Multimarker Panels for Detection of Early Stage Hepatocellular Carcinoma: A Prospective, Multicenter, Case-Control Study

Advancing Surveillance Strategies for Hepatocellular Carcinoma: A New Era of Efficacy and Precision

Hepatocellular carcinoma (HCC) is one of the few cancers with a 5-year survival that has remained below 20%; however, prognosis differs by tumor stage at diagnosis. Curative treatment options among patients with early-stage HCC afford a median survival of 5-10 years. Accordingly, international society guidelines recommend semi-annual HCC surveillance in at-risk patients, including those with cirrhosis or high-risk chronic hepatitis B infection. Surveillance is associated with increased early-stage HCC detection and curative treatments, leading to reduced HCC-related mortality. Abdominal ultrasound has been the cornerstone for HCC surveillance for the past two decades, but recent data have highlighted its suboptimal sensitivity for early-stage HCC detection, particularly in patients with obesity and those with non-viral etiologies of liver disease. The combination of ultrasound plus alpha fetoprotein (AFP) has higher sensitivity for early-stage HCC detection than ultrasound alone, although the combination still misses over one-third of HCC at an early stage. Emerging imaging and blood-based biomarker strategies have promising data in biomarker phase 2 (case-control) and phase 3 (cohort) studies. Beyond ultrasound, Magnetic resonance imaging (MRI) is the best-studied imaging strategy, with superior sensitivity and specificity compared to ultrasound in a cohort study. Abbreviated MRI protocols have been proposed to address concerns about MRI radiological capacity, costs, and patient acceptance. Of biomarker strategies, GALAD (a panel including gender, age, AFP, AFP-L3, and DCP) is the best validated, with promising sensitivity for early-stage HCC detection in a national multi-center cohort study. Liquid biopsy biomarkers, including methylated DNA markers, have also shown promising accuracy in case-control studies. Abbreviated MRI and GALAD are now entering prospective trials that examine clinical outcomes such as early-stage HCC detection and screening-related harms, which are essential data to understand for adoption in clinical practice. As additional surveillance strategies become available, it will allow an era of precision surveillance in which optimal surveillance modalities are tailored to individual patient risk and expected test performance.

Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

Background & Aims

The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of current screening modalities.

Methods

We developed a multicenter prospective cohort of patients with cirrhosis undergoing surveillance with MRI and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up.

Results

We identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who did not develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, and PNPLA3 and TMS6SF2 single nucleotide polymorphisms, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top six variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC 0.88, 95% CI 0.83-0.93). Finally, 23 metabolites distinguished Cases with LI-RADS-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases.

Conclusions

This study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as biomarkers of HCC risk, and microbiota-derived metabolites as contributors to HCC development.

Impact and implications

The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, particularly blood biomarkers. Longitudinal collection of paired blood samples and MRI images from patients with cirrhosis is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early-stage HCC detection for patients with cirrhosis undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.

British Society of Gastroenterology guidelines for the management of hepatocellular carcinoma in adults

Deaths from the majority of cancers are falling globally, but the incidence and mortality from hepatocellular carcinoma (HCC) is increasing in the United Kingdom and in other Western countries. HCC is a highly fatal cancer, often diagnosed late, with an incidence to mortality ratio that approaches 1. Despite there being a number of treatment options, including those associated with good medium to long-term survival, 5-year survival from HCC in the UK remains below 20%. Sex, ethnicity and deprivation are important demographics for the incidence of, and/or survival from, HCC. These clinical practice guidelines will provide evidence-based advice for the assessment and management of patients with HCC. The clinical and scientific data underpinning the recommendations we make are summarised in detail. Much of the content will have broad relevance, but the treatment algorithms are based on therapies that are available in the UK and have regulatory approval for use in the National Health Service.

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.

High-throughput Proteomics-Guided Biomarker Discovery of Hepatocellular Carcinoma

Liver cancer stands as the fifth leading cause of cancer-related deaths globally. Hepatocellular carcinoma (HCC) comprises approximately 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients qualify for curative therapy, primarily due to the absence of reliable tools for early detection and prognosis of HCC. This underscores the critical need for molecular biomarkers for HCC management. Since proteins reflect disease status directly, proteomics has been utilized in biomarker developments for HCC. In particular, proteomics coupled with liquid chromatography-mass spectrometer (LC-MS) methods facilitate the process of discovering biomarker candidates for diagnosis, prognosis, and therapeutic strategies. In this work, we investigated LC-MS-based proteomics methods through recent reference reviews, with a particular focus on sample preparation and LC-MS methods appropriate for the discovery of HCC biomarkers and their clinical applications. We classified proteomics studies of HCC according to sample types, and we examined the coverage of protein biomarker candidates based on LC-MS methods in relation to study scales and goals. Comprehensively, we proposed protein biomarker candidates categorized by sample types and biomarker types for appropriate clinical use. In this review, we summarized recent LC-MS-based proteomics studies on HCC and proposed potential protein biomarkers. Our findings are expected to expand the understanding of HCC pathogenesis and enhance the efficiency of HCC diagnosis and prognosis, thereby contributing to improved patient outcomes.

