AFP-negative Hepatocellular Carcinoma Research Articles

Serum ApoB/ApoA1 ratio in patients with CHB and the occurrence of HBV related cirrhosis and HBV related hepatocellular carcinoma

Clinical research has suggested that chronic HBV infection exerts a certain effect on the occurrence of cardiovascular disease by regulating cholesterol metabolism in liver cells. High serum apolipoprotein B/apolipoprotein A1 (ApoB/ApoA1) ratio plays a certain role in the above regulation, and it serves as a risk factor for cardiovascular disease. However, whether the ApoB/ApoA1 ratio is correlated with chronic HBV infection and its disease progression remains unclear. In accordance with the inclusion and exclusion criteria, all 378 participants administrated at Renmin Hospital of Wuhan University from March 2021 to March 2022, fell into Healthy Control (HC) group (50 participants), Hepatocellular carcinoma (HCC) group (107 patients), liver cirrhosis (LC) group (64 patients), chronic hepatitis B (CHB) group (62 patients), chronic hepatitis C (CHC) group (46 patients) and Hepatitis E Virus (HEV) group (49 patients). Serum ApoA1 and ApoB concentrations were measured at admission, and the ApoB/ApoA1 ratio was determined. The levels of laboratory parameters in the respective group were compared and ApoB/ApoA1 ratios in HCC patients and LC patients with different severity were further analyzed. ROC curves were plotted to analyze the early diagnostic ability of ApoB/ApoA1 ratio for HBV-associated HCC. Logistic regression and restricted cubic spline analysis were used to explore the correlation between ApoB/ApoA1 ratio and LC and HCC risk. A comparison was drawn in terms of ApoB/ApoA1 ratio between the groups, and the result was expressed in descending sequence: HEV group > CHB group > LC group > HCC group > CHC group > HC group, early-stage HCC < middle-stage HCC < advanced-stage HCC, Class A LC < Class B LC < Class C LC. Serum ApoB/ApoA1 ratio combined diagnosis with AFP exhibited the capability of increasing the detection efficacy and specificity of AFP for HCC and AFP-negative HCC. The incidence of LC and HCC in the respective logistic regression model showed a negative correlation with the serum ApoB/ApoA1 ratio in CHB patients (P < 0.05). After all confounding factors covered in this study were regulated, the result of the restricted cubic spline analysis suggested that in a certain range, serum ApoB/ApoA1 ratio showed an inverse correlation with the prevalence of LC or HCC in CHB patients. Serum ApoB/ApoA1 ratio in CHB patients may be conducive to identifying high-risk patients for HCC or LC, such that LC and HCC can be early diagnosed and treated.

DGPRI, a new liver fibrosis assessment index, predicts recurrence of AFP-negative hepatocellular carcinoma after hepatic resection: a single-center retrospective study

Although patients with alpha-fetoprotein-negative hepatocellular carcinoma (AFPNHCC) have a favorable prognosis, a high risk of postoperative recurrence remains. We developed and validated a novel liver fibrosis assessment index, the direct bilirubin-gamma-glutamyl transpeptidase-to-platelet ratio (DGPRI). DGPRI was calculated for each of the 378 patients with AFPNHCC who underwent hepatic resection. The patients were divided into high- and low-score groups using the optimal cutoff value. The Lasso-Cox method was used to identify the characteristics of postoperative recurrence, followed by multivariate Cox regression analysis to determine the independent risk factors associated with recurrence. A nomogram model incorporating the DGPRI was developed and validated. High DGPRI was identified as an independent risk factor (hazard ratio = 2.086) for postoperative recurrence in patients with AFPNHCC. DGPRI exhibited better predictive ability for recurrence 1–5 years after surgery than direct bilirubin and the gamma-glutamyl transpeptidase-to-platelet ratio. The DGPRI-nomogram model demonstrated good predictive ability, with a C-index of 0.674 (95% CI 0.621–0.727). The calibration curves and clinical decision analysis demonstrated its clinical utility. The DGPRI nomogram model performed better than the TNM and BCLC staging systems for predicting recurrence-free survival. DGPRI is a novel and effective predictor of postoperative recurrence in patients with AFPNHCC and provides a superior assessment of preoperative liver fibrosis.

