AFP-negative Hepatocellular Carcinoma Patients Research Articles

Lasso-Cox interpretable model of AFP-negative hepatocellular carcinoma.

In AFP-negative hepatocellular carcinoma patients, markers for predicting tumor progression or prognosis are limited. Therefore, our objective is to establish an optimal predicet model for this subset of patients, utilizing interpretable methods to enhance the accuracy of HCC prognosis prediction. We recruited a total of 508 AFP-negative HCC patients in this study, modeling with randomly divided training set and validated with validation set. At the same time, 86 patients treated in different time periods were used as internal validation. After comparing the cox model with the random forest model based on Lasso regression, we have chosen the former to build our model. This model has been interpreted with SHAP values and validated using ROC, DCA. Additionally, we have reconfirmed the model's effectiveness by employing an internal validation set of independent periods. Subsequently, we have established a risk stratification system. The AUC values of the Lasso-Cox model at 1, 2, and 3years were 0.807, 0.846, and 0.803, and the AUC values of the Lasso-RSF model at 1, 2, and 3years were 0.783, 0.829, and 0.776. Lasso-Cox model was finally used to predict the prognosis of AFP-negative HCC patients in this study. And BCLC stage, gamma-glutamyl transferase (GGT), diameter of tumor, lung metastases (LM), albumin (ALB), alkaline phosphatase (ALP), and the number of tumors were included in the model. The validation set and the separate internal validation set both indicate that the model is stable and accurate. Using risk factors to establish risk stratification, we observed that the survival time of the low-risk group, the middle-risk group, and the high-risk group decreased gradually, with significant differences among the three groups. The Lasso-Cox model based on AFP-negative HCC showed good predictive performance for liver cancer. SHAP explained the model for further clinical application.

Development of a diagnostic nomogram for alpha-fetoprotein-negative hepatocellular carcinoma based on serological biomarkers.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Serum biomarkers play an important role in the early diagnosis and prognosis of HCC. Because a certain percentage of HCC patients are negative for alpha-fetoprotein (AFP), the diagnosis of AFP-negative HCC is essential to improve the detection rate of HCC. To establish an effective model for diagnosing AFP-negative HCC based on serum tumour biomarkers. A total of 180 HCC patients were enrolled in this study. The expression levels of GP73, des-γ-carboxyprothrombin (DCP), CK18-M65, and CK18-M30 were detected by a fully automated chemiluminescence analyser. The variables were selected by logistic regression analysis. Several models were constructed using stepwise backward logistic regression. The performance of the models was compared using the C statistic, integrated discrimination improvement, net reclassification improvement, and calibration curves. The clinical utility of the nomogram was assessed using decision curve analysis (DCA). The results showed that the expression levels of GP73, DCP, CK18-M65, and CK18-M30 were significantly greater in AFP-negative HCC patients than in healthy controls (P < 0.001). Multivariate logistic regression analysis revealed that GP73, DCP, and CK18-M65 were independent factors for diagnosing AFP-negative HCC. By comparing the diagnostic performance of multiple models, we included GP73 and CK18-M65 as the model variables, and the model had good discrimination ability (area under the curve = 0.946) and good goodness of fit. The DCA curves indicated the good clinical utility of the nomogram. Our study identified GP73 and CK18-M65 as serum biomarkers with certain application value in the diagnosis of AFP-negative HCC. The diagnostic nomogram based on CK18-M65 combined with GP73 demonstrated good performance and effectively identified high-risk groups of patients with HCC.

Radiomics model based on contrast-enhanced computed tomography imaging for early recurrence monitoring after radical resection of AFP-negative hepatocellular carcinoma

