Clinical value of serum AFP and PIVKA-II for diagnosis, treatment and prognosis of hepatocellular carcinoma

Construction and evaluation of a liver cancer risk prediction model based on machine learning

BACKGROUND

Liver cancer is one of the most prevalent malignant tumors worldwide, and its early detection and treatment are crucial for enhancing patient survival rates and quality of life. However, the early symptoms of liver cancer are often not obvious, resulting in a late-stage diagnosis in many patients, which significantly reduces the effectiveness of treatment. Developing a highly targeted, widely applicable, and practical risk prediction model for liver cancer is crucial for enhancing the early diagnosis and long-term survival rates among affected individuals.

AIM

To develop a liver cancer risk prediction model by employing machine learning techniques, and subsequently assess its performance.

METHODS

In this study, a total of 550 patients were enrolled, with 190 hepatocellular carcinoma (HCC) and 195 cirrhosis patients serving as the training cohort, and 83 HCC and 82 cirrhosis patients forming the validation cohort. Logistic regression (LR), support vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO) regression models were developed in the training cohort. Model performance was assessed in the validation cohort. Additionally, this study conducted a comparative evaluation of the diagnostic efficacy between the ASAP model and the model developed in this study using receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) to determine the optimal predictive model for assessing liver cancer risk.

RESULTS

Six variables including age, white blood cell, red blood cell, platelet counts, alpha-fetoprotein and protein induced by vitamin K absence or antagonist II levels were used to develop LR, SVM, RF, and LASSO regression models. The RF model exhibited superior discrimination, and the area under curve of the training and validation sets was 0.969 and 0.858, respectively. These values significantly surpassed those of the LR (0.850 and 0.827), SVM (0.860 and 0.803), LASSO regression (0.845 and 0.831), and ASAP (0.866 and 0.813) models. Furthermore, calibration and DCA indicated that the RF model exhibited robust calibration and clinical validity.

CONCLUSION

The RF model demonstrated excellent prediction capabilities for HCC and can facilitate early diagnosis of HCC in clinical practice.

Diagnostic value and clinical significance of serum miR-4534 combined with transvaginal color Doppler ultrasound in cervical cancer

AIM

The purpose of the present study was to evaluate the diagnostic performance of serum miR-4534 combined with Transvaginal Color Doppler Ultrasound (TVCDS) in cervical cancer patients.

METHODS

Blood samples from 126 patients with cervical cancer and 83 patients with benign uterine lesions were retrospectively analyzed. Quantitative real time polymerase chain reaction (qRT-PCR) was applied to examine the relative abundances of serum miR-4534 in cervical cancer based on a case-control study. Chi-square test was adopted to analyze the association between serum miR-4534 and other clinicopathological factors. The blood flow of cervix was examined using TVCDS, and the blood flow resistance index (RI) of cervix was summarized. Receiver operating characteristic (ROC) curves were plotted to explore the diagnostic capacity of serum miR-4534 combined with blood flow RI. Logistic regression was employed to analyze the risk factors of cervical cancer.

RESULTS

Serum miR-4534 was distinctly increased in the study group compared with the control group (P < 0.05), while blood flow RI was dramatically decreased (P < 0.05). Moreover, increased miR-4534 was closely associated with lymph node metastasis (P = 0.010), FIGO stage (P = 0.007) and HR-HPV (P = 0.025). ROC curves demonstrated that the area under curve (AUC) of serum miR-4534 combined with the blood flow RI was 0.854, with the sensitivity and specificity of 88.9% and 73.5%, respectively, which displayed a better diagnostic capacity than serum miR-4534 and blood flow RI alone. Logistic regression analysis demonstrated that serum miR-4534 (OR = 8.805, 95% CI = 4.124-18.798; P < 0.001) was a risk factor related to the initiation and formation of cervical cancer, as well as blood flow RI (OR = 0.112; 95% CI = 0.054-0.235; P < 0.001).

CONCLUSION

Serum miR-4534 was highly expressed in cervical cancer, and associated with the development and metastasis of cervical cancer patients. MiR-4534 combined with TVCDS exhibited a considerable biomarker to detect cervical cancer patients.

Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram

PURPOSE

To develop a nomogram using clinical features and the MRI parameters for preoperatively predicting the expression of Ki-67 in patients with hepatocellular carcinoma (HCC).