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

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. This study aimed to develop an efficient nomogram model to distinguish patients with alpha- protein-negative HCC and liver cirrhosis. 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. 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. 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. This proposed nomogram was an accurate and useful method to distinguish patients with AFP-negative HCC from liver cirrhosis.

Prognostic performance of MRI LI-RADS version 2018 features and clinical-pathological factors in alpha-fetoprotein-negative hepatocellular carcinoma.

To evaluate the role of the magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS) version 2018 features and clinical-pathological factors for predicting the prognosis of alpha-fetoprotein (AFP)-negative (≤ 20ng/ml) hepatocellular carcinoma (HCC) patients, and to compare with other traditional staging systems. We retrospectively enrolled 169 patients with AFP-negative HCC who received preoperative MRI and hepatectomy between January 2015 and August 2020 (derivation dataset:validation dataset = 118:51). A prognostic model was constructed using the risk factors identified via Cox regression analysis. Predictive performance and discrimination capability were evaluated and compared with those of two traditional staging systems. Six risk factors, namely the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade, were associated with recurrence-free survival. The prognostic model constructed using these factors achieved C-index of 0.705 and 0.674 in the derivation and validation datasets, respectively. Furthermore, the model performed better in predicting patient prognosis than traditional staging systems. The model effectively stratified patients with AFP-negative HCC into high- and low-risk groups with significantly different outcomes (p < 0.05). A prognostic model integrating the LI-RADS category, blood products in mass, microvascular invasion, tumor size, cirrhosis, and albumin-bilirubin grade may serve as a valuable tool for refining risk stratification in patients with AFP-negative HCC.

Prediction of survival and analysis of prognostic factors for patients with AFP negative hepatocellular carcinoma: a population-based study

PurposeHepatocellular carcinoma (HCC) has a poor prognosis, and alpha-fetoprotein (AFP) is widely used to evaluate HCC. However, the proportion of AFP-negative individuals cannot be disregarded. This study aimed to establish a nomogram of risk factors affecting the prognosis of patients with AFP-negative HCC and to evaluate its diagnostic efficiency.Patients and methodsData from patients with AFP-negative initial diagnosis of HCC (ANHC) between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and validation. We randomly divided overall cohort into the training or validation cohort (7:3). Univariate and multivariate Cox regression analysis were used to identify the risk factors. We constructed nomograms with overall survival (OS) and cancer-specific survival (CSS) as clinical endpoint events and constructed survival analysis by using Kaplan-Meier curve. Also, we conducted internal validation with Receiver Operating Characteristic (ROC) analysis and Decision curve analysis (DCA) to validate the clinical value of the model.ResultsThis study included 1811 patients (1409 men; 64.7% were Caucasian; the average age was 64 years; 60.7% were married). In the multivariate analysis, the independent risk factors affecting prognosis were age, ethnicity, year of diagnosis, tumor size, tumor grade, surgery, chemotherapy, and radiotherapy. The nomogram-based model related C-indexes were 0.762 (95% confidence interval (CI): 0.752–0.772) and 0.752 (95% CI: 0.740–0.769) for predicting OS, and 0.785 (95% CI: 0.774–0.795) and 0.779 (95% CI: 0.762–0.795) for predicting CSS. The nomogram model showed that the predicted death was consistent with the actual value. The ROC analysis and DCA showed that the nomogram had good clinical value compared with TNM staging.ConclusionThe age(HR:1.012, 95% CI: 1.006–1.018, P-value < 0.001), ethnicity(African-American: HR:0.946, 95% CI: 0.783–1.212, P-value: 0.66; Others: HR:0.737, 95% CI: 0.613–0.887, P-value: 0.001), tumor diameter(HR:1.006, 95% CI: 1.004–1.008, P-value < 0.001), year of diagnosis (HR:0.852, 95% CI: 0.729–0.997, P-value: 0.046), tumor grade(Grade 2: HR:1.124, 95% CI: 0.953–1.326, P-value: 0.164; Grade 3: HR:1.984, 95% CI: 1.574–2.501, P-value < 0.001; Grade 4: HR:2.119, 95% CI: 1.115–4.027, P-value: 0.022), surgery(Liver Resection: HR:0.193, 95% CI: 0.160–0.234, P-value < 0.001; Liver Transplant: HR:0.102, 95% CI: 0.072–0.145, P-value < 0.001), chemotherapy(HR:0.561, 95% CI: 0.471–0.668, P-value < 0.001), and radiotherapy(HR:0.641, 95% CI: 0.463–0.887, P-value:0.007) were independent prognostic factors for patients with ANHC. We developed a nomogram model for predicting the OS and CSS of patients with ANHC, with a good predictive performance.