BackgroundAlthough radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. Emerging radiomics can reveal subtle structural changes in tumors by analyzing preoperative contrast-enhanced computer tomography (CECT) imaging data and may provide new ways to predict early recurrence (recurrence within 2 years) in AFP-negative HCC. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.Patients and methodsPatients with AFP-negative HCC who underwent radical resection were included in this study. A computerized tool was used to extract radiomic features from the tumor region of interest (ROI), select the best radiographic features associated with patient’s postoperative recurrence, and use them to construct the radiomics score (RadScore), which was then combined with clinical and follow-up information to comprehensively evaluate the reliability of the model.ResultsA total of 148 patients with AFP-negative HCC were enrolled in this study, and 1,977 radiographic features were extracted from CECT, 2 of which were the features most associated with recurrence in AFP-negative HCC. They had good predictive ability in both the training and validation cohorts, with an area under the ROC curve (AUC) of 0.709 and 0.764, respectively. Tumor number, microvascular invasion (MVI), AGPR and radiomic features were independent risk factors for early postoperative recurrence in patients with AFP-negative HCC. The AUCs of the integrated model in the training and validation cohorts were 0.793 and 0.791, respectively. The integrated model possessed the clinical value of predicting early postoperative recurrence in patients with AFP-negative HCC according to decision curve analysis, which allowed the classification of patients into subgroups of high-risk and low-risk for early recurrence.ConclusionThe nomogram constructed by combining clinical and imaging features has favorable performance in predicting the probability of early postoperative recurrence in AFP-negative HCC patients, which can help optimize the therapeutic decision-making and prognostic assessment of AFP-negative HCC patients.

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.

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.

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.

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.

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.

Inflammation-Related Marker NrLR Predicts Prognosis in AFP-Negative HCC Patients After Curative Resection.

The role of inflammation-related markers in alpha-fetoprotein (AFP) negative hepatocellular carcinoma (HCC) is not well known. This study aimed to investigate the clinical significance of inflammation-related markers in AFP-negative HCC patients after curative resection. One thousand one hundred and seventy-nine AFP-negative HCC patients after curative resection were included. Survival rate and prognostic analysis were performed using Kaplan-Meier and Cox regression analysis. Propensity score matching (PSM) was used for patient selection. Multivariate Cox regression showed that neutrophil times γ-glutamyl transpeptidase to lymphocyte ratio (NrLR) was the independent risk factor associated with OS (p = 0.002) and RFS (p = 0.017). Low NrLR groups (n = 628) had lower rates of albumin-bilirubin (ALBI) grade 2 (p < 0.001), lower rates of bleeding and blood transfusion (p < 0.001) than high NrLR groups. Considering tumor features, low NrLR groups had lower AFP levels (p < 0.001), smaller tumor size (p < 0.001), and lower rates of Edmondson grade III-IV (p = 0.024) than high NrLR groups. After PSM, the 1-year, 3 year-, and 5-year OS rates in the low NrLR and high NrLR groups were 96.3%, 86.9%, 64.9%, and 91.4%, 76.7%, 59.5% (p < 0.001), respectively. The 1-year, 3-year, and 5-year RFS rates in the low NrLR and high NrLR groups were 80.0%, 62.9%, 47.5%, and 71.7%, 52.6%, 39.5% (p < 0.001), respectively. NrLR was a poor prognostic factor for mortality and tumor recurrence in AFP-negative HCC patients after curative resection. The simple and low-cost marker could help physician to determine patients at high risk of tumor recurrence for frequent clinical surveillance.

Nomogram Based on Platelet-Albumin-Bilirubin for Predicting Tumor Recurrence After Surgery in Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Patients.

In this study, we developed a nomogram based on the platelet-albumin-bilirubin (PALBI) score to predict recurrence-free survival (RFS) after curative resection in alpha-fetoprotein (AFP)-negative (≤20 ng/mL) hepatocellular carcinoma (HCC) patients. A total of 194 pathologically confirmed AFP-negative HCC patients were retrospectively analyzed. Univariate and multivariate Cox regression analyses were performed to screen the independent risk factors associated with RFS, and a nomogram prediction model for RFS was established according to the independent risk factors. The receiver operating characteristic (ROC) curve and the C-index were used to evaluate the accuracy and the efficacy of the model prediction. The correction curve was used to assess the calibration of the prediction model, and decision curve analysis was performed to evaluate the clinical application value of the prediction model. PALBI score, MVI, and tumor size were independent risk factors for postoperative tumor recurrence (P < 0.05). A nomogram prediction model based on the independent predictive factors was developed to predict RFS, and it achieved a good C-index of 0.704 with an area under the ROC curve of 0.661 and the sensitivity was 73.2%. Patients with AFP-negative HCC could be divided into the high-risk group or the low-risk group by the risk score calculated by the nomogram, and there was a significant difference in RFS between the two groups (P < 0.05). Decision curve analysis (DCA) showed that the nomogram increased the net benefit in predicting the recurrence of AFP-negative HCC and exhibited a wider range of threshold probabilities than the independent risk factors (PALBI score, MVI, and tumor size) by risk stratification. The nomogram based on the PALBI score can predict RFS after curative resection in AFP-negative HCC patients and can help clinicians to screen out high-risk patients for early intervention.