METHODS

One hundred and forty patients (training cohorts: n = 108; validation cohorts: n = 32) with confirmed HCC were investigated. Mann-Whitney U test, independent sample t-test, and chi-squared test were used to analyze the continuous and categorical variables. Univariate and multivariate logistic regression analyses were performed to examine the clinical variables and parameters from MRI associated with Ki-67 expression. As a result, a nomogram was developed based on these associations in patients with HCC. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.

RESULTS

In the training set, multivariable logistic regression analysis revealed that lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) levels, protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels, and tumor shape were independent predictors for Ki-67 expression (p < 0.05). These three variables and the apparent diffusion coefficient (ADC) value were used to establish a nomogram, while the ADC value was found to be a marginal significant predictor. The model demonstrated a strong ability to discriminate Ki-67 expression in both the training and validation cohorts (AUC = 0.862, 0.877).

CONCLUSION

A non-invasive preoperative prediction method, which incorporates MRI variables and clinical features was developed, and showed effectiveness in evaluating Ki-67 expression in HCC patients.

Drug Repurposing Approach to Identify Candidate Drug Molecules for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, with a high mortality rate due to the limited therapeutic options. Systemic drug treatments improve the patient's life expectancy by only a few months. Furthermore, the development of novel small molecule chemotherapeutics is time-consuming and costly. Drug repurposing has been a successful strategy for identifying and utilizing new therapeutic options for diseases with limited treatment options. This study aims to identify candidate drug molecules for HCC treatment through repurposing existing compounds, leveraging the machine learning tool MDeePred. The Open Targets Platform, UniProt, ChEMBL, and Expasy databases were used to create a dataset for drug target interaction (DTI) predictions by MDeePred. Enrichment analyses of DTIs were conducted, leading to the selection of 6 out of 380 DTIs identified by MDeePred for further analyses. The physicochemical properties, lipophilicity, water solubility, drug-likeness, and medicinal chemistry properties of the candidate compounds and approved drugs for advanced stage HCC (lenvatinib, regorafenib, and sorafenib) were analyzed in detail. Drug candidates exhibited drug-like properties and demonstrated significant target docking properties. Our findings indicated the binding efficacy of the selected drug compounds to their designated targets associated with HCC. In conclusion, we identified small molecules that can be further exploited experimentally in HCC therapeutics. Our study also demonstrated the use of the MDeePred deep learning tool in in silico drug repurposing efforts for cancer therapeutics.

Clinical application of serum CST4 combined with tumor markers in the diagnosis of digestive system malignant tumors

The aim of the present study was to evaluate the diagnostic value of plasma human cystatin-S (CST4) in patients with digestive system malignant tumors. CST4 and tumor markers, such as α-fetoprotein (AFP), carcinoembryonic antigen (CEA), carbohydrate antigen (CA)199, CA125, CA153 and CA724, were detected in blood samples from 100 patients with a digestive system malignant tumor and 100 patients with benign digestive system diseases. The tumor markers AFP, CEA, CA199, CA125, CA153 and CA724 were detected using an electrochemiluminescence immunoassay, and CST4 levels were detected using a human CST4 ELISA kit. The results demonstrated that the sensitivities of AFP and CA153 (both 5.00%) were significantly lower than that of CST4 (38.00%) in the diagnosis of digestive system malignancy (P<0.001), and CA724 (18.00%) was also less sensitive than CST4 (P<0.05). The sensitivities of CA199 (26.00%), CEA (31.00%) and CA125 (25.00%) were similar to that of CST4 (P>0.05). There was no significant difference in the CEA, CA125, CA724 and CST4 specificities (P>0.05), which were 91.00, 95.00, 94.00 and 83.00%, respectively. The specificities of AFP (99.00%), CA199 (98.00%) and CA153 (100.00%) were significantly higher than that of CST4 (P<0.01). By constructing a receiver operating characteristic curve and comparing the area under the curve as well as sensitivity, the findings of the present study demonstrated that combining CST4 with AFP, CEA, CA199, CA125, CA153 and CA724 can significantly enhance the diagnostic sensitivity for malignancies of the digestive system. However, the introduction of CST4 into the traditional diagnostic groups (CEA + AFP, CA199 + CA125 + CA153 + CA724 and AFP + CEA + CA199 + CA125 + CA153 + CA724) resulted in an increased sensitivity and loss of specificity, thereby not offering significant advantages in terms of comprehensive diagnostic efficiency compared with the traditional diagnostic groups. In conclusion, CST4 detection may be a promising diagnostic tool. Nonetheless, the potential false positive results in tumor diagnosis should be taken into consideration when developing new diagnostic groups involving CST4.

