This was a narrative review of select studies published through September of 2024. We review the shift toward multi-dimensional scores such as HCC early detection screening (HES), GALAD, ASAP, and mt-HBT represents a significant advancement in biomarker research for hepatocellular carcinoma (HCC) detection. Unlike single biomarker approaches, these scores integrate various clinical and biochemical factors to enhance predictive accuracy by reflecting different complementary aspects of disease progression and HCC oncogenesis. Proper testing and validation of biomarker scores in phase 3 biomarker studies is essential before wide use can be recommended. We also review the comparative performance of biomarker scores in phase 3 studies. The new version of HES (HES V2.0) which includes AFP, AFP L3, DCP, and changes in their levels the past one year, if available, in addition to age, platelets, albumin, ALT and underlying liver disease etiology outperforms GALAD in detecting early-stage HCC with overall 6.7% higher sensitivity, and ASAP with 13.4%-18.0% higher sensitivity, both at fixed 90% specificity. HES V2.0 is a leading candidate biomarker score for prospective testing in clinical studies of early HCC detection.

Selectively and sensitively detecting specific exosomal markers is critical for early diagnosis of liver cancer. However, identifying specific exosomal biomarkers and establishing accurate, convenient detection methods remain challenging. In this study, we used bioinformatics to identify the higher levels of EpCAM and GPC-3 proteins on liver cancer exosomes. These markers were used to create a dual-antibody functionalized transistor biosensor for precise detection of liver cancer exosomes. The techniques exhibited outstanding specificity and sensitivity. Detection thresholds in PBS and simulated plasma were established at 20 particles/μL and 47 particles/μL, respectively, facilitating the distinction of liver cancer cell-derived exosomes from those originating from various other cancer cells. Furthermore, in clinical samples testing, this approach not only distinguished clinical samples among liver cancer patients and healthy individuals, but also demonstrated the ability to differentiate liver cancer from other types of tumors, achieving a precision and accuracy rate of 100 %. The developed biosensor demonstrates excellent potential for clinical application and this work offers a promising and effective approach for cancer diagnosis.

Early diagnosis of hepatocellular carcinoma (HCC) is crucial for improving patient survival and treatment outcomes and the early detection of biomarkers for HCC is key to achieving this goal. However, conventional detection methods often lack sufficient specificity and sensitivity. In recent years, CRISPR/Cas12a-based biosensing has gained significant attention due to its ease of use and high sensitivity, demonstrating its potential to address the limitations of conventional detection methods. This paper primarily reviews the research progress of CRISPR/Cas12a-based biosensors for HCC detection, introducing their fluorescence, electrochemical, colorimetric, and other detection principles, as well as practical applications in detail. Additionally, the differences in sensitivity, specificity, and detection speed among different types of CRISPR/Cas12a biosensors are comparatively analyzed. Finally, the potential future directions for the development and application of CRISPR/Cas12a technology in clinical settings are explored.

The current review analyzes progress in electrochemical detection techniques for hepatocellular carcinoma biosignatures, highlighting their potential to enhance the timely detection and management of hepatocellular carcinoma. In this study, the authors explore the present state of hepatocellular carcinoma biosignatures, encompassing conventional proteins such as alpha-fetoprotein and promising biosignatures like non-coding RNAs and circulatory tumor DNA (ctDNA). This text analyzes the principles of electrochemical biosensing and explores sophisticated sensor designs employing surface modification techniques, innovative recognition elements, and nanomaterials. Particular focus is directed towards aptamer-based sensors, microfluidic technologies, and label-free methodologies. Herein, recent advancements in enhancing sensitivity and specificity are discussed, with some platforms reaching a threshold at the femtogram scale. The discussion also encompasses the progress achieved in point-of-care applications and the obstacles faced in transitioning experimental paradigms to medical applications. The prospective influence of these methodologies on medical results is under evaluation, emphasizing early detection and tailored treatment approaches. Future research should focus on creating advanced, integrated detection systems and conducting comprehensive clinical validation studies to assess the real-world effectiveness of electrochemical biosensors.

Cancer remains a major global public health concern, with considerable interest in exploring biological molecules for cancer treatment and prevention. Growth inhibitory peptide (GIP), a promising new class of biological therapeutics, has drawn attention for its distinct anti-tumor properties. Derived from human alpha-fetoprotein (HAFP), this synthetic 34-amino-acid peptide has demonstrated substantial anti-tumor effects across various cancer cell lines, effectively inhibiting tumor cell proliferation, migration, and metastasis. Studies reveal that GIP mediates its effects through a range of mechanisms, including interactions with G protein-coupled receptors (GPCRs), anti-cell adhesion activities, inhibition of cell spreading and metastatic processes, morphological alterations, platelet aggregation inhibition, immune enhancement, cell membrane disruption, ion channel blockade, and cell cycle arrest. While GIP has exhibited promising anti-tumor activity in both in vitro and in vivo models, further investigation is essential to advance its development as a therapeutic drug, particularly regarding pharmacokinetics, safety profiles, storage stability, and clinical efficacy.