A new biomarker panel for differential diagnosis of cholangiocarcinoma: Results from an exploratory analysis

INTRODUCTION

Diagnosis of cholangiocarcinoma (CCA) can be challenging due to unclear imaging criteria and difficulty obtaining adequate tissue biopsy. Although serum cancer antigen 19-9 and carcinoembryonic antigen have been proposed as potential diagnostic aids, their use remains limited by insufficient sensitivity and specificity. This exploratory analysis aimed to identify individual- and combinations of serum biomarkers to distinguish CCA from hepatocellular carcinoma (HCC) and chronic liver disease (CLD) controls using samples from a published study.

METHODS

This prospective, multicenter, case-control study included patients aged ≥18 years at high-risk of HCC. Serum and ethylene diamine tetraacetic acid-plasma samples were collected prior to any treatment and confirmed diagnosis of HCC or CCA. Fourteen biomarkers (measured by electrochemiluminescence immunoassays or enzyme-linked immunosorbent assays) were subjected to univariate analysis and 13 included in a multivariate analysis (per selected combinations and exhaustive search).

RESULTS

Overall, 55 CCA, 306 HCC, and 733 CLD control samples were analyzed. For distinguishing CCA from HCC, alpha-fetoprotein and matrix metalloproteinase-2 (MMP-2) showed the best individual performance (area under the curve (AUC) 86.6% and 84.4%, respectively); tissue inhibitor of metalloproteinase-1 (TIMP-1) was most able to distinguish CCA from CLD (AUC 94.5%) and from HCC  +  CLD (AUC 88.6%). The combination of MMP-2 and TIMP-1 was the best-performing two-marker panel, with AUC >90% for all comparisons.

CONCLUSION

MMP-2 and TIMP-1 are promising biomarkers that could support differential diagnosis of CCA. Incorporating these assays into the diagnostic algorithm could provide additional diagnostic information in a non-invasive, rapid manner, and could supplement existing diagnostic methods.

Role of biomarkers in the diagnosis and management of HCC

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.

The Future Role of Abdominal US in Hepatocellular Carcinoma Surveillance

Abdominal US is currently the best-validated surveillance strategy for hepatocellular carcinoma (HCC) in at-risk patients. It is the only modality shown to have completed all five phases of validation and can achieve high sensitivity and specificity for HCC detection, especially when conducted by expert sonographers in high-volume centers. However, US also has limitations, including operator dependency and varying sensitivity in clinical practice. Further, the sensitivity of US for early-stage HCC detection is lower in patients with obesity or nonviral liver disease, increasingly common populations undergoing surveillance. Imaging-based and blood-based surveillance strategies, including abbreviated MRI and biomarker panels, may overcome some limitations of US-based surveillance. Both strategies have promising test performance in phase II and phase III biomarker studies and are undergoing prospective validation. Considering the variation in HCC risk and test performance between patients, there will likely be a shift away from a one-size-fits-all approach and toward precision screening, in which the "best" test is selected based on individual patient characteristics. In this upcoming era of precision HCC screening among patients with cirrhosis, US will likely continue to have an important, albeit reduced, surveillance role.

Circulating miRNA's biomarkers for early detection of hepatocellular carcinoma in Egyptian patients based on machine learning algorithms

Liver cancer, which ranks sixth globally and third in cancer-related deaths, is caused by chronic liver disorders and a variety of risk factors. Despite therapeutic improvements, the prognosis for Hepatocellular Carcinoma (HCC) remains poor, with a 5-year survival rate for advanced cases of less than 12%. Although there is a noticeable decrease in the frequency of cases, liver cancer remains a significant worldwide health concern, with estimates surpassing one million cases by 2025. The prevalence of HCC has increased in Egypt, and it includes several neoplasms with distinctive messenger RNA (mRNA) and microRNA (miRNA) expression profiles. In HCC patients, certain miRNAs, such as miRNA-483-5P and miRNA-21, are upregulated, whereas miRNA-155 is elevated in HCV-infected people, encouraging hepatocyte proliferation. Short noncoding RNAs called miRNAs in circulation have the potential as HCC diagnostic and prognostic markers. This paper proposed a model for examining circulating miRNAs as diagnostic and predictive markers for HCC in Egyptian patients and their clinical and pathological characteristics. The proposed HCC detection model consists of three main phases: data preprocessing phase, feature selection based on the proposed Binary African Vulture Optimization Algorithm (BAVO) phase, and finally, classification as well as cross-validation phase. The first phase namely the data preprocessing phase tackle the main problems associated with the adopted datasets. In the feature selection based on the proposed BAVO algorithm phase, a new binary version of the BAVO swarm-based algorithm is introduced to select the relevant markers for HCC. Finally, in the last phase, namely the classification and cross-validation phase, the support vector machine and k-folds cross-validation method are utilized. The proposed model is evaluated on three studies on Egyptians who had HCC. A comparison between the proposed model and traditional statistical studies is reported to demonstrate the superiority of using the machine learning model for evaluating circulating miRNAs as diagnostic markers of HCC. The specificity and sensitivity for differentiation of HCC cases in comparison with the statistical-based method for the first study were 98% against 88% and 99% versus 92%, respectively. The second study revealed the sensitivity and specificity were 97.78% against 90% and 98.89% versus 92.5%, respectively. The third study reported 83.2% against 88.8% and 95.80% versus 92.4%, respectively. Additionally, the results show that circulating miRNA-483-5p, 21, and 155 may be potential new prognostic and early diagnostic biomarkers for HCC.