Nomograms established for predicting microvascular invasion and early recurrence in patients with small hepatocellular carcinoma

BACKGROUND

In this study, we aimed to establish nomograms to predict the microvascular invasion (MVI) and early recurrence in patients with small hepatocellular carcinoma (SHCC), thereby guiding individualized treatment strategies for prognosis improvement.

METHODS

This study retrospectively analyzed 326 SHCC patients who underwent radical resection at Wuhan Union Hospital between April 2017 and January 2022. They were randomly divided into a training set and a validation set at a 7:3 ratio. The preoperative nomogram for MVI was constructed based on univariate and multivariate logistic regression analysis, and the prognostic nomogram for early recurrence was constructed based on univariate and multivariate Cox regression analysis. We used the receiver operating characteristic (ROC) curves, area under the curves (AUCs), and calibration curves to estimate the predictive accuracy and discriminability of nomograms. Decision curve analysis (DCA) and Kaplan-Meier survival curves were employed to further confirm the clinical effectiveness of nomograms.

RESULTS

The AUCs of the preoperative nomogram for MVI on the training set and validation set were 0.749 (95%CI: 0.684-0.813) and 0.856 (95%CI: 0.805-0.906), respectively. For the prognostic nomogram, the AUCs of 1-year and 2-year RFS respectively reached 0.839 (95%CI: 0.775-0.903) and 0.856 (95%CI: 0.806-0.905) in the training set, and 0.808 (95%CI: 0.719-0.896) and 0.874 (95%CI: 0.804-0.943) in the validation set. Subsequent calibration curves, DCA analysis and Kaplan-Meier survival curves demonstrated the high accuracy and efficacy of the nomograms for clinical application.

CONCLUSIONS

The nomograms we constructed could effectively predict MVI and early recurrence in SHCC patients, providing a basis for clinical decision-making.

Diagnostic accuracy of serum protein induced by vitamin K absence (PIVKA-II), serum a-fetoprotein and their combination for hepatocellular carcinoma among Caucasian cirrhotic patients with diagnostic or non-diagnostic serum a-fetoprotein levels

AIM

The aim of our study was to evaluate the accuracy of serum biomarkers (AFP/PIVKA-II) and their combination in HCC diagnosis among Caucasian cirrhotic patients.

METHODS

Serum AFP/PIVKA-II levels were evaluated in 218 cirrhotics (163 males, 118 CTP-A, 66 ALBI-I, 111 with varices, 63 with diabetes) with (n = 90) or without (n = 128) HCC. Patients with HCC were categorized to BCLC Stage 0/A (n = 12), B (n = 21), C (n = 48), and D (n = 9).

RESULTS

The two groups were comparable for all baseline parameters except for age, platelets, and diabetes presence. Median levels of AFP (239.1 vs. 4.0 ng/mL) and PIVKA-II (4082.7 vs. 45.8 mAU/mL) were both significantly higher in HCC group compared to controls (p < 0.001). AUROC and cutoff value for HCC diagnosis were 88%/12.35 ng/mL (AFP) and 84.4%/677.13 mAU/mL (PIVKA-II), whereas their combination showed better diagnostic accuracy (AUROC = 90.2%). The diagnostic accuracy of each biomarker separately was moderate or good in BCLC-0/A/B and was excellent only for BCLC-C patients (AFP: AUROC = 94.3%, cutoff = 12.35 ng/mL and PIVKA-II: 91.3%, 253.51 mAU/mL) whereas their combination presented quite acceptable results in BCLC-B (AUROC = 92.4%) and BCLC-C (AUROC = 95.7%). Excluding HCC patients with high AFP (above 400 ng/mL), the diagnostic accuracy of each biomarker separately and their combination was moderate/good in all groups, except for their combination in BCLC-C (AUROC = 90.5%).