Signal changes after high dose irradiation on MRI make it difficult to assess the therapeutic response of hepatocellular carcinoma (HCC). To overcome the limitation of imaging work-up, our study predicted clinical outcomes through tumor marker dynamics in HCC after external beam radiotherapy (EBRT). As a single-center retrospective study, those who underwent conventional fractionated EBRT for viable HCC from 2010 to 2021 were analyzed. Patients with elevated tumor markers of AFP ≥ 10 ng/ml or PIVKA-II ≥ 30 mAU/ml before EBRT were enrolled. Remission of AFP, PIVKA-II, and MoRAL score (=11*√PIVKA-II + 2*√AFP) from pre-EBRT to post-EBRT at 1 month and 3 months was examined. For 1-year and 2-years OS, variables of tumor markers were examined using the receiver operation characteristics (ROC). Multivariate analyses of Cox-regression for OS were conducted. Among 111 patients, 34 patients were estimated to survive more than 2-years. In multivariate analyses for OS, tumor number (P = 0.004), portal vein tumor thrombus (P = 0.004), and Barcelona liver cancer staging (P < 0.001) were found to be significant. For 2-years OS, the degree of AFP remission at 3 months (rAFP_3M) had an AUC of 0.852 (95% CI: 0.758-0.946, P < 0.001), a sensitivity of 85.5%, and a specificity of 82.6% with a cut-off value of 3.7%. MoRAL score at 3 months (MoRAL_3M) had an AUC of 0.814 (95% CI: 0.728-0.900, P = 0.000), a sensitivity of 76.5%, and a specificity of 77.8% with a cut-off value of 111.64. In new multivariate analyses including the above significant factors plus either rAFP_3M or MoRAL_3M, rAFP_3M (P < 0.001) and MoRAL_3M (P < 0.001) were found to be independent prognostic factors in each model. This study confirmed the importance of the changed tumor marker after EBRT rather than the baseline value. Dynamic change of AFP and MoRAL score at post-EBRT 3 months could be recommended as potential indicators for clinical outcomes.

Hepatocellular carcinoma (HCC) is a common malignancy associated with high morbidity and mortality rates worldwide. To improve the prognosis of HCC, early diagnosis is crucial. However, to date, little is known about the role of natural killer cell-related genes (NKCRGs) in predicting the prognosis of hepatocellular carcinoma patients. In this study, we identified 24 differentially expressed NKCRGs in HCC specimens from the TCGA dataset, including 22 upregulated genes and 2 downregulated genes. Functional enrichment analysis revealed that these genes were mainly involved in immune response pathways and various cancer-related pathways. Univariate analysis identified 21 prognostic NKCRGs, with eight genes (PAK1, MAP2K2, MAPK3, PLCG1, SHC1, HRAS, NRAS, and MICB) confirmed to be involved in HCC prognosis through Venn diagram analysis. A prognostic model was developed using LASSO-Cox regression, incorporating four genes (MAP2K2, SHC1, HRAS, and NRAS). The model's risk score was significantly associated with overall survival (OS) in both the TCGA and ICGC cohorts. Patients with high-risk scores had poorer OS, as demonstrated by Kaplan-Meier curves and ROC analyses. The risk score was not significantly correlated with gender or age but was higher in patients with advanced tumor grades and stages. Immune status analysis using ssGSEA showed higher enrichment scores for various immune cells and pathways in the high-risk group. Additionally, the risk score was positively correlated with the immune score, indicating its potential role in tumor microenvironment modulation. Expression analysis revealed that HRAS, SHC1, MAP2K2, and NRAS were upregulated in HCC tissues, with higher expressions of HRAS, MAP2K2, and NRAS associated with shorter OS. Knockdown experiments confirmed that silencing NRAS suppressed the proliferation of HCC cells, highlighting its potential as a therapeutic target. Overall, our findings suggest that the identified NKCRGs, particularly NRAS, play crucial roles in HCC progression and could serve as valuable prognostic markers and therapeutic targets.

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.

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.

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%).

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.

This retrospective multicenter study is aimed at evaluating the diagnostic accuracy and influence factors of serum des-gamma-carboxy prothrombin (DCP) as a diagnostic biomarker of hepatocellular carcinoma (HCC).

Clinical data were collected from 4555 subjects with DCP tests, composed of primary liver cancer (PLC), metastatic liver cancer (MLC), chronic hepatitis (CH), liver cirrhosis (LC), benign liver diseases (BLD), biliary tract diseases (BTD), non-liver cancers (NLC), and non-liver benign diseases (NLBD). The clinical data collected included medical history, treatment records, various serum tests, and imaging examination.