Transcriptomic evaluation of N6-methyladenosine modification can be used to identify differentially gene and immune-related biological processes in TX mice with liver fibrosis

BACKGROUND

N6-methyladenosine (m6A) modification controls the stability, splicing, and translation of mRNA, which is important in the development of illnesses. Wilson's disease (WD) is an autosomal recessive liver copper metabolic disorder that causes liver fibrosis. The role of m6A methylation in WD-induced liver fibrosis development is still unclear. Thus, the goal of this study was to examine the scope of m6A methylation and further explore the potential targets related to WD-induced liver fibrosis.

RESULTS

A total of 1930 significantly different m6A peaks were found on 1737 mRNAs, of which 993 were hypermethylated and 744 were hypomethylated when comparing normal and WD-induced liver fibrosis mice (n = 3). In parallel, 1261 differentially expressed mRNAs, comprising 557 upregulated and 704 downregulated mRNAs, were found. Overall, 114 mRNAs with significant changes in m6A levels and RNA expression were identified via joint analysis. Then, through PPI network construction and functional enrichment analysis, 12 hub genes were identified, these genes were mainly enriched in the inflammatory response and immunomodulation, and they are associated with immune cell infiltration.

CONCLUSIONS

The significant difference in the amount of mRNA m6A modifications indicates that m6A modification is involved in the progression of WD-induced liver fibrosis, and theidentified hub genes are involved in inflammation and immune infiltration. These results may provide insights for subsequent studies on potential regulatory mechanisms.

Establishment and Validation of a Blood Test-based Nomogram to Diagnose Patients with AFP-negative HCC

BACKGROUND

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. Alpha-protein (AFP) is the most widely used blood biomarker for HCC. However, elevated serum AFP is only observed in part of HCC.

AIMS

This study aimed to develop an efficient nomogram model to distinguish patients with alpha- protein-negative HCC and liver cirrhosis.

OBJECTIVES

A total of 1130 patients (508 HCC patients + 622 cirrhosis patients) were enrolled in the training cohort. A total of 244 HCC patients and 246 cirrhosis patients were enrolled in the validation cohort.

METHODS

A total of 41 parameters about blood tests were analyzed with logistic regression. The nomogram was based on independent factors and validated both internally and externally.

RESULTS

Independent factors were eosinophils %, hemoglobin concentration distribution width, fibrinogen, platelet counts, total bile acid, and mitochondria aspartate aminotransferase. The calibration curve for the probability of HCC showed good agreement between prediction by nomogram and actual observation. The concordance index was 0.851. In the validation cohort, the nomogram distinguished HCC from liver cirrhosis with an area under the curve of receiver operating characteristic of 0.754.

CONCLUSION

This proposed nomogram was an accurate and useful method to distinguish patients with AFP-negative HCC from liver cirrhosis.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Global trends in hepatocellular carcinoma epidemiology: implications for screening, prevention and therapy

Hepatocellular carcinoma (HCC) mortality rates are increasing globally, and particularly in the Western world. Cirrhosis remains the predominant risk factor for HCC. However, epidemiological shifts in the incidence of HCC from patients with virus-related liver disease to those with non-viral aetiologies, including alcohol-associated and metabolic dysfunction-associated steatotic liver disease, have important implications for prevention, surveillance and treatment. Hepatitis B vaccination and antiviral therapy for hepatitis B and C are effective for primary prevention of virus-related HCCs, but chemoprevention strategies for non-viral liver disease remain an unmet need. Emerging data suggest associations between aspirin, statins, metformin and coffee and reduced HCC incidence, although none has been proved to be causally related. Secondary prevention of HCC via semi-annual surveillance is associated with improvements in early detection and thus reduced mortality; however, current tools, including abdominal ultrasonography, have suboptimal sensitivity for the detection of early stage HCC, particularly in patients with obesity and/or non-viral liver disease. Promising blood-based or imaging-based surveillance strategies are emerging, although these approaches require further validation before adoption in clinical practice. In the interim, efforts should be focused on maximizing use of the existing surveillance tools given their prevalent underuse globally. Remarkable advances have been made in the treatment of HCC, including expanded eligibility for surgical therapies, improved patient selection for locoregional treatments and increased systemic treatment options, including immune-checkpoint inhibitors. In this Review, we discuss trends in the epidemiology of HCC and their implications for screening, prevention and therapy.

Development and clinical validation of a novel algorithmic score (GAAD) for detecting HCC in prospective cohort studies

BACKGROUND

Alpha-fetoprotein (AFP) and des-gamma carboxyprothrombin (DCP), also known as protein induced by vitamin K absence-II (PIVKA-II [DCP]) are biomarkers for HCC with limited diagnostic value when used in isolation. The novel GAAD algorithm is an in vitro diagnostic combining PIVKA-II (DCP) and AFP measurements, age, and gender (biological sex) to generate a semi-quantitative result. We conducted prospective studies to develop, implement, and clinically validate the GAAD algorithm for differentiating HCC (early and all-stage) and benign chronic liver disease (CLD), across disease stages and etiologies.