CONCLUSIONS

Each biomarker separately showed acceptable accuracy for detecting HCC in cirrhotic patients and excellent for those in BCLC-C stage. The combination of the biomarkers presented excellent results in BCLC-B/C patients. The diagnostic accuracy of PIVKA-II and the combination of the two biomarkers in patients expressing low/non-diagnostic AFP levels was good in BCLC-B and excellent in BCLC-C patients.

Early C-reactive Protein Kinetics Predict Response to Immune Checkpoint Blockade in Unresectable Hepatocellular Carcinoma

Purpose

In recent years, a new therapeutic approach, known as immune checkpoint blockade (ICB), has been proposed as approach to improve outcomes in patients with intermediate stage (Barcelona Clinic Liver Cancer, BCLC B) or advanced stage (BCLC C) hepatocellular carcinoma (HCC). Unfortunately, only a select patients can benefit from ICB. Hence, biomarkers that can predict the success and survival of treatment are still necessary.

Patients and Methods

Between 2018 to 2021, 132 patients received ICB treatment for intermediate or advanced stage HCC. Based on the early kinetics of C-reactive protein (CRP), the patients were classified into three groups. The study endpoints were progression-free survival (PFS) and overall survival (OS).

Results

Our findings support the predictive power of early CRP kinetics in determining immunotherapy response for intermediate or advanced HCC. Objective response rates (ORR) were found in 41.2% of CRP flare-responders, 13.3% of CRP responders, and 3.5% of CRP non-responders (p<0.001). Disease control rates (DCR) in the three groups were substantially different (p<0.001). The improved PFS and OS were strongly correlated with the early kinetics of CRP. Compared to CRP non-responders, CRP responders, especially CRP flare-responders, had significantly longer PFS (median PFS: CRP flare-responders: 11.6 months vs CRP responders: 5.2 months vs CRP non-responders: 2.3 months, p<0.001).

Conclusion

The CRP flare response robustly predicts the immunotherapy response and outcomes in patients with HCC. Early CRP kinetics may be an inexpensive, easily implemented and non-invasive biomarker to anticipate response to ICB therapy in intermediate or advanced HCC, with the potential to optimize treatment monitoring.

Effect of PIVKA-II and AFP secretion status on early recurrence of hepatocellular carcinoma after open and laparoscopic surgery

BACKGROUND

Prothrombin induced by vitamin K absence-II (PIVKA-II) and Alpha-fetoprotein (AFP) have been widely used as diagnostic markers in hepatocellular carcinoma (HCC), but the prognostic values of the two serum markers and their clinical usefulness in patient selection for different surgical approaches remain largely unclear.

METHODS

HCC patients received surgical treatment between 2015 and 2019 were included. Patients were divided into four statuses according to the serum PIVKA-II and AFP secretion status: PIVKA-II (-) AFP (-) (status 1); PIVKA-II (+) AFP (-) (status 2); PIVKA-II (-) AFP (+) (status 3); PIVKA-II (+) AFP (+) (status 4). Kaplan-Meier analyses were conducted to compare the survivals of the four groups and the HCC patients received different surgical interventions; time-dependent AUC curves were introduced to evaluate the prognostic value of the PIV-AFP status; Cox regression model was used to identify prognostic indexes for overall survival (OS) and recurrence-free survival (RFS).

RESULTS

A total of 518 patients were included. Patients with PIVKA-II (+) and APF (+) presented significantly decreased OS and RFS comparing to the other statuses. The areas under ROC curves of PIV-AFP status in predicting OS and RFS were superior to the PIVKA-II or the AFP alone. The HCC patients in early stages with PIVKA-II (+) and APF (+) had worse RFS when received laparoscopic hepatectomy than those who received open hepatectomy, whereas there was no difference in other secretion statuses. The PIVKA-II (+) and AFP (+) secretion status was an independent risk factor for OS, RFS.

CONCLUSIONS

The PIV-AFP secretion status is of favorable clinical utility in predicting the OS and RFS of the HCC patients; extra caution is needed when applicated the laparoscopic approach in the HCC patients with PIVKA-II (+) and AFP (+).