Serum DCP was measured with Abbott agents in each center. In HCC, serum DCP concentration was at 9086.00 ± 366.10 mAU/mL, higher than that in other diseases (p < 0.05). At 40.00 mAU/mL recommended by instruction, positive rates of serum DCP were at 85.11% in HCC, 30.12% in intrahepatic cholangiocellular carcinoma (ICC), 31.65% in MLC, 13.95% in BLD, 18.14% in CH, 27.87% in LC, 15.75% in BTD, 35.29% in NLC, and 20.00% in NLBD. In this study, the diagnostic specificity of serum DCP in HCC was affected by liver function. In HCC, serum AFP concentrations also increased compared to non-HCC diseases (p < 0.05), but specificity varied with agents from different providers. Serum DCP decreased after the surgical removal of HCC, but remained elusive in systemic treatment.

Serum DCP may serve as an optimal biomarker for the diagnosis of HCC, but its accuracy appears influenced by liver function; attention needs to be paid to the liver function of patients for false positivity.

Although liquid biopsy has garnered increasing attention in recent years for diagnosing hepatocellular carcinoma (HCC), serum biomarkers continue to hold significant value for HCC diagnosis due to their simple operation, cost-effectiveness, and high efficiency. This study aimed to screen for the optimal diagnostic combinations of alpha fetoprotein (AFP), a protein induced by vitamin K deficiency or antagonist II (PIVKA-II), golgi glycoprotein 73 (GP73), and routine clinical indicators for diagnosing hepatitis B-associated HCC (HBV-HCC). A retrospective analysis was conducted on 358 HBV-HCC patients treated at Taizhou People's Hospital from August 2015 to October 2021; 124 patients with chronic hepatitis B (CHB) and 241 patients with hepatitis B cirrhosis composed the control group. With liver pathology as the gold standard, the concordance between the screened indicators and liver pathology for HCC diagnosis was analyzed by Cohen's kappa coefficient. In the CHB group, AFP, PIVKA-II, and GP73 were statistical significance, and the triple biomarker combination achieved the highest AUC (0.908) for HCC diagnosis, surpassing the efficacy of both individual indicators and two biomarker combinations. In both the Child‒Pugh A and Child‒Pugh B&C cirrhosis groups, AFP and PIVKA-II were significantly different between patients with and without HCC, and the AUC values of AFP combined with PIVKA-II for HCC diagnosis were 0.969 and 0.956, respectively. Using liver pathology as the gold standard, the Kappa values of the above combinations in the three groups were 0.866, 0.780, and 0.800, respectively. The triple combination of AFP, PIVKA-II, and GP73 in the CHB group and the combination of AFP and PIVKA-II in both the Child‒Pugh A and Child‒Pugh B&C cirrhosis groups had excellent diagnostic accuracy for HCC, consistent with liver pathology, and were superior to the diagnostic ability of individual biomarkers.

Hepatocellular carcinoma (HCC) is the third major cause of cancer death worldwide, with more than a doubling of incidence over the past two decades in the United States. Yet, the survival rate remains less than 20%, often due to late diagnosis at advanced stages. Current HCC screening approaches are serum alpha-fetoprotein (AFP) testing and ultrasound (US) of cirrhotic patients. However, these remain suboptimal, particularly in the setting of underlying obesity and metabolic dysfunction-associated steatotic liver disease/steatohepatitis (MASLD/MASH), which are also rising in incidence. Therefore, there is an urgent need for novel biomarkers that can stratify risk and predict early diagnosis of HCC, which is curable. Advances in liver cancer biology, multi-omics technologies, artificial intelligence, and precision algorithms have facilitated the development of promising candidates, with several emerging from completed phase 2 and 3 clinical trials. This review highlights the performance of these novel biomarkers and algorithms from a mechanistic perspective and provides new insight into how pathological processes can be detected through blood-based biomarkers. Through human studies compiled with animal models and mechanistic insight in pathways such as the TGF-β pathway, the biological progression from chronic liver disease to cirrhosis and HCC can be delineated. This integrated approach with new biomarkers merit further validation to refine HCC screening and improve early detection and risk stratification.

Metastasis remains a major cause of morbidity and mortality in patients with malignant tumors. The pre-metastatic niche is a prerequisite for distant metastasis driven by primary tumors. Circular RNAs (circRNAs), a class of single-stranded closed non-coding RNAs, exhibit high stability, evolutionary conservation, and cell-type specificity. Exosomes, as natural carriers of circRNAs, mediate intercellular communication and contribute to the formation of the pre-metastatic niche; however, the mechanisms by which they do so remain incompletely understood. This review summarizes the biological characteristics and functions of exosomal circRNAs and outlines the molecular pathways through which they shape the tumor pre-metastatic microenvironment, with emphasis on immunosuppression, vascular permeability, extracellular matrix remodeling, and lymphangiogenesis. This is the first review to focus on the functional roles and molecular mechanisms of exosomal circRNAs in pre-metastatic niche regulation, providing a basis for the development of therapeutic strategies targeting metastatic progression.