METHODS

Patients aged ≥18 years with HCC or CLD were prospectively enrolled internationally into algorithm development [n = 1084; 309 HCC cases (40.7% early-stage) and 736 controls] and clinical validation studies [n = 877; 366 HCC cases (47.6% early-stage) and 303 controls]. Serum samples were analyzed on a cobas® e 601 analyzer. Performance was assessed using receiver operating characteristic curve analyses to calculate AUC.

RESULTS

For algorithm development, AUC for differentiation between early-stage HCC and CLD was 90.7%, 84.4%, and 77.2% for GAAD, AFP, and PIVKA-II, respectively. The sensitivity of GAAD for the detection of early-stage HCC was 71.8% with 90.0% specificity. Similar results were shown in the clinical validation study; AUC for differentiation between early-stage HCC and CLD was 91.4% with 70.1% sensitivity and 93.7% specificity. GAAD also showed strong specificity, with a lower rate of false positives regardless of disease stage, etiology, or region.

CONCLUSIONS

The GAAD algorithm significantly improves early-stage HCC detection for patients with CLD undergoing HCC surveillance. Further phase III and IV studies are warranted to assess the utility of incorporating the algorithm into clinical practice.

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.

Development and validation of a diagnostic model for AFP-negative hepatocellular carcinoma

PURPOSE

AFP appears to be negative in about 30% of overall hepatocellular carcinoma (HCC). Our study aimed to develop a nomogram model to diagnose AFP-negative HCC (AFPN-HCC).

PATIENTS AND METHODS

The training set included 294 AFPN-HCC patients, 159 healthy objects, 63 patients with chronic hepatitis B(CHB), and 64 patients with liver cirrhosis (LC). And the validation set enrolled 137 healthy controls objects, 47 CHB patients and 45 patients with LC. LASSO, univariate, and multivariable logistic regression analysis were performed to construct the model and then transformed into a visualized nomogram. The receiver operating characteristic (ROC) curves, the calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were further used for validation.

RESULTS

Four variables including age, PIVKA-II, platelet (PLT) counts, and prothrombin time (PT) were selected to establish the nomogram. The area under the curve (AUC) of the ROC to distinguish AFPN-HCC patients was 0.937(95% CI 0.892-0.938) in training set and 0.942(95% CI 0.921-0.963) in validation set. We also found that the model had high diagnostic value for small-size HCC (tumor size < 5 cm) (AUC = 0.886) and HBV surface antigen-positive AFPN-HCC (AUC = 0.883).

CONCLUSIONS

Our model was effective for discrimination of AFPN-HCC from patients with benign liver diseases and healthy controls, and might be helpful for the diagnosis for AFPN-HCC.

Validation and optimization of AFP-based biomarker panels for early HCC detection in Latin America and Europe

BACKGROUND

HCC is a major cause of cancer death worldwide. Serum biomarkers such as alpha-fetoprotein (AFP), protein induced by vitamin K absence-II, and the Gender, Age, AFP-L3, AFP, Des-gamma-carboxy prothrombin (GALAD) score have been recommended for HCC surveillance. However, inconsistent recommendations in international guidelines limit their clinical utility.

METHODS

In this multicenter study, over 2000 patient samples were collected in 6 Latin American and 2 European countries. The performance of the GALAD score was validated in cirrhotic cases, and optimized versions were tested for early-stage HCC and prediagnostic HCC detection.

RESULTS

The GALAD score could distinguish between HCC and cirrhosis in Latin American patients with an AUC of 0.76, sensitivity of 70%, and specificity of 83% at the conventional cutoff value of -0.63. In a European cohort, GALAD had an AUC of 0.69, sensitivity of 66%, and specificity of 72%. Optimizing the score in the 2 large multicenter cohorts revealed that AFP-L3 contributed minimally to early-stage HCC detection. Thus, we developed a modified GALAD score without AFP-L3, the ASAP (age, sex, AFP, and protein induced by vitamin K absence-II), which showed promise for early-stage HCC detection upon validation. The ASAP score also identified patients with cirrhosis at high risk for advanced-stage HCC up to 15 months before diagnosis (p < 0.0001) and differentiated HCC from hemangiomas, with a specificity of 100% at 71% sensitivity.

CONCLUSION

Our comprehensive analysis of large sample cohorts validates the GALAD score's utility in Latin American, Spanish, and Dutch patients for early-stage HCC detection. The optimized GALAD without AFP-L3, the ASAP score, is a good alternative and shows greater promise for HCC prediction.

Real-time temperature correction for magnetoresistive biosensors integrated with temperature modulator

Magnetoresistance-based biosensors utilize changes in electrical resistance upon varying magnetic fields to measure biological molecules or events involved with magnetic tags. However, electrical resistance fluctuates with temperature. To decouple unwanted temperature-dependent signals from the signal of interest, various methods have been proposed to correct signals from magnetoresistance-based biosensors. Yet, there is still a need for a temperature correction method capable of instantaneously correcting signals from all sensors in an array, as multiple biomarkers need to be detected simultaneously with a group of sensors in a central laboratory or point-of-care setting. Here we report a giant magnetoresistive biosensor system that enables real-time temperature correction for individual sensors using temperature correction coefficients obtained through a temperature sweep generated by an integrated temperature modulator. The algorithm with individual temperature correction coefficients obviously outperformed that using the average temperature correction coefficient. Further, temperature regulation did not eliminate temperature-dependent signals completely. To demonstrate that the method can be used in biomedical applications where large temperature variations are involved, binding kinetics experiments and melting curve analysis were conducted with the temperature correction method. The method successfully removed all temperature-dependent artifacts and thus produced more precise kinetic parameters and melting temperatures of DNA hybrids.

