomic glycosylation, and even totally non-invasive salivary metabolomics and/or micro-RNAS demonstrate great promise for early detection and long-term surveillance, but still require large-scale prospective validation to definitively validate their clinical validity. This review aims to provide an update on clinically available and emerging biomarkers for HCC, focusing on their respective clinical strengths and weaknesses.

Decoding the glycoproteome: a new frontier for biomarker discovery in cancer

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

Differential Protease Specificity by Collagenase as a Novel Approach to Serum Proteomics That Includes Identification of Extracellular Matrix Proteins without Enrichment

Circulating extracellular matrix (ECM) proteins are serological biomarkers of interest due to their association with pathologies involving disease processes such as fibrosis and cancers. In this study, we investigate the potential for serum biomarker research using differential protease specificity (DPS), leveraging alternate protease specificity as a targeting mechanism to selectively digest circulating ECM protein serum proteins. A proof-of-concept study is presented using serum from patients with cirrhotic liver or hepatocellular carcinoma. The approach uses collagenase DPS for digestion of deglycosylated serum and liquid-chromatography-trapped ion mobility-tandem mass spectrometry (LC-TIMS-MS/MS) to enhance the detection of ECM proteins in serum. It requires no sample enrichment and minimizes the albumin average precursor intensity readout to less than 1.2%. We further demonstrate the capabilities for using the method as a high-throughput matrix-assisted laser/desorption ionization mass spectrometry (MALDI-MS) assay coupled with reference library searching. A goal is to improve the depth and breadth of biofluid proteomics for noninvasive assays.

Ferroptosis in hepatocellular carcinoma, from mechanism to effect

Hepatocellular carcinoma (HCC) is a prevalent malignant tumor worldwide, characterized by high malignancy and rapid progression. Most cases are diagnosed at intermediate to advanced stages. Current treatment methods have limited efficacy, resulting in high recurrence rates and poor prognosis. Radical hepatectomy remains the primary treatment for HCC, complemented by radiotherapy, chemotherapy, targeted therapy, and immunotherapy. Despite significant improvement in patient prognosis with radical hepatectomy, the five-year survival rate post-surgery remains low; thus necessitating exploration of more effective therapeutic approaches. Ferroptosis is a recently discovered form of cell death that can modulate the occurrence and development of HCC through various mechanisms. This article aims to elucidate the mechanism of ferroptosis and its impact on HCC development to provide novel insights for diagnosis and treatment.

Protein kinase C delta enhances the diagnostic performance of hepatocellular carcinoma

BACKGROUND

The conventional markers for hepatocellular carcinoma (HCC), α-fetoprotein (AFP) and des-γ-carboxy prothrombin (DCP), have several limitations; both have low sensitivity in patients with early-stage HCC; low sensitivity for AFP with HCC after eliminating hepatitis C virus (HCV); low specificity for DCP in patients with non-viral HCC, which is increasing worldwide; low specificity for AFP in patients with liver injury; and low specificity for DCP in patients treated with warfarin. To overcome these issues, the identification of novel biomarkers is an unmet need.

OBJECTIVE

This study aimed to assess the usefulness of serum protein kinase C delta (PKCδ) for detecting these HCCs.

METHODS

PKCδ levels were measured using a sandwich enzyme-linked immunosorbent assay in 363 chronic liver disease (CLD) patients with and without HCC.

RESULTS

In both viral and non-viral CLD, PKCδ can detect HCCs with high sensitivity and specificity, particularly in the very early stages. Notably, the value and sensitivity of PKCδ were not modified by HCV elimination status. Liver injury and warfarin administration, which are known to cause false-positive results for conventional markers, did not modify PKCδ levels.

CONCLUSIONS

PKCδ is an enhanced biomarker for the diagnosis of HCC that compensates for the drawbacks of conventional markers.

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

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

Identification and validation of palmitoylation metabolism-related signature for liver hepatocellular carcinoma

BACKGROUND

Protein S-palmitoylation is a reversible posttranslational modification widely involved in tumor progression. Nevertheless, the function of palmitoylation metabolism in prognosis and tumor microenvironment characteristics in liver hepatocellular carcinoma (LIHC) patients is not fully understood.