Exosomes, nanoscale extracellular vesicles secreted by diverse cell types, have emerged as promising biomarkers for non-invasive tumor diagnostics, offering significant advantages over traditional methods. These vesicles, typically ranging from 30 to 150 nanometers in size, carry a diverse cargo of proteins, lipids, RNA, and microRNAs, which reflect the molecular alterations occurring within their parent cells. Notably, exosomes can be isolated from easily accessible biofluids such as blood, urine, and saliva, making them ideal candidates for liquid biopsy applications. This review explores the transformative potential of exosome-based biomarkers in the early detection and monitoring of cancers across diverse organ systems, including respiratory, digestive, hematological, neurological, endocrine malignancies and so on. Special emphasis is placed on their application in clinical trials, where exosome-based diagnostics have demonstrated promising results in detecting tumors at early stages and monitoring treatment responses, offering a less invasive and more accessible alternative to traditional biopsies. While recent advancements in exosome isolation and characterization technologies have significantly improved the sensitivity and specificity of these diagnostics, challenges such as biological heterogeneity, lack of standardization, and regulatory hurdles remain. Nevertheless, exosome-based diagnostics hold the promise of providing real-time, dynamic insights into tumor progression, enhancing personalized medicine. The integration of exosomes into clinical practice could revolutionize cancer diagnostics and therapy, improving patient outcomes. Further research and large-scale clinical validation are essential to fully realize the clinical potential of exosome-based biomarker applications in routine clinical settings.

Hepatocellular carcinoma (HCC) remains one of the most prevalent and deadliest cancers. With the approval of multiple first- and second-line agents, especially the combination therapies based on immune checkpoint inhibitor (ICI) regimens, the landscape of systemic therapy for advanced HCC (aHCC) is more diverse than ever before. The efficacy of current systemic therapies shows great heterogeneity in patients with aHCC, thereby identifying biomarkers for response prediction and patient stratification has become an urgent need. The main biomarkers for systemic therapy in hepatocellular carcinoma are derived from peripheral blood, tissues, and imaging. Currently, the understanding of the clinical response to systemic therapy indicates unequivocally that a single biomarker cannot be used to identify patients who are likely to benefit from these treatments. In this review, we provide an integrated landscape of the recent development in molecular targeted therapies and ICIs-based therapies, especially focusing on the role of clinically applicable predictive biomarkers. Additionally, we further highlight the latest advancements in biomarker-driven therapies, including targeted treatments, adoptive cell therapies, and bispecific antibodies.

Identifying alpha-fetal protein (AFP)-negative focal hepatic lesions presents a significant challenge, particularly in China. We sought to develop an economically portable tool for the diagnosis of benign and malignant liver lesions with AFP-negative status, and explore its clinical diagnostic efficiency.

A retrospective study was conducted at Peking University Shenzhen Hospital from January 2017 to February 2023, including a total of 348 inpatients with AFP-negative liver space-occupying lesions. The study used a training set of 252 inpatients from January 2017 to September 2021 to establish a diagnostic model for differentiating benign and malignant AFP-negative liver space-occupying lesions. Additionally, a validation cohort of 96 inpatients from October 2021 to February 2023 was used to confirm the diagnostic performance of the model. From January 2017 to February 2023, patients at JingNing People's Hospital, Gansu Province were assigned to the external cohort (n = 78).

A predictive tool was established by screening age, gender, hepatitis B virus (HBV)/hepatitis C virus (HCV) infected, single lesion, alanine amino transferase (ALT), and lymphocyte-to-monocyte ratio (LMR) using multivariate logistic regression analysis and clinical practice. The area under the curve (AUC) of the model was 0.911 (95% CI [0.873-0.949]) in the training set and 0.882 (95% CI [0.815-0.949]) in the validation cohort. In addition, the model achieved an area under the curve of 0.811 (95% CI [0.687-0.935]) in the external validation cohort.

Our results demonstrated that the predictive tool has the characteristics of good diagnostic efficiency, economy and convenience, which is helpful for the clinical triage and decision-making of AFP-negative liver space-occupying lesions.

To evaluate the effect of combining regorafenib with immunotherapy, and further adding transarterial chemoembolization (TACE), on the survival rates of patients suffering from advanced hepatocellular carcinoma (HCC).

A retrospective cohort study was conducted on clinical data from 219 patients with advanced HCC treated from January 2019 to December 2020 at Zhangzhou Affiliated Hospital of Fujian Medical University. Patients were divided into two groups: regorafenib combined with immunotherapy (Group A; n = 106) and regorafenib combined with immunotherapy plus TACE (Group B; n = 113). Assessment included baseline characteristics, serum indicators, treatment response, adverse events, progression-free survival (PFS), quality of life and overall survival (OS).

Six months after treatment, Group B demonstrated a significant decrease in α-fetoprotein (AFP) levels (P < 0.001), Alanine aminotransferase (ALT) levels (P < 0.001), and aspartate Aminotransferase (AST) levels (P < 0.001), along with a significant increase in albumin (ALB) levels (P = 0.010) compared to Group A. The addition of TACE resulted in higher partial response rates (PR) (P = 0.044), disease control rates (DCR) (P = 0.005), overall response rates (ORR) (P = 0.014), improved 1- and 2-year survival rates (P = 0.019, 0.025), and 6-month PFS rates (P = 0.003). However, this combination therapy was related to a higher incidence of grade 3-4 adverse events.