Profiling of aberrant sialylated N-glycans in hepatocellular carcinoma by liquid chromatography mass spectrometry

BackgroundAberrant sialylation is closely associated with the tumorigenesis, progression, and metastasis, and may be of importance for disease diagnosis. However, the analysis of altered expression of sialylated glycans (SGs) in blood is particularly challenging due to the low content and poor ionization efficiency of sialylated glycans in mass spectrometry. MethodsAn analytical strategy based on enrichment of SGs, liquid chromatography-high resolution mass spectrometric detection, and automatic glycan annotation was developed to profile the sialylated N-glycome in serum. The enrichment of sialylated glycans was accomplished using cationic cotton via electrostatic and hydrogen interaction. Using partial least squares-discriminant analysis (PLS-DA), the approach was applied for nontarget screening and profiling of aberrant sialylated N-glycans in hepatocellular carcinoma (HCC). Results55 SGs were identified in human serum, and three important SGs (SG35, SG45, and SG46) were screened to have good diagnostic specificity for HCC. Their areas under the receiver operating characteristic (ROC) curve (AUC) were higher than α-fetoprotein (AFP)’s (AUC = 0.85), at 0.88, 0.87, and 0.91, respectively. When three SGs are combined, the diagnostic specificity for HCC may increase to 94 %. The fact that SGs biomarkers are sensitive to AFP-Negative HCC is very noteworthy. ConclusionsThe method significantly advanced the search for sialylated glycan-based cancer biomarkers. In comparison to traditional indicators like AFP and imaging tools, SGs showed a higher diagnostic sensitivity for HCC.

The Prognostic Value of Alpha-Fetoprotein Ratio in Patients With Resectable Alpha-Fetoprotein-Negative Hepatocellular Carcinoma.

This study aimed to investigate the prognostic value of alpha-fetoprotein (AFP) ratio in patients with AFP-negative hepatocellular carcinoma (HCC). We retrospectively analyzed 600 AFP-negative HCC patients who underwent hepatectomy. The AFP ratio was calculated as the ratio of AFP level 1week before surgery to the level 20-40days after hepatectomy. Immunohistochemistry assay was used to assess protein expression in HCC tissue. The primary outcome measures were overall survival (OS) and disease-free survival (DFS). The study found that a cutoff value of 1.6ng/ml for AFP ratio, determined using X-tile software, was optimal for predicting prognosis. Patients with a high AFP ratio had a worse prognosis compare to those with a low AFP ratio (DFS, P = .026; OS, P = .034). Patients with a high AFP ratio had a worse prognosis compared to those with a low AFP ratio. Multivariate analysis revealed that AFP ratio >1.6, negative HepPar-1 expression, and vascular invasion were independent predictors of both DFS and OS. Vascular invasion had a higher area under the curve (AUC) than AFP ratio and HepPar-1 expression in predicting recurrence and death. The combination of AFP ratio, HepPar-1 expression, and vascular invasion provided better predictive accuracy for DFS and OS. The AFP ratio is a potential prognostic marker for AFP-negative HCC patients after hepatectomy. Combining the analysis of AFP ratio with HepPar-1 expression and vascular invasion can enhance the accuracy of predicting prognosis in these patients.

Serum Aldo-Keto Reductase Family 1 Member B10 (AKR1B10) as a Potential Biomarker for Diagnosis of Hepatocellular Carcinoma.