METHODS

mRNA and clinical data of LIHC patients were obtained from the TCGA and ICGC databases. Consensus clustering was used to construct palmitoylation metabolism-related clusters. Univariate Cox and Lasso regression analyses were employed to establish a palmitoylation metabolism-related signature (PMS). ssGSEA was applied to evaluate the immune cell score in each LIHC sample. Functional enrichments were accessed through GO, KEGG and GSVA. Drug sensitivity data were downloaded from the GDSC database.

RESULTS

Three palmitoylation metabolism-related clusters with different prognostic and immune infiltration characteristics were constructed in LIHC. We identified PMS with distinct survival, clinical, and tumor immune microenvironment characteristics. The high PMS group had a poorer prognosis, higher infiltration of immunosuppressive cells and higher expression of immune checkpoints. ZDHHC20 exerted a tumor-promoting role in LIHC and was significantly associated with immunosuppressive cells and immunosuppressive checkpoints. Additionally, in HepG-2 and SMCC-7721 cells, si-ZDHHC20 boosted apoptosis but decreased proliferation and migration when compared to si-NC.

CONCLUSION

Our research revealed that PMS may accurately predict the prognosis and immune characteristics of LIHC patients. ZDHHC20 has significant clinical and immune relevance in LIHC and may contribute to the formulation of new targets for LIHC immunotherapy.

Systematic review: Glycomics as diagnostic markers for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer with one of the highest cancer-related mortality rates worldwide. Early diagnosis is crucial for improving the therapeutic options and reducing the disease-related mortality.

AIM

To investigate serum N-glycomics as diagnostic markers for HCC.

METHODS

We performed a comprehensive search in PubMed, EMBASE, Web of Science and Scopus through August 17, 2023. Eligible studies assessed the potential use of serum N-glycomics as diagnostic biomarkers for HCC. Study selection, data extraction and quality assessment were performed by two independent reviewers.

RESULTS

Of the 48 articles included, 11 evaluated the utility of N-glycomics for the diagnosis of HCC in whole serum while the remaining articles focused on specific protein glycoforms or protein levels. Of these specific proteins, haptoglobin, alpha-fetoprotein (AFP), kininogen (Kin), α-1-antitrypsin and Golgi protein 73 (GP73) were the most frequently studied. Increased levels of fucosylation and branching presented as the most prevalent post-translational modifications of glycoproteins in patients with HCC compared to controls. Notably, glycomics-based biomarkers may provide a clinical benefit for the diagnosis of early HCC, as several algorithms achieved AUCs between 0.92-0.97. However, these were based on single studies with limited sample sizes and should therefore be validated.

CONCLUSIONS

Alterations in serum N-glycomics, characterised by increased levels of fucosylation and branching, have potential as diagnostic biomarkers for HCC. Optimisation of study design, patient selection and analysing techniques are needed before clinical implementation will be possible.

A meta-analysis and of clinical values of 11 blood biomarkers, such as AFP, DCP, and GP73 for diagnosis of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma lacks ideal diagnostic biomarkers. There is a lack of scientific evaluation of relevant promising biomarkers as well. Therefore this study reanalyzes the related studies of 11 blood biomarkers of HCC, and compares the diagnostic value of these biomarkers for HCC systematically.

METHODS

The relevant literatures on the diagnostic value in HCC of 11 blood indexes in recent 5 years were searched in PubMed, Embase, and Cochrane libraries. Data were extracted and analyzed.

RESULTS

Finally, 83 literature studies were brought into meta-analysis. The pooled sensitivity and specificity of AFP were 0.61 and 0.87, respectively. The AUC of AFP were 0.78. The AUC and sum of sensitivity and specificity of the combination of AFP and other biomarkers were all significantly higher than that of AFP, including AFP + AFP-L3 + DCP, AFP + DCP, AFP/DCP, AFP + GPC3. Among other biomarkers, the AUC and sum of sensitivity and specificity of biomarkers including DCP, GPC3, GP73, Hsp90alpha, midkine, and OPN were significantly higher than that of AFP. In this study, GP73 had the highest sum of sensitivity and specificity (1.78) and AUC (0.95).