The combination of serum oligosaccharide chain (G-test), alpha-fetoprotein, and aspartate aminotransferase to alanine aminotransferase ratio provides the optimal diagnostic value for early detection of hepatocellular carcinoma

BackgroundThe purpose of this study was to compare the diagnostic value of serum oligosaccharide chain (G-test), alpha-fetoprotein (AFP) and aspartic aminotransferase to alanine aminotransferase ratios (AAR), both alone and in combination, for predicting hepatocellular carcinoma (HCC) onset.MethodsBetween Januarys 2020–2022, 152 subjects admitted to the First Affiliated Hospital of Nanchang University was enrolled in this study, of which 77 had HCC, 18 chronic hepatitis (CH), 37 liver cirrhosis (LC) and 20 were healthy. Data for patient characteristics were collected, and differences between groups were analyzed by either Mann-Whitney U or χ2 tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of AFP, G-test, and AAR for HCC.ResultsG-test, AFP, and AAR were all found to have close correlations with HCC among the different patient groups, with G-test being the most predictive for HCC among healthy and CL patients, as represented by respective areas under the curve (AUC) of 0.953 and 0.792 (P < 0.001). By contrast, AAR had the greatest diagnostic ability for HCC among CH patients (AUC = 0.850; P < 0.001). However, the combination of all 3 biomarkers obtained the most optimal results for predicting HCC onset, in terms of predictive capability for all 3 non-HCC patient groups, yielding AUCs of 0.958, 0.898, and 0.808 (P < 0.001) for, respectively, healthy, CH, and LC patients. Additionally, AFP had higher specificity, but lower sensitivity, with increased threshold values, as the recommended threshold of AFP ≥ 400 ng/mL yielded a missed diagnosis rate of 72.7%. For AFP-negative HCC (AFP-NHCC) patients, G-test alone had the greatest diagnostic capability (AUC = 0.855; P < 0.001), sensitivity (83.8%), and specificity (87.5%).ConclusionG-test has the greatest diagnostic capability for HCC and AFP-NHCC, with high sensitivity and specificity, among healthy and LC patients. However, AAR had the highest diagnostic capability and sensitivity for HCC in CH. Overall, though, the combination of G-test, AFP and AAR provided the most optimal outcomes for predicting HCC onset, no matter the patient pre-conditions.

Long non-coding RNA LINC01793 as a potential diagnostic biomarker of hepatitis B virus-related hepatocellular carcinoma

BackgroundThere is growing evidence that long non-coding RNAs (lncRNAs) play important roles in the progression of hepatocellular carcinoma (HCC) and may serve as diagnostic markers. This study investigates the diagnostic efficiency of the long intergenic non-protein-coding RNA 1793 (LINC01793) in hepatitis B virus (HBV)-related HCC. MethodsBioinformatics methods were used to screen the aberrantly expressed lncRNAs in HCC tissues based on The Cancer Genome Atlas (TCGA). Quantitative reverse transcription polymerase chain reaction was performed to assess the expression of the candidate lncRNAs in tissues, cells and whole blood samples of patients with HBV-related HCC, liver cirrhosis (LC), chronic hepatitis (CHB), and healthy controls. Then, the correlations between LINC01793 and clinical characteristics were analyzed. Finally, the diagnostic value of LINC01793 was explored based on the receiver operating characteristic curve. ResultsLINC01793 was remarkably upregulated in the HCC tissues and cells. It was highly expressed in the whole blood of the HBV-related HCC patients, unlike in that of the healthy controls and of the CHB and LC patients. Subsequent analysis revealed that high LINC01793 was related to the Barcelona Clinic Liver Cancer (P = 0.007), tumor invasion (P = 0.042), the number of tumors (P = 0.031) and serum level of alanine aminotransferase(p = 0.022). The areas under the curve of LINC01793, for distinguishing HCC from healthy controls, CHB and LC patients, were 0.824, 0.767 and 0.756, respectively. In addition, the combination of LINC01793 with alpha fetoprotein (AFP) had a stronger diagnostic value than LINC01793 or AFP alone in AFP-negative HCC patients. ConclusionHigh expression of LINC01793 is correlated with adverse clinical characteristics and can serve as a non-invasive biomarker of HCC.