To evaluate the diagnostic performance of aldo-keto reductase family 1 member B10 (AKR1B10) in a Beijing cohort with hepatocellular carcinoma (HCC). This study included 521 subjects who visited Peking Union Medical College Hospital from June 2017 to May 2023, including 109 cases of HCC, 165 cases of healthy controls, 106 cases of benign liver diseases, and 141 cases of other cancers. Serum AKR1B10 levels were measured and compared across various groups. Diagnostic performances of serum AKR1B10 and other tumor markers were assessed using receiver operator characteristic (ROC) curves. In addition, a subset of HCC patients who underwent surgical resection were recruited for clinical follow-up study. We found that serum AKR1B10 expression was higher in patients with HCC relative to other control groups. The association between serum AKR1B10 and clinical features of HCC was not observed. Serum AKR1B10 showed a high diagnostic performance for HCC, and when combined with AFP, the diagnostic effectiveness was significantly improved. Specifically, serum AKR1B10 showed superior diagnostic effectiveness for AFP-negative HCC. The clinical follow-up study indicated a gradual decrease in serum AKR1B10 after surgery. Our study demonstrated that serum AKR1B10 is a promising biomarker for HCC, and when used in combination with AFP can significantly improve the detection rate of HCC.

PIVKA-II combined with tumor burden score to predict long-term outcomes of AFP-negative hepatocellular carcinoma patients after liver resection.

This study aimed to establish a simple prognostic scoring model based on tumor burden score (TBS) and PIVKA-II to predict long-term outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients. 511 patients were divided into the training cohort (n = 305) and the validation cohort (n = 206) at a ratio of 6:4. Receiver operating characteristic curves (ROC) were established to identify cutoff values of TBS and PIVKA-II. Kaplan-Meier curves were used to analyze survival outcomes. The multivariable Cox regression was used to identify variables independently associated with survival outcomes. The predictive performance of the TBS-PIVKA II score (TPS) model was compared with Barcelona clinic liver cancer (BCLC) stage and American Joint Committee on Cancer (AJCC TNM) stage. The present study established the TPS model using a simple scoring system (0, 1 for low/high TBS [cutoff value: 4.1]; 0, 1 for low/high PIVKA-II [cutoff value: 239 mAU/mL]). The TPS scoring model was divided into three levels according to the summation of TBS score and PIVKA-II score: TPS 0, TPS 1, and TPS 2. The TPS scoring model was able to stratify OS (training: p < 0.001, validation: p < 0.001) and early recurrence (training: p < 0.001; validation: p = 0.001) in the training cohort and the validation cohort. The TPS score was independently associated with OS (TPS 1 vs. 0, HR: 2.28, 95% CI: 1.01-5.17; TPS 2 vs. 0, HR: 4.21, 95% CI: 2.01-8.84) and early recurrence (TPS 1 vs. 0, HR: 3.50, 95% CI: 1.71-7.16; TPS 2 vs. 0, HR: 3.79, 95% CI: 1.86-7.75) in the training cohort. The TPS scoring model outperformed BCLC stage and AJCC TNM stage in predicting OS and early recurrence in the training cohort and the validation cohort. But the TPS scoring model was unable to stratify the late recurrence in the training cohort (p = 0.872) and the validation cohort (p = 0.458). The TPS model outperformed the BCLC stage and AJCC TNM stage in predicting OS and early recurrence of AFP-negative HCC patients after liver resection, which might better assist surgeons in screening AFP-negative HCC patients who may benefit from liver resection.

Assessment of alpha-fetoprotein clinical performances in the diagnosis of the hepatocellular carcinoma at Sominé DOLO hospital of Mopti

Serum AFP as a poor clinical performance values especially when it comes to deal with the early and AFP-negative diagnostic of HCC. The aim of this work was to assess the contribution of AFP in the diagnosis of HCC. : A total of 95 subjects was enrolled a prospective observational study by consecutive enrolment and divided in two groups. The first group was made up with subjects in whom the diagnosis of HCC had been retained while the second was the control group which was free of HCC. AFP levels were performed by electrochemiluminescence immunoassay on the cobas e411. Data were captured in Excel and analyzed by Ri386 version 4.1.2 binary for macOS 10.13. The Log of median of AFP in HCC subjects was significantly greater than in non HCC subjects 6.91 ng/mL versus 1.43 ng/mL, Wilcoxon &amp;#60; 0.001. At the cut-off of 200 ng/mL, the clinical performances showed an acceptable sensitivity 97.1% CI 95% [93.7 – 100] but a poor specificity 73,8% CI 95% [64.9 – 82.6] and out of the 34 cases of HCC, one case (2.9%) was AFP-negative HCC. our data show an acceptable sensitivity but a weak specificity of AFP as a biomarker for HCC at cut-off 200 ng/mL. This suggests that AFP should be used with other biomarkers mainly for the early and AFP-negative HCC diagnosis.