Curative surgery for multiple hepatocellular carcinomas after lenvatinib plus transarterial chemoembolization: a case report

Surgical therapy following lenvatinib (LEN) plus transarterial chemoembolization (TACE) is a useful therapeutic option for intermediate-stage hepatocellular carcinoma (HCC). A 66-year-old man with a history of hepatitis C was detected four masses in the caudate lobe and segment 6/7 of the liver, with a maximum lesion diameter of 14 cm by computed tomography. The patient was diagnosed with intermediate-stage HCC and received LEN plus TACE. After resuming LEN for 8 weeks, computed tomography showed weakened stained areas of the tumors, and no new lesions. Thus, the patient was evaluated as having a partial response in the modified Response Evaluation Criteria in Solid Tumors. The patient underwent hepatic caudate lobectomy, partial hepatectomy of S6/7, and S6 microwave coagulation therapy for radical resection. The patient is currently alive and recurrence-free at 12 months postoperatively. In patients with multiple HCC lesions, hepatic resection combined with local therapy might be an effective treatment option.

Protein Induced by Vitamin K Absence or Antagonist-II Versus Alpha-Fetoprotein in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review With Meta-Analysis

Background

Protein induced by vitamin K absence or antagonist-II (PIVKA-II) and α-fetoprotein (AFP) are promising tumor markers for the diagnosis of hepatocellular carcinoma (HCC). Yet, their diagnostic performance differs throughout HCC investigations. The aim of this meta-analysis was to assess the effectiveness of PIVKA-II and AFP in the diagnosis of HCC.

Methods

A systematic literature search was performed to identify relevant studies from eight databases, which were published up to February 2023, in order to compare the diagnostic performance of PIVKA-II and AFP for HCC. Pooled sensitivity and specificity were calculated. Summary receiver operating characteristic (SROC) curve was performed to assess the diagnostic accuracy of each biomarker.

Results

Fifty-three studies were identified. The pooled sensitivity (95% confidence interval (CI)) of PIVKA-II and AFP was 0.71 (0.70 - 0.72) and 0.64 (0.63 - 0.65), respectively in diagnosis of HCC, and the corresponding pooled specificity (95% CI) was 0.90 (0.89 - 0.90) and 0.87 (0.87 - 0.88), respectively. The area under the ROC curve (AUC) of PIVKA-II and AFP was 0.89 (0.88 - 0.90) and 0.78 (0.77 - 0.79), respectively. Subgroup analysis demonstrated that PIVKA-II presented higher AUC values compared to AFP in terms of ethnic group (African, European, Asian, and American patients), etiology (mixed-type HCC, hepatitis C virus (HCV)-related, and hepatitis B virus (HBV)-related) and sample size of cases (≤ 100 and > 100).

Conclusion

This study reveals that PIVKA-II is a promising biomarker for identifying and tracking HCC, exhibiting greater accuracy than AFP. Our findings indicate that PIVKA-II outperforms AFP in detecting HCC across diverse racial groups and sample sizes, as well as in cases of HBV-related, HCV-related, or mixed-etiology HCC.

Identification of the Best Cut-Off Value of PIVKA-II for the Surveillance of Patients at Risk of Hepatocellular Carcinoma Development

Patients with cirrhosis are at risk of hepatocellular carcinoma (HCC) development and, according to current guidelines, should undergo surveillance by ultrasound at six month intervals. Due to the known limitations of surveillance strategies based on ultrasonography, the use of tumor biomarkers, although debated, is common practice in many centers. The aim of the study was to identify the best cut-off value for one of such biomarkers, protein induced by vitamin K absence, or antagonist-II (PIVKA-II). We retrospectively enrolled 1187 patients with liver cirrhosis: 205 with a diagnosis of HCC (median age 67 years, 81.0% males) and 982 without tumor (median age 64 years, 56.2% males). During a median follow-up (FU) of 34.6 (11.4−43.7) months, 118 out of 982 (12.0%) patients developed HCC. Serum PIVKA-II was assessed by chemiluminescence immunoassay on the Lumipulse® G600 II platform (Fujirebio, Tokyo, Japan). In the overall cohort (n = 1187), PIVKA-II showed an area under the curve (AUC) of 0.802 for HCC detection. The best cut-off value that maximized sensitivity was 50 mAU/mL (sensitivity = 80%, specificity = 64%). In the 982 patients without HCC at baseline, PIVKA-II > 50 mAU/mL was associated with an increased risk of HCC development during the FU (HR = 1.74, 95% CI 1.21−2.51; p = 0.003)). In conclusion, the evaluation of serum PIVKA-II showed a good performance for HCC detection; a cut-off value > 50 mAU/mL could be suitable for the surveillance of patients who are at risk of developing HCC.