A Statistical Approach to the Diagnosis and Prediction of HCC Using CK19 and Glypican 3 Biomarkers

Various statistical models predict the probability of developing hepatocellular carcinoma (HCC) in patients with cirrhosis, with GALAD being one of the most extensively studied scores. Biomarkers like alpha-fetoprotein (AFP), AFP-L3, and des-g-carboxyprothrombin (DCP) are widely used alone or in conjunction with ultrasound to screen for HCC. Our study aimed to compare the effectiveness of Cytokeratin 19 (CK19) and Glypican-3 (GPC3) as standalone biomarkers and in a statistical model to predict the likelihood of HCC. We conducted a monocentric prospective study involving 154 participants with previously diagnosed liver cirrhosis, divided into two groups: 95 patients with confirmed HCC based on clinical, biological, and imaging features and 59 patients without HCC. We measured the levels of AFP, AFP-L3, DCP, GPC3, and CK19 in both groups. We used univariate and multivariate statistical analyses to evaluate the ability of GPC3 and CK19 to predict the presence of HCC and incorporated them into a statistical model—the GALKA score—which was then compared to the GALAD score. AFP performed better than AFP-F3, DCP, GPC3, and CK19 in predicting the presence of HCC in our cohort. Additionally, GPC3 outperformed CK19. We used multivariate analysis to compute the GALKA score to predict the presence of HCC. Using these predictors, the following score was formulated: 0.005*AFP-L3 + 0.00069*AFP + 0.000066*GPC3 + 0.01*CK19 + 0.235*Serum Albumin—0.277. The optimal cutoff was >0.32 (AUROC = 0.98, sensitivity: 96.8%, specificity: 93%, positive predictive value—95.8%, negative predictive value—94.8%). The GALKA score had a similar predictive value to the GALAD score for the presence of HCC. In conclusion, AFP, AFP-L3, and DCP were the best biomarkers for predicting the likelihood of HCC. Our score performed well overall and was comparable to the GALAD score.

Diagnostic Performance of Extrahepatic Protein Induced by Vitamin K Absence in the Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

BACKGROUND AND OBJECTIVES

the early diagnosis of hepatocellular carcinoma (HCC) benefits from the use of alpha-fetoprotein (AFP) together with imaging diagnosis using abdominal ultrasonography, CT, and MRI, leading to improved early detection of HCC. A lot of progress has been made in the field, but some cases are missed or late diagnosed in advanced stages of the disease. Therefore, new tools (serum markers, imagistic technics) are continually being reconsidered. Serum alpha-fetoprotein (AFP), protein induced by vitamin K absence or antagonist II (PIVKA II) diagnostic accuracy for HCC (global and early disease) has been investigated (in a separate or cumulative way). The purpose of the present study was to determine the performance of PIVKA II compared to AFP.

MATERIALS AND METHODS

systematic research was conducted in PubMed, Web of Science, Embase, Medline and the Cochrane Central Register of Controlled Trials, taking into consideration articles published between 2018 and 2022.

RESULTS

a total number of 37 studies (5037 patients with HCC vs. 8199 patients-control group) have been included in the meta-analysis. PIVKA II presented a better diagnostic accuracy in HCC diagnostic vs. alpha-fetoprotein (global PIVKA II AUROC 0.851 vs. AFP AUROC 0.808, respectively, 0.790 vs. 0.740 in early HCC cases). The conclusion from a clinical point of view, concomitant use of PIVKA II and AFP can bring useful information, added to that brought by ultrasound examination.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

The Performance of GALAD Score for Diagnosing Hepatocellular Carcinoma in Patients with Chronic Liver Diseases: A Systematic Review and Meta-Analysis