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

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). 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. 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 < 5cm) (AUC = 0.886) and HBV surface antigen-positive AFPN-HCC (AUC = 0.883). 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.

A preliminary discussion on carnosine dipeptidase 1 as a potential novel biomarker for the diagnostic and prognostic evaluation of hepatocellular carcinoma

Objective: To explore carnosine dipeptidase 1 (CNDP1) potential value as a diagnostic and prognostic evaluator of hepatocellular carcinoma (HCC). Methods: A gene chip and GO analysis were used to screen the candidate marker molecule CNDP1 for HCC diagnosis. 125 cases of HCC cancer tissues, 85 cases of paracancerous tissues, 125 cases of liver cirrhosis tissues, 32 cases of relatively normal liver tissue at the extreme end of hepatic hemangioma, 66 cases from serum samples of HCC, and 82 cases of non-HCC were collected. Real-time fluorescent quantitative PCR, immunohistochemistry, western blot, and enzyme-linked immunosorbent assay were used to detect the differences in mRNA and protein expression levels of CNDP1 in HCC tissue and serum. Receiver operating characteristic (ROC) curves and Kaplan-Meier survival were used to analyze and evaluate the value of CNDP1 in the diagnosis and prognosis of HCC patients. Results: The expression level of CNDP1 was significantly reduced in HCC cancer tissues. The levels of CNDP1 were significantly lower in the cancer tissues and serum of HCC patients than those in liver cirrhosis patients and normal controls. ROC curve analysis showed that the area under the curve of serum CNDP1 in the diagnosis of HCC patients was 0.753 2 (95% CI 0.676-0.830 5), and the sensitivity and specificity were 78.79% and 62.5%, respectively. The combined detection of serum CNDP1 and serum alpha-fetoprotein (AFP) significantly improved the diagnostic accuracy (AUC = 0.820 6, 95% CI 0.753 5-0.887 8). The diagnostic sensitivity and specificity of serum CNDP1 for AFP-negative HCC patients were 73.68% and 68.75% (AUC = 0.793 1, 95% CI 0.708 8-0.877 4), respectively. In addition, the level of serum CNDP1 distinguished small liver cancer (tumor diameter < 3 cm) (AUC = 0.757 1, 95% CI 0.637 4-0.876 8). Kaplan-Meier survival analysis showed that CNDP1 was associated with a poor prognosis in HCC patients. Conclusion: CNDP1 may be a potential biomarker for the diagnostic and prognostic evaluation of HCC, and it has certain complementarity with serum AFP.

Multi-dimensional single-cell characterization revealed suppressive immune microenvironment in AFP-positive hepatocellular carcinoma

Alpha-fetoprotein (AFP)-secreting hepatocellular carcinoma (HCC), which accounts for ~75% of HCCs, is more aggressive with a worse prognosis than those without AFP production. The mechanism through which the interaction between tumors and the microenvironment leads to distinct phenotypes is not yet clear. Therefore, our study aims to identify the characteristic features and potential treatment targets of AFP-negative HCC (ANHC) and AFP-positive HCC (APHC). We utilized single-cell RNA sequencing to analyze 6 ANHC, 6 APHC, and 4 adjacent normal tissues. Integrated multi-omics analysis together with survival analysis were also performed. Further validation was conducted via cytometry time-of-flight on 30 HCCs and multiplex immunohistochemistry on additional 59 HCCs. Our data showed that the genes related to antigen processing and interferon-γ response were abundant in tumor cells of APHC. Meanwhile, APHC was associated with multifaceted immune distortion, including exhaustion of diverse T cell subpopulations, and the accumulation of tumor-associated macrophages (TAMs). Notably, TAM-SPP1+ was highly enriched in APHC, as was its receptor CD44 on T cells and tumor cells. Targeting the Spp1-Cd44 axis restored T cell function in vitro and significantly reduced tumor burden when treated with either anti-Spp1 or anti-Cd44 antibody alone or in combination with anti-Pd-1 antibody in the mouse model. Furthermore, elevated IL6 and TGF-β1 signaling contributed to the enrichment of TAM-SPP1+ in APHC. In conclusion, this study uncovered a highly suppressive microenvironment in APHC and highlighted the role of TAM-SPP1+ in regulating the immune microenvironment, thereby revealing the SPP1-CD44 axis as a promising target for achieving a more favorable immune response in APHC treatment.