Regorafenib combined with immunotherapy plus TACE may lead to improved short-term survival outcomes in advanced HCC patients, albeit with an increased risk of adverse events as well as possible effects on quality of life. These findings emphasize the complexity of treatment decisions in advanced HCC.

Hepatocellular carcinoma (HCC) remains a deadly cancer in the UK despite advancements in curative therapies. Societal conditions and health inequalities influence the development of chronic liver disease and outcomes from complications including HCC. Scoping this emergent evidence-base is required to inform research and solutions for the NHS.

A PRISMA scoping review was performed up to September 2023. Articles exploring health inequalities in HCC involving the UK population were included.

This review has characterised axes of health inequality and their impact across the HCC care continuum in the UK. Studies predominantly employed a cohort design or population-based analyses, with meta-analyses of surveillance utilisation including only a single UK study. These methodologies provided an appropriate lens to understand longitudinal trends and identify disadvantaged groups. However, important evidence gaps remain, including exploration of patient perspectives, intersectional analyses, and statistical measures of socioeconomic inequity in HCC.

HCC is a rapidly growing cause of cancer mortality and disproportionally affects underserved groups, presenting a major public health concern. Further research is required to innovate and evaluate surveillance and management pathways to reduce systemic inequities. Direction is needed at the national level to improve prevention, early diagnosis and access to curative treatment.

For many cancers, biomarkers have served as an important tool across the cancer care continuum from risk stratification and early detection to diagnosis and treatment. Alpha-fetoprotein (AFP) remains one of the few validated biomarkers for patients with HCC. Although AFP has shown potential for each of these steps, its performance, when used alone, has often been suboptimal. There continue to be discordant recommendations about AFP's value when combined with ultrasound for surveillance, as well as its role in diagnostic algorithms. Conversely, high AFP levels are associated with aggressive tumor biology and survival, so it remains a key factor for the selection of candidates for liver transplant. There have been immense efforts to identify and validate additional biomarkers for each of these steps in the HCC care continuum. Indeed, biomarker panels have shown promising data for HCC risk stratification and surveillance among patients with cirrhosis, as well as prognostication and detection of minimal residual disease in patients undergoing HCC treatment. Several large prospective studies are currently ongoing to evaluate the role of these emerging biomarkers in clinical practice.

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.

To investigate how effectively clinical features and CT-based radiomic features predict the pathological grade of hepatocellular carcinoma (HCC).

We retrospectively analyzed 108 patients diagnosed with hepatocellular carcinoma who underwent pathological examination between May 2020 and May 2024 at the Second Hospital of Jilin University. All patients underwent laboratory tests and contrast-enhanced computed tomography (CECT) scanning of the liver within one month prior to pathological examination. First, we analyzed laboratory tests, such as alpha fetoprotein (AFP) and des-γ-carboxy prothrombin (PIVKA-II), to identify risk factors associated with the pathological grading of HCC. Then, we built and evaluated the performance of the clinical model. Next, we imported the arterial-phase and venous-phase images of the CECT images into the uAI Research Portal research platform for 'one-stop' processing, which included semiautomatic ROI outlining, feature extraction, dimensionality reduction, model construction and evaluation. To evaluate the model's diagnostic effectiveness, receiver operating characteristic (ROC) curves were produced, and the related accuracy, sensitivity, specificity, and area under the curve (AUC) were computed. The models were compared using the Delong test, and the clinical value of the predictive model was assessed via the use of calibration curves and decision curve analysis (DCA) to quantify the agreement between the model and the actual outcomes.

Poorly differentiated hepatocellular carcinoma (pHCC) is associated with risk variables such as hepatitis C virus antibodies(HCVAb), PIVKA-II, and sex. In the training and validation cohorts, the AUC values of the clinical model were 0.719 and 0.692, respectively; those of the AP model were 0.843 and 0.773; those of the VP model were 0.806 and 0.804; those of the AP + VP model were 0.953 and 0.844; and those of the AP + VP + clinical model were 0.926 (95% CI: 0.88-0.995) and 0.863 (95% CI: 0.711-1). The DCA curves revealed that the overall net benefit of the AP + VP + clinical model was greater than that of the other models and that it had the best diagnostic results.

CT-based radiomic modeling combined with clinical features (sex) and laboratory tests (e.g., AFP and PIVKA-II) can reliably predict the pathological grade of HCC patients prior to surgery.

The original hepatocellular carcinoma early detection screening (HES) score, which combines alpha-fetoprotein (AFP) with age, alanine aminotransferase, and platelets, has better performance than AFP alone for early HCC detection. We have developed HES V2.0 by adding AFP-L3 and des-gamma-carboxy prothrombin to the score and compared its performance to GALAD and ASAP scores among patients with cirrhosis.