Background GALAD score, comprising five clinical parameters, is a predictive model developed for hepatocellular carcinoma (HCC) detection. Since its emergence, its diagnostic ability has been validated in different populations with a wide variation. Therefore, we conducted a meta-analysis to investigate its overall diagnostic performance in differentiating HCC in chronic liver diseases. Methods Eligible studies were searched in the Web of Science, PubMed, Scopus, Ovid, Cochrane Library, and Embase databases by 29 May 2022. Pooled sensitivity, pooled specificity, and area under the receiver operating characteristic curve (AUC) with the corresponding 95% confidence intervals (CI) were estimated. Results Fifteen original studies (comprising 19,021 patients) were included. For detecting any-stage HCC, GALAD score yielded an excellent ability, with pooled sensitivity, specificity, and AUC of 0.82 (95%CI: 0.78-0.85), 0.89 (95%CI: 0.85-0.91), and 0.92 (95%CI: 0.89-0.94), respectively. Notably, further analyses demonstrated a good diagnostic accuracy of GALAD score for identifying Barcelona Clinic Liver Cancer staging (BCLC) 0/A HCC, with a moderate sensitivity (0.73 (95%CI: 0.66-0.79)) and a high specificity (0.87 (95%CI: 0.81-0.91)); by contrast, only 38% of early-stage patients can be identified by alpha-fetoprotein, with an AUC value of 0.70 (95%CI: 0.66-0.74). Following subgroup analyses based on different HCC etiologies, higher sensitivities and AUC values were observed in subgroups with hepatitis C or non-viral liver diseases. For detecting BCLC 0/A HCC in the cirrhotic population, GALAD score had a pooled sensitivity, specificity, and AUC of 0.78 (95%CI: 0.66-0.87), 0.80 (95%CI: 0.72-0.87), and 0.86 (95%CI: 0.83-0.89). Conclusions We highlighted the superior diagnostic accuracy of GALAD score for detecting any-stage HCC with a high sensitivity and specificity, especially for early-stage HCC, with a relatively stable diagnostic performance. The addition of GALAD score into ultrasound surveillance may identify more HCC patients. Our findings imply the robust power of the GALAD score as a HCC screening or diagnostic tool, and it should be further validated by more studies with high quality.

RPS24 Is Associated with a Poor Prognosis and Immune Infiltration in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver malignancy, with increased mortality and morbidity. Accumulating evidence suggested that 40S ribosomal protein S24 (RPS24) is related to malignant outcomes and progression. However, the role of RPS24 remains unclear in HCC. The mRNA and protein expression pattern of RPS24 in HCC was explored and confirmed based on the bioinformatics analysis and histological examination. The correlation between RPS24 expression and clinicopathological features, diagnostic value, prognosis, methylation status, and survival were evaluated. Then, we divided the HCC cohort into two groups based on the expression of RPS24, and performed the functional enrichment and immune cells infiltration analysis of RPS24. Furthermore, in vivo and in vitro experiments were performed to investigate the effect of RPS24 on HCC cells. RPS24 was observed to be elevated in HCC samples. RPS24 overexpression or RPS24 promoter methylation contributed to an unfavorable prognosis for HCC patients. The genes in the high RPS24 expression group were mainly enriched in DNA replication, cell cycle E2F targets, and the G2M checkpoint pathway. Moreover, the expression level of RPS24 was significantly related to immune infiltration and immunotherapy response. Our experiments also demonstrated that RPS24 knockdown suppressed the growth of HCC cells and tumor proliferation of the xenograft model. Therefore, RPS24 can be a potential adverse biomarker of HCC prognosis acting through facilitating cell proliferation and the formation of an immunosuppressive microenvironment in HCC. Targeting RPS24 may offer a promising therapeutic option for HCC management.

Blood-based biomarkers for hepatocellular carcinoma screening: Approaching the end of the ultrasound era?

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, in part because of inadequate early detection strategies. Current recommendations for screening consist of semi-annual abdominal ultrasound with or without serum alpha-fetoprotein in patients with cirrhosis and in demographic subgroups with chronic hepatitis B infection. However, this screening strategy has several deficiencies, including suboptimal early-stage sensitivity, false positives with subsequent harms, inter-operator variability in ultrasound performance, and poor adherence. A blood-based biomarker with sufficient performance characteristics for early-stage disease could overcome several of these barriers to improving early-stage detection. However, prior to use of a biomarker for screening in clinical practice, a multistep validation is required in order to understand test performance characteristics. These steps include case-control validation, followed by validation in prospective cohorts of at-risk patients. Until recently, we lacked adequate longitudinal validation cohorts for early HCC detection; however, several validation cohorts are maturing, including the Hepatocellular Carcinoma Early Detection Study and the Texas Hepatocellular Carcinoma Consortium, which will allow for rigorous validation of candidate biomarkers. While there are several promising biomarkers awaiting validation, in order to supplant abdominal ultrasound, a candidate biomarker must show adequate test performance and overcome practical hurdles to ensure adoption in clinical practice. The promise of blood-based biomarkers is significant, especially given the limitations of ultrasound-based screening; however, they require adequate validation and several logistical obstacles must be overcome prior to clinical implementation.

Circulating Metabolic Markers Related to the Diagnosis of Hepatocellular Carcinoma

Primary liver carcinoma is the sixth most common cancer worldwide, while hepatocellular carcinoma (HCC) is the most dominant cancer type. Chronic hepatitis B and C virus infections and aflatoxin exposure are the main risk factors, while nonalcoholic fatty liver disease caused by obesity, diabetes, and metabolic syndrome are the more common risk factors for HCC. Metabolic disorders caused by these high-risk factors are closely related to the tumor microenvironment of HCC, revealing a possible cause-and-effect relationship between the two. These metabolic disorders involve many complex metabolic pathways, such as carbohydrate, lipid, lipid derivative, amino acid, and amino acid derivative metabolic processes. The resulting metabolites with significant abnormal changes in the concentration level in circulating blood may be used as biomarkers to guide the diagnosis, treatment, or prognosis of HCC. At present, there are high-throughput technologies that can quickly detect small molecular metabolites in many samples. Compared to tissue biopsy, blood samples are easier to obtain, and patients’ willingness to participate is higher, which makes it possible to study blood HCC biomarkers. Over the past few years, a substantial body of research has been performed worldwide, and other potential biomarkers have been identified. Unfortunately, due to the limitations of each study, only a few markers have been widely verified and are suitable for clinical use. This review briefly summarizes the potential blood metabolic markers related to the diagnosis of HCC, mainly focusing on amino acids and their derivative metabolism, lipids and their derivative metabolism, and other possible related metabolisms.