CONCLUSIONS

The pooled sensitivity and specificity of AFP were 0.61 and 0.87, respectively. The AUC of AFP were 0.78. The combination of AFP and other biomarkers improved the diagnostic efficiency. The diagnostic value of biomarkers including DCP, GPC3, GP73, Hsp90alpha, midkine, and OPN was higher than that of AFP. GP73 had the best diagnostic value for HCC with the highest sum of sensitivity and specificity (1.78) and AUC (0.95).KEY MESSAGESThe pooled sensitivity and specificity of AFP were 0.61 and 0.87, respectively. The AUC of AFP were 0.78. The combination of AFP and other biomarkers improved the diagnostic efficiency of HCC.The diagnostic value of biomarkers including DCP, GPC3, GP73, Hsp90alpha, midkine, and OPN was higher than that of AFP.GP73 had the best diagnostic value for HCC.

Predictive value of PIVKA-II and AFP for the non-objective response of HBV-associated hepatocellular carcinoma after transarterial chemoembolization: a prospective study

BACKGROUND

To determine the predictive value of serum abnormal prothrombin (PIVKA-II) and alpha-fetoprotein (AFP) for the non-objective response of HBV-associated hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE).

METHODS

This prospective study included HBV-associated HCC patients who underwent TACE at the Fourth People's Hospital of Qinghai Province between December 2021 and July 2022. According to contrast-enhanced ultrasound and upper abdomen contrast-enhanced MRI, the patients were divided into the objective response group and the non-objective response group 3 months after TACE.

RESULTS

There were 54 patients, of whom 31 experienced non-objective responses. The PIVKA-II levels in the objective response group were significantly lower than in the non-objective response group at 1 month [352.00 (142.16-722.54) vs. 528.58(241.32-1681.23) mAU/ml, P = 0.005] and 3 months [28.96 (20.01-42.49) vs. 2082.55 (52.63-10 057.30) mAU/ml, P = 0.016] after TACE. The Spearman rank correlation analysis showed no significant correlation between PIVKA-II and AFP (r = 0.315, P > 0.05). The areas under the curve (AUCs) of AFP and PIVKA-II before TACE were 0.632 and 0.529. One month after TACE, the AUC of PIVKA-II combined with AFP (AUC = 0.787) was higher than for PIVKA-II (AUC = 0.658) and AFP (AUC = 0.749).

CONCLUSION

PIVKA-II does not outperform AFP in predicting non-objective response after TACE in HCC patients. The combination of PIVKA-II and AFP might improve the diagnosis of HCC non-objective response after TACE.

Protein induced by vitamin K absence or antagonist II: Experience to date and future directions

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high mortality. The realization of precision medicine in HCC relies upon efficient biomarkers. Protein induced by vitamin K absence or antagonist II (PIVKA-II) is an immature prothrombin with insufficient coagulation activity, overexpressing in HCC cells. Previous evidence confirmed the role of PIVKA-II in screening and diagnosing HCC. However, the increased PIVKA-II was observed not only in HCC, but also in non-HCC individuals such as vitamin K deficiency. The joint detection of PIVKA-II and other biomarkers could significantly improve diagnostic accuracy in HCC. Furthermore, PIVKA-II serves as a valuable prognostic predictor, transplantation eligibility, resectability, tumor recurrence, therapeutic efficacy, and malignant tumor behaviors. Additionally, PIVKA-II represents a potential target for agent development to establish new therapeutic strategies. Besides HCC, PIVKA-II also serves as a biomarker of vitamin K status. In this review, we assess the role of PIVKA-II in diagnosis, prediction, and treatment. Over the past decades, substantial progress has been achieved in the application of PIVKA-II. Exploration and innovation are required for further advances in the field of PIVKA-II investigation.

Dynamic changes in three biomarkers predict early-stage hepatocellular carcinoma in patients with chronic hepatitis B receiving antiviral therapy

PURPOSE

Patients with chronic hepatitis B (CHB) remain at risk for hepatocellular carcinoma during antiviral therapy. We aimed to clarify the values of alpha-fetoprotein (AFP), lectin-reactive fraction of AFP (AFP-L3), and des-γ-carboxyprothrombin (DCP) for early warning of HCC.