We conducted a prospective-specimen collection, retrospective-blinded-evaluation phase 3 biomarker cohort study in patients with cirrhosis enrolled in imaging and AFP surveillance. True-positive rate (TPR)/sensitivity and false-positive rate for any or early HCC were calculated for GALAD, ASAP, and HES V2.0 scores within 6, 12, and 24 months of HCC diagnosis. We calculated the AUROC curve and estimated TPR based on an optimal threshold at a fixed false-positive rate of 10%. We analyzed 2331 patients, of whom 125 developed HCC (71% in the early stages). For any HCC, HES V2.0 had higher TPR than GALAD overall (+7.2%), at 6 months (+3.6%), at 12 months (+7.2%), and 24 months (+13.0%) before HCC diagnosis. HES V2.0 had higher TPR than ASAP for all time points (+5.9% to +12.0%). For early HCC, HES V2.0 had higher sensitivity/TPR than GALAD overall (+6.7%), at 12 months (+6.3%), and 24 months (+14.6%) but not at 6 months (+0.0%) and higher than ASAP for all time points (+13.4% to +18.0%).

In a prospective cohort study, HES V2.0 had a significantly higher performance for identifying new HCC, including early stage, than GALAD or ASAP.

Promoting the early detection and diagnosis of hepatocellular carcinoma (HCC) is a critical strategy to improve patient outcomes as this can lead to greater access to curative treatments. This review highlights the diagnostic tests for HCC, including the use of the Liver Imaging Reporting and Data System systems and histopathology. Staging is essential for informing prognosis and guiding treatment decisions; this review also covers a widely used and well-validated staging system called the Barcelona-Clinic Liver Cancer (BCLC) algorithm. The BCLC incorporates tumor status, liver function, and patient performance to stage patients with newly diagnosed HCC.

Hepatocellular carcinoma (HCC) is a major global burden, ranking as the third leading cause of cancer-related mortality. HCC due to chronic hepatitis B virus (HBV) or C virus (HCV) infection has decreased due to universal vaccination for HBV and effective antiviral therapy for both HBV and HCV, but HCC related to metabolic dysfunction-associated steatotic liver disease and alcohol-associated liver disease is increasing. Biannual liver ultrasonography and serum α-fetoprotein are the primary surveillance tools for early HCC detection among high-risk patients (e.g., cirrhosis, chronic HBV). Alternative surveillance tools such as blood-based biomarker panels and abbreviated magnetic resonance imaging (MRI) are being investigated. Multiphasic computed tomography or MRI is the standard for HCC diagnosis, but histological confirmation should be considered, especially when inconclusive findings are seen on cross-sectional imaging. Staging and treatment decisions are complex and should be made in multidisciplinary settings, incorporating multiple factors including tumor burden, degree of liver dysfunction, patient performance status, available expertise, and patient preferences. Early-stage HCC is best treated with curative options such as resection, ablation, or transplantation. For intermediate-stage disease, locoregional therapies are primarily recommended although systemic therapies may be preferred for patients with large intrahepatic tumor burden. In advanced-stage disease, immune checkpoint inhibitor-based therapy is the preferred treatment regimen. In this review article, we discuss the recent global epidemiology, risk factors, and HCC care continuum encompassing surveillance, diagnosis, staging, and treatments.

We compared the clinical performance of the novel GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], des-gamma carboxyprothrombin [DCP]) and GALAD (gender [biological sex], age, AFP, Lens culinaris agglutinin-reactive AFP [AFP-L3], DCP) algorithms to deduce the clinical utility of AFP-L3 for detecting early-stage hepatocellular carcinoma (HCC) from chronic liver disease (CLD).

An algorithm development study (STOP-HCC-ARP) and clinical validation study (STOP-HCC-MCE) were conducted, recruiting adult participants with HCC (confirmed by radiology or pathology) or CLD in an international, multicenter, case-control design. Serum biomarkers were measured using Elecsys assays (GAAD and GALAD [Cobas]) or μTASWAKO assays (GALAD [μTASWAKO]) while blinded to case/control status.

In STOP-HCC-ARP (algorithm development cohort), 1,006 patients {297 HCC (41.4% early-stage [Barcelona Clinic Liver Cancer {BCLC} 0/A) and 709 CLD} were included. Area under the curve (AUCs) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.4%, and 90.8% for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO), respectively. The clinical validation cohort of STOP-HCC-MCE comprised 1,142 patients, (366 HCC cases [48% early-stage], 468 specificity samples and 302 CLD); AUCs for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.5%, and 91.0%, respectively; AUCs were 94.7-95.0% for all-stage HCC. The GAAD and GALAD algorithms demonstrated similar good performance regardless of disease etiology, presence of cirrhosis, geographical region, and within pan-tumor specificity panels (p <0.001).

GAAD (Cobas) demonstrated good clinical performance, similar to GALAD (Cobas and μTASWAKO) algorithms, in differentiating HCC and CLD controls, across all disease stages, etiologies, and regions; therefore, AFP-L3 may have a negligible role in GALAD for HCC surveillance.