Emerging Tools for Hepatocellular Carcinoma Surveillance

Abdominal ultrasound, with or without alpha-fetoprotein, is the recommended strategy for hepatocellular carcinoma (HCC) surveillance but misses over one-third of HCC at an early stage. Emerging imaging modalities, including computed tomography and magnetic resonance imaging, have early data showing high sensitivity for early-stage HCC, but potential issues such as radiologic capacity, patient acceptance, cost-effectiveness, and need for validation in Western non-hepatitis B virus populations still need to be evaluated. Similarly, blood-based biomarker panels, including GALAD and liquid biopsy techniques, have shown promising data in phase II case-control studies and may concurrently help address issues of surveillance underuse; however, these tools require validation in phase III and IV cohort studies. While awaiting prospective validation data for these emerging strategies, ultrasound with or without alpha-fetoprotein remains the current gold standard HCC surveillance strategy.

Circulating Cytokines Reflect the Etiology-Specific Immune Environment in Cirrhosis and HCC

Background and Aims: Chronic liver disease—from any etiology—can progress to fibrosis, cirrhosis and hepatocellular carcinoma (HCC). The progression of liver cirrhosis to the end stages of disease is influenced by a variety of factors, including inflammatory cytokines. We pursued a study of cytokine-mediated inflammatory responses in hepatitis B (HBV), hepatitis C (HCV), alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD) patients with liver cirrhosis. Methods: Immune profiles were determined through the serum multiplex profiling of >100 cytokines in a 188 cirrhotic patients, 35 healthy controls and 196 early-stage HCC patients. Results: Patients with liver cirrhosis exhibited a vast upregulation of proinflammatory cytokines (p < 0.0001), including those with pro-oncogenic features, when compared to healthy individuals. In contrast to prevailing assumptions, each etiological cause of cirrhosis exhibited a unique cytokine profile in blood. Regardless of antiviral therapy, HBV cirrhosis patients had the largest number of upregulated proinflammatory mediators, compared to HCV, ALD and NAFLD (p < 0.0001). To further evaluate the etiology-dependent modulation of cytokine response in relation to liver cancer, we studied cytokine profiles in early-stage HCC patients strictly stratified by underlying liver disease. We observed unique sets of differentially expressed cytokines in each cohort of early-stage HCC patients of different cirrhosis etiologies. Conclusions: Our findings, therefore, underscore the importance of stratification by the etiological cause of liver cirrhosis in immune-based studies.

New insights into vitamin K biology with relevance to cancer

Phylloquinone (vitamin K1) and menaquinones (vitamin K2 family) are essential for post-translational γ-carboxylation of a small number of proteins, including clotting factors. These modified proteins have now been implicated in diverse physiological and pathological processes including cancer. Vitamin K intake has been inversely associated with cancer incidence and mortality in observational studies. Newly discovered functions of vitamin K in cancer cells include activation of the steroid and xenobiotic receptor (SXR) and regulation of oxidative stress, apoptosis, and autophagy. We provide an update of vitamin K biology, non-canonical mechanisms of vitamin K actions, the potential functions of vitamin K-dependent proteins in cancer, and observational trials on vitamin K intake and cancer.

Cartilage Oligomeric Matrix Protein, Diseases, and Therapeutic Opportunities

Cartilage oligomeric matrix protein (COMP) is an extracellular matrix (ECM) glycoprotein that is critical for collagen assembly and ECM stability. Mutations of COMP cause endoplasmic reticulum stress and chondrocyte apoptosis, resulting in rare skeleton diseases. The bouquet-like structure of COMP allows it to act as a bridging molecule that regulates cellular phenotype and function. COMP is able to interact with many other ECM components and binds directly to a variety of cellular receptors and growth factors. The roles of COMP in other skeleton diseases, such as osteoarthritis, have been implied. As a well-established biochemical marker, COMP indicates cartilage turnover associated with destruction. Recent exciting achievements indicate its involvement in other diseases, such as malignancy, cardiovascular diseases, and tissue fibrosis. Here, we review the basic concepts of COMP and summarize its novel functions in the regulation of signaling events. These findings renew our understanding that COMP has a notable function in cell behavior and disease progression as a signaling regulator. Interestingly, COMP shows distinct functions in different diseases. Targeting COMP in malignancy may withdraw its beneficial effects on the vascular system and induce or aggravate cardiovascular diseases. COMP supplementation is a promising treatment for OA and aortic aneurysms while it may induce tissue fibrosis or cancer metastasis.