HepaClear, a blood-based panel combining novel methylated CpG sites and protein markers, for the detection of early-stage hepatocellular carcinoma

BackgroundEarly screening and detection of hepatocellular carcinoma (HCC) can efficiently improve patient prognosis. We aimed to identify a series of hypermethylated DNA markers and develop a blood-based HCC diagnosis panel containing DNA methylation sites and protein markers with improved sensitivity for early-stage HCC detection.ResultsOverall, 850K methylation arrays were performed using paired tissue DNA samples from 60 HCC patients. Ten candidate hypermethylated CpG sites were selected for further evaluation by quantitative methylation-specific PCR with 60 pairs of tissue samples. Six methylated CpG sites, along with α-fetoprotein (AFP) and des-gamma-carboxyprothrombin (DCP), were assayed in 150 plasma samples. Finally, an HCC diagnosis panel, named HepaClear, was developed in a cohort consisting of 296 plasma samples and validated in an independent cohort consisting of 198 plasma samples. The HepaClear panel, containing 3 hypermethylated CpG sites (cg14263942, cg12701184, and cg14570307) and 2 protein markers (AFP and DCP), yielded a sensitivity of 82.6% and a specificity of 96.2% in the training set and a sensitivity of 84.7% and a specificity of 92.0% in the validation set. The HepaClear panel had higher sensitivity (72.0%) for early-stage HCC than AFP (≥ 20 ng/mL, 48.0%) and DCP (≥ 40 mAU/mL, 62.0%) and detected 67.5% of AFP-negative HCC patients (AFP ≤ 20 ng/mL).ConclusionsWe developed a multimarker HCC detection panel (HepaClear) that shows high sensitivity for early-stage HCC. The HepaClear panel exhibits high potential for HCC screening and diagnosis from an at-risk population.

Nomogram to predict the prognosis of patients with AFP-negative hepatocellular carcinoma undergoing chemotherapy: A SEER based study.

This study aimed to formulate reliable nomograms for predicting the outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients after chemotherapy. HCC patients with normal AFP expression who received chemotherapy were screened and evaluated from the surveillance, epidemiology, and end results database. The prognostic factors for predicting outcomes of HCC patients undergoing chemotherapy were chosen by analyzing the results of Cox analyses. Then, a nomogram integrating the prognostic factors was established. The discrimination ability of the nomogram was evaluated with computation of area under the curve (AUC) and calibration curve. A total of 2424 patients with AFP-negative HCC undergoing chemotherapy were identified. The median overall survival (OS) for HCC patients undergoing chemotherapy was 33 months. Age, race, pathologic grade, N stage, M stage, surgery, and lung metastases were significantly linked to OS. These relevant factors were incorporated into the nomogram. AUC values of the prognostic nomogram for 3- and 5-year OS were 0.696 and 0.706 in the training groups, which were superior to those of the tumor node metastasis (TNM) stage (0.641 and 0.671) in training groups. The calibration curves indicated a high consistency between the predicted probability of nomograms and the actual observation. The validation groups produced AUC values of 0.674 and 0.736 for 3- and 5-year OS, which were superior to those of the TNM stage (0.601 and 0.637) in validation groups. The results revealed significantly unfavorable OS in the high-risk group (P < .001). Nomograms to accurately predict the OS for AFP-negative HCC patients after chemotherapy were established and exhibited a more accurate predication than the conventional TNM staging system.