METHODS

A total of 1348 CHB patients received antiviral therapy and follow-up every 26 weeks. Eighty-four patients with HCC were age-, sex-, and cirrhosis-matched with 168 controls. AFP, AFP-L3, and DCP were compared between the groups from 104 weeks before HCC diagnosis (- 104 w) to the time of diagnosis (0 w).

RESULTS

Of the 84 HCC patients, 60 (71.4%) had early-stage HCC, AFP increased from - 26 w, and AFP-L3 and DCP increased from - 78 w. However, levels were unchanged in controls. ΔAFP, ΔAFP-L3, and ΔDCP showed similar abilities for predicting HCC (P > 0.05). Receiver operating characteristic curve analysis showed that AFP had better diagnostic performance for HCC than AFP-L3, DCP, or their combination. The cut-off values of AFP, AFP-L3, and DCP were 5.3 ng/mL, 1.05%, and 31.5 mAU/mL, respectively. Notably, lower AFP values were required to diagnose HCC in patients with detectable HBV DNA (4.1 ng/mL) or elevated alanine aminotransferase (5.2 ng/mL).

CONCLUSIONS

Changes in AFP, AFP-L3, and DCP can help to predict HCC in CHB patients receiving antiviral therapy. A lower AFP value is needed to diagnose HCC, especially in patients with detectable HBV DNA or elevated alanine aminotransferase.

Discovery of a haptoglobin glycopeptides biomarker panel for early diagnosis of hepatocellular carcinoma

Background

There is a need for new serum biomarkers for early detection of hepatocellular carcinoma (HCC). Haptoglobin (Hp) N-glycosylation is altered in HCC, but the diagnostic value of site-specific Hp glycobiomarkers is rarely reported. We aimed to determine the site-specific glycosylation profile of Hp for early-stage HCC diagnosis.

Method

Hp glycosylation was analyzed in the plasma of patients with liver diseases (n=57; controls), early-stage HCC (n=50) and late-stage HCC (n=32). Hp phenotype was determined by immunoblotting. Hp was immunoisolated and digested into peptides. N-glycopeptides were identified and quantified using liquid chromatography-mass spectrometry. Cohort samples were compared using Wilcoxon rank-sum (Mann-Whitney U) tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under curve (AUC).

Results

Significantly higher fucosylation, branching and sialylation of Hp glycans, and expression of high-mannose glycans, was observed as disease progressed from cirrhosis to early- and late-stage HCC. Several glycopeptides demonstrated high values for early diagnosis of HCC, with an AUC of 93% (n=1), >80% (n=3), >75% (n=13) and >70% (n=11), compared with alpha-fetoprotein (AFP; AUC of 79%). The diagnostic performance of the identified biomarkers was only slightly affected by Hp phenotype.

Conclusion

We identified a panel of Hp glycopeptides that are significantly differentially regulated in early- and late-stage HCC. Some glycobiomarkers exceeded the diagnostic value of AFP (the most commonly used biomarker for HCC diagnosis). Our findings provide evidence that glycobiomarkers can be effective in the diagnosis of early HCC - individually, as a panel of glycopeptides or combined with conventional serological biomarkers.

Early Tumor Marker Response Predicts Treatment Outcomes in Patients with Unresectable Hepatocellular Carcinoma Receiving Combined Lenvatinib, Immune Checkpoint Inhibitors, and Transcatheter Arterial Chemoembolization Therapy

Purpose

Few reliable biomarkers for predicting the efficacy of triple therapy (lenvatinib + immune checkpoint inhibitors + transarterial chemoembolization) exist for patients with unresectable hepatocellular carcinoma (uHCC). This study explored the prognostic role of alpha-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP) levels in patients with uHCC receiving triple therapy.