4210\xa0Da and 1866\xa0Da polypeptides as potential biomarkers of liver disease progression in hepatitis B virus patients

HBV infection is recognized as a serious global health problem, and hepatitis B virus infection is a complicated chronic disease leading to liver cirrhosis (LC) and hepatocellular carcinoma (HCC). New biochemical serum markers could be used to advance the diagnosis and prognosis of HBV-associated liver diseases during the progression of chronic hepatitis B into cirrhosis and HCC. We determined whether the 4210 Da and 1866 Da polypeptides are serum metabolite biomarkers of hepatopathy with hepatitis B virus. A total of 570 subjects were divided into five groups: healthy controls, those with natural clearance, and patients with CHB, LC, and HCC. The 1866 Da and 4210 Da polypeptides were measured by Clin-ToF II MALDI-TOF–MS. There were significant differences in 4210 Da and 1866 Da levels among the five groups (P < 0.001). For the differential diagnosis of CHB from normal liver, the areas under the receiver operating characteristic (ROC) curve of 4210 Da and 1866 Da and their combination via logistic regression were 0.961, 0.849 and 0.967. For the differential diagnosis of LC from CHB, the areas under the ROC curve were 0.695, 0.841 and 0.826. For the differential diagnosis of HCC from CHB, the areas under the ROC curve were 0.744, 0.710 and 0.761, respectively. For the differential diagnosis of HCC from LC, the areas under the ROC curve of 4210 Da and 1866 Da were 0.580 and 0.654. The positive rate of 1866 Da was 45.5% and 69.0% in AFP-negative HCC patients and that of 4210 Da was 60.6% 58.6% in AFP-negative HCC patients of the study HCC vs. CHB and HCC vs. LC. The 4210 Da and 1866 Da polypeptide levels were positively correlated with HBV DNA levels (P < 0.001, r = 0.269; P < 0.001, r = 0.285). The 4210 Da and 1866 Da polypeptides had good diagnostic value for the occurrence and progression of HBV-related chronic hepatitis, liver cirrhosis and hepatocellular carcinoma and could serve to accurately guide treatment management and predict clinical outcomes.

Noninvasive Detection of Hepatocellular Carcinoma with Circulating Tumor DNA Features and α-Fetoprotein

Liver cancer is the fifth-most common cancer worldwide, with the third-highest rate of cancer-related mortality. Hepatocellular carcinoma (HCC) is the leading pathologic subtype, contributing 85% to 90% of cases of primary liver cancer. Most HCC patients are diagnosed at an advanced stage at which treatment is not curative. This study assessed the performance of a newly developed blood-based assay that utilizes genomic features and protein markers for the early detection of HCC. Two cancer-associated hallmarks, copy-number aberrations (CNA) and fragment size (FS), were characterized by shallow whole-genome sequencing of cell-free DNA and utilized to differentiate cancer patients from healthy subjects. As a clinically implemented biomarker of HCC, plasma α-fetoprotein (AFP) was also used with the genomic surrogates to optimize the detection of HCCs. The sensitivity of AFP ≥20.0 μg/L in detecting HCC was 57.9%. The combined genomic classifier CNA + FS via cell-free DNA shallow whole-genome sequencing identified nearly half of AFP-negative HCC patients (43.8%). By integrating CNA, FS as well as AFP (HCCseek), 75.0% sensitivity was achieved at 98.0% specificity, resulting in 92.6% accuracy, with 58.6% sensitivity in stage I HCC. The quantitative output of HCCseek was correlated with the severity of the disease (tumor size, stage, and recurrence-free survival). In summary, this study describes an efficient, noninvasive, and cost-effective method to detect HCC.

Analysis of Serum Paraoxonase 1 Using Mass Spectrometry and Lectin Immunoassay in Patients With Alpha-Fetoprotein Negative Hepatocellular Carcinoma.