Prediction of Microvascular Invasion in Solitary AFP-Negative Hepatocellular Carcinoma ≤ 5 cm Using a Combination of Imaging Features and Quantitative Dual-Layer Spectral-Detector CT Parameters

AFP-negative hepatocellular carcinoma (AFPN-HCC) within 5 cm is a special subgroup of HCC. This study aimed to investigate the value of dual-layer spectral-detector CT (DLCT) and construct a scoring model based on imaging features as well as DLCT for predicting microvascular invasion (MVI) in AFPN-HCC within 5 cm. This retrospective study enrolled 104 HCC patients who underwent multiphase contrast-enhanced DLCT studies preoperatively. Combined radiological features (CR) and combined DLCT quantitative parameter (CDLCT) were constructed to predict MVI. Multivariable logistic regression was applied to identify potential predictors of MVI. Based on the coefficient of the regression model, a scoring model was developed. The predictive efficacy was assessed through ROC analysis. Microvascular invasion (MVI) was found in 28 (26.9%) AFPN-HCC patients. Among single parameters, the effective atomic number in arterial phase demonstrated the best predictive efficiency for MVI with an area under the curve (AUC) of 0.792. CR and CDLCT showed predictive performance with AUCs of 0.848 and 0.849, respectively. A risk score (RS) was calculated using the independent predictors of MVI as follows: RS=2×(mosaic architecture)+2×(corona enhancement)+2×(incomplete tumor capsule)+2×(2-trait predictor of venous invasion [TTPVI])+3×(CDLCT > -1.229). Delong's test demonstrated this scoring system could significantly improve the AUC to 0.929 compared with CR (p=0.016) and CDLCT (p=0.034). The scoring model combining radiological features with DLCT provides a promising tool for predicting MVI in solitary AFPN-HCC within 5 cm preoperatively.

Circulating the HLA-DR+ T Cell Ratio Is a Prognostic Factor for Recurrence of Patients with Hepatocellular Carcinoma after Curative Surgery.

HLA-DR+ T cell, accounting for 1.2%-5.8% of peripheral lymphocyte, is a type of activated T lymphocyte. This retrospective study aimed to evaluate the prognostic value of HLA-DR+ T cell for progression-free survival (PFS) and overall survival (OS) in hepatocellular carcinoma (HCC) patients after curative surgery. Patients and Methods. Clinicopathological data of 192 patients who underwent curative resection for hepatocellular carcinoma in the affiliated hospital of Qingdao University between January 2013 and December 2021 were collected and analyzed. Statistical tests used in this study were the chi-square test and Fisher's exact test. The prognostic value of the HLA-DR+ T cell ratio was analyzed using univariate and multivariate Cox regression analyses. The Kaplan-Meier curves were drawn by the R programming language. HCC patients were divided into high (≥5.8%) and low (<5.8%) HLADR+ T cell ratio groups. Cox regression analysis indicated that a high HLA-DR+ T cell ratio was positively related to the PFS in HCC patients (P=0.003) and AFP-positive (≥20 ng/ml) HCC patients (P=0.020). HCC patients and AFP-positive HCC patients in the high HLA-DR+ T cell ratio group were prone to have a higher T cell ratio, a higher CD8+T cell ratio, and a lower B cell ratio than the low HLA-DR+ T cell ratio group. However, the HLA-DR+ T cell ratio was not a statistically significant predictor for OS in HCC patients (P=0.57) as well as PFS (P=0.088) and OS (P=0.63) in AFP-negative HCC patients. This study confirmed that the HLA-DR+ T cell ratio was a significant predictor of PFS in HCC patients and AFP-positive HCC patients after curative surgery. This association may have guiding significance for the follow-up work of HCC patients after surgery.

Establishment and validation of nomogram model for the diagnosis of AFP-negative hepatocellular carcinoma.

As one of the most common malignant tumors in clinical practice, hepatocellular carcinoma (HCC) is a major threat to human health, where alpha-fetoprotein (AFP) is widely used for early screening and diagnoses. However, the level of AFP would not elevate in about 30-40% of HCC patients, which is clinically referred to as AFP-negative HCC, with small tumors at an early stage and atypical imaging features, making it difficult to distinguish benign from malignant by imaging alone. A total of 798 patients, with the majority being HBV-positive, were enrolled in the study and were randomized 2:1 to the training and validation groups. Univariate and multivariate binary logistic regression analyses were used to determine the ability of each parameter to predict HCC. A nomogram model was constructed based on the independent predictors. A unordered multicategorical logistic regression analyses showed that the age, TBIL, ALT, ALB, PT, GGT and GPR help identify non-hepatic disease, hepatitis, cirrhosis, and hepatocellular carcinoma. A multivariate logistic regression analyses showed that the gender, age, TBIL, GAR, and GPR were independent predictors for the diagnosis of AFP-negative HCC. And an efficient and reliable nomogram model (AUC=0.837) was constructed based on independent predictors. Serum parameters help reveal intrinsic differences between non-hepatic disease, hepatitis, cirrhosis, and HCC. The nomogram based on clinical and serum parameters could be used as a marker for the diagnosis of AFP-negative HCC, providing an objective basis for the early diagnosis and individualized treatment of hepatocellular carcinoma patients.