Comprehensive evaluation of microRNA as a biomarker for the diagnosis of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Current guidelines for HCC management recommend surveillance of high-risk patients every 6 mo using ultrasonography. Serum biomarkers, like alpha-fetoprotein (AFP), protein induced by vitamin K absence/antagonist-II (PIVKA-II) and lectin-reactive AFP, show suboptimal performance for detection of HCC, which is crucial for successful resection or treatment. Thus, there is a significant need for new biomarkers to aid early diagnosis of HCC. Studies have shown that the expression level of human microRNAs (miRNAs), a small, non-coding RNA species released into the blood, can serve as an early marker for various diseases, including HCC.

AIM

To evaluate the diagnostic role of miRNAs in HCC as single markers, signatures or in combination with known protein biomarkers.

METHODS

Our prospective, multicenter, case-control study recruited 660 participants (354 controls with chronic liver disease and 306 participants with HCC) and employed a strategy of initial screening by two independent methods, real-time quantitative PCR (n = 60) and next-generation sequencing (n = 100), to assess a large number of miRNAs. The results from the next-generation sequencing and real-time quantitative PCR screening approaches were then combined to select 26 miRNAs (including two putative novel miRNAs). Those miRNAs were analyzed for their diagnostic potential as single markers or in combination with other miRNAs or established protein biomarkers AFP and PIVKA-II via real-time quantitative PCR in training (n = 200) and validation cohorts (n = 300).

RESULTS

We identified 26 miRNAs that differentiated chronic liver disease controls from (early) HCC via two independent discovery approaches. Three miRNAs, miR-21-5p (miR-21), miR-320a and miR-186-5p, were selected by both methods. In the training cohort, only miR-21, miR-320d and miR-423 could significantly distinguish (Q < 0.05) between the HCC and chronic liver disease control groups. In the multivariate setting, miR-21 with PIVKA-II was selected as the best combination, resulting in an area under the curve of 0.87 for diagnosis and area under the curve of 0.74 for early diagnosis of HCC. In the validation cohort, only miR-21 and miR-423 could be confirmed as potential HCC biomarkers. A combination of miRNAs did not perform better than any single miRNA. Improvement of PIVKA-II performance through combination with miRNAs could not be confirmed in the validation panel. Two putative miRs, put-miR-6 and put-miR-99, were tested in the training and validation panels, but their expression could only be detected in very few samples and at a low level (cycle threshold between 31.24 and 34.97).

CONCLUSION

miRNAs alone or as a signature in combination with protein biomarkers AFP and PIVKA-II do not improve the diagnostic performance of the protein biomarkers.

N-glycosylation stabilizes MerTK and promotes hepatocellular carcinoma tumor growth

Despite the evidences of elevated expression of Mer tyrosine kinase (MerTK) in multiple human cancers, mechanisms underlying the oncogenic roles of MerTK in hepatocellular carcinoma (HCC) remains undefined. We explored the functional effects of MerTK and N-Glycosylated MerTK on HCC cell survival and tumor growth. Here, we show that MerTK ablation increases reactive oxygen species (ROS) production and promotes the switching from glycolytic metabolism to oxidative phosphorylation in HCC cells, thus suppressing HCC cell proliferation and tumor growth. MerTK is N-glycosylated in HCC cells at asparagine 294 and 454 that stabilizes MerTK to promote oncogenic transformation. Moreover, we observed that nuclear located non-glycosylated MerTK is indispensable for survival of HCC cells under stress. Pathologically, tissue microarray (TMA) data indicate that MerTK is a pivotal prognostic factor for HCC. Our data strongly support the roles of MerTK N-glycosylation in HCC tumorigenesis and suggesting N-glycosylation inhibition as a potential HCC therapeutic strategy.

•

MerTK promotes the switching from oxidative phosphorylation to glycolytic metabolism in HCC cells.

•

MerTK is N-glycosylated in HCC cells at asparagine 294 and 454 that stabilizes MerTK to promote HCC tumor growth.

•

The nuclear located non-glycosylated MerTK is indispensable for survival of HCC cells under stress.

•

MerTK is a pivotal prognostic factor for HCC and its N-glycosylation inhibition is a potential HCC therapeutic strategy.

Application and progress of the detection technologies in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a very high incidence and fatality rate, and in most cases, it is already at an advanced stage when diagnosed. Therefore, early prevention and detection of HCC are two of the most effective strategies. However, the methods recommended in the practice guidelines for the detection of HCC cannot guarantee high sensitivity and specificity except for the liver biopsy, which is known as the "gold standard". In this review, we divided the detection of HCC into pre-treatment diagnosis and post-treatment monitoring, and found that in addition to the traditional imaging detection and liver biopsy, alpha fetoprotein (AFP), lens culinaris-agglutinin-reactive fraction of AFP (AFP-L3), protein induced by vitamin K absence or antagonist-II (PIVKA-II) and other biomarkers are excellent biomarkers for HCC, especially when they are combined together. Most notably, the emerging liquid biopsy shows great promise in detecting HCC. In addition, lactic dehydrogenase (LDH), suppressor of cytokine signaling (SOCS) and other relevant biomarkers may become promising biomarkers for HCC post-treatment monitoring. Through the detailed introduction of the diagnostic technology of HCC, we can have a detailed understanding of its development process and then obtain some enlightenment from the diagnosis, to improve the diagnostic rate of HCC and reduce its mortality.