The diagnosis of AFP (alpha-fetoprotein)-negative HCC (hepatocellular carcinoma) mostly relies on imaging and pathological examinations, and it lacks valuable and practical markers. Protein N-glycosylation is a crucial post-translation modifying process related to many biological functions in an organism. Alteration of N-glycosylation correlates with inflammatory diseases and infectious diseases including hepatocellular carcinoma. Here, serum N-linked intact glycopeptides with molecular weight (MW) of 40–55 kDa were analyzed in a discovery set (n = 40) including AFP-negative HCC and liver cirrhosis (LC) patients using label-free quantification methodology. Quantitative lens culinaris agglutin (LCA) ELISA was further used to confirm the difference of glycosylation on serum PON1 in liver diseases (n = 56). Then, the alteration of site-specific intact N-glycopeptides of PON1 was comprehensively assessed by using Immunoprecipitation (IP) and mass spectrometry based 16O/18O C-terminal labeling quantification method to distinguish AFP-negative HCC from LC patients in a validation set (n = 64). Totally 195 glycopeptides were identified using a dedicated search engine pGlyco. Among them, glycopeptides from APOH, HPT/HPTR, and PON1 were significantly changed in AFP-negative HCC as compared to LC. In addition, the reactivity of PON1 with LCA in HCC patients with negative AFP was significantly elevated than that in cirrhosis patients. The two glycopeptides HAN253WTLTPLK (H5N4S2) and (H5N4S1) corresponding to PON1 were significantly increased in AFP-negative HCC patients, as compared with LC patients. Variations in PON1 glycosylation may be associated with AFP-negative HCC and might be helpful to serve as potential glycomic-based biomarkers to distinguish AFP-negative HCC from cirrhosis.

Combination of serum paraoxonase/arylesterase 1 and antithrombin-III is a promising non-invasion biomarker for discrimination of AFP-negative HCC versus liver cirrhosis patients

α-fetoprotein is often used in the diagnosis of hepatocellular carcinoma (HCC). However, there are currently less efficient and highly specific biomarkers to distinguish AFP-negative HCC from liver cirrhosis (LC) patients. We retrospectively analyzed the data of patients who were treated in our hospitals. iTRAQ coupled with mass spectrometry was used to identify candidate serum proteins in a discovery set (n = 36) including AFP-negative HCC and LC patients. After Western blot detection, potential serum biomarkers were confirmed using ELISA in a validation set (n = 90). The diagnostic performance of the selected proteins was assessed using receiver operating characteristic (ROC). PON1 and ATIII were selected as target proteins and were significantly higher in LC than those in AFP-negative HCC patients as validated by Western blot and ELISA, which was consistent with the result of iTRAQ. The AUC was 0.848 as PON1 and ATIII were combined (sensitivity: 80.0%; specificity: 73.3%), and performed much better than that of a single biomarker. These findings suggest that PON1 and ATIII have the potential to serve as effective biomarkers for distinguishing AFP-negative HCC from cirrhosis.

The Diagnostic Value of Serum PIVKA-II Alone or in Combination with AFP in Chinese Hepatocellular Carcinoma Patients.

Background At present, the diagnostic accuracy of alpha-fetoprotein (AFP) for hepatocellular carcinoma (HCC) surveillance is insufficient. It remains controversial whether prothrombin induced by vitamin K absence II (PIVKA-II) has a better diagnostic value than AFP for HCC patients. Objective To investigate the diagnostic role of PIVKA-II alone or in combination with AFP in Chinese HCC patients. Methods Serum AFP and PIVKA-II levels were detected and analyzed in 308 HCC afflicted patients and 120 unafflicted controls. The receiver operator curve (ROC) and area under the curve (AUC) were conducted to evaluate the clinical value of AFP and PIVKA-II for diagnosing HCC and early HCC. Results In the whole HCC cohort, the diagnostic values of PIVKA-II were better than that of AFP. The AUC of PIVKA-II and AFP was 0.90 (95% CI 0.87-0.94) and 0.79 (95% CI 0.74-0.84), respectively. “AFP + PIVKA-II” yielded a high sensitivity of 95.1% and a specificity of 83.3%, with the AUC 0.89 (95% CI 0.85-0.93). In the early stage HCC group, the diagnostic accuracy of PIVKA-II was also better than that of AFP. The AUC of PIVKA-II and AFP was 0.83 (95% CI 0.77-0.89) and 0.75 (95% CI 0.68-0.81), respectively. “AFP + PIVKA-II” achieved the sensitivity of 83.3% and specificity of 89.1%, with an AUC of 0.86 (95% CI 0.81-0.91). Moreover, for AFP-negative HCC patients, serum PIVKA-II showed good diagnostic performance, with an AUC of 0.804 (95% CI 0.720-0.887). Besides, elevated PIVKA-II level was a strong independent risk factor for HCC patients with portal vein tumor thrombus (PVTT) (OR = 4.890, P = 0.020). Conclusion PIVKA-II is superior to AFP in HCC screening, and AFP in combination with PIVKA-II significantly improves the diagnostic value for Chinese HCC patients. PIVKA-II could effectively indicate HCC accompanied by PVTT and help to optimize the therapeutic strategy.