Characterization of Circulating Tumor Cells Using Imaging Flow Cytometry in Liver Disease Patients

Hepatocellular carcinoma (HCC) is asymptomatic at an early stage which delays its timely diagnosis and treatment. Circulating tumor cells (CTCs), derived from a primary or secondary tumor, may help in the management of HCC. Here, we evaluate and characterize CTCs in liver disease patients. In total, 65 patients, categorized into liver cirrhosis (LC) (n=30) and HCC (n=35), were enrolled. Using ImagestreamX MkII imaging flow cytometer, CTCs were detected and characterized using biomarker expression of EpCAM, CK, AFP, CD45, and DRAQ5 in LC and HCC patients. CTCs were detected in 33/35 (94%) HCC patients and in 28/30 (93%) LC patients. In the HCC group, the number of biomarker-positive CTCs was higher in BCLC stage D when compared with others. EpCAM+CK was the most expressed biomarker on CTCs in LC versus HCC (83.3% vs. 77.14%), followed by AFP (80% vs. 65.71%), EpCAM (30% vs. 28.57%), and CK (16.6% vs. 14.28%). The EpCAM cell area was significantly associated (P value=0.031) with the CTC-positive status. The combination biomarker expression of CTCs cell area (EpCAM, CK, and AFP) performed well with the area under the curve of 0.92, high sensitivity, and specificity in detecting early-stage and AFP-negative HCC as well as in AFP-negative LC cases. Enumeration and cell area of CTCs may be used as a biomarker for early detection of HCC and guiding treatment.

Metabolomic biomarkers for the diagnosis and post-transplant outcomes of AFP negative hepatocellular carcinoma.

Early diagnosis for α-fetoprotein (AFP) negative hepatocellular carcinoma (HCC) remains a critical problem. Metabolomics is prevalently involved in the identification of novel biomarkers. This study aims to identify new and effective markers for AFP negative HCC. In total, 147 patients undergoing liver transplantation were enrolled from our hospital, including liver cirrhosis patients (LC, n=25), AFP negative HCC patients (NEG, n=44) and HCC patients with AFP over 20 ng/mL (POS, n=78). 52 Healthy volunteers (HC) were also recruited in this study. Metabolomic profiling was performed on the plasma of those patients and healthy volunteers to select candidate metabolomic biomarkers. A novel diagnostic model for AFP negative HCC was established based on Random forest analysis, and prognostic biomarkers were also identified. 15 differential metabolites were identified being able to distinguish NEG group from both LC and HC group. Random forest analysis and subsequent Logistic regression analysis showed that PC(16:0/16:0), PC(18:2/18:2) and SM(d18:1/18:1) are independent risk factor for AFP negative HCC. A three-marker model of Metabolites-Score was established for the diagnosis of AFP negative HCC patients with an area under the time-dependent receiver operating characteristic curve (AUROC) of 0.913, and a nomogram was then established as well. When the cut-off value of the score was set at 1.2895, the sensitivity and specificity for the model were 0.727 and 0.92, respectively. This model was also applicable to distinguish HCC from cirrhosis. Notably, the Metabolites-Score was not correlated to tumor or body nutrition parameters, but difference of the score was statistically significant between different neutrophil-lymphocyte ratio (NLR) groups (≤5 vs. >5, P=0.012). Moreover, MG(18:2/0:0/0:0) was the only prognostic biomarker among 15 metabolites, which is significantly associated with tumor-free survival of AFP negative HCC patients (HR=1.160, 95%CI 1.012-1.330, P=0.033). The established three-marker model and nomogram based on metabolomic profiling can be potential non-invasive tool for the diagnosis of AFP negative HCC. The level of MG(18:2/0:0/0:0) exhibits good prognosis prediction performance for AFP negative HCC.