To improve the detection of early-stage hepatocellular carcinoma (HCC) from benign chronic liver disease (CLD), algorithms combining demographic characteristics and serum biomarkers, such as GAAD and GALAD, have been developed. GAAD combines gender (biological sex), age, alpha-fetoprotein (AFP), des-gamma carboxy-prothrombin (DCP); GALAD combines the same characteristics and biomarkers as GAAD with the addition of Lens culinaris agglutinin-reactive AFP (AFP-L3). Changing disease etiologies and treatment paradigms have raised questions regarding the utility of AFP-L3 in HCC surveillance. Our work demonstrates that the GAAD (Cobas) algorithm demonstrated good clinical performance and was as sensitive and specific as the GALAD (Cobas) and GALAD (μTASWAKO) algorithms in differentiating HCC and CLD controls, across all disease stages, etiologies, and geographical regions; therefore, AFP-L3 may have a negligible role in HCC detection. Our study provides supporting evidence that in participants with CLD undergoing guideline-directed HCC surveillance, the GAAD (Cobas) algorithm may be used as an effective method for the detection of HCC, potentially resulting in improved patient outcomes.

The early detection of Hepatocellular Carcinoma (HCC) is crucial for improving patient survival rates.Early diagnosis of HCC can significantly enhance treatment outcomes and reduce disease progression. Antigen detection of tumor markers is one of the important diagnostic methods for HCC. However, Traditional antigen detection methods often rely on heavy detection equipment, involve lengthy turnaround times, and must be conducted in laboratory settings. Therefore, there is a clear need for a portable, low-skill, rapid sample-to-result detection method for early HCC biomarkers.

We propose a new platform based on electrowetting-on-dielectric digital microfluidic(EWOD-DMF) for the detection of early-stage HCC biomarkers, enabling the quantitative measurement of Alpha-Fetoprotein (AFP), the proportion of AFP-L3 in total AFP (AFP-L3%), and Des-Gamma-Carboxy Prothrombin (DCP). First, serum samples are processed through the microfluidic system, achieving the separation of AFP-L3 within 10 min. Next, immunoassays are performed within 15 min, using magnetic particles to capture biomarkers such as AFP, AFP-L3, and DCP, followed by enzymatic reactions that generate detectable signals. Each chip can simultaneously detect three biomarkers from five different samples, allowing for a total of fifteen targets to be tested, with only approximately 2.4 μL of serum required for each biomarker detection. Ultimately, data are analyzed with dedicated software to quantitatively measure the HCC biomarkers. The detection limits for AFP or AFP-L3 and for DCP are 0.24 ng/mL and 1.89 ng/mL, respectively.

This study presents a EWOD-DMF platform for early-stage HCC diagnosis, capable of simultaneously detecting multiple samples and biomarkers, thus improving detection efficiency and diagnostic accuracy. Moreover, the platform has POCT capability, with advantages in portability and cost-effectiveness, providing clinicians and primary healthcare institutions with a fast and convenient solution for early-stage HCC diagnosis.

Primary hepatic carcinosarcoma (HCS) is an extremely rare malignant tumor with carcinomatous and sarcomatous elements. Few reported cases of HCS exist, especially with sufficient records to describe imaging and pathological features, making the diagnosis, treatment, and prognosis of HCS a significant challenge for physicians. Here, we report a case of HCS with spontaneous rupture as the initial symptom in a 77-year-old elderly male who was admitted with right upper abdominal pain for 8 days. The computed tomography enhancement scan revealed one intrahepatic enhancement with mixed density and a massive, enhanced shadow located mainly outside the liver. We performed a hepatectomy of segment 4 through a laparotomy. The postoperative pathology results demonstrated HCS. The patient recovered smoothly and was discharged after surgery. However, the patient experienced a recurrence and died 5 months after surgery. This case underscores the importance of identifying high-risk populations and personalized treatment strategies in HCS cases.

Hepatocellular carcinoma (HCC) continues to be a major cause of cancer-related death worldwide, primarily due to delays in diagnosis and resistance to existing treatments. Recent research has identified ATP-dependent chromatin remodeling-related genes (ACRRGs) as promising targets for therapeutic intervention across various types of cancer. This development offers potential new avenues for addressing the challenges in HCC management.

This study integrated bioinformatics analyses and experimental approaches to explore the role of ACRRGs in HCC. We utilized data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), applying machine learning algorithms to develop a prognostic model based on ACRRGs' expression. Experimental validation was conducted using quantitative real-time Polymerase Chain Reaction (qRT-PCR), Western blotting, and functional assays in HCC cell lines and xenograft models.

Our bioinformatics analysis identified four key ACRRGs-MORF4L1, HDAC1, VPS72, and RUVBL2-that serve as prognostic markers for HCC. The developed risk prediction model effectively distinguished between high-risk and low-risk patients, showing significant differences in survival outcomes and predicting responses to immunotherapy in HCC patients. Experimentally, MORF4L1 was demonstrated to enhance cancer stemness by activating the Hedgehog signaling pathway, as supported by both in vitro and in vivo assays.