Patients and Methods

This retrospective study included 93 patients with uHCC who received triple therapy at Fujian Provincial Hospital between August 2020 and November 2022. Depending on the respective baseline levels, the patients were divided into high-AFP and high-DCP groups. An early response was defined as an AFP or DCP concentration >50% less than the baseline concentration after 6 weeks of triple therapy. The primary endpoint was the objective response rate (ORR). The secondary endpoints were progression-free survival (PFS) and overall survival (OS).

Results

After 6 weeks of triple therapy, 75.3% (58/77) and 78.9% (60/76) of patients in the high-AFP and high-DCP groups achieved an objective response. Early AFP and DCP responses were positively associated with ORR (high-AFP group: odds ratio [OR]: 13.542; 95% confidence interval [CI]: 3.991-45.950, p<0.001; high-DCP group: OR: 17.853; 95% CI: 4.478-71.179, p<0.001). In the high-AFP group, the 6-month, 12-month, and 18-month PFS and OS rates were higher in the AFP responders than those in the non-responders (PFS: 66.4%, 59.6%, 48.2% vs 42.3%, 19.3%, 0%, p<0.001; OS: 94.5%, 90.4%, 77.3% vs 75.6%, 66.2%, 49.6%, p=0.006). In the high-DCP group, the 6-month, 12-month, and 18-month PFS and OS rates were higher in the DCP responders than those in the non-responders (PFS: 67.4%, 57.7%, 39.0% vs 38.9%, 8.1%, 0%, p<0.001; OS: 94.7%, 94.7%, 83.3% vs 77.0%, 53.9%, 36.0%, p<0.001).

Conclusion

After 6 weeks of triple therapy, an AFP or DCP reduction of >50% predicts better treatment outcomes in uHCC patients.

Longitudinal surveillance of three biomarkers to predict recurrence of hepatocellular carcinoma after radical resection

BACKGROUND

Radical resection is a curative treatment for patients with hepatocellular carcinoma (HCC), but the incidence of recurrence remains high. We aimed to explore the performance of predicting HCC recurrence by longitudinal surveillance of the protein induced by vitamin K absence (PIVKA-II), alpha- fetoprotein (AFP), and lectin-reactive AFP (AFP-L3) during postoperative follow-up.

METHODS

Patients who underwent radical resection for HCC at the Ningbo Medical Centre Lihuili Hospital between January 2015 and December 2020 were included. All enrolled patients regularly monitor PIVKA-II, AFP, AFP-L3 every 3 months during postoperative follow-up. The surveillance performance of PIVKA-II, AFP, AFP-L3 during follow-up for the prediction of HCC recurrence was compared in patients. The generalized estimation equation (GEE) was used to analyze the trends of the tumor biomarkers and interactions with time. Area under the receiver operator characteristic (AUROC) curves, the optimal cut-off value, the sensitivity and specificity were calculated to evaluate the performance of the three biomarkers. The recurrence-free survival (RFS) and overall survival (OS) of patients with any of the elevated biomarkers was analyzed by Kaplan-Meier curves and the log-rank test. Multivariate logistic regression models were used to analyze potential risk factors for recurrence.

RESULTS

The GEE analysis indicated that PIVKA-II, AFP, AFP-L3 in the recurrence patients were higher than the no recurrence patients during follow-up, PIVKA-II and AFP showed increasing trends from 6 months before recurrence. In predicting recurrence, the AUROCs for PIVKA-II, AFP, AFP-L3 and their combination were 0.885, 0.754, 0.781 and 0.885 respectively, the optimal cut-off value for PIVKA-II, AFP, AFP-L3 was 29.5 mAU/ml, 10.7 ng/L, 1.5% respectively. The sensitivity in predicting recurrence for PIVKA-II, AFP, AFP-L3 and combination were 75.0, 54.7, 57.8 and 79.7% respectively. The RFS and the OS of patients with any of the biomarkers elevated during the follow-up was significantly shorter than that without elevated biomarkers ( P  < 0.001). Multivariate analysis showed that any of the biomarkers elevated was the independent risk factor of recurrence.

CONCLUSION

Longitudinal surveillance of PIVKA-II, AFP and AFP-L3 can effectively predict recurrence of HCC after operation.