ACRRGs, particularly MORF4L1, play crucial roles in modulating HCC progression, offering new insights into the molecular mechanisms driving HCC and potential therapeutic targets. Our findings advocate for the inclusion of chromatin remodeling dynamics in the strategic development of precision therapies for HCC.

Mounting evidence suggests that circulating microRNAs (miRNAs) hold diagnostic value in various malignancies. To identify circulating miRNAs for the early diagnosis of hepatocellular carcinoma (HCC), we conducted a meta-analysis to evaluate the diagnostic utility of miRNAs in HCC and further validated the results of the meta-analysis. English articles published prior to December 2023 were retrieved from databases including PubMed, Embase, and Web of Science. A random-effects or fixed-effects model was applied depending on the heterogeneity among studies. The pooled sensitivity, specificity, and the area under the summary receiver operating characteristic curve (AUC) were calculated to assess diagnostic accuracy. Additionally, RT-qPCR and receiver operating characteristic (ROC) analyses were employed to further validate the findings. A total of 36 studies were included, involving 3362 patients with HCC and 2150 patients with chronic hepatitis. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.79 (95% CI 0.75-0.82), 0.79 (95% CI 0.73-0.84), and 14 (95% CI 9-22), respectively; the positive and negative likelihood ratios were 4.0 and 0.27, respectively; the area under the curve (AUC) in the summary receiver operating characteristic (ROC) was 0.85 (95% CI 0.82-0.88). Validation indicated a significant upregulation of miR-1246, miR-21, and miR-221 in HCC patients compared to those with chronic hepatitis (P < 0.01), while miR-122 and miR-26a were significantly downregulated (P < 0.01). Moreover, the validation results also demonstrated that serum levels of miR-21, miR-26a, miR-122, miR-221, and miR-1246 exhibit high sensitivity and specificity in the diagnosis of HCC. Circulating miRNAs may be promising biomarkers for HCC diagnosis.

Hepatocellular carcinoma (HCC) is a cancer caused by inflammation, which affects the immune response and treatment outcomes. Finding new immune-related targets could improve HCC immunotherapy. New research suggests that TMEM family proteins can act as either tumor suppressors or oncogenes, but the role of TMEM101 in HCC development is unclear. This study conducted an analysis of TMEM101 mRNA expression and its correlation with clinical outcomes in HCC patients using RNA sequencing data from various open databases. Additionally, differences in TMEM101 expression in HCC cell lines and HCC tissue microarrays were examined using RT-qPCR, western blotting, and in situ hybridization staining. The findings presented herein offer initial evidence indicating a significant upregulation of TMEM101 mRNA expression in HCC, which is linked to a poorer prognosis. Furthermore, TMEM101 expression was found to be positively associated with the histological grade and clinical stage of HCC patients. Moreover, a notable reduction in promoter methylation of TMEM101 was observed in HCC patients. Cox regression analysis indicated that TMEM101 was an independent prognostic factor for overall survival (OS) in HCC patients. A nomogram incorporating TMEM101 and tumor stage was constructed and assessed. Comparative analysis with four established HCC diagnostic biomarkers (AFP, EFNA3, MDK, and SMYD5) using ROC curve and time-dependent ROC curves demonstrated the diagnostic potential of TMEM101 in HCC. Gene set enrichment analysis (GSEA) revealed a correlation between TMEM101 and the cell cycle, DNA replication, and repair signaling pathways, which were differentially enriched in the TMEM101 high expression phenotype. The findings from CIBERSORT analysis suggest that TMEM101's pro-tumor effect may be due to decreasing the number of anti-tumor immune cells (M1 macrophages and resting memory CD4+ T cells) and promoting M0 macrophage infiltration in the tumor microenvironment (TME). Overall, our study indicates that TMEM101 could serve as a promising diagnostic and prognostic biomarker for HCC.

Time-resolved fluorescence immunochromatographic test strips (TRFIS) was developed for the rapid detection of hepatocellular carcinoma (HCC)-specific plasma exosomes (hExos) by targeting the hExo-surface membrane protein glypican-3 (GPC3). The GPC3-TRFIS could directly detect plasma exosomes without the isolation and purification process, and the whole immunoassay could be completed within 15 min. The visual detection limit of GPC3-TRFIS was 3.44 × 10^9 particles/mL, with a minimum detection limit of 1.8 × 10^9 particles/mL. For analysis of the clinical HCC samples, GPC3-TRFIS shows high specificity for detection of hExo, and was nearly unreactive for healthy donors' samples. GPC3-TRFIS was able to efficiently distinguish HCC patients (19 cases) from healthy donors (19 cases). Overall, the developed TRFIS offers the benefits of high sensitivity, simple operation, and no need of large precision instruments and professional technical personnel for rapid detection of plasma hExos, and supplies a novel approach for early screening of HCC.