Egyptian Society of Liver Cancer Recommendation Guidelines for the Management of Hepatocellular Carcinoma

Globally, hepatocellular carcinoma (HCC) is the fourth most common cause of death from cancer. The prevalence of this pathology, which has been on the rise in the last 30 years, has been predicted to continue increasing. HCC is the most common cause of cancer-related morbidity and mortality in Egypt and is also the most common cancer in males. Chronic liver diseases, including chronic hepatitis C, which is a primary health concern in Egypt, are considered major risk factors for HCC. However, HCC surveillance is recommended for patients with chronic hepatitis B virus (HBV) and liver cirrhosis; those above 40 with HBV but without cirrhosis; individuals with hepatitis D co-infection or a family history of HCC; and Nonalcoholic fatty liver disease (NAFLD) patients exhibiting significant fibrosis or cirrhosis. Several international guidelines aid physicians in the management of HCC. However, the availability and cost of diagnostic modalities and treatment options vary from one country to another. Therefore, the current guidelines aim to standardize the management of HCC in Egypt. The recommendations presented in this report represent the current management strategy at HCC treatment centers in Egypt. Recommendations were developed by an expert panel consisting of hepatologists, oncologists, gastroenterologists, surgeons, pathologists, and radiologists working under the umbrella of the Egyptian Society of Liver Cancer. The recommendations, which are based on the currently available local diagnostic aids and treatments in the country, include recommendations for future prospects.

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

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

Advances in the Early Detection of Hepatobiliary Cancers

Hepatocellular cancer (HCC) and biliary tract cancers (BTCs) have poor survival rates and a low likelihood of a cure, especially in advanced-stage disease. Early diagnosis is crucial and can significantly improve survival rates through curative treatment approaches. Current guidelines recommend abdominal ultrasonography (USG) and alpha-fetoprotein (AFP) monitoring for HCC screening in high-risk groups, and abdominal USG, magnetic resonance imaging (MRI), and magnetic resonance cholangiopancreatography (MRCP) monitoring for biliary tract cancer. However, despite this screening strategy, many high-risk individuals still develop advanced-stage HCC and BTC. Blood-based biomarkers are being developed for use in HCC or BTC high-risk groups. Studies on AFP, AFP-L3, des-gamma-carboxy prothrombin, glypican-3 (GPC3), osteopontin (OPN), midkine (MK), neopterin, squamous cell carcinoma antigen (SCCA), Mac-2-binding protein (M2BP), cyclic guanosine monophosphate (cGMP), and interleukin-6 biomarkers for HCC screening have shown promising results when evaluated individually or in combination. In the case of BTCs, the potential applications of circulating tumor DNA, circulating microRNA, and circulating tumor cells in diagnosis are also promising. These biomarkers have shown potential in detecting BTCs in early stages, which can significantly improve patient outcomes. Additionally, these biomarkers hold promise for monitoring disease progression and evaluating response to therapy in BTC patients. However, further research is necessary to fully understand the clinical utility of these biomarkers in the diagnosis and management of HCC and BTCs.

Promising Novel Biomarkers for Hepatocellular Carcinoma: Diagnostic and Prognostic Insights

The systemic therapy landscape for hepatocellular carcinoma is rapidly evolving, as the recent approvals of checkpoint inhibitor-based regimens such as atezolizumab-bevacizumab and durvalumab-tremelimumab in advanced disease have led to an expanding therapeutic armamentarium. The development of biomarkers, however, has not kept up with the approvals of new agents. Nevertheless, biomarker research for hepatocellular carcinoma has recently been growing at a rapid pace. The most active areas of research are biomarkers for early detection and screening, accurate prognostication, and detection of minimal residual disease following curative intent therapies, and, perhaps most importantly, predictive markers to guide selection and sequencing of the individual agents, including tyrosine kinase inhibitors and immunotherapy. In this review, we briefly summarize the recent developments in systemic therapeutics for hepatocellular carcinoma, introduce the key completed and ongoing prospective and retrospective studies evaluating diagnostic, prognostic, and predictive biomarkers with high clinical relevance, highlight several potentially important areas of future research, and share our insights for each